Suvasish Das Shuvo, Md Mohtasim Hasan, Tapon Kumar Das, Md Emran Hossain, Tamanna Aktar, Md Riazuddin, Md Sakib Hasan
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引用次数: 0
Abstract
Introduction
The onset of the COVID-19 pandemic has disrupted food access, resulting in substantial consequences for food insecurity and contributing to adverse individual and public health outcomes. To comprehensively evaluate these challenges and grasp their implications for food security, this study aimed to evaluate the contributing determinants of food insecurity among rural households in the southwestern region of Bangladesh.
Study design
A cross-sectional study was conducted using a validated questionnaire in selected 310 rural household respondents from the southwestern region of Bangladesh.
Methods
Household food insecurity status was the outcome variable for the analysis. Multinomial logistic regression analysis was used to explore and predict risk factors correlated with food insecurity among southwestern Bangladeshi households.
Results
We found that 59 % and 27.5 % of households were suffering from moderate food insecurity and severe food insecurity, respectively. The multinomial regression model revealed that respondents residing in Kusthia (RRR = 5.56 CI:2.67–8.4 and RRR = 6.65, CI:3.37–9.22) aged between 30 and 40 years (RRR = 2.32, 95 % CI:1.84–3.77 and RRR = 1.87, 95 % CI:1.48–3.97) and 40–50 years (RRR = 1.86 95 % CI:1.46–3.82 and RRR = 1.95, 95 % CI:1.75–3.26) were significantly associated with mild-to-moderate and severe food insecurity. Respondents with a monthly family income of <58.96 USD (3.38 times and 2.18 times), had ≥5 family members (2.68 times and 1.89 times), and had poor income during the pandemic (4.25 times and 2.75 times) more likely to be moderate and severe food insecure.
Conclusion
The results emphasized that during the COVID-19 lockdown in Bangladesh, rural households faced diverse levels of food insecurity, ranging from moderate to severe. It suggests that efforts to raise awareness and implement support strategies for those at higher risk should not only focus on income but also consider additional factors such as family size, adults aged 30–40 years, and occupation.