Detecting persons at risk for diabetes mellitus type 2 using FINDRISC: results from a community pharmacy-based study

Detecting persons at risk for diabetes mellitus type 2 using FINDRISC: results from a community... Abstract Background This cross-sectional study has been developed within the framework of the Italian project ‘We love your heart’ (‘Ci sta a cuore il tuo cuore’) and reports the results of the initial type 2 diabetes mellitus (T2DM) risk assessment carried out in a big network of community pharmacies in Italy and Spain. Methods In total 4002 pharmacists from 854pharmacies were specifically trained to collect data and perform the evaluation of the probability of developing T2DM among pharmacy customers. The risk of developing T2DM within 10 years was evaluated using the FINDRISC. Results Overall, 7234 (22.1%) subjects were at low risk to develop the disease, whereas 43.3% were at slightly elevated risk (scores 7–11), 19.3% were at moderate (scores 12–14), 13.9% were at high (scores 15–20), and 1.4% were at very high risk (scores > 20). Spanish participants showed higher levels of risk than Italian (16.7 vs. 14.7%) taking the cut-off FINDRISC ≥ 15. Conclusion This study shows that considerable percentage of persons is likely to develop diabetes in the next 10 years. Analyses of the risk factors indicate that men were more susceptible to develop this disease, as well as the Spanish participants respect to Italian. Introduction Type 2 diabetes mellitus (T2DM) represents an enormous public health issue,1 for which an effective intervention for prevention is not always easy to implement on a population level. Therefore, early identification of the subjects at risk to develop the disease with cost-effective, non-invasive and reliable risk tools is highly important, especially in raising awareness of the risk and changes of their behaviours and lifestyles in time. In the previous decades, there has been made a great effort to develop a simple, fast and practical tool for identification of these individuals,2–9 among which the FINDRISC was shown to be a reliable, validated and practical in some previously published studies conducted mostly in Caucasian population.10–18 The wide applicability and reliability of FINDRISC can be explained with its focus on the most prevalent risk factors for T2DM.19 FINDRISC is defined by eight items: age, BMI (kg/m2), WC (cm), physical activity, diet, anti-hypertensive drug use, history of high blood glucose and family history of diabetes.2,18 Prevalence of elevated FINDRISC has not been widely studied in the general population or using stratification by gender or age. Still, in some studies higher prevalence of elevated FINDRISC in women respect to men has been showed,10,20,21 while it is still questionable whether an elevated FINDRISC carries a similar risk of diabetes in younger respect to the older adults. This kind of information is essential also for evaluating the need for follow-up of individuals at high risk, particularly at the population level, therefore stressing an important role of community pharmacists in the health promotion field.22 The World Health Organization reported that ‘Pharmacists have an important role to play, which is much more than selling medicines’, highlighting the importance of community pharmacies as an ideal counselling site of the population due to the following reasons: pharmacies are easily accessible because of the extended opening hours, frequency of contacts with the general public is high, and wide territorial distribution.23,24 This study has been developed within the framework of the Italian campaign ‘We love your heart’ (‘Ci sta a cuore il tuo cuore’), brought by the ‘Apoteca Natura’ network of pharmacies with the support of the Italian Society of General Practitioner programme (SIMG) and the Italian Association of Diabetologists (AMD). The developed initiative was focussed on prevention of cardiovascular diseases and T2DM through early identification of high-risk individuals, and aimed to raise the awareness on the promotion of healthy lifestyles. This study aimed to identify the persons at risk for T2DM in the following 10 years and to classify themusing FINDRISC questionnaire. Additional objective wasto estimate the prevalence of elevated FINDRISC by several demographic characteristics. Methods Study sample and campaign characteristics This cross-sectional study was developed within the project of the ‘Apoteca Natura’ pharmacy network titled ‘We love your heart’ (‘Ci sta a cuore il tuo cuore’). In total 4002 Italian and Spanish pharmacists from 854 pharmacies have been specifically trained to collect the data from all apparently healthy subjects older than 18 years using validated questionnaires, and to perform the evaluation of the probability to develop T2DM in the next ten years. The prevention campaign was performed in the period from January 2014 to December 2015 by assessing voluntary customers. The campaign in pharmacies was actively performed in November, but it was further extended also to the other periods of the year and widely advertised through leaflets, posters, TV-commercials, invitations to participate transmitted on web, in the newspapers etc. The questionnaire included information on previously known diabetes and the FINDRISC items, and measurements of principal health indicators (i.e. blood pressure and cholesterol). Individuals filled in the questionnaire only once per person during the initiative. Persons affected by diabetes mellitus type 2 were excluded from the study (n = 2189, 6.3%), as well as the customers who were not able to autonomously fill in the questionnaire. The risk of developing T2DM within 10 years was categorized according to the risk scores: <7 points (low), 7–11 points (slightly elevated), 12–14 points (moderate), 15–20 points (high) and >20 points (very high). In the original Finnish study population, the maximum total score was 26 and a score >15 points was associated with a high risk of developing type 2 diabetes in the following 10 years.2,10 All measurements of FINDRISC items were performed in the pharmacies by trained personnel. Data on weight and height, obtained through measuring with light clothes and without shoes, were subsequently used to calculate BMI (body mass index) as weight (in kg) divided by the squared value of height (in meters). Waist circumference (WC) was obtained while the participants were standing, using an unextendable measuring band. Physical activity was initially described as ‘during working hours’ and ‘during leisure time’, and categorized in the following way: ‘absent’, ‘light’, ‘medium’ and ‘high’ (at least 30 min/d). For the purpose of our analysis, two types of physical activities (working time and leisure time) were merged and dichotomized as ‘>30 min/d’ or ‘<30 min/d’, according to the FINDRISC methodology. Daily consumption of fruits, berries or vegetables was investigated using the subsequent categories of intake: ‘never/sometimes’, ‘not every day’ and ‘every day’. For the purpose of this study the variable was dichotomized and reported as: ‘every day’ and ‘not every day’. Previous use of antihypertensive medications was reported within ‘Yes/No’ question. Blood pressure (systolic and diastolic) was measured by the pharmacists at the screening sites. Data regarding history of high blood glucose were not collected by direct tests in the pharmacies, but only by using simple recall ‘Have you ever had high blood glucose’ question. Family history of diabetes was reported within two family grades: first degree relatives (parents, brother, sisters and children), and second degree relatives (grandparents, uncles, aunts and cousins). The participants were informed that participation was strictly voluntary and after reading the privacy policy statement, those who were willing to participate in the study enclosed their firmed informed consents. All persons recruited for this campaign were assured that their personal data are confidential and that no information could lead to identification of any individual, because the data were