Abstract

BackgroundHigh adiposity is associated with higher risks for a variety of adverse health outcomes, including higher rates of age-adjusted mortality and increased morbidity. This has important implications for the management of healthcare systems, since the endocrinal, cardiometabolic and other changes associated with increased adiposity may be associated with substantial healthcare costs.MethodsWe studied the association between various measures of adiposity and inpatient hospital costs through record linkage between UK Biobank and records of inpatient care in England and Wales. UK Biobank is a large prospective cohort study that aimed to recruit men and women aged between 40 and 69 from 2006 to 2010. We applied generalised linear models to cost per person year to estimate the marginal effect of adiposity, and average adjusted predicted costs of adiposity.ResultsValid cost and body mass index (BMI) data from 457,689 participants were available for inferential analysis. Some 54.4% of individuals included in the analysis sample had positive inpatient healthcare costs over the period of follow-up. Median hospital costs per person-year of follow-up were £89, compared to mean costs of £481. Mean BMI overall was 27.4 kg/m2 (standard deviation 4.8). The marginal effect of a unit increase in BMI was £13.61 (99% confidence interval £12.60–£14.63) per person-year of follow up. The marginal effect of a standard deviation increase in BMI was £69.20 (99% confidence interval £64.98–£73.42). The marginal effect of becoming obese was £136.35 (99% confidence interval £124.62–£148.08). Average adjusted predicted inpatient hospital costs increased almost linearly when modelled using continuous measure of adiposity. Sensitivity analysis of different scenarios did not substantially change these conclusions, although there was some evidence of attenuation of the effects of adiposity when controlling for waist-hip ratios, and when individuals who self-reported any pre-existing conditions were excluded from analysis.ConclusionsHigher adiposity is associated with higher inpatient hospital costs. Further scrutiny using causal inferential methods is warranted to establish if further public health investments are required to manage the large healthcare costs observationally associated with overweight and obesity.Electronic supplementary materialThe online version of this article (10.1007/s40258-018-0450-2) contains supplementary material, which is available to authorized users.

Highlights

  • Body mass index (BMI)—weight divided by the square of standing height—is a widely used indicator of nutritional status, adiposity and overall health [1,2,3,4,5,6,7]

  • Average adjusted predicted costs were calculated for the entire analysis sample, for the samples defined in sensitivity analyses, and at representative ages stratified by sex

  • Following exclusion of data as described above, records from up to 457,689 participants were available for the inferential analysis (Fig. 1), of whom 54.4% at baseline were female (Table 1)

Read more

Summary

Introduction

Body mass index (BMI)—weight divided by the square of standing height—is a widely used indicator of nutritional status, adiposity and overall health [1,2,3,4,5,6,7]. The underlying aetiology between BMI and health is complex [9], but robust associations have been found between higher BMI and risks for a variety of adverse health and social outcomes, including higher rates of age-adjusted mortality [10], increased morbidity [6, 11] and poor labour market outcomes [12] This has important implications for the management of healthcare systems [13], since the endocrinal [14], cardiometabolic [15, 16] and other changes [13] associated with increased adiposity are associated with substantial healthcare resource requirements [17]. Further scrutiny using causal inferential methods is warranted to establish if further public health investments are required to manage the large healthcare costs observationally associated with overweight and obesity

Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call