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1.
Nat Commun ; 13(1): 267, 2022 01 18.
Artigo em Inglês | MEDLINE | ID: mdl-35042849

RESUMO

An unhealthy diet is a major risk factor for chronic diseases including cardiovascular disease, type 2 diabetes, and cancer1-4. Limited access to healthy food options may contribute to unhealthy diets5,6. Studying diets is challenging, typically restricted to small sample sizes, single locations, and non-uniform design across studies, and has led to mixed results on the impact of the food environment7-23. Here we leverage smartphones to track diet health, operationalized through the self-reported consumption of fresh fruits and vegetables, fast food and soda, as well as body-mass index status in a country-wide observational study of 1,164,926 U.S. participants (MyFitnessPal app users) and 2.3 billion food entries to study the independent contributions of fast food and grocery store access, income and education to diet health outcomes. This study constitutes the largest nationwide study examining the relationship between the food environment and diet to date. We find that higher access to grocery stores, lower access to fast food, higher income and college education are independently associated with higher consumption of fresh fruits and vegetables, lower consumption of fast food and soda, and lower likelihood of being affected by overweight and obesity. However, these associations vary significantly across zip codes with predominantly Black, Hispanic or white populations. For instance, high grocery store access has a significantly larger association with higher fruit and vegetable consumption in zip codes with predominantly Hispanic populations (7.4% difference) and Black populations (10.2% difference) in contrast to zip codes with predominantly white populations (1.7% difference). Policy targeted at improving food access, income and education may increase healthy eating, but intervention allocation may need to be optimized for specific subpopulations and locations.


Assuntos
Dieta , Características de Residência , Índice de Massa Corporal , Estudos Transversais , Diabetes Mellitus Tipo 2/epidemiologia , Dieta/estatística & dados numéricos , Abastecimento de Alimentos , Frutas , Humanos , Renda , Obesidade , Fatores de Risco , Fatores Socioeconômicos , Estados Unidos/epidemiologia , Verduras
2.
Nature ; 547(7663): 336-339, 2017 07 20.
Artigo em Inglês | MEDLINE | ID: mdl-28693034

RESUMO

To be able to curb the global pandemic of physical inactivity and the associated 5.3 million deaths per year, we need to understand the basic principles that govern physical activity. However, there is a lack of large-scale measurements of physical activity patterns across free-living populations worldwide. Here we leverage the wide usage of smartphones with built-in accelerometry to measure physical activity at the global scale. We study a dataset consisting of 68 million days of physical activity for 717,527 people, giving us a window into activity in 111 countries across the globe. We find inequality in how activity is distributed within countries and that this inequality is a better predictor of obesity prevalence in the population than average activity volume. Reduced activity in females contributes to a large portion of the observed activity inequality. Aspects of the built environment, such as the walkability of a city, are associated with a smaller gender gap in activity and lower activity inequality. In more walkable cities, activity is greater throughout the day and throughout the week, across age, gender, and body mass index (BMI) groups, with the greatest increases in activity found for females. Our findings have implications for global public health policy and urban planning and highlight the role of activity inequality and the built environment in improving physical activity and health.


Assuntos
Exercício Físico , Internacionalidade , Saúde Pública/estatística & dados numéricos , Acelerometria , Adolescente , Adulto , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Índice de Massa Corporal , Criança , Cidades , Planejamento de Cidades , Conjuntos de Dados como Assunto , Planejamento Ambiental , Feminino , Política de Saúde , Humanos , Masculino , Pessoa de Meia-Idade , Obesidade/epidemiologia , Prevalência , Fatores Sexuais , Smartphone , Caminhada , Adulto Jovem
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