TY - JOUR
AB - Abstract Background The aim of the study was to measure the effect of colder winters compared to warmer winters on hospital admission rates in Suffolk County. Methods The setting of this study was Suffolk County in eastern England. The period of the study was financial years 2003/04–2012/13. The study was an analytic ecological study. Analysis involved calculation of rate ratios of hospital admission rates in colder winters compared to warmer winters, in all persons and the elderly. Results The main finding of the study was that all rate ratios for hospital admission rates in colder winters compared to warmer winters were significantly raised with effects of 2–5%. Rate ratios for all admissions in persons of all ages and persons aged 65 years and over were, respectively, 1.02 (99% confidence interval (CI): 1.01, 1.03; P < 0.001) and 1.02 (99% CI: 1.01, 1.04; P < 0.001). Rate ratios for emergency admissions in persons of all ages and persons aged 65 years and over were, respectively, 1.05 (99% CI: 1.03, 1.06; P < 0.001) and 1.04 (99% CI: 1.01, 1.06; P < 0.001). Conclusion In Suffolk County, hospital admission rates are significantly raised in colder winters compared to warmer winters. This evidence may be useful in planning hospital services. climate, hospital admissions, rates, temperature, winter Introduction Weather, including variations in temperature, is an important environmental factor affecting human health. Seasonal variations in temperature are well-known to be correlated with health outcomes, including incidence of various diseases and mortality from such causes as cardiovascular diseases, respiratory diseases and accidents.1,2 Epidemiological research into effects of weather and temperature on health has focused mainly on effects on mortality.3 Studies of effects of high temperatures and heat waves have been more frequent than studies of cold-weather effects. Where cold-weather effects have been studied, research has been wide-ranging, focusing on countries or groups of cities.4–7 Much research has involved development of statistical models to investigate short-term temporal effects, including time lags between temperature extremes and health outcomes, and harvesting.6,8,9 Local studies of effects of ambient temperatures on hospital activity are less common, particularly the effect of cold temperatures.10 Generally, these studies have investigated associations between temperature and cause-specific hospital admissions, including admissions for cardiovascular diseases and respiratory diseases. Some of these studies are complex and, for cardiovascular diseases, they have produced varying results.9,11–13 Studies in the UK have identified winter excesses in hospital admissions for respiratory diseases, a cause of hospital admission for which evidence of the harmful effect of cold weather is more clear-cut.14–16 UK studies have also identified winter excesses in hospital admissions for asthma, falls, certain types of road accidents, atrial fibrillation, heart failure, pulmonary embolism, stroke and intensive care.17–24 Also, influenza epidemics, and high levels of hospital admissions for this cause, typically occur in winter.25,26 A study analysing daily numbers of emergency admissions in a 15-year period in England reported a 0.78% increase (95% confidence interval (CI): 0.53%, 1.04%) in emergency admissions for every 1°C drop in temperature below identified cold-weather thresholds.27 Recently, the NHS has come under strain as demand for in-patient care has increased and many hospitals are struggling to cope.28 Hence, any predictor of increased demand for in-patient care would be welcomed by NHS clinicians, managers and policy makers. This paper describes a county-wide study to investigate the association between variations in winter temperature and hospital admission rates for all causes over a 10-year period. More specifically, the study investigates the association between variations in temperatures in colder and warmer winters and rates of all admissions and emergency admissions in all persons and the elderly. The study was originally commissioned in the Public Health Department of Suffolk County Council in 2014 to provide data to inform the Warm Homes, Healthy People initiative in Suffolk.29 Methods This section describes the setting of the study, calculation of annual and monthly hospital admission rates and mean temperatures in Suffolk and statistical analysis in the study. Setting The setting of this study is Suffolk County. Suffolk is a largely rural county in eastern England. In 2013, the estimated population of Suffolk was 734 466 persons of all ages. Three main acute hospitals in Ipswich and Bury St. Edmunds and in Great Yarmouth in the neighbouring county of Norfolk serve the population of Suffolk, and patients from Suffolk are also treated in other regional centres, including hospitals in Cambridge, Colchester