Livelihood vulnerability to climate change health impacts among Amhara Sayint district community, northeastern Ethiopia: A composite index approach

Abstract

Climate change significantly impacts public health, affecting nearly everyone across the globe and contributing to approximately 10% of global mortality. Ethiopia is particularly vulnerable to the changing climate attributed impacts due to economic, and social determinants. While research on climate change is expanding, it often prioritizes its effects on agriculture. The impacts from public health perspective are frequently overlooked. We address this shortcoming by evaluating the vulnerability of the community in the district of Amhara Sayint, Amhara, northeastern Ethiopia, to the health impacts of climate change, and identifying factors involved. Data was collected using a community-based cross-sectional approach, involving 605 randomly selected households between July Twenty and September Five, 2022. The data collection process utilized a validated and pilot-tested questionnaire, which was administered through face-to-face interview with the aid of Kobo Collect toolbox. The community's vulnerability was assessed using the IPCC's framework of vulnerability. Household's Vulnerability status was then classified into three levels according to their Livelihood Vulnerability Index (LVI) score. A partial proportional oddsapproach of ordinal logistic regression model was used to identify factors associated with vulnerability to climate change attributed health impacts. Among the 605 respondents, 48% (95% CI: 44.1, 52.1) were identified as vulnerable, and about 4.6 % (95% CI: 3, 6.6) were classified as highly vulnerable. Wealth status (AOR1 = 1.8; 95 % CI: 1.2, 2.8), educational status (AOR1 = 2.8; 95% CI: 1.1, 7.3), marital status (AOR2 = 4.7, 95% CI: 1.6, 13.4), and home crowdedness (AOR2 = 2.9, 95% CI: 1.1, 8.1) significantly associated with vulnerability. Over half of the residents in the district wereeither being vulnerable or highly vulnerable to climate change attributed health impacts. Therefore, prioritizing prevention and preparedness along with conducting spatial analysis to identify high-risk areas for timely intervention, is essential.

Keywords

• Climate change
• Health impacts
• Vulnerability Index
• Partial proportional odds model