Do acute hospitalised patients in Australia have a different body mass index to the general Australian population: a point prevalence study?Diane M. Dennis A D E , Vicki Carter A , Michelle Trevenen B C , Jacinta Tyler A , Luisa Perrella A , Erika Lori A and Ian Cooper A D
A Physiotherapy Department, Sir Charles Gairdner Hospital, Hospital Avenue, Nedlands, WA 6009, Australia. Email: Vicki.Carter2@health.wa.gov.au; Jacintainman@gmail.com; Luisa.Perrella@health.wa.gov.au; Erika.Lori@health.wa.gov.au; Ian.Cooper@health.wa.gov.au
B University of Western Australia, Centre for Applied Statistics, 35 Stirling Highway, Crawley, WA 6009, Australia. Email: email@example.com
C Department of Research, Sir Charles Gairdner Hospital, Hospital Avenue, Nedlands, WA 6009, Australia.
D Curtin University, School of Physiotherapy and Exercise Science, Kent Street, Bentley, WA 6102, Australia.
E Corresponding author. Email: Diane.Dennis@health.wa.gov.au
Australian Health Review - https://doi.org/10.1071/AH16171
Submitted: 1 August 2016 Accepted: 11 December 2016 Published online: 23 February 2017
Objective The aim of the present study was to provide a current snapshot of the body mass index (BMI) of the entire patient cohort of an Australian tertiary hospital on one day and compare these data with current published Australian and state (Western Australia) population norms.
Methods A single-centre prospective point prevalence study was performed whereby BMI was calculated following actual measurement of patient weight (nurse) and height (physiotherapist) on one day during 2015. Variables were summarised descriptively, and one-way analysis of variance was used to investigate the relationship between continuous BMI and hospital speciality. Multivariate Cox proportional hazards regression was used to analyse the time to leaving hospital, where those who died were censored at their date of death.
Results Data were collected from 416 patients (96% of the hospital population on that day). The mean (± s.e.m.) BMI across the whole hospital population was 26.6 ± 2.2 kg m–2, with 37% of patients having normal BMI, 8% being underweight, 32% being overweight, 19% being obese and 4% being severely obese. Comparison with both national and state population norms for 2014–15 reflected higher proportions of the hospital population in the underweight and extremely obese categories, and lower proportions in the overweight and obese categories. There was no significant difference in BMI across medical specialties.
Conclusions Despite health warnings about the direct relationship between illness and being overweight or obese, the results of the present study reveal fewer hospitalised patients in these BMI categories and more underweight patients than in the non-hospitalised general Australian population. Being overweight or obese may offer some protection against hospitalisation, but there is a point where the deleterious effect of obesity results in more extremely obese individuals being hospitalised than the proportion represented in the general population.
What is known about the topic? Although there is significant current published data relating to general Australian population BMI, there is little pertaining specifically to the hospitalised population. Accordingly, although we know that as an affluent Western country we are seeing growing rates of overweight and obese people and relatively few underweight or undernourished people in the general population, we do not know whether these trends are mirrored or magnified in those who are sick in hospital. We also know that although caring for obese patients carries a significant burden, there is the suggestion in some healthcare literature of an ‘obesity paradox’, whereby in certain disease states being overweight actually decreases mortality and promotes a faster recovery from illness compared with underweight people, who have poorer outcomes.
What does this paper add? This paper is the first of its kind to actually measure and calculate the BMI of a whole tertiary Australian hospital population and provide some comparison with published Australian norms. On average, the hospital cohort was overweight, with a mean (± s.e.m.) BMI of 26.6 ± 2.2 kg m–2, but less so than the general population, which had a mean BMI of 27.5 ± 0.2 kg m–2. The results also indicate that compared with state and national norms, underweight and extremely obese patients were over-represented in the hospitalised cohort, whereas overweight or obese patients were under-represented.
What are the implications for practitioners? Although only a single-centre study, the case-mix and socioeconomic catchment area of the hospital evaluated in the present study suggest that it is a typical tertiary urban West Australian facility and, as such, there may be some implications for practitioners. Primarily, administrators need to ensure that we are able to accommodate people of increasing weight in our hospital facilities and have the resources with which to do so, because, on average, hospitalised patients were overweight. In addition, resources need to be available for managing the extremely obese if numbers in this subset of the population increase. Finally, practitioners may also need to consider that although the management of underweight and undernourished patients may be less of a physical burden, there are actually more of these patients in hospital compared with the general population, and they may require a different package of resource utilisation.
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