and Norwich. The climate of eastern England, including Suffolk, is generally mild, with moderate rainfall and infrequent extremes of temperature. Mean annual temperatures range between 9°C and 10.5°C.30 January and February are the coldest months. Mean daily maximum temperatures range from 5°C to 8°C in winter months to 19–22.5°C in summer. Average numbers of days of air frost per year range from 30 to 55 days. The warming effect of the sea can delay the start of the frost season at coastal sites. On average, December is the month with least sunshine and July is the sunniest month. Rainfall is generally low, and eastern England is one of the more sheltered, less windy parts of the UK. Hospital admission rates Data relating to hospital activity among residents of Suffolk County in financial years 2003/04–2012/13 were downloaded from NHS Digital’s Hospital Episode Statistics Data Interrogation System.31 Annual and monthly hospital admission rates for Suffolk in 2003/04–2012/13, directly standardized for age and sex, were calculated for all admissions and emergency admissions for all causes in males, females and persons of all ages and aged 65 years and over.32 The directly standardized hospital admission rates were standardized to the 2013 European Standard Population.33 For the calculation of monthly hospital admission rates, estimates of monthly person-time at risk, by age and sex, were calculated by dividing Office for National Statistics mid-year population estimates for Suffolk in calendar years 2003–13 by the number of days in the year and multiplying by the number of days in each month. The monthly person-time at risk estimates were grouped to the financial years in the study period. Temperature estimates Monthly temperature readings for the weather station at Lowestoft in Suffolk were downloaded from the Met Office website.34 From this data set, temperature readings for the months in the study period were extracted. These temperature readings included maximum and minimum monthly temperatures. Mean monthly temperatures were calculated as: (Maximumtemperature+Minimumtemperature)/2 Temperature readings were not available for the following months in the period: August 2003, August 2006, September 2006 and August 2007. These months were excluded from the analysis. Readings for October 2009, March 2010 and November 2010-March 2013 were estimated readings. The estimated readings were interpolated from a UK climate model.35 Winter was defined as the period December–March. This is the definition of winter used in the Excess Winter Deaths Atlas.36 Colder winters in Lowestoft were defined as those winters for which the mean monthly temperature in December–March was <5°C. Other studies have specified <5°C as a threshold for measuring cold-weather effects.7,37 Hajat et al. specified a threshold of 4°C for measuring the effect of cold weather on mortality in East of England, and temperatures of 4–5°C are considered to be reasonable thresholds for measuring cold-weather health impacts in the UK.27 (Personal communication from Dr Hajat). Statistical analysis Hospital admission rates were calculated in Microsoft Excel 2010. Further statistical analysis, including calculation of monthly mean temperatures, Pearson correlation coefficients and modelled rate ratios of hospital admission rates in colder and warmer winters, was performed in Stata 13.38 Statistical significance was measured at the 1% level to allow for multiple testing. Results This section describes hospital admission rates in Suffolk during the study period, seasonal patterns in hospital admission rates, mean annual and winter temperatures during the period, correlations of monthly hospital admission rates with monthly temperatures throughout the year and in winter, and the effect of colder winters on hospital admission rates as measured by rate ratios of admission rates in colder winters compared to warmer winters. Numbers and rates of hospital admissions In financial years 2003/04–2012/13, there were 1 690 335 hospital admissions for all causes among persons of all ages in Suffolk County, including 676 527 admissions among persons aged 65 years and over. During this period there were 596 444 emergency admissions for all causes among persons of all ages in Suffolk County, including 274 012 emergency admissions among persons aged 65 years and over. Figure 1 shows annual age-sex standardized hospital admission rates for all causes in residents of Suffolk County in financial years 2003/04–2012/13. Rates are shown for all admissions and emergency admissions in persons of all ages and persons aged 65 years and over. Fig. 1 View largeDownload slide Annual age-sex standardized hospital admission rates. Hospital admissions for all causes. Residents of Suffolk County. Financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. Fig. 1 View largeDownload slide Annual age-sex standardized