Income and Household Material Hardship in Children With Medical Complexity.

BACKGROUND AND OBJECTIVES: Household economic hardship negatively impacts child health but may not be adequately captured by income. We sought to determine the prevalence of household material hardship (HMH), a measure of household economic hardship, and to examine the relationship between household poverty and material hardship in a population of children with medical complexity. METHODS: We conducted a cross-sectional survey study of parents of children with medical complexity receiving primary care at a tertiary children's hospital. Our main predictor was household income as a percentage of the federal poverty limit (FPL): <50% FPL, 51% to 100% FPL, and >100% FPL. Our outcome was HMH measured as food, housing, and energy insecurity. We performed logistic regression models to calculate adjusted odds ratios of having ≥1 HMH, adjusted for patient and clinical characteristics from surveys and the Pediatric Health Information System. RESULTS: At least 1 material hardship was present in 40.9% of participants and 28.2% of the highest FPL group. Families with incomes <50% FPL and 51% to 100% FPL had ∼75% higher odds of having ≥1 material hardship compared with those with >100% FPL (<50% FPL: odds ratio 1.74 [95% confidence interval: 1.11-2.73], P = .02; 51% to 100% FPL: 1.73 [95% confidence interval: 1.09-2.73], P = .02). CONCLUSIONS: Poverty underestimated household economic hardship. Although households with incomes <100% FPL had higher odds of having ≥1 material hardship, one-quarter of families in the highest FPL group also had ≥1 material hardship.

Effectiveness of Screening for Household Gun Ownership in an Urban Primary Care Clinic.

Gun-related suicide and homicide are leading causes of death among children. Little is known about the effectiveness of screening for gun ownership in primary care. We examined positive gun ownership screens over a 2.5-year period in a pediatric primary care clinic. The main outcome was a positive screen for gun ownership. The main predictors included insurance type, neighborhood median income, number of clinic visits, and other social needs. Of 19 163 patients, 474 (2.5%) screened positive for gun ownership. Patients with private insurance and from higher income neighborhoods had 2 to 3 times higher odds of a positive screen. Patients with more visits and with food insecurity had approximately 2 to 4 times the odds of a positive screen for household gun ownership. In conclusion, the rate of positive gun ownership screens was very low and far below known gun ownership rates. Improved screening methods could better identify opportunities for gun safety advocacy.