used anonymously with encrypted codes. Referral to the general practitioner for further assessment was recommended as appropriate, with the request for providing care for those with abnormal results or at high risk. Statistical analysis A descriptive analysis was conducted to report demographic and basic clinical characteristics of the involved participants, as well as for the distribution of FINDRISC variables. In order to have two populations comparable on age profiles, a direct standardization technique has been performed to calculate the age-adjusted prevalence of persons at risk to develop it in the next 10 years (FINDRISC cut-off ≥15), using the European population as reference.25 General characteristics of the participants and FINDRISC variables were compared across Italy and Spain using t-test and one-way ANOVA for the continuous variables, while the categorical variables were analysed with chi-squared test. P values < 0.05 were considered statistically significant. Statistical analyses were performed using IC Stata 14 for Mac. This study followed the recommendation of the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) checklist. Results This initiative for early detection of risk for T2DM using FINDRISC questionnaire involved the total of 32722 adults, out of which 65.4% were females, and 34.6% males (table 1). Table 1 Main demographic characteristics of the participants and distribution of FINDRISC variables     Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000      Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Table 1 Main demographic characteristics of the participants and distribution of FINDRISC variables     Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000      Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Italians accounted for 73.3% of the participants, while remaining 26.7% were Spanish citizens. The age ranged from 18 to 100 years, while mean age was 56.5 ± 12.3 (mean ± SD), which was not statistically different between two countries (P = 0.155) (table 1). Further details on population characteristics are provided in the table 1. Overall, 7234 (22.1%) subjects were at low risk to develop the disease, while 43.3% were at slightly elevated risk (scores 7–11), 19.3% were at moderate (scores 12–14), 13.9% were at high (scores 15–20) and 1.4% were at very high risk (scores > 20). In the categories with the cut-off FINDRISC ≥15, Spanish participants showed higher level of risk respect to Italians (16.7 vs. 14.7%), which was further confirmed when the age-adjusted prevalence for FINDRISC ≥15 was calculated (10.8 vs. 9.9%, respectively). Analysis of the age categories showed the same trend, where starting from the youngest to the oldest participants, the percentage of risk rose from 3.42% (<45 years) to finally reach its peak in the oldest category (≥65 years) with 25.2% (table 2). Table 2 Distribution of FINDRISC classes: overall, across demographic groups, by FINDRISC variables and other variables of interest FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    Abbreviations: BMI, body mass index; WC, waist circumference. Table 2 Distribution of FINDRISC classes: overall, across demographic groups, by FINDRISC variables and other variables of interest FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    Abbreviations: BMI, body mass index; WC, waist circumference. Findings from table 3 speak in favor of women as generally healthier than men. They had lower BMI values (−1.4 kg/m2, P < 0.001), practiced more balanced diet (+8.8%, P < 0.001), and were less treated for hypertension (−5.7%, P < 0.001). In addition, men showed higher percentage for history of high blood glucose (9.9 vs. 8.9%, P < 0.001). On the other hand, men were more physically active (+7.8%, P < 0.001). All variables taken into account for FINDRISC calculations differed statistically between countries (P < 0.001), except for, age, daily consumption of fruits and vegetables, previous hypertension treatment, and history of high blood glucose (table 1). To delineate, Italians compared with Spanish people had lower BMI (−1.5 kg/m2, P < 0.001), and WC (−1.2 cm, P < 0.001). Table 3 Distribution of FINDRISC variables across gender and age groups FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Table 3 Distribution of FINDRISC variables across gender and age groups FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Discussion To the best of our knowledge, this is the first study reporting the results of the initial T2DM risk assessment carried out in a big network of community pharmacies in Italy and Spain. Within the ‘Ci sta a cuore il tuo cuore’ initiative a large sample was collected in the period 2014–15, out of which 4988 people (15.3%) from the study population are at high or very high risk to develop diabetes in the next 10 years, which is in accordance with the risk range of 9.6–qw45% shown in studies conducted in other countries that used the same cut-off point of FINDRISC (≥15).26–28 This wide range mirrors different probabilities to develop T2DM between populations due to their variability in genetic characteristics, dietary patterns or age distribution. Spanish participants were more represented in ‘high’ and ‘very high’ risk group respect to Italians (16.7 vs. 14.7%; P < 0.001). Few previously published papers in the two countries of interest used the FINDRISC tool in examining the T2DM risk and our results are in accordance with their findings. Nevertheless, studies from Italy were performed on remarkably smaller samples and only at provincial level.29,30 Bonaccorsi et al analysed 658 persons aged 35–70 years (mean age: men 54 years, women 53 years) and found that 16.7% were at high risk, while 4.9% were at very high risk.29 On the other hand, our study that involved very large sample, collected through all the Italian regions, may mirror more appropriately the risk for T2DM in Italy. With regard to Spain, one study reported T2DM risk using the FINDRISC questionnaire.28 In the sample of 4222 pharmacy users who were older than 18 years (mean age 55.3 years), Fornos-Perez et al found that 20.9% were at high risk, while 2.6% was at very high risk. Findings from this article are in accordance with what has been published in other European studies conducted in populations demographically similar to ours, which used the same cut-off for FINDRISC. One study on FINDRISC conducted in Norway in the population aged ≥20 years had similar mean age (women 52.2 ± 16.2 years, men 53.0 ± 15.6),31 and the reported risk to develop T2DM in the following 10 years was 11% for high and very high-risk categories. Similarly, a group of American authors assessed the participants comparable to ours (mean age of 47.6 ± 17.8 years), and the risk for the categories with FINDRISC ≥ 15 was reported to be 17%20. The FINDRISC was rising as the age increased, which was also confirmed by the dichotomization of FINDRISC with the cut-off of 15 points. The risk was growing steadily starting from the youngest age class (<45: 3.42%), through middle age categories (45–54 years: 9.7%, and 55–64: 17.5%, respectively), to the oldest persons (≥65: 25.2%). These results are in accordance with some previously published studies.28,31 When considering sex differences, the analysis of the risk factors for the onset of T2DM indicate that men were more susceptible to develop this disease. They were also more diagnosed respect to women. These findings are consistent for the two countries, as well as with the literature evidence.31–35 Nevertheless, the analysis across FINDRISC categories did not show any significant difference between men and women (table 2). A possible explanation of the lack of differences in gender-specific FINDRISC, as previously suggested by Jolle et al.,31 may be a potentially poorer recall regarding family history of diabetes among men respect to women, therefore causing a recall bias and reducing the overall FINDRISC in men.36 Previous findings using the FINDRISC tool are conflicting.10,31,37 A slightly higher FINDRISC in women respect to men was noted in two studies,10,31 while one recently published Spanish paper reported no significant difference between women and men in mean FINDRISCs (11.4 vs. 11.2, P = 0.2).37 When interpreting the results of this study, some limitations need to be discussed as follows. The lower representation of men, as well as of Spanish people in the study sample might have limited the analysis. This can be justified because women usually enter the pharmacies at their own initiative to get an advice, to buy medications for family members, or some natural products and cosmetics. Furthermore, women are believed to have a lower employment rate which allows them a frequent access to the pharmacies also during the weekly working time. The differences in age distribution within the study sample and the general population can be explained similarly. The older persons usually have plenty of free time, and are also more susceptible to the polypharmacy, which requires more frequent contacts with the pharmacies respect to the younger population. In order to overcome this limit, the age-adjusted prevalence for persons at increased risk to develop the disease has been calculated. Regarding the lower participation rate of Spanish customers, it is likely due to the greater number of pharmacies within the ‘Apoteca Natura’ network in Italy respect to Spain. Lack of information on response rates leaves open the question of the ability of community pharmacies to reach a significant proportion of the population for the analysis of campaign effectiveness. Considerable strength of this study is the choice of community setting as initiative site, which allowed reaching the specific population of apparently healthy persons. Moreover, taking into account the differences between these kinds of participants respect to the hospital subjects who can be studied more easily, collecting the sample with great number of subjects from the pharmacies rendered this article even more relevant. Sample size of 32 722 well-characterized subjects, enabled calculating the estimates across sex, age and other demographic groups. Additionally, FINDRISC questionnaires were guided and filled in with help of trained pharmacists, limiting the risk of inaccuracy and enhancing the quality and reliability of the collected data. Taking into account that a large number of apparently healthy subjects from our sample was conversely at elevated risk for T2DM, our study might suggest pharmacy as an important public health site for developing and implementing future preventive strategies. Acknowledgements The authors would like to acknowledge the’ Apoteca Natura’ network, in particular Mr Massimo Mercati, Mrs Alessia Scarpocchi, Mrs Maria del Pilar Garcia del Gado, and Mr Roberto Zizza for ideating the campaign ‘Ci sta a cuore il tuo cuore’, developing the tools and materials and providing all the necessary support for the realization of the initiative. Additionally, a high valuable scientific contribution was made by SIMG (Italian General Medicine Society), ADI (Association of Italian diabetologists) and FOFI (Italian Federation of Pharmacists) in the validation of tools and materials of the initiative ‘Ci sta a cuore il tuo cuore’. Finally, a special thanks goes to the the ‘Apoteca Natura’ pharmacists for their serious and constant commitment in carrying on this important project and their efforts to spread this community-pharmacy based health promotion initiative. Funding The authors would like to acknowledge ‘Apoteca Natura’ for the unconditional grant provided for this study to the Università Cattolica del Sacro Cuore. Conflicts of interest: None declared. Key points More than 15% of ‘health’ pharmacy customers evaluated by the FINDRISC questionnaire are at high risk to develop T2DM in the next 10 years. Community pharmacies may represent a great opportunity to strengthen primary prevention at local level since they are often the first point for addressing the health problems for the majority of the population. Specifically designed health promotion interventions with active involvement of the pharmacists as health care team members might be an important future public health strategy. Further studies with an adequate follow-up period can be helpful in evaluating the efficacy of this kind of health promotion campaign. References 1 International Diabetes Federation. IDF Diabetes Atlas 5th edn. Media, 2011. Available from: https://www.idf.org/e-library/epidemiology-research/diabetes-atlas.html (13 March 2017, date last accessed). 2 Lindström J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care  2003; 26: 725– 31. Google Scholar CrossRef Search ADS PubMed  3 Stern MP, Williams K, Haffner SM. Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med  2002; 136: 575. Google Scholar CrossRef Search ADS PubMed  4 Griffin SJ, Little PS, Hales CN, et al.   Diabetes risk score: towards earlier detection of type 2 diabetes in general practice. Diabetes Metab Res Rev  2000; 16: 164– 71. Google Scholar CrossRef Search ADS PubMed  5 Colagiuri S, Hussain Z, Zimmet P, et al.   Screening for type 2 diabetes and impaired glucose metabolism: the Australian experience. Diabetes Care  2004; 27: 367– 71. Google Scholar CrossRef Search ADS PubMed  6 Kanaya AM, Wassel Fyr CL, de Rekeneire N, et al.   Predicting the development of diabetes in older adults: the derivation and validation of a prediction rule. Diabetes Care  2005; 28: 404– 8. Google Scholar CrossRef Search ADS PubMed  7 Heikes KE, Eddy DM, Arondekar B, Schlessinger L. Diabetes Risk Calculator A simple tool for detecting undiagnosed diabetes and pre-diabetes. Diabetes Care  2008; 31: 1040– 5. Google Scholar CrossRef Search ADS PubMed  8 Ruige JB, Neeling J. N D d, Kostense PJ, et al.   Performance of an NIDDM screening questionnaire based on symptoms and risk factors. Diabetes Care  1997; 20: 491– 6. Google Scholar CrossRef Search ADS PubMed  9 Balkau B, Lange C, Fezeu L, et al.   Predicting diabetes: clinical, biological, and genetic approaches. Diabetes Care  2008; 31: 2056– 61. Google Scholar CrossRef Search ADS PubMed  10 Saaristo T, Peltonen M, Lindström J, et al.   Cross-sectional evaluation of the Finnish Diabetes Risk Score: a tool to identify undetected type 2 diabetes, abnormal glucose tolerance and metabolic syndrome. Diabetes Vasc Dis Res  2005; 2: 67– 72. Google Scholar CrossRef Search ADS   11 Abduelkarem AR, Sharif SI, Hammrouni AM, et al.   Risk calculation of developing type 2 diabetes in Libyan adults. Pract Diabetes Int  2009; 26: 148– 51. Google Scholar CrossRef Search ADS   12 Mohieldein AH, Alzohairy M, Hasan M. Risk Estimation of Type 2 Diabetes and Dietary Habits among Adult Saudi Non-diabetics in Central Saudi Arabia. Glob J Health Sci  2011; 3: 123– 33. Google Scholar CrossRef Search ADS   13 Hjellset VT, Bjørge B, Eriksen HR, Høstmark AT. Risk factors for type 2 diabetes among female Pakistani immigrants: the InvaDiab-DEPLAN study on Pakistani immigrant women living in Oslo, Norway. J Immigr Minor Health  2011; 13: 101– 10. Google Scholar CrossRef Search ADS PubMed  14 García-Alcalá H, Nathalie C, Genestier-Tamborero, et al.   Frequency of diabetes, impaired fasting glucose, and glucose intolerance in high-risk groups identified by a FINDRISC survey in Puebla city, Mexico. Diabetes. Metab Syndr Obes Targets Ther  2012; 5: 403– 6. Google Scholar CrossRef Search ADS   15 Naranjo A a, Rodríguez ÁY, Llera RE, et al.   Diabetes risk in a Cuban primary care setting in persons with no known glucose abnormalities. MEDICC Rev  2013; 15: 16– 9. Google Scholar CrossRef Search ADS PubMed  16 Winkler G, Hídvégi T, Vándorfi G, et al.   Prevalence of undiagnosed abnormal glucose tolerance in adult patients cared for by general practitioners in Hungary. Results of a risk-stratified screening based on FINDRISC questionnaire. Med Sci Monit  2013; 19: 67– 72. Google Scholar CrossRef Search ADS PubMed  17 Vermunt PWA, Milder IEJ, Wielaard F, et al.   Lifestyle counseling for type 2 diabetes risk reduction in dutch primary care: results of the APHRODITE study after 0.5 and 1.5 years. Diabetes Care  2011; 34: 1919– 25. Google Scholar CrossRef Search ADS PubMed  18 Paulweber B, Valensi P, Lindstrom J, et al.   