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Temporal Shifts in Cardiovascular Risk Factor Distribution

BACKGROUND: Complementary strategies to shift risk factor population distributions and target high-risk individuals are required to reduce the burden of type 2 diabetes and cardiovascular disease (CVD). PURPOSE: To examine secular changes in glucose and CVD risk factors over 20 years during an indiv...

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Autores principales: Long, Gráinne H., Simmons, Rebecca K., Norberg, Margareta, Wennberg, Patrik, Lindahl, Bernt, Rolandsson, Olov, Griffin, Simon J., Weinehall, Lars
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3898870/
https://www.ncbi.nlm.nih.gov/pubmed/24439344
http://dx.doi.org/10.1016/j.amepre.2013.10.011
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author Long, Gráinne H.
Simmons, Rebecca K.
Norberg, Margareta
Wennberg, Patrik
Lindahl, Bernt
Rolandsson, Olov
Griffin, Simon J.
Weinehall, Lars
author_facet Long, Gráinne H.
Simmons, Rebecca K.
Norberg, Margareta
Wennberg, Patrik
Lindahl, Bernt
Rolandsson, Olov
Griffin, Simon J.
Weinehall, Lars
author_sort Long, Gráinne H.
collection PubMed
description BACKGROUND: Complementary strategies to shift risk factor population distributions and target high-risk individuals are required to reduce the burden of type 2 diabetes and cardiovascular disease (CVD). PURPOSE: To examine secular changes in glucose and CVD risk factors over 20 years during an individual and population-based CVD prevention program in Västerbotten County, Sweden. METHODS: Population-based health promotion intervention was conducted and annual invitation for individuals turning 40, 50, and 60 years to attend a health assessment, including an oral glucose tolerance test, biochemical measures, and a questionnaire. Data were collected between 1991 and 2010, analyzed in 2012 and available for 120,929 individuals. Linear regression modeling examined age-adjusted differences in CVD risk factor means over time. Data were direct-age-standardized to compare disease prevalence. RESULTS: Between 1991–1995 and 2006–2010, mean age-adjusted cholesterol (men=−0.53, 95% CI=−0.55, −0.50 mmol/L; women=−0.48, 95% CI=−0.50, −0.45 mmol/L) and systolic blood pressure declined (men=−3.06, 95% CI=−3.43, −2.70 mm Hg; women=−5.27, 95% CI=−5.64, −4.90 mm Hg), with corresponding decreases in the age-standardized prevalence of hypertension and hyperlipidemia. Mean age-adjusted 2-hour plasma glucose (men=0.19, 95% CI=0.15, 0.23 mmol/L; women=0.08, 95% CI=0.04, 0.11 mmol/L) and BMI increased (men=1.12, 95% CI=1.04, 1.21; women=0.65, 95% CI=0.55, 0.75), with increases in the age-standardized prevalence of diabetes and obesity. CONCLUSIONS: These data demonstrate the potential of combined individual- and population-based approaches to CVD risk factor control and highlight the need for additional strategies addressing hyperglycemia and obesity.
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spelling pubmed-38988702014-02-01 Temporal Shifts in Cardiovascular Risk Factor Distribution Long, Gráinne H. Simmons, Rebecca K. Norberg, Margareta Wennberg, Patrik Lindahl, Bernt Rolandsson, Olov Griffin, Simon J. Weinehall, Lars Am J Prev Med Research Article BACKGROUND: Complementary strategies to shift risk factor population distributions and target high-risk individuals are required to reduce the burden of type 2 diabetes and cardiovascular disease (CVD). PURPOSE: To examine secular changes in glucose and CVD risk factors over 20 years during an individual and population-based CVD prevention program in Västerbotten County, Sweden. METHODS: Population-based health promotion intervention was conducted and annual invitation for individuals turning 40, 50, and 60 years to attend a health assessment, including an oral glucose tolerance test, biochemical measures, and a questionnaire. Data were collected between 1991 and 2010, analyzed in 2012 and available for 120,929 individuals. Linear regression modeling examined age-adjusted differences in CVD risk factor means over time. Data were direct-age-standardized to compare disease prevalence. RESULTS: Between 1991–1995 and 2006–2010, mean age-adjusted cholesterol (men=−0.53, 95% CI=−0.55, −0.50 mmol/L; women=−0.48, 95% CI=−0.50, −0.45 mmol/L) and systolic blood pressure declined (men=−3.06, 95% CI=−3.43, −2.70 mm Hg; women=−5.27, 95% CI=−5.64, −4.90 mm Hg), with corresponding decreases in the age-standardized prevalence of hypertension and hyperlipidemia. Mean age-adjusted 2-hour plasma glucose (men=0.19, 95% CI=0.15, 0.23 mmol/L; women=0.08, 95% CI=0.04, 0.11 mmol/L) and BMI increased (men=1.12, 95% CI=1.04, 1.21; women=0.65, 95% CI=0.55, 0.75), with increases in the age-standardized prevalence of diabetes and obesity. CONCLUSIONS: These data demonstrate the potential of combined individual- and population-based approaches to CVD risk factor control and highlight the need for additional strategies addressing hyperglycemia and obesity. Elsevier Science 2014-02 /pmc/articles/PMC3898870/ /pubmed/24439344 http://dx.doi.org/10.1016/j.amepre.2013.10.011 Text en © 2014 Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Research Article
Long, Gráinne H.
Simmons, Rebecca K.
Norberg, Margareta
Wennberg, Patrik
Lindahl, Bernt
Rolandsson, Olov
Griffin, Simon J.
Weinehall, Lars
Temporal Shifts in Cardiovascular Risk Factor Distribution
title Temporal Shifts in Cardiovascular Risk Factor Distribution
title_full Temporal Shifts in Cardiovascular Risk Factor Distribution
title_fullStr Temporal Shifts in Cardiovascular Risk Factor Distribution
title_full_unstemmed Temporal Shifts in Cardiovascular Risk Factor Distribution
title_short Temporal Shifts in Cardiovascular Risk Factor Distribution
title_sort temporal shifts in cardiovascular risk factor distribution
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3898870/
https://www.ncbi.nlm.nih.gov/pubmed/24439344
http://dx.doi.org/10.1016/j.amepre.2013.10.011
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