Literature DB >> 28320207

Examination of cardiovascular risk factors and rurality in Appalachian children.

Christa L Lilly1, Amna Umer2, Lesley Cottrell3, Lee Pyles4, William Neal5.   

Abstract

INTRODUCTOIN: The prevalence of childhood cardiovascular disease (CVD) risk factors often increases in more rural geographic regions in the USA. However, research on the topic often has conflicting results. Researchers note differences in definitions of rurality and other factors that would lead to differences in inference, including appropriate use of statistical clustering analysis, representative data, and inclusion of individual-level covariates. The present study's objective was to examine CVD risk factors during childhood by geographic distribution in the US Appalachian region as a first step towards understanding the health disparities in this area.
METHODS: Rurality and CVD risk factors (including blood pressure, body-mass index (BMI), and cholesterol) were examined in a large, representative sample of fifth-grade students (<i>N=</i>73 014) from an Appalachian state in the USA. A six-category Rural-Urban Continuum Codes classification system was used to define rurality regions. Mixed modeling analysis was used to appropriately cluster individuals within 725 unique zip codes in each of these six regions, and allowed for including several individual-level socioeconomic factors as covariates.
RESULTS: Rural areas had better outcomes for certain CVD risk factors (lowest low-density lipoprotein cholesterol (LDL-C), and blood pressure (BP) and highest high-density lipoprotein cholesterol (HDL-C)) whereas mid-sized metro and town areas presented with the worst CVD risk factors (highest BMI% above ideal, mean diastolic BP, LDL-C, total cholesterol, triglyceride levels and lowest HDL-C) outcomes in children and adolescence in this Appalachian state.
CONCLUSIONS: Counter to the study hypothesis, mid-sized metro areas presented with the worst CVD risk factors outcomes in children and adolescence in the Appalachian state. This data contradicts previous literature suggesting a straightforward link between rurality and cardiovascular risk factors. Future research should include a longitudinal design and explore some of the mechanisms between cardiovascular risk factors and rurality.

Entities:  

Keywords:  Cardiovascular health; Maternal and Child Health; North America

Mesh:

Year:  2017        PMID: 28320207      PMCID: PMC5513183          DOI: 10.22605/rrh4200

Source DB:  PubMed          Journal:  Rural Remote Health        ISSN: 1445-6354            Impact factor:   1.759


  33 in total

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3.  Obesity disparities among elementary-aged children: data from school-based BMI surveillance.

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4.  Cardiovascular disease risk factors and obesity of rural and urban elementary school children.

Authors:  R G McMurray; J S Harrell; S I Bangdiwala; S Deng
Journal:  J Rural Health       Date:  1999       Impact factor: 4.333

5.  Morbidly obese diagnosis as an indicator of cardiovascular disease risk in children: results from the CARDIAC Project.

Authors:  Christa L Ice; Emily Murphy; Lesley Cottrell; William A Neal
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6.  New options for child health surveillance by state health departments.

Authors:  Kenneth D Rosenberg; Larry Hembroff; Jodi Drisko; Samara Viner-Brown; Kathy Decker; Erika Lichter
Journal:  Matern Child Health J       Date:  2011-04

7.  Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010.

Authors:  Cynthia L Ogden; Margaret D Carroll; Brian K Kit; Katherine M Flegal
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8.  Diet, physical activity, and sedentary behaviors as risk factors for childhood obesity: an urban and rural comparison.

Authors:  Ji-Hong Liu; Sonya J Jones; Han Sun; Janice C Probst; Anwar T Merchant; Philip Cavicchia
Journal:  Child Obes       Date:  2012-10       Impact factor: 2.992

Review 9.  Hypertension in children and adolescents: epidemiology and natural history.

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Journal:  Pediatr Nephrol       Date:  2009-05-07       Impact factor: 3.714

10.  A multilevel approach to estimating small area childhood obesity prevalence at the census block-group level.

Authors:  Xingyou Zhang; Stephen Onufrak; James B Holt; Janet B Croft
Journal:  Prev Chronic Dis       Date:  2013-05-02       Impact factor: 2.830

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