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Journal articles on the topic 'Health; socioecomic position'

Author: Grafiati

Published: 3 June 2025

Last updated: 6 July 2025

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1

Nettle, Daniel, and Melissa Bateson. "Childhood and adult socioeconomic position interact to predict health in mid life in a cohort of British women." PeerJ 5 (June 29, 2017): e3528. https://doi.org/10.7717/peerj.3528.

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Galobardes, B., J. Lynch, and G. D. Smith. "Measuring socioeconomic position in health research." British Medical Bulletin 81-82, no. 1 (2007): 21–37. http://dx.doi.org/10.1093/bmb/ldm001.

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Turner, R. Jay, Tony N. Brown, and William Beardall Hale. "Race, Socioeconomic Position, and Physical Health." Journal of Health and Social Behavior 58, no. 1 (2017): 23–36. http://dx.doi.org/10.1177/0022146516687008.

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A substantial and long-standing body of research supports the widely held conclusion that socioeconomic position (SEP) is a primary determinant of physical health risk. However, supporting evidence derives almost entirely from studies of dominantly white populations, and more recent research suggests that this relationship may vary across race-ethnicity. This article considers the extent to which such evidence applies to African Americans. It does so by examining the within-race relationships between SEP and physical health utilizing alternative research definitions of health and a nearly exhaustive array of measures of SEP. The results offer minimal support for SEP as a fundamental cause of disease among African Americans. They do not challenge the widely held view that health differences are rooted in the fundamental conditions of social context and experience. Rather, they indicate that these conditions tend to be defined more by being black than by being of lower SEP.

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Gianaros, Peter J., and Stephen B. Manuck. "Neurobiological Pathways Linking Socioeconomic Position and Health." Psychosomatic Medicine 72, no. 5 (2010): 450–61. http://dx.doi.org/10.1097/psy.0b013e3181e1a23c.

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Moreno-Maldonado, Concepción, Pilar Ramos, Carmen Moreno, and Francisco Rivera. "Direct and Indirect Influences of Objective Socioeconomic Position on Adolescent Health: The Mediating Roles of Subjective Socioeconomic Status and Lifestyles." International Journal of Environmental Research and Public Health 16, no. 9 (2019): 1637. http://dx.doi.org/10.3390/ijerph16091637.

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The use of composite indices and subjective measures to evaluate socioeconomic position, taking into account the effect of inequalities on adolescent health-related behaviors, can contribute to understanding the effect of inequalities on health during adolescence. The aim of this study was to examine the direct and indirect contribution of objective and subjective socioeconomic factors in a broad range of health and lifestyles outcomes. The data come from a representative sample of adolescents (N = 15,340; M age = 13.69) of the Health Behavior in School-aged Children study in Spain. Structural equation modeling was used for data analysis. A global index for evaluating objective socioeconomic position predicted both health and healthy lifestyles. Subjective socioeconomic status mediated the relationship between objective socioeconomic position and health but did not have a significant effect on healthy lifestyles when objective indicators were considered. Lastly, fit indices of the multiple-mediator model—including the direct effect of objective socioeconomic position on health and its indirect effects through the subjective perception of wealth and lifestyles—explained 28.7% of global health variance. Interventions aimed at reducing the impact of health inequalities should address, in addition to material deprivation, the psychological and behavioral consequences of feeling poor.

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Salmond, Clare, and Peter Crampton. "Measuring socioeconomic position in New Zealand." Journal of Primary Health Care 4, no. 4 (2012): 271. http://dx.doi.org/10.1071/hc12280.

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INTRODUCTION: Measures of socioeconomic position (SEP) are widely used in health research. AIM: To provide future researchers with empirically based guidance about the relative utility of five measures of SEP in predicting health outcomes. METHODS: Data from 12 488 adults were obtained from the 2006 New Zealand Health Survey. Seven health-related outcome measures with expected variations by SEP are modelled using five measures of SEP: a census-based small-area index of relative socioeconomic deprivation, NZDep2006; a questionnaire-based individual-level index of socioeconomic deprivation, NZiDep; an index of living standards, ELSI; education, measured by highest qualification; and equivalised household income. RESULTS: After including the individual measure of deprivation, the area-based measure of deprivation adds useful explanatory power, and, separately, the broader spectrum provided by the living standards index adds only a small amount of extra explanatory power. The education and household income variables add little extra explanatory power. DISCUSSION: Both NZiDep and ELSI are useful health-outcome predictors. NZiDep is the cheapest data to obtain and less prone to missing data. The area index, NZDep, is a useful addition to the arsenal of individual SEP indicators, and is a reasonable alternative to them where the use of individual measures is impracticable. Education and household income, using commonly used measurement tools, may be of limited use in research if more proximal indicators of SEP are available. NZDep and NZiDep are cost-effective measures of SEP in health research. Other or additional measures may be useful if costs allow and/or for topic-related hypothesis testing. KEYWORDS: Deprivation; inequalities; living standards; New Zealand; socioeconomic position

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Robert, Stephanie A. "SOCIOECONOMIC POSITION AND HEALTH: The Independent Contribution of Community Socioeconomic Context." Annual Review of Sociology 25, no. 1 (1999): 489–516. http://dx.doi.org/10.1146/annurev.soc.25.1.489.

