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

Clare Relton¹  Tracey Young¹  Roberta Ara¹  Benjamin Kearns¹ 

[1] School of Health and Related Research, University of Sheffield, Sheffield, UK

关键词: Mediating;    Confounding;    Regression analysis;    Co-morbidities;    EQ-5D;    Underweight;    Overweight;    Obesity;   

Others  :  1161613
DOI  :  10.1186/1471-2458-13-1009

 received in 2013-01-28, accepted in 2013-09-25,  发布年份 2013

【 摘 要 】

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.

【 授权许可】

   
2013 Kearns et al.; licensee BioMed Central Ltd.

【 参考文献 】

• [1]World Health Organization: World Health Organization: Global Database on Body Mass Index. 2012. http://www.who.int/bmi webcite
• [2]Sach T, Barton G, Doherty M, Muir K, Jenkinson C, Avery A: The relationship between body mass index and health-related quality of life: comparing the EQ-5D, EuroQol VAS and SF-6D. Int J Obes (Lond) 2006, 31:189-196.
• [3]Soltoft F, Hammer M, Kragh N: The association of body mass index and health-related quality of life in the general population: data from the 2003 health survey of England. Qual Life Res 2009, 18:1293-1299.
• [4]Ara R, Blake L, Gray L, Hernandez M, Crowther M, Dunkley A, et al.: What is the clinical effectiveness and cost-effectiveness of using drugs in treating obese patients in primary care? A systematic review. Health Technol Assess 2012, 16:1-197.
• [5]Blissmer B, Riebe D, Dye G, Ruggiero L, Greene G, Caldwell M: Health-related quality of life following a clinical weight loss intervention among overweight and obese adults: intervention and 24 month follow-up effects. Health Qual Life Outcomes 2006, 4:43.
• [6]Scottish Intercollegiate Guidelines Network: SIGN National Clinical Guideline 115: Management of Obesity. Manage Obes 2010., 115http://www.sign.ac.uk/pdf/sign115.pdf webcite
• [7]Field A, Coakley E, Must A, Spadano J, Laird N, Dietz W, et al.: Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Intern Med 2012, 161:1581-1586.
• [8]Wilson P, D'Agnostino R, Sullivan L, Parise H, Kannel W: Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Arch Intern Med 2002, 162:1867-1872.
• [9]Kopelman P: Health risks associated with overweight and obesity. Obes Rev 2007, 8:S13-S17.
• [10]Department of Health. Healthy Lives, Healthy People: A Call to Action on Obesity in England. 2011. https://www.gov.uk/government/publications/healthy-lives-healthy-people-a-call-to-action-on-obesity-in-england webcite
• [11]Allender S, Rayner M: The burden of overweight and obesity-related ill health in the UK. Obes Rev 2007, 8:467-473.
• [12]Butland B, Jebb S, Kopelman P, McPherson K, Thomas S, Mardell J, et al.: Foresight. Tackling obesities. Future choices 2007. http://www.bis.gov.uk/assets/foresight/docs/obesity/17.pdf webcite
• [13]Jia H, Lubetkin E: The impact of obesity on health-related quality-of-life in the general adult US population. J Public Health 2005, 27:156-164.
• [14]Grandy S, Fox K: EQ-5D visual analog scale and utility index values in individuals with diabetes and at risk for diabetes: findings from the study to help improve early evaluation and management of risk factors leading to diabetes (SHIELD). Health Qual Life Outcomes 2008, 6:18.
• [15]Kinge J, Morris S: Socioeconomic variation in the impact of obesity on health-related quality of life. Soc Sci Med 2010, 1-9.
• [16]Relton C, Bissell P, Smith C, Blackburn J, Cooper C, Nicholl J, et al.: South yorkshire cohort: a ‘cohort trials facility’ study of health and weight - protocol for the recruitment phase. BMC Public Health 2011, 11:640.
• [17]Relton C, Torgerson D, O’Cathain A, Nicholl J: Rethinking pragmatic randomised controlled trials: introducing the “cohort multiple randomised controlled trial” design. Br Med J 2010, 340:963-967.
