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Background: This paper explores the heterogeneities in antenatal care (ANC) utilization in India's most populated state, Uttar Pradesh. Taking an intersectionality lens, multiple individual- and district-level factors are used to identify segments of any antenatal care usage in Uttar Pradesh Objective: This paper seeks to understand the multilevel contexts of ANC utilization. The planning and programming challenge is that such knowledge of contextual specificity is rarely known upfront at the initial stages of planning or implementing an intervention. Exploratory data analysis might be needed to identify such contextual specificity. Methods: Tree-structured regression methods are used to identify segments and interactions between factors. The results from the tree-structured regression were complemented with multilevel models that controlled for the clustering of individuals within districts. Results: Heterogeneities in utilization of any ANC were observed. The multiple segments of ANC utilization that were developed went from a low utilization of 23.7% for respondents who were not literate and did not have home ownership to a high of 82.4% for respondents who were literate and at the highest level of wealth. Key variables that helped define the segments of ANC utilization include: woman's literacy, ownership of home, wealth index, and district-level sex ratio. Based on the multilevel model of any ANC utilization, cross-level interactions also were obtained between sex ratio and ownership of home as well as between sex ratio and literacy. Increases in sex ratio increased the influence of ownership of home on any ANC, while increases in sex ratio reduced the impact of woman's literacy on receiving any ANC. Conclusion: We argue that a focus on heterogeneous segments of utilization can help build knowledge of the mechanisms that underlie inequities in maternal health utilization. Such knowledge of heterogeneity needs to be incorporated in contextualizing interventions to meet a variety of recipients' needs. [ABSTRACT FROM AUTHOR]

Background:This paper explores the multilevel factors associated with maternal health utilization in India’s most populous state, Uttar Pradesh. 3 key utilization practices: registration of pregnancy, receipt of antenatal care, and delivery at home are examined for district and individual level predictors. The data is based on 5666 household surveys conducted as part of a baseline evaluation of the Uttar Pradesh Technical Support Unit (UPTSU.) program. Objectives:This intervention aims to assist the Government of Uttar Pradesh in increasing the efficiency, effectiveness, and equity of service delivery across a continuum of reproductive, maternal, new-born, child, and adolescent health (RMNCH+A) outcomes. Methods:The paper employs multilevel models that control for individuals being nested within districts in order to understand the predictors of maternal health care utilization. Results:The study identifies several individual-level predictors of health care utilization, including: literacy of the woman, the husband’s schooling, age at marriage, and socio-economic factors. Key predictors of pregnancy registration include husband’s schooling (OR 1.49, 95% CI 1.26–1.76), having a bank account (OR 1.36, 95% CI 1.11–1.68), and owning a house (OR 2.28, 95% CI 1.85–2.80). Factors affecting antenatal care include the woman’s literacy (OR 1.49, 95% CI 1.28–1.73), the respondent having had a job in the last year (OR 1.39, 95% CI 1.10–1.77), and owning a house (OR 2.83, 95% CI 2.27–3.53). Home delivery tends to be associated with woman’s literacy (OR 0.62, 95% CI 0.54–0.72) and marriage age of 15 and younger (OR 1.48, 95% CI 1.26–1.73). Conclusions:Interventions having equity considerations need to disrupt existing patterns of the health gradient. Successful implementation of such interventions, necessitate understanding the mechanisms that can disrupt the unequal utilization patterns and target domains of disadvantage. Knowledge of key predictors of utilization can aid in the implementation of such complex interventions. [ABSTRACT FROM PUBLISHER]