The association between obesity, health service use, and work productivity in Australia: a cross-sectional quantile regression analysis.

The burden of disease attributable to obesity is rapidly increasing and becoming a public health challenge globally. Using a nationally representative sample in Australia, this study aims to examine the association of obesity with healthcare service use and work productivity across outcome distributions. We used Household, Income and Labour Dynamics Australia (HILDA) Wave 17 (2017-2018), including 11,211 participants aged between 20 and 65 years. Two-part models using multivariable logistic regressions and quantile regressions were employed to understand variations in the association between obesity levels and the outcomes. The prevalence of overweight and obesity was 35.0% and 27.6%, respectively. After adjusting for socio-demographic factors, low socioeconomic status was associated with a higher probability of overweight and obesity (Obese III: OR = 3.79; 95% CI 2.53-5.68) while high education group was associated with a lower likelihood of being high level of obesity (Obese III OR = 0.42, 95% CI 0.29-0.59). Higher levels of obesity were associated with higher probability of health service use (GP visit Obese, III: OR = 1.42 95% CI 1.04-1.93,) and work productivity loss (number of paid sick leave days, Obese III: OR = 2.40 95% CI 1.94-2.96), compared with normal weight. The impacts of obesity on health service use and work productivity were larger for those with higher percentiles compared to lower percentiles. Overweight and obesity are associated with greater healthcare utilisation, and loss in work productivity in Australia. Australia's healthcare system should prioritise interventions to prevent overweight and obesity to reduce the cost on individuals and improve labour market outcomes.

The Joint Effect of Physical Multimorbidity and Mental Health Conditions Among Adults in Australia.

INTRODUCTION: The prevalence of chronic physical and mental health conditions is rising globally. Little evidence exists on the joint effect of physical and mental health conditions on health care use, work productivity, and health-related quality of life in Australia. METHODS: We analyzed data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, waves 9 (2009), 13 (2013), and 17 (2017). Economic effects associated with multimorbidity were measured through health service use, work productivity loss, and health-related quality of life. We used generalized estimating equations to assess the effect of the association between physical multimorbidity and mental health conditions and economic outcomes. RESULTS: From 2009 through 2017 the prevalence of physical multimorbidity increased from 15.1% to 16.2%, and the prevalence of mental health conditions increased from 11.2% to 17.3%. The number of physical health conditions was associated with the number of health services used (general practitioner visits, incidence rate ratio = 1.41), work productivity loss (labor force participation, adjusted odds ratio = 0.71), and reduced health-related quality of life (SF-6D score: Coefficient = -0.03). These effects were exacerbated by the presence of mental health conditions and low socioeconomic status. CONCLUSION: Having multiple physical health conditions (physical multimorbidity) creates substantial health and financial burdens on individuals, the health system, and society, including increased use of health services, loss of work productivity, and decreased health-related quality of life. The adverse effects of multimorbidity on health, quality of life, and economic well-being are exacerbated by the co-occurrence of mental health conditions and low socioeconomic status.