Abstract P212: How Much Do Psychosocial Factors Mediate the Association Between Socioeconomic Status and 1-Year Angina After Myocardial Infarction?

2011 ◽  
Vol 4 (suppl_1) ◽  
Author(s):  
Donna M Buchanan ◽  
Kymberley K Bennett ◽  
Philip G Jones ◽  
Judith H Lichtman ◽  
John A Spertus
Keyword(s):  
Socioeconomic Status ◽  
Depressive Symptoms ◽  
Psychosocial Factors ◽  
Perceived Stress ◽  
Low Socioeconomic Status ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Modeling ◽  
Reserve Capacity ◽  
Capacity Model

Background: Low socioeconomic status (SES) is associated with worse cardiovascular (CV) outcomes. The Reserve Capacity Model (RCM) is a published, but not yet fully tested, framework linking SES, psychosocial factors and health outcomes. “Reserve capacity” is one's inter-/intrapersonal resources for managing stress. We tested the RCM to determine what portion of the association between SES and angina frequency 1 year post-MI is attributable to psychosocial factors. Methods: In 2481 post-MI patients enrolled in the 19-center PREMIER registry, we used confirmatory factor analysis to create latent variables of health-related SES and reserve capacity (including social support, optimism, and internal health locus of control). Structural equation modeling was used to test the associations between baseline SES, 1-month psychosocial factors (perceived stress, reserve capacity, and depressive symptoms) and 1-yr angina, adjusting for age, sex, and baseline angina. Results: The overall correlation between SES and 1-yr angina was significant (r = -.21*). Of this, 37% was explained by psychosocial factors. (See figure.) Higher SES was associated with greater reserve capacity (r = .43*), which was strongly and inversely associated with stress (r = -.68*) and depressive symptoms (r = -.36*). Depressive symptoms were directly associated with angina (r = .12*). (*p < .05) Conclusion: These results validate the RCM, showing that perceived stress, reserve capacity, and depressive symptoms partially mediate the link between SES and 1-yr angina post-MI. This identifies possible areas for intervention to reduce SES-related disparities in angina and potentially other CV outcomes.

scholarly journals How Does Low Socioeconomic Status Increase Blood Lead Levelsin KoreanChildren?

2018 ◽  
Vol 15 (7) ◽  
pp. 1488 ◽  
Author(s):  
Eunjung Kim ◽  
Ho-jang Kwon ◽  
Mina Ha ◽  
Ji-Ae Lim ◽  
Myung Lim ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Environmental Factors ◽  
Low Socioeconomic Status ◽  
Structural Equation ◽  
Blood Lead ◽  
Population Based ◽  
Equation Modeling ◽  
Cross Sectional ◽  
Korean Children ◽  
Low Socioeconomic

Although studies have shown that a low socioeconomic status (SES) is associated with high blood lead levels (BLLs) in children, the mechanism underlying this observation is not well known. To determine how SES influences BLLs via environmental factors in Korean children, we conducted a population-based cross-sectional study of 4744 children aged 5–13 years. Questionnaires on sociodemographic information, environmental factors, and food consumption were administered to the children’s parents. BLLs in the study subjects were measured.The complete set of hypothesized associations was assessed using regression analysis and structural equation modeling. SES was associated with high BLLs. The total effects of nutritional factors, lead in the air and total length of nearby roads, and agriculture on BLLs were −0.062 (p < 0.001), 0.068 (p = 0.005), and 0.038 (p = 0.035), respectively. The direct effects of playing outdoors and SES on BLLs were 0.113 (p < 0.001) and −0.111 (p < 0.001), respectively. Although playing outdoors had a greater direct effect on BLLs than did SES, the total effect of SES (standardized β = −0.132, p < 0.001) was greater than that of other sources owing to indirect effects (β = −0.020, p = 0.004). A low SES was a major risk factor for elevated BLLs via environmental factors.

scholarly journals Factors Influencing Depression and Mental Distress Related to COVID-19 Among University Students in China: Online Cross-sectional Mediation Study (Preprint)

