Dataset Information

Influence of Socio-Economic Status on Psychopathology in Ecuadorian Children.

ABSTRACT: The socioeconomic status (SES) of parents has been reported to have a crucial impact on emotional competence in childhood. However, studies have largely been carried out in developed countries and in children in a specific age range, and it is not clear whether the effect of the SES of parents varies by age. The objective of this study was to investigate the psychopathological profile (including externalizing and internalizing problems) of children aged 7, 9, and 11 years old with low SES in a developing country (Ecuador). The study included 274 children (139 boys and 135 girls), who were divided between medium-SES (n = 133) and low-SES (n = 141) groups. Data were gathered on socioeconomic and anthropometric variables of the children, and the parents completed the Child Behavior Check-List (CBCL). In comparison to the medium-SES group, children in the low-SES group obtained higher scores for internalizing and externalizing symptoms and for total problems, and they obtained lower scores for social competence skills. The housing risk index and school competence were the two main predictors of internalizing and externalizing problems in this population.

SUBMITTER: Perez-Marfil MN

PROVIDER: S-EPMC7034357 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Influence of Socio-Economic Status on Psychopathology in Ecuadorian Children.

Pérez-Marfil María Nieves MN Fernández-Alcántara Manuel M Fasfous Ahmed F AF Burneo-Garcés Carlos C Pérez-García Miguel M Cruz-Quintana Francisco F

Frontiers in psychiatry 20200214

The socioeconomic status (SES) of parents has been reported to have a crucial impact on emotional competence in childhood. However, studies have largely been carried out in developed countries and in children in a specific age range, and it is not clear whether the effect of the SES of parents varies by age. The objective of this study was to investigate the psychopathological profile (including externalizing and internalizing problems) of children aged 7, 9, and 11 years old with low SES in a d ...[more]

PMID: 32116858

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Project description:Since its outbreak, COVID-19 disease has claimed over one hundred thousand lives in the United States, resulting to multiple and complex nation-wide challenges. In this study, we employ global and local regression models to assess the influence of socio-economic and health conditions on COVID-19 mortality in contiguous USA. For a start, stepwise and exploratory regression models were employed to isolate the main explanatory variables for COVID-19 mortality from the ensemble 33 socio-economic and health parameters between January 1st and 16th of September 2020. Preliminary results showed that only five out of the examined variables (case fatality rate, vulnerable population, poverty, percentage of adults that report no leisure-time physical activity, and percentage of the population with access to places for physical activity) can explain the variability of COVID-19 mortality across the Counties of contiguous USA within the study period. Consequently, we employ three global and two local regression algorithms to model the relationship between COVID-19 and the isolated socio-economic and health variables. The outcomes of the regression analyses show that the adopted models can explain 61%-81% of COVID-19 mortality across the contiguous USA within the study period. However, MGWR yielded the highest R2 (0.81) and lowest AICc values (4031), emphasizing that it is the most efficient among the adopted regression models. The computed average adjusted R2 values show that local regression models (mean adj. R2 = 0.80) outperformed the global regression models (mean adj. R2 = 0.64), indicating that the former is ideal for modeling spatial causal relationships. The GIS-based optimized cluster analyses results show that hotspots for COVID-19 mortality as well as socioeconomic variables are mostly delineated in the South, Mid-West and Northeast of contiguous USA. COVID-19 mortality exhibited positive and significant association with black race (0.51), minority (0.48) and poverty (0.34). Whereas, the percentage of persons that attended college was negatively associated with poverty (-0.51), obesity (-0.50) and diabetes (-0.45). Results show that education is crucial to improve socio-economic and health conditions of the Americans. We conclude that investing in people's standard of living would reduce the vulnerability of an entire population.

Project description:BackgroundWe sought to determine whether socio-economic status (SES) is an independent predictor of outcome following total knee (TKR) and hip (THR) replacement in Australians.MethodsIn this prospective cohort study, we included patients undergoing TKR and THR in a public hospital in whom baseline and 12-month follow-up data were available. SES was determined using the Australian Bureau of Statistics 'Index of Relative Advantage and Disadvantage'. Other independent variables included patients' demographics, comorbidities and procedure-related variables. Outcome measures were the International Knee Society Score and Harris Hip Score pain and function subscales, and the Short Form Health Survey (SF-12) physical and mental component scores.ResultsAmong 1,016 patients undergoing TKR and 835 patients undergoing THR, in multiple regression analysis, SES score was not independently associated with pain and functional outcomes. Female sex, older age, being a non-English speaker, higher body mass index and presence of comorbidities were associated with greater post-operative pain and poorer functional outcomes following arthroplasty. Better baseline function, physical and mental health, and lower baseline level of pain were associated with better outcomes at 12 months. In univariate analysis, for TKR, the improvement in SF-12 mental health score post arthroplasty was greater in patients of lower SES (3.8 ± 12.9 versus 1.5 ± 12.2, p=0.008), with a statistically significant inverse association between SES score and post-operative SF-12 mental health score in linear regression analysis (coefficient-0.28, 95% CI: -0.52 to -0.04, p=0.02).ConclusionsWhen adjustments are made for other covariates, SES is not an independent predictor of pain and functional outcome following large joint arthroplasty in Australian patients. However, relative to baseline, patients in lower socioeconomic groups are likely to have greater mental health benefits with TKR than more privileged patients. Large joint arthroplasty should be made accessible to patients of all SES.

Dataset Information

Influence of Socio-Economic Status on Psychopathology in Ecuadorian Children.

Publications

Influence of Socio-Economic Status on Psychopathology in Ecuadorian Children.

Similar Datasets

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