Literature DB >> 19121885

The contribution of material, psychosocial, and behavioral factors in explaining educational and occupational mortality inequalities in a nationally representative sample of South Koreans: relative and absolute perspectives.

Young-Ho Khang1, John W Lynch, Seungmi Yang, Sam Harper, Sung-Cheol Yun, Kyunghee Jung-Choi, Hye Ryun Kim.   

Abstract

The contributions of material, psychosocial, and behavioral factors in explaining socioeconomic inequalities in health have been explored in many Western studies. Most prior investigations have looked at relative abilities to explain such inequalities. In addition, little research focuses on Asian countries, despite the fact that the prevalence and socioeconomic distribution of risk factors for mortality are different there. This study examined relative and absolute abilities of material, psychosocial, and behavioral pathways to explain educational and occupational inequalities in mortality in a nationally representative sample from South Korea. The 1998 and 2001 National Health and Nutrition Examination Survey data were pooled and linked to national mortality data. Of 8366 men and women over 30 years of age, 310 died between 1999 and 2005. Nine pathway variables were examined: three material factors (income, health insurance, and car ownership status), three psychosocial factors (depression, stress, and marital status), and three behavioral factors (smoking, alcohol consumption, and physical exercise). The relative risk and relative index of inequality were used as measures of relative inequality, and risk differences and the slope index of inequality were used as measures of absolute inequality. Material factors explained a total of 29.0% of the excess in relative risk for education and 50.0% of the excess in relative risk for occupational class. Material factors explained 78.6% of the excess in absolute mortality difference for education and 41.1% for occupational class. Psychosocial factors for both education and occupational class had a relative and absolute explanatory power of less than 15%. Behavioral factors showed a relative explanatory power of about 15%, but absolute explanatory power reached 84.0% for education and 105.4% for occupational class. However, the number of deaths used to calculate the absolute explanatory power was small. Results of this study suggest that absolute socioeconomic mortality inequalities could be substantially reduced if behavioral risk factors were reduced in the whole population.

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Year:  2009        PMID: 19121885     DOI: 10.1016/j.socscimed.2008.12.003

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  26 in total

1.  Self-rated health and mortality: gender- and age-specific contributions of explanatory factors in South Korea.

Authors:  Young-Ho Khang; Hye Ryun Kim
Journal:  Int J Public Health       Date:  2010-02-09       Impact factor: 3.380

2.  Relative contribution of health-related behaviours and chronic diseases to the socioeconomic patterning of low-grade inflammation.

Authors:  Marialaura Bonaccio; Augusto Di Castelnuovo; George Pounis; Amalia De Curtis; Simona Costanzo; Mariarosaria Persichillo; Chiara Cerletti; Maria Benedetta Donati; Giovanni de Gaetano; Licia Iacoviello
Journal:  Int J Public Health       Date:  2017-01-21       Impact factor: 3.380

3.  Dynamics of health behaviours and socioeconomic differences in mortality in the USA.

Authors:  Neil K Mehta; James S House; Michael R Elliott
Journal:  J Epidemiol Community Health       Date:  2015-01-06       Impact factor: 3.710

4.  Contribution of material, occupational, and psychosocial factors in the explanation of social inequalities in health in 28 countries in Europe.

Authors:  B Aldabe; R Anderson; M Lyly-Yrjänäinen; A Parent-Thirion; G Vermeylen; C C Kelleher; I Niedhammer
Journal:  J Epidemiol Community Health       Date:  2010-06-27       Impact factor: 3.710

5.  Socioeconomic and behavioral risk factors for mortality in a national 19-year prospective study of U.S. adults.

Authors:  Paula M Lantz; Ezra Golberstein; James S House; Jeffrey Morenoff
Journal:  Soc Sci Med       Date:  2010-02-20       Impact factor: 4.634

Review 6.  Psychological perspectives on pathways linking socioeconomic status and physical health.

Authors:  Karen A Matthews; Linda C Gallo
Journal:  Annu Rev Psychol       Date:  2011       Impact factor: 24.137

7.  The promise of prevention: the effects of four preventable risk factors on national life expectancy and life expectancy disparities by race and county in the United States.

Authors:  Goodarz Danaei; Eric B Rimm; Shefali Oza; Sandeep C Kulkarni; Christopher J L Murray; Majid Ezzati
Journal:  PLoS Med       Date:  2010-03-23       Impact factor: 11.069

8.  The changing contribution of smoking to educational differences in life expectancy: indirect estimates for Finnish men and women from 1971 to 2010.

Authors:  Pekka Martikainen; Jessica Y Ho; Samuel Preston; Irma T Elo
Journal:  J Epidemiol Community Health       Date:  2012-11-30       Impact factor: 3.710

9.  Interaction between education and income on the risk of all-cause mortality: prospective results from the MOLI-SANI study.

Authors:  Marialaura Bonaccio; Augusto Di Castelnuovo; Simona Costanzo; Mariarosaria Persichillo; Maria Benedetta Donati; Giovanni de Gaetano; Licia Iacoviello
Journal:  Int J Public Health       Date:  2016-04-18       Impact factor: 3.380

10.  The contribution of behavioural and metabolic risk factors to socioeconomic inequalities in mortality: the Italian Longitudinal Study.

Authors:  Cristiano Piccinelli; Paolo Carnà; Silvia Stringhini; Gabriella Sebastiani; Moreno Demaria; Michele Marra; Giuseppe Costa; Angelo d'Errico
Journal:  Int J Public Health       Date:  2018-01-30       Impact factor: 3.380

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