Multiple vulnerabilities and maternal healthcare in Vietnam: findings from the Multiple Indicator Cluster Surveys,
Hoang Van Minh1, Juhwan Oh2, Kim Bao Giang3
1Hanoi School of Public Health, Hanoi, Vietnam; hvm@hsph.edu.vn.
Background:
Knowledge of the aggregate effects of multiple socioeconomic vulnerabilities is important for shedding light on the determinants of growing health inequalities and inequities in maternal healthcare.
Objective:
This paper describes patterns of inequity in maternal healthcare utilization and analyzes associations between inequity and multiple socioeconomic vulnerabilities among women in Vietnam.
Design:
This is a repeated cross-sectional study using data from the Vietnam Multiple Indicator Cluster Surveys 2000, 2006, and 2011. Two maternal healthcare indicators were selected: (1) skilled antenatal care and (2) skilled delivery care. Four types of socioeconomic vulnerabilities - low education, ethnic minority, poverty, and rural location - were assessed both as separate explanatory variables and as composite indicators (combinations of three and four vulnerabilities). Pairwise comparisons and adjusted odds ratios were used to assess socioeconomic inequities in maternal healthcare.
Results:
In all three surveys, there were increases across the survey years in both the proportions of women who received antenatal care by skilled staff (68.6% in 2000, 90.8% in 2006, and 93.7% in 2011) and the proportions of women who gave birth with assistance from skilled staff (69.9% in 2000, 87.7% in 2006, and 92.9% in 2011). The receipt of antenatal care by skilled staff and birth assistance from skilled health personnel were less common among vulnerable women, especially those with multiple vulnerabilities.
Conclusions:
Even though Vietnam has improved its coverage of maternal healthcare on average, policies should target maternal healthcare utilization among women with multiple socioeconomic vulnerabilities. Both multisectoral social policies and health policies are needed to tackle multiple vulnerabilities more effectively by identifying those who are poor, less educated, live in rural areas, and belong to ethnic minority groups.
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