Family income gradients in the health and health care access of US children.
This study sought to examine the shape and magnitude of family income gradients in US children's health, access to care, and use of services. We analyzed cross-sectional data from the 2003 National Survey of Children's Health, a telephone survey of 102,353 parents of children aged 0-17 years. Associations between family income [Below 100% Federal Poverty Level (FPL), 100-199% FPL, 200-299% FPL, 300-399% FPL, 400% FPL or Greater] and a set of 32 health and health care indicators were examined using linear polynomial testing and multivariate logistic regression. The percentage of children in better health increased with family income for 15 health outcomes. In multivariate logistic regression models that controlled for health insurance coverage and socio-demographic confounders, odds ratios >2 comparing the lowest to the highest income groups were noted for health conditions across both physical and developmental domains (diabetes, headaches, ear infections, learning disabilities, behavior/conduct problems, speech problems). Parent-reported global child health status, activity limitation, and oral health status showed steeper gradients than specific chronic and acute conditions. Ten measures of health care access and utilization were associated with family income in multivariate logistic regression models. Income gradients are pervasive across many health indicators at an early age. Social and health policy interventions are needed to address the multitude of factors that can affect children's health and initiate disparities in development.
Larson
Kandyce
K
UCLA Center for Healthier Children, Families, and Communities, 10990 Wilshire Boulevard, Suite 900, Los Angeles, CA 90024, USA. kandyce@ucla.edu
Halfon
Neal
N
D000293:Adolescent; D002648:Child; D002662:Child Health Services / Q000191:economics / Q000706:statistics & numerical data; D002669:Child Welfare / Q000706:statistics & numerical data*; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D019538:Health Care Surveys; D006297:Health Services Accessibility / Q000191:economics*; D006301:Health Services Needs and Demand; D054624:Health Status Disparities; D006306:Health Surveys; D054625:Healthcare Disparities; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D007223:Infant; D016014:Linear Models; D016015:Logistic Models; D009017:Morbidity; D015999:Multivariate Analysis; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology