Public health monitoring of hypertension, diabetes and elevated cholesterol: comparison of different data sources

Public health monitoring of hypertension, diabetes and elevated cholesterol: comparison of... Abstract Background Three data sources are generally used in monitoring health on the population level. Health interview surveys (HISs) are based on participants’ self-report. Health examination surveys (HESs) yield more objective data, and also persons who are unaware of their elevated risks can be detected. Medical records (MRs) and other administrative registers also provide objective data, but their availability, coverage and quality vary between countries. We summarized studies comparing self-reported data with (i) measured data from HESs or (ii) MRs. We aimed to describe differences in feasibility and comparability of different data sources for monitoring (i) elevated blood pressure or hypertension (ii) elevated blood glucose or diabetes and (iii) elevated total cholesterol. Methods We conducted a literature search to identify studies, which validated self-reported measures against objective measures. We found 30 studies published since the year 2000 fulfilling our inclusion criteria (targeted to adults and comparing prevalence among the same persons). Results Hypertension and elevated total cholesterol were prone to be under-estimated in HISs. The under-estimate was more pronounced, when the HIS data were compared with HES data, and lower when compared with MRs. For diabetes, the HISs and the objective methods resulted in fairly similar prevalence rates. Conclusion The three data sources measure different manifestations of the risk factors and cannot be expected to yield similar prevalence rates. Using HIS data only may lead to under-estimation of elevated risk factor levels or disease prevalence. Whenever possible, information from the three data sources should be evaluated and combined. Introduction In 2015, high blood pressure, high fasting blood glucose and high total cholesterol were among the 10 most common risk factors explaining disability-adjusted life years according to the Global Burden of Disease Study 2015.1 Their relevance as risk factors had increased since 2005. One of the six objectives in the WHO global action plan for the prevention and control of noncommunicable diseases 2013–20 is to monitor the trends and determinants of noncommunicable diseases and to evaluate progress in their prevention and control.2 The action plan calls for undertaking periodic data collection on cardiovascular and metabolic risk factors. Three indicators (i) prevalence of elevated blood pressure (defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg) and mean systolic blood pressure, (ii) prevalence of elevated blood glucose or diabetes (defined as fasting plasma glucose concentration ≥7.0 mmol/l or on medication for elevated blood glucose) and (iii) prevalence of elevated total cholesterol (defined as total cholesterol ≥5.0 mmol/l) and mean total cholesterol concentration are among the 25 indicators that are recommended to be monitored to follow up the achievements in the voluntary global targets. Diabetes and blood pressure are also among the European Community Health Indicators (ECHI). In 2007, it was evaluated that data for these indicators were widely available in European countries, mostly from National Health Interview Surveys (HIS). In some cases, they were available from registers and health examination surveys (HESs).3,4 Based on information gathered during the European Community Health Indicators and Monitoring project (ECHIM), it was concluded that registers and statistical information systems are important sources of health data, but both national HISs and HESs are additionally needed to provide comprehensive information on morbidity, functioning and health determinants in the whole population. Several countries have conducted repeated national HESs in order to monitor key health indicators of the population. Collecting data with HESs including questionnaires, physical measurements and often also collection of biological samples, yields objective and up-to-date data, and also persons who are unaware of their elevated risk factor levels can be detected. However, HESs are costly and time-consuming and require proper standardization. For blood pressure measurement, as an example, thorough training of the survey personnel is essential.5,6 Furthermore, recruiting of participants is often challenging in HESs.7 Because of lower costs HISs are used more frequently than HESs. Self-administered questionnaires, face-to-face interviews and telephone interviews can be used. The disadvantages of self-report (SR) in HISs include that it rests on the subjects’ memory, awareness and ability to report on a health condition.5,8 The two objective data sources, HES data and medical records (MRs), describe different dimensions of the outcome. HES data mostly rely on measurements conducted on one occasion and clinical diagnoses cannot be made based on such data. However, people with elevated risk but without diagnosis can be identified from HES data. The availability and coverage of MRs vary between countries according to the national health care system.9 The data depend on access and use of health services. Undiagnosed persons that have not sought medical care but might fulfil diagnostic criteria cannot be identified. For example, routine registers reveal diabetes or cardiovascular disease only in those who have used services and have been diagnosed.10,11 Furthermore, many administrative registers only cover information from hospital care. There may be inconsistences in coding of the conditions by the health care personnel as well as in measurements, laboratory analysis and clinical practice.12 There are numerous studies that have examined the validity of self-reported data against more objective measures.8,13 To gather up-to date information on different data sources and to discuss their strengths and limitations as well as to evaluate their usability for public health monitoring purposes, we summarized studies that compared self-reported data with two more objective data types: (i) measured data from HESs or (ii) MRs or other administrative register-based data. Three key risk factors or disease diagnoses were chosen to this evaluation: (i) elevated blood pressure or hypertension, (ii) elevated blood glucose or diabetes and (iii) elevated total cholesterol. We aimed to describe differences in feasibility and comparability of different data sources for monitoring major cardiovascular risk factors. Methods Literature search The literature search was conducted in PubMed in October 2016 and again in the beginning of January 2017 to identify studies on elevated blood pressure or hypertension, elevated blood glucose or diabetes and elevated total cholesterol which validated self-reported measures against measures based on (i) HES data or (ii) MRs or other administrative register-based data. Henceforth, the latter is referred to as MRs. The search terms are listed in Supplementary file 1. Studies published since the year 2000 were included. Older studies were excluded based on three reasons. Firstly, we were mainly interested in clarifying the current situation in relation to health monitoring. Secondly, the methods to identify and treat the selected risk factors have developed, the treatment alternatives have increased, and the indications for treatment have changed. Furthermore, the awareness of one’s own risk factor status may have improved among the population. Thirdly, we wanted to focus on studies that were not included in earlier reviews.8,13,14 The following inclusion criteria were applied: at least one of the following conditions was included as an outcome: elevated blood pressure/hypertension, elevated blood glucose/diabetes or elevated total cholesterol (i.e. either a diagnosis or a measure that indicated an elevated risk of the outcome); self-reported data were compared with data from (i) HES and/or (ii) MRs or other administrative registers; prevalence of the outcome was reported; risk factor status was assessed among the same study subjects with the two methods; the study was performed among adults (18+); and the study was published in English. To compare population level estimates, we excluded studies in which persons with known hypertension, diabetes or elevated cholesterol were excluded. We also excluded studies where finger prick samples were used to analyze blood glucose or total cholesterol. Furthermore, studies using other lipid markers than total cholesterol such as low-density lipoprotein or triglycerides were not included. Altogether 17 studies that compared self-reported data with HES data and 13 studies that compared self-reported data with MRs were found (table 1). These studies were presented in 28 publications, as two publications included two studies: (i) in the publication by El Fakiri et al.15 SR was compared separately with both HES and MRs and is thus included in both categories and (ii) the two age groups in Navin Cristina et al.16 are treated as two separate studies because their results were presented separately in the publication. The publications comprised 8 studies from Europe,9,15,17–21 12 from the North America,22–33 1 from the South America,34 4 from Asia35–38 and 5 from Australia/New Zealand16,39–41 (references 41–49 in the Supplementary file 2). The study population covered general population in 23 studies and clinical population in 7 studies. Table 1 Description of studies and study populations First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Note: NR, not reported; RCT, randomized clinical trial; CVD, cardiovascular disease. a Low-income women. b Persons of color, low-income, rural residency and persons for whom English was a second language. c Mexican American people. d American Indian and Alaska Native people. Table 1 Description of studies and study populations First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Note: NR, not reported; RCT, randomized clinical trial; CVD, cardiovascular disease. a Low-income women. b Persons of color, low-income, rural residency and persons for whom English was a second language. c Mexican American people. d American Indian and Alaska Native people. Statistical methods Various statistical methods such as prevalence rates, κ coefficient, sensitivity and specificity and positive and negative predictive values were applied in describing the agreement between two compared methods. In this evaluation, we focus on prevalence rates. κ coefficients are also presented if available. Also 95% confidence intervals for prevalence rates and κ coefficients are reported whenever available. None of the original publications presented standard errors or standard deviations for prevalence rates. Results Comparability of data collection methods SR measures The self-reported data were collected by interviews or self-administered questionnaires. The format of questions varied between the studies (Supplementary file 1). Most studies reported the actual question whereas in some studies the questions were described less accurately. Typically, the self-reported data relied on questions like: Have you ever been told (by a doctor or other health professional) that you have high blood pressure/diabetes/high cholesterol? (tables 2–4, Supplementary file 1). In most studies, either current conditions or conditions that had ‘ever’ been observed were asked. In some studies, only diagnosed conditions or conditions that a health professional had ‘told’ about were enquired while in other studies diagnosis or health professionals were not specified. Table 2 The format of question used in SR, the definition of hypertension/elevated blood pressure used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) Note: NR, not reported. a The question format was as follows: ‘Do you suffer from high blood pressure and/or has a physician/doctor/nurse diagnosed you as a hypertensive?’ b Persons who were taking blood pressure lowering medications were excluded. c Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 2 The format of question used in SR, the definition of hypertension/elevated blood pressure used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) Note: NR, not reported. a The question format was as follows: ‘Do you suffer from high blood pressure and/or has a physician/doctor/nurse diagnosed you as a hypertensive?’ b Persons who were taking blood pressure lowering medications were excluded. c Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 3 The format of question used in SR, the definition of diabetes/elevated blood glucose used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and kappa coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) Note: NR, not reported. a Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 3 The format of question used in SR, the definition of diabetes/elevated blood glucose used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and kappa coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) Note: NR, not reported. a Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 4 The format of question used in SR, the definition of elevated total cholesterol used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) Note: NR, not reported. Table 4 The format of question used in SR, the definition of elevated total cholesterol used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) Note: NR, not reported. Objective data HES measures In HES’s, blood pressure was measured twice or three times. In some studies, the average of two or three measurements was used in the analyses, whereas in others the result of only one measurement was used (Supplementary file 1). Diabetes or elevated blood glucose and elevated total cholesterol status were analyzed from blood samples. For elevated blood glucose, fasting plasma glucose (FPG) or HbA1c from non-fasting samples were used (table 3, Supplementary file 1). In one study, also glucose tolerance test was used.38 Total cholesterol was analyzed from fasting samples in four studies,15,36,39,40 both fasting and non-fasting samples in two studies9,22 and non-fasting samples in one study23 (Supplementary file 1). The definitions and cut-off values for the selected risk factors or diseases varied between the studies (see tables 2–4). In most studies, the use of medication for the condition was taken into account in the definition (measured value exceeded the cut-off value and/or medication was used for the condition). We focus on these studies. Studies based on measurements only are listed in the tables but not used in comparison. For studies that compared self-reported data with HES data the terms ‘hypertension’ and ‘diabetes’ are used when the definition in HES data was based on both measurements (blood pressure or fasting blood glucose/HbA1C) and medication for the condition (tables 2 and 3). We are aware that all respondents in these groups may not fulfil the clinical diagnostic criteria. When the definition was based on measurements only, the terms ‘elevated blood pressure’ and ‘elevated blood glucose’ are used. For cholesterol, the term ‘elevated total cholesterol’ is used in both cases (table 4). Data from MRs The data on MRs or other administrative registers typically relied on diagnostic codes and also the use of medication was taken into account in several studies (tables 2–4). For studies that compared self-reported data with MRs the terms ‘hypertension’, ‘diabetes’ and ‘elevated total cholesterol’ are used. Comparability of prevalence rates obtained from different data sources Self-reported data under-estimated the prevalence of hypertension and elevated total cholesterol in the majority of studies compared with HES data (tables 2 and 4). The difference between SR and MRs was less pronounced. For diabetes, under-estimate was negligible (table 3). Hypertension Self-reported data under-estimated hypertension prevalence in eight out of nine studies where the data for men and women were combined, and the reference data came from HESs (table 2). In a study that showed the prevalence rates for men and women separately, the self-reported hypertension prevalence rate was 10.1 percentage points lower among men and 3.5 percentage points higher among women compared with HES data.9 Among four studies where CI’s were presented, statistically significant under-estimation was observed in three studies. The difference between the prevalence rates by self-reported data and HES ranged from −15.9 to +3.9 percentage points including figures both for men and women combined and separately. The differences between self-reported data and MR data were less consistent (table 2). Hypertension was under-estimated by self-reported data in six out of eight studies that only showed the results for men and women combined. Under-estimation of hypertension was also seen in a study including men only.21 On the contrary, substantial and significant over-estimation of hypertension by SRs was observed in the two age groups in a study for older women.16 The difference between the hypertension prevalence rates by self-reporting and MRs ranged from −14.5 to +19.7 percentage points. The κ coefficients assessing the agreement between two methods ranged from 0.41 to 0.72 for self-reported data vs. HES and from 0.21 to 0.75 for self-reported data vs. MRs (table 2). Diabetes The self-reported data provided fairly similar prevalence rates as did HES and MRs (table 3). The difference in prevalence rates between self-reporting and HES ranged from −2.9 to +0.9 percentage points. When self-reported data were compared with MRs, the difference between the methods ranged from −3.0 to +0.9 percentage points. The κ coefficients ranged from 0.76 to 0.86 for self-reported data vs. HES and from 0.68 to 0.92 for self-reported data vs. MRs (table 3). Elevated total cholesterol Under-reporting of elevated cholesterol was observed in four out of five studies combining data for men and women and comparing self-reporting with HES data (table 4). Substantial under-estimation was observed both among men and women (−49.6 and −43.6 percentage points, respectively) in a study where the data for men and women were analyzed separately.9 The difference between the prevalence rates by self-reporting and HES ranged from −49.6 to +11.7 percentage points. Under-reporting was observed in two out of three studies, when data from self-reporting were compared with data from