A European evidence-based guideline for the prevention of type 2 diabetes. Horm Metab Res  2010; 42(Suppl 1): S3– 36. Google Scholar CrossRef Search ADS PubMed  19 Schwarz PEH, Li J, Reimann M, et al.   The Finnish Diabetes Risk Score is associated with insulin resistance and progression towards type 2 diabetes. J Clin Endocrinol Metab  2009; 94: 920– 6. Google Scholar CrossRef Search ADS PubMed  20 Zhang L, Zhang Z, Zhang Y, et al.   Evaluation of Finnish diabetes risk score in screening undiagnosed diabetes and prediabetes among U.S. adults by gender and race: nHANES 1999-2010. PLoS One  2014; 9: e97865., Google Scholar CrossRef Search ADS   21 Saaristo T, Moilanen L, Jokelainen J, et al.   Cardiometabolic profile of people screened for high risk of type 2 diabetes in a national diabetes prevention programme (FIN-D2D). Prim Care Diabetes  2010; 4: 231– 9. Google Scholar CrossRef Search ADS PubMed  22 O’Loughlin J, Masson P, Déry V, Fagnan D. The role of community pharmacists in health education and disease prevention: a survey of their interests and needs in relation to cardiovascular disease. Prev Med (Baltim)  1999; 28: 324– 31. Google Scholar CrossRef Search ADS   23 the World Health Organization (WHO). The Role of the Pharmacist in the Health Care System. 1994. Available from: http://apps.who.int/medicinedocs/en/d/Jh2995e/ (13 March 2017, date last accessed). 24 Laliberté M, Perreault S, Damestoy N, Lalonde L. Ideal and actual involvement of community pharmacists in health promotion and prevention: a cross-sectional study in Quebec, Canada. BMC Public Health  2012; 12: 192. Google Scholar CrossRef Search ADS PubMed  25 Eurostat. Eurostat population by age group, sex and NUTS2 region [Internet]. Available at: http://appsso.eurostat.ec.europa.eu/nui/show.do? dataset=demo_r_pjangroup&lang=en (01 September 2017, date last accessed). 26 Hellgren MI, Petzold M, Björkelund C, et al.   Feasibility of the FINDRISC questionnaire to identify individuals with impaired glucose tolerance in Swedish primary care. A cross-sectional population-based study. Diabet Med  2012; 29: 1501– 5. Google Scholar CrossRef Search ADS PubMed  27 Makrilakis K, Liatis S, Grammatikou S, et al.   Validation of the Finnish diabetes risk score (FINDRISC) questionnaire for screening for undiagnosed type 2 diabetes, dysglycaemia and the metabolic syndrome in Greece. Diabetes Metab  2011; 37: 144– 51. Google Scholar CrossRef Search ADS PubMed  28 Fornos-Pérez JA, Andrés-Rodríguez NF, Andrés-Iglesias JC, et al.   Detection of people at risk of diabetes in community pharmacies of Pontevedra (Spain) (DEDIPO). Endocrinol Nutr  2016; 63: 387– 96. Google Scholar CrossRef Search ADS PubMed  29 Bonaccorsi G, Guarducci S, Ruffoli E, Lorini C. Diabetes screening in primary care: the PRE.DI.CO. study. Ann Ig  2012; 24: 527– 34. Google Scholar PubMed  30 Noto D, Cefalu AB, Barbagallo CM, et al.   Prediction of incident type 2 diabetes mellitus based on a twenty-year follow-up of the Ventimiglia heart study. Acta Diabetol  2012; 49: 145– 51. Google Scholar CrossRef Search ADS PubMed  31 Jølle A, Midthjell K, Holmen J, et al.   Impact of sex and age on the performance of FINDRISC: the HUNT Study in Norway. BMJ open diabetes Res care  2016; 4: e000217. Google Scholar CrossRef Search ADS PubMed  32 Sociietà Italiana di Diabetologia. Il diabete in Italia. 2016. 33 Wändell PE, Carlsson AC. Gender differences and time trends in incidence and prevalence of type 2 diabetes in Sweden-A model explaining the diabetes epidemic worldwide today?. Diabetes Res Clin Pract  2014; 106: e90– 2. Google Scholar CrossRef Search ADS PubMed  34 Danaei G, Finucane MM, Lu Y, et al.   National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2-7 million participants. Lancet  2011; 378: 31– 40. Google Scholar CrossRef Search ADS PubMed  35 International Diabetes Federation [Internet]. IDF Diabates Atlas, 7th edition. 2015 [cited 2017 Jan 1]. Available at: http://www.diabetesatlas.org/across-the-globe.html (25 November 2016, date last accessed). 36 Fuentes A, Desrocher M. The effects of gender on the retrieval of episodic and semantic components of autobiographical memory. Memory  2013; 21: 619– 32. Google Scholar CrossRef Search ADS PubMed  37 Salinero-Fort MA, Burgos-Lunar C, Lahoz C, et al.   Performance of the finnish diabetes risk score and a simplified finnish diabetes risk score in a community-based, cross-sectional programme for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in Madrid, Spain: the SPREDIA-2 study. PLoS One  2016; 11: e0158489– 17. 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The European Journal of Public Health Oxford University Press

Detecting persons at risk for diabetes mellitus type 2 using FINDRISC: results from a community pharmacy-based study

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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.
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1101-1262
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1464-360X
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Abstract

Abstract Background This cross-sectional study has been developed within the framework of the Italian project ‘We love your heart’ (‘Ci sta a cuore il tuo cuore’) and reports the results of the initial type 2 diabetes mellitus (T2DM) risk assessment carried out in a big network of community pharmacies in Italy and Spain. Methods In total 4002 pharmacists from 854pharmacies were specifically trained to collect data and perform the evaluation of the probability of developing T2DM among pharmacy customers. The risk of developing T2DM within 10 years was evaluated using the FINDRISC. Results Overall, 7234 (22.1%) subjects were at low risk to develop the disease, whereas 43.3% were at slightly elevated risk (scores 7–11), 19.3% were at moderate (scores 12–14), 13.9% were at high (scores 15–20), and 1.4% were at very high risk (scores > 20). Spanish participants showed higher levels of risk than Italian (16.7 vs. 14.7%) taking the cut-off FINDRISC ≥ 15. Conclusion This study shows that considerable percentage of persons is likely to develop diabetes in the next 10 years. Analyses of the risk factors indicate that men were more susceptible to develop this disease, as well as the Spanish participants respect to Italian. Introduction Type 2 diabetes mellitus (T2DM) represents an enormous public health issue,1 for which an effective intervention for prevention is not always easy to implement on a population level. Therefore, early identification of the subjects at risk to develop the disease with cost-effective, non-invasive and reliable risk tools is highly important, especially in raising awareness of the risk and changes of their behaviours and lifestyles in time. In the previous decades, there has been made a great effort to develop a simple, fast and practical tool for identification of these individuals,2–9 among which the FINDRISC was shown to be a reliable, validated and practical in some previously published studies conducted mostly in Caucasian population.10–18 The wide applicability and reliability of FINDRISC can be explained with its focus on the most prevalent risk factors for T2DM.19 FINDRISC is defined by eight items: age, BMI (kg/m2), WC (cm), physical activity, diet, anti-hypertensive drug use, history of high blood glucose and family history of diabetes.2,18 Prevalence of elevated FINDRISC has not been widely studied in the general population or using stratification by gender or age. Still, in some studies higher prevalence of elevated FINDRISC in women respect to men has been showed,10,20,21 while it is still questionable whether an elevated FINDRISC carries a similar risk of diabetes in younger respect to the older adults. This kind of information is essential also for evaluating the need for follow-up of individuals at high risk, particularly at the population level, therefore stressing an important role of community pharmacists in the health promotion field.22 The World Health Organization