Investigating the poverty-obesity paradox in Europe

Salmasi, Luca; Celidoni, Martina

doi:10.1016/j.ehb.2017.02.005

Cited by 30 publications

(14 citation statements)

References 37 publications

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“…This discrepancy in the prevalence of obesity compared with other studies may be related to the unique characteristics of the studied sample. Other research has shown an association between low socioeconomic status and increased risk of obesity [29,30]. This is probably due to the presence of food insecurity and food choices in low-income households, in which foods of low nutritional value and high energy density are predominant.…”

Section: Discussionmentioning

confidence: 99%

Ultra-processed food consumption and obesity in adolescents

2019

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Objective To evaluate the relationship between ultra-processed food consumption and obesity indicators in adolescents. Methods Cross-sectional study with a convenience sample of 200 10- to 18-year-old adolescents from Campinas, São Paulo (SP). Usual dietary intake was determined through a semiquantitative food frequency questionnaire. Daily intake of each food was obtained from the intake frequency. Subsequently, foods were classified as raw and minimally processed, cooking ingredients or ultra-processed foods, and their caloric contribution to the total energy value was calculated. Sociodemographic and anthropometric variables were also investigated. Overweight was defined as Z-score>+1 and obesity was defined as Z-score>+2 according to the Body Mass Index per age group. The associations were tested by chi-square test and linear trend. Results The frequency of obesity was 47.0%, and 21.5% presented increased waist circumference. The average energy intake was 4,176kcal/day, of which 50.6% was derived from ultra-processed foods. The categories with the highest caloric contributions among ultra-processed foods were industrial loaves/cakes (16.2%), sweets and candy (6.2%), pastas (6.0%) and sweetened drinks (5.1%). No association was found between ultra-processed food consumption and anthropometric indicators. Conclusion The significant contribution of ultra-processed foods to daily calories is evidence of a poor diet of this population of young people, although this has not been shown as a factor associated with excess weight. Therefore, there is an urgent need for public policies that discourage the consumption of these products and encourage the return to a traditional diet.

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Section: Discussionmentioning

confidence: 99%

Ultra-processed food consumption and obesity in adolescents

2019

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“…Hojjat and Hojjat (2017) confirmed that a long-term relationship exists among obesity, income inequality, and poverty in the U.S., finding that the greater the income inequality and poverty, the higher the obesity rate. Salmasi & Celidoni (2017) studied the effect of income and wealth-based poverty on the probability of being obese for the elderly in Europe. Their study shows that poverty significantly increases the likelihood of being obese for both men and women.…”

Section: Figure 1 Gini Coefficient Perú: 2008-2017mentioning

confidence: 99%

Obesity and Socioeconomic Status Among Peruvian Women: Evidence of Panel Data Analysis

2019

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The rise in global obesity and overweight population rates has reached a pandemic level. This dramatic rise in rates is more pronounced in developing countries, as compared to more industrialized societies. In Peru, obesity rates are escalating, the information available shows that during the years 2008 and 2017 the rate of obesity among Peruvian women increased from 14.60 to 22.91 percent, despite the progress made in reducing poverty and income inequality during the reference period. In this paper, Panel-data analysis from 2008-2017, 24 regions, and a sample size of 240 data points is used. We find that there is a cointegration among obesity, poverty, and income inequality, which ensures a long-run relationship among the variables.

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“…In 2015, over 35% of the population was obese in U.S. states where median household incomes were below $45,000 per year, whereas obesity was less than 25% of state populations where median incomes were above $65,000 (Centers for Disease Control and Prevention, 2017c). Similarly in Europe today, poor individuals are 10% to 20% more likely to be obese (Salmasi and Celidon, 2017). This pattern is unique to Developed economies; within China, for example, an inverse correlation between income and obesity/diabetes is observed only in the most economically developed regions (Tafreschi, 2015).…”

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confidence: 98%

Recent origin and evolution of obesity-income correlation across the United States

2018

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From a gene-culture evolutionary perspective, the recent rise in obesity rates around the Developed world is unprecedented; perhaps the most rapid population-scale shift in human phenotype ever to occur. Focusing on the recent rise of obesity and diabetes in the United States, we consider the predictions of human behavioral ecology (HBE) versus the predictions of social learning (SL) of obesity through cultural traditions and/or peer-to-peer influence. To isolate differences that might discriminate these different models, we first explore temporal and geographic trends in the inverse correlation between household income and obesity and diabetes rates in the U.S. Whereas by 2015 these inverse correlations were strong, these correlations were non-existent as recently as 1990. The inverse correlations have evolved steadily over recent decades, and we present equations for their time evolution since 1990. We then explore evidence for a "social multiplier" effect at county scale over a ten-year period, as well as a social diffusion pattern at state scale over a 26-year period. We conclude that these patterns support HBE and SL as factors driving obesity, with HBE explaining ultimate causation. As a specific "ecological" driver for this human behavior, we speculate that refined sugar in processed foods may be a prime driver of increasing obesity and diabetes.

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Investigating the poverty-obesity paradox in Europe

Cited by 30 publications

References 37 publications

Ultra-processed food consumption and obesity in adolescents

Ultra-processed food consumption and obesity in adolescents

Obesity and Socioeconomic Status Among Peruvian Women: Evidence of Panel Data Analysis

Recent origin and evolution of obesity-income correlation across the United States

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