Reproductive Health Challenges and Statistical Modeling in North East India: Addressing Socio-Cultural and Healthcare Disparities
Keywords:
North East India, statistical modeling, reproductive health, healthcare disparities, cultural practices.Abstract
North East India presents a unique landscape for studying reproductive health due to its ethnic diversity, socio-economic disparities, and distinct cultural practices. Challenges such as early marriage, limited healthcare access, and pronounced socio-economic inequalities have profound implications for reproductive health outcomes, including maternal and child health. Early marriage, prevalent across the region, leads to early childbearing, affecting fertility rates and perpetuating cycles of poor health and economic limitations. Cultural norms, deeply rooted in diverse ethnic traditions, significantly influence family planning decisions and contraceptive use. Simultaneously, healthcare access disparities, exacerbated by rural isolation and inadequate infrastructure, further hinder equitable health outcomes. Statistical modeling has become a cornerstone in addressing these multifaceted challenges by providing critical insights and guiding targeted interventions. Age-structured models have successfully analysed the effects of early marriage and cultural norms on fertility trends, while fertility transition models offer insights into the shifts from high to low fertility rates in the context of socio-economic developments. Stochastic models effectively capture regional disparities and uncertainties in healthcare access, offering valuable insights into demographic variability. Agent-based models (ABMs) simulate the complex interactions between cultural, socio-economic, and individual factors, providing nuanced perspectives on reproductive health dynamics. Despite their utility, statistical models face challenges, including inconsistent data quality and the need for cultural integration. Continuous calibration and validation of models are essential to maintain their relevance in a rapidly changing socio-economic context. Future advancements require robust data collection systems and the incorporation of regional cultural and socio-economic characteristics. Collaborative efforts involving local communities and experts are crucial for ensuring that models reflect regional realities and contribute to informed public health strategies and policy decisions tailored to North East India’s unique needs.