Australian Health Review Australian Health Review Society
Journal of the Australian Healthcare & Hospitals Association
RESEARCH ARTICLE

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: michelle.trevenen@uwa.edu.au

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 - http://dx.doi.org/10.1071/AH16171
Submitted: 1 August 2016  Accepted: 11 December 2016   Published online: 23 February 2017

Abstract

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.


References

[1]  Chang S-H, Pollack LM, Colditz GA. Life years lost associated with obesity-related diseases for U.S. non-smoking adults. PLoS One 2013; 8 e66550
Life years lost associated with obesity-related diseases for U.S. non-smoking adults.CrossRef | 1:CAS:528:DC%2BC3sXhtVGqt7rL&md5=de87093e65af2b2f745112301992ebfeCAS | open url image1

[2]  Sugerman HJ. The epidemic of severe obesity: the value of surgical treatment. Mayo Clin Proc 2000; 75 669–72.
The epidemic of severe obesity: the value of surgical treatment.CrossRef | 1:STN:280:DC%2BD3czovVagsA%3D%3D&md5=912f3c8bf5a6ce31d3d964773e6f63f0CAS | open url image1

[3]  Zizza C, Herring A, Stevens J, Popkin B. Length of hospital stays among obese individuals. Am J Public Health 2004; 94 1587–91.
Length of hospital stays among obese individuals.CrossRef | open url image1

[4]  Obesity Australia. No time to weight. 2015. Available at: http://obesityaustralia.cipcms.com.au/resources-general-public/no-time-to-weight-2 [verified 10 January 2017].

[5]  Organisation for Economic Co-Operation and Development (OECD). OECD health statistics 2015: key indicators. 2015. Available at: http://www.oecd.org/health/health-systems/OECD-Health-Statistics-2015-Frequently-Requested-Data.xls?bcsi_scan_c221d61a0ea4ff4c=1 [verified 10 January 2017].

[6]  Australian Bureau of Statistics. 4364.0.55.001 – Australian health survey: first results, 2014–15. 2015. Available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4364.0.55.0012014-15?OpenDocument [verified 10 January 2017].

[7]  Australian Bureau of Statistics. 4364.0.55.001 – Australian health survey: first results, 2011–12. 2012. Available at: http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/4364.0.55.001Chapter1002011-12 [verified 10 January 2017].

[8]  Australian Bureau of Statistics. 4364.0.55.003 – Australian health survey: updated results, 2011–2012. 2013. Available at: http://www.abs.gov.au/ausstats/abs@.nsf/lookup/33C64022ABB5ECD5CA257B8200179437?opendocument [verified 10 January 2017].

[9]  Australian Government Department of Health. How overweight and obesity are defined. 2009 Available at: http://www.health.gov.au/internet/main/Publishing.nsf/Content/health-pubhlth-strateg-hlthwt-obesity.htm#defined [verified 10 January 2017].

[10]  Bloomfield R, Steel E, MacLennan G, Noble D. Accuracy of weight and height estimation in an intensive care unit: implications for clinical practice and research. Crit Care Med 2006; 34 2153–7.
Accuracy of weight and height estimation in an intensive care unit: implications for clinical practice and research.CrossRef | open url image1

[11]  Leary TS, Milner QJ, Niblett DJ. The accuracy of the estimation of body weight and height in the intensive care unit. Eur J Anaesthesiol 2000; 17 698–703.
The accuracy of the estimation of body weight and height in the intensive care unit.CrossRef | 1:STN:280:DC%2BD3M%2FmtVGrsA%3D%3D&md5=7d2a2e9b2ff32496981c65efcf85eae1CAS | open url image1

[12]  Rice S. Retrofitting hospitals for obese patients. Hospitals balance safety, costs in equipping facilities for bariatric care. Mod Healthc 2014; 44 16–7. open url image1

[13]  Muir M, Archer-Heese G. Essentials of a bariatric patient handling program. Online J Issues Nurs 2009; 14 Manuscript 5 open url image1

[14]  Blackett A, Gallagher S, Dugan S, Gates JL, Henn T, Kennedy-Evans KL, Lutz JH. Caring for persons with bariatric health care issues: a primer for the WOC nurse. J Wound Ostomy Continence Nurs 2011; 38 133–8.
Caring for persons with bariatric health care issues: a primer for the WOC nurse.CrossRef | open url image1

[15]  Curtis JP, Selter JG, Wang Y, Rathore SS, Jovin IS, Jadbabaie F, Kosiborod M, Portnay EL, Sokol SI, Bader F, Krumholz HM. The obesity paradox: body mass index and outcomes in patients with heart failure. Arch Intern Med 2005; 165 55–61.
The obesity paradox: body mass index and outcomes in patients with heart failure.CrossRef | open url image1