hospital admission rates. Hospital admissions for all causes. Residents of Suffolk County. Financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. During the period, annual age-sex standardized hospital admission rates for all causes in Suffolk generally increased: All admissions, all ages: by 15.0% between 2003/04 and 2012/13. All admissions, age 65 years and over: 18.2%. Emergency admissions, all ages: 8.6%. Emergency admissions, age 65 years and over: 9.9%. Figure 2 shows mean monthly age-sex standardized hospital admission rates for all causes in residents of Suffolk County in financial years 2003/04–2012/13. Rates are shown for all admissions and emergency admissions in persons of all ages and persons aged 65 years and over. Fig. 2 View largeDownload slide Mean monthly hospital admission rates. Hospital admissions for all causes. Residents of Suffolk County. Financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. Fig. 2 View largeDownload slide Mean monthly hospital admission rates. Hospital admissions for all causes. Residents of Suffolk County. Financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. Figure 2 shows that, for trends in all admissions in persons of all ages and persons aged 65 years and over, there were slight peaks in mean monthly hospital admission rates in June and November and decreases in August and December. These decreases may relate to reductions in hospital activity during holiday periods. Between April–November and December–March mean monthly age-sex standardized hospital admission rates for all types of admissions in persons of all ages and persons aged 65 years and over in 2003/04–2012/13 increased by 0.1% and 0.5%, respectively. There was little variation in monthly emergency admission rates in persons of all ages. In persons aged 65 years and over there was a peak in mean monthly emergency admission rates in December: an increase of 6.7% from November, which may be related to the effect of cold weather. Between April–November and December–March mean monthly age-sex standardized emergency admission rates in persons of all ages and persons aged 65 years and over in 2003/04–2012/13 increased by 3.5% and 4.8%, respectively. Temperature readings in Lowestoft Mean annual temperatures in Lowestoft in 2003/04–2012/13 ranged between 9.6°C and 11.4°C. Mean winter temperatures in Lowestoft in 2003/04–2012/13 ranged between 3.7°C and 7.1°C. The following winters in Lowestoft were categorized as colder winters (<5°C): 2005/06, 2008/09, 2009/10, 2010/11 and 2012/13. Correlations of monthly hospital admission rates with monthly mean temperatures Monthly hospital admission rates for all causes in Suffolk were correlated with monthly mean temperatures in Lowestoft to measure associations between these variables. All correlations of variables in the data set were examined in scatterplots (graphs not shown). All correlation coefficients for correlations for all months in the year were negative, indicating that, to a greater or lesser extent, monthly hospital admission rates increased as monthly mean temperatures decreased. For all types of admissions in persons, males and females of all ages and persons, males and females aged 65 years and over, the correlation coefficients ranged between −0.01 and −0.11 but none were statistically significant. For emergency admissions in persons, males and females of all ages and persons, males and females aged 65 years and over, the correlation coefficients for correlations for all months in the year ranged between −0.29 and −0.46 and all were statistically significant (P < 0.01). All correlations for winter months (December–March) were negative, indicating that, to a greater or lesser extent, monthly hospital admission rates increased as monthly mean temperatures in winter decreased. For all types of admissions in persons, males and females of all ages the correlation coefficients ranged between −0.01 and −0.10 but none were statistically significant. For all types of admissions in persons, males and females aged 65 years and over, the correlation coefficients ranged between −0.22 and −0.23 but none were statistically significant. For emergency admissions in persons, males and females of all ages and persons, males and females aged 65 years and over, the correlation coefficients for winter months ranged between −0.33 and −0.41. All were statistically significant at the 5% level of significance but only the correlation coefficient for emergency admissions in persons aged 65 years and over was significant at the 1% level. Calculation of rate ratios The final stage of the analysis involved the calculation in Poisson regression models of rate ratios of age-standardized hospital admission rates in colder winters compared to warmer winters. Four of the five colder winters occurred in the second half of the analysis period, when hospital admission rates were higher compared