BackgroundMalnutrition is one of the major contributors to child mortality in Ethiopia. Currently established, child nutrition status is assessed by four anthropometric indicators. However, there are other factors affecting children’s anthropometric statuses. Thus, the main objective of this paper is to explore some of the determinants of child anthropometric indicators in Ethiopia.MethodsData from GROW (the Growing Nutrition for Mothers and Children), a survey including 1261 mothers and 1261 children was carried out in Ethiopia in 2016. Based on the data gathered, the goal of GROW is to improve the nutritional status of women of reproductive age (15–49), as well as boys and girls under 5 years of age in Ethiopia. In order to investigate the association between different factors and child anthropometric indicators, this study employs various statistical methods, such as ANOVA, T-test, and linear regressions.ResultsChild’s sex (confidence intervals for (wasting = − 0.782, − 0.151; stunting = − 0.936,-0.243) (underweight = − 0.530, − 0.008), child’s age (confidence intervals for (wasting = − 0.020, 0.007; stunting = − 0.042,-0.011) (underweight = − 0.025, − 0.002), maternal MUAC (confidence intervals for (wasting = 0.189, 0.985; BMI-for-age = 0.077, 0.895), maternal education (stunting = 0.095, 0.897; underweight = 0.120, 0.729), and open defecation (stunting = 0.055, 0.332; underweight = 0.042, 0.257) were found to be significantly associated with anthropometric indicators. Contrary to some findings, maternal dietary diversity does not present significance in aforementioned child anthropometric indicators.ConclusionDepending on the choice of children anthropometric indicator, different conclusions were drawn demonstrating the association between each factor to child nutritional status. Results showed child’s sex, age, region, open defecation, and maternal MUAC significantly increases the risk of child anthropometric indicators. Highlighting the factors influencing child undernutrition will help inform future policies and programs designed to approach this major problem in Ethiopia.

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Youth in fragile settings face disproportionate risks of experiencing food insecurity and poor mental health. Cross-national evidence is lacking on the association between food insecurity and mental health in youth populations, and on state fragility as a social determinant of these experiences. We analysed data from six cycles of the Gallup World Poll (2014–2019), an annual survey that contains multi-item scales of food insecurity, mental health problems and positive wellbeing. The analytic sample included 164,118 youth aged 15–24 years in 160 states. We linked individual responses to state-level data from the Fragile States Index—an aggregate measure of state vulnerability to collapse or conflict (coded: sustainable, stable, warning, or alert) and estimated adjusted relative risk (RR) of food insecurity as a function of state fragility. We then used linear regression to examine associations of state fragility and food insecurity with mental health and wellbeing. The prevalence of moderate or severe food insecurity rose from 22.93% in 2014 to 37.34% in 2019. State fragility (alert vs. sustainable) was related to an increased risk of food insecurity (RR = 2.28 [95% CI 1.30 to 4.01]), more mental health symptoms (b = 6.36 [95% CI 1.79 to 10.93]), and lower wellbeing (b = −4.49 [95% CI -8.28 to −0.70]) after controlling for state wealth and household income. Increased food insecurity (severe vs. none or mild) was uniquely related to more mental health symptoms (b = 18.44 [95% CI 17.24 to 19.64]) and reduced wellbeing (b = −9.85 [95% CI -10.88 to −8.83]) after state fragility was also controlled. Globally, youth experience better mental health where states are more robust and food access is more secure. The findings underscore the importance of strong governance and coordinated policy actions that may improve youth mental health.

Objectives: The goal of the present study was to evaluate the association between depression and ultra-processed food consumption as risk factors for developing type 2 diabetes (T2D). Design: A prospective community study. Setting: Baseline data (2009 – 2010) from CARTaGENE community health study from Quebec, Canada, was used. Food and drink consumption was assessed using the Canadian- Diet History Questionnaire II and grouped according to their degree of processing by the NOVA classification, and participants were categorized into tertiles of UPFs (grams/day). Depression was defined either using a validated cut-off score on the Patient Health Questionnaire-9 (PHQ-9) or antidepressant use. The outcome was the incidence of T2D, examined in N = 3,880 participants by linking survey data with administrative health insurance data. Cox regression models estimated the associations between UPFs, depression, and incident T2D. Participants: 40–69-year-old individuals at baseline. Results: In total, 263 (6.8%) individuals developed T2D. Participants with high depressive symptoms and high UPFs consumption showed the highest risk for T2D (adjusted hazard ratios (aHR)=1.58, 95% CI: 0.98–2.68), compared to those with low depressive symptoms and low UPFs consumption. The risk for T2D was similar when high depressive symptoms and antidepressant use were combined with high UPFs (aHR 1.62, 95% CI: 1.02-2.57). Conclusions: This study shows that co-occurring depression and high UPFs consumption were associated with a higher risk for T2D. Early management and monitoring of both risk factors might be essential for diabetes prevention.

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