Background: This study examines the levels and predictors of malnutrition in Indian children under 5 years of age. Methods: Composite Index of Anthropometric Failure was applied to data from the India National Family Health Survey 2019–2021. A multivariable logistic regression model was used to assess the predictors. Results: 52.59% of children experienced anthropometric failure. Child predictors of lower malnutrition risk included female gender (adjusted odds ratio (AOR) = 0.881) and average or large size at birth (AOR = 0.729 and 0.715, respectively, compared to small size). Higher birth order increased malnutrition odds (2nd-4th: AOR = 1.211; 5th or higher: AOR = 1.449) compared to firstborn. Maternal predictors of lower malnutrition risk included age 20–34 years (AOR = 0.806), age 35–49 years (AOR = 0.714) compared to 15–19 years, normal BMI (AOR = 0.752), overweight and obese BMI (AOR = 0.504) compared to underweight, and secondary or higher education vs. no education (AOR = 0.865). Maternal predictors of higher malnutrition risk included severe anemia vs. no anemia (AOR = 1.232). Protective socioeconomic factors included middle (AOR = 0.903) and rich wealth index (AOR = 0.717) compared to poor, and toilet access (AOR = 0.803). Children’s malnutrition risk also declined with paternal education (primary: AOR = 0.901; secondary or higher: AOR = 0.822) vs. no education. Conversely, malnutrition risk increased with Hindu (AOR = 1.258) or Islam religion (AOR = 1.369) vs. other religions. Conclusions: Child malnutrition remains a critical issue in India, necessitating concerted efforts from both private and public sectors. A ‘Health in All Policies’ approach should guide public health leadership in influencing policies that impact children’s nutritional status.

Background and Objective: This study examines the factors associated with child undernutrition among children under five in Ethiopia, Kenya, Madagascar, and Tanzania. It uses the Composite Index of Anthropometric Failure to measure the full burden of undernutrition, combining weight-for-height (WHZ), weight-for-age (WAZ), and height-for-age (HAZ) indicators. This approach captures children facing multiple forms of failure that single indicators miss. Methods: The study analyzed 37,570 children using nationally representative Demographic and Health Survey (DHS) data for Ethiopia 2019, Kenya 2022, Madagascar 2021, and Tanzania 2022. A binary logistic regression model identified key predictors of child undernutrition across countries. Results: The prevalence of anthropometric failure ranged from 24% to 44%. Higher parental education, child’s age, socioeconomic status, child’s sex, and a postnatal checkup within 2 months were associated with a lower odds of anthropometric failure. Children of educated mothers in Ethiopia (AOR = 0.547) and Tanzania (AOR = 0.606) had better outcomes. Educated fathers in Kenya (AOR = 0.589) and Madagascar (AOR = 0.369) reduced the risk of child undernutrition. Children aged 13–24 months had a higher risk in all countries. In Madagascar (AOR = 0.309), children who received a postnatal checkup had a decreased risk of malnutrition. Children from rich households in Ethiopia (AOR = 0.645) and from middle (AOR = 0.683) and rich (AOR = 0.535) households in Kenya had significantly lower odds of undernutrition. In comparison, female children had lower odds of anthropometric failure in all four countries. Conclusions: Viewed through a nutrition equity lens, these findings underscore the importance of recognizing how the intersectionality of anthropometric failures disproportionately affects children from poorer households and communities with limited access to education and postnatal care. This study advances existing knowledge by using the Composite Index of Anthropometric Failure to show overlapping and hidden forms of undernutrition. The findings identify child age, parental education, postnatal checkup, child sex, and socioeconomic status as shared priorities for reducing undernutrition. The results provide country-specific insights for designing integrated, evidence-based nutrition interventions in Eastern Africa.

Background: Health equity can only be achieved when every individual has access to quality healthcare without fear of being discriminated against. This study analyzed the sociodemographic characteristics associated with self-reported racial discrimination when receiving medical care in the United States. Methods: This quantitative cross-sectional study utilized the 2022 National Trends Survey 6. We performed a logistic regression analysis using 6102 survey responses from study participants who answered the question about perceived discrimination. Results: Older adults aged 75 years and above had significantly lower odds of reporting perceived discrimination when receiving medical care compared to those aged 18–34 years (AOR = 0.24; 95% CI: 0.10–0.58). The odds of reporting perceived discrimination were significantly higher among non-Hispanic Blacks (AOR = 7.30; 95% CI: 4.48–11.88), Hispanics (AOR = 3.56; 95% CI: 2.45–5.17), non-Hispanic Asians (AOR = 5.95; 95% CI: 2.25–15.73), and individuals identifying as non-Hispanic Other (AOR = 10.91; 95% CI: 5.42–21.98), compared to non-Hispanic Whites. Compared to individuals from households earning less than USD 20,000, the odds of reporting perceived discrimination when receiving medical care were significantly lower among individuals from households earning between USD 50,000 and <USD 75,000 (AOR = 0.42; 95% CI: 0.23–0.78) and those earning USD 75,000 or more (AOR = 0.43; 95% CI: 0.22–0.83). Conclusions: Despite having a multicultural and ethnically diverse population, racial discrimination persists in the United States and has become a barrier to achieving health equity. Health organizations should implement policies that ensure health workers attend mandatory anti-racism training.

