Malamardi Sowmya, Lambert Katrina, Siddaiah Jayaraj Biligere, Erbas Bircan, Mahesh Padukudru Anand
Department of Public Health, School of Psychology & Public Health, College of Science Health and Engineering, La Trobe University, Melbourne, VIC 3083, Australia.
Department of Respiratory Medicine, JSS Academy of Higher Education & Research (JSSAHER), JSS Medical College, Mysore 570015, Karnataka, India.
Children (Basel). 2023 Jul 31;10(8):1322. doi: 10.3390/children10081322.
Air pollutants are known to trigger asthma and wheezing-associated lower respiratory infections in children, but evidence regarding their effect on hospital admissions in India is limited. We conducted a time-series study over a period of five years to assess the role of ambient air pollutants in daily asthma-related hospital admissions in children in Mysore, India. Daily asthma and wheeze (associated with lower respiratory infections) admissions were modelled using a generalised additive model (GAM) to examine the non-linear effects and generalised linear models (GLM) for linear effects, if any. Models were adjusted by day of the week and lag days, with smooth terms for time, maximum temperature, and relative humidity, and they were stratified by sex and age group. Of the 362 children admitted, more than 50% were boys, and the mean age was 5.34 years (±4.66). The GAMs showed non-linear associations between NO, PM, and NH. For example, a 10 µgm (or 10%) increase in NO increased admissions by 2.42. These non-linear effects were more pronounced in boys. A linear effect was detected for PM with a relative risk (95% CI) of 1.028, 1.013, and 1.043 with admission. Further research is needed to explore whether these findings can be replicated in different cities in India. Air pollution needs to be controlled, and policies that focus on lower cut-off levels for vulnerable populations are necessary.
已知空气污染物会引发儿童哮喘和与喘息相关的下呼吸道感染，但关于其对印度住院率影响的证据有限。我们进行了一项为期五年的时间序列研究，以评估环境空气污染物在印度迈索尔儿童每日哮喘相关住院病例中的作用。使用广义相加模型（GAM）对每日哮喘和喘息（与下呼吸道感染相关）住院病例进行建模，以检验非线性效应；对于线性效应（如有），则使用广义线性模型（GLM）。模型按星期几和滞后天数进行调整，对时间、最高温度和相对湿度设置平滑项，并按性别和年龄组进行分层。在362名住院儿童中，超过50%为男孩，平均年龄为5.34岁（±4.66）。GAM显示，一氧化氮（NO）、颗粒物（PM）和氨气（NH）之间存在非线性关联。例如，NO每增加10微克/立方米（或10%），住院率就会增加2.42。这些非线性效应在男孩中更为明显。检测到PM存在线性效应，入院时相对风险（95%置信区间）分别为1.028、1.013和1.043。需要进一步研究，以探讨这些发现能否在印度不同城市得到重复验证。空气污染需要得到控制，制定针对弱势群体更低临界值的政策很有必要。
