DOI QR코드

DOI QR Code

The Effect of Socioeconomic Status to Change in Adolescent Depression: A Multilevel Latent Growth Analysis

사회경제적 수준이 청소년 우울감에 미치는 영향: 다층잠재성장모형을 적용하여

  • Choi, You-Jung (BK21 PLUS Program in Embodiment: Health-Society Interaction, Department of Health Science, Graduate School, Korea University) ;
  • Lee, Tae-Ro (BK21 PLUS Program in Embodiment: Health-Society Interaction, Department of Health Science, Graduate School, Korea University)
  • 최유정 (고려대학교 대학원 보건과학과 BK21 플러스 인간생명-사회환경 상호작용융합사업단) ;
  • 이태노 (고려대학교 대학원 보건과학과 BK21 플러스 인간생명-사회환경 상호작용융합사업단)
  • Received : 2019.03.13
  • Accepted : 2019.04.10
  • Published : 2019.04.30

Abstract

Objectives: The purpose of this study is to examine change in adolescent depression across time and to determine the relation between individual and neighborhood socioeconomic status (SES) and depression. Methods: This study employed multilevel latent growth analysis using longitudinal data from Korea Children and Youth Panel Survey. A sample of this study consists of 2,351 adolescents who were in first grade of middle school in 2010. Results: Results showed that both initial level and downward trajectory of depression varied significantly across individuals as well as across neighborhoods. On the individual level, self-rated economic condition(b=-0.203, p<.001) was related to the initial level of depression. Adolescents whose father had a high educational level(b=0.028, p<.001) or whose mother had a low educational level(b=-0.022, p=.011) had lower rates of decline in adolescent depression. On the neighborhood level, neighborhood deprivation index (b=0.003, p=.019) and gini coefficient(b=0.124, p=.040) were associated with lower rates of decline in depression. Conclusions: Low SES in adolescence is correlated with worse mental health, especially depression. Social disparities in depression likely originate before adulthood. The findings argue for the importance of understanding depression in adolescence from a multilevel or ecological framework.