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Lwin, Kaung Suu, Shuhei Nomura, Daisuke Yoneoka, Peter Ueda, Sarah Krull Abe, and Kenji Shibuya. "Associations between parental socioeconomic position and health-seeking behaviour for diarrhoea and acute respiratory infection among under-5 children in Myanmar: a cross-sectional study." BMJ Open 10, no. 3 (2020): e032039. http://dx.doi.org/10.1136/bmjopen-2019-032039.

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ObjectivesTo examine the associations of parental social and economic position with health-seeking behaviour for diarrhoea and acute respiratory infection (ARI) among under-5 children in Myanmar and explore potential underlying mechanisms.DesignA cross-sectional study.SettingA secondary dataset from the nationwide 2015–2016 Myanmar Demographic and Health Survey (MDHS).ParticipantsAll under-5 children in the sampled households with reported symptoms of diarrhoea and ARI during the 2-week period preceding the MDHS survey interview.Primary and secondary outcome measuresFour parental health-seeking behaviours: ‘seeking treatment’, ‘formal health provider’, ‘public provider’ and ‘private provider’ were considered. Social and economic positions were determined by confirmatory factor analysis. Multilevel logistic regressions were employed to examine the associations of social and economic positions with health-seeking behaviours for diarrhoea and ARI. Mediation analyses were conducted to explore potential underlying mechanisms in these associations.ResultsOf the 4099 under-5 children from the sampled households in MDHS, 427 (10.4%) with diarrhoea and 131 (3.2%) with ARI were considered for the analyses. For diarrhoea, social position was positively associated with seeking treatment and private provider use (adjusted OR: 1.60 (95% CIs: 1.07 to 2.38) and 1.83 (1.00 to 3.34), respectively). Economic position was positively associated with private provider use for diarrhoea (1.57 (1.07 to 2.30)). Negative associations were observed between social and economic positions with public provider use for diarrhoea (0.55 (0.30 to 0.99) and 0.64 (0.43 to 0.94), respectively). Social position had more influence than economic position on parental health-seeking behaviour for children with diarrhoea. No evidence for a significant association of social and economic position with health-seeking for ARI was observed.ConclusionsSocial and economic positions were possible determinants of health-seeking behaviour for diarrhoea among children; and social position had more influence than economic position. The results of this study may contribute to improve relevant interventions for diarrhoea and ARI among children in Myanmar.

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Jones, Jennifer R. A., Sue Berney, Bronwen Connolly, et al. "Socioeconomic Position and Health Outcomes Following Critical Illness." Critical Care Medicine 47, no. 6 (2019): e512-e521. http://dx.doi.org/10.1097/ccm.0000000000003727.

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Akkoyun-Farinez, Julie, Abdou Y. Omorou, Johanne Langlois, et al. "Measuring adolescents’ weight socioeconomic gradient using parental socioeconomic position." European Journal of Public Health 28, no. 6 (2018): 1097–102. http://dx.doi.org/10.1093/eurpub/cky064.

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Komulainen, Kaisla, Murray A. Mittleman, Markus Jokela, et al. "Socioeconomic position and intergenerational associations of ideal health behaviors." European Journal of Preventive Cardiology 26, no. 15 (2019): 1605–12. http://dx.doi.org/10.1177/2047487319850959.

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Background Promoting ideal cardiovascular health behaviors is an objective of the American Heart Association 2020 goals. We hypothesized that ideal health behaviors of parents are associated with health behaviors of their adult offspring, and that higher socioeconomic position in either generation enhances intergenerational associations of ideal health behaviors. Design Prospective cohort study. Methods We included 1856 Young Finns Study participants who had repeated measurements of socioeconomic position (education, income, occupation), smoking status, body mass index, physical activity and diet from 2001, 2007 and 2011, and data on parental socioeconomic position and health behaviors from 1980. We calculated the total number of ideal behaviors in both generations using American Heart Association definitions. Intergenerational associations were examined using ordinal and linear multilevel regression with random intercepts, in which each participant contributed one, two or three measurements of adult health behaviors (2001, 2007, 2011). All analyses were adjusted for offspring sex, birth year, age, parental education and single parenthood. Results Overall, parental ideal health behaviors were associated with ideal behaviors among offspring (odds ratio (OR) 1.28, 95% confidence interval 1.17, 1.39). Furthermore, ORs for these intergenerational associations were greater among offspring whose parents or who themselves had higher educational attainment (OR 1.56 for high vs. OR 1.19 for low parental education; P = 0.01 for interaction, OR 1.32 for high vs. OR 1.04 for low offspring education; P = 0.02 for interaction). Similar trends were seen with parental income and offspring occupation. Results from linear regression analyses were similar. Conclusions These prospective data suggest higher socioeconomic position in parents or in their adult offspring strengthens the intergenerational continuum of ideal cardiovascular health behaviors.

