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Journal articles on the topic '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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2

González-Santiago, Omar. "Socioeconomic Position and Mortality." JAMA 304, no. 3 (2010): 270. http://dx.doi.org/10.1001/jama.2010.984.

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Gross, Raz. "Socioeconomic Position and Mortality." JAMA 304, no. 3 (2010): 270. http://dx.doi.org/10.1001/jama.2010.985.

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4

Wang, Simon B., and Jamie L. Hanson. "Childhood socioeconomic position relates to adult decision-making: Evidence from a large cross-cultural investigation." PLOS ONE 19, no. 11 (2024): e0310972. http://dx.doi.org/10.1371/journal.pone.0310972.

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Early exposure to poverty may have profound and enduring impacts on developmental trajectories over the lifespan. This study investigated potential links between childhood socioeconomic position, recent economic change, and temporal discounting in a large international cohort (N = 12,951 adults from 61 countries). Temporal discounting refers to the tendency to prefer smaller immediate rewards over larger rewards delivered after a delay, and connects to consequential outcomes including academic achievement, occupational success, and risk-taking behaviors. Consistent with multiple theories about the impacts of stress exposure, individuals who reported lower socioeconomic positions in childhood exhibited greater temporal discounting in adulthood compared to peers who did not. Furthermore, an interaction emerged between childhood socioeconomic position and recent economic change, such that the steepest temporal discounting was found among those from lower childhood socioeconomic positions who also recently experienced negative economic change as a result of the COVID pandemic. These associations remained significant even when accounting for potentially confounding factors like education level and current employment. Findings provide new evidence that childhood socioeconomic position relates to greater temporal discounting and steeper devaluation of future rewards later in adulthood, particularly in response to contemporaneous economic change. This suggests childhood socioeconomic position may have longer-term impacts on developmental trajectories. Speculatively, childhood socioeconomic position may shape adult behavior through increased life stress, diminished access to resources, and lower perceived trust and reliability in social systems. These findings underscore the long-term implications of socioeconomic gaps, cycles of disadvantage and economic marginalization.

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Nettle, Daniel. "Does Hunger Contribute to Socioeconomic Gradients in Behavior?" Frontiers in Psychology 8 (May 31, 2017): 358. https://doi.org/10.3389/fpsyg.2017.00358.

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6

Groot, J., A. M. Nybo Andersen, A. Adam, T. E. Tind Nielsen, C. Blegvad, and L. Skov. "Maternal socioeconomic position and psoriasis." British Journal of Dermatology 180, no. 2 (2019): e38-e38. http://dx.doi.org/10.1111/bjd.17469.

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Mullie, P., P. Clarys, M. Hulens, and G. Vansant. "Dietary patterns and socioeconomic position." European Journal of Clinical Nutrition 64, no. 3 (2010): 231–38. http://dx.doi.org/10.1038/ejcn.2009.145.

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Singh-Manoux, Archana. "Socioeconomic Position and Mortality—Reply." JAMA 304, no. 3 (2010): 270. http://dx.doi.org/10.1001/jama.2010.986.

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9

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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Ahacic, Kozma, Sven Trygged, and Ingemar Kåreholt. "Income and Education as Predictors of Stroke Mortality after the Survival of a First Stroke." Stroke Research and Treatment 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/983145.

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Background. It is well known that socioeconomic indicators, such as income and education, predict both stroke incidence and stroke mortality. This means that persons in lower socioeconomic positions are less likely to survive their stroke, and there will be a selective survival in the group discharged from hospital after their first stroke.Question. Does socioeconomic position continue to predict mortality, stroke specific, or from other causes, among patients surviving their first stroke in spite of this selective survival?Methods. All persons in Sweden aged 40–59 years who were discharged after a first hospitalization for stroke in 1996–2000 were included (n= 10,487), then followed up until the end of the fourth calendar year after discharge. Data were analysed with Cox regressions controlling for age, sex, and stroke type.Results. Persons with high socioeconomic position, measured by education and income, have lower mortality than those of low position. Education was not significant when adjusted for income, however. The risk of dying was similar for stroke-specific mortality and all-cause mortality, for those with cerebral infarction as well as for all patients.Conclusions. Socioeconomic position predicted stroke-specific mortality also in the selective group of persons who survived their first stroke.

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11

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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12

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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13

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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14

Muntaner, C. "Socioeconomic Position and Major Mental Disorders." Epidemiologic Reviews 26, no. 1 (2004): 53–62. http://dx.doi.org/10.1093/epirev/mxh001.

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15

Matukala Nkosi, Thomas, Marie-Élise Parent, Jack Siemiatycki, and Marie-Claude Rousseau. "Socioeconomic Position and Lung Cancer Risk." Epidemiology 23, no. 3 (2012): 377–85. http://dx.doi.org/10.1097/ede.0b013e31824d0548.

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16

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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17

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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18

Ebrahim, Shah. "Socioeconomic position (again), causes and confounding." International Journal of Epidemiology 34, no. 2 (2005): 237–38. http://dx.doi.org/10.1093/ije/dyi041.