to the first half. To control for confounding by higher hospital admission rates in the second half of the analysis period, a term for time period was included in the Poisson regression models. Table 1 shows rate ratios of hospital admission rates for all types of admissions. Table 1 Ratios of hospital admission rates in colder winters compared to warmer wintersa Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.02 1.01 1.03 <0.001 27 258.8 26 738.4  Males of all ages 1.02 1.01 1.04 <0.001 27 310.6 26 704.3  Females of all ages 1.02 1.00 1.03 0.001 27 705.3 27 251.3  Persons aged 65+ (age-sex stand. rates) 1.02 1.01 1.04 <0.001 57 986.4 56 834.2  Males aged 65+ 1.02 1.00 1.04 0.007 65 513.3 64 194.1  Females aged 65+ 1.02 1.00 1.04 0.022 50 460.3 49 475.0 Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.02 1.01 1.03 <0.001 27 258.8 26 738.4  Males of all ages 1.02 1.01 1.04 <0.001 27 310.6 26 704.3  Females of all ages 1.02 1.00 1.03 0.001 27 705.3 27 251.3  Persons aged 65+ (age-sex stand. rates) 1.02 1.01 1.04 <0.001 57 986.4 56 834.2  Males aged 65+ 1.02 1.00 1.04 0.007 65 513.3 64 194.1  Females aged 65+ 1.02 1.00 1.04 0.022 50 460.3 49 475.0 Age-standardized hospital admission rates (admissions per 100 000 residents). Hospital admissions of all types for all causes. Residents of Suffolk County. Winter months (December–March) in financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. aColder winters: 2005/06, 2008/09, 2009/10, 2010/11 and 2012/13; Warmer winters: 2003/04, 2004/05, 2006/07, 2007/08 and 2011/12. bRates adjusted for effect of time period: 2003/04–2007/08 versus 2008/09–2012/13. Table 1 Ratios of hospital admission rates in colder winters compared to warmer wintersa Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.02 1.01 1.03 <0.001 27 258.8 26 738.4  Males of all ages 1.02 1.01 1.04 <0.001 27 310.6 26 704.3  Females of all ages 1.02 1.00 1.03 0.001 27 705.3 27 251.3  Persons aged 65+ (age-sex stand. rates) 1.02 1.01 1.04 <0.001 57 986.4 56 834.2  Males aged 65+ 1.02 1.00 1.04 0.007 65 513.3 64 194.1  Females aged 65+ 1.02 1.00 1.04 0.022 50 460.3 49 475.0 Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.02 1.01 1.03 <0.001 27 258.8 26 738.4  Males of all ages 1.02 1.01 1.04 <0.001 27 310.6 26 704.3  Females of all ages 1.02 1.00 1.03 0.001 27 705.3 27 251.3  Persons aged 65+ (age-sex stand. rates) 1.02 1.01 1.04 <0.001 57 986.4 56 834.2  Males aged 65+ 1.02 1.00 1.04 0.007 65 513.3 64 194.1  Females aged 65+ 1.02 1.00 1.04 0.022 50 460.3 49 475.0 Age-standardized hospital admission rates (admissions per 100 000 residents). Hospital admissions of all types for all causes. Residents of Suffolk County. Winter months (December–March) in financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. aColder winters: 2005/06, 2008/09, 2009/10, 2010/11 and 2012/13; Warmer winters: 2003/04, 2004/05, 2006/07, 2007/08 and 2011/12. bRates adjusted for effect of time period: 2003/04–2007/08 versus 2008/09–2012/13. Rate ratios for all types of hospital admissions in colder winters compared to warmer winters in persons, males and females of all ages and persons, males and females aged 65 years and over were all 1.02. All rate ratios for all types of admissions in persons, males and females of all ages and persons aged 65 years and over were statistically significant at the 1% level. The rate ratio for all types of admissions in males aged 65 years and over was borderline significant at the 1% level (95% CI: 1.01, 1.04). The rate ratio for all types of admissions in females aged 65 years and over was borderline significant at the 1% level (95% CI: 1.00, 1.04). Table 2 shows rate ratios of hospital admission rates for emergency admissions in colder winters compared to warmer winters. Table 2 Ratios of hospital admission rates in colder winters compared to warmer wintersa Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.05 1.03 1.06 <0.001 9987.2 9544.3  Males of all ages 1.04 1.02 1.07 <0.001 10 595.8 10 159.1  Females of all ages 1.05 1.03 1.07 <0.001 9411.6 8962.9  Persons aged 65+ (age-sex stand. rates) 1.04 1.01 1.06 <0.001 28 990.6 27 945.9  Males aged 65+ 1.04 1.01 1.08 <0.001 31 693.9 30 398.6  Females aged 65+ 1.03 1.00 1.07 0.021 26 289.0 25 498.5 Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.05 1.03 1.06 <0.001 9987.2 9544.3  Males of all ages 1.04 1.02 1.07 <0.001 10 595.8 10 159.1  Females of all ages 1.05 1.03 1.07 <0.001 9411.6 8962.9  Persons aged 65+ (age-sex stand. rates) 1.04 1.01 1.06 <0.001 28 990.6 27 945.9  Males aged 65+ 1.04 1.01 1.08 <0.001 31 693.9 30 398.6  Females aged 65+ 1.03 1.00 1.07 0.021 26 289.0 25 498.5 Age-standardized hospital admission rates (admissions per 100 000 residents). Emergency admissions for all causes. Residents of Suffolk County. Winter months (December–March) in financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. aColder winters: 2005/06, 