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Frances, R. J. "Association of Socioeconomic Position With Health Behaviors and Mortality." Yearbook of Psychiatry and Applied Mental Health 2012 (January 2012): 188–89. http://dx.doi.org/10.1016/j.ypsy.2011.07.035.

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Roizen, M. F. "Association of Socioeconomic Position With Health Behaviors and Mortality." Yearbook of Anesthesiology and Pain Management 2011 (January 2011): 235–36. http://dx.doi.org/10.1016/j.yane.2011.01.014.

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Lal, Anita, Mohammad Siahpush, Marjory Moodie, Anna Peeters, and Robert Carter. "Weighting Health Outcomes by Socioeconomic Position Using Stated Preferences." PharmacoEconomics - Open 2, no. 1 (2017): 43–51. http://dx.doi.org/10.1007/s41669-017-0036-1.

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Perna, Laura, Andreas Mielck, Maria E. Lacruz, et al. "Socioeconomic position, resilience, and health behaviour among elderly people." International Journal of Public Health 57, no. 2 (2011): 341–49. http://dx.doi.org/10.1007/s00038-011-0294-0.

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Stringhini, Silvia. "Association of Socioeconomic Position With Health Behaviors and Mortality." JAMA 303, no. 12 (2010): 1159. http://dx.doi.org/10.1001/jama.2010.297.

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Sankar, Uma Vadassery, V. Raman kutty, and TN Anand. "Measuring childhood socioeconomic position in health research:Development and validation of childhood socioeconomic position questionnaire using mixed method approach." Health Promotion Perspectives 9, no. 1 (2019): 40–49. http://dx.doi.org/10.15171/hpp.2019.05.

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Background: There is no single best indicator to assess the childhood socioeconomic position (CSEP) in public health research. The aim of the study is to develop and validate a new questionnaire, with adequate psychometric properties, to measure the childhood SEP of the young adults. Methods: The first phase consisted of a qualitative phase to identify the variables to measure childhood SEP through the in-depth interviews among 15 young adults (18-45 years) of rural Kerala. The second phase was a quantitative phase to validate the questionnaire through a cross sectional survey among 200 young adults of Kerala. We did content validity, reliability tests and construct validity by using exploratory factor analysis of the questionnaire to demonstrate its psychometric properties. Results: The qualitative analysis reported 26 variables spread across 5 domains to measure the CSEP. Finally, the questionnaire has 11 questions with 3 domains named as value added through paternity, maternal occupation-related factors and parental education. The questionnaire has good reliability (Cronbach's α=0.88) also. Conclusion: We have developed a reliable and valid questionnaire to measure the childhood SEP of younger adults and can be used in various public health research.

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Manuel, Douglas G., Carol Bennett, Richard Perez, et al. "Burden of health behaviours and socioeconomic position on health care expenditure in Ontario." F1000Research 8 (March 18, 2019): 303. http://dx.doi.org/10.12688/f1000research.18205.1.

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Background: Smoking, unhealthy alcohol consumption, poor diet and physical inactivity are leading risk factors for morbidity and mortality, and contribute substantially to overall healthcare costs. The availability of health surveys linked to health care provides population-based estimates of direct healthcare costs. We estimated health behaviour and socioeconomic-attribute healthcare costs, and how these have changed during a period when government policies have aimed to reduce their burden. Methods: The Ontario samples of the Canadian Community Health Surveys (conducted in 2003, 2005, and 2007-2008) were linked at the individual level to all records of health care use of publicly funded healthcare. Generalized linear models were estimated with a negative binomial distribution to ascertain the relationship of health behaviours and socioeconomic risk factors on health care costs. The multivariable cost model was then applied to unlinked, cross-sectional CCHS samples for each year from 2004 to 2013 to examine the evolution of health behaviour and socioeconomic-attributable direct health care expenditures over a 10-year period. Results: We included 80,749 respondents, aged 25 years and older, and 312,952 person-years of follow-up. The cost model was applied to 200,324 respondents aged 25 years and older (CCHS 2004 to 2013). During the 10-year period from 2004 to 2013, smoking, unhealthy alcohol consumption, poor diet and physical inactivity attributed to 22% of Ontario’s direct health care costs. Ontarians in the most disadvantaged socioeconomic position contributed to 15% of the province’s direct health care costs. Taken together, health behaviours and socioeconomic position were associated with 34% ($134 billion) of direct health care costs (2004 to 2013). Over this time period, we estimated a 1.9% reduction in health care expenditure ($5.0 billion) attributable to improvements in some health behaviours, most importantly reduced rates of smoking. Conclusions: Health behaviours and socioeconomic position cause a large direct health care system cost burden.

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Manuel, Douglas G., Carol Bennett, Richard Perez, et al. "Burden of health behaviours and socioeconomic position on health care expenditure in Ontario." F1000Research 8 (October 16, 2019): 303. http://dx.doi.org/10.12688/f1000research.18205.2.