2020 ◽  
Author(s):  
Yanqiu Yu ◽  
Rui She ◽  
Sitong Luo ◽  
Meiqi Xin ◽  
Lijuan Li ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
University Students ◽  
Psychosocial Factors ◽  
Structural Equation ◽  
Large Scale ◽  
Mental Distress ◽  
Severe Depression ◽  
Cognitive Behavioral ◽  
Equation Modeling ◽  
Cross Sectional

BACKGROUND The COVID-19 epidemic may elevate mental distress and depressive symptoms in various populations in China. OBJECTIVE This study investigates the levels of depression and mental distress due to COVID-19, and the associations between cognitive, behavioral, and psychosocial factors, and depression and mental distress due to COVID-19 among university students in China. METHODS A large-scale online cross-sectional study (16 cities in 13 provinces) was conducted among university students from February 1 to 10, 2020, in China; 23,863 valid questionnaires were returned. The Patient Health Questionnaire-9 was used to assess depression. Structural equation modeling was performed to test mediation and suppression effects. RESULTS Of the 23,863 participants, 47.1% (n=11,235) reported high or very high levels of one or more types of mental distress due to COVID-19; 39.1% (n=9326) showed mild to severe depression. Mental distress due to COVID-19 was positively associated with depression. All but one factor (perceived infection risks, perceived chance of controlling the epidemic, staying at home, contacted people from Wuhan, and perceived discrimination) were significantly associated with mental distress due to COVID-19 and depression. Mental distress due to COVID-19 partially mediated and suppressed the associations between some of the studied factors and depression (effect size of 6.0%-79.5%). CONCLUSIONS Both mental distress due to COVID-19 and depression were prevalent among university students in China; the former may have increased the prevalence of the latter. The studied cognitive, behavioral, and psychosocial factors related to COVID-19 may directly or indirectly (via mental distress due to COVID-19) affect depression. Interventions to modify such factors may reduce mental distress and depressive symptoms during the COVID-19 epidemic.

scholarly journals Factors Influencing Depression and Mental Distress Related to COVID-19 Among University Students in China: Online Cross-sectional Mediation Study

10.2196/22705 ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. e22705
Author(s):  
Yanqiu Yu ◽  
Rui She ◽  
Sitong Luo ◽  
Meiqi Xin ◽  
Lijuan Li ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
University Students ◽  
Psychosocial Factors ◽  
Structural Equation ◽  
Large Scale ◽  
Mental Distress ◽  
Severe Depression ◽  
Cognitive Behavioral ◽  
Equation Modeling ◽  
Cross Sectional

Background The COVID-19 epidemic may elevate mental distress and depressive symptoms in various populations in China. Objective This study investigates the levels of depression and mental distress due to COVID-19, and the associations between cognitive, behavioral, and psychosocial factors, and depression and mental distress due to COVID-19 among university students in China. Methods A large-scale online cross-sectional study (16 cities in 13 provinces) was conducted among university students from February 1 to 10, 2020, in China; 23,863 valid questionnaires were returned. The Patient Health Questionnaire-9 was used to assess depression. Structural equation modeling was performed to test mediation and suppression effects. Results Of the 23,863 participants, 47.1% (n=11,235) reported high or very high levels of one or more types of mental distress due to COVID-19; 39.1% (n=9326) showed mild to severe depression. Mental distress due to COVID-19 was positively associated with depression. All but one factor (perceived infection risks, perceived chance of controlling the epidemic, staying at home, contacted people from Wuhan, and perceived discrimination) were significantly associated with mental distress due to COVID-19 and depression. Mental distress due to COVID-19 partially mediated and suppressed the associations between some of the studied factors and depression (effect size of 6.0%-79.5%). Conclusions Both mental distress due to COVID-19 and depression were prevalent among university students in China; the former may have increased the prevalence of the latter. The studied cognitive, behavioral, and psychosocial factors related to COVID-19 may directly or indirectly (via mental distress due to COVID-19) affect depression. Interventions to modify such factors may reduce mental distress and depressive symptoms during the COVID-19 epidemic.

