OBJECTIVE: We aimed to analyze the frequency of adherence to social distancing and individual protection measures of adult and older populations in two cities in southern Brazil and to characterize the sociodemographic aspects of these individuals.
METHODS: This cross-sectional, population-based study was conducted in the cities of Rio Grande, RS, and Criciúma, SC, Brazil. The outcome measure was the frequency of adherence to social distancing measures. Fisher\'s exact test (5% significance) was used to calculate the differences in prevalence according to exposure variables.
RESULTS: Among the 2,170 participants over the age of 18, the prevalence of adherence to social distancing was 18.5%. Adherence was significantly higher among women; older adults; single, divorced, or widowed people with a low educational level; people of lower socioeconomic status; and people affected by multiple chronic diseases.
CONCLUSIONS: Approximately one in five respondents adhered to measures of social distancing, and adherence was more prevalent among the risk groups.

The body mass index (BMI) is a commonly employed metric for determining the nutritional status and health risks associated with weight. Tribal women in India face neglect and discrimination in terms of livelihood, nutrition, education, wealth, and health-care access. The study examined 18,697 tribal women from Bihar, West Bengal, Jharkhand, and Odisha, using data from the National Family Health Survey-5. Multinomial logistic regression has been used to determine how the multiple background factors are associated with the BMI of tribal women. The study found that the prevalence of underweight and overweight was 28.5% and 7.6% among tribal women, respectively. Rural tribal women had a higher likelihood of being underweight, whereas urban women were more likely to be overweight. Odisha had a higher prevalence of underweight tribal women, whereas the prevalence is lower in Bihar. The higher prevalence of underweight among tribal women is alarming and necessitates a reconsideration of health infrastructure in the tribal areas.

UNASSIGNED: The COVID-19 pandemic has had tremendous implications for billions of adolescents worldwide due to school closures, forcing students to embrace internet usage for daily tasks. Uncontrolled use of the internet among adolescents makes them vulnerable to internet addiction (IA). This study aims to determine the prevalence of IA among adolescents and assess its association with sociodemographic factors, smartphone use, and psychological distress during the pandemic.
UNASSIGNED: A cross-sectional self-administered online survey was conducted among students aged 13-17 from May 15th, 2021, until May 30th, 2021, using the Malay version of the Internet Addiction Test (MVIAT), the Depression, Anxiety, and Stress Scale (DASS-21), and the Coronavirus Impacts Questionnaires, as well as a sociodemographic information form. The data was analyzed with IBM SPSS Statistics version 23.
UNASSIGNED: A total of 420 adolescents participated in the survey. The majority of them (70.7%) were female, with a mean age of 15.47 years (±1.49 years old). About 45.5% of the respondents were classified as internet addicted users. The Chi-square test analysis showed that age (p = 0.002), smartphone usage (p = 0.010), rate of midnight use (p < 0.001), frequency (p < 0.001), duration (p < 0.001) of device usage, and presence of depression, anxiety, and stress (p < 0.001) were all significantly associated with IA. Multiple logistic regression showed age (aOR = 1.16, 95% CI [1.00-1.35], p = 0.048), smartphone usage (aOR =3.52, 95% CI [1.43-8.67], p = 0.006), mild or moderate depression (aOR = 2.43, 95% CI [1.36-4.34], p = 0.003), severe or extremely severe stress (aOR = 6.41, 95% CI [2.18-18.82], p = 0.001) were significantly related to IA.
UNASSIGNED: Late adolescence, the use of smartphones, and the presence of psychological distress like depression, and stress were potentially associated with IA. Wise use of smartphones and early identification of any psychological distress among adolescents are warranted, especially during the pandemic.

BACKGROUND: There are limited population-representative data that describe the potential burden of Post-COVID conditions (PCC) in Mexico. We estimated the prevalence of PCC overall and by sociodemographic characteristics among a representative sample of adults previously diagnosed with COVID-19 in Mexico. We additionally, characterized the PCC symptoms, and estimated the association between diagnosed type-2 diabetes and hypertension with PCC.
METHODS: We used data from the 2021 National Health and Nutrition Survey in Mexico, a nationally and regionally representative survey, from August 1st to October 31st, 2021. Using the WHO definition, we estimated the prevalence of PCC by sociodemographics and prevalence of PCC symptoms. We fit multivariable log-binomial regression models to estimate the associations.
RESULTS: The prevalence of PCC was 37.0%. The most common persistent symptoms were fatigue (56.8%), myalgia or arthralgia (47.5%), respiratory distress and dyspnea (42.7%), headache (34.0%), and cough (25.7%). The prevalence was higher in older people, women, and individuals with low socioeconomic status. There was no significant association between hypertension and PCC or diabetes and PCC prevalence.
CONCLUSIONS: About one-third of the adult Mexican population who had COVID-19 in 2021 had Post-COVID conditions. Our population-based estimates can help assess potential priorities for PCC-related health services, which is critical in light of our weak health system and limited funding.