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Background: Smoking, unhealthy alcohol consumption, poor diet and physical inactivity are leading risk factors for morbidity and mortality, and contribute substantially to overall healthcare costs. The availability of health surveys linked to health care provides population-based estimates of direct healthcare costs. We estimated health behaviour and socioeconomic-attribute healthcare costs, and how these have changed during a period when government policies have aimed to reduce their burden. Methods: The Ontario samples of the Canadian Community Health Surveys (conducted in 2003, 2005, and 2007-2008) were linked at the individual level to all records of health care use of publicly funded healthcare. Generalized linear models were estimated with a negative binomial distribution to ascertain the relationship of health behaviours and socioeconomic risk factors on health care costs. The multivariable cost model was applied to unlinked, Ontario CCHS samples for each year from 2004 to 2013 to examine the evolution of health behaviour and socioeconomic-attributable direct health care expenditures over a 10-year period. Results: We included 80,749 respondents, aged 25 years and older, and 312,952 person-years of follow-up. The cost model was applied to 200,324 respondents aged 25 years and older (CCHS 2004 to 2013). During the 10-year period from 2004 to 2013, smoking, unhealthy alcohol consumption, poor diet and physical inactivity attributed to 22% of Ontario’s direct health care costs. Ontarians in the most disadvantaged socioeconomic position contributed to 15% of the province’s direct health care costs. Combined, these health behaviour and socioeconomic risk factors were associated with 34% ($134 billion) of direct health care costs (2004 to 2013). Over this time period, we estimated a 1.9% reduction in health care expenditure ($5.0 billion) attributable to improvements in some health behaviours, most importantly reduced rates of smoking. Conclusions: Adverse health behaviours and socioeconomic position cause a large direct health care system cost burden.

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Barboza Solís DDS, MSc, PhD, Cristina, and Romain Fantin MSc. "The Role of Socioeconomic Position in Determining Tooth Loss in Elderly Costa Rican: Findings from the CRELES Cohort." Odovtos - International Journal of Dental Sciences 19, no. 3 (2017): 79. http://dx.doi.org/10.15517/ijds.v19i3.29851.

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Objective: Differences in health status between socioeconomic groups continue to challenge epidemiological research. To evaluate health inequalities in tooth loss, using indicators of socioeconomic position (education level, occupation and subjective economic situation), in a large representative sample of elderly Costa Ricans, can contribute to conceive better adapted public health interventions. Methods: Data are from the Costa Rican Longevity and Healthy Aging Study (CRELES Pre-1945), a longitudinal study of a nationally representative sample of elders. 2827 participants were included in the study using data from the first wave conducted in 2005, and analyzed cross-sectionally. The sample was imputed for missing data using a multiple imputation model. Tooth loss was self-reported and informed about the quantity of missing teeth. Information on participant’s socioeconomic factors was collected via a questionnaire, including three measures approaching socioeconomic position: education level, occupation and subjective economic situation. Additional variables were included in the multivariate analyses as potential confounders. Results: Tooth loss was found to be strongly socially patterned, using variables characterizing socioeconomic position, mainly education level, occupational status and subjective economic situation. Conclusions: To highlight how socioeconomic position relates to tooth loss, can allow a better understanding of the origins of the social gradient in oral health, to tackle the most common chronic diseases across the world.

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Herd, Pamela, Brian Goesling, and James S. House. "Socioeconomic Position and Health: The Differential Effects of Education versus Income on the Onset versus Progression of Health Problems." Journal of Health and Social Behavior 48, no. 3 (2007): 223–38. http://dx.doi.org/10.1177/002214650704800302.

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This article seeks to elucidate the relationship between socioeconomic position and health by showing how different facets of socioeconomic position (education and income) affect different stages (onset vs. progression) of health problems. The biomedical literature has generally treated socioeconomic position as a unitary construct. Likewise, the social science literature has tended to treat health as a unitary construct. To advance our understanding of the relationship between socioeconomic position and health, and ultimately to foster appropriate policies and practices to improve population health, a more nuanced approach is required—one that differentiates theoretically and empirically among dimensions of both socioeconomic position and health. Using data from the Americans' Changing Lives Study (1986 through 2001/2002), we show that education is more predictive than income of the onset of both functional limitations and chronic conditions, while income is more strongly associated than education with the progression of both.

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Galobardes, B. "Indicators of socioeconomic position (part 1)." Journal of Epidemiology & Community Health 60, no. 1 (2006): 7–12. http://dx.doi.org/10.1136/jech.2004.023531.

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Galobardes, B. "Indicators of socioeconomic position (part 2)." Journal of Epidemiology & Community Health 60, no. 2 (2006): 95–101. http://dx.doi.org/10.1136/jech.2004.028092.

