Decomposing cross-country differences in levels of obesity and overweight: Does the social environment matter?

Font, Joan Costa; Fabbri, Daniele; Gil, Joan

doi:10.1016/j.socscimed.2009.12.011

Cited by 47 publications

(24 citation statements)

References 40 publications

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“…Such a research program might also consider conceptualizing and defining "communities" in non-spatial as well as spatial terms, as group social and cultural norms that influence obesity outcomes are likely to transcend geographic boundaries (Font et al, 2010). Further research along these lines holds promise for enhancing our understanding of how "place" -broadly construed -influences obesity and other critical health conditions, behaviors, and outcomes.…”

Section: Discussionmentioning

confidence: 99%

Ethnic density and obesity: Evidence from fixed-effects models

Moloney

South

2015

Health & Place

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Section: Discussionmentioning

confidence: 99%

Ethnic density and obesity: Evidence from fixed-effects models

Moloney

South

2015

Health & Place

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“…Since obesity is essentially an imbalance between calorie intake and expenditure, the inclusion of information on physical activity is important. Although there is high probability that the inclusion of the lifestyle factors could be endogenous, we strongly believe in the importance of these factors in the decomposition analysis not only because of the demonstrated association of these factors with obesity and obesity inequality in the literature [54] but also because they can be classified as “policy- relevant variables” in the context of the measurement of socioeconomic related inequality in health or healthcare (Gravelle estimated a directly standardized partial concentration index, and suggests the use of three types of variables in the regression equation used for the decomposition analysis, namely: income, need standardizing variables and other possible policy-relevant variables [55]). Consequently, our estimated regression model can be viewed as a reduced form demand model for obesity and no causal interpretation is implied.…”

Section: Methodsmentioning

confidence: 99%

Socioeconomic Inequalities in Adult Obesity Prevalence in South Africa: A Decomposition Analysis

Alaba

Chola

2014

IJERPH

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In recent years, there has been a dramatic increase in obesity in low and middle income countries. However, there is limited research in these countries showing the prevalence and determinants of obesity. In this study, we examine the socioeconomic inequalities in obesity among South African adults. We use nationally representative data from the South Africa National Income Dynamic Survey of 2008 to: (1) construct an asset index using multiple correspondence analyses (MCA) as a proxy for socioeconomic status; (2) estimate concentration indices (CI) to measure socioeconomic inequalities in obesity; and (3) perform a decomposition analysis to determine the factors that contribute to socioeconomic related inequalities. Consistent with other studies, we find that women are more obese than men. The findings show that obesity inequalities exist in South Africa. Rich men are more likely to be obese than their poorer counterparts with a concentration index of 0.27. Women on the other hand have similar obesity patterns, regardless of socioeconomic status with CI of 0.07. The results of the decomposition analysis suggest that asset index contributes positively and highly to socio-economic inequality in obesity among females; physical exercise contributes negatively to the socio-economic inequality. In the case of males, educational attainment and asset index contributed more to socio-economic inequalities in obesity. Our findings suggest that focusing on economically well-off men and all women across socioeconomic status is one way to address the obesity problem in South Africa.

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“…This methodology decomposes the observed group difference in outcome into two main components: the disparity associated with the differences in determinants and the disparity associated with the differential response by ethnic groups to those determinants. Several recent studies have applied this methodology to studying disparities in public health including gender differences in smoking (Chung, Lim, & Lee, 2010) and cross-country differences in obesity between the U.S. and Canada (Auld & Powell, 2006) and Spain and Italy (Font, Fabbri, & Gil, 2010). …”

Section: Methodsmentioning

confidence: 99%

Ethnic disparities in adolescent body mass index in the United States: The role of parental socioeconomic status and economic contextual factors

Powell

Wada

Krauss

et al. 2012

Social Science & Medicine

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This paper examined the importance of household and economic contextual factors as determinants of ethnic disparities in adolescent body mass index (BMI). Individual-level data from the National Longitudinal Survey of Youth 1997 for the years 1997 through 2000 were combined with economic contextual data on food prices, outlet density and median household income. The Oaxaca–Blinder decomposition method was used to examine the factors that could help explain ethnic disparities in BMI. Ethnic differences in household demographic, parental socioeconomic status (SES), and economic contextual factors explained the majority of the male black–white (63%), male Hispanic–white (78%) and female Hispanic–white (62%) BMI gaps but less than one-half of the female black–white BMI gap (44%). We found that adding the economic contextual factors increased the explained portion of the ethnic BMI gap for both female and male adolescents: the economic contextual factors explained 28% and 38% of the black–white and Hispanic–white BMI gaps for males and 13% and 8% of the black–white and Hispanic–white BMI gaps for females, respectively. Parental SES was more important in explaining the Hispanic–white BMI gap than the black–white BMI gap for both genders, whereas neighborhood economic contextual factors were more important in explaining the male BMI gap than the female BMI gap for both black–white and Hispanic–white ethnic disparities. A significantly large portion of the ethnic BMI gap, however, remained unexplained between black and white female adolescents.

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Decomposing cross-country differences in levels of obesity and overweight: Does the social environment matter?

Cited by 47 publications

References 40 publications

Ethnic density and obesity: Evidence from fixed-effects models

Ethnic density and obesity: Evidence from fixed-effects models

Socioeconomic Inequalities in Adult Obesity Prevalence in South Africa: A Decomposition Analysis

Ethnic disparities in adolescent body mass index in the United States: The role of parental socioeconomic status and economic contextual factors

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