title: Impact of diabetes on hospital admission and length of stay among a general population aged 45 year or more: a record linkage study.
abstract: BACKGROUND
  The increased prevalence of diabetes and its significant impact on use of health care services, particularly hospitals, is a concern for health planners. This paper explores the risk factors for all-cause hospitalisation and the excess risk due to diabetes in a large sample of older Australians.
  
  
  METHODS
  The study population was 263,482 participants in the 45 and Up Study. The data assessed were linked records of hospital admissions in the 12 months following completion of a baseline questionnaire. All cause and ambulatory care sensitive admission rates and length of stay were examined. The associations between demographic characteristics, socioeconomic status, lifestyle factors, and health and wellbeing and risk of hospitalisation were explored using zero inflated Poisson (ZIP) regression models adjusting for age and gender. The ratios of adjusted relative rates and 95% confidence intervals were calculated to determine the excess risk due to diabetes.
  
  
  RESULTS
  Prevalence of diabetes was 9.0% (n = 23,779). Age adjusted admission rates for all-cause hospitalisation were 631.3 and 454.8 per 1,000 participant years and the mean length of stay was 8.2 and 7.1 days respectively for participants with and without diabetes. In people with and without diabetes, the risk of hospitalisation was associated with age, gender, household income, smoking, BMI, physical activity, and health and wellbeing. However, the increased risk of hospitalisation was attenuated for participants with diabetes who were older, obese, or had hypertension or hyperlipidaemia and enhanced for those participants with diabetes who were male, on low income, current smokers or who had anxiety or depression.
  
  
  CONCLUSIONS
  This study is one of the few studies published to explore the impact of diabetes on hospitalisation in a large non-clinical population, the 45 and Up Study. The attenuation of risk associated with some factors is likely to be due to correlation between diabetes and factors such as age and obesity. The increased risk in association with other factors such as gender and low income in participants with diabetes is likely to be due to their synergistic influence on health status and the way services are accessed.
authors.affiliation: Centre for Primary Health Care and Equity, University of New South Wales, Sydney, NSW, 2052, Australia. E.Comino@unsw.edu.au.
authors.forename: Elizabeth Jean
authors.initials: EJ
authors.lastname: Comino
authors.affiliation: Centre for Primary Health Care and Equity, University of New South Wales, Sydney, NSW, 2052, Australia. M.F.Harris@unsw.edu.au.
authors.forename: Mark Fort
authors.initials: MF
authors.lastname: Harris
authors.affiliation: Centre for Primary Health Care and Equity, University of New South Wales, Sydney, NSW, 2052, Australia. f.islam@unsw.edu.au.
authors.forename: M D Fakhrul
authors.initials: MD
authors.lastname: Islam
authors.affiliation: Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, 2052, Australia. Danielle.Tran@unsw.edu.au.
authors.forename: Duong Thuy
authors.initials: DT
authors.lastname: Tran
authors.affiliation: Centre for Research, Evidence Management and Surveillance, Sydney and South Western Sydney Local Health Districts, Locked Bag 7017, Liverpool, NSW, 1871, Australia. bin.jalaludin@sswahs.nsw.gov.au.|School of Public Health and Community Medicine, University of New South Wales, Sydney, 2052, Australia. bin.jalaludin@sswahs.nsw.gov.au.
authors.forename: Bin
authors.initials: B
authors.lastname: Jalaludin
authors.affiliation: Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, 2052, Australia. L.Jorm@uws.edu.au.|Centre for Health Research, School of Medicine, University of Western Sydney, Locked Bag 1797, Penrith, NSW, 2751, Australia. L.Jorm@uws.edu.au.
authors.forename: Louisa
authors.initials: L
authors.lastname: Jorm
authors.affiliation: Bankstown-Lidcombe Hospital, Eldridge Road, Bankstown, NSW, 2200, Australia. Jeff.Flack@sswahs.nsw.gov.au.
authors.forename: Jeff
authors.initials: J
authors.lastname: Flack
authors.affiliation: Centre for Health Economics Research and Evaluation, Faculty of Business, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Level 4, 645 Harris Street, Ultimo, NSW, 2007, Australia. Marion.Haas@chere.uts.edu.au.
authors.forename: Marion
authors.initials: M
authors.lastname: Haas
mesh_terms: D000368:Aged; D003863:Depression / Q000453:epidemiology; D003922:Diabetes Mellitus, Type 1 / Q000150:complications* / Q000453:epidemiology; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000453:epidemiology; D004812:Epidemiologic Methods; D005260:Female; D006304:Health Status; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D009517:New South Wales / Q000453:epidemiology; D009765:Obesity / Q000453:epidemiology; D011203:Poverty / Q000706:statistics & numerical data; D012907:Smoking / Q000453:epidemiology; D012959:Socioeconomic Factors