reported that ‘Pharmacists have an important role to play, which is much more than selling medicines’, highlighting the importance of community pharmacies as an ideal counselling site of the population due to the following reasons: pharmacies are easily accessible because of the extended opening hours, frequency of contacts with the general public is high, and wide territorial distribution.23,24 This study has been developed within the framework of the Italian campaign ‘We love your heart’ (‘Ci sta a cuore il tuo cuore’), brought by the ‘Apoteca Natura’ network of pharmacies with the support of the Italian Society of General Practitioner programme (SIMG) and the Italian Association of Diabetologists (AMD). The developed initiative was focussed on prevention of cardiovascular diseases and T2DM through early identification of high-risk individuals, and aimed to raise the awareness on the promotion of healthy lifestyles. This study aimed to identify the persons at risk for T2DM in the following 10 years and to classify themusing FINDRISC questionnaire. Additional objective wasto estimate the prevalence of elevated FINDRISC by several demographic characteristics. Methods Study sample and campaign characteristics This cross-sectional study was developed within the project of the ‘Apoteca Natura’ pharmacy network titled ‘We love your heart’ (‘Ci sta a cuore il tuo cuore’). In total 4002 Italian and Spanish pharmacists from 854 pharmacies have been specifically trained to collect the data from all apparently healthy subjects older than 18 years using validated questionnaires, and to perform the evaluation of the probability to develop T2DM in the next ten years. The prevention campaign was performed in the period from January 2014 to December 2015 by assessing voluntary customers. The campaign in pharmacies was actively performed in November, but it was further extended also to the other periods of the year and widely advertised through leaflets, posters, TV-commercials, invitations to participate transmitted on web, in the newspapers etc. The questionnaire included information on previously known diabetes and the FINDRISC items, and measurements of principal health indicators (i.e. blood pressure and cholesterol). Individuals filled in the questionnaire only once per person during the initiative. Persons affected by diabetes mellitus type 2 were excluded from the study (n = 2189, 6.3%), as well as the customers who were not able to autonomously fill in the questionnaire. The risk of developing T2DM within 10 years was categorized according to the risk scores: <7 points (low), 7–11 points (slightly elevated), 12–14 points (moderate), 15–20 points (high) and >20 points (very high). In the original Finnish study population, the maximum total score was 26 and a score >15 points was associated with a high risk of developing type 2 diabetes in the following 10 years.2,10 All measurements of FINDRISC items were performed in the pharmacies by trained personnel. Data on weight and height, obtained through measuring with light clothes and without shoes, were subsequently used to calculate BMI (body mass index) as weight (in kg) divided by the squared value of height (in meters). Waist circumference (WC) was obtained while the participants were standing, using an unextendable measuring band. Physical activity was initially described as ‘during working hours’ and ‘during leisure time’, and categorized in the following way: ‘absent’, ‘light’, ‘medium’ and ‘high’ (at least 30 min/d). For the purpose of our analysis, two types of physical activities (working time and leisure time) were merged and dichotomized as ‘>30 min/d’ or ‘<30 min/d’, according to the FINDRISC methodology. Daily consumption of fruits, berries or vegetables was investigated using the subsequent categories of intake: ‘never/sometimes’, ‘not every day’ and ‘every day’. For the purpose of this study the variable was dichotomized and reported as: ‘every day’ and ‘not every day’. Previous use of antihypertensive medications was reported within ‘Yes/No’ question. Blood pressure (systolic and diastolic) was measured by the pharmacists at the screening sites. Data regarding history of high blood glucose were not collected by direct tests in the pharmacies, but only by using simple recall ‘Have you ever had high blood glucose’ question. Family history of diabetes was reported within two family grades: first degree relatives (parents, brother, sisters and children), and second degree relatives (grandparents, uncles, aunts and cousins). The participants were informed that participation was strictly voluntary and after reading the privacy policy statement, those who were willing to participate in the study enclosed their firmed informed consents. All persons recruited for this campaign were assured that their personal data are confidential and that no information could lead to identification of any individual, because the data were used anonymously with encrypted codes. Referral to the general practitioner for further assessment was recommended as appropriate, with the request for providing care for those with abnormal results or at high risk. Statistical analysis A descriptive analysis was conducted to report demographic and basic clinical characteristics of the involved participants, as well as for the distribution of FINDRISC variables. In order to have two populations comparable on age profiles, a direct standardization technique has been performed to calculate the age-adjusted prevalence of persons at risk to develop it in the next 10 years (FINDRISC cut-off ≥15), using the European population as reference.25 General characteristics of the participants and FINDRISC variables were compared across Italy and Spain using t-test and one-way ANOVA for the continuous variables, while the categorical variables were analysed with chi-squared test. P values < 0.05 were considered statistically significant. Statistical analyses were performed using IC Stata 14 for Mac. This study followed the recommendation of the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) checklist. Results This initiative for early detection of risk for T2DM using FINDRISC questionnaire involved the total of 32722 adults, out of which 65.4% were females, and 34.6% males (table 1). Table 1 Main demographic characteristics of the participants and distribution of FINDRISC variables     Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000      Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Table 1 Main demographic characteristics of the participants and distribution of FINDRISC variables     Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000      Country       Overall  Italy  Spain  P value   Number of participants, n (%)  32 722  23 991 (73.3)  8731 (26.7)    Number of questionnaires per year, n (%)    0.000      2014  8283 (25.3)  5885 (24.5)  2398 (27.5)        2015  24439 (74.7)  18106 (75.5)  6333 (72.5)    Gender, n (%)        0.021      Male  11 330 (34.6)  8395 (35.0)  2935 (34.6)        Female  21 392 (65.4)  15 596 (65.0)  5796 (65.4)    Education level, n (%)        0.000      Uneducated  768 (2.3)  224 (0.9)  544 (6.2)        Elementary school  5465 (16.7)  2645 (11.0)  2820 (32.3)        High school  8692 (26.6)  7092 (29.6)  1600 (18.3)        Bachelor degree  11931 (36.5)  10376 (43.2)  1555 (17.8)        Higher university degrees  5866 (17.9)  3654 (15.2)  2212 (25.3)    Occupation, n (%)        0.000      Employed  15 692 (47.9)  11 339 (47.3)  4353 (49.9)        Unemployed  8141 (24.9)  5924 (24.7)  2217 (25.4)        Retired persons  8889 (27.2)  6728 (28.0)  2161 (24.7)    FINDRISC variables              Age (mean ± SD)  56.5 ± 12.3  56.5 ± 12.1  56.3 ± 12.9  0.155      BMI (kg/m2), mean ± SD  26.1 ± 4.4  25.7 ± 4.2  27.2 ± 4.6  0.0000      WC (cm), mean ± SD  93.7 ± 13.2  93.4 ± 12.8  94.6 ± 14.0  0.0000      Physical activity at least 30 min/d, n (%)  4384 (13.4)  2939 (12.2)  1445 (16.5)  0.0000      Daily consumption of fruits, berries or vegetables (%)  24759 (75.7)  18133 (75.6)  6626 (75.9)  0.566      Hypertension medication (%)  10334 (31.6)  7608 (31.7)  2726 (31.2)  0.399      History of high blood glucose (%)  3031 (9.3)  2185 (9.1)  846 (9.7)  0.108      Family history of diabetes (first degree relatives), (%)  9700 (29.6)  7200 (30.0)  2500 (28.6)  0.001      Family history of diabetes (second degree relatives), (%)  4309 (13.2)  3250 (13.5)  1059 (12.1)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Italians accounted for 73.3% of the participants, while remaining 26.7% were Spanish citizens. The age ranged from 18 to 100 years, while mean age was 56.5 ± 12.3 (mean ± SD), which was not statistically different between two countries (P = 0.155) (table 1). Further details on population characteristics are provided in the table 1. Overall, 7234 (22.1%) subjects were at low risk to develop the disease, while 43.3% were at slightly elevated risk (scores 7–11), 19.3% were at moderate (scores 12–14), 13.9% were at high (scores 15–20) and 1.4% were at very high risk (scores > 20). In the categories with the cut-off FINDRISC ≥15, Spanish participants showed higher level of risk respect to Italians (16.7 vs. 14.7%), which was further confirmed when the age-adjusted prevalence for FINDRISC ≥15 was calculated (10.8 vs. 9.9%, respectively). Analysis of the age categories showed the same trend, where starting from the youngest to the oldest participants, the percentage of risk rose from 3.42% (<45 years) to finally reach its peak in the oldest category (≥65 years) with 25.2% (table 2). Table 2 Distribution of FINDRISC classes: overall, across demographic groups, by FINDRISC variables and other variables of interest FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    Abbreviations: BMI, body mass index; WC, waist circumference. Table 2 Distribution of FINDRISC classes: overall, across demographic groups, by FINDRISC variables and other variables of interest FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    FINDRISC classes, n (%)     <7   7–11  12–14  15–20  >20  Total, n (%)   P value  Overall  7234 (22.1)  14 182 (43.3)  6318 (19.3)  4550 (13.9)  438 (1.4)  32 722 (100)    Country              <0.001      Italy  5320 (22.2)  10 557 (44.0)  4589 (19.1)  3229 (13.5)  296 (1.2)  23 991 (100)        Spain  1914 (21.9)  3625 (41.5)  1729 (19.8)  1321 (15.1)  142 (1.6)  8731 (100)    Gender              0.374      Female  4704 (21.9)  9298 (43.5)  4112 (19.2)  3007 (14.1)  271 (1.3)  21 392 (100)        Male  2530 (22.3)  4884 (43.1)  2206 (19.5)  1543 (13.6)  167 (1.5)  11 330 (100)    Age classes              <0.001      <45  2905 (53.7)  1868 (34.5)  447 (8.3)  185 (3.4)  1 (0.02)  5406 (100)        45–54  2308 (26.7)  3904 (45.2)  1593 (18.4)  780 (9.0)  61 (0.7)  8646 (100)        55–64  1533 (15.9)  4352 (45.1)  2068 (21.4)  1580 (16.4)  109 (1.1)  9642 (100)        ≥65  488 (5.4)  4058 (44.9)  2210 (24.5)  2005 (22.2)  267 (2.96)  9028 (100)    FINDRISC variables                    BMI (kg/m2), mean ± SD  22.7 ± 2.6  25.8 ± 3.7  27.9 ± 4.3  29.6 ± 4.5  31.5 ± 4.1  32 723 (100)  <0.001      WC (cm), mean ± SD  82.3 ± 9.7  93.7 ± 12.9  82.3 ± 0.1  103.2 ± 11.9  107.5 ± 11.0  32 723 (100)  <0.001      Physical activity at least 30 min/d, n (%)  371 (8.5)  650 (14.8)  1497 (34.1)  1849 (42.2)  17 (0.4)  4384 (100)  <0.001      Daily consumption of fruits, berries or vegetables, n (%)  5700 (23.0)  10 997 (44.4)  4659 (18.8)  3129 (12.6)  274 (1.1)  24 759 (100)  <0.001      Hypertension medication, n (%)  445 (4.3)  3863 (37.4)  2661 (25.8)  2980 (28.8)  385 (3.7)  10 334 (100)  <0.001      History of high blood glucose, n (%)  19 (0.6)  355 (11.7)  631 (20.8)  1612 (53.2)  414 (13.7)  3031 (100)  <0.001      Family history of diabetes (first degree relatives), n (%)  241 (2.5)  2543 (26.2)  3265 (33.7)  3249 (33.5)  402 (4.1)  9700 (100)  <0.001      Family history of diabetes (second degree relatives), n (%)  864 (20.0)  1969 (45.7)  931 (21.6)  517 (12.0)  29 (0.7)  4310 (100)  <0.001  Other variables of interest                    Smoking, n (%)              <0.001          Yes  1652 (25.9)  2775 (43.5)  1126 (17.7)  758 (11.9)  63 (1.0)  6374 (100)            No  5582 (21.2)  11408 (43.3)  5192 (19.7)  3792 (14.4)  375 (1.4)  26 349 (100)        Total cholesterol levels, mean ± SD  203.1 ± 39.7  208.5 ± 40.3  207.1 ± 39.8  205.4 ± 40.5  201.4 ± 39.4  32 723 (100)  <0.001      Blood pressure, (mean ± SD)                          Diastolic  74.9 ± 10.2  78.2 ± 10.5  79.2 ± 10.4  80.1 ± 10.9  80.0 ± 11.0  32 723 (100)  <0.001          Systolic  120.4 ± 15.6  128.5 ± 16.9  131.4 ± 16.7  134.6 ± 17.7  137.2 ± 17.9  32 723 (100)  <0.001      Education, n (%)              <0.001          Uneducated/elementary school  583 (9.3)  2622 (42.1)  1461 (23.4)  1394 (22.4)  173 (2.8)  6233 (100)            High school  1773 (19.9)  3892 (44.0)  1772 (20.4)  1257 (14.5)  101 (1.2)  8692 (100)            University degree  4918 (27.6)  7732 (43.4)  3085 (17.3)  1899 (10.7)  164 (0.9)  17 798 (100)        Occupation, n (%)              <0.001          Employed  4787 (30.5)  6626 (42.2)  2590 (16.5)  1581 (10.1)  109 (0.7)  15 693 (100)            Unemployed  1665 (20.4)  3468 (42.6)  1646 (20.2)  1251 (15.4)  111 (1.4)  8141 (100)            Retired  801 (9.0)  4089 (46.0)  2063 (23.2)  1718 (19.3)  218 (2.4)  8889 (100)    Abbreviations: BMI, body mass index; WC, waist circumference. Findings from table 3 speak in favor of women as generally healthier than men. They had lower BMI values (−1.4 kg/m2, P < 0.001), practiced more balanced diet (+8.8%, P < 0.001), and were less treated for hypertension (−5.7%, P < 0.001). In addition, men showed higher percentage for history of high blood glucose (9.9 vs. 8.9%, P < 0.001). On the other hand, men were more physically active (+7.8%, P < 0.001). All variables taken into account for FINDRISC calculations differed statistically between countries (P < 0.001), except for, age, daily consumption of fruits and vegetables, previous hypertension treatment, and history of high blood glucose (table 1). To delineate, Italians compared with Spanish people had lower BMI (−1.5 kg/m2, P < 0.001), and WC (−1.2 cm, P < 0.001). Table 3 Distribution of FINDRISC variables across gender and age groups FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Table 3 Distribution of FINDRISC variables across gender and age groups FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  FINDRISC variables  Gender     Age groups       Women  Men  P value  ≤45  46–54  55–64  ≥65   P value  Age, (mean ± SD)  56.6 ± 12.1  56.3 ± 12.7  0.0228  37.6 ± 6.0  49.6 ± 2.9  59.4 ± 2.9  71.2 ± 5.4  0.000  BMI (kg/m2), mean ± SD  25.6 ± 4.6  27.0 ± 3.8  0.0000  25.3 ± 4.5  25.9 ± 4.5  26.2 ± 4.4  26.7 ± 4.1  0.000  WC (cm), mean ± SD  90.8 ± 13.0  99.2 ± 11.6  0.0000  89.8 ± 13.6  92.5 ± 12.9  94.1 ± 12.8  96.9 ± 12.8  0.000  Physical activity at least 30 min/d, n (%)  2284 (10.7)  2100 (18.5)  0.000  931 (17.2)  1353 (15.6)  1234 (12.8)  866 (9.6)  0.000  Daily consumption of fruits, berries or vegetables (%)  16835 (78.7)  7924 (69.9)  0.000  3347 (61.9)  6313 (73.0)  7707 (79.9)  7392 (81.9)  0.000  Hypertension medication (%)  6339 (29.6)  3995 (35.3)  0.000  462 (8.5)  1733 (20.0)  3201 (33.2)  4938 (54.7)  0.000  History of high blood glucose (%)  1903 (8.9)  1128 (10.0)  0.002  411 (7.6)  703 (8.1)  899 (9.3)  1018 (11.3)  0.000  Family history of diabetes (first degree relatives), (%)  6637 (31.0)  3063 (27.0)  0.000  1403 (25.9)  2857 (33.0)  3013 (31.2)  2427 (26.9)  0.000  Family history of diabetes (second degree relatives), (%)  3069 (14.3)  1240 (10.9)  0.000  1328 (24.6)  1295 (15.0)  1034 (10.7)  652 (7.2)  0.000  Abbreviations: BMI, body mass index; WC, waist circumference. Discussion To the best of our knowledge, this is the first study reporting the results of the initial T2DM risk assessment carried out in a big network of community pharmacies in Italy and Spain. Within the ‘Ci sta a cuore il tuo cuore’ initiative a large sample was collected in the period 2014–15, out of which 4988 people (15.3%) from the study population are at high or very high risk to develop diabetes in the next 