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Association of Socioeconomic Position and Demographic Characteristics with Cardiovascular Disease Risk Factors and Healthcare Access among Adults Living in Pohnpei, Federated States of Micronesia.

Hosey GM, Samo M, Gregg EW, Barker L, Padden D, Bibb SG - Int J Chronic Dis (2014)

Bottom Line: Healthcare access did not differ significantly by socioeconomic position.Women reported significantly higher mean waist circumference than men.Conclusion.

View Article: PubMed Central - PubMed

Affiliation: Division of Diabetes Translation, Centers for Disease Control and Prevention, National Center for Chronic Disease and Health Promotion, 4770 Buford Highway, Mailstop K10, Atlanta, GA 30341, USA.

ABSTRACT
Background. The burden of cardiovascular disease (CVD) is increasing in low-to-middle income countries. We examined how socioeconomic and demographic characteristics may be associated with CVD risk factors and healthcare access in such countries. Methods. We extracted data from the World Health Organization's STEPwise approach to surveillance 2002 cross-sectional dataset from Pohnpei, Federated States of Micronesia (FSM). We used these data to estimate associations for socioeconomic position (education, income, and employment) and demographics (age, sex, and urban/rural) with CVD risk factors and with healthcare access, among a sample of 1638 adults (25-64 years). Results. In general, we found significantly higher proportions of daily tobacco use among men than women and respondents reporting primary-level education (<9 years) than among those with postsecondary education (>12 years). Results also revealed significant positive associations between paid employment and waist circumference and systolic blood pressure. Healthcare access did not differ significantly by socioeconomic position. Women reported significantly higher mean waist circumference than men. Conclusion. Our results suggest that socioeconomic position and demographic characteristics impact CVD risk factors and healthcare access in FSM. This understanding may help decision-makers tailor population-level policies and programs. The 2002 Pohnpei data provides a baseline; subsequent population health surveillance data might define trends.

No MeSH data available.


Related in: MedlinePlus

Map of the US Associated Pacific Island Jurisdictions, Federated States of Micronesia.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig1: Map of the US Associated Pacific Island Jurisdictions, Federated States of Micronesia.

Mentions: In 2002, Pohnpei State, Federated States of Micronesia (FSM) (Figure 1), implemented a population-based surveillance survey to measure chronic disease risk factors among adults. While survey reports provide weighted analysis as a whole and by subgroup (i.e., age and sex), disaggregated analysis by socioeconomic position is unavailable [9]. In an effort to increase understanding of CVD risk factors within the population, the FSM Department of Health and Social Affairs requested assistance in broadening the analysis of the available population-based dataset.


Association of Socioeconomic Position and Demographic Characteristics with Cardiovascular Disease Risk Factors and Healthcare Access among Adults Living in Pohnpei, Federated States of Micronesia.

Hosey GM, Samo M, Gregg EW, Barker L, Padden D, Bibb SG - Int J Chronic Dis (2014)

Map of the US Associated Pacific Island Jurisdictions, Federated States of Micronesia.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4590923&req=5

fig1: Map of the US Associated Pacific Island Jurisdictions, Federated States of Micronesia.
Mentions: In 2002, Pohnpei State, Federated States of Micronesia (FSM) (Figure 1), implemented a population-based surveillance survey to measure chronic disease risk factors among adults. While survey reports provide weighted analysis as a whole and by subgroup (i.e., age and sex), disaggregated analysis by socioeconomic position is unavailable [9]. In an effort to increase understanding of CVD risk factors within the population, the FSM Department of Health and Social Affairs requested assistance in broadening the analysis of the available population-based dataset.

Bottom Line: Healthcare access did not differ significantly by socioeconomic position.Women reported significantly higher mean waist circumference than men.Conclusion.

View Article: PubMed Central - PubMed

Affiliation: Division of Diabetes Translation, Centers for Disease Control and Prevention, National Center for Chronic Disease and Health Promotion, 4770 Buford Highway, Mailstop K10, Atlanta, GA 30341, USA.

ABSTRACT
Background. The burden of cardiovascular disease (CVD) is increasing in low-to-middle income countries. We examined how socioeconomic and demographic characteristics may be associated with CVD risk factors and healthcare access in such countries. Methods. We extracted data from the World Health Organization's STEPwise approach to surveillance 2002 cross-sectional dataset from Pohnpei, Federated States of Micronesia (FSM). We used these data to estimate associations for socioeconomic position (education, income, and employment) and demographics (age, sex, and urban/rural) with CVD risk factors and with healthcare access, among a sample of 1638 adults (25-64 years). Results. In general, we found significantly higher proportions of daily tobacco use among men than women and respondents reporting primary-level education (<9 years) than among those with postsecondary education (>12 years). Results also revealed significant positive associations between paid employment and waist circumference and systolic blood pressure. Healthcare access did not differ significantly by socioeconomic position. Women reported significantly higher mean waist circumference than men. Conclusion. Our results suggest that socioeconomic position and demographic characteristics impact CVD risk factors and healthcare access in FSM. This understanding may help decision-makers tailor population-level policies and programs. The 2002 Pohnpei data provides a baseline; subsequent population health surveillance data might define trends.

No MeSH data available.


Related in: MedlinePlus