State level income inequality affects cardiovascular stress responses: Evidence from the Midlife in the United States (MIDUS) study

Ryan, Megan; Gallagher, Stephen; Jetten, Jolanda; Muldoon, Orla T.

doi:10.1016/j.socscimed.2022.115359

Cited by 3 publications

(3 citation statements)

References 76 publications

(107 reference statements)

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“…[20][21][22] In addition, living in lower-income-stressful environments is associated with individual-level health, and previous studies have emphasized the psychophysiological pathway linking income inequality and health. 23,24 Individuals with higher incomes may have certain coping strategies for stress (ie, greater material resources, attention, and information processing ability), which could increase their mental and physical resilience to external stressors. 25,26 Those with higher incomes may pay more attention to the control and treatment of basic diseases (hypertension, diabetes, etc.…”

Section: Discussionmentioning

confidence: 99%

Cardiovascular Disease in China: Socioeconomic Status Variation in Prevalence

Zhang,

Shen,

Wang

et al. 2023

RMHP

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Cardiovascular disease is the single largest contributor to global mortality and the leading cause of both death and premature death in China. Data on the association between cardiovascular disease and socioeconomic status are sparse, especially for Asian countries. Our study collected data to describe the socioeconomic status variation across cardiovascular disease using a large nationwide cross-sectional study. Methods: We chose participants using the cluster sampling method, prepared a face-to-face questionnaire interview for the selected community residents, and collected information on health conditions, socioeconomic status, demographics, and comorbidities. All collected data were reported as frequencies and corresponding percentages. Linear regression and simple and multivariable logistic regression were performed to identify the prevalence variation. All statistical analyses were performed using SPSS version 26 software. Results: Socioeconomic information was available for 394,688 participants (covering most provincial districts). The prevalence of cardiovascular disease was 7.9%. The prevalence was higher in rural areas than that in urban areas (rural, 8.4%; urban, 7.5%). There was a negative relationship between urbanization and cardiovascular disease prevalence. Furthermore, cardiovascular disease prevalence had a negative relationship with average earnings. Conclusion: This cross-sectional analysis of socioeconomic status variation in the prevalence of cardiovascular disease in China showed a significant negative relationship between regional and individual socioeconomic status and cardiovascular disease. The results imply that governments would benefit communities by focusing on effective and targeted interventions for prevention, screening, and treatment in individuals who may be in the socioeconomic status with a high risk for cardiovascular disease.Plain Language Summary: Benefits from the inclusion of many provinces, and large sample size, this study provided important new viewpoints on the prevalence of CVD. We described the current CVD status in China and the socioeconomic status variation on cardiovascular disease in the prevalence. In our study, significant differences were observed in iSES and CVD. And we identified the rSES in CVD prevalence disparities among provincial districts based on large administrative data sets. These results are essential for the government to put the target prevention programs and effective public health to those in status with a high risk to reduce prevalence. Besides, the English language in our manuscript had been proofread and revised by professional editing service in Editage.

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Section: Discussionmentioning

confidence: 99%

Cardiovascular Disease in China: Socioeconomic Status Variation in Prevalence

Zhang,

Shen,

Wang

et al. 2023

RMHP

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“…Building on this knowledge, increasing attention has thus been placed on advancing research by using available biomarkers associated with CVDs. [6][7][8][9] In social sciences and medicine, attention has primarily been directed towards linking just a few selected biomarkers acting as antecedents of CVDs to issues such as stress levels and socioeconomic differences, overlooking the broader picture of how a set of biomarkers could combine with existing risk factors to predict the onset of CVDs. We argue that by leveraging available secondary data collected via routine assessments, this knowledge represents a valuable asset for health systems to envision more targeted interventions aimed at early diagnosis and prevention of CVDs, thereby reducing the economic and societal burden they impose.…”

Section: Introductionmentioning

confidence: 99%

Identifying Biomarkers of Cardiovascular Diseases with Machine Learning: Evidence from The UK Household Longitudinal Study

Nikolaou,

Massaro,

Fakhimi

et al. 2024

MRAJ

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Cardiovascular diseases are a significant global health concern, responsible for one-third of deaths worldwide and posing a substantial burden on society and national healthcare systems. To effectively address this challenge and develop targeted intervention strategies, the ability to predict cardiovascular diseases from standardized assessments, such as occupational health encounters or national surveys, is critical. This study aims to assist these efforts by identifying a set of biomarkers, which together with known risk factors, can predict cardiovascular diseases on the onset. We used a sample of 7,767 individuals from the UK household longitudinal study ‘Understanding Society’ to train several machine learning models able to pinpoint biomarkers and risk factors at baseline that predict cardiovascular diseases at a ten-year follow-up. A logistic regression model was trained for comparison. A gaussian naïve bayes classifier returned 82% recall in contrast to 48% of the logistic regression, allowing us to identify the most prominent biomarkers predicting cardiovascular diseases. These findings show the opportunity to use machine learning to identify a wide range of previously overlooked biomarkers associated with cardiovascular diseases onset and thus encourage the implementation of such a model in the early diagnosis and prevention of cardiovascular diseases in future research and practice.

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“…For now, available evidence seems to suggest that chronic stress and the disadvantages that co-exist with traumatic experiences tend to make the establishment of predictable and healthy lifestyle practices difficult. Indeed, disadvantaged circumstances would appear to be a type of stress in and of itself (Ryan et al, 2021;Ryan et al, 2022).…”

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confidence: 99%

The Social Psychology of Trauma

Muldoon

2024

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Many of us have been affected by trauma and struggle to manage our health and well-being. The social psychological approach to health highlights how social and cultural forces, as much as individual ones, are central to how we experience and cope with adversity. This book integrates psychology, politics, and medicine to offer a new understanding that speaks to the causes and consequences of traumatic experiences. Connecting the personal with the political, Muldoon details the evidence that traumatic experiences can, under certain conditions, impact people's political positions and appetite for social change. This perspective reveals trauma as a socially situated phenomenon linked to power and privilege or disempowerment and disadvantage. The discussion will interest those affected by trauma and those supporting them, as well as students, researchers, practitioners, and policy makers in social psychology, health and clinical psychology, and political science. This title is available as open access on Cambridge Core.

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State level income inequality affects cardiovascular stress responses: Evidence from the Midlife in the United States (MIDUS) study

Cited by 3 publications

References 76 publications

Cardiovascular Disease in China: Socioeconomic Status Variation in Prevalence

Cardiovascular Disease in China: Socioeconomic Status Variation in Prevalence

Identifying Biomarkers of Cardiovascular Diseases with Machine Learning: Evidence from The UK Household Longitudinal Study

The Social Psychology of Trauma

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