The relationship between body mass index and hospitalisation rates, days in hospital and costs: findings from a large prospective linked data study

Rosemary J Korda; Grace Joshy; Ellie Paige; James R G Butler; Louisa R Jorm; Bette Liu; Adrian E Bauman; Emily Banks

doi:10.1371/journal.pone.0118599

The relationship between body mass index and hospitalisation rates, days in hospital and costs: findings from a large prospective linked data study

PLoS One. 2015 Mar 4;10(3):e0118599. doi: 10.1371/journal.pone.0118599. eCollection 2015.

Authors

Rosemary J Korda¹, Grace Joshy¹, Ellie Paige¹, James R G Butler², Louisa R Jorm³, Bette Liu⁴, Adrian E Bauman⁵, Emily Banks⁶

Affiliations

¹ National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia.
² Australian Centre for Economic Research on Health, The Australian National University, Canberra, Australian Capital Territory, Australia.
³ Centre for Health Research, The University of Western Sydney, Sydney, New South Wales, Australia.
⁴ School of Public Health and Community Medicine, The University of New South Wales, Sydney, New South Wales, Australia; The Sax Institute, Sydney, New South Wales, Australia.
⁵ School of Public Health, The University of Sydney, Sydney, New South Wales, Australia.
⁶ National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia; The Sax Institute, Sydney, New South Wales, Australia.

Abstract

Background: Internationally there is limited empirical evidence on the impact of overweight and obesity on health service use and costs. We estimate the burden of hospitalisation-admissions, days and costs-associated with above-normal BMI.

Methods: Population-based prospective cohort study involving 224,254 adults aged ≥45y in Australia (45 and Up Study). Baseline questionnaire data (2006-2009) were linked to hospitalisation and death records (median follow-up 3.42y) and hospital cost data. The relationships between BMI and hospital admissions and days were modelled using zero-inflated negative binomial regression; generalised gamma models were used to model costs. Analyses were stratified by sex and age (45-64, 65-79, ≥80y), and adjusted for age, area of residence, education, income, smoking, alcohol-intake and private health insurance status. Population attributable fractions were also calculated.

Results: There were 459,346 admissions (0.55/person-year) and 1,483,523 hospital days (1.76/person-year) during follow-up. For ages 45-64y and 65-79y, rates of admissions, days and costs increased progressively with increments of above-normal BMI. Compared to BMI 22.5-<25kg/m2, rates of admissions and days were 1.64-2.54 times higher for BMI 40-50kg/m2; costs were 1.14-1.24 times higher for BMI 27.5-<30kg/m2, rising to 1.77-2.15 times for BMI 40-50kg/m2. The BMI-hospitalisation relationship was less clear for ≥80y. We estimated that among Australians 45-79y, around 1 in every 8 admissions are attributable to overweight and obesity (2% to overweight, 11% to obesity), as are 1 in every 6 days in hospital (2%, 16%) and 1 in every 6 dollars spent on hospitalisation (3%, 14%).

Conclusions: The dose-response relationship between BMI and hospital use and costs in mid-age and older Australians in the above-normal BMI range suggests even small downward shifts in BMI among these people could result in considerable reductions in their annual health care costs; whether this would result in long-term savings to the health care system is not known from this study.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Aged, 80 and over
Body Mass Index*
Female
Humans
Length of Stay / economics*
Male
Middle Aged
Models, Statistical
Patient Admission / statistics & numerical data
Prospective Studies
Surveys and Questionnaires

Grants and funding

This work was supported by a grant from the Australian National Health and Medical Research Council [Grant No. 585402]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.