Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance

The existence of excess zeros in the distribution of antenatal care (ANC) visits in Bangladesh raises the research question of whether there are two separate generating processes in taking ANC and the frequency of ANC. Thus the main objective of this study is to identify a proper count regression model for the number of ANC visits by pregnant women in Bangladesh covering the issues of overdispersion, zero-inflation, and intra-cluster correlation with an additional objective of determining risk factors for ANC use and its frequency. The data have been extracted from the nationally representative 2014 Bangladesh Demographic and Health Survey, where 22% of the total 4493 women did not take any ANC during pregnancy. Since these zero ANC visits can be either structural or sampling zeros, two-part zero-inflated and hurdle regression models are investigated along with the standard one-part count regression models. Correlation among response values has been accounted for by incorporating cluster-specific random effects in the models. The hurdle negative binomial regression model with cluster-specific random intercepts in both the zero and the count part is found to be the best model according to various diagnostic tools including likelihood ratio and uniformity tests. The results show that women who have poor education, live in poor households, have less access to mass media, or belong to the Sylhet and Chittagong regions are less likely to use ANC and also have fewer ANC visits. Additionally, women who live in rural areas, depend on family members’ decisions to take health care, and have unintended pregnancies had fewer ANC visits. The findings recommend taking both cluster-specific random effects and overdispersion and zero-inflation into account in modelling the ANC data of Bangladesh. Moreover, safe motherhood programmes still need to pay particular attention to disadvantaged and vulnerable subgroups of women.

孟加拉国产前保健（Antenatal Care, ANC）就诊次数的分布中存在过量零值，这一现象引发了如下研究问题：孕妇接受产前保健的行为与就诊频率是否分属两种独立的生成过程？因此本研究的核心目标是，为孟加拉国孕妇的产前保健就诊次数筛选适配的计数回归模型，同时覆盖过度离散、零膨胀与组内相关三类建模问题；附加目标则为明确产前保健使用及其就诊频率的风险影响因素。本研究数据取自具有全国代表性的2014年孟加拉国人口与健康调查（Demographic and Health Survey），在全部4493名受访孕妇中，有22%的女性在孕期未接受任何产前保健服务。由于这类零就诊记录可分为结构性零值与抽样性零值两类，因此本研究除考察标准单部分计数回归模型外，还对两部分零膨胀模型与障碍回归模型进行了分析。研究通过在模型中纳入组特异性随机效应，对响应变量间的组内相关进行了控制。基于似然比检验、均匀性检验等多种诊断工具的评估结果，同时在零值部分与计数部分均设置组特异性随机截距的障碍负二项回归模型，被确定为最优模型。分析结果显示，受教育程度较低、家庭经济状况不佳、接触大众媒体机会有限，或是居住在锡尔赫特与吉大港地区的女性，其使用产前保健服务的概率更低，且实际就诊次数也更少。此外，居住在农村地区、依赖家庭成员做出医疗决策、以及非计划妊娠的孕妇，其产前保健就诊次数同样相对偏少。本研究结果建议，在对孟加拉国产前保健就诊数据进行建模时，应同时考虑组特异性随机效应、过度离散与零膨胀三类特征。此外，安全孕产项目仍需重点关注处境不利与弱势的女性亚群体。