当前位置: X-MOL 学术Spatial Demography › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Spatial Variation in Contraceptive Practice Across the Districts of India, 1998–2016
Spatial Demography Pub Date : 2021-08-19 , DOI: 10.1007/s40980-021-00092-9
Shareen Joshi 1 , Uttamacharya 2 , Kakoli Borkotoky 3 , Abhishek Gautam 3 , Nitin Datta 3 , Pranita Achyut 3 , Priya Nanda 4 , Ravi Verma 3
Affiliation  

India is currently one of the most demographically diverse regions of the world. Fertility and mortality rates are known to show considerable variation at the level of regions, states and districts. Little is known however, about the spatial variations of the contraceptive usage—a critical variable that is relevant to fertility as well as health policy. This paper uses data from four national population-based household surveys conducted between 1998 and 2016 to explore district-level variations in the contraceptive prevalence rate. We find no clear evidence of convergence. The gap between the best and worst performing districts is more than 70 percent across the four rounds and does not diminish over time. We also find considerable evidence of spatial clustering across districts. Districts with high prevalence concentrate in Southern states and more recently, in the Northeast of the country. Our analysis suggests that female literacy and health care infrastructure are important correlates of spatial clusters. This suggests that investments in women’s human capital and health-care infrastructure play a role in expanding women’s opportunities to time their births.



中文翻译:

1998-2016 年印度各地区避孕实践的空间变化

印度目前是世界上人口最多样化的地区之一。众所周知,生育率和死亡率在地区、州和地区的水平上表现出相当大的差异。然而,人们对避孕药具使用的空间变化知之甚少——这是一个与生育率和健康政策相关的关键变量。本文使用 1998 年至 2016 年间进行的四次全国人口家庭调查的数据来探索避孕普及率的地区级差异。我们没有发现收敛的明确证据。在四轮比赛中,表现最好和最差的地区之间的差距超过 70%,并且不会随着时间的推移而缩小。我们还发现了跨地区空间聚集的大量证据。流行率高的地区集中在南部各州,最近在该国东北部。我们的分析表明,女性识字率和医疗保健基础设施是空间集群的重要相关因素。这表明,对女性人力资本和医疗保健基础设施的投资在扩大女性的生育机会方面发挥了作用。

更新日期:2021-08-19
down
wechat
bug