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Summary: Ultraprocessed foods (UPF) consumption is associated with excess adiposity in adults, but this linkage remains unclear among children and adolescents. The present systematic review sought to address this research gap. Publications up to November 2023 were retrieved from PubMed, Web of Science, and Scopus databases. Outcomes included overweight/obesity anthropometric and body composition indicators; the exposure was UPF consumption based on the NOVA classification system. The review included 23 studies (i.e., 8 cohort and 15 cross‐sectional); approximately half were carried out in Brazil. Inconclusive and heterogeneous evidence exists as few cohort studies found positive/mixed associations between UPF consumption and excess adiposity in pediatric populations, whereas most cross‐sectional studies reported null associations. Such inconsistencies may be attributed to underlying methodological issues, especially heterogeneity in the outcomes assessed and UPF consumption operationalization and/or categorization. Future studies should adopt longitudinal designs with sufficiently extended follow‐up periods, account for relevant confounding factors, employ validated and standardized measurement tools to assess dietary exposure, ensure consistent operationalization of variables, and encompass diverse geographic contexts. Ultimately, strengthening the quality of existing research evidence may better inform current and forthcoming policy and practice interventions aimed at mitigating the increasing prevalence of overweight/obesity in childhood and across the life course. [ABSTRACT FROM AUTHOR]

Objectives: Few panel studies have investigated how different types of mental health (MH) and socio-emotional wellbeing (SEW) outcomes have changed during the pandemic and if their burden has been equally distributed at the population-level. We aimed to examine temporal changes in these outcomes and their socio-ecological predictors using panel data. Study design: Longitudinal population-based survey with overlapping panels. Methods: Analyses were carried out using four measurements of data from the Health and Social Survey (April 2020 to April 2021). Participants included Andalusian (Spanish) residents aged 16 years or older who participated in all four measurements (n = 1223). Seven dichotomous MH and SEW outcomes, as well as several socio-ecological predictors informed by a conceptual model, were examined in descriptive and multivariate analyses. Results: Unadjusted odds of regular/bad perceived mental health (vs. excellent/very good/good), low socio-emotional wellbeing (vs. regular), low happiness (vs. regular), and feeling anxious (vs. not feeling anxious) decreased significantly from the first to the second measurement; however, in the fourth, low socio-emotional wellbeing significantly increased while low optimism decreased. Considering varying coefficients, objectively measured COVID-19 status and self-reported severity levels of the infection were statistically significant. Health status, social support, and household financial difficulty predicted higher adjusted odds in most of the seven assessed outcomes. Conclusions: Significant temporal variations in MH and SEW outcomes, along with their predictors, were observed during the first year of the pandemic. Some of these outcomes worsened as the pandemic progressed, whereas others improved. Findings also suggest that some individuals such as those experiencing poor health, limited social support, and low socioeconomic status are disproportionately impacted. [ABSTRACT FROM AUTHOR]

Air pollution stands as an environmental risk to child mental health, with proven relationships hitherto observed only in urban areas. Understanding the impact of pollution in rural settings is equally crucial. The novelty of this article lies in the study of the relationship between air pollution and behavioural and developmental disorders, attention deficit hyperactivity disorder (ADHD), anxiety, and eating disorders in children below 15 living in a rural area. The methodology combines spatio-temporal models, Bayesian inference and Compositional Data (CoDa), that make it possible to study areas with few pollution monitoring stations. Exposure to nitrogen dioxide (NO2), ozone (O3), and sulphur dioxide (SO2) is related to behavioural and development disorders, anxiety is related to particulate matter (PM10), O3 and SO2, and overall pollution is associated to ADHD and eating disorders. To sum up, like their urban counterparts, rural children are also subject to mental health risks related to air pollution, and the combination of spatio-temporal models, Bayesian inference and CoDa make it possible to relate mental health problems to pollutant concentrations in rural settings with few monitoring stations. Certain limitations persist related to misclassification of exposure to air pollutants and to the covariables available in the data sources used. [ABSTRACT FROM AUTHOR]

Objectives: To assess the impact of prior chronic treatment with angiotensin-converting enzyme inhibitors (ACEIs)/ angiotensin-receptor blockers (ARBs), both as a group and by active ingredient, on severity (risk of hospitalization and mortality), progression of and susceptibility to COVID-19. Methods: We conducted a multiple population-based case–control study in Galicia (north-west Spain). The study data were sourced from medical, administrative and clinical databases. We assessed: (1) risk of hospitalization, by selecting all patients hospitalized due to COVID-19 with PCR + as cases, and a random sample of subjects without a PCR + as controls; (2) COVID-19 mortality risk; (3) risk of disease progression; and (4) susceptibility to SARS-CoV-2, considering all patients with PCR + as cases, and the same subjects used in the previous model as controls. Adjusted odds ratios (aORs) were calculated. Results: ACEIs and ARBs were shown to decrease the risk of hospitalization (aOR = 0.78 [95%CI 0.69–0.89] and aOR = 0.80 [95%CI 0.72–0.90] respectively), risk of mortality (aOR = 0.71 [95%CI 0.52–0.98] and aOR = 0.69 [95%CI 0.52–0.91] respectively), and susceptibility to the virus (aOR = 0.88 [95%CI 0.82–0.94] and aOR = 0.92 [95%CI 0.86–0.97] respectively). By active ingredient: use of enalapril was associated with a significantly lower risk of hospitalization (aOR = 0.72 [95%CI 0.61–0.85]), mortality (aOR = 0.59 [95%CI 0.38–0.92]) and susceptibility to COVID-19 (aOR = 0.86 [95%CI 0.79–0.94]); and use of candesartan was associated with a decreased risk of hospitalization (aOR = 0.76 [95%CI 0.60–0.95]), mortality (aOR = 0.36 [95%CI 0.17–0.75]) and disease progression (aOR = 0.73 [95%CI 0.56–0.95]). Conclusion: This large-scale real-world data study suggest that enalapril and candesartan are associated with a considerable reduction in risk of severe COVID19 outcomes. [ABSTRACT FROM AUTHOR]

Background: The reallocation of health care services during the coronavirus disease 2019 (COVID-19) pandemic disrupted the continuity of primary care. This study examines the repercussions of the COVID-19 pandemic on clinical indicators within the Catalan population, emphasising individuals with chronic conditions. It provides insights into mortality and transfer rates considering intersectional perspectives., Methods: We designed a retrospective, observational population-based cohort study based on routinely collected data from January 2015 to June 2021 for all individuals available in the Information System for Research in Primary Care (Sistema d'Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP)), the largest public primary care database in Catalonia, Spain. We included 6 301 095 individuals, constituting 81.6% of Catalonia's population in 2020. To perform a repeated measurements analysis of the indicators, we focussed on individuals who had one or more indicators in both the pre-pandemic (January 2015 to March 2020) and pandemic periods (March 2020 to June 2021), and those diagnosed with type 2 diabetes mellitus (T2D), high blood pressure, and heart failure. We selected key clinical indicators for analysis, including systolic and diastolic blood pressure, body mass index (BMI), cholesterol (total, high, and low-density lipoprotein), triglycerides, glycosylated haemoglobin, the Barthel index, and cardiovascular risk (Registre Gironí del cor (REGICOR) index)., Results: Mortality and transfer rates increased during the pandemic, contributing to a decline in the active population in the public health system. We also observed a reduction in pandemic period prevalence of patients with chronic conditions: -26.7% for heart failure, -15.1% for high blood pressure, and -14.6% for T2D. In both pre-pandemic and pandemic periods, 1 632 013 subjects had at least one clinical indicator record. Clinical indicators worsened in patients diagnosed with chronic conditions during the pandemic. Most indicators worsened, with differences between men and women (+9.4% vs +3.7% for the REGICOR index and -14.1% vs -16.6% for the Barthel index in men and in women, respectively), and to a similar extent (or greater in some cases) in individuals without these conditions., Conclusions: We used longitudinal data to assess the repercussions of the COVID-19 pandemic on population health while considering a wide range of clinical indicators and socioeconomic determinants. Our analysis shows a deterioration in clinical indicators during the pandemic, particularly in cardiometabolic factors, underscoring the importance of continuous primary care for individuals with chronic conditions., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no relevant interests., (Copyright © 2024 by the Journal of Global Health. All rights reserved.)