Psychological distress, an emotional condition with symptoms of anxiety and depression, leads to impaired function, behavior, and personal traits. The current study examined the association between social determinants of health and the severity of psychological distress among adults in the United States after the COVID-19 pandemic. Using multinomial multivariable logistic regression, we analyzed data from 5106 (n = 5106) participants in the Health Information National Trends Survey (HINTS) 6. Compared to non-Hispanic Whites, African Americans (AOR = 0.62, CI = 0.42–0.93) had lower odds of reporting mild psychological distress rather than no stress. Other variables associated with a higher likelihood of reporting moderate to severe psychological distress, rather than no distress, are being in the 50–64 years age group (AOR = 2.77, CI = 1.45–5.28), divorced (AOR = 2.50, CI = 1.70–3.69), and widowed (AOR = 3.78, CI = 2.15–6.64). Respondents living in an urban area had lower odds of reporting moderate to severe psychological distress (AOR = 0.56, CI = 0.39–0.80) compared to those living in rural areas. Our findings identify several risk factors for psychological distress by sociodemographic characteristics such as age, race, marital status, and urban living, providing empirical evidence for interventions in behavioral health. These findings suggest there is an utmost need for a multi-sectoral approach to address the social determinants of health associated with psychological distress post-COVID-19 pandemic.

The use of the internet and supported apps is at historically unprecedented levels for the exchange of health information. The increasing use of the internet and social media platforms can affect patients’ health behavior. This study aims to assess the variations in patterns of social media engagement between individuals diagnosed with either chronic diseases or mental health conditions. Data from four iterations of the Health Information National Trends Survey Cycle 4 from 2017 to 2020 were used for this study with a sample size (N) = 16,092. To analyze the association between the independent variables, reflecting the presence of chronic conditions or mental health conditions, and various levels of social media engagement, descriptive statistics and logistic regression were conducted. Respondents who had at least one chronic condition were more likely to join an internet-based support group (Adjusted Odds Ratio or AOR = 1.5; Confidence Interval, CI = 1.11–1.93) and watch a health-related video on YouTube (AOR = 1.2; CI = 1.01–1.36); respondents with a mental condition were less likely to visit and share health information on social media, join an internet-based support group, and watch a health-related video on YouTube. Race, age, and educational level also influence the choice to watch a health-related video on YouTube. Understanding the pattern of engagement with health-related content on social media and how their online behavior differs based on the patient’s medical conditions can lead to the development of more effective and tailored public health interventions that leverage social media platforms.

Background/Objectives: Mental health problems are common among university students and are more consistently associated with dissatisfaction with academic performance than with low grades alone. This study examined the prevalence and determinants of perceived stress, depressive symptoms, and low psychological well-being among university students in Punjab, Pakistan, and assessed their association with academic performance. Methods: A cross-sectional survey was conducted among students aged 15 to 29 years at three public universities in Punjab, Pakistan. A total of 1308 questionnaires were completed, yielding a response rate of 91.4%. This study uses data collected in 2015 as a pre-COVID historical baseline, providing valuable insights into student mental health before the global pandemic. This temporal context offers a benchmark for future comparative studies, especially when assessing the mental health impact of COVID-19 on university students. Data were analyzed using SPSS with descriptive statistics, chi-square tests, binary logistic regression, and multinomial logistic regression. Results: The findings revealed that perceived stress and depressive symptoms were prevalent, with 54.9% of students reporting high levels of stress (mean PSS score = 27.6, SD = 8.3), and 44.2% experiencing depressive symptoms (mean M-BDI score = 33.8, SD = 16.2). Female students exhibited higher stress and depressive symptoms compared to male students. Year of study was also a factor, with second- and third-year students experiencing more stress than their final-year counterparts (p < 0.05). Financial strain was associated with poorer mental health outcomes; 62% of students who reported inadequate financial support also reported higher stress levels (p < 0.05). In contrast, students with sufficient financial resources had lower odds of experiencing stress and depressive symptoms (AOR = 0.55, p < 0.05). Additionally, students living in university or private hostels reported better psychological well-being than those living at home (AOR = 0.47, p < 0.01). Mental health issues, particularly high stress and depression, were more strongly linked with academic dissatisfaction than low grades alone, with students in the “low grades and unsatisfied” group exhibiting higher odds of mental health problems (AOR = 2.30, p < 0.05). Conclusions: Mental health problems were common among university students and were associated with poorer academic experiences, particularly dissatisfaction with academic performance. Universities should strengthen accessible mental health support through counseling services, stress-management programs, and stigma-reduction initiatives.