BMI and Cause‐Specific Hospital Admissions and Costs: The UK Biobank Cohort Study

Abstract

Objective: To estimate the effect of BMI on cause-specific hospital admissions and costs in men and women is not well understood, and this study's aim is to address this. Methods: For 451,320 men and women aged 40 years or older recruited into the UK Biobank, followed up for 6 years on average, this study estimated annual rates and costs (at 2016 UK prices) of hospital admissions, overall and by diagnostic category (using International Classification of Diseases, Tenth Revision chapters), in relation to BMI. Results: Among those who were never smokers, a 2-kg/m 2 higher BMI (above 20 kg/m 2) was associated with a 6.2% (99% CI: 5.3% to 7.2%) higher admission rate and an 8.6% (99% CI: 7.3% to 10.0%) higher annual cost in men and with a 5.7% (99% CI: 4.9% to 6.6%) higher admission rate and an 8.4% (99% CI: 7.5% to 9.3%) higher annual cost in women. Higher BMI was associated with higher admission rates and costs for many types of health conditions, particularly for endocrine, skin, and musculoskeletal disorders in both men and women and for circulatory diseases in men. Conclusions: BMI beyond healthy weight is strongly associated with higher annual rates of hospital admission and higher costs in both men and women across a wide range of health conditions.

Mendelian Randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission

“…We show the causal role of higher BMI and WHR in increasing the risk of hospital admission, using a large high-quality dataset. While a positive association of BMI and hospital admissions has previously been shown [15,47], this is the first time hospital admissions have been modeled using MR methods – the MR framework allowing us to obtain estimates of causal effects less sensitive to confounding and bias problems present in traditional epidemiological studies [23,24]. Our results further emphasize the necessity of increasing efforts towards the development of policies to combat the global rise in adiposity.…”

“…A positive association of BMI and all-cause hospital admissions has previously been shown in observational studies investigating populations from the UK (Kent, Green, et al, 2017; O’Halloran, 2020), Australia (Korda et al, 2015), Canada (Chen et al, 2007), Italy (Migliore et al, 2013), and the USA (Buys et al, 2014; Han et al, 2009). An observational study of approximately 1.09 million UK women found a yearly hospital admission rate increase of 1.12 (95% CI: 1.12, 1.13) for every 5kg/m 2 increase in BMI (Reeves et al, 2014).…”

“…In just over 300,000 individuals, we observed estimates amounting to rate coefficients of 1.02 5 = 1.08 (95% CI: 1.07, 1.10), 1.14 (95% CI: 1.02, 1.28) and 1.10 (95% CI: 1.01, 1.21) from the multivariable observational, one-sample MR and two-sample MR analyses, respectively, giving effect estimates of a magnitude comparable to those observed previously in UK women. Another multivariable study, examining the association between BMI and hospital admissions in 451,320 UK Biobank participants, found increases in yearly hospital admission rates, measured per 2kg/m 2 BMI, of 1.06 (95% CI: 1.05, 1.07) and 1.06 (95% CI: 1.05, 1.07) for male and female never-smokers, respectively [47]. We observed comparable estimates, with increases across both genders, per 2kg/m 2 BMI, of 1.02 2 =1.03 (95% CI: 1.03, 1.04), 1.05 (95% CI: 1.01, 1.11), and 1.04 (95% CI: 1.00, 1.08), for the multivariable observational, one-sample MR and two-sample MR analyses, respectively.…”

Mendelian randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission

“…A positive association of BMI and all-cause hospital admissions was reported in observational studies investigating populations from the UK ( Kent et al, 2017b , O'Halloran et al, 2020 ), Australia ( Korda et al, 2015 ), Canada ( Chen et al, 2007 ), Italy ( Migliore et al, 2013 ), and the USA ( Buys et al, 2014 , Han et al, 2009 ). An observational study of approximately 1·09 million UK women found a yearly hospital admission rate increase of 1·12 (95% CI: 1·12, 1·13) for every 5 kg/m 2 increase in BMI ( Reeves et al, 2014 ).…”

“…Individuals with higher adiposity, as indexed by measures such as body mass index (BMI) and waist hip ratio (WHR), attend hospital more frequently than others ( Buys et al, 2014 , Chen et al, 2007 , Han et al, 2009 , Korda et al, 2015 , Migliore et al, 2013 , O'Halloran et al, 2020 , Reeves et al, 2014 ). Establishing the causal impact of adiposity on hospital admissions is an important step in understanding the impacts of adverse weight profiles on the health system.…”