Get access

Disparities in Primary Care for Vulnerable Children: The Influence of Multiple Risk Factors

Authors

  • Gregory D. Stevens,

    Search for more papers by this author
    • Address correspondence to Gregory D. Stevens, Ph.D., M.H.S, Division of Community Health, USC Keck School of Medicine, 1000 South Fremont Avenue, Building A7, Room 7411, Alhambra, CA. Michael Seid, Ph.D., is with the RAND Corp., Santa Monica, CA; Ritesh Mistry, Ph.D., M.P.H, is with the Division of Cancer Prevention and Control Research, UCLA School of Public Health, Jonsson Comprehensive Cancer Center, Los Angeles, CA. Neal Halfon, M.D., M.P.H, is with the Center for Healthier Children, Families, and Communities, UCLA Schools of Medicine and Public Health, 1100 Glendon Ave, Suite 850, Los Angeles, CA.

  • Michael Seid,

  • Ritesh Mistry,

  • Neal Halfon


Abstract

Objectives. To analyze vulnerability as a profile of multiple risk factors for poor pediatric care based on race/ethnicity, poverty status, parent education, insurance, and language. Profiles are used to examine disparities in child/adolescent health status and primary care experience.

Data Sources. Cross-sectional data on 19,485 children/adolescents 0–19 years of age from the 2001 California Health Interview Survey.

Study Design. Multiple logistic regression models are used to examine risk profiles in relation to health status and three aspects of primary care: access (physician and dental visit; access surety), continuity (regular source of care), and comprehensiveness (i.e., health promotion counseling).

Principal Findings. About 43 percent of (or 4.4 million) children in California have two or more risk factors (RF). Controlling for age and gender, more RFs is associated with poorer health status (i.e. percent reporting “excellent/very good” health: no RFs=81 percent, 1=71 percent, 2=57 percent, 3=45 percent, 4=35 percent, 5=28 percent, all p<.001). Controlling for health status, higher risk profiles is associated with poorer primary care access and continuity, but greater comprehensiveness of care. For example, higher risk profile children are less likely to have a regular source of care: one RF (prevalence ratio [PR]=0.92, confidence interval [CI]: 0.86–0.98), two (PR=0.77, CI: 0.69–0.84), three (PR=0.55, CI: 0.46–0.65), and four or more (PR=0.31, CI: 0.22–0.44), all p<.001.

Conclusions. This study demonstrates a dose–response relationship of higher risk profiles with poorer child health status, access to, and continuity of primary care. Having gained access, however, adolescents with higher risk profiles are more likely to receive health promotion counseling. Higher profiles appear to be associated with greater barriers to accessing primary care for children in “fair or poor” health, suggesting that vulnerable children who have the greatest health care needs also have the greatest difficulty obtaining primary care.

Ancillary