10 years, which is in accordance with the risk range of 9.6–qw45% shown in studies conducted in other countries that used the same cut-off point of FINDRISC (≥15).26–28 This wide range mirrors different probabilities to develop T2DM between populations due to their variability in genetic characteristics, dietary patterns or age distribution. Spanish participants were more represented in ‘high’ and ‘very high’ risk group respect to Italians (16.7 vs. 14.7%; P < 0.001). Few previously published papers in the two countries of interest used the FINDRISC tool in examining the T2DM risk and our results are in accordance with their findings. Nevertheless, studies from Italy were performed on remarkably smaller samples and only at provincial level.29,30 Bonaccorsi et al analysed 658 persons aged 35–70 years (mean age: men 54 years, women 53 years) and found that 16.7% were at high risk, while 4.9% were at very high risk.29 On the other hand, our study that involved very large sample, collected through all the Italian regions, may mirror more appropriately the risk for T2DM in Italy. With regard to Spain, one study reported T2DM risk using the FINDRISC questionnaire.28 In the sample of 4222 pharmacy users who were older than 18 years (mean age 55.3 years), Fornos-Perez et al found that 20.9% were at high risk, while 2.6% was at very high risk. Findings from this article are in accordance with what has been published in other European studies conducted in populations demographically similar to ours, which used the same cut-off for FINDRISC. One study on FINDRISC conducted in Norway in the population aged ≥20 years had similar mean age (women 52.2 ± 16.2 years, men 53.0 ± 15.6),31 and the reported risk to develop T2DM in the following 10 years was 11% for high and very high-risk categories. Similarly, a group of American authors assessed the participants comparable to ours (mean age of 47.6 ± 17.8 years), and the risk for the categories with FINDRISC ≥ 15 was reported to be 17%20. The FINDRISC was rising as the age increased, which was also confirmed by the dichotomization of FINDRISC with the cut-off of 15 points. The risk was growing steadily starting from the youngest age class (<45: 3.42%), through middle age categories (45–54 years: 9.7%, and 55–64: 17.5%, respectively), to the oldest persons (≥65: 25.2%). These results are in accordance with some previously published studies.28,31 When considering sex differences, the analysis of the risk factors for the onset of T2DM indicate that men were more susceptible to develop this disease. They were also more diagnosed respect to women. These findings are consistent for the two countries, as well as with the literature evidence.31–35 Nevertheless, the analysis across FINDRISC categories did not show any significant difference between men and women (table 2). A possible explanation of the lack of differences in gender-specific FINDRISC, as previously suggested by Jolle et al.,31 may be a potentially poorer recall regarding family history of diabetes among men respect to women, therefore causing a recall bias and reducing the overall FINDRISC in men.36 Previous findings using the FINDRISC tool are conflicting.10,31,37 A slightly higher FINDRISC in women respect to men was noted in two studies,10,31 while one recently published Spanish paper reported no significant difference between women and men in mean FINDRISCs (11.4 vs. 11.2, P = 0.2).37 When interpreting the results of this study, some limitations need to be discussed as follows. The lower representation of men, as well as of Spanish people in the study sample might have limited the analysis. This can be justified because women usually enter the pharmacies at their own initiative to get an advice, to buy medications for family members, or some natural products and cosmetics. Furthermore, women are believed to have a lower employment rate which allows them a frequent access to the pharmacies also during the weekly working time. The differences in age distribution within the study sample and the general population can be explained similarly. The older persons usually have plenty of free time, and are also more susceptible to the polypharmacy, which requires more frequent contacts with the pharmacies respect to the younger population. In order to overcome this limit, the age-adjusted prevalence for persons at increased risk to develop the disease has been calculated. Regarding the lower participation rate of Spanish customers, it is likely due to the greater number of pharmacies within the ‘Apoteca Natura’ network in Italy respect to Spain. Lack of information on response rates leaves open the question of the ability of community pharmacies to reach a significant proportion of the population for the analysis of campaign effectiveness. Considerable strength of this study is the choice of community setting as initiative site, which allowed reaching the specific population of apparently healthy persons. Moreover, taking into account the differences between these kinds of participants respect to the hospital subjects who can be studied more easily, collecting the sample with great number of subjects from the pharmacies rendered this article even more relevant. Sample size of 32 722 well-characterized subjects, enabled calculating the estimates across sex, age and other demographic groups. Additionally, FINDRISC questionnaires were guided and filled in with help of trained pharmacists, limiting the risk of inaccuracy and enhancing the quality and reliability of the collected data. Taking into account that a large number of apparently healthy subjects from our sample was conversely at elevated risk for T2DM, our study might suggest pharmacy as an important public health site for developing and implementing future preventive strategies. Acknowledgements The authors would like to acknowledge the’ Apoteca Natura’ network, in particular Mr Massimo Mercati, Mrs Alessia Scarpocchi, Mrs Maria del Pilar Garcia del Gado, and Mr Roberto Zizza for ideating the campaign ‘Ci sta a cuore il tuo cuore’, developing the tools and materials and providing all the necessary support for the realization of the initiative. Additionally, a high valuable scientific contribution was made by SIMG (Italian General Medicine Society), ADI (Association of Italian diabetologists) and FOFI (Italian Federation of Pharmacists) in the validation of tools and materials of the initiative ‘Ci sta a cuore il tuo cuore’. Finally, a special thanks goes to the the ‘Apoteca Natura’ pharmacists for their serious and constant commitment in carrying on this important project and their efforts to spread this community-pharmacy based health promotion initiative. Funding The authors would like to acknowledge ‘Apoteca Natura’ for the unconditional grant provided for this study to the Università Cattolica del Sacro Cuore. Conflicts of interest: None declared. Key points More than 15% of ‘health’ pharmacy customers evaluated by the FINDRISC questionnaire are at high risk to develop T2DM in the next 10 years. Community pharmacies may represent a great opportunity to strengthen primary prevention at local level since they are often the first point for addressing the health problems for the majority of the population. Specifically designed health promotion interventions with active involvement of the pharmacists as health care team members might be an important future public health strategy. Further studies with an adequate follow-up period can be helpful in evaluating the efficacy of this kind of health promotion campaign. References 1 International Diabetes Federation. IDF Diabetes Atlas 5th edn. Media, 2011. Available from: https://www.idf.org/e-library/epidemiology-research/diabetes-atlas.html (13 March 2017, date last accessed). 2 Lindström J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care  2003; 26: 725– 31. Google Scholar CrossRef Search ADS PubMed  3 Stern MP, Williams K, Haffner SM. Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med  2002; 136: 575. Google Scholar CrossRef Search ADS PubMed  4 Griffin SJ, Little PS, Hales CN, et al.   