Socioeconomic Inequalities in Body Mass Index in Barcelona 1986-2016: An Unconditional Quantile Regression Approach

Understanding gender differences in body mass index (BMI) between males and females has been much debated and received considerable attention. This study aims to decompose gender differentials in the BMI of people of the Kingdom of Saudi Arabia. The study decomposed the BMI gender gap into its associated factors across the entire BMI distribution by using counterfactual regression methods. The main method of analysis was newly developed unconditional quantile regression-based decomposition, which applied Blinder–Oaxaca decomposition using data from the Saudi Health Interview Survey. Gender differentials were found in the BMI, with females showing a higher BMI than males. The aggregate decomposition showed that both the covariate effect and the structural effect were significant at the 25th and 50th quantiles. Detailed decomposition indicated that income level and employment status as well as soda consumption and the consumption of red meat were significantly correlated in explaining gender differentials in BMI across various quantiles, but the magnitude varied by quantile. Our study suggests the government should consider introducing programs that specifically target women to help them reduce BMI. These programs could include organizing sporting events at the workplace and at the national level. Furthermore, the effect of soda consumption could be reduced by levying a tax on beverages, which might reduce the demand for soda due to the increased price.

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Better Dietary Knowledge and Socioeconomic Status (SES), Better Body Mass Index? Evidence from China—An Unconditional Quantile Regression Approach

Nutrients ◽

10.3390/nu12041197 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1197 ◽

Cited By ~ 2

Author(s):

Jie Yu ◽

Xiao Han ◽

Hongxing Wen ◽

Jinzheng Ren ◽

Lihong Qi

Keyword(s):

Body Mass Index ◽

Socioeconomic Status ◽

Quantile Regression ◽

Body Mass ◽

Inverse Association ◽

Nutrition Survey ◽

Dietary Knowledge ◽

Unconditional Quantile Regression ◽

Heterogeneous Nature ◽

The Relationship

Obesity is a rapidly growing public health threat in China. Improvement of dietary knowledge may potentially reduce the risk of obesity and being overweight. However, existing studies focus on measuring the mean effects of nutrition knowledge on body mass index (BMI). There is a lack of literature on the effect of dietary knowledge on BMI, and the potential heterogeneity of the effect across the whole BMI distribution and across socioeconomic status (SES) groups. This study aims to investigate the heterogeneous nature of the relationship between dietary knowledge, SES, and BMI, using data from the China Health and Nutrition Survey (CHNS) in 2015. We employed unconditional quantile regression (UQR) to assess how the relationship between dietary knowledge, SES, and BMI varies across the whole BMI distribution, and conducted subgroup analyses using different socio-economic subsamples. Results indicate that dietary knowledge had no statistically significant impact on BMI across the BMI distribution. There was a large degree of heterogeneity in the SES effect across the BMI distribution as well as a major gender difference in the SES effect on BMI. Education had a significant and inverse association with BMI across the BMI distribution, greater at higher BMI quantiles. Income growth had a larger effect on the 50th quantile of BMI for males in the middle-income group, but was not significant for females. As income increased, males without college educations had higher BMI while females with college or higher education generally had lower BMI. The findings of this study reveal the heterogeneous nature of the relationship between SES, gender, and obesity across the entire BMI distribution, suggesting that quantile regressions might offer a valuable framework for exploring the complex relationship of dietary knowledge, demographic, and socio-economic factors on obesity.

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