Dataset Information

Relative Severity of Food Insecurity During Overland Migration in Transit Through Mexico.

ABSTRACT: Despite anecdotal reports of food insufficiency in the overland migration through Mexico, little is known about the frequency and extent of food insecurity during this transit. In a shelter in north central Mexico, we interviewed 95 Central American migrants traveling overland to the US regarding their experiences of food insecurity in transit. 74% experienced some degree of food insecurity, ranging from having only one meal to no food at all in one or several consecutive 24 h periods. Factors associated with relatively more severe food insecurity included more days in active transit, more severe illness impacting mobility, or travel companion illness in the prior 2 weeks. Illness was predicted by a pre-migration diagnosis of chronic disease. Understanding the factors associated with relative severity of food insecurity during overland migration can inform policies for prioritizing assistance and prevention.

SUBMITTER: Aragon Gama AC

PROVIDER: S-EPMC7686084 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Relative Severity of Food Insecurity During Overland Migration in Transit Through Mexico.

Aragón Gama Alondra Coral AC Infante Xibille Cesar C Mundo Rosas Verónica V Liu Xinhua X Orjuela-Grimm Manuela M

Journal of immigrant and minority health 20201201 6

Despite anecdotal reports of food insufficiency in the overland migration through Mexico, little is known about the frequency and extent of food insecurity during this transit. In a shelter in north central Mexico, we interviewed 95 Central American migrants traveling overland to the US regarding their experiences of food insecurity in transit. 74% experienced some degree of food insecurity, ranging from having only one meal to no food at all in one or several consecutive 24 h periods. Factors a ...[more]

PMID: 32749566

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Project description:BackgroundHousehold food insecurity (HFI) increased in Latin America by 9% between 2019 and 2020. Scant evidence shows who was unable to recover from the COVID-19 pandemic. Our aim was to use a Machine Learning (ML) approach to identify consistent and influential predictors of persistent moderate or severe HFI over 2 years.MethodsWe use a three-wave longitudinal telephone survey with a probabilistic sample representative of the Mexican population. With a response rate of 51.3 and 60.8% for the second and third waves, the final sample size consisted of 1,074 individuals. The primary outcome was persistent HFI, i.e., respondents who reported moderate or severe HFI in 2021 and 2022. Twelve income-related predictors were measured in 2020, including baseline HFI. We employed 6 supervised ML algorithms to cross-validate findings in models, examined its precision with 4 standard performance indicators to assess precision, and used SHAP values (Shapley Additive exPlanations) to identify influential predictors in each model.ResultsPrevalence of persistent moderate/severe HFI in 2021 and 2022 was 8.8%. Models with only a HFI 2020 baseline measure were used as a reference for comparisons; they had an accuracy of 0.79, a Cohen's Kappa of 0.57, a sensitivity of 0.68, and a specificity of 0.88. When HFI was substituted by the suite of socioeconomic indicators, accuracy ranged from 0.70 to 0.84, Cohen's Kappa from 0.40 to 0.67, sensitivity from 0.86 to 0.90, and specificity from 0.75 to 0.82. The best performing models included baseline HFI and socioeconomic indicators; they had an accuracy between 0.81 and 0.92, a Cohen's Kappa between 0.61 and 0.85, a sensitivity from 0.74 to 0.95, and a specificity from 0.85 to 0.92. Influential and consistent predictors across the algorithms were baseline HFI, socioeconomic status (SES), adoption of financial coping strategies, and receiving government support.DiscussionPersistent HFI can be a relevant indicator to identify households that are less responsive to food security policies. These households should be prioritized for innovative government support and monitored to assess changes. Forecasting systems of HFI can be improved with longitudinal designs including baseline measures of HFI and socioeconomic predictors.

Project description:BackgroundDisruptions from the coronavirus disease 2019 (COVID-19) pandemic potentially exacerbated food insecurity among adults and youth.ObjectivesThe objective was to examine changes in the prevalence and severity of food insecurity among adults and youth from before (2019) to during (2020) the pandemic in multiple countries.MethodsRepeated cross-sectional data were collected among adults aged 18-100 y (n = 63,278) in 5 countries in November to December in 2018-2020 and among youth aged 10-17 y (n = 23,107) in 6 countries in November to December in 2019 and 2020. Food insecurity in the past year was captured using the Household Food Security Survey Module and the Child Food Insecurity Experiences Scale. Changes in the prevalence and severity of food insecurity were examined using logistic and generalized logit regression models, respectively. Models included age, gender, racial-ethnic identity, and other sociodemographic characteristics associated with food insecurity to adjust for possible sample differences across waves. Models were weighted to reflect each country's population.ResultsAdults [adjusted OR (AOR): 1.15; 95% CI: 1.02, 1.31] and youth (AOR: 1.43; 95% CI: 1.19, 1.71) in Mexico were more likely to live in food-insecure households in 2020 compared to 2019. Adults in Australia (AOR: 0.81; 95% CI: 0.72, 0.92) and Canada (AOR: 0.87; 95% CI: 0.77, 0.99) were less likely to live in food-insecure households in 2020. Trends in severity aligned with changes in prevalence, with some exceptions. Youth in Australia (AOR: 2.24; 95% CI: 1.65, 3.02) and the United States (AOR: 1.39; 95% CI: 1.04, 1.86) were more likely to have many compared with no experiences of food insecurity in 2020 compared to 2019. There was no evidence of change among adults and youth in the remaining countries.ConclusionsExcept for Mexico, few changes in food insecurity among adults and youth were observed from before to during the COVID-19 pandemic. Action is needed to support households at risk of food insecurity. J Nutr 20XX;xx:xx-xx.

Dataset Information

Relative Severity of Food Insecurity During Overland Migration in Transit Through Mexico.

Publications

Relative Severity of Food Insecurity During Overland Migration in Transit Through Mexico.

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