MRs. The difference between the prevalence rates by self-reporting and MRs ranged from −4.4 to +11 percentage points. The κ coefficients ranged from 0.30 to 0.55 for self-reported data vs. HES. The two κ coefficients reported in the selected publications for self-reported data vs. MRs were 0.48 and 0.57 (table 4). Discussion We compared self-reported data on hypertension, diabetes and elevated total cholesterol with two more objective data sources, HES and MRs or other register based data, to increase knowledge on which methods are most feasible, and produce reliable, accurate and comparable information for health monitoring purposes. Studies published in 2000–16 that compared self-reported data with either HES data or MRs were evaluated. Self-reported data tended to under-estimate prevalence rates especially for hypertension and elevated total cholesterol, which is in line with earlier reviews.8,13 The under-estimate was more pronounced, when the self-reported data were compared with HES data instead of MRs. Hypertension and elevated total cholesterol are typically asymptomatic for a long time and remain therefore easily unmeasured and undetected. Therefore, they may be under-estimated in MR data. In a study from the Netherlands, both HES and MRs were included as reference material.15 Higher hypertension prevalence was reported with HES than with MRs (59% and 44%, respectively), which also suggests that MRs do not cover all hypertensive subjects. Diabetes was more accurately self-reported both compared with HES data and MRs, which is also in line with earlier reviews.13 As the screening of blood glucose and the use risk tests for diabetes have become more common the awareness of the condition has improved. The κ coefficients were consistent with the comparisons based on prevalence rates in that the overall agreement between SR and HES or MRs was higher for diabetes than for hypertension or elevated cholesterol. In an earlier review, the following factors, among others, were reported to explain the inaccuracy of SR: respondents may lack the knowledge to accurately answer the questions posed, and poorly designed survey instruments could result in respondents not fully comprehending the questions.13 Participants’ awareness of the disease or risk factor levels is crucial to obtain accurate reporting in HIS studies.9 Unless a diagnosis is set or risk factors examined and thoroughly explained to the patient by medical professionals, the participants are not aware of them, as many conditions are asymptomatic. In general, women have been more often aware of their hypertension than men,42–44 which can be partly explained by regular follow-up during pregnancies. This applied also to the evaluated studies reporting hypertension separately for men and women.9,36,39 If SR is based on having ever been told to have elevated blood pressure or elevated blood glucose, pregnancy complications may lead to higher prevalence rates for women. This might explain a part of the slight overestimation of hypertension among women.9 In contrast, the substantial overestimation of hypertension among older women cannot be explained with conditions related to pregnancies as the question concerned the past 3 years only.16 Instead, the authors’ presumed hypertension to be underestimated in the hospital data. The awareness of one’s own conditions or risk factor levels may have increased over time in many populations. Measuring blood pressure with digital devices at home has become more common and cholesterol and blood glucose measurements may be available more widely than earlier and also outside medical services, e.g. at pharmacies and health clubs. Hypertension awareness has increased significantly among hypertensives43,44 and this development can be presumed to have continued. The comparability of studies included in this evaluation was hindered by many discrepancies in their methods. Self-reported data on risk factors or diseases were collected heterogeneously as varying questions and definitions were used in different studies and the time frame covered with the question varied. Both population level coverage of the service and coverage in recording diagnoses and measures limit comparability of data from MRs or other administrative registers. For HES data, the use of medication was not taken into account in the definition of the conditions in all studies. We decided to focus on studies where the definition was based on both measured values and the use of medication, although the issue of medication is not straightforward. Antihypertensive drugs and statins are also used for other indications than elevated blood pressure or cholesterol. Considering medication based on recorded product names may hence have led to overestimation of hypertension or elevated cholesterol if the indication was not specified. Furthermore, different cut-off values were used, especially for elevated total cholesterol. The cut-offs used for elevated total cholesterol ranged from 5.0 to 6.5 mmol/l. The lowest cut-off was applied in a study in which also the largest underestimate of elevated total cholesterol by SR was seen.9 In addition, results for two cut-offs were shown in one study.23 Using the lower cut-off (5.17 mmol/l) resulted in a conclusion that SR underestimated, whereas using the higher cut-off (6.2 mmol/l) resulted in a conclusion that SR overestimated elevated total cholesterol. This might be related to practicing clinicians using different thresholds for communicating elevated cholesterol levels.22 Medication was included in the definition only in the case of the higher cut-off, which is why we only included the results by the higher cut-off from the study in question in this evaluation. Masked or white coat hypertension may also affect the prevalence rates for elevated blood pressure, as in HESs blood pressure is measured on one occasion only and most commonly in an office at the examination site.45,46 Methodological differences, such as the format of questions, response rates and survey modes, among national surveys have hampered valid mutual comparisons,4,47,48 but recent efforts for standardization in European countries will improve the situation.6 However, rising non-participation rates cause problems and attention needs to be given to recruitment methods.7 While electronic patient records have improved the availability of data and provide information not available from survey data such as comorbidity and diagnostic and treatment details, they cannot fully substitute survey data. MRs may not always be up-to-date and there may be socio-economic differences in access to medical care.49 In clinical practice, screening for cardiovascular risk factors and control of diagnosed diseases may not be systematic. The measures rely on health professionals’ practice patterns and accuracy of recording.12 MRs may also lack information on diagnoses performed in different health care sectors (public vs. private sector), and background and health behaviours. There may also be limitations in availability of or access to MRs for research purposes. Conclusions All the data sources have their strengths and limitations, and none of them alone should be regarded as a gold standard. However, using only self-reported data in monitoring vascular diseases and their risk at the population level may lead to underestimation of the true prevalence especially in regards to hypertension and elevated total cholesterol. Whenever feasible, combined information from standardized interviews and measurements supplemented with register data to exploit the advantages of all of them might be used for public health monitoring. Supplementary data Supplementary data are available at EURPUB online. Funding This work was supported by the European Commission/DG SANTÉ (BRIDGE Health Project, grant number 664691). The views expressed here are those of the authors and they do not represent the Commission’s official position. Conflicts of interest: None declared Key points The prevalence rates of hypertension and elevated total cholesterol were under-estimated with self-reported data compared with data from HESs and to a smaller extent compared with medical records. Instead, all the three data sources resulted in quite similar diabetes prevalence rates. The methods and the wordings used in questions varied between the studies which hindered the comparison. 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Comparing self-reported and measured high blood pressure and high cholesterol status using data from a large representative cohort study . Aust N Z J Public Health 2010 ; 34 : 394 – 400 . Google Scholar CrossRef Search ADS PubMed 40 Peterson KL , Jacobs JP , Allender S , et al. Characterising the extent of misreporting of high blood pressure, high cholesterol, and diabetes using the Australian Health Survey . BMC Public Health 2016 ; 16 : 695 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The European Journal of Public Health Oxford University Press

Public health monitoring of hypertension, diabetes and elevated cholesterol: comparison of different data sources

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
ISSN
1101-1262
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1464-360X
D.O.I.
