Association between body mass index and health-related quality of life, and the impact of self-reported long-term conditions – cross-sectional study from the south Yorkshire cohort dataset

BMC Public Health, Oct 2013

Background We sought to quantify the relationship between body mass index (BMI) and health-related quality (HRQoL) of life, as measured by the EQ-5D, whilst controlling for potential confounders. In addition, we hypothesised that certain long-term conditions (LTCs), for which being overweight or obese is a known risk factor, may mediate the association between BMI and HRQoL. Hence the aim of our study was to explore the association between BMI and HRQoL, first controlling for confounders and then exploring the potential impact of LTCs. Methods We used baseline data from the South Yorkshire Cohort, a cross-sectional observational study which uses a cohort multiple randomised controlled trial design. For each EQ-5D health dimension we used logistic regression to model the probability of responding as having a problem for each of the five health dimensions. All continuous variables were modelled using fractional polynomials. We examined the impact on the coefficients for BMI of removing LTCs from our model. We considered the self-reported LTCs: diabetes, heart disease, stroke, cancer, osteoarthritis, breathing problems and high blood pressure. Results The dataset used in our analysis had data for 19,460 individuals, who had a mean EQ-5D score of 0.81 and a mean BMI of 26.3 kg/m2. For each dimension, BMI and all of the LTCs were significant predictors. For overweight or obese individuals (BMI ≥ 25 kg/m2), each unit increase in BMI was associated with approximately a 3% increase in the odds of reporting a problem for the anxiety/depression dimension, a 8% increase for the mobility dimension, and approximately 6% for the remaining dimension s. Diabetes, heart disease, osteoarthritis and high blood pressure were identified as being potentially mediating variables for all of the dimensions. Conclusions Compared to those of a normal weight (18.5 < BMI < 25 kg/m2), overweight and obese individuals had a reduced HRQoL, with each unit increase in BMI associated with approximately a 6% increase in the odds of reporting a problem on any of the EQ-5D health dimensions. There was evidence to suggest that diabetes, heart disease, osteoarthritis and high blood pressure may mediate the association between being overweight and HRQoL.

A PDF file should load here. If you do not see its contents the file may be temporarily unavailable at the journal website or you do not have a PDF plug-in installed and enabled in your browser.

Alternatively, you can download the file locally and open with any standalone PDF reader:

http://www.biomedcentral.com/content/pdf/1471-2458-13-1009.pdf

Association between body mass index and health-related quality of life, and the impact of self-reported long-term conditions – cross-sectional study from the south Yorkshire cohort dataset

BMC Public Health Association between body mass index and health-related quality of life, and the impact of self-reported long-term conditions - cross-sectional study from the south Yorkshire cohort dataset Benjamin Kearns 0 Roberta Ara 0 Tracey Young 0 Clare Relton 0 0 School of Health and Related Research, University of Sheffield , Sheffield , UK Background: We sought to quantify the relationship between body mass index (BMI) and health-related quality (HRQoL) of life, as measured by the EQ-5D, whilst controlling for potential confounders. In addition, we hypothesised that certain long-term conditions (LTCs), for which being overweight or obese is a known risk factor, may mediate the association between BMI and HRQoL. Hence the aim of our study was to explore the association between BMI and HRQoL, first controlling for confounders and then exploring the potential impact of LTCs. Methods: We used baseline data from the South Yorkshire Cohort, a cross-sectional observational study which uses a cohort multiple randomised controlled trial design. For each EQ-5D health dimension we used logistic regression to model the probability of responding as having a problem for each of the five health dimensions. All continuous variables were modelled using fractional polynomials. We examined the impact on the coefficients for BMI of removing LTCs from our model. We considered the self-reported LTCs: diabetes, heart disease, stroke, cancer, osteoarthritis, breathing problems and high blood pressure. Results: The dataset used in our analysis had data for 19,460 individuals, who had a mean EQ-5D score of 0.81 and a mean BMI of 26.3 kg/m2. For each dimension, BMI and all of the LTCs were significant predictors. For overweight or obese individuals (BMI 25 kg/m2), each unit increase in BMI was associated with approximately a 3% increase in the odds of reporting a problem for the anxiety/depression dimension, a 8% increase for the mobility dimension, and approximately 6% for the remaining dimension s. Diabetes, heart disease, osteoarthritis and high blood pressure were identified as being potentially mediating variables for all of the dimensions. Conclusions: Compared to those of a normal weight (18.5 < BMI < 25 kg/m2), overweight and obese individuals had a reduced HRQoL, with each unit increase in BMI associated with approximately a 6% increase in the odds of reporting a problem on any of the EQ-5D health dimensions. There was evidence to suggest that diabetes, heart disease, osteoarthritis and high blood pressure may mediate the association between being overweight and HRQoL. Obesity; Overweight; Underweight; EQ-5D; Co-morbidities; Regression analysis; Confounding; Mediating - Background For adults, body mass index (BMI [kg/m2]) is recommended as a way of classifying their weight as being either underweight (BMI < 18.5), healthy weight (BMI 18.5 to 24.9), overweight (BMI 25 to 29.9) or obese (BMI > 29.9) [1]. Deviations away from the healthy weight range are associated with a lower health-related quality of life (HRQoL) [2-4]. Of the non-healthy weights, the effects of being overweight or obese have received the most attention in the literature, with reports that their prevalence has reached epidemic levels in many countries [5,6]. Being overweight or obese is a major risk factor for many diseases including diabetes, hypertension, coronary heart disease, cancer and stroke [7-9]. There are also substantial cost implications for society; for example it is estimated that in 2007 the economic costs of overweight and obesity were 16 billion in England alone [10], with direct costs to the National Health Service of 3.2 billion [11]. The association between BMI and HRQoL is potentially confounded by the complex biological and social frameworks that cause deviations away from healthy weight [12]. Age, gender, ethnicity, deprivation, education and lifestyle choices such as smoking and activity levels are all potential confounders or mediators that have been explored in the literature [13-15]. The South Yorkshire Cohort (SYC) study [16], is a large observational study which uses a cohort multiple randomised controlled trial design [17]. It collects data on a range of socio-demographics, socio-economics, comorbidities, health resource use and HRQoL and provides an opportunity to study the impact of a wide range of factors that may confound or mediate any assessments of the association between BMI and HRQoL. For our study we hypothesised that socio-demographic and social-economic variables may confound the association between BMI and HRQoL, whilst certain comorbidities (those for which unhealthy weight is a known risk factor) may mediate the association between BMI and HRQoL (that is, being overweight causes the long-term condition, which in turn causes a reduction in HRQoL). Hence the aim of our study was to use the baseline results from the SYC to explore the association between BMI and HRQoL, first controlling for confou (...truncated)


This is a preview of a remote PDF: http://www.biomedcentral.com/content/pdf/1471-2458-13-1009.pdf

Benjamin Kearns, Roberta Ara, Tracey Young, Clare Relton. Association between body mass index and health-related quality of life, and the impact of self-reported long-term conditions – cross-sectional study from the south Yorkshire cohort dataset, BMC Public Health, 2013, pp. 1009, 13, DOI: 10.1186/1471-2458-13-1009