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Mckenzie, S., K. Carter, T. Blakely, and V. Ivory. "P1-206 Effects of childhood socioeconomic position on subjective health and health behaviours in adulthood: how much is mediated by adult socioeconomic position?" Journal of Epidemiology & Community Health 65, Suppl 1 (2011): A123. http://dx.doi.org/10.1136/jech.2011.142976d.99.

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Orton, Lois Catherine, Andy Pennington, Shilpa Nayak, et al. "What is the evidence that differences in ‘control over destiny’ lead to socioeconomic inequalities in health? A theory-led systematic review of high-quality longitudinal studies on pathways in the living environment." Journal of Epidemiology and Community Health 73, no. 10 (2019): 929–34. http://dx.doi.org/10.1136/jech-2019-212565.

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BackgroundLow control and high demand in the places where people work has been shown to partially explain why those in lower socioeconomic positions experience poorer health than their counterparts in higher socioeconomic positions. It would seem likely then that experiences of control in the wider living environment, beyond people’s places of work, might also play a role in shaping these health inequalities. Our recent review of theory revealed potential pathways by which low control in the living environment might explain the social patterning of health via low control beliefs and low actual control.MethodsBased on the potential pathways identified in our review of theory, we conducted a systematic review of longitudinal studies on the relationship between low control in the living environment and social inequalities in health published by January 2019, in English.ResultsSix studies were included in the review. Taken together, they provide evidence that lower social positions are associated with lower control beliefs and poorer health outcomes, in terms of heart disease, anxiety, depression and self-rated health, and that some of the association between low social position and health outcomes is explained by low control beliefs. No studies investigated the pathway from low actual control to poorer health in more disadvantaged groups.ConclusionThere is strong evidence from a small number of high-quality longitudinal studies that low perceived control in the living environment may play an important role in the pathways leading from low social position to poorer health and well-being. Further studies are needed to distinguish between the effects of having low control beliefs and having actual low control.

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Morris, N. M. "The influence of socioeconomic position on health--and vice versa." American Journal of Public Health 86, no. 11 (1996): 1649–50. http://dx.doi.org/10.2105/ajph.86.11.1649-a.

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Winnersjö, Rocio, Antonio Ponce de Leon, Joaquim F. Soares, and Gloria Macassa. "Violence and self-reported health: does individual socioeconomic position matter?" Journal of Injury and Violence Research 4, no. 2 (2012): 93–102. http://dx.doi.org/10.5249/jivr.v4i2.122.

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Choi, Yong-Jun, Baek-Geun Jeong, Sung-Il Cho, et al. "A Review on Socioeconomic Position Indicators in Health Inequality Research." Journal of Preventive Medicine and Public Health 40, no. 6 (2007): 475. http://dx.doi.org/10.3961/jpmph.2007.40.6.475.

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Materia, E. "Hysterectomy and socioeconomic position in Rome, Italy." Journal of Epidemiology & Community Health 56, no. 6 (2002): 461–65. http://dx.doi.org/10.1136/jech.56.6.461.

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Wu, Yu-Tzu, Sam Gnanapragasam, Albert Sanchez-Niubo, et al. "Childhood socioeconomic position and healthy ageing: results from five harmonised cohort studies in the ATHLOS consortium." BMJ Public Health 3, no. 1 (2025): e001590. https://doi.org/10.1136/bmjph-2024-001590.

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IntroductionChildhood socioeconomic position (SEP) has been identified as a key determinant of health. However, earlier literature is largely from high-income countries and provides limited evidence on the prolonging impacts of childhood disadvantage on healthy ageing across diverse settings and populations. The aim of this study is to investigate the associations between childhood SEP and healthy ageing across multiple countries and the mediation effects of adult SEP, individual education and wealth, on these associations.MethodsUsing the harmonised dataset of five cohort studies in the Ageing Trajectories of Health-Longitudinal Opportunities and Synergies (ATHLOS) project, this study was based on 57 956 people aged ≥50 years (women: 53.3%) living in China, Finland, UK, Poland, South Africa and Mexico. The associations between childhood SEP (parental education and occupation) and healthy ageing scores were examined using linear regression modelling. Causal mediation analysis was carried out to estimate the percentage of indirect effects via adult SEP (individual education and wealth).ResultsHigher levels of childhood SEP were associated with higher healthy ageing scores by up to five points and similar patterns were observed across populations from different countries. The associations were mediated by adult SEP and the range of mediation effects was between 21% and 78%.ConclusionsThis study found childhood SEP was associated with poor health in later life across high-income, middle-income and low-income countries. Addressing socioeconomic disadvantage, such as improving education attainment, may moderate the impacts of adversity in early life and support health and functioning in later life.

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Elgar, Frank J., Britt McKinnon, Torbjørn Torsheim, et al. "Patterns of Socioeconomic Inequality in Adolescent Health Differ According to the Measure of Socioeconomic Position." Social Indicators Research 127, no. 3 (2015): 1169–80. http://dx.doi.org/10.1007/s11205-015-0994-6.

