Prior studies have suggested that women’s empowerment is highly associated with women’s health behavior; however, only a limited number of studies have developed the measurement of women’s empowerment and provided empirical evidence to understand the relationship between women’s empowerment and health behavior. This study is a two-year study for the women in Cambodia. In the first year, this study will develop the measurement model of women’s empowerment. In the second year, this study will use geographical information system and spatial analysis to understand the spatial distribution of maternal health service utilization and examine the relationships between women’s empowerment, socioeconomic factors as well as maternal service utilization. Data come from the 2014 Cambodia Demographic and Health Survey. This survey employed a two-stage stratified sampling design. The sampling design first randomly selected clusters by probability proportional to their size. The second stage selected households using a systematic probability sampling method . The final sample size includes 611 communities and 17,578women. Interpersonal interviews were conducted using a structured questionnaire with women aged 15-49. Geographic coordinates of the community centroids were also collected for the purpose of geocoding with other data. The outcome variables include antenatal care, postnatal care, and health facility delivery. The individual-level women’s empowerment includes four domains including labor force participation, decision making, family planning, and education level. The community-level empowerment is based on the aggregation of individual empowerment scores to the community level. This study will also control for other individual-level and community-level confounding factors. This study will use confirmatory factor analysis in the development of the measurement of women’s empowerment. This study then uses Geographic Information System (GIS) to create maps and calculate Local Indicators of Spatial Association (LISA). This study will further combine spatial error regression models and multilevel models to analyze the relationship between explanatory variables and outcomes.
|Effective start/end date||8/1/17 → 7/31/18|
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.