Depressive symptoms, perceived stress, self-efficacy, and outcome expectations: Predict fitness among adolescents with obesity

2017 ◽  
Vol 25 (6) ◽  
pp. 798-809 ◽  
Author(s):  
Heather Tulloch ◽  
Adam Heenan ◽  
Shane Sweet ◽  
Gary S Goldfield ◽  
Glen P Kenny ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Perceived Stress ◽  
Self Efficacy ◽  
Structural Equation ◽  
Outcome Expectations ◽  
Outcome Expectancies ◽  
Outcome Expectancy ◽  
Equation Modeling ◽  
Exercise Interventions ◽  
Efficacy Outcome

The objective of the present study was to test if outcome expectancy mediated the relationship between fitness and self-efficacy, perceived stress, and depressive symptoms.Adolescents with obesity ( n = 228) completed measures of perceived stress and depressive symptoms at baseline, self-efficacy and outcome expectancy at baseline and 3 months, and fitness at baseline and 6 months. Structural equation modeling was used to analyze the data. Results showed that self-efficacy was positively associated with fitness via outcome expectancies. For females, fewer depressive symptoms were linked to fitness via self-efficacy and outcome expectancies. Exercise interventions that enhance exercise self-efficacy, outcome expectancy, and reduce depressive symptoms may increase fitness.

Neonatal Adverse Outcomes, Neonatal Birth Risks, and Socioeconomic Status: Combined Influence on Preterm Infants’ Cognitive, Language, and Motor Development in Brazil

2020 ◽  
Vol 35 (14) ◽  
pp. 989-998
Author(s):  
Carolina Panceri ◽  
Nadia Cristina Valentini ◽  
Rita C. Silveira ◽  
Beth A. Smith ◽  
Renato S. Procianoy
Keyword(s):  
Socioeconomic Status ◽  
Preterm Infants ◽  
Motor Development ◽  
Latent Variables ◽  
Structural Equation ◽  
Infant Development ◽  
Adverse Outcomes ◽  
Equation Modeling ◽  
Socioeconomic Risk

Background: This study extended previous research by investigating the combined effects of neonatal birth risks, neonatal adverse outcomes, and socioeconomic status on preterm neurodevelopment. Method: A total of 184 preterm infants were assessed using the Bayley Scales of Infant Development III in a follow-up clinic in southern Brazil. Structural equation modeling was conducted with 3 latent variables (neonatal birth risks, neonatal adverse outcomes, and socioeconomic status) and 3 outcomes (cognitive, language, and motor development). Results: The analyses showed that neonatal adverse outcomes were associated with infants’ cognitive (b = –0.45, P < .001), language (b = –0.23, P = .001), and motor (b = –0.51, P < .001) development. Socioeconomic status also explained the variances (cognitive: b = 0.20, P = .006; language: b = 0.28, P = .001; and motor: b = 0.21, P = .004), whereas neonatal birth risks remained significant only in the motor development (b = 0.15, P = .040). Conclusion: This study suggests that the most evident contributors to poor neurodevelopment were adverse outcomes and socioeconomic risk factors.

scholarly journals Adolescent Obesity Modeling: A Framework of Socio-Economic Analysis on Public Health

Healthcare ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 925
Author(s):  
Hashem Salarzadeh Jenatabadi ◽  
Nurulaini Abu Shamsi ◽  
Boon-Kwee Ng ◽  
Nor Aishah Abdullah ◽  
Khairul Anam Che Mentri
Keyword(s):  
Socioeconomic Status ◽  
Food Intake ◽  
Body Fat ◽  
Latent Variables ◽  
Structural Equation ◽  
Adolescent Obesity ◽  
Equation Modeling ◽  
Time Data ◽  
Research Areas ◽  
Household Socioeconomic Status

Bayesian Structural Equation Modeling (SEM-Bayesian) was applied across different research areas to model the correlation between manifest and latent variables. The primary purpose of this study is to introduce a new framework of complexity to adolescent obesity modeling based on adolescent lifestyle through the application of SEM-Bayesian. The introduced model was designed based on the relationships among several factors: household socioeconomic status, healthy food intake, unhealthy food intake, lifestyle, body mass index (BMI) and body fat. One of the main contributions of this study is from considering both BMI and body fat as dependent variables. To demonstrate the reliability of the model, especially in terms of its fitting and accuracy, real-time data were extracted and analyzed across 881 adolescents from secondary schools in Tehran, Iran. The output of this study may be helpful for researchers who are interested in adolescent obesity modeling based on the lifestyle and household socioeconomic status of adolescents.

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