Introduction The pursuit of health care equity is a fundamental objective for Aotearoa New Zealand, and patient co-payments in primary care challenge this goal. Aim This study aimed to investigate the relationship between primary health care co-payments and the sociodemographic variables in areas where general practices provide health care. Methods Using census data, facilities information from the Ministry of Health, and socioeconomic deprivation indices, linear regression models were used to explore the relationship between weighted average fees charged by general practices and various sociodemographic variables in statistical area 2 regions. Results The study finds that areas with higher proportions of males and economically deprived individuals are associated with lower weighted average fees. Conversely, areas with higher proportions of retirement-aged and European individuals are linked with higher weighted average fees. The inclusion of the Very-Low-Cost-Access variable, indicating a subsidy scheme at the general practice level, made all the sociodemographic variables practically insignificant, suggesting Very-Low-Cost-Access practices are in the right geographical location to target high needs groups. Discussion The findings affirm the complexity of health care inequities in Aotearoa New Zealand, influenced not only by financial factors but also by demographic variables as they play out geographically. While subsidy schemes like the Very-Low-Cost-Access scheme appear to reach groups with greater need, a high level of unmet need due to cost suggests that the fees are still too high. Policymakers need to consider disparities in the on-going health care reforms and make further changes to subsidy schemes to reduce unmet need.

Introduction The inability to afford a consultation with a general practitioner may lead to delays in accessing care pathways. Aim This study aimed to explore the characteristics of people by their unmet need for a general practitioner consultation because of cost, and the characteristics of subsequent inpatient hospitalisations. Methods From the New Zealand Health Surveys (2013/14-2018/19), two groups were formed based on their unmet need for a general practitioner consultation due to cost. These groups were compared by socio-demographic factors and subsequent inpatient hospitalisation characteristics during follow-up. Time to an inpatient hospitalisation was the outcome in a proportional hazards regression model with need status as the key variable. The model was expanded to include confounding variables: sex, age group, ethnicity, the New Zealand Deprivation Index and self-rated health. Results The need group, characterised by having a higher proportion of females, younger adults, Māori, increased socioeconomic deprivation and poorer self-rated health experienced a greater chance of hospitalisation, a similar number of visits during follow-up, shorter stays and a quicker time to hospitalisation compared to the no-need group. Proportional hazards survival models gave a 28% higher hazard rate for the time to an inpatient hospitalisation for the need group compared to the no-need group. The inclusion of all the confounders in the model gave a similar hazard ratio. Discussion Although consultation fees vary across general practices, it is evident that this may not eliminate the cost barriers to accessing care for some groups. Needing multiple consultations may contribute to persistent unmet needs.

CONCLUSIONS: Depression is a common illness, it being the fourth-leading cause of disability in the world. The global lifetime prevalence falls between 8% and 12%, with female preponderance. A cross-sectional study was designed to assess the burden of depression among married women in a rural setting in North Kerala and identify its sociodemographic risk factors. The sample size was calculated to be 453 (prevalence = 24.9%; error = 20%; design-effect = 1.5). Systematic random sampling was used to select the participants from the eligible couple register. They were interviewed using MINI and Montgomery-Ashberg Depression Rating Scales. Descriptive analysis showed that 24.2% was suffering from current depression, mostly mild and none severe. Two percent reported past depression and 5.4% experienced spousal violence. Poor family support, experience of domestic violence, morbidity, and older spouses were found to be significant risk factors. The provision of mental health services by trained personnel and strict vigilance against the marriage of girls below the legal age and domestic violence are need of the hour.

Food insecurity is a public health concern that affects children worldwide, yet it represents a particular burden for low- and middle-income countries. This study aims to utilize machine learning to identify the associations between food insecurity and nutrient intake among children aged 5 to 18 years. The study\'s sample encompassed 1040 participants selected from a 2022 food insecurity household conducted in the West Bank, Palestine. The results indicated that food insecurity was significantly associated with dietary nutrient intake and sociodemographic factors, such as age, gender, income, and location. Indeed, 18.2% of the children were found to be food-insecure. A significant correlation was evidenced between inadequate consumption of various nutrients below the recommended dietary allowance and food insecurity. Specifically, insufficient protein, vitamin C, fiber, vitamin B12, vitamin B5, vitamin A, vitamin B1, manganese, and copper intake were found to have the highest rates of food insecurity. In addition, children residing in refugee camps experienced significantly higher rates of food insecurity. The findings emphasize the multilayered nature of food insecurity and its impact on children, emphasizing the need for personalized interventions addressing nutrient deficiencies and socioeconomic factors to improve children\'s health and well-being.