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Tello-Majluf, D. "COVID 19: Sin distinción de raza, sexo o posición socioeconómica; Nadie está seguro." Revista de la Facultad de Medicina Humana 20, no. 2 (2020): 162–64. http://dx.doi.org/10.25176/rfmh.v20i2.2929.

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20

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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21

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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22

Medoff, Marshall H. "Positional Segregation and the Economic Hypothesis." Sociology of Sport Journal 3, no. 4 (1986): 297–304. http://dx.doi.org/10.1123/ssj.3.4.297.

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The various biological, psychological, and sociological hypotheses and the economic hypothesis provided possible explanations of why blacks will be underrepresented at central positions in professional sports. The economic hypothesis attributes this phenomena to the inferior socioeconomic status of blacks and differential skill and development costs. Over the time period 1970–1984, when the psychological and sociological factors remained relatively constant but blacks’ socioeconomic status and access to facilities increased, the data showed that in major league baseball the recruitment of blacks in central positions increased and declined at the noncentral outfield position. This finding was consistent with the economic hypothesis but inconsistent with the alternative hypotheses.

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23

Slayton, R. L. "Socioeconomic Position and Risk of Oral Clefts." AAP Grand Rounds 35, no. 1 (2016): 4. http://dx.doi.org/10.1542/gr.35-1-4.

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24

Canney, Mark, Dilshani Induruwage, Anahat Sahota, et al. "Socioeconomic Position and Incidence of Glomerular Diseases." Clinical Journal of the American Society of Nephrology 15, no. 3 (2020): 367–74. http://dx.doi.org/10.2215/cjn.08060719.

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Background and objectivesSocial deprivation is a recognized risk factor for undifferentiated CKD; however, its association with glomerular disease is less well understood. We sought to investigate the relationship between socioeconomic position and the population-level incidence of biopsy-proven glomerular diseases.Design, setting, participants, & measurementsIn this retrospective cohort study, a provincial kidney pathology database (2000–2012) was used to capture all incident cases of membranous nephropathy (n=392), IgA nephropathy (n=818), FSGS (n=375), ANCA-related GN (ANCA-GN, n=387), and lupus nephritis (n=389) in British Columbia, Canada. Quintiles of area-level household income were used as a proxy for socioeconomic position, accounting for regional differences in living costs. Incidence rates were direct standardized to the provincial population using census data for age and sex and were used to generate standardized rate ratios. For lupus nephritis, age standardization was performed separately in men and women.ResultsA graded increase in standardized incidence with lower income was observed for lupus nephritis (P<0.001 for trend in both sexes) and ANCA-GN (P=0.04 for trend). For example, compared with the highest quintile, the lowest income quintile had a standardized rate ratio of 1.7 (95% confidence interval, 1.19 to 2.42) in women with lupus nephritis and a standardized rate ratio of 1.5 (95% confidence interval, 1.09 to 2.06) in ANCA-GN. The association between income and FSGS was less consistent, in that only the lowest income quintile was associated with a higher incidence of disease (standardized rate ratio, 1.55; 95% confidence interval, 1.13 to 2.13). No significant associations were demonstrated for IgA nephropathy or membranous nephropathy.ConclusionsUsing population-level data and a centralized pathology database, we observed an inverse association between socioeconomic position and the standardized incidence of lupus nephritis and ANCA-GN.

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25

Grandner, Michael A., Megan E. Ruiter Petrov, Pinyo Rattanaumpawan, Nicholas Jackson, Alec Platt, and Nirav P. Patel. "Sleep Symptoms, Race/Ethnicity, and Socioeconomic Position." Journal of Clinical Sleep Medicine 09, no. 09 (2013): 897–905. http://dx.doi.org/10.5664/jcsm.2990.

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26

Shkaratan, O. I., and S. A. Iniasevskii. "The Socioeconomic Position of Professionals and Managers." Sociological Research 46, no. 5 (2007): 47–69. http://dx.doi.org/10.2753/sor1061-0154460503.

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27

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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28

Bacon, W. Edward, and Wilbur C. Hadden. "Occurrence of Hip Fractures and Socioeconomic Position." Journal of Aging and Health 12, no. 2 (2000): 193–203. http://dx.doi.org/10.1177/089826430001200203.

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29

Grandner, Michael A., Natasha J. Williams, Kristen L. Knutson, Dorothy Roberts, and Girardin Jean-Louis. "Sleep disparity, race/ethnicity, and socioeconomic position." Sleep Medicine 18 (February 2016): 7–18. http://dx.doi.org/10.1016/j.sleep.2015.01.020.

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30

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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31

Fichtenberg, Caroline M., Jacky M. Jennings, Thomas A. Glass, and Jonathan M. Ellen. "Neighborhood Socioeconomic Environment and Sexual Network Position." Journal of Urban Health 87, no. 2 (2010): 225–35. http://dx.doi.org/10.1007/s11524-009-9425-9.