Diabetes risk score: towards earlier detection of type 2 diabetes in general practice. Diabetes Metab Res Rev  2000; 16: 164– 71. Google Scholar CrossRef Search ADS PubMed  5 Colagiuri S, Hussain Z, Zimmet P, et al.   Screening for type 2 diabetes and impaired glucose metabolism: the Australian experience. Diabetes Care  2004; 27: 367– 71. Google Scholar CrossRef Search ADS PubMed  6 Kanaya AM, Wassel Fyr CL, de Rekeneire N, et al.   Predicting the development of diabetes in older adults: the derivation and validation of a prediction rule. Diabetes Care  2005; 28: 404– 8. Google Scholar CrossRef Search ADS PubMed  7 Heikes KE, Eddy DM, Arondekar B, Schlessinger L. Diabetes Risk Calculator A simple tool for detecting undiagnosed diabetes and pre-diabetes. Diabetes Care  2008; 31: 1040– 5. Google Scholar CrossRef Search ADS PubMed  8 Ruige JB, Neeling J. N D d, Kostense PJ, et al.   Performance of an NIDDM screening questionnaire based on symptoms and risk factors. Diabetes Care  1997; 20: 491– 6. Google Scholar CrossRef Search ADS PubMed  9 Balkau B, Lange C, Fezeu L, et al.   Predicting diabetes: clinical, biological, and genetic approaches. Diabetes Care  2008; 31: 2056– 61. Google Scholar CrossRef Search ADS PubMed  10 Saaristo T, Peltonen M, Lindström J, et al.   Cross-sectional evaluation of the Finnish Diabetes Risk Score: a tool to identify undetected type 2 diabetes, abnormal glucose tolerance and metabolic syndrome. Diabetes Vasc Dis Res  2005; 2: 67– 72. Google Scholar CrossRef Search ADS   11 Abduelkarem AR, Sharif SI, Hammrouni AM, et al.   Risk calculation of developing type 2 diabetes in Libyan adults. Pract Diabetes Int  2009; 26: 148– 51. Google Scholar CrossRef Search ADS   12 Mohieldein AH, Alzohairy M, Hasan M. Risk Estimation of Type 2 Diabetes and Dietary Habits among Adult Saudi Non-diabetics in Central Saudi Arabia. Glob J Health Sci  2011; 3: 123– 33. Google Scholar CrossRef Search ADS   13 Hjellset VT, Bjørge B, Eriksen HR, Høstmark AT. Risk factors for type 2 diabetes among female Pakistani immigrants: the InvaDiab-DEPLAN study on Pakistani immigrant women living in Oslo, Norway. J Immigr Minor Health  2011; 13: 101– 10. Google Scholar CrossRef Search ADS PubMed  14 García-Alcalá H, Nathalie C, Genestier-Tamborero, et al.   Frequency of diabetes, impaired fasting glucose, and glucose intolerance in high-risk groups identified by a FINDRISC survey in Puebla city, Mexico. Diabetes. Metab Syndr Obes Targets Ther  2012; 5: 403– 6. Google Scholar CrossRef Search ADS   15 Naranjo A a, Rodríguez ÁY, Llera RE, et al.   Diabetes risk in a Cuban primary care setting in persons with no known glucose abnormalities. MEDICC Rev  2013; 15: 16– 9. Google Scholar CrossRef Search ADS PubMed  16 Winkler G, Hídvégi T, Vándorfi G, et al.   Prevalence of undiagnosed abnormal glucose tolerance in adult patients cared for by general practitioners in Hungary. Results of a risk-stratified screening based on FINDRISC questionnaire. Med Sci Monit  2013; 19: 67– 72. Google Scholar CrossRef Search ADS PubMed  17 Vermunt PWA, Milder IEJ, Wielaard F, et al.   Lifestyle counseling for type 2 diabetes risk reduction in dutch primary care: results of the APHRODITE study after 0.5 and 1.5 years. Diabetes Care  2011; 34: 1919– 25. Google Scholar CrossRef Search ADS PubMed  18 Paulweber B, Valensi P, Lindstrom J, et al.   A European evidence-based guideline for the prevention of type 2 diabetes. Horm Metab Res  2010; 42(Suppl 1): S3– 36. Google Scholar CrossRef Search ADS PubMed  19 Schwarz PEH, Li J, Reimann M, et al.   The Finnish Diabetes Risk Score is associated with insulin resistance and progression towards type 2 diabetes. J Clin Endocrinol Metab  2009; 94: 920– 6. Google Scholar CrossRef Search ADS PubMed  20 Zhang L, Zhang Z, Zhang Y, et al.   Evaluation of Finnish diabetes risk score in screening undiagnosed diabetes and prediabetes among U.S. adults by gender and race: nHANES 1999-2010. PLoS One  2014; 9: e97865., Google Scholar CrossRef Search ADS   21 Saaristo T, Moilanen L, Jokelainen J, et al.   Cardiometabolic profile of people screened for high risk of type 2 diabetes in a national diabetes prevention programme (FIN-D2D). Prim Care Diabetes  2010; 4: 231– 9. Google Scholar CrossRef Search ADS PubMed  22 O’Loughlin J, Masson P, Déry V, Fagnan D. The role of community pharmacists in health education and disease prevention: a survey of their interests and needs in relation to cardiovascular disease. Prev Med (Baltim)  1999; 28: 324– 31. Google Scholar CrossRef Search ADS   23 the World Health Organization (WHO). The Role of the Pharmacist in the Health Care System. 1994. Available from: http://apps.who.int/medicinedocs/en/d/Jh2995e/ (13 March 2017, date last accessed). 24 Laliberté M, Perreault S, Damestoy N, Lalonde L. Ideal and actual involvement of community pharmacists in health promotion and prevention: a cross-sectional study in Quebec, Canada. BMC Public Health  2012; 12: 192. Google Scholar CrossRef Search ADS PubMed  25 Eurostat. Eurostat population by age group, sex and NUTS2 region [Internet]. Available at: http://appsso.eurostat.ec.europa.eu/nui/show.do? dataset=demo_r_pjangroup&lang=en (01 September 2017, date last accessed). 26 Hellgren MI, Petzold M, Björkelund C, et al.   Feasibility of the FINDRISC questionnaire to identify individuals with impaired glucose tolerance in Swedish primary care. A cross-sectional population-based study. Diabet Med  2012; 29: 1501– 5. Google Scholar CrossRef Search ADS PubMed  27 Makrilakis K, Liatis S, Grammatikou S, et al.   Validation of the Finnish diabetes risk score (FINDRISC) questionnaire for screening for undiagnosed type 2 diabetes, dysglycaemia and the metabolic syndrome in Greece. Diabetes Metab  2011; 37: 144– 51. Google Scholar CrossRef Search ADS PubMed  28 Fornos-Pérez JA, Andrés-Rodríguez NF, Andrés-Iglesias JC, et al.   Detection of people at risk of diabetes in community pharmacies of Pontevedra (Spain) (DEDIPO). Endocrinol Nutr  2016; 63: 387– 96. Google Scholar CrossRef Search ADS PubMed  29 Bonaccorsi G, Guarducci S, Ruffoli E, Lorini C. Diabetes screening in primary care: the PRE.DI.CO. study. Ann Ig  2012; 24: 527– 34. Google Scholar PubMed  30 Noto D, Cefalu AB, Barbagallo CM, et al.   Prediction of incident type 2 diabetes mellitus based on a twenty-year follow-up of the Ventimiglia heart study. Acta Diabetol  2012; 49: 145– 51. Google Scholar CrossRef Search ADS PubMed  31 Jølle A, Midthjell K, Holmen J, et al.   Impact of sex and age on the performance of FINDRISC: the HUNT Study in Norway. BMJ open diabetes Res care  2016; 4: e000217. Google Scholar CrossRef Search ADS PubMed  32 Sociietà Italiana di Diabetologia. Il diabete in Italia. 2016. 33 Wändell PE, Carlsson AC. Gender differences and time trends in incidence and prevalence of type 2 diabetes in Sweden-A model explaining the diabetes epidemic worldwide today?. Diabetes Res Clin Pract  2014; 106: e90– 2. Google Scholar CrossRef Search ADS PubMed  34 Danaei G, Finucane MM, Lu Y, et al.   National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2-7 million participants. Lancet  2011; 378: 31– 40. Google Scholar CrossRef Search ADS PubMed  35 International Diabetes Federation [Internet]. IDF Diabates Atlas, 7th edition. 2015 [cited 2017 Jan 1]. Available at: http://www.diabetesatlas.org/across-the-globe.html (25 November 2016, date last accessed). 36 Fuentes A, Desrocher M. The effects of gender on the retrieval of episodic and semantic components of autobiographical memory. Memory  2013; 21: 619– 32. Google Scholar CrossRef Search ADS PubMed  37 Salinero-Fort MA, Burgos-Lunar C, Lahoz C, et al.   Performance of the finnish diabetes risk score and a simplified finnish diabetes risk score in a community-based, cross-sectional programme for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in Madrid, Spain: the SPREDIA-2 study. PLoS One  2016; 11: e0158489– 17. 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.

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Published: Feb 2, 2018

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