2008/09, 2009/10, 2010/11, 2012/13; Warmer winters: 2003/04, 2004/05, 2006/07, 2007/08, 2011/12. bRates adjusted for effect of time period: 2003/04–2007/08 versus 2008/09–2012/13. Table 2 Ratios of hospital admission rates in colder winters compared to warmer wintersa Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.05 1.03 1.06 <0.001 9987.2 9544.3  Males of all ages 1.04 1.02 1.07 <0.001 10 595.8 10 159.1  Females of all ages 1.05 1.03 1.07 <0.001 9411.6 8962.9  Persons aged 65+ (age-sex stand. rates) 1.04 1.01 1.06 <0.001 28 990.6 27 945.9  Males aged 65+ 1.04 1.01 1.08 <0.001 31 693.9 30 398.6  Females aged 65+ 1.03 1.00 1.07 0.021 26 289.0 25 498.5 Rate ratio 99% CI P-value Hospital admission ratesb Lower limit Upper limit Colder winters Warmer winters Sex and age group  Persons of all ages (age-sex stand. rates) 1.05 1.03 1.06 <0.001 9987.2 9544.3  Males of all ages 1.04 1.02 1.07 <0.001 10 595.8 10 159.1  Females of all ages 1.05 1.03 1.07 <0.001 9411.6 8962.9  Persons aged 65+ (age-sex stand. rates) 1.04 1.01 1.06 <0.001 28 990.6 27 945.9  Males aged 65+ 1.04 1.01 1.08 <0.001 31 693.9 30 398.6  Females aged 65+ 1.03 1.00 1.07 0.021 26 289.0 25 498.5 Age-standardized hospital admission rates (admissions per 100 000 residents). Emergency admissions for all causes. Residents of Suffolk County. Winter months (December–March) in financial years 2003/04–2012/13. Persons of all ages and persons aged 65 years and over. aColder winters: 2005/06, 2008/09, 2009/10, 2010/11, 2012/13; Warmer winters: 2003/04, 2004/05, 2006/07, 2007/08, 2011/12. bRates adjusted for effect of time period: 2003/04–2007/08 versus 2008/09–2012/13. Rate ratios for emergency admissions in colder winters compared to warmer winters in persons, males and females of all ages ranged from 1.04 to 1.05. In persons, males and females aged 65 years and over, these rate ratios ranged from 1.03 to 1.04. All rate ratios for emergency admissions except emergency admissions in females aged 65 years and over were statistically significant at the 1% level of significance. The rate ratio for emergency admissions in females aged 65 years and over was borderline significant at the 1% level (95% CI: 1.01, 1.06). Discussion Main findings of the study In Suffolk County during the period, there were statistically significant negative associations between monthly emergency admission rates and monthly mean temperatures, in all months and in winter months and in both persons of all ages and the elderly. In this analysis the correlations were not strong, but generally emergency admission rates increased as mean temperatures decreased. For all admissions, in persons of all ages and in the elderly, the correlations were weak and non-significant. Rate ratios for hospital admission rates in colder winters compared to warmer winters were calculated from pooled data, which increased the power of the study compared to the correlations of monthly data. For all admissions, all rate ratios for colder winters compared to warmer winters were significantly raised with effects of 2%. For emergency admissions, all rate ratios for colder winters compared to warmer winters were significantly raised with effects of 3–5%. These effects were consistent across all categories of hospital admission rates. These effects are relatively small but may have importance for public health.8 What is already known on this topic Most local studies of the effects of cold temperatures on hospital activity have investigated associations between temperature and cause-specific hospital admissions, including admissions for cardiovascular diseases and respiratory diseases. It is known that hospital activity increases in cold weather and winter but the association of hospital activity with variations in winter temperatures is less well-known. What this study adds This paper has described a county-wide study of the association between hospital admission rates and ambient temperatures in colder and warmer winters. It is believed that a study of this kind has not been published before. Some epidemiological temperature studies have suggested the application of their findings to the development of early warning systems to alert agencies of the onset of cold weather and its negative effects on health.11,27,37 Such systems have been developed in recent years.39,40 The findings of this study could contribute to the design of hospital-based early warning systems and cold weather plans that could provide warning of cold winters, say, based on temperature readings in November, and the need to open more wards and beds and increase and strengthen primary and community care facilities. Limitations of this study In this study, the source of the temperature readings was Lowestoft weather station, which is situated in the north-east corner of Suffolk on the North Sea coast. This was the only weather station in Suffolk for which historic temperature