{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:27:52Z","timestamp":1787027272733,"version":"build-2736575974"},"reference-count":60,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T00:00:00Z","timestamp":1670889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>In India, acute respiratory infections (ARIs) are a leading cause of mortality in children under 5 years. Mapping the hotspots of ARIs and the associated risk factors can help understand their association at the district level across India.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Data on ARIs in children under 5 years and household variables (unclean fuel, improved sanitation, mean maternal BMI, mean household size, mean number of children, median months of breastfeeding the children, percentage of poor households, diarrhea in children, low birth weight, tobacco use, and immunization status of children) were obtained from the National Family Health Survey-4. Surface and ground-monitored PM\n                      <jats:sub>2.5<\/jats:sub>\n                      and PM\n                      <jats:sub>10<\/jats:sub>\n                      datasets were collected from the Global Estimates and National Ambient Air Quality Monitoring Programme. Population density and illiteracy data were extracted from the Census of India. The geographic information system was used for mapping, and ARI hotspots were identified using the Getis-Ord Gi\n                      <jats:sup>*<\/jats:sup>\n                      spatial statistic. The quasi-Poisson regression model was used to estimate the association between ARI and household, children, maternal, environmental, and demographic factors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Acute respiratory infections hotspots were predominantly seen in the north Indian states\/UTs of Uttar Pradesh, Bihar, Delhi, Haryana, Punjab, and Chandigarh, and also in the border districts of Uttarakhand, Himachal Pradesh, and Jammu and Kashmir. There is a substantial overlap among PM\n                      <jats:sub>2.5<\/jats:sub>\n                      , PM\n                      <jats:sub>10<\/jats:sub>\n                      , population density, tobacco smoking, and unclean fuel use with hotspots of ARI. The quasi-Poisson regression analysis showed that PM\n                      <jats:sub>2.5<\/jats:sub>\n                      , illiteracy levels, diarrhea in children, and maternal body mass index were associated with ARI.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      To decrease ARI in children, urgent interventions are required to reduce the levels of PM\n                      <jats:sub>2.5<\/jats:sub>\n                      and PM\n                      <jats:sub>10<\/jats:sub>\n                      (major environmental pollutants) in the hotspot districts. Furthermore, improving sanitation, literacy levels, using clean cooking fuel, and curbing indoor smoking may minimize the risk of ARI in children.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2022.906248","type":"journal-article","created":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T01:30:40Z","timestamp":1670895040000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["Spatial epidemiology of acute respiratory infections in children under 5 years and associated risk factors in India: District-level analysis of health, household, and environmental datasets"],"prefix":"10.3389","volume":"10","author":[{"given":"Karuppusamy","family":"Balasubramani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kumar 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