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Abstract：
BACKGROUND: Short birth interval (SBI) has profound implications for the health of both mothers and children, yet there remains a notable dearth of studies addressing wealth-based inequality in SBI and its associated factors in India. This study aims to address this gap by investigating wealth-based disparities in SBI and identifying the underlying factors associated with SBI in India.
METHODS: We used information on 109,439 women of reproductive age (15-49 years) from the fifth round of the National Family Health Survey (2019-21). We assessed wealth-based inequality in SBI for India and its states using the Erreygers Normalised Concentration Index (ECI). Additionally, we used a multilevel binary logistic regression to assess the factors associated with SBI in India.
RESULTS: In India, the prevalence of SBI was 47.8% [95% CI: 47.4, 48.3] during 2019-21, with significant variation across states. Bihar reported the highest prevalence of SBI at 61.2%, while Sikkim the lowest at 18.1%. SBI prevalence was higher among poorer mothers compared to richer ones (Richest: 33.8% vs. Poorest: 52.9%). This wealth-based inequality was visible in the ECI as well (ECI= -0.13, p < 0.001). However, ECI varied considerably across the states. Gujarat, Punjab, and Manipur exhibited the highest levels of wealth-based inequality (ECI= -0.28, p < 0.001), whereas Kerala showed minimal wealth-based inequality (ECI= -0.01, p = 0.643). Multilevel logistic regression analysis identified several factors associated with SBI. Mothers aged 15-24 (OR: 12.01, p < 0.001) and 25-34 (2.92, < 0.001) were more likely to experience SBI. Women who married after age 25 (3.17, < 0.001) and those belonging to Scheduled Caste (1.18, < 0.001), Scheduled Tribes (1.14, < 0.001), and Other Backward Classes (1.12, < 0.001) also had higher odds of SBI. Additionally, the odds of SBI were higher among mothers in the poorest (1.97, < 0.001), poorer (1.73, < 0.001), middle (1.62, < 0.001), and richer (1.39, < 0.001) quintiles compared to the richest quintile. Women whose last child had passed away were also significantly more likely to have SBI (2.35, < 0.001). Furthermore, mothers from communities with lower average schooling levels (1.18, < 0.001) were more likely to have SBI. Geographically, mothers from eastern (0.67, < 0.001) and northeastern (0.44, < 0.001) regions of India were less likely to have SBI.
CONCLUSIONS: The significant wealth-based inequality in SBI in India highlights the need for targeted interventions focusing on economically disadvantaged women, particularly in states with high SBI prevalence. Special attention should be given to younger mothers and those from socially disadvantaged groups to enhance maternal and child health outcomes across the country.
METHODS: We used information on 109,439 women of reproductive age (15-49 years) from the fifth round of the National Family Health Survey (2019-21). We assessed wealth-based inequality in SBI for India and its states using the Erreygers Normalised Concentration Index (ECI). Additionally, we used a multilevel binary logistic regression to assess the factors associated with SBI in India.
RESULTS: In India, the prevalence of SBI was 47.8% [95% CI: 47.4, 48.3] during 2019-21, with significant variation across states. Bihar reported the highest prevalence of SBI at 61.2%, while Sikkim the lowest at 18.1%. SBI prevalence was higher among poorer mothers compared to richer ones (Richest: 33.8% vs. Poorest: 52.9%). This wealth-based inequality was visible in the ECI as well (ECI= -0.13, p < 0.001). However, ECI varied considerably across the states. Gujarat, Punjab, and Manipur exhibited the highest levels of wealth-based inequality (ECI= -0.28, p < 0.001), whereas Kerala showed minimal wealth-based inequality (ECI= -0.01, p = 0.643). Multilevel logistic regression analysis identified several factors associated with SBI. Mothers aged 15-24 (OR: 12.01, p < 0.001) and 25-34 (2.92, < 0.001) were more likely to experience SBI. Women who married after age 25 (3.17, < 0.001) and those belonging to Scheduled Caste (1.18, < 0.001), Scheduled Tribes (1.14, < 0.001), and Other Backward Classes (1.12, < 0.001) also had higher odds of SBI. Additionally, the odds of SBI were higher among mothers in the poorest (1.97, < 0.001), poorer (1.73, < 0.001), middle (1.62, < 0.001), and richer (1.39, < 0.001) quintiles compared to the richest quintile. Women whose last child had passed away were also significantly more likely to have SBI (2.35, < 0.001). Furthermore, mothers from communities with lower average schooling levels (1.18, < 0.001) were more likely to have SBI. Geographically, mothers from eastern (0.67, < 0.001) and northeastern (0.44, < 0.001) regions of India were less likely to have SBI.
CONCLUSIONS: The significant wealth-based inequality in SBI in India highlights the need for targeted interventions focusing on economically disadvantaged women, particularly in states with high SBI prevalence. Special attention should be given to younger mothers and those from socially disadvantaged groups to enhance maternal and child health outcomes across the country.