data were available on the Met Office website. The use of the temperature data from Lowestoft is possibly a source of measurement error and bias in the study design. It is arguable that temperature readings from an inland weather station in central Suffolk, near Ipswich or Stowmarket, for example, would have been more representative of mean temperatures in Suffolk as a whole. Perhaps, in this analysis, more representative temperature readings for Suffolk would have produced stronger correlations and higher rate ratios for hospital admission rates in colder winters compared to warmer winters. It is possible that air pollution may confound or modify the effect of ambient temperature on hospital admission rates in Suffolk.41 However, the effect of air pollution in Suffolk is unlikely to be substantial. Data for all seven local authority districts in the county produced for the Annual Report of the Director of Public Health for NHS Suffolk in 2010 showed that air pollution only affected the more urbanized districts of Ipswich and St. Edmundsbury to any extent.42 This would be a subject for further research at the local level. Also, confounding by influenza epidemics could be estimated.37 Finally, this study has focused on hospital activity in winter, as defined by the months December–March. Recent research has shown that this may be a limited approach and that a large proportion of cold-related health impacts in the UK occur outside this period.43 Conclusion This paper has described a county-wide study of the association between hospital admission rates and ambient temperatures in colder and warmer winters. It is believed that a study of this kind has not been published before. The main finding of the study is that rate ratios for hospital admission rates were raised by 2–5% in colder winters compared to warmer winters. In each of the categories of hospital admissions studied this effect was statistically significant, and the measures of effect were consistent across all categories of hospital admissions studied. The findings of this study could be useful in winter planning of local health services, including early warning systems and cold weather plans for hospital services and primary and community care. Further research in this area could focus on differentials in cause-specific or specialty-specific hospital admission rates in colder and warmer winters, seasonal variations in hospital admission rates throughout the year, quantification of the effect of colder and warmer winters in terms of numbers of hospital admissions, and the effects of air pollution and influenza epidemics on hospital admission rates in colder and warmer winters. Acknowledgements This study was originally commissioned by Mr Simon Aalders, Lead Engagement Manager (Adults) in the Department of Public Health of Suffolk County Council, to provide data to inform the Warm Homes, Healthy People initiative in Suffolk. Thanks to Dr Padmanabhan Badrinath, Consultant in Public Health Medicine, Suffolk County Council, for his helpful comments and suggestions on earlier versions of the manuscript and for his support and encouragement. Thanks to Mr Graham R.H. Hoare, Senior Sales Executive at the Met Office, for links to weather data on the Met Office website. Thanks to Ms. Antoinette Woodhouse, Public Health Information Specialist at Public Health England Local Knowledge and Intelligence Service East, for help with accessing the Hospital Episode Statistics Data Interrogation System. Thanks to Mrs. Wendy Marsh, Head of Knowledge and Intelligence, and Mrs. Lynn Scannell, Assistant Librarian, Department of Public Health, Suffolk County Council, for literature searches and finding articles for this study. Funding The research for this paper was conducted by the author in the course of his work as an employee of Suffolk County Council. No external funding contributed to this research. References 1 McMichael AJ . Planetary Overload. In: Global Environmental Change and the Health of the Human Species . Cambridge, New York and Melbourne : Cambridge University Press , 1995 . 2 Team for Friends of the Earth . 2011 . The Health Impact of Cold Homes and Fuel Poverty. http://www.instituteofhealthequity.org/projects/the-health-impacts-of-cold-homes-and-fuel-poverty (14 August 2014, date last accessed) Marmot Review. 3 Basu R . High ambient temperature and mortality: a review of epidemiologic studies from 2001 to 2008 . Environ Health 2009 ; 8 ( 40 ): 1 – 13 . 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TI - Do hospital admission rates increase in colder winters? A decadal analysis from an eastern county in England
JO - Journal of Public Health
DO - 10.1093/pubmed/fdx076
DA - 2017-07-05
UR - https://www.deepdyve.com/lp/oxford-university-press/do-hospital-admission-rates-increase-in-colder-winters-a-decadal-oG0baqDjhM
SP - 1
EP - 228
VL - Advance Article
IS - 2
DP - DeepDyve
ER -