Unconditional quantile regressions to determine the social gradient of obesity in Spain 1993–2014

International Journal for Equity in Health

Research

Beatriz Lopez-Valcarcel¹  Alejandro Rodriguez-Caro¹  Laura Vallejo-Torres² 

[1] Department of Quantitative Methods, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain;UCL Department of Applied Health Research, UCL, University College London, Gower Street, WC1E 6BT, London, UK;

关键词: Obesity;    Social inequalities;    Unconditional quantile regression;   

DOI  :  10.1186/s12939-016-0454-1

 received in 2016-06-08, accepted in 2016-09-26,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundThere is a well-documented social gradient in obesity in most developed countries. Many previous studies have conventionally categorised individuals according to their body mass index (BMI), focusing on those above a certain threshold and thus ignoring a large amount of the BMI distribution. Others have used linear BMI models, relying on mean effects that may mask substantial heterogeneity in the effects of socioeconomic variables across the population.MethodIn this study, we measure the social gradient of the BMI distribution of the adult population in Spain over the past two decades (1993–2014), using unconditional quantile regressions. We use three socioeconomic variables (education, income and social class) and evaluate differences in the corresponding effects on different percentiles of the log-transformed BMI distribution. Quantile regression methods have the advantage of estimating the socioeconomic effect across the whole BMI distribution allowing for this potential heterogeneity.ResultsThe results showed a large and increasing social gradient in obesity in Spain, especially among females. There is, however, a large degree of heterogeneity in the socioeconomic effect across the BMI distribution, with patterns that vary according to the socioeconomic indicator under study. While the income and educational gradient is greater at the end of the BMI distribution, the main impact of social class is around the median BMI values. A steeper social gradient is observed with respect to educational level rather than household income or social class.ConclusionThe findings of this study emphasise the heterogeneous nature of the relationship between social factors and obesity across the BMI distribution as a whole. Quantile regression methods might provide a more suitable framework for exploring the complex socioeconomic gradient of obesity.

【 授权许可】

CC BY   
© The Author(s). 2016