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Diabetes control is associated with environmental quality in the USA
Environmental parameters, including built and sociodemographic environments, can impact diabetes control (DC). Epidemiological studies have associated specific environmental factors with DC; however, the impact of multidimensional environmental status has not been assessed. The Environmental Quality...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Bioscientifica Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428089/ https://www.ncbi.nlm.nih.gov/pubmed/34343109 http://dx.doi.org/10.1530/EC-21-0132 |
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author | Jagai, Jyotsna S Krajewski, Alison K Price, Kyla N Lobdell, Danelle T Sargis, Robert M |
author_facet | Jagai, Jyotsna S Krajewski, Alison K Price, Kyla N Lobdell, Danelle T Sargis, Robert M |
author_sort | Jagai, Jyotsna S |
collection | PubMed |
description | Environmental parameters, including built and sociodemographic environments, can impact diabetes control (DC). Epidemiological studies have associated specific environmental factors with DC; however, the impact of multidimensional environmental status has not been assessed. The Environmental Quality Index (EQI), a comprehensive quantitative metric capturing five environmental domains, was considered as an exposure. Age-adjusted rates of DC prevalence for each county in the United States were used as an outcome. DC was defined as the proportion of adults aged 20+ years with a previous diabetes diagnosis who currently do not have high fasting blood glucose (≥126 mg/dL) or elevated HbA1c (≥6.5). We conducted county-level analyses of DC prevalence rates for the years 2004–2012 in association with EQI for 2006–2010 and domain-specific indices using random intercept multilevel linear regression models clustered by state and controlled for county-level rates of obesity and physical inactivity. Analyses were stratified by rural–urban strata, and results are reported as prevalence rate differences (PRD) with 95% CIs comparing highest quintile/worst environmental quality to lowest quintile/best environmental quality. The association of DC with cumulative environmental quality was negative after control for all counties (PRD −0.32, 95% CI: −0.38, −0.27); suggesting that rates of DC worsen as environmental quality declines. While overall environmental quality exerts effects on DC that vary across the rural–urban spectrum, poor sociodemographic, and built environmental factors are associated with decreased DC nationally. These data suggest improvements in environmental quality mediated by larger-scale policy and practice interventions may improve glycemic control and reduce the morbidity and mortality arising from hyperglycemia. |
format | Online Article Text |
id | pubmed-8428089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Bioscientifica Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-84280892021-09-13 Diabetes control is associated with environmental quality in the USA Jagai, Jyotsna S Krajewski, Alison K Price, Kyla N Lobdell, Danelle T Sargis, Robert M Endocr Connect Research Environmental parameters, including built and sociodemographic environments, can impact diabetes control (DC). Epidemiological studies have associated specific environmental factors with DC; however, the impact of multidimensional environmental status has not been assessed. The Environmental Quality Index (EQI), a comprehensive quantitative metric capturing five environmental domains, was considered as an exposure. Age-adjusted rates of DC prevalence for each county in the United States were used as an outcome. DC was defined as the proportion of adults aged 20+ years with a previous diabetes diagnosis who currently do not have high fasting blood glucose (≥126 mg/dL) or elevated HbA1c (≥6.5). We conducted county-level analyses of DC prevalence rates for the years 2004–2012 in association with EQI for 2006–2010 and domain-specific indices using random intercept multilevel linear regression models clustered by state and controlled for county-level rates of obesity and physical inactivity. Analyses were stratified by rural–urban strata, and results are reported as prevalence rate differences (PRD) with 95% CIs comparing highest quintile/worst environmental quality to lowest quintile/best environmental quality. The association of DC with cumulative environmental quality was negative after control for all counties (PRD −0.32, 95% CI: −0.38, −0.27); suggesting that rates of DC worsen as environmental quality declines. While overall environmental quality exerts effects on DC that vary across the rural–urban spectrum, poor sociodemographic, and built environmental factors are associated with decreased DC nationally. These data suggest improvements in environmental quality mediated by larger-scale policy and practice interventions may improve glycemic control and reduce the morbidity and mortality arising from hyperglycemia. Bioscientifica Ltd 2021-08-03 /pmc/articles/PMC8428089/ /pubmed/34343109 http://dx.doi.org/10.1530/EC-21-0132 Text en © The authors https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | Research Jagai, Jyotsna S Krajewski, Alison K Price, Kyla N Lobdell, Danelle T Sargis, Robert M Diabetes control is associated with environmental quality in the USA |
title | Diabetes control is associated with environmental quality in the USA |
title_full | Diabetes control is associated with environmental quality in the USA |
title_fullStr | Diabetes control is associated with environmental quality in the USA |
title_full_unstemmed | Diabetes control is associated with environmental quality in the USA |
title_short | Diabetes control is associated with environmental quality in the USA |
title_sort | diabetes control is associated with environmental quality in the usa |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428089/ https://www.ncbi.nlm.nih.gov/pubmed/34343109 http://dx.doi.org/10.1530/EC-21-0132 |
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