Subjective socioeconomic status, health, and early-life conditions

Kim, Younoh; Radoias, Vlad

doi:10.1177/1359105319828137

Cited by 11 publications

(10 citation statements)

References 28 publications

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“…The association between childhood and subjective SEP could potentially explain the pathway from childhood SEP to adult health via the status generated from growing up with a ‘silver spoon’. However, the influence of childhood SEP on subjective SEP in adulthood has been sparsely studied ( Ferreira et al, 2018 ; Kim & Radoias, 2019 ), especially in Western contexts.…”

Section: Introductionmentioning

confidence: 99%

Explaining subjective social status in two countries: The relative importance of education, occupation, income and childhood circumstances

Lindberg¹,

Chen²,

Olsen³

et al. 2021

SSM - Population Health

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In the literature on social inequalities in health, subjective socioeconomic position (SEP) is increasingly applied as a determinant of health, motivated by the hypothesis that having a high subjective SEP is health-enhancing. However, the relative importance of determinants of subjective SEP is not well understood. Objective SEP indicators, such as education, occupation and income, are assumed to determine individuals' position in the status hierarchy. Furthermore, an extensive literature has shown that past childhood SEP affects adult health. Does it also affect subjective SEP? In this paper, we estimate the relative importance of i) the common objective SEP indicators (education, occupation and income) in explaining subjective SEP, and ii) childhood SEP (childhood financial circumstances and parents' education) in determining subjective SEP, after controlling for objective SEP. Given that the relative importance of these factors is expected to differ across institutional settings, we compare data from two countries: Australia and Norway. We use data from an online survey based on adult samples, with N ≈ 1400 from each country. Ordinary least squares regression is conducted to assess how objective and childhood SEP indicators predict subjective SEP. We use Shapley value decomposition to estimate the relative importance of these factors in explaining subjective SEP. Income was the strongest predictor of subjective SEP in Australia; in Norway, it was occupation. Of the childhood SEP variables, childhood financial circumstances were significantly associated with subjective SEP, even after controlling for objective SEP. This association was the strongest in the Norwegian sample. Only the mother's education had a significant impact on subjective SEP. Our findings highlight the need to understand the specific mechanisms between objective and subjective SEP as determinants of inequalities in health, and to assess the role of institutional factors in influencing these complex relationships.

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Section: Introductionmentioning

confidence: 99%

Explaining subjective social status in two countries: The relative importance of education, occupation, income and childhood circumstances

Lindberg¹,

Chen²,

Olsen³

et al. 2021

SSM - Population Health

View full text Add to dashboard Cite

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“…Moreover, poor mental health influences the wider health and development of adolescents and is also associated with higher alcohol, tobacco, and illicit substances use, adolescent pregnancy, and anti-social behaviors. Together, these factors may result in a downward spiral, increasing socioeconomic inequalities in health during the life course (Haas, 2008;Allen et al, 2014;Kim and Radoias, 2019).…”

Section: Introductionmentioning

confidence: 99%

Trends in Socioeconomic Inequalities in Norwegian Adolescents’ Mental Health From 2014 to 2018: A Repeated Cross-Sectional Study

et al. 2020

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Background: Adolescents' mental health, and its consistent relationship with their socioeconomic background, is a concern that should drive education, health, and employment policies. However, information about this relationship on a national scale is limited. We explore national overall trends and investigate possible socioeconomic disparities in adolescents' mental health, including psychological distress and symptoms of depression, anxiety, and loneliness in Norway during the period 2014-2018. Methods: The present study builds on data retrieved from five waves of the national cross-sectional Ungdata survey (2014-2018). In total 136,525 upper secondary school students (52% girls) completed the questionnaire during the study period. Trends in socioeconomic inequalities were assessed using the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII). Results: The prevalence of students with moderate to high symptoms score and mean symptoms scores of psychological distress (in terms of symptoms of depression, anxiety, and loneliness) increased among girls and boys during 2014-2018, with girls showing higher rates. Our results suggest distinct, but stable, inequalities between socioeconomic groups, both in absolute and relative terms, among girls and boys during the study period. Conclusion: Rising rates of adolescents' psychological distress, particularly among girls, may have long-term consequences for individuals involved and the society as a whole. Future studies should investigate the causes of these results. We did not find evidence of any change in inequalities in adolescents' mental health between socioeconomic groups, suggesting current strategies are not sufficiently addressing mental health inequalities in the adolescent population and therefore a significant need for research and public health efforts.

