Spatial Association Between Maternal and Early Life Exposure to Aire Pollution and Acute Respiratory Infection among Children in Nigeria
dc.contributor.advisor | Zhan, F. Benjamin | |
dc.contributor.author | Anyanwu, Chijioke I. | |
dc.contributor.committeeMember | Lu, Yongmei | |
dc.contributor.committeeMember | Chow, Edwin | |
dc.contributor.committeeMember | Perkins, Harold | |
dc.date.accessioned | 2024-05-01T19:40:23Z | |
dc.date.available | 2024-05-01T19:40:23Z | |
dc.date.issued | 2024-05 | |
dc.description.abstract | Acute respiratory infections (ARIs) are one of the leading causes of childhood morbidity and mortality in Nigeria and are often triggered by exposure to ambient air pollution. Due to their higher breathing rates, smaller airways, and developing lungs and immune systems, children are more susceptible to adverse health impacts from air pollution. While concerted efforts have been directed towards tackling the disease, it remains a major public health concern. There are currently no studies on maternal and early life exposure to air pollution and the risks of ARIs among Nigerian children. This dissertation had three main objectives: 1) to evaluate the spatial relationship between prenatal and early life exposure to air pollution, and childhood ARIs in Nigerian children under the age of 5 years, 2) To identify and analyze multi-level risk factors of childhood ARIs, and 3) To examine spatial variations and clustering of the disease. The study deploys a case-control epidemiological analysis to examine the environmental, socioeconomic, cultural, and lifestyle risk factors of childhood ARIs. We used remote sensing air pollution data from the Giovanni earth science data information systems, and health data from the Nigeria Demographic and Health Survey (NDHS, 2018) which includes 1,692 cases and 28,915 controls selected for this study. We analyzed three exposure periods: maternal exposure, and early-life exposure, and combined both maternal and early-life exposure for a wider assessment. For the maternal exposure assessment, NO2 showed the strongest association with childhood ARI in offspring. In contrast, PM2.5 showed the strongest association with childhood ARI for both the early life and the combined exposure assessment studies. We found that educational attainment, socioeconomic status, building quality, and lifestyle factors were significant risk factors for ARI among Nigerian children. The study identified disease clusters using a new hybrid hotspot analysis and spatial clustering analysis (spatial scan statistics). We observed a spatial overlap between childhood ARI clusters and socioeconomically disadvantaged groups. In conclusion, this study provided novel insights into the linkages between air pollution as well as multi-level risk factors, and incidences of childhood ARIs in Nigeria while detecting disease clusters and locations of the most vulnerable populations. This could provide invaluable information for a targeted approach to ARI prevention and reducing child mortality. | |
dc.description.department | Geography and Environmental Studies | |
dc.format | 162 pages | |
dc.format.extent | 162 pages | |
dc.format.medium | 1 file (.pdf) | |
dc.identifier.citation | Anyanwu, C. I. (2024). Spatial association between maternal and early life exposure to aire pollution and acute respiratory infection among children in Nigeria (Unpublished dissertation). Texas State University, San Marcos, Texas. | |
dc.identifier.uri | https://hdl.handle.net/10877/18507 | |
dc.language.iso | en | |
dc.subject | acute respiratory infection | |
dc.subject | health | |
dc.subject | GIS | |
dc.subject | infant mortality | |
dc.subject | Nigeria | |
dc.subject | air pollution | |
dc.title | Spatial Association Between Maternal and Early Life Exposure to Aire Pollution and Acute Respiratory Infection among Children in Nigeria | |
dc.type | Dissertation | |
thesis.degree.department | Geography and Environmental Studies | |
thesis.degree.discipline | Geographic Information Science | |
thesis.degree.grantor | Texas State University | |
thesis.degree.level | Doctoral | |
thesis.degree.name | Doctor of Philosophy |