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Laaksonen, Mikko, Ossi Rahkonen, Pekka Martikainen, and Eero Lahelma. "Socioeconomic Position and Self-Rated Health: The Contribution of Childhood Socioeconomic Circumstances, Adult Socioeconomic Status, and Material Resources." American Journal of Public Health 95, no. 8 (2005): 1403–9. http://dx.doi.org/10.2105/ajph.2004.047969.

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Rattay, Petra, Miriam Blume, Benjamin Wachtler, et al. "Socioeconomic position and self-rated health among female and male adolescents: The role of familial determinants in explaining health inequalities. Results of the German KiGGS study." PLOS ONE 17, no. 4 (2022): e0266463. http://dx.doi.org/10.1371/journal.pone.0266463.

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Objective Although health inequalities in adolescence are well documented, the underlying mechanisms remain unclear. Few studies have examined the role of the family in explaining the association between the family’s socioeconomic position and adolescents’ self-rated health. The current study aimed to explore whether the association between socioeconomic position and self-rated health was mediated by familial determinants. Methods Using data from wave 2 of the”German Health Interview and Examination Survey for Children and Adolescents” (KiGGS) (1,838 female and 1,718 male 11- to 17-year-olds), linear regression analyses were conducted to decompose the total effects of income, education, occupational status, socioeconomic position index and adolescents’ subjective social status on self-rated health into direct effects and indirect effects through familial determinants (family cohesion, parental well-being, parental stress, parenting styles, parental obesity, smoking and sporting activity). Results A significant total effect of all socioeconomic position indicators on self-rated health was found, except for income in male adolescents. In female adolescents, more than 70% of the total effects of each socioeconomic position indicator were explained by familial mediators, whereas no significant direct effects remained. The most important mediator was parental well-being, followed by family cohesion, parental smoking and sporting activity. In male adolescents, the associations between income, parental education, the socioeconomic position index and subjective social status were also mediated by familial determinants (family cohesion, parental smoking, obesity and living in a single-mother family). However, a significant direct effect of subjective social status remained. Conclusion The analysis revealed how a family’s position of socioeconomic disadvantage can lead to poorer health in adolescents through different family practices. The family appears to play an important role in explaining health inequalities, particularly in female adolescents. Reducing health inequalities in adolescence requires policy interventions (macro-level), community-based strategies (meso-level) and programs to improve parenting and family functioning (micro-level).

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Dobe, Madhumita, and C. S. Taklikar. "Health Inequalities in India â€“ Will Looking through The Social Determinants Lens, Make A Difference?" Journal of Comprehensive Health 7, no. 2 (2019): 6–11. http://dx.doi.org/10.53553/jch.v07i02.002.

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In other words, what good will universal health coverage be, if we cannot change the circumstances in which people are born, grow up, live, work and age (the social determinants) These conditions are, in turn, shaped by political, social, and economic forces resulting in differences in health that are closely linked with social disadvantages, most of which are avoidable /preventable through well designed and implemented policies and programs.1These avoidable inequalities within and between societies which determine their risk of illness and the actions taken to prevent them becoming ill or treat illness when it occurs are termed Health inequities.From time immemorial public health has tried to look into differences in numbers (prevalence/incidence) in different socioeconomic positions and revealed that, health and illness follow a social gradient- the lower the socioeconomic position, the worse the health. 1

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Ljung, Rickard, and Johan Hallqvist. "Misclassification of occupation-based socioeconomic position and gender comparisons of socioeconomic risk." Scandinavian Journal of Public Health 35, no. 1 (2007): 17–22. http://dx.doi.org/10.1080/14034940600777260.

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Aims: Because occupational classification systems tend to be less precise in the female sector of the working market there has been concern that this might imply more misclassification of socioeconomic position among women, biasing comparisons of gender-specific socioeconomic differences in risk. Methods: The Stockholm Heart Epidemiology Program (SHEEP) is a population-based case-control study of risk factors for incident myocardial infarction. The study base included all Swedish citizens aged 45—70 in Stockholm County during 1992—94, 550 female and 1201 male cases, and 776 female and 1538 male controls. The use of an occupational classification as the base for categorizing socioeconomic position was compared with socioeconomic position based on detailed self-reported information on job titles and work tasks. Results: Women are categorized into fewer occupational categories than men and the socioeconomic heterogeneity within occupational categories is substantial for women as has been reported by others. However, despite more occupational categories for male types of jobs the socioeconomic heterogeneity within occupational categories is actually larger for men, implying larger misclassification among men. In simulations with different levels of socioeconomic misclassification among women, the effects on the gender comparison of socioeconomic differences in disease risk were small and they were mostly compensated for by less misclassification among men. Conclusions: The findings do not support the assumption that misclassification of socioeconomic position among women due to a restricted working market and a crude occupational classification for female jobs is an important issue when comparing measures of socioeconomic inequalities in health between men and women.