[16]  Engel A, McDonough S, Smith JM. Does an obese body mass index affect hospital outcomes after coronary artery bypass graft surgery? Ann Thorac Surg 2009; 88 1793–800.
Does an obese body mass index affect hospital outcomes after coronary artery bypass graft surgery?CrossRef | open url image1

[17]  Fleischmann E, Teal N, Dudley J, May W, Bower JD, Salahuden AK. Influence of excess weight on mortality and hospital stay in 1346 hemodialysis patients. Kidney Int 1999; 55 1560–7.
Influence of excess weight on mortality and hospital stay in 1346 hemodialysis patients.CrossRef | 1:STN:280:DyaK1M3hslSrsg%3D%3D&md5=48007be7c76345c32a55319e7ef9fc09CAS | open url image1

[18]  Gong MN, Bajwa EK, Thompson BT, Christiani DC. Body mass index is associated with the development of acute respiratory distress syndrome. Thorax 2010; 65 44–50.
Body mass index is associated with the development of acute respiratory distress syndrome.CrossRef | 1:STN:280:DC%2BD1Mfjsl2qtg%3D%3D&md5=6ec755dfa2670fa2902bae13ed99917aCAS | open url image1

[19]  Maradit Kremers H, Visscher S, Kremers W, Naessens J, Lewallen D. Obesity increases length of stay and direct medical costs in total hip arthroplasty. Clin Orthop Relat Res 2014; 472 1232–9.
Obesity increases length of stay and direct medical costs in total hip arthroplasty.CrossRef | open url image1

[20]  Vemmos K, Ntaios G, Spengos K, Savvari P, Vemmou A, Pappa T, Manios E, Georgiopoulos G, Alevizaki M. Association between obesity and mortality after acute first-ever stroke: the obesity–stroke paradox. Stroke 2011; 42 30–6.
Association between obesity and mortality after acute first-ever stroke: the obesity–stroke paradox.CrossRef | open url image1

[21]  Zittermann A, Becker T, Gummert JF, Börgermann J. Body mass index, cardiac surgery and clinical outcome. A single-center experience with 9125 patients. Nutr Metab Cardiovasc Dis 2014; 24 168–75.
Body mass index, cardiac surgery and clinical outcome. A single-center experience with 9125 patients.CrossRef | 1:STN:280:DC%2BC2c%2FksVeltw%3D%3D&md5=d86ea12f1b2ce11955e132eb67fa8840CAS | open url image1

[22]  Hauck K, Hollingsworth B. The impact of severe obesity on hospital length of stay. Med Care 2010; 48 335–40.
The impact of severe obesity on hospital length of stay.CrossRef | open url image1

[23]  Anzueto A, Frutos Vivar F, Esteban A, Bensalami N, Marks D, Raymondos K, Apezteguia C, Arabi Y, Hurtado J, Gonzalez M, Tomicic V, Abroug F, Elizalde J, Cakar N, Pelosi P, Ferguson ND, for the Ventila 366 Group. Influence of body mass index on outcome of the mechanically ventilated patients. Thorax 2011; 66 66–73.
Influence of body mass index on outcome of the mechanically ventilated patients.CrossRef | 1:STN:280:DC%2BC3M%2FmvF2itw%3D%3D&md5=c1af730d8aa41f141404f045af31a989CAS | open url image1

[24]  Australian Bureau of Statistics. 2033.0.55.001 – Census of population and housing: socio-economic indexes for areas (SEIFA), Australia. 2014. Available at: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2033.0.55.0012011?OpenDocument [verified 10 January 2017].

[25]  Health Department of Western Australia. Sir Charles Gairdner Hospital services directory for general practitioners. 2016. Available at: http://www.scgh.health.wa.gov.au/Clinicians/pdf/SCGH_Clinical_Services_Directory.pdf [verified 10 January 2017].

[26]  Nestle Nutrition Institute. Nutritional screening as easy as MNA. 2009. Available at: http://www.mna-elderly.com/forms/mna_guide_english.pdf [verified 10 January 2017].

[27]  Dennis D, Hunt E, Budgeon C. Measuring height in recumbent critical care patients. Am J Crit Care 2015; 24 41–7.
Measuring height in recumbent critical care patients.CrossRef | open url image1

[28]  Garrouste-Orgeas M, Troché G, Azoulay E, Caubel A, de Lassence A, Cheval C, Montesino L, Thuong M, Vincent F, Cohen Y, Timsit J-F. Body mass index. An additional prognostic factor in ICU patients. Intensive Care Med 2004; 30 437–43.
Body mass index. An additional prognostic factor in ICU patients.CrossRef | open url image1

[29]  Rafe B. Obesity and the longevity myth. Summit preview. 2015. Available at: http://www.actuaries.digital/2015/05/12/obesity-and-the-longevity-myth-summit-preview/ [verified 10 January 2017].



Export Citation