10.1093/eurpub/cky020
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Abstract

Abstract Background Three data sources are generally used in monitoring health on the population level. Health interview surveys (HISs) are based on participants’ self-report. Health examination surveys (HESs) yield more objective data, and also persons who are unaware of their elevated risks can be detected. Medical records (MRs) and other administrative registers also provide objective data, but their availability, coverage and quality vary between countries. We summarized studies comparing self-reported data with (i) measured data from HESs or (ii) MRs. We aimed to describe differences in feasibility and comparability of different data sources for monitoring (i) elevated blood pressure or hypertension (ii) elevated blood glucose or diabetes and (iii) elevated total cholesterol. Methods We conducted a literature search to identify studies, which validated self-reported measures against objective measures. We found 30 studies published since the year 2000 fulfilling our inclusion criteria (targeted to adults and comparing prevalence among the same persons). Results Hypertension and elevated total cholesterol were prone to be under-estimated in HISs. The under-estimate was more pronounced, when the HIS data were compared with HES data, and lower when compared with MRs. For diabetes, the HISs and the objective methods resulted in fairly similar prevalence rates. Conclusion The three data sources measure different manifestations of the risk factors and cannot be expected to yield similar prevalence rates. Using HIS data only may lead to under-estimation of elevated risk factor levels or disease prevalence. Whenever possible, information from the three data sources should be evaluated and combined. Introduction In 2015, high blood pressure, high fasting blood glucose and high total cholesterol were among the 10 most common risk factors explaining disability-adjusted life years according to the Global Burden of Disease Study 2015.1 Their relevance as risk factors had increased since 2005. One of the six objectives in the WHO global action plan for the prevention and control of noncommunicable diseases 2013–20 is to monitor the trends and determinants of noncommunicable diseases and to evaluate progress in their prevention and control.2 The action plan calls for undertaking periodic data collection on cardiovascular and metabolic risk factors. Three indicators (i) prevalence of elevated blood pressure (defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg) and mean systolic blood pressure, (ii) prevalence of elevated blood glucose or diabetes (defined as fasting plasma glucose concentration ≥7.0 mmol/l or on medication for elevated blood glucose) and (iii) prevalence of elevated total cholesterol (defined as total cholesterol ≥5.0 mmol/l) and mean total cholesterol concentration are among the 25 indicators that are recommended to be monitored to follow up the achievements in the voluntary global targets. Diabetes and blood pressure are also among the European Community Health Indicators (ECHI). In 2007, it was evaluated that data for these indicators were widely available in European countries, mostly from National Health Interview Surveys (HIS). In some cases, they were available from registers and health examination surveys (HESs).3,4 Based on information gathered during the European Community Health Indicators and Monitoring project (ECHIM), it was concluded that registers and statistical information systems are important sources of health data, but both national HISs and HESs are additionally needed to provide comprehensive information on morbidity, functioning and health determinants in the whole population. Several countries have conducted repeated national HESs in order to monitor key health indicators of the population. Collecting data with HESs including questionnaires, physical measurements and often also collection of biological samples, yields objective and up-to-date data, and also persons who are unaware of their elevated risk factor levels can be detected. However, HESs are costly and time-consuming and require proper standardization. For blood pressure measurement, as an example, thorough training of the survey personnel is essential.5,6 Furthermore, recruiting of participants is often challenging in HESs.7 Because of lower costs HISs are used more frequently than HESs. Self-administered questionnaires, face-to-face interviews and telephone interviews can be used. The disadvantages of self-report (SR) in HISs include that it rests on the subjects’ memory, awareness and ability to report on a health condition.5,8 The two objective data sources, HES data and medical records (MRs), describe different dimensions of the outcome. HES data mostly rely on measurements conducted on one occasion and clinical diagnoses cannot be made based on such data. However, people with elevated risk but without diagnosis can be identified from HES data. The availability and coverage of MRs vary between countries according to the national health care system.9 The data depend on access and use of health services. Undiagnosed persons that have not sought medical care but might fulfil diagnostic criteria cannot be identified. For example, routine registers reveal diabetes or cardiovascular disease only in those who have used services and have been diagnosed.10,11 Furthermore, many administrative registers only cover information from hospital care. There may be inconsistences in coding of the conditions by the health care personnel as well as in measurements, laboratory analysis and clinical practice.12 There are numerous studies that have examined the validity of self-reported data against more objective measures.8,13 To gather up-to date information on different data sources and to discuss their strengths and limitations as well as to evaluate their usability for public health monitoring purposes, we summarized studies that compared self-reported data with two more objective data types: (i) measured data from HESs or (ii) MRs or other administrative register-based data. Three key risk factors or disease diagnoses were chosen to this evaluation: (i) elevated blood pressure or hypertension, (ii) elevated blood glucose or diabetes and (iii) elevated total cholesterol. We aimed to describe differences in feasibility and comparability of different data sources for monitoring major cardiovascular risk factors. Methods Literature search The literature search was conducted in PubMed in October 2016 and again in the beginning of January 2017 to identify studies on elevated blood pressure or hypertension, elevated blood glucose or diabetes and elevated total cholesterol which validated self-reported measures against measures based on (i) HES data or (ii) MRs or other administrative register-based data. Henceforth, the latter is referred to as MRs. The search terms are listed in Supplementary file 1. Studies published since the year 2000 were included. Older studies were excluded based on three reasons. Firstly, we were mainly interested in clarifying the current situation in relation to health monitoring. Secondly, the methods to identify and treat the selected risk factors have developed, the treatment alternatives have increased, and the indications for treatment have changed. Furthermore, the awareness of one’s own risk factor status may have improved among the population. Thirdly, we wanted to focus on studies that were not included in earlier reviews.8,13,14 The following inclusion criteria were applied: at least one of the following conditions was included as an outcome: elevated blood pressure/hypertension, elevated blood glucose/diabetes or elevated total cholesterol (i.e. either a diagnosis or a measure that indicated an elevated risk of the outcome); self-reported data were compared with data from (i) HES and/or (ii) MRs or other administrative registers; prevalence of the outcome was reported; risk factor status was assessed among the same study subjects with the two methods; the study was performed among adults (18+); and the study was published in English. To compare population level estimates, we