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Andrade, Fabíola Bof de, José Leopoldo Ferreira Antunes, Paulo Roberto Borges de Souza Junior, Maria Fernanda Lima-Costa, and Cesar De Oliveira. "Life course socioeconomic inequalities and oral health status in later life." Revista de Saúde Pública 52, Suppl 2 (2019): 7s. http://dx.doi.org/10.11606/s1518-8787.2018052000628.

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OBJECTIVE: To investigate the association between life course socioeconomic conditions and two oral health outcomes (edentulism and use of dental prostheses among individuals with severe tooth loss) among older Brazilian adults. METHODS: This was a cross-sectional study with data from the Brazilian Longitudinal Study of Aging (ELSI-Brazil) which includes information on persons aged 50 years or older residing in 70 municipalities across the five great Brazilian regions. Regression models using life history information were used to investigate the relation between childhood (parental education) and adulthood (own education and wealth) socioeconomic circumstances and edentulism and use of dental prostheses. Slope index of inequality and relative index of inequality for edentulism and use of dental prostheses assessed socioeconomic inequalities in both outcomes. RESULTS: Approximately 28.8% of the individuals were edentulous and among those with severe tooth loss 80% used dental prostheses. Significant absolute and relative inequalities were found for edentulism and use of dental prostheses. The magnitude of edentulism was higher among individuals with lower levels of socioeconomic position during childhood, irrespective of their current socioeconomic position. Absolute and relative inequalities related to the use of dental prostheses were not related to childhood socioeconomic position. CONCLUSIONS: These findings substantiate the association between life course socioeconomic circumstances and oral health in older adulthood, although use of dental prostheses was not related to childhood socioeconomic position. The study also highlights the long-lasting relation between childhood socioeconomic inequalities and oral health through the life course.

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Kawada, Tomoyuki. "Occupational class as the indicator of socioeconomic position." Occupational and Environmental Medicine 69, no. 8 (2012): 606.2–607. http://dx.doi.org/10.1136/oemed-2011-100565.

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Fuhrer, R., M. J. Shipley, J. F. Chastang, et al. "Socioeconomic Position, Health, and Possible Explanations: A Tale of Two Cohorts." American Journal of Public Health 92, no. 8 (2002): 1290–94. http://dx.doi.org/10.2105/ajph.92.8.1290.

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Eachus, J., P. Chan, N. Pearson, C. Propper, and G. Davey Smith. "An additional dimension to health inequalities: disease severity and socioeconomic position." Journal of Epidemiology & Community Health 53, no. 10 (1999): 603–11. http://dx.doi.org/10.1136/jech.53.10.603.

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Chinn, D. J., M. White, J. Harland, C. Drinkwater, and S. Raybould. "Barriers to physical activity and socioeconomic position: implications for health promotion." Journal of Epidemiology & Community Health 53, no. 3 (1999): 191–92. http://dx.doi.org/10.1136/jech.53.3.191.

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Amone-P’Olak, Kennedy, Huibert Burger, Johan Ormel, Martijn Huisman, Frank C. Verhulst, and Albertine J. Oldehinkel. "Socioeconomic position and mental health problems in pre- and early-adolescents." Social Psychiatry and Psychiatric Epidemiology 44, no. 3 (2008): 231–38. http://dx.doi.org/10.1007/s00127-008-0424-z.

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Jung-Choi, K., and Y. H. Khang. "P1-157 Effect of adolescent socioeconomic position on adulthood health status and health behaviors." Early Human Development 83 (September 2007): S127. http://dx.doi.org/10.1016/s0378-3782(07)70327-4.

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Adams, J. "Socioeconomic position and sleep quantity in UK adults." Journal of Epidemiology & Community Health 60, no. 3 (2006): 267–69. http://dx.doi.org/10.1136/jech.2005.039552.

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Coombs, N., and E. Stamatakis. "PP69 Occupational Sedentary Time, Socioeconomic Position, and Obesity." Journal of Epidemiology and Community Health 67, Suppl 1 (2013): A76.1—A76. http://dx.doi.org/10.1136/jech-2013-203126.163.

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Massar, Karlijn, Natalie Kopplin, and Karen Schelleman-Offermans. "Childhood Socioeconomic Position, Adult Educational Attainment and Health Behaviors: The Role of Psychological Capital and Health Literacy." International Journal of Environmental Research and Public Health 18, no. 17 (2021): 9399. http://dx.doi.org/10.3390/ijerph18179399.

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Socioeconomic circumstances during childhood and adulthood are known to negatively affect health promoting behaviors. On the other hand, psychological capital (PsyCap) and health literacy are positively associated with these lifestyle behaviors. We, therefore, reasoned that PsyCap and health literacy might “buffer” the negative influences of socioeconomic circumstances on health-promoting behaviors. Method: We measured subjective childhood socioeconomic position (SEP) and adult educational attainment (as a proxy for adult socioeconomic circumstances), health literacy, PsyCap, and health behaviors (fruits and vegetables consumption, exercise, and sweets and cookies consumption) in a sample of N = 150 individuals (mean age 34.98 years, 66.7% female). Results: Bootstrapped mediation analyses including PsyCap and health literacy as parallel mediators revealed that: (I) The relationship between childhood SEP and (a) fruits and vegetables consumption and (b) exercise was mediated by PsyCap, and (II) the relationship between adult educational attainment and (a) fruits and vegetables consumption and (b) exercise was mediated by PsyCap and health literacy. We found no significant effects for consumption of sweets and cookies. Conclusion: These results suggest that larger studies are warranted that confirm the potential of PsyCap and health literacy in mitigating the negative effects of lower SEP on health behaviors and health outcomes.