Keywords

References

  1. 강영주, 정광호. (2012). 한국사회의소득불평등과 건강에 관한 실증연구. 한국행정학보, 46(4), 265-291.
  2. 강현아. (2010). 빈곤이 위험한 지역사회 환경을 통해 청소년의 우울 및 불안에 미치는 영향. 사회복지연구, 41(3), 327-348.
  3. 김광일, 김재환, 원호택. (1984). 간이정신진단검사 실시 요강. 서울: 중앙적성출판사, 1-39.
  4. 김동진 외 10명. (2013). 한국의 건강불평등 지표와 정책과제(Developing health inequalities indicators and monitoring the status of health inequalities in Korea). 한국보건사회연구원, 1-567.
  5. 김보은 외 5명. (2015). 고등학생의 우울 및 스트레스와 건강위험행위와의 관련성. 한국학교지역 보건교육학회지, 16(2), 69-87.
  6. 김세원. (2009). 지역사회특성이 청소년의 심리사회적 적응에 미치는 영향. 한국아동복지학(28), 101-135.
  7. 김정현, 천성수. (2016). 청소년 자녀의 건강관련 삶의 질에 대한 부모와 자녀의 인식차이가 청소년 우울에 미치는 영향. 한국학교지역보건교육학회지, 17(2), 1-16.
  8. 박다혜, 장숙랑. (2013). 부모의 사회 경제적 지위가 청소년의 스트레스, 우울, 자살생각에 미치는 영향. 한국산학기술학회 논문지, 14(6), 2667-2676.
  9. 보건복지부 중앙자살예방센터. (2018). 2018 자살 예방백서. 서울: 보건복지부.
  10. 백학영. (2007). 지역의 사회경제적 특성이 빈곤에 미치는 영향.[박사학위논문]. 서울: 서울대학교 대학원.
  11. 조정아. (2009). 선형모형을 적용한 청소년의 우울 변화에 관한 종단연구: 변화경향과 개인차에 대한 성별 부모 또래 교사 요인 검증. 한국청소년연구, 20(3), 167-192.
  12. 최유정, 김혜영. (2018). 청소년의 주관적 건강 상태의 변화 궤적과 영향 요인. Child Health Nursing Research, 24(4), 496-505. https://doi.org/10.4094/chnr.2018.24.4.496
  13. 황성희, 계승희. (2018). 한국 청소년의 주관적 건강상태에 영향을 미치는 요인 분석: 가정환경, 건강행태, 심리적 요인 및 식습관. 한국학교지역 보건교육학회지, 19(1), 27-45.
  14. 황여정. (2008). 고등학생의 학업 스트레스 지각수준에 영향을 미치는 요인. 한국청소년연구, 19(3), 85-114.
  15. Ahn DH. (2009). Mental Disorders in Adolescents. Korean Med Assoc, 52(8), 745-757. https://doi.org/10.5124/jkma.2009.52.8.745
  16. Aneshensel CS, Sucoff CA. (1996). The neighborhood context of adolescent mental health. Journal of health social behavior, 293-310.
  17. Baker LA, Mutchler JE. (2010). Poverty and material hardship in grandparent headed households. Journal of Marriage Family, 72(4), 947-962. https://doi.org/10.1111/j.1741-3737.2010.00741.x
  18. Bernburg JG, Thorlindsson T, Sigfusdottir ID. (2009). Relative deprivation and adolescent outcomes in Iceland: A multilevel test. Social forces, 87(3), 1223-1250. https://doi.org/10.1353/sof.0.0177
  19. Cubbin C, Egerter S, Braveman P, Pedregon V. (2008). Where we live matters for our health: Neighborhoods and health.
  20. Curran PJ, McGinley JS, Serrano D, Burfeind, C. (2012). A multivariate growth curve model for three-level data. In HM. Cooper & American Psychological Association (Eds.), APA handbook of research methods in psychology (pp. 335-358). Washington, DC: American Psychological Association.
  21. Deb S, Strodl E, Sun J. (2015). Academics tress, parental pressure, anxiety and mental health among Indian high school students. International Journal of Psychology Behavioral Sciences, 5(1), 26-34.
  22. Dormann CF, et al. (2013). Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27-46. https://doi.org/10.1111/j.1600-0587.2012.07348.x
  23. Duncan TE, Duncan SC, Strycker LA. (2006). An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Applications. Lawrence Erlbaum.
  24. Elgar FJ, Craig W, Boyce W, Morgan A, Vella-Zarb R. (2009). Income inequality and school bullying: multilevel study of adolescents in 37 countries. Journal of Adolescent Health, 45(4), 351-359. https://doi.org/10.1016/j.jadohealth.2009.04.004
  25. Fitzpatrick KM, Wright DR, Piko BF, LaGory M. (2005). Depressive symptomatology, exposure to violence, and the role of social capital among African American adolescents. American Journal of Orthopsychiatry, 75(2), 262-274. https://doi.org/10.1037/0002-9432.75.2.262
  26. Garber J, Keiley MK, Martin NC. (2002). Developmental trajectories of adolescents' depressive symptoms: Predictors of change. Journal of consulting clinical psychology, 70(1), 79. https://doi.org/10.1037/0022-006X.70.1.79
  27. Gephart MA. (1997). Neighborhoods and communities as contexts for development, In J. Brooks-Gunn, G. Duncan, & JL. Aber (Eds.) Neighborhood poverty: Context and Consequences for Children (pp. 1-43). New York: Russel Sage Foundation.
  28. Goodman E, Slap GB, Huang B. (2003). The public health impact of socioeconomic status on adolescent depression and obesity. American journal of public health, 93(11), 1844-1850. https://doi.org/10.2105/AJPH.93.11.1844
  29. Hu Lt, Bentler PM. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
  30. Kawachi I, Kennedy BP, Lochner K, Prothrow-Stith D. (1997). Social capital, income inequality, and mortality. American journal of public health, 87(9), 1491-1498. https://doi.org/10.2105/AJPH.87.9.1491
  31. Levenstien MA, Yang Y, Ott J. (2003). Statistical significance for hierarchical clustering in genetic association and microarray expression studies. BMC Bioinformatics, 4(1), 62. https://doi.org/10.1186/1471-2105-4-62
  32. Leventhal T, Brooks-Gunn J. (2000). The neighborhoods they live in: the effects of neighborhood residence on child and adolescent outcomes. American journal of public health, 126(2), 309.
  33. Meadows SO, Brown JS, Elder GH. (2006). Depressive symptoms, stress, and support: Gendered trajectories from adolescence to young adulthood. Journal of Youth Adolescence, 35(1), 89-99. https://doi.org/10.1007/s10964-005-9021-6
  34. Michael E, Diener E. (2004). Global judgments of subjective well-being: Situational variability and long-term stability. Social indicators research, 65(3), 245-277. https://doi.org/10.1023/B:SOCI.0000003801.89195.bc
  35. Nettles SM, Pleck JH. (1994). Risk, resilience, and development: The multiple ecologies of black adolescents in the United States. Stress, risk, resilience in children adolescents: Processes, mechanisms, interventions, (pp.147-181). New York, NY: Cambridge University Press.
  36. Park HY, Heo J, Subramanian S, Kawachi I, Oh J. (2012). Socioeconomic inequalities in adolescent depression in South Korea: a multilevel analysis. PloS one, 7(10), 1-7.
  37. Quesnel-Vallee A, Taylor M. (2012). Socioeconomic pathways to depressive symptoms in adulthood: evidence from the National Longitudinal Survey of Youth 1979. Social science medicine, 74(5), 734-743. https://doi.org/10.1016/j.socscimed.2011.10.038
  38. Steptoe A, Tsuda A, Tanaka Y. (2007). Depressive symptoms, socio-economic background, sense of control, and cultural factors in university students from 23 countries. International journal of behavioral medicine, 14(2), 97-107. https://doi.org/10.1007/BF03004175