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“…After several iterations, PLFCMs will reach one of the following states: (1) The state value of node converges to a fixed point, which is called the probabilistic linguistic fixed-point attractor. (2) The state continues to cycle between several fixed states. It is called the probabilistic linguistic limit cycle; (3) It may be confusion, which is useless.…”

Section: Propertymentioning

confidence: 99%

“…1 The physiological function of older adults gradually declines as they age, and their morbidity is also higher than that of other age groups. According to Analysis Report of National Health Services Survey, the prevalence of chronic diseases in older adults is 71%, 2 while the proportion of deaths caused by chronic diseases has reached 86% 3 in China. Chronic diseases not only reduce the quality of life of older adults, but also increase medical expenses and the cost of care, imposing a significant socioeconomic burden.…”

Section: Introductionmentioning

confidence: 99%

“…Previous research demonstrated that a variety of factors, such as natural conditions, socioeconomic status, lifestyle, sickness, access to healthcare, individual demographic characteristics, etc. [1][2][3][4][5][6], have an impact on health. At present, the existing methods for analyzing the factors affecting the health of older adults primarily consider the impact of a single factor or a small number of factors on health, and few consider the interaction between factors or the reverse impact of health on its factors.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic linguistic fuzzy cognitive maps: applications to the critical factors affecting the health of rural older adults

Chen²,

Wang

et al. 2022

BMC Med Inform Decis Mak

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Background Achieving healthy ageing has become the only way for China to alleviate the pressure of ageing, especially in rural areas. However, the factors affecting the health of rural older adults are numerous and complex. It is important to identify the critical factors that affecting the health of older adults in rural areas and provide decision-making support for targeted health interventions. Methods To overcome some limitations of existing works, an extended probabilistic linguistic fuzzy cognitive map model is proposed in this paper as a useful tool for modeling the cause-effect relationship between factors. The proposed model integrates the advantages of probabilistic linguistic term sets and fuzzy cognitive maps. In the end, to rank and identify the critical factors affecting the health, a novel similarity measure based on Euclidean distance and Z-mapping function is proposed. Results The proposed model can effectively deal with the uncertainty of experts and reflect different opinions of groups well. In terms of representing uncertainty and ambiguity, the proposed method outperforms other models in modeling complex systems. In the real-world case analysis, we find that education is the most important factor affecting the health of rural older adults, followed by previous occupational experiences, psychology, and physical exercise, among other things. Intergenerational relationship has become another important factor affecting the health of rural older adults in China as the development of Chinese society. Conclusions From a macro perspective, social economic status, living environment, lifestyle, and health management, are the variables that have the greatest impact on the health of rural older adults. As a result, providing more precise health interventions with the characteristics of factors influencing health is a crucial guarantee for preserving and improving the health of rural older adults in China.

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Subjective socioeconomic status, health, and early-life conditions

Cited by 11 publications

References 28 publications

Explaining subjective social status in two countries: The relative importance of education, occupation, income and childhood circumstances

Explaining subjective social status in two countries: The relative importance of education, occupation, income and childhood circumstances

Trends in Socioeconomic Inequalities in Norwegian Adolescents’ Mental Health From 2014 to 2018: A Repeated Cross-Sectional Study

Probabilistic linguistic fuzzy cognitive maps: applications to the critical factors affecting the health of rural older adults

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