Caregiving and Place: Combining Geographic Information System (GIS) and Survey Methods to Examine Neighborhood Context and Caregiver Outcomes

Abstract

Abstract Background Little is known about the impact of neighborhood context on family caregivers, or how environmental factors combine with individual-level caregiver risk factors to affect caregiver outcomes. Objectives To combine Geographic Information System (GIS) and survey methods to examine the effects of caregiver residence in disadvantaged/underserved neighborhoods on caregiver outcomes. Research Design and Methods Telephone surveys with 758 caregivers from the Pittsburgh Regional Caregiver Survey geocoded for classification into Environmental Justice Areas (EJAs) and Medically Underserved Areas (MUAs). We examine the impact of EJA/MUA caregiver residence on care recipient unmet needs for care, caregiver depression and burden, and positive aspects of caregiving, adjusting for sociodemographics, caregiving context, care recipient disability level, caregiving intensity, and additional risk factors. Results There was spatial clustering of caregiver depression and burden outside of the disadvantaged/underserved areas, while positive aspects of caregiving were clustered within EJAs/MUAs. Approximately 36% of caregivers lived in EJAs/MUAs, and they differed, sociodemographically, on caregiver risk factors and caregiver outcomes. Multivariable models showed that caregivers residing in EJAs/MUAs were less likely to be depressed and reported more positive aspects of caregiving after adjusting for known individual-level risk factors. Residence in disadvantaged/underserved areas also modified the effects of several risk factors on caregiver outcomes. Discussion and Implications Caregiver outcomes show interesting spatial patterns. Unexpectedly, caregivers living in these potentially challenging environments were less depressed and reported more gains from caregiving after adjusting for known risk factors. Results suggest that socioeconomic disadvantage does not necessarily translate into poor caregiver outcomes. Understanding the mechanism for these effects is important to designing effective caregiver interventions. The paper also demonstrates the value of using GIS methods to study caregiving.