Department of Mathematical Demography & Statistics, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, 400088, India.
Department of Population Policies & Programmes, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, 400088, India.
BMC Pulm Med. 2020 Jul 14;20(1):190. doi: 10.1186/s12890-020-1124-z.
Asthma is one of the leading causes of disease burden when measured in terms of disability adjusted life years, despite low prevalence of self-reported cases among young women. This paper deals with the meso-scale correlates and spatial heterogeneity in the prevalence of self-reported Asthma across 640 districts in India, using a nationally representative sample of 699,686 women aged 15-49 years from all 36 States/UTs under NFHS-4 (2015-16).
Analytical methods used in this paper include multivariate logistic regression to examine the adjusted effects of various independent variables on self-reported Asthma and poor-rich ratios (PRR) and concentration index (CI) to understand the economic inequalities in the prevalence of Asthma. For the spatial analysis in the prevalence of Asthma, univariate and bivariate local Moran's I statistic have been computed in addition to measure of spatial autocorrelation and auto regression using spatial error and spatial lag models.
Results highlight that women's education was an important marker to the prevalence of Asthma. Smoking tobacco in any form among women were significantly more likely to suffer from Asthma. The prevalence of Asthma was further aggravated among women from the households without a separate room for kitchen, as well as those using unclean fuel for cooking. The poor-rich ratio in the prevalence of Asthma across various States/UTs in India depict inherent inequality. An analysis of spatial clustering in the prevalence of Asthma based on spatial autocorrelation portrays that Moran's I values were significant for improved source of drinking water, clean fuel used for cooking, and household environment. When spatial weights are taken into consideration, the autoregression model noticeably becomes stronger in predicting the prevalence of Asthma.
Any programmatic effort to curb the prevalence of Asthma through vertical interventions may hinge around the use of clean fuel, poverty, and lifestyle of subjects, irrespective of urban-rural place of their residence, environmental and ecological factors.
尽管年轻女性中自我报告的哮喘病例患病率较低，但从残疾调整生命年来衡量，哮喘是疾病负担的主要原因之一。本文使用来自 NFHS-4（2015-16 年）的来自印度所有 36 个邦/联邦属地的 699,686 名年龄在 15-49 岁的女性的全国代表性样本，研究了印度 640 个地区自我报告的哮喘流行率的中尺度相关性和空间异质性。
本文使用的分析方法包括多变量逻辑回归，以检查各种自变量对自我报告的哮喘和贫富比（PRR）的调整影响，以及集中指数（CI），以了解哮喘流行率的经济不平等。为了分析哮喘流行率的空间分布，除了使用空间误差和空间滞后模型计算空间自相关和自回归的单变量和双变量局部 Moran's I 统计量外，还计算了单变量和双变量局部 Moran's I 统计量。
结果突出表明，女性的教育是哮喘流行率的重要标志。女性以任何形式吸烟都更有可能患哮喘。没有单独的厨房房间的家庭以及使用不洁燃料做饭的妇女中，哮喘的患病率进一步加重。印度各邦/联邦属地哮喘流行率的贫富比表明存在内在不平等。基于空间自相关的哮喘流行率的空间聚类分析表明，Moran's I 值对于改善饮用水来源、用于烹饪的清洁燃料和家庭环境具有重要意义。当考虑空间权重时，自回归模型在预测哮喘流行率方面明显变得更强。
通过垂直干预来遏制哮喘流行率的任何计划工作都可能取决于清洁燃料的使用、贫困以及研究对象的生活方式，而不论其居住的城乡地点、环境和生态因素如何。
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