Uneven livelihood vulnerability across coastal communities in Bangladesh using LVI and logistic regression

Livelihood vulnerability associated with climatic hazards is a pressing global concern, particularly for coastal populations in developing countries such as Bangladesh. Owing to their geographic location, coastal areas are disproportionately exposed to climate-related hazards, intensifying existing socio-economic challenges. Using cross-sectional approach over 270 households, equally distributed between Sundarban and Mithakhali unions (135 households per union) in Mongla Upazila, Bangladesh, this study assesses climate-related livelihood vulnerability. The Livelihood Vulnerability Index (LVI) was constructed from 35 indicators to evaluate and compare multidimensional vulnerability between the two unions. Binary logistic regression was further used to examine household-level associations between exposure, sensitivity, adaptive-capacity deficit, location, and a food-insecurity-based indicator of high livelihood stress. The results reveal that Sundarban has a higher overall livelihood vulnerability (LVI = 0.622) than Mithakhali (LVI = 0.560), characterized particularly by greater exposure and sensitivity, while adaptive-capacity conditions are comparatively similar between the two unions. Household-level analysis shows that greater Water- and Health-based sensitivity is significantly associated with high livelihood stress, with a 0.10-point increase in sensitivity corresponding to approximately twice the odds of high livelihood stress (OR = 1.99; 95% CI 1.46–2.72; p < 0.001). Households in Sundarban also have substantially higher odds of high livelihood stress than those in Mithakhali (OR = 5.92; 95% CI 2.52–13.88; p < 0.001), after accounting for the measured vulnerability dimensions. Exposure and adaptive-capacity deficit are not independently associated with livelihood stress in the adjusted model. These disparities highlight the need for location-specific interventions, particularly in food security, safe-water access, healthcare, climate-resilient livelihoods, and infrastructure to strengthen resilience in vulnerable coastal communities.

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Journal
Discover Sustainability
Published
2026-10-28
DOI
https://doi.org/10.1007/s43621-026-05157-7
Primary Topic
Climate change impacts on agriculture
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article
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article

Uneven livelihood vulnerability across coastal communities in Bangladesh using LVI and logistic regression

Razaun Parvaz Ovi, Md. Tanvir Hossain, Bristi Sarkar, Md. Sohel Rana et al.
2 links
Discover Sustainability
Climate change impacts on agriculture
article

Uneven livelihood vulnerability across coastal communities in Bangladesh using LVI and logistic regression

Razaun Parvaz Ovi, Md. Tanvir Hossain, Bristi Sarkar, Md. Sohel Rana, Bishojit Sarkar
article en

Abstract

Livelihood vulnerability associated with climatic hazards is a pressing global concern, particularly for coastal populations in developing countries such as Bangladesh. Owing to their geographic location, coastal areas are disproportionately exposed to climate-related hazards, intensifying existing socio-economic challenges. Using cross-sectional approach over 270 households, equally distributed between Sundarban and Mithakhali unions (135 households per union) in Mongla Upazila, Bangladesh, this study assesses climate-related livelihood vulnerability. The Livelihood Vulnerability Index (LVI) was constructed from 35 indicators to evaluate and compare multidimensional vulnerability between the two unions. Binary logistic regression was further used to examine household-level associations between exposure, sensitivity, adaptive-capacity deficit, location, and a food-insecurity-based indicator of high livelihood stress. The results reveal that Sundarban has a higher overall livelihood vulnerability (LVI = 0.622) than Mithakhali (LVI = 0.560), characterized particularly by greater exposure and sensitivity, while adaptive-capacity conditions are comparatively similar between the two unions. Household-level analysis shows that greater Water- and Health-based sensitivity is significantly associated with high livelihood stress, with a 0.10-point increase in sensitivity corresponding to approximately twice the odds of high livelihood stress (OR = 1.99; 95% CI 1.46–2.72; p < 0.001). Households in Sundarban also have substantially higher odds of high livelihood stress than those in Mithakhali (OR = 5.92; 95% CI 2.52–13.88; p < 0.001), after accounting for the measured vulnerability dimensions. Exposure and adaptive-capacity deficit are not independently associated with livelihood stress in the adjusted model. These disparities highlight the need for location-specific interventions, particularly in food security, safe-water access, healthcare, climate-resilient livelihoods, and infrastructure to strengthen resilience in vulnerable coastal communities.

Discover Sustainability
Khulna University (BD)
No poverty, Climate action, Good health and well-being, Decent work and economic growth, Sustainable cities and communities
Openalex Percentile: Top 8%
Climate change impacts on agriculture
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