Women's health issues : official publication of the Jacobs Institute of Women's Health · 2012
Multilevel analysis of the determinants of receipt of clinical preventive services among reproductive-age women.
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McCall-Hosenfeld Jennifer S, Weisman Carol S, Camacho Fabian, Hillemeier Marianne M, Chuang Cynthia H
Аннотация
BACKGROUND: We investigated the impact of individual- and county-level contextual variables on women's receipt of a comprehensive panel of preventive services in a region that includes both urban and rural communities.
METHODS: Outcome variables were a screening and vaccination index (a count of Papanicolaou test, blood pressure check, lipid panel, sexually transmitted infections [STI] or HIV test, and influenza vaccination received in the past 2 years) and a preventivecounseling index (a count of topics discussed in the past 2 years: Smoking and tobacco, alcohol or drugs, violence and safety, pregnancy planning or contraception, diet/nutrition, and STIs). Contextual covariates from the Area Resource File (2004-2005) were appended to prospective survey data from the Central Pennsylvania Women's Health Study. Individual-level variables included predisposing, enabling, and need-based measures. Contextual variables included community characteristics and healthcare resources, including a measure of primary care physician (PCP) density specifically designed for this study of women's preventive care. Multilevel analyses were performed.
RESULTS: We found low overall use of preventive services. In multilevel models, individual-level factors predicted receipt of both screening and vaccinations and counseling services; significant predictors differed for each index. One contextual variable (PCP density) predicted receipt of screenings and vaccinations.
CONCLUSIONS: Women's receipt of preventive services was determined primarily by individual-level variables. Different variables predicted receipt of screening and vaccination versus counseling services. A contextual measure, PCP density, predicted receipt of preventive screenings and vaccinations. Individual variability in women's receipt of counseling services is largely explained by psychosocial factors and seeing an obstetrician-gynecologist.
METHODS: Outcome variables were a screening and vaccination index (a count of Papanicolaou test, blood pressure check, lipid panel, sexually transmitted infections [STI] or HIV test, and influenza vaccination received in the past 2 years) and a preventivecounseling index (a count of topics discussed in the past 2 years: Smoking and tobacco, alcohol or drugs, violence and safety, pregnancy planning or contraception, diet/nutrition, and STIs). Contextual covariates from the Area Resource File (2004-2005) were appended to prospective survey data from the Central Pennsylvania Women's Health Study. Individual-level variables included predisposing, enabling, and need-based measures. Contextual variables included community characteristics and healthcare resources, including a measure of primary care physician (PCP) density specifically designed for this study of women's preventive care. Multilevel analyses were performed.
RESULTS: We found low overall use of preventive services. In multilevel models, individual-level factors predicted receipt of both screening and vaccinations and counseling services; significant predictors differed for each index. One contextual variable (PCP density) predicted receipt of screenings and vaccinations.
CONCLUSIONS: Women's receipt of preventive services was determined primarily by individual-level variables. Different variables predicted receipt of screening and vaccination versus counseling services. A contextual measure, PCP density, predicted receipt of preventive screenings and vaccinations. Individual variability in women's receipt of counseling services is largely explained by psychosocial factors and seeing an obstetrician-gynecologist.
Предметные рубрики MeSH
AdolescentAdultCounselingFemaleHealth BehaviorHealth Knowledge, Attitudes, PracticeHealth Services AccessibilityHealth SurveysHumansMass ScreeningMiddle AgedMultilevel AnalysisPennsylvaniaPopulation SurveillancePreventive Health ServicesReproductive Health ServicesRural PopulationSocial SupportSocioeconomic FactorsUrban PopulationVaccinationYoung Adult