Shedding Light on the Mechanisms Underlying Health Disparities Through Community Participatory Methods: The Stress Pathway.

Health disparities are large and persistent gaps in the rates of disease and death between racial/ethnic and socioeconomic status subgroups in the population. Stress is a major pathway hypothesized to explain such disparities. The Eunice Kennedy Shriver National Institute of Child Health and Human Development formed a community/research collaborative-the Community Child Health Network-to investigate disparities in maternal and child health in five high-risk communities. Using community participation methods, we enrolled a large cohort of African American/Black, Latino/Hispanic, and non-Hispanic/White mothers and fathers of newborns at the time of birth and followed them over 2 years. A majority had household incomes near or below the federal poverty level. Home interviews yielded detailed information regarding multiple types of stress such as major life events and many forms of chronic stress including racism. Several forms of stress varied markedly by racial/ethnic group and income, with decreasing stress as income increased among Caucasians but not among African Americans; other forms of stress varied by race/ethnicity or poverty alone. We conclude that greater sophistication in studying the many forms of stress and community partnership is necessary to uncover the mechanisms underlying health disparities in poor and ethnic-minority families and to implement community health interventions

Neighbourhood-level deprivation indices and postpartum women’s health: results from the Community Child Health Network (CCHN) multi-site study

Abstract Background Area-level socioeconomic characteristics have been shown to be related to health status and mortality however, little is known about the association between residential community characteristics in relation to postpartum women’s health. Methods Data from the longitudinal, multi-site Community Child Health Network (CCHN) study were used. Postpartum women (n = 2510), aged 18–40 were recruited from 2008 to 2012 within a month of delivery. Socioeconomic data was used to create deprivation indices. Census data were analysed using principal components analysis (PCA) and logistic regression to assess the association between deprivation indices (DIs) and various health indicators. Results PCA resulted in two unique DIs that accounted for 67.5% of the total variance of the combined all-site area deprivation. The first DI was comprised of variables representing a high percentage of Hispanic or Latina, foreign-born individuals, dense households (more than one person per room of residence), with less than a high-school education, and who spent more than 30% of their income on housing costs. The second DI was comprised of a high percentage of African-Americans, single mothers, and high levels of unemployment. In a multivariate logistic regression model, using the quartiles of each DI, women who reside in the geographic area of Q4-Q2 of the second DI, were almost twice as likely to have more than three adverse health conditions compared to those who resided in the least deprived areas. (Q2vs.Q1:OR = 2.09,P = 0.001,Q3vs.Q1:OR = 1.89,P = 0.006,Q4vs.Q1:OR = 1.95,P = 0.004 respectively). Conclusions Our results support the utility of examining deprivation indices as predictors of maternal postpartum health

Neighbourhood-level deprivation indices and postpartum women's health: results from the Community Child Health Network (CCHN) multi-site study.

BackgroundArea-level socioeconomic characteristics have been shown to be related to health status and mortality however, little is known about the association between residential community characteristics in relation to postpartum women's health.MethodsData from the longitudinal, multi-site Community Child Health Network (CCHN) study were used. Postpartum women (n = 2510), aged 18-40 were recruited from 2008 to 2012 within a month of delivery. Socioeconomic data was used to create deprivation indices. Census data were analysed using principal components analysis (PCA) and logistic regression to assess the association between deprivation indices (DIs) and various health indicators.ResultsPCA resulted in two unique DIs that accounted for 67.5% of the total variance of the combined all-site area deprivation. The first DI was comprised of variables representing a high percentage of Hispanic or Latina, foreign-born individuals, dense households (more than one person per room of residence), with less than a high-school education, and who spent more than 30% of their income on housing costs. The second DI was comprised of a high percentage of African-Americans, single mothers, and high levels of unemployment. In a multivariate logistic regression model, using the quartiles of each DI, women who reside in the geographic area of Q4-Q2 of the second DI, were almost twice as likely to have more than three adverse health conditions compared to those who resided in the least deprived areas. (Q2vs.Q1:OR = 2.09,P = 0.001,Q3vs.Q1:OR = 1.89,P = 0.006,Q4vs.Q1:OR = 1.95,P = 0.004 respectively).ConclusionsOur results support the utility of examining deprivation indices as predictors of maternal postpartum health