Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura.
Department of Pathology, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura.
Geospat Health. 2022 Nov 29;17(2). doi: 10.4081/gh.2022.1110.
We provide a novel approach to understanding the multiple causations of maternal anaemia in a geospatial context, highlighting how genetics, environment and socioeconomic disparities at the micro-geographical level lead to the inequitable distribution of anaemia. All first-trimester pregnant women registered for the antenatal care programme in Anuradhapura District, Sri Lanka from July to September 2019 were invited to the Rajarata Pregnancy Cohort (RaPCo), which assessed the prevalence of anaemia in early pregnancy. The combination of the prevalence of anaemia and minor haemoglobinopathy-related anaemia (MHA) with the poverty headcount index of the 22 health divisions in the district was investigated using GeoDa spatial K-means clustering. Sociodemographic and economic data at the divisional level were compared between identified clusters. Combining the analysis with the geographical and environmental characteristics of the region, further hypotheses regarding anaemia in this community were formulated. The study included data from 3,137 pregnant women in early pregnancy. The anaemia and MHA prevalence varied from 13.6 to 21.7% and from 2.6% to 5%, respectively. We identified four distinct spatial clusters. The cluster with the highest anaemia prevalence also included high poverty and the highest prevalence of MHA. The clusters had significant differences with regard to ethnic distribution, access to water, sanitation and dietary patterns. Areas supplied by major irrigation projects had significantly low levels of anaemia, probably attributable to internal migration and improved livelihood. It was evident that genetic, socioeconomic and environmental risk factors were grouped at the divisional level, and that their complex interactions make controlling anaemia with blanket interventions unsuccessful. Analysis of the distribution of heterogeneous risk factors at the micro-geospatial level helped identify context-specific approaches to tackle anaemia in pregnancy.
我们提供了一种新颖的方法来理解地理空间背景下孕产妇贫血的多种病因，强调了遗传因素、环境因素和微观地理水平上的社会经济差异如何导致贫血的不平等分布。2019 年 7 月至 9 月，斯里兰卡阿努拉达普拉区所有登记参加产前保健计划的初孕妇女都被邀请参加拉贾拉特卡妊娠队列（RaPCo），该队列评估了早孕期间贫血的患病率。使用 GeoDa 空间 K-均值聚类法，调查了该地区 22 个卫生分区的贫血患病率和轻微血红蛋白病相关贫血（MHA）与贫困人数指数的组合。比较了确定聚类之间的分区一级的社会人口和经济数据。将分析与该地区的地理和环境特征相结合，进一步提出了该社区贫血的假设。该研究包括了 3137 名早孕孕妇的数据。贫血和 MHA 的患病率从 13.6%到 21.7%不等，从 2.6%到 5%不等。我们确定了四个不同的空间聚类。贫血患病率最高的聚类还包括高贫困和最高的 MHA 患病率。这些聚类在族裔分布、获得水、卫生设施和饮食模式方面存在显著差异。主要灌溉项目供应的地区贫血水平显著较低，这可能归因于内部迁移和生计改善。显然，遗传、社会经济和环境风险因素在分区一级分组，其复杂的相互作用使得使用全面干预措施控制贫血不成功。在微观地理空间层面分析异质风险因素的分布有助于确定针对妊娠贫血的具体情况的方法。
