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How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis

Accumulating evidence links cardiometabolic health with social and environmental neighborhood exposures, which may contribute to health inequities. We examined whether environmental characteristics were individually or jointly associated with insulin resistance, hypertension, obesity, type 2 diabete...

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Autores principales: Letellier, Noémie, Zamora, Steven, Yang, Jiue-An, Sears, Dorothy D., Jankowska, Marta M., Benmarhnia, Tarik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562428/
https://www.ncbi.nlm.nih.gov/pubmed/36245803
http://dx.doi.org/10.1016/j.pmedr.2022.102005
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author Letellier, Noémie
Zamora, Steven
Yang, Jiue-An
Sears, Dorothy D.
Jankowska, Marta M.
Benmarhnia, Tarik
author_facet Letellier, Noémie
Zamora, Steven
Yang, Jiue-An
Sears, Dorothy D.
Jankowska, Marta M.
Benmarhnia, Tarik
author_sort Letellier, Noémie
collection PubMed
description Accumulating evidence links cardiometabolic health with social and environmental neighborhood exposures, which may contribute to health inequities. We examined whether environmental characteristics were individually or jointly associated with insulin resistance, hypertension, obesity, type 2 diabetes, and metabolic syndrome in San Diego County, CA. As part of the Community of Mine Study, cardiometabolic outcomes of insulin resistance, hypertension, BMI, diabetes, and metabolic syndrome were collected in 570 participants. Seven census tract level characteristics of participants’ residential environment were assessed and grouped as follows: economic, education, health care access, neighborhood conditions, social environment, transportation, and clean environment. Generalized estimating equation models were performed, to take into account the clustered nature of the data and to estimate β or relative risk (RR) and 95 % confidence intervals (CIs) between each of the seven environmental characteristics and cardiometabolic outcomes. Quantile g-computation was used to examine the association between the joint effect of a simultaneous increase in all environmental characteristics and cardiometabolic outcomes. Among 570 participants (mean age 58.8 ± 11 years), environmental economic, educational and health characteristics were individually associated with insulin resistance, diabetes, obesity, and metabolic syndrome. In the mixture analyses, a joint quartile increase in all environmental characteristics (i.e., improvement) was associated with decreasing insulin resistance (β, 95 %CI: −0.09, −0.18–0.01)), risk of diabetes (RR, 95 %CI: 0.59, 0.36–0.98) and obesity (RR, 95 %CI: 0.81, 0.64–1.02). Environmental characteristics synergistically contribute to cardiometabolic health and independent analysis of these determinants may not fully capture the potential health impact of social and environmental determinants of health.
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spelling pubmed-95624282022-10-15 How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis Letellier, Noémie Zamora, Steven Yang, Jiue-An Sears, Dorothy D. Jankowska, Marta M. Benmarhnia, Tarik Prev Med Rep Regular Article Accumulating evidence links cardiometabolic health with social and environmental neighborhood exposures, which may contribute to health inequities. We examined whether environmental characteristics were individually or jointly associated with insulin resistance, hypertension, obesity, type 2 diabetes, and metabolic syndrome in San Diego County, CA. As part of the Community of Mine Study, cardiometabolic outcomes of insulin resistance, hypertension, BMI, diabetes, and metabolic syndrome were collected in 570 participants. Seven census tract level characteristics of participants’ residential environment were assessed and grouped as follows: economic, education, health care access, neighborhood conditions, social environment, transportation, and clean environment. Generalized estimating equation models were performed, to take into account the clustered nature of the data and to estimate β or relative risk (RR) and 95 % confidence intervals (CIs) between each of the seven environmental characteristics and cardiometabolic outcomes. Quantile g-computation was used to examine the association between the joint effect of a simultaneous increase in all environmental characteristics and cardiometabolic outcomes. Among 570 participants (mean age 58.8 ± 11 years), environmental economic, educational and health characteristics were individually associated with insulin resistance, diabetes, obesity, and metabolic syndrome. In the mixture analyses, a joint quartile increase in all environmental characteristics (i.e., improvement) was associated with decreasing insulin resistance (β, 95 %CI: −0.09, −0.18–0.01)), risk of diabetes (RR, 95 %CI: 0.59, 0.36–0.98) and obesity (RR, 95 %CI: 0.81, 0.64–1.02). Environmental characteristics synergistically contribute to cardiometabolic health and independent analysis of these determinants may not fully capture the potential health impact of social and environmental determinants of health. 2022-09-26 /pmc/articles/PMC9562428/ /pubmed/36245803 http://dx.doi.org/10.1016/j.pmedr.2022.102005 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Letellier, Noémie
Zamora, Steven
Yang, Jiue-An
Sears, Dorothy D.
Jankowska, Marta M.
Benmarhnia, Tarik
How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis
title How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis
title_full How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis
title_fullStr How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis
title_full_unstemmed How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis
title_short How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis
title_sort how do environmental characteristics jointly contribute to cardiometabolic health? a quantile g-computation mixture analysis
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562428/
https://www.ncbi.nlm.nih.gov/pubmed/36245803
http://dx.doi.org/10.1016/j.pmedr.2022.102005
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