excluded studies in which persons with known hypertension, diabetes or elevated cholesterol were excluded. We also excluded studies where finger prick samples were used to analyze blood glucose or total cholesterol. Furthermore, studies using other lipid markers than total cholesterol such as low-density lipoprotein or triglycerides were not included. Altogether 17 studies that compared self-reported data with HES data and 13 studies that compared self-reported data with MRs were found (table 1). These studies were presented in 28 publications, as two publications included two studies: (i) in the publication by El Fakiri et al.15 SR was compared separately with both HES and MRs and is thus included in both categories and (ii) the two age groups in Navin Cristina et al.16 are treated as two separate studies because their results were presented separately in the publication. The publications comprised 8 studies from Europe,9,15,17–21 12 from the North America,22–33 1 from the South America,34 4 from Asia35–38 and 5 from Australia/New Zealand16,39–41 (references 41–49 in the Supplementary file 2). The study population covered general population in 23 studies and clinical population in 7 studies. Table 1 Description of studies and study populations First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Note: NR, not reported; RCT, randomized clinical trial; CVD, cardiovascular disease. a Low-income women. b Persons of color, low-income, rural residency and persons for whom English was a second language. c Mexican American people. d American Indian and Alaska Native people. Table 1 Description of studies and study populations First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – First author and year n (men/women) Age (years) Country Population Study Hypertension/elevated blood pressure Diabetes/elevated blood glucose Elevated total cholesterol SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 200717 4950 (2221/2729) 18+ The Netherlands General Utrecht Health Project x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Huerta et al. 200918 1556 (719/837) 20+ Spain General Diabetes, Nutrition and Obesity study (DINO) x x – Tolonen et al. 20149 4127 (1816/2311) 25–64 12 European countries General EHES Pilot Project x x x North America Natarajan et al. 200222 8236 (3558/4678) 21+ USA General NHANES III (1988–94) – – x Ahluwalia et al. 200923 733 (0/733) 40–64 USA Generala WISEWOMAN x – x Dey et al. 201526 101 (49/52) 18–80 Canada Patients with recent history of high-risk TIA and/or minor stroke Cohort study at a Stroke Prevention Clinic and inpatient ward – x – Asia Goldman et al. 200335 1004 (585/419) 54+ Taiwan General Social Environment and Biomarkers of Aging Study x x – Chun et al. 201636 7270 (3096/4174) 50+ South Korea General KNHANES IV x x x South America Lima-Costa et al. 200434 970 (422/548) 18+ Brazil General Bambuí study x – – Australia/New Zealand Taylor et al. 201039 1525 (749/776) 18+ Australia General North West Adelaide Health Study (NWAHS) x – x (b) Definition based on measurement only North America Cowie et al. 201024 13094 (NR) 20+ USA General NHANES (2003–2006) – x – Dave et al. 201325 16598 (5747/10087) 18+ USA Generalb Community Initiative to Eliminate Stroke x – – Fisher-Hoch et al. 201527 2838 (NR) 18+ USA Generalc Cameron County Hispanic Cohort – x – Asia Bao et al. 201538 7913 (2841/5072) 20–74 China General A population-based cross-sectional study in the city of Harbin – x – Ning et al. 201637 17708 (8479/9229) 45+ China General China Health and Retirement Longitudinal Study x x – Australia/New Zealand Peterson et al. 201640 7269 (3275/3994) 18+ Australia General Australian Health Survey x x x SR vs. MRs Europe Tormo et al. 200019 248 (44/204) 29–69 Spain General Subsample of Spanish EPIC cohort x – – El Fakiri et al. 200715 430 (198/232) 30–70 The Netherlands High risk for CVD RCT on CVD x x x Englert et al. 201020 7640 (4271/3369) 18+ Germany Hypercholesterolemia patients Orbital study x x – Frost et al. 201221 600 (600/0) 60–74 Denmark General Cross-sectional study x x – North America Simpson et al. 200428 1002 (0/1002) 65+ USA Disabled older women Women’s Health and Aging Study I – x – Okura et al. 200429 2037 (981/1056) 45+ USA General Rochester Epidemiology Project x x – St Sauver et al. 200530 26162 (10192/15970) 20+ USA General Patients at Mayo Clinic x – x Muggah et al. 201331 85549 (38743/46806) 20+ Canada General Canadian community health survey x x – Leong et al. 201332 3322 (1555/1767) 20+ Canada General Quebec Statistical Institute (QSI) survey – x – Koller et al. 201433 3821 (NR) 18+ USA Generald Alaska EARTH study x x x Australia/New Zealand Teh et al. 201341 878 (395/483) 80–90 New Zealand General The Life and Living to Advanced Age: a Cohort Study in New Zealand (LiLACS NZ) x – – Navin Cristina et al. 201616 1002 (0/1002) 56–61 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Navin Cristina et al. 201616 1926 (0/1926) 82–87 Australia Recent acute care episode Australian Longitudinal Study on Women's Health (ALSWH) x x – Note: NR, not reported; RCT, randomized clinical trial; CVD, cardiovascular disease. a Low-income women. b Persons of color, low-income, rural residency and persons for whom English was a second language. c Mexican American people. d American Indian and Alaska Native people. Statistical methods Various statistical methods such as prevalence rates, κ coefficient, sensitivity and specificity and positive and negative predictive values were applied in describing the agreement between two compared methods. In this evaluation, we focus on prevalence rates. κ coefficients are also presented if available. Also 95% confidence intervals for prevalence rates and κ coefficients are reported whenever available. None of the original publications presented standard errors or standard deviations for prevalence rates. Results Comparability of data collection methods SR measures The self-reported data were collected by interviews or self-administered questionnaires. The format of questions varied between the studies (Supplementary file 1). Most studies reported the actual question whereas in some studies the questions were described less accurately. Typically, the self-reported data relied on questions like: Have you ever been told (by a doctor or other health professional) that you have high blood pressure/diabetes/high cholesterol? (tables 2–4, Supplementary file 1). In most studies, either current conditions or conditions that had ‘ever’ been observed were asked. In some studies, only diagnosed conditions or conditions that a health professional had ‘told’ about were enquired while in other studies diagnosis or health professionals were not specified. Table 2 The format of question used in SR, the definition of hypertension/elevated blood pressure used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) Note: NR, not reported. a The question format was as follows: ‘Do you suffer from high blood pressure and/or has a physician/doctor/nurse diagnosed you as a hypertensive?’ b Persons who were taking blood pressure lowering medications were excluded. c Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 2 The format of question used in SR, the definition of hypertension/elevated blood pressure used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of hypertension SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe Molenaar et al. 2007 (n = 4950)17 General practitioner or specialist 12 months Systolic blood pressure ≥140 mmHg (<60y), 10.7 (9.8–11.6) 22.9 (21.7–24.1) -12.2 NR systolic blood pressure ≥160 mmHg (≥60y) or diastolic blood pressure≥90 or medication El Fakiri et al. 2007 (n = 430)15 Not defined Current Systolic blood pressure ≥160 mmHg 52 59 -7 0.51 (0.43–0.59) or diastolic blood pressure ≥95 mmHg or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Systolic blood pressure ≥140 mmHg 19.5 (17.6–21.6) 35.4 (33.0–37.8) -15.9 0.51 (0.47–0.56) or diastolic blood pressure ≥90 mmHg or medication Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or medication Men 22.6 32.7 -10.1 NR Women 25.4 21.9 +3.5 NR North America Ahluwalia et al. 2009 (n = 733)23 Doctor, nurse or other health professional Ever Systolic blood pressure ≥140 mmHg 49.6 56 -6.4 0.62 (0.56–0.67) or diastolic blood pressure ≥90 mmHg or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Currently Systolic blood pressure ≥140 mmHg 30.3 (27.5-33.2) 57.3 (54.3-60.4) -27 0.41 (0.36–0.47) or diastolic blood pressure ≥90 mmHg or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Systolic blood pressure ≥140 mmHgor diastolic blood pressure ≥90 mmHgor medication 36.4 48.8 -12.4 0.72 (NR) Ning et al. 2016 (n = 17 708)37 Doctor Ever Systolic blood pressure ≥140 mmHg 24 38.5 -14.5 0.57 (0.55–0.58) or diastolic blood pressure ≥90 mmHg or medication South America Lima-Costa et al. 2004 (n = 970)34 Doctor or other health professional Ever Systolic blood pressure ≥140 mmHg 27.2 (24.4-30.1) 23.3 (20.7-26.1) +3.9 NR or diastolic blood pressure ≥90 mmHg or medication Australia/New Zealand Taylor et al. 2010 (n = 1525)39 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 15.8 30.6 -14.8 0.55 (NR) or diastolic blood pressure ≥90 mmHg or medication (b) Definition based on measurement only North America Dave et al. 2013 (n = 16 598)25 Physician, doctor or nursea Evera Systolic blood pressure ≥140 mmHg 16.15 24.81 -8.66 0.25 (NR) or diastolic blood pressure ≥90 mmHgb Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Currently Systolic blood pressure ≥140 mmHg 17.4 (16.5-18.3) 23.9 (22.9-24.9) -6.5 0.21 (0.18–0.23) or diastolic blood pressure ≥90 mmHg SR vs.MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe Tormo et al. 2000 (n = 248)19 Physician Ever Diagnosis of high blood pressure 27.4 26.6 +0.8 0.65 (0.53–0.76) or medication or attending a hypertension control programme run only for hypertensive people El Fakiri et al. 2007 (n = 430)15 Not defined Current ICPC (International Classification of Primary Care) code K86/K87 52 44 +8 0.63 (0.55–0.70) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 56 62 -6 0.69 (0.66–0.71) Frost et al. 2012 (n = 600)21 Not defined NR Diagnosis of hypertension or medication Men 22.2 36.7 -14.5 NR North America Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of hypertension 35.8 37.7 -1.9 0.75 (0.72–0.78) and medication or the words ‘borderline’ or ‘labile’ used in reference to blood pressure with documentation of two blood pressure measurements (consecutively but may be subsequent visits) systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg within a 12-month period St Sauver et al. 2005 (n = 26 162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with hypertension 23.5 26.8 -3.3 NR Muggah et al. 2013 (n = 85 549)31 Not defined Current One hospital admission with a hypertension diagnosis code or one OHIP record with a hypertension diagnosis code, followed within 2 years by another OHIP record or a hospital admission with a hypertension diagnosis code. 20.8 27.6 -6.8 0.66 (0.65–0.66) Codes used: ICD-9: 401x, 402x, 403x, 404x, 405x (any type), ICD-10-CA: I10, I11, I12, I13, I15 (any type), OHIP diagnosis code: 401, 402, 403, 404, 405 (any type) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for hypertension 25.1 25.8 -0.7 0.62 (NR) Australia/New Zealand Teh et al. 2013 (n = 878)41 Doctor Ever Primary health care record: Diagnoses were either ascertained from READ codes, a standardized primary care coding system, from hospital discharge letter, or from reading through the medical records. 54.8 68.4 -13.6 0.44 (0.38–0.50) Administrative hospitalization discharge diagnosis records: Diagnosis codes for hypertension ICD-10: I10, ICD-9: 401.0, 401.1, 401.9 were identified. Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 32.5 (29.7-35.3) 12.8 (10.8-14.8) +19.7 0.35 (0.29–0.41) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) code I10 Womenc 57.8 (55.0-60.7) 38.2 (35.3-41.0) +19.6 0.21 (0.15–0.26) Note: NR, not reported. a The question format was as follows: ‘Do you suffer from high blood pressure and/or has a physician/doctor/nurse diagnosed you as a hypertensive?’ b Persons who were taking blood pressure lowering medications were excluded. c Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 3 The format of question used in SR, the definition of diabetes/elevated blood glucose used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and kappa coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) Note: NR, not reported. a Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 3 The format of question used in SR, the definition of diabetes/elevated blood glucose used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and kappa coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of diabetes or elevated blood glucose SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current Fasting glucose ≥7.0 mmol/l 29 31 −2 0.76 (0.69–0.83) or medication Huerta et al. 2009 (n = 1556)18 Not defined Ever Fasting blood glucose ≥7.0 mmol/l 7.8 (6.5–9.3) 10.6 (9.1–12.3) −2.8 0.78 (0.73–0.84) or treatment (insulin, hypoglycemic drugs or diet) Tolonen et al. 2014 (n = 4127)9 Medical doctor Ever Fasting plasma glucose ≥7.0 mmol/l or HbA1C≥6.5% or medication Men 5.8 6.6 −0.8 NR Women 4.8 3.9 +0.9 NR North America Dey et al. 2015 (n = 101)26 Physician Ever Fasting plasma glucose ≥6.9 mmol/l 23.8 26.7 −2.9 0.76 (0.61–0.91) or HbA1C≥6.5% or medication Asia Goldman et al. 2003 (n = 1004)35 Not defined Current HbA1c≥7.0% 14.6 (12.4–16.7) 15.5 (13.2–17.7) −0.9 0.86 (0.79–0.92) or medication Chun et al. 2016 (n = 7270)36 Doctor Ever Fasting plasma glucose ≥7.0 mmol/l 13.6 15.4 −1.8 0.82 (NR) or treatment (b) Definition based on measurement only North America Cowie et al. 2010 (n = 13 094)24 Doctor or health care provider Ever (other than during pregnancy) HbA1c≥6.5% 7.8 (7.0–8.6) 9.6 (8.7–10.5) −1.8 NR Fisher-Hoch et al. 2015 (n = 2838)27 Health care provider Ever Fasting plasma glucose ≥7.0 mmol/l (or other criteria of the 2010 American Diabetes Association definition) 16.4 27.6 −11.2 NR Asia Bao et al. 2015 (n = 7913)38 Doctor Ever (other than during pregnancy for women) Fasting plasma glucose ≥7.0 mmol/l and/or 2-h post-load plasma glucose ≥11.1 mmol/l 4.4 12.7 −8.3 NR Ning et al. 2016 (n = 17 708)37 Doctor Ever HbA1c≥6.5% 5.8 6.9 −1.1 0.65 (0.62–0.68) Australia/New Zealand Peterson et al. 2016 (n = 7269)40 Doctor or nurse Current Fasting plasma glucose ≥7.0 mmol/l 6.1 (5.6–6.7) 4.5 (4.0–4.9) +1.6 0.58 (0.54–0.62) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n = 430)15 Not defined Current International Classification of Primary Care code T90 29 29 0 0.84 (0.78–0.89) or medication and/or search terms or registration codes specific for the primary health care center Englert et al. 2010 (n = 7640)20 Not defined Ever ‘…coded according to the internationally agreed medical dictionary for regulatory activities (MedDRA 5.0) and converted into a yes/no format….’ 20 23 −3 0.89 (0.86–0.92) Frost et al. 2012 (n = 600)21 Not defined Not defined Diagnosis of type II diabetes or medication Men 6.5 7.2 −0.7 NR North America Simpson et al. 2004 (n = 1002)28 Physician Ever ‘Based on standardized specific criteria using data from medical history, standardized research physical examination (e.g. electrocardiograms, ankle brachial index, spirometric testing), review of all medications, review of hospital records, x-rays, and a physician questionnaire.’ 17 17 0 0.92 (0.86–0.98) Okura et al. 2004 (n = 2037)29 Medical provider Ever Diagnosis of diabetes mellitus 5.2 7.4 −2.2 0.76 (0.70–0.82) Muggah et al. 2013 (n = 85 549)31 Not defined Current Based on Ontario Health Insurance Plan diagnosis codes and DAD admissions. Different criteria for different age groups. 