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Spatial exploration of non-resilience to food insecurity, its association with COVID-19 and household coping strategies in East Gojjam districts, Northwest Ethiopia, 2020. Sci Rep 2022; 12:15511. [PMID: 36109660 PMCID: PMC9476421 DOI: 10.1038/s41598-022-19963-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 09/07/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractThe coronavirus disease-2019 (COVID-19) pandemic has posed a significant multifaceted threat to the global community. Ethiopia, as a Sub-Saharan African country, is suffering from chronic food insecurity, and the emergence of such a pandemic will exacerbate the situation. As a result, this study investigated the spatial variation of non-resilience to food insecurity, its relationship with COVID-19, and household coping strategies to become resilient in the long run among households in the East Gojjam Zone of Northwest Ethiopia. From September 22 to December 24, 2020, an agro-ecological-based cross-sectional study of 3532 households was conducted to assess the spatial distribution and associated factors of non-resilience to household food insecurity. The enumeration areas (EAs) and households were chosen using a multistage sampling technique. Data were gathered using a semi-structured questionnaire and checklist using an Android device loaded with an Open Data Kit (ODK) template. Binary logistic regression was used to identify the specific factors associated with household non-resilience to food insecurity. A thematic analysis was conducted to investigate the opportunities and challenges of resilience for household food insecurity. Nearly two-thirds (62.5%) of the households were farmers, 67.9% lived in rural areas, and nearly three-quarters (73.8%) earned less than or equal to ETB 2100 per month. Males headed more than four-fifths of the households (81.7%). We found that nearly two-thirds of the households (60.02%), 95% CI 58.40, 61.64) were food insecure. After bivariate logistic regression, we found that households who were divorced (AOR = 2.54 (1.65, 3.87)), daily laborers (AOR = 2.37 (1.15, 4.87)), government employees (AOR = 2.06 (1.05, 4.05)), residents of highland and hot areas (AOR = 11.5 (5.37, 16.77)) and lowland areas (AOR = 1.35 (1.02, 3.15)) were frustrated by COVID-19 (AOR = 1.23 (1.02, 1.50)) and price inflation (1.89 (AOR = 1.42, 2.56))) were at higher odds of being non-resilient to household food insecurity at a 95% confidence level. Geospatial hot spot analysis revealed that Kurar kebele (the lowest government administrative unit) in Dejen District and Debre Markos town were the red-hotspot areas of household non-resilience to food insecurity. Less than a quarter of the households attempted to cope with food insecurity by adjusting their food consumption, while more than 60% of the households chose none of the coping strategies tested. According to the thematic analysis, the degree of poverty (lack of asset ownership), the COVID-19 pandemic, farm decreased variety, and low crop productivity were identified as challenges to coping with the hardship of resilience to food insecurity. During the COVID-19 pandemic and public emergency, the proportion of households that were unprepared for food insecurity reached its peak. It was recognized that a segment of the population with low economic capacity was more vulnerable to food insecurity and less resilient. Tough developmental gains will be undermined in this case. As a result, each responsible body and stakeholder should develop and implement solid corrective plans for the local context.
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Haq IU, Mehmood Z, Khan N, Khan MN, Israr M, Ali Khan E, Nisar M, Ahmad MI, Ali M. Risk Factors of Mid-upper Arm Circumference (MUAC) Based Child Malnutrition in the Flood-affected Areas of Pakistan: A Cross-sectional Study. Ecol Food Nutr 2021; 60:491-507. [PMID: 33472422 DOI: 10.1080/03670244.2021.1872024] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Low- and middle-income countries are usually at high risk of malnutrition. Not only that but the prevalence of malnutrition is much higher. It is important to evaluate the determinants of malnutrition in flood-affected areas of Pakistan. The present study examined the prevalence and risk factors of MUAC-based child malnutrition in flood-hit regions of Khyber Pakhtunkhwa, Pakistan. Multi-stage sampling was employed to select 656 households. Finally, 298 children of 6-59 months were selected. MUAC, an independent anthropometric parameter, was used to investigate the nutritional status of children. An automated logistic regression model was used to identify the risk factors of MUAC-based malnutrition. The prevalence of MUAC-based malnutrition was found 46%, including 40.5% females and 52.1% males. More than 90% of people had improved water quality and soap hand washing facility. Almost 17% of respondents had no toilet facility. Through automated logistic model, child age, maternal age, family size, income level, mother education, water quality, toilet facility were the significant determinants (P < .05) of MUAC-based undernutrition in flood affecting the area. The findings suggest that MUAC-based malnutrition can be minimized in flood-hit areas by targeting the listed risk factors. Community-based awareness programs regarding guidance on nutrition might be a key to reducing malnutrition in the target areas.
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Affiliation(s)
- Ijaz Ul Haq
- School of Food Science, Jiangsu Food & Pharmaceutical Science College, Jiangsu, Huai'an, China.,Department of Public Health and Nutrition, University of Haripur, Haripur, Khyber Pakhtunkhwa, Pakistan
| | - Zafar Mehmood
- School of Food Science, Jiangsu Food & Pharmaceutical Science College, Jiangsu, Huai'an, China.,Department of Math's, Stats & Computer Science, the University of Agriculture Peshawar, Pakistan
| | - Nadar Khan
- Department of Animal Nutrition, The University of Agriculture Peshawar, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Nadeem Khan
- Department of Medicine, Lady Reading Hospital, Peshawar, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Israr
- Department of Ophthalmology, Hayatabad Medical Complex, Peshawar, Khyber Pakhtunkhwa, Pakistan
| | - Ejaz Ali Khan
- Institue of Nursing Sciences, Khyber Medical University Peshawar, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Nisar
- Department of Epidemiology & Public Health, Cholistan University of Veterinary and Animal Sciences, Punjab, Pakistan
| | - Muhammad Ijaz Ahmad
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Majid Ali
- Department of Health Policy, School of Health Policy and Management, Nanjing Medical University, Nanjing, Jiangsu, China
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