IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v166y2016icp223-232.html
   My bibliography  Save this article

Alternative measures to BMI: Exploring income-related inequalities in adiposity in Great Britain

Author

Listed:
  • Davillas, Apostolos
  • Benzeval, Michaela

Abstract

Socio-economic inequalities in adiposity are of particular interest themselves but also because they may be associated with inequalities in overall health status. Using cross-sectional representative data from Great Britain (1/2010-3/2012) for 13,138 adults (5652 males and 7486 females) over age 20, we aimed to explore the presence of income-related inequalities in alternative adiposity measures by gender and to identify the underlying factors contributing to these inequalities. For this reason, we employed concentration indexes and regression-based decomposition techniques. To control for non-homogeneity in body composition, we employed a variety of adiposity measures including body fat (absolute and percentage) and central adiposity (waist circumference) in addition to the conventional body mass index (BMI). The body fat measures allowed us to distinguish between the fat- and lean-mass components of BMI. We found that the absence of income-related obesity inequalities for males in the existing literature may be attributed to their focus on BMI-based measures. Pro-rich inequalities were evident for the fat-mass and central adiposity measures for males, while this was not the case for BMI. Irrespective of the adiposity measure applied, pro-rich inequalities were evident for females. The decomposition analysis showed that these inequalities were mainly attributable to subjective financial well-being measures (perceptions of financial strain and material deprivation) and education, with the relative contribution of the former being more evident in females. Our findings have important implications for the measurement of socio-economic inequalities in adiposity and indicate that central adiposity and body composition measures should be included health policy agendas. Psycho-social mechanisms, linked to subjective financial well-being, and education -rather than income itself-are more relevant for tackling inequalities.

