Asthma prevalence and risk factors in Poonch and Rajouri districts, India: an epidemiological and geospatial analysis

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Asthma is a significant global health issue, especially in high-altitude areas where unique environmental conditions and socioeconomic disparities may elevate disease risk and severity. This study examines the prevalence and determinants of asthma among the Gujjar and Bakarwal tribes living in the high-altitude regions of the western Himalayas, providing insights into the influence of altitude, socioeconomic factors, and lifestyle on asthma risk. We conducted a cross-sectional survey across 816 households in 50 villages in Poonch and Rajouri districts, utilizing a stratified random sampling approach to ensure a representative sample. Villages were categorized by altitude and population density. Geographic Information System (GIS) tools were used to map asthma prevalence using inverse distance weighting (IDW) and Natural Breaks classification to identify high-risk zones. To determine asthma risk factors, we applied a binary logistic regression model (BLRM), with model fit assessed via pseudo-R² and Hosmer-Lemeshow tests, and predictive accuracy evaluated through receiver operating characteristic (ROC) curve analysis. Asthma prevalence was 22.5% among the study population. Higher altitudes were linked to a significantly lower likelihood of asthma (adjusted odds ratio [AOR]: 0.10, p = 0.002). In contrast, extended family living arrangements (AOR: 8.80, p = 0.008) and individuals in their prime working years (AOR: 93.36, p = 0.001) showed elevated asthma risk. Protective factors included higher education, government employment, farming, increased household income, and residence in modern housing. The model exhibited strong fit (Nagelkerke R 2 = 0.82) and high predictive accuracy (ROC-AUC = 0.98). Asthma prevalence among Gujjar and Bakarwal tribes in the high-altitude Himalayas is shaped by a complex interplay of altitude, socioeconomic status, and demographic factors. Altitude appears protective, while social structure, economic activities, and housing conditions modulate asthma risk. GIS-based spatial analysis effectively identifies high-risk areas, underscoring the need for targeted public health interventions tailored to the specific needs of these geographically isolated communities.

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