6.8 8.4 −1.6 0.80 (0.80–0.81) Codes used: ICD-9: 250 (any type), ICD-10-CA: E10, E11, E13, E14 (any type), OHIP diagnosis code: 250, OHIP fee code: Q040, K029, K030 Leong et al. 2013 (n = 3322)32 Doctor or another health professional Ever Two or more physical billings for diabetes and/or one or more hospitalizations for diabetes 7.9 8.5 −0.6 0.79 (0.76–0.83) Koller et al. 2014 (n = 3821)33 Doctor or health care provider Ever ICD-9 codes for diabetes 5.1 6.5 −1.4 0.68 (NR) Australia/New Zealand Navin Cristina et al. 2016 (n = 1002)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 8.6 (6.9–10.3) 7.7 (6.1–9.3) +0.9 0.75 (0.68–0.83) Navin Cristina et al. 2016 (n = 1926)16 Not defined Past 3 years ICD-10-AM (Australian Modification) codes E10, E11, E13, E14 Womena 12.8 (10.8–14.7) 12.7 (10.7–14.6) +0.1 0.77 (0.72–0.83) Note: NR, not reported. a Includes survey responses from the last survey (survey 5) only (‘case 1’ in the publication). Table 4 The format of question used in SR, the definition of elevated total cholesterol used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) Note: NR, not reported. Table 4 The format of question used in SR, the definition of elevated total cholesterol used for the HES or MRs data, prevalence rates from SR and HES or MR (%), the difference between the prevalence rates from SR and HES or MR (%) and κ coefficients for agreement SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) SR, the format of question Objective data (HES or MR) Diagnosed/told by Time frame covered Definition of elevated total cholesterol SR (%) (95% CI) HES (%) (95% CI) SR-HES (%) κ (95% CI) SR vs. HES (a) Definition based on measurement and medication Europe El Fakiri et al. 2007 (n =430)15 Not defined Current Total cholesterol ≥6.5 mmol/l 34 36 -2 0.55 (0.42–0.59) or medication Tolonen et al. 2014 (n =4127)9 Medical doctor Ever Total cholesterol ≥5.0 mmol/l or medication Men 21.5 71.1 -49.6 NR Women 19 62.6 -43.6 NR North America Natarajan et al. 2002 (n =8236)22 Doctor or other health professional Ever Total cholesterol ≥5.17 mmol/l 32.1 59.4 -27.3 NR or medication Ahluwalia et al. 2009 (n =733)23 Doctor, nurse or other health professional Ever Total cholesterol ≥6.2 mmol/l 56 44.3 +11.7 0.51 (0.44–0.57) or medication Asia Chun et al. 2016 (n =7270)36 Doctor Ever Total cholesterol ≥6.2 mmol/l 11.7 16.7 -5 0.48 (NR) or medication Australia/New Zealand Taylor et al. 2010 (n =1525)39 Doctor or nurse Currently (‘still’) Total cholesterol ≥5.5 mmol/l 12.3 42.8 -30.5 0.30 (NR) or medication (b) Definition based on measurement only Australia/New Zealand Peterson et al. 2016 (n =7269)40 Doctor or nurse Current Total cholesterol ≥5.5 mmol/l 12.2 (11.5–13.0) 37.3 (36.2–38.4) -25.1 -0.02 (-0.04–0.01) SR vs. MR SR (%) (95% CI) MR (%) (95% CI) SR-MR (%) κ (95% CI) Europe El Fakiri et al. 2007 (n =430)15 Not defined Current ICPC (International Classification of Primary Care) code T93 34 23 +11 0.48 (0.39–0.57) or medication and/or search terms or registration codes specific for the primary health care center North America St Sauver et al. 2005 (n =26162)30 Not defined Ever HICDA-8 (Hospital Adaptation of the International Classification of Diseases, Eight Revision) codes associated with high cholesterol 22.8 27.2 -4.4 NR Koller et a. 2014 (n =3821)33 Doctor or health care provider Ever ICD-9 codes for elevated cholesterol 17.3 18.5 -1.2 0.57 (NR) Note: NR, not reported. Objective data HES measures In HES’s, blood pressure was measured twice or three times. In some studies, the average of two or three measurements was used in the analyses, whereas in others the result of only one measurement was used (Supplementary file 1). Diabetes or elevated blood glucose and elevated total cholesterol status were analyzed from blood samples. For elevated blood glucose, fasting plasma glucose (FPG) or HbA1c from non-fasting samples were used (table 3, Supplementary file 1). In one study, also glucose tolerance test was used.38 Total cholesterol was analyzed from fasting samples in four studies,15,36,39,40 both fasting and non-fasting samples in two studies9,22 and non-fasting samples in one study23 (Supplementary file 1). The definitions and cut-off values for the selected risk factors or diseases varied between the studies (see tables 2–4). In most studies, the use of medication for the condition was taken into account in the definition (measured value exceeded the cut-off value and/or medication was used for the condition). We focus on these studies. Studies based on measurements only are listed in the tables but not used in comparison. For studies that compared self-reported data with HES data the terms ‘hypertension’ and ‘diabetes’ are used when the definition in HES data was based on both measurements (blood pressure or fasting blood glucose/HbA1C) and medication for the condition (tables 2 and 3). We are aware that all respondents in these groups may not fulfil the clinical diagnostic criteria. When the definition was based on measurements only, the terms ‘elevated blood pressure’ and ‘elevated blood glucose’ are used. For cholesterol, the term ‘elevated total cholesterol’ is used in both cases (table 4). Data from MRs The data on MRs or other administrative registers typically relied on diagnostic codes and also the use of medication was taken into account in several studies (tables 2–4). For studies that compared self-reported data with MRs the terms ‘hypertension’, ‘diabetes’ and ‘elevated total cholesterol’ are used. Comparability of prevalence rates obtained from different data sources Self-reported data under-estimated the prevalence of hypertension and elevated total cholesterol in the majority of studies compared with HES data (tables 2 and 4). The difference between SR and MRs was less pronounced. For diabetes, under-estimate was negligible (table 3). Hypertension Self-reported data under-estimated hypertension prevalence in eight out of nine studies where the data for men and women were combined, and the reference data came from HESs (table 2). In a study that showed the prevalence rates for men and women separately, the self-reported hypertension prevalence rate was 10.1 percentage points lower among men and 3.5 percentage points higher among women compared with HES data.9 Among four studies where CI’s were presented, statistically significant under-estimation was observed in three studies. The difference between the prevalence rates by self-reported data and HES ranged from −15.9 to +3.9 percentage points including figures both for men and women combined and separately. The differences between self-reported data and MR data were less consistent (table 2). Hypertension was under-estimated by self-reported data in six out of eight studies that only showed the results for men and women combined. Under-estimation of hypertension was also seen in a study including men only.21 On the contrary, substantial and significant over-estimation of hypertension by SRs was observed in the two age groups in a study for older women.16 The difference between the hypertension prevalence rates by self-reporting and MRs ranged from −14.5 to +19.7 percentage points. The κ coefficients assessing the agreement between two methods ranged from 0.41 to 0.72 for self-reported data vs. HES and from 0.21 to 0.75 for self-reported data vs. MRs (table 2). Diabetes The self-reported data provided fairly similar prevalence rates as did HES and MRs (table 3). The difference in prevalence rates between self-reporting and HES ranged from −2.9 to +0.9 percentage points. When self-reported data were compared with MRs, the difference between the methods ranged from −3.0 to +0.9 percentage points. The κ coefficients ranged from 0.76 to 0.86 for self-reported data vs. HES and from 0.68 to 0.92 for self-reported data vs. MRs (table 3). Elevated total cholesterol Under-reporting of elevated cholesterol was observed in four out of five studies combining data for men and women and comparing self-reporting with HES data (table 4). Substantial under-estimation was observed both among men and women (−49.6 and −43.6 percentage points, respectively) in a study where the data for men and women were analyzed separately.9 The difference between the prevalence rates by self-reporting and HES ranged from −49.6 to +11.7 percentage points. Under-reporting was observed in two out of three studies, when data from self-reporting were compared with data from MRs. The difference between the prevalence rates by self-reporting and MRs ranged from −4.4 to +11 percentage points. The κ coefficients ranged from 0.30 to 0.55 for self-reported data vs. HES. The two κ coefficients reported in the selected publications for self-reported data vs. MRs were 0.48 and 0.57 (table 4). Discussion We compared self-reported data on hypertension, diabetes and elevated total