摘要：
背景：短出生间隔（SBI）对母亲和孩子的健康具有深远的影响，然而，在印度，解决SBI基于财富的不平等及其相关因素的研究仍然明显缺乏。这项研究旨在通过调查SBI中基于财富的差距并确定与印度SBI相关的潜在因素来解决这一差距。
方法：我们使用了来自第五轮全国家庭健康调查（2019-21）的109,439名育龄妇女（15-49岁）的信息。我们使用Erreygers归一化集中指数（ECI）评估了印度及其各州SBI的基于财富的不平等。此外,我们使用多水平二元逻辑回归来评估与印度SBI相关的因素。
结果：在印度，在2019-21年期间，SBI的患病率为47.8%[95%CI：47.4，48.3]，各州之间存在显著差异。比哈尔邦报告SBI的患病率最高，为61.2%，而锡金最低，为18.1%。与较富有的母亲相比，较贫穷的母亲的SBI患病率更高(最富有：33.8%与最贫穷：52.9%）。这种基于财富的不平等在ECI中也很明显(ECI=-0.13，p<0.001)。然而,ECI在各州之间差异很大。古吉拉特邦,旁遮普,曼尼普尔邦表现出最高水平的基于财富的不平等(ECI=-0.28，p<0.001)，而喀拉拉邦显示出最小的财富不平等（ECI=-0.01，p=0.643）。多水平Logistic回归分析确定了与SBI相关的几个因素。年龄在15-24岁（OR：12.01，p<0.001）和25-34岁（2.92，<0.001）的母亲更有可能经历SBI。25岁以后结婚的妇女（3.17，<0.001）和属于预定种姓的妇女（1.18，<0.001），预定部落（1.14，<0.001），和其他落后类别(1.12，<0.001)也有更高的SBI几率。此外,在最贫穷的母亲中，SBI的几率更高(1.97，<0.001)，较差（1.73，<0.001），中（1.62，<0.001），与最富有的五分之一相比，更富有(1.39，<0.001)五分之一。最后一个孩子去世的妇女也更有可能患有SBI（2.35，<0.001）。此外，来自平均受教育程度较低(1.18,<0.001)社区的母亲更有可能患有SBI.地理上,来自印度东部（0.67，<0.001）和东北部（0.44，<0.001）地区的母亲患SBI的可能性较小。
结论：印度SBI基于财富的严重不平等凸显了有针对性的干预措施的必要性，重点是经济上处于不利地位的妇女，特别是在SBI患病率较高的州。应特别注意年轻母亲和社会弱势群体的母亲，以改善全国的妇幼保健成果。
方法：我们使用了来自第五轮全国家庭健康调查（2019-21）的109,439名育龄妇女（15-49岁）的信息。我们使用Erreygers归一化集中指数（ECI）评估了印度及其各州SBI的基于财富的不平等。此外,我们使用多水平二元逻辑回归来评估与印度SBI相关的因素。
结果：在印度，在2019-21年期间，SBI的患病率为47.8%[95%CI：47.4，48.3]，各州之间存在显著差异。比哈尔邦报告SBI的患病率最高，为61.2%，而锡金最低，为18.1%。与较富有的母亲相比，较贫穷的母亲的SBI患病率更高(最富有：33.8%与最贫穷：52.9%）。这种基于财富的不平等在ECI中也很明显(ECI=-0.13，p<0.001)。然而,ECI在各州之间差异很大。古吉拉特邦,旁遮普,曼尼普尔邦表现出最高水平的基于财富的不平等(ECI=-0.28，p<0.001)，而喀拉拉邦显示出最小的财富不平等（ECI=-0.01，p=0.643）。多水平Logistic回归分析确定了与SBI相关的几个因素。年龄在15-24岁（OR：12.01，p<0.001）和25-34岁（2.92，<0.001）的母亲更有可能经历SBI。25岁以后结婚的妇女（3.17，<0.001）和属于预定种姓的妇女（1.18，<0.001），预定部落（1.14，<0.001），和其他落后类别(1.12，<0.001)也有更高的SBI几率。此外,在最贫穷的母亲中，SBI的几率更高(1.97，<0.001)，较差（1.73，<0.001），中（1.62，<0.001），与最富有的五分之一相比，更富有(1.39，<0.001)五分之一。最后一个孩子去世的妇女也更有可能患有SBI（2.35，<0.001）。此外，来自平均受教育程度较低(1.18,<0.001)社区的母亲更有可能患有SBI.地理上,来自印度东部（0.67，<0.001）和东北部（0.44，<0.001）地区的母亲患SBI的可能性较小。
结论：印度SBI基于财富的严重不平等凸显了有针对性的干预措施的必要性，重点是经济上处于不利地位的妇女，特别是在SBI患病率较高的州。应特别注意年轻母亲和社会弱势群体的母亲，以改善全国的妇幼保健成果。