• [18]National Obesity Observatory. NOO e-Atlas: Adult Obesity, Determinants and Associated Diseases. http://www.noo.org.uk/visualisation/eatlas webcite
• [19]EuroQol. EuroQol. http://www.euroqol.org/ webcite
• [20]Dolan P: Modeling valuations for EuroQol health states. Med Care 1997, 35:1095-1108.
• [21]Department of Health: National standards for ethnic group and related matters. 2012. http://webarchive.nationalarchives.gov.uk/+/www.dh.gov.uk/en/publicationsandstatistics/publications/publicationspolicyandguidance/browsable/dh_5319155 webcite
• [22]HM Government. Index of Multiple Deprivation (IMD) 2007 - Datasets. http://data.gov.uk/dataset/index_of_multiple_deprivation_imd_2007 webcite
• [23]Office for National Statistics: The National Statistics Socio-economic Classification (NS-SEC). http://www.ons.gov.uk/ons/guide-method/classifications/current-standard-classifications/soc2010/soc2010-volume-3-ns-sec--rebased-on-soc2010--user-manual/index.html webcite
• [24]Purshouse R, Meier P, Brennan A, Taylor K, Rafia R: Estimated effect of alcohol pricing policies on health and health economic outcomes in England: an epidemiological model. Lancet 2010, 375:1355-1364.
• [25]National Audit Office: Tackling Obesity in England. http://www.nao.org.uk/report/tackling-obesity-in-england/ webcite
• [26]Royston P, Sauerbrei W: Multivariable model-building: a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables. Chichester: John Wiley & Sons; 2008.
• [27]STATACORP: Stata Statistical Software: Release 10. [10]. TX: StataCorp LP. College Station; 2007.
• [28]Hosmer David W, Stanley L: Applied Logistic Regression. John Wiley & Sons; 2000.
• [29]World Health Organization: GPE Discussion Paper Series: Age Standardization Of Rates: A New Who Standard. http://www.who.int/healthinfo/paper31.pdf webcite
• [30]Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE: Regression methods in biostatistics: linear, logistic, survival, and repeated measures models. New York: Springer; 2011.
• [31]Wee H-L, Cheung Y-B, Loke W-C, Tan C-B, Chow M-H, Li S-C, et al.: The association of body mass index with health-related quality of life:an exploratory study in a multiethnic asian population. Value Health 2008, 11:S105-S114.
• [32]Dixon S, Currie C, McEwan P: Utility values for obesity and preliminary analysis of the health outcomes data repository. Future Drugs 2004, 4(6):657-65.
• [33]Groessl EJ, Kaplan RM, Barrett-Connor E, Ganiats TG: Body mass index and quality of well-being in a community of older adults. Am J Prev Med 2004, 26:126-129.
• [34]Fortin M, Lapointe L, Hudon C, Vanasse A, Ntetu AL, Maltais D: Multimorbidity and quality of life in primary care: a systematic review. Health Qual Life Outcomes 2004, 2:51.
• [35]Alonso J, Ferrer M, Gandek B, Ware JE Jr, Aaronson NK, Mosconi P, et al.: Health-related quality of life associated with chronic conditions in eight countries: results from the international quality of life assessment (IQOLA) project. Qual Life Res 2004, 13:283-298.
• [36]Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B: Depression, chronic diseases, and decrements in health: results from the world health surveys. Lancet 2007, 370:851-858.
• [37]Vasiljevic N, Ralevic S, Marinkovic J, Kocev N, Maksimovic M, Milosevic GS, et al.: The assessment of health-related quality of life in relation to the body mass index value in the urban population of Belgrade. Health Qual Life Outcomes 2008, 6:106.
• [38]Doll HA, Petersen SE, Stewart†Brown SL: Obesity and physical and emotional well-being: associations between body mass index, chronic illness, and the physical and mental components of the SF-36 questionnaire. Obes Res 2000, 8:160-170.