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Carmen, Salinas Goodier, López Torres Rómulo Guillermo, Lozada López Fanny Del Rocío, and Armijos Briones Fernando Marcelo. "Socioeconomic Position and Dental Caries in Latin America: A Systematic Review." Journal of Advanced Zoology 44, S-1 (2023): 9–14. http://dx.doi.org/10.17762/jaz.v44is-1.266.

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People who are in a bad socioeconomic position usually experience bad health outcomes. Moreover, higher mortality rates are linked to deteriorating socioeconomic status. This trend can also be observed in oral health. Worldwide, the highest prevalence of disease caries in permanent teeth was observed in Andean Latin America. The aim of this review was to determine the risk of caries based on the socioeconomic position in Latin America. The protocol was designed in accordance with the Cochrane standards for systematic reviews. The search criteria met the Preferred Reporting Items for Systematic reviews and Meta-Analysis Protocols (PRISMA) guidelines. A total of 152 articles were reviewed. Finally, 9 studies were included in the review. There is a direct association between socioeconomic status, parents' educational level, family income, and oral health education and patients' caries experience. Furthermore, this review highlights the lack of research in Latin America on oral health and the lack of policies based on scientific evidence to try to reduce the caries rate in the pediatric and adult population.

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Boclin, Karine de Limas Irio, Eduardo Faerstein, and Moyses Szklo. "Does life-course socioeconomic position influence racial inequalities in the occurrence of uterine leiomyoma? Evidence from the Pro-Saude Study." Cadernos de Saúde Pública 30, no. 2 (2014): 305–17. http://dx.doi.org/10.1590/0102-311x00025413.

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We aimed to investigate whether life-course socioeconomic position mediates the association between skin color/race and occurrence of uterine leiomyomas. We analyzed 1,475 female civil servants with baseline data (1999-2001) of the Pró-Saúde Study in Rio de Janeiro State, Brazil. Life-course socioeconomic position was determined by parental education (early life socioeconomic position), participant education (socioeconomic position in early adulthood) and their combination (cumulative socioeconomic position). Gynecological/breast exams and health insurance status were considered markers of access to health care. Hazard ratios (HR) and 95% confidence intervals (95%CI) were estimated using Cox proportional hazards models. Compared with white women, black and parda (“brown”) women had higher risk of reporting uterine leiomyomas, respectively HR: 1.6, 95%CI: 1.2-2.1; HR: 1.4, 95%CI: 0.8-2.5. Estimates were virtually identical in models including different variables related to life-course socioeconomic position. This study corroborated previous evidence of higher uterine leiomyomas risk in women with darker skin color, and further suggest that life-course socioeconomic position adversity does not influence this association.

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Osler, Merete, Bjørn Holstein, Kirsten Avlund, Mogens Trab Damsgaard, and Niels Kr Rasmussen. "Socioeconomic position and smoking behaviour in Danish adults." Scandinavian Journal of Public Health 29, no. 1 (2001): 32–39. http://dx.doi.org/10.1177/14034948010290010801.

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Hyde, M. "Comparison of the effects of low childhood socioeconomic position and low adulthood socioeconomic position on self rated health in four European studies." Journal of Epidemiology & Community Health 60, no. 10 (2006): 882–86. http://dx.doi.org/10.1136/jech.2005.043083.

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Gurmeet, Kayin, and Arman Mohammadi. "Understanding the Social Determinants of Health: Implications for Health Sociology." Jurnal Perilaku Kesehatan Terpadu 2, no. 1 (2023): 12–17. http://dx.doi.org/10.61963/jpkt.v2i1.37.

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The purpose of this study was to investigate the social determinants of health and how health sociology may be affected. A mixed-methods approach was used to study both quantitative and qualitative data in order to fully comprehend the relationships between socioeconomic factors and various health outcomes. Higher levels of socioeconomic position and educational attainment were linked, according to the quantitative study, to lower death rates, a decline in the prevalence of chronic illnesses, and improved health practices. The qualitative study emphasized the significance of addressing social determinants to minimize health inequalities and promote health equality by highlighting the impact of socioeconomic variables and the social and physical environment on health outcomes. The findings highlight the need for legislative initiatives that tackle socioeconomic inequalities, advance educational opportunities, and foster safe surroundings. By identifying and we may work to improve health outcomes and create a fairer society by tackling socioeconomic factors. To verify these results using bigger and more varied samples, more study is required.

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