Self-rated health is an indicator that can be easily identified in health surveys, widely used to measure physical, social, mental, and health aspects of the population, and predict premature mortality. In Venezuela, this information only began to be collected recently, in the National Survey of Living Conditions (ENCOVI). In this context, our study aims to analyze the demographic and socioeconomic factors associated with non-positive self-rated health among Venezuelan adults. The ENCOVI 2021 (n = 16,803) was used as a data source, assessing a probability stratified sample with questions about health, education, emigration, and other social and economic aspects. Crude and adjusted prevalence ratio analyses were performed using Poisson regression models with robust variance. The prevalence of fair/bad self-rated health among Venezuelans was 17.8%. The results indicated a strong association between outcome prevalence and age group, 3.81 times higher (95%CI: 3.29-4.41) among individuals aged 60 or more when compared to individuals aged 18 to 29 years. Also, participants experiencing severe food insecurity had a prevalence 2 times higher (95%CI: 1.61-2.47) than those who did not have any level of food insecurity. Factors such as poverty, education, recent emigration of family members, and sex also showed a significant influence, also when analyzed independently. The results show that special attention should be dedicated to the health of individuals facing hunger and of the older people.

The COVID-19 pandemic provided an additional spotlight on the longstanding socioeconomic/health impacts of redlining and has added to the myriad of environmental justice issues, which has caused significant loss of life, health, and productive work. The Centers for Disease Control and Prevention (CDC) reports that a person with any selected underlying health conditions is more likely to experience severe COVID-19 symptoms, with more than 81% of COVID-19-related deaths among people aged 65 years and older. The effects of COVID-19 are not homogeneous across populations, varying by socioeconomic status, PM2.5 exposure, and geographic location. This variability is supported by analysis of existing data as a function of the number of cases and deaths per capita/1,00,000 persons. We investigate the degree of correlation between these parameters, excluding health conditions and age. We found that socioeconomic variables alone contribute to ~40% of COVID-19 variability, while socioeconomic parameters, combined with political affiliation, geographic location, and PM2.5 exposure levels, can explain ~60% of COVID-19 variability per capita when using an OLS regression model; socioeconomic factors contribute ~28% to COVID-19-related deaths. Using spatial coordinates in a Random Forest (RF) regressor model significantly improves prediction accuracy by ~120%. Data visualization products reinforce the fact that the number of COVID-19 deaths represents 1% of COVID-19 cases in the US and globally. A larger number of democratic voters, larger per-capita income, and age >65 years is negatively correlated (associated with a decrease) with the number of COVID cases per capita. Several distinct regions of negative and positive correlations are apparent, which are dominated by two major regions of anticorrelation: (1) the West Coast, which exhibits high PM2.5 concentrations and fewer COVID-19 cases; and (2) the middle portion of the US, showing mostly high number of COVID-19 cases and low PM2.5 concentrations. This paper underscores the importance of exercising caution and prudence when making definitive causal statements about the contribution of air quality constituents (such as PM2.5) and socioeconomic factors to COVID-19 mortality rates. It also highlights the importance of implementing better health/lifestyle practices and examines the impact of COVID-19 on vulnerable populations, particularly regarding preexisting health conditions and age. Although PM2.5 contributes comparable deaths (~7M) per year, globally as smoking cigarettes (~8.5M), quantifying any causal contribution toward COVID-19 is non-trivial, given the primary causes of COVID-19 death and confounding factors. This becomes more complicated as air pollution was reduced significantly during the lockdowns, especially during 2020. This statistical analysis provides a modular framework, that can be further expanded with the context of multilevel analysis (MLA). This study highlights the need to address socioeconomic and environmental disparities to better prepare for future pandemics. By understanding how factors such as socioeconomic status, political affiliation, geographic location, and PM2.5 exposure contribute to the variability in COVID-19 outcomes, policymakers and public health officials can develop targeted strategies to protect vulnerable populations. Implementing improved health and lifestyle practices and mitigating environmental hazards will be essential in reducing the impact of future public health crises on marginalized communities. These insights can guide the development of more resilient and equitable health systems capable of responding effectively to similar future scenarios.