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32

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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33

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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Zileni, Barbara Debra, Pauline Glover, Kung-Keat Teoh, Chisomo Waazileni Zileni, and Amanda Müller. "Factors influencing labour and birthing positions in Malawi." African Journal of Midwifery and Women's Health 15, no. 4 (2021): 1–10. http://dx.doi.org/10.12968/ajmw.2020.0049.

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Background/aims The World Health Organization encourages women in labour to ambulate and assume upright positions shown to be associated with favourable childbirth outcomes. However, the literature shows that most women in developed and developing countries, including Malawi, give birth in the supine position. There is a lack of research on factors that influence choice of birthing positions among women in Malawi. This study aimed to identify these factors. Methods A face-to-face descriptive survey was conducted on 373 low-risk postnatal women in Malawi. Bivariate and multivariate analyses were used to determine association between sociodemographic characteristics and choice of labour and birthing position, as well as to identify predictive factors. Results Walking during labour was significantly associated with age (P=0.018) and monthly family income (P=0.012). During birth, women who had received some degree of education were more likely to use the supine position than those who had not (93% vs 78%; P=0.011). However, women with a higher level of income were less likely to use the supine position than women with low income (82% vs 93%; P=0.005). Conclusions Age, income and education influence Malawian women's choices for labour and birthing position. There is a need for Malawian women to be informed about and encouraged to use different labour and birthing positions, regardless of their socioeconomic and demographic status, to promote positions that improve maternal and neonatal outcomes. Childbirth education sessions or classes during antenatal care should include information on different birthing positions.

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35

Hvilsom, Gitte B., Lisbet R. Hölmich, Kirsten Frederiksen, Marianne Steding-Jessen, Søren Friis, and Susanne O. Dalton. "Socioeconomic position and breast reconstruction in Danish women." Acta Oncologica 50, no. 2 (2010): 265–73. http://dx.doi.org/10.3109/0284186x.2010.529823.

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Luoto, Severi, Tatjana Krama, Anna Rubika, et al. "Socioeconomic position, immune function, and its physiological markers." Psychoneuroendocrinology 127 (May 2021): 105202. http://dx.doi.org/10.1016/j.psyneuen.2021.105202.

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Briggs, Farren B., Matthew C. Green, and Miranda L. Ritterman Weintraub. "Role of socioeconomic position in multiple sclerosis etiology." Neurodegenerative Disease Management 5, no. 4 (2015): 333–43. http://dx.doi.org/10.2217/nmt.15.22.

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38

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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Gage, Anastasia J. "Women's Socioeconomic Position and Contraceptive Behavior in Togo." Studies in Family Planning 26, no. 5 (1995): 264. http://dx.doi.org/10.2307/2138012.

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Borrell, Luisa N., and Natalie D. Crawford. "Socioeconomic position indicators and periodontitis: examining the evidence." Periodontology 2000 58, no. 1 (2011): 69–83. http://dx.doi.org/10.1111/j.1600-0757.2011.00416.x.

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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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Osler, Bjorn Holstein, Kirsten Avlu, Merete. "Socioeconomic position and smoking behaviour in Danish adults." Scandinavian Journal of Public Health 29, no. 1 (2001): 32–39. http://dx.doi.org/10.1080/14034940151106984.

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Senese, L. C., N. D. Almeida, A. K. Fath, B. T. Smith, and E. B. Loucks. "Associations Between Childhood Socioeconomic Position and Adulthood Obesity." Epidemiologic Reviews 31, no. 1 (2009): 21–51. http://dx.doi.org/10.1093/epirev/mxp006.

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Kaplan, George A., Gavin Turrell, John W. Lynch, Susan A. Everson, Eeva-Liisa Helkala, and Jukka T. Salonen. "Childhood socioeconomic position and cognitive function in adulthood." International Journal of Epidemiology 30, no. 2 (2001): 256–63. http://dx.doi.org/10.1093/ije/30.2.256.

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Agha, Golareh, Joanne M. Murabito, John W. Lynch, Michal Abrahamowicz, Sam B. Harper, and Eric B. Loucks. "Relation of Socioeconomic Position With Ankle–Brachial Index." American Journal of Cardiology 108, no. 11 (2011): 1651–57. http://dx.doi.org/10.1016/j.amjcard.2011.07.030.

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46

Frederiksen, B. L., T. Jørgensen, K. Brasso, I. Holten, and M. Osler. "Socioeconomic position and participation in colorectal cancer screening." British Journal of Cancer 103, no. 10 (2010): 1496–501. http://dx.doi.org/10.1038/sj.bjc.6605962.

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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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48

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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49

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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Smith, G. D., C. Hart, D. Blane, C. Gillis, and V. Hawthorne. "Lifetime socioeconomic position and mortality: prospective observational study." BMJ 314, no. 7080 (1997): 547. http://dx.doi.org/10.1136/bmj.314.7080.547.

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