cholesterol with two more objective data sources, HES and MRs or other register based data, to increase knowledge on which methods are most feasible, and produce reliable, accurate and comparable information for health monitoring purposes. Studies published in 2000–16 that compared self-reported data with either HES data or MRs were evaluated. Self-reported data tended to under-estimate prevalence rates especially for hypertension and elevated total cholesterol, which is in line with earlier reviews.8,13 The under-estimate was more pronounced, when the self-reported data were compared with HES data instead of MRs. Hypertension and elevated total cholesterol are typically asymptomatic for a long time and remain therefore easily unmeasured and undetected. Therefore, they may be under-estimated in MR data. In a study from the Netherlands, both HES and MRs were included as reference material.15 Higher hypertension prevalence was reported with HES than with MRs (59% and 44%, respectively), which also suggests that MRs do not cover all hypertensive subjects. Diabetes was more accurately self-reported both compared with HES data and MRs, which is also in line with earlier reviews.13 As the screening of blood glucose and the use risk tests for diabetes have become more common the awareness of the condition has improved. The κ coefficients were consistent with the comparisons based on prevalence rates in that the overall agreement between SR and HES or MRs was higher for diabetes than for hypertension or elevated cholesterol. In an earlier review, the following factors, among others, were reported to explain the inaccuracy of SR: respondents may lack the knowledge to accurately answer the questions posed, and poorly designed survey instruments could result in respondents not fully comprehending the questions.13 Participants’ awareness of the disease or risk factor levels is crucial to obtain accurate reporting in HIS studies.9 Unless a diagnosis is set or risk factors examined and thoroughly explained to the patient by medical professionals, the participants are not aware of them, as many conditions are asymptomatic. In general, women have been more often aware of their hypertension than men,42–44 which can be partly explained by regular follow-up during pregnancies. This applied also to the evaluated studies reporting hypertension separately for men and women.9,36,39 If SR is based on having ever been told to have elevated blood pressure or elevated blood glucose, pregnancy complications may lead to higher prevalence rates for women. This might explain a part of the slight overestimation of hypertension among women.9 In contrast, the substantial overestimation of hypertension among older women cannot be explained with conditions related to pregnancies as the question concerned the past 3 years only.16 Instead, the authors’ presumed hypertension to be underestimated in the hospital data. The awareness of one’s own conditions or risk factor levels may have increased over time in many populations. Measuring blood pressure with digital devices at home has become more common and cholesterol and blood glucose measurements may be available more widely than earlier and also outside medical services, e.g. at pharmacies and health clubs. Hypertension awareness has increased significantly among hypertensives43,44 and this development can be presumed to have continued. The comparability of studies included in this evaluation was hindered by many discrepancies in their methods. Self-reported data on risk factors or diseases were collected heterogeneously as varying questions and definitions were used in different studies and the time frame covered with the question varied. Both population level coverage of the service and coverage in recording diagnoses and measures limit comparability of data from MRs or other administrative registers. For HES data, the use of medication was not taken into account in the definition of the conditions in all studies. We decided to focus on studies where the definition was based on both measured values and the use of medication, although the issue of medication is not straightforward. Antihypertensive drugs and statins are also used for other indications than elevated blood pressure or cholesterol. Considering medication based on recorded product names may hence have led to overestimation of hypertension or elevated cholesterol if the indication was not specified. Furthermore, different cut-off values were used, especially for elevated total cholesterol. The cut-offs used for elevated total cholesterol ranged from 5.0 to 6.5 mmol/l. The lowest cut-off was applied in a study in which also the largest underestimate of elevated total cholesterol by SR was seen.9 In addition, results for two cut-offs were shown in one study.23 Using the lower cut-off (5.17 mmol/l) resulted in a conclusion that SR underestimated, whereas using the higher cut-off (6.2 mmol/l) resulted in a conclusion that SR overestimated elevated total cholesterol. This might be related to practicing clinicians using different thresholds for communicating elevated cholesterol levels.22 Medication was included in the definition only in the case of the higher cut-off, which is why we only included the results by the higher cut-off from the study in question in this evaluation. Masked or white coat hypertension may also affect the prevalence rates for elevated blood pressure, as in HESs blood pressure is measured on one occasion only and most commonly in an office at the examination site.45,46 Methodological differences, such as the format of questions, response rates and survey modes, among national surveys have hampered valid mutual comparisons,4,47,48 but recent efforts for standardization in European countries will improve the situation.6 However, rising non-participation rates cause problems and attention needs to be given to recruitment methods.7 While electronic patient records have improved the availability of data and provide information not available from survey data such as comorbidity and diagnostic and treatment details, they cannot fully substitute survey data. MRs may not always be up-to-date and there may be socio-economic differences in access to medical care.49 In clinical practice, screening for cardiovascular risk factors and control of diagnosed diseases may not be systematic. The measures rely on health professionals’ practice patterns and accuracy of recording.12 MRs may also lack information on diagnoses performed in different health care sectors (public vs. private sector), and background and health behaviours. There may also be limitations in availability of or access to MRs for research purposes. Conclusions All the data sources have their strengths and limitations, and none of them alone should be regarded as a gold standard. However, using only self-reported data in monitoring vascular diseases and their risk at the population level may lead to underestimation of the true prevalence especially in regards to hypertension and elevated total cholesterol. Whenever feasible, combined information from standardized interviews and measurements supplemented with register data to exploit the advantages of all of them might be used for public health monitoring. Supplementary data Supplementary data are available at EURPUB online. Funding This work was supported by the European Commission/DG SANTÉ (BRIDGE Health Project, grant number 664691). The views expressed here are those of the authors and they do not represent the Commission’s official position. Conflicts of interest: None declared Key points The prevalence rates of hypertension and elevated total cholesterol were under-estimated with self-reported data compared with data from HESs and to a smaller extent compared with medical records. Instead, all the three data sources resulted in quite similar diabetes prevalence rates. The methods and the wordings used in questions varied between the studies which hindered the comparison. 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Journal

The European Journal of Public HealthOxford University Press

Published: Feb 16, 2018

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