Suggested Citation

  • Davillas, Apostolos & Benzeval, Michaela, 2016. "Alternative measures to BMI: Exploring income-related inequalities in adiposity in Great Britain," Social Science & Medicine, Elsevier, vol. 166(C), pages 223-232.
    • Handle: RePEc:eee:socmed:v:166:y:2016:i:c:p:223-232
    DOI: 10.1016/j.socscimed.2016.08.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953616304683
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2016.08.032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wagstaff, Adam & Paci, Pierella & van Doorslaer, Eddy, 1991. "On the measurement of inequalities in health," Social Science & Medicine, Elsevier, vol. 33(5), pages 545-557, January.
    2. Donal O’Neill & Olive Sweetman, 2013. "The consequences of measurement error when estimating the impact of obesity on income," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-20, December.
    3. Owen O'Donnell & Eddy van Doorslaer & Adam Wagstaff & Magnus Lindelow, 2008. "Analyzing Health Equity Using Household Survey Data : A Guide to Techniques and Their Implementation," World Bank Publications - Books, The World Bank Group, number 6896.
    4. Wu, Hania Fei, 2021. "Social determination, health selection or indirect selection? Examining the causal directions between socioeconomic status and obesity in the Chinese adult population," Social Science & Medicine, Elsevier, vol. 269(C).
    5. Rashad, Inas, 2006. "Structural estimation of caloric intake, exercise, smoking, and obesity," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 268-283, May.
    6. Hughes, Amanda & Kumari, Meena, 2019. "Testosterone, risk, and socioeconomic position in British men: Exploring causal directionality," Social Science & Medicine, Elsevier, vol. 220(C), pages 129-140.
    7. Davillas, Apostolos & Jones, Andrew M., 2020. "Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment," Economics & Human Biology, Elsevier, vol. 38(C).
    8. Zhang, Qi & Wang, Youfa, 2004. "Socioeconomic inequality of obesity in the United States: do gender, age, and ethnicity matter?," Social Science & Medicine, Elsevier, vol. 58(6), pages 1171-1180, March.
    9. O’Neill, Donal, 2015. "Measuring obesity in the absence of a gold standard," Economics & Human Biology, Elsevier, vol. 17(C), pages 116-128.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Davillas, Apostolos & Burlinson, Andrew & Liu, Hui-Hsuan, 2022. "Getting warmer: Fuel poverty, objective and subjective health and well-being," Energy Economics, Elsevier, vol. 106(C).
    2. Apostolos Davillas & Victor Hugo Oliveira & Andrew M. Jones, 2024. "A model of errors in BMI based on self-reported and measured anthropometrics with evidence from Brazilian data," Empirical Economics, Springer, vol. 67(5), pages 2371-2410, November.
    3. Antonio Di Paolo & Joan Gil Trasfi & Athina Raftopoulou, 2018. "“What drives regional differences in BMI? Evidence from Spain”," IREA Working Papers 201808, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
    4. Davillas, A.; Jones, A.M.; Benzeval, M.;, 2017. "The income-health gradient: Evidence from self-reported health and biomarkers using longitudinal data on income," Health, Econometrics and Data Group (HEDG) Working Papers 17/04, HEDG, c/o Department of Economics, University of York.
    5. Hughes, Amanda & Kumari, Meena, 2019. "Testosterone, risk, and socioeconomic position in British men: Exploring causal directionality," Social Science & Medicine, Elsevier, vol. 220(C), pages 129-140.
    6. Wu, Hania Fei, 2021. "Social determination, health selection or indirect selection? Examining the causal directions between socioeconomic status and obesity in the Chinese adult population," Social Science & Medicine, Elsevier, vol. 269(C).
    7. Davillas, Apostolos & Jones, Andrew M., 2020. "Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment," Economics & Human Biology, Elsevier, vol. 38(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Apostolos Davillas & Victor Hugo Oliveira & Andrew M. Jones, 2024. "A model of errors in BMI based on self-reported and measured anthropometrics with evidence from Brazilian data," Empirical Economics, Springer, vol. 67(5), pages 2371-2410, November.
    2. Athina Raftopoulou & Joan Gil Trasfi, 2024. "Income-related inequality in obesity and its determinants in Spain: What happens beyond the obesity threshold?," International Journal of Health Economics and Management, Springer, vol. 24(1), pages 135-153, March.
    3. Georgia S. Papoutsi & Andreas C. Drichoutis & Rodolfo M. Nayga Jr., 2013. "The Causes Of Childhood Obesity: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 27(4), pages 743-767, September.
    4. Nesson, Erik T. & Robinson, Joshua J., 2019. "On the measurement of health and its effect on the measurement of health inequality," Economics & Human Biology, Elsevier, vol. 35(C), pages 207-221.
    5. Robson, Matthew & O’Donnell, Owen & Van Ourti, Tom, 2024. "Aversion to health inequality — Pure, income-related and income-caused," Journal of Health Economics, Elsevier, vol. 94(C).
    6. Tomson Ogwang & Germano Mwabu, 2024. "Adaptation of the Foster‐Greer‐Thorbecke poverty measures for the measurement of catastrophic health expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 33(10), pages 2419-2436, October.
    7. Mohammed Khaled Al-Hanawi & Rubayyat Hashmi & Sarh Almubark & Ameerah M. N. Qattan & Mohammad Habibullah Pulok, 2020. "Socioeconomic Inequalities in Uptake of Breast Cancer Screening among Saudi Women: A Cross-Sectional Analysis of a National Survey," IJERPH, MDPI, vol. 17(6), pages 1-13, March.
    8. Di Novi, C. & Piacenza, M. & Robone, S. & Turati, G., 2015. "How does fiscal decentralization affect within-regional disparities in well-being? Evidence from health inequalities in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 15/23, HEDG, c/o Department of Economics, University of York.
    9. Erreygers, Guido & Van Ourti, Tom, 2011. "Measuring socioeconomic inequality in health, health care and health financing by means of rank-dependent indices: A recipe for good practice," Journal of Health Economics, Elsevier, vol. 30(4), pages 685-694, July.
    10. Aristides dos Santos, Anderson Moreira & Perelman, Julian & Jacinto, Paulo de Andrade & Tejada, Cesar Augusto Oviedo & Barros, Aluísio J.D. & Bertoldi, Andréa D. & Matijasevich, Alicia & Santos, Iná S, 2019. "Income-related inequality and inequity in children’s health care: A longitudinal analysis using data from Brazil," Social Science & Medicine, Elsevier, vol. 224(C), pages 127-137.
    11. Olufunke Alaba & Lumbwe Chola, 2014. "Socioeconomic Inequalities in Adult Obesity Prevalence in South Africa: A Decomposition Analysis," IJERPH, MDPI, vol. 11(3), pages 1-20, March.
    12. Daouli, Joan & Davillas, Apostolos & Demoussis, Michael & Giannakopoulos, Nicholas, 2014. "Obesity persistence and duration dependence: Evidence from a cohort of US adults (1985–2010)," Economics & Human Biology, Elsevier, vol. 12(C), pages 30-44.
    13. Chavas, Jean-Paul, 2013. "On the microeconomics of food and malnutrition under endogenous discounting," European Economic Review, Elsevier, vol. 59(C), pages 80-96.
    14. Aizawa, Toshiaki, 2019. "Ex-ante Inequality of Opportunity in Child Malnutrition: New Evidence from Ten Developing Countries in Asia," Economics & Human Biology, Elsevier, vol. 35(C), pages 144-161.
    15. Mohamad A. Khaled & Paul Makdissi & Rami V. Tabri & Myra Yazbeck, 2018. "A framework for testing the equality between the health concentration curve and the 45‐degree line," Health Economics, John Wiley & Sons, Ltd., vol. 27(5), pages 887-896, May.
    16. Baltica Cabieses & Richard Cookson & Manuel Espinoza & Gillian Santorelli & Iris Delgado, 2015. "Did Socioeconomic Inequality in Self-Reported Health in Chile Fall after the Equity-Based Healthcare Reform of 2005? A Concentration Index Decomposition Analysis," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-21, September.
    17. Batana, Yélé Maweki, 2010. "Evolution of social inequalities in health in Quebec?," MPRA Paper 20710, University Library of Munich, Germany.
    18. Barbosa, Estela Capelas & Cookson, Richard, 2019. "Multiple inequity in health care: An example from Brazil," Social Science & Medicine, Elsevier, vol. 228(C), pages 1-8.
    19. Joan Costa-Font & Cristina Hernandez-Quevedo & Azusa Sato, 2018. "A Health ‘Kuznets’ Curve’? Cross-Sectional and Longitudinal Evidence on Concentration Indices’," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(2), pages 439-452, April.
    20. E. Xie, 2011. "Income-related inequalities of health and health care utilization," Frontiers of Economics in China, Springer;Higher Education Press, vol. 6(1), pages 131-156, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:166:y:2016:i:c:p:223-232. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.