Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Association and causal mediation between marital status and depression in seven countries

Nature Human Behaviour volume 8, pages 2392–2405 (2024)Cite this article

Subjects

Abstract

Depression represents a significant global public health challenge, and marital status has been recognized as a potential risk factor. However, previous investigations of this association have primarily focused on Western samples with substantial heterogeneity. Our study aimed to examine the association between marital status and depressive symptoms across countries with diverse cultural backgrounds using a large-scale, two-stage, cross-country analysis. We used nationally representative, de-identified individual-level data from seven countries, including the USA, the UK, Mexico, Ireland, Korea, China and Indonesia (106,556 cross-sectional and 20,865 longitudinal participants), representing approximately 541 million adults. The follow-up duration ranged from 4 to 18 years. Our analysis revealed that unmarried individuals had a higher risk of depressive symptoms than their married counterparts across all countries (pooled odds ratio, 1.86; 95% confidence interval (CI), 1.61–2.14). However, the magnitude of this risk was influenced by country, sex and education level, with greater risk in Western versus Eastern countries (β = 0.36; 95% CI, 0.16–0.56; P < 0.001), among males versus females (β = 0.25; 95% CI, 0.003–0.47; P = 0.047) and among those with higher versus lower educational attainment (β2 = 0.34; 95% CI, 0.11–0.56; P = 0.003). Furthermore, alcohol drinking causally mediated increased later depressive symptom risk among widowed, divorced/separated and single Chinese, Korean and Mexican participants (all P < 0.001). Similarly, smoking was as identified as a causal mediator among single individuals in China and Mexico, and the results remained unchanged in the bootstrap resampling validation and the sensitivity analyses. Our cross-country analysis suggests that unmarried individuals may be at greater risk of depression, and any efforts to mitigate this risk should consider the roles of cultural context, sex, educational attainment and substance use.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Study design.
Fig. 2: Unmarried individuals have a significantly higher risk of depressive symptoms than their married counterparts (all P < 0.01).
Fig. 3: Modification effects on the association between marital status and depressive symptom risk.
Fig. 4: The direct and indirect causal associations between marital status and later risk of developing depressive symptoms, mediated by alcohol drinking and smoking.
Fig. 5: Bootstrap resampling (n = 100 times) demonstrating the robustness of probit-regression-based causal mediation analysis.

Similar content being viewed by others

Data availability

Data from the NHANES are available at https://www.cdc.gov/nchs/nhanes/index.htm. Data from the WLS are available on the application at https://wls.wisc.edu/. Data from the APMS are available on the application at https://ukdataservice.ac.uk/find-data/. Data from the MHAS are available on the application at https://www.mhasweb.org/Home/index.aspx. Data from KLoSA are available on the application at https://survey.keis.or.kr/eng/klosa/klosa01.jsp. Data from TILDA are available on the application at https://tilda.tcd.ie/. Data from CHARLS are available on the application at https://charls.pku.edu.cn/. Data from the IFLS are available on the application at https://www.rand.org/well-being/social-and-behavioral-policy/data/FLS/IFLS.html.

Code availability

The computational code for causal mediation analysis with bootstrap resampling is shared at https://github.com/Li-OmicsLab/Causal_NHB.

References

  1. Malhi, G. S. & Mann, J. J. Depression. Lancet 392, 2299–2312 (2018).

    Article  PubMed  Google Scholar 

  2. Li, J. et al. Anxiety and depression among general population in China at the peak of the COVID-19 epidemic. World Psychiatry 19, 249–250 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Charlson, F. J., Baxter, A. J., Cheng, H. G., Shidhaye, R. & Whiteford, H. A. The burden of mental, neurological, and substance use disorders in China and India: a systematic analysis of community representative epidemiological studies. Lancet 388, 376–389 (2016).

    Article  PubMed  Google Scholar 

  4. Zheng, X. et al. Dissecting the mediating and moderating effects of depression on the associations between traits and coronary artery disease: a two-step Mendelian randomization and phenome-wide interaction study. Int. J. Clin. Health Psychol. 23, 100394 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Friedrich, M. J. Depression is the leading cause of disability around the world. JAMA 317, 1517 (2017).

    PubMed  Google Scholar 

  6. The cooperative human. Nat. Hum. Behav. 2, 427–428 (2018).

  7. Krajc, K. et al. Marital status and survival in cancer patients: a systematic review and meta-analysis. Cancer Med. 12, 1685–1708 (2023).

    Article  PubMed  Google Scholar 

  8. de Oliveira, C. M. et al. Relationship between marital status and incidence of type 2 diabetes mellitus in a Brazilian rural population: the Baependi Heart Study. PLoS ONE 15, e0236869 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Wong, C. W. et al. Marital status and risk of cardiovascular diseases: a systematic review and meta-analysis. Heart 104, 1937–1948 (2018).

    Article  PubMed  Google Scholar 

  10. Leung, C. Y. et al. Association of marital status with total and cause-specific mortality in Asia. JAMA Netw. Open 5, e2214181 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ensel, W. M. The role of age in the relationship of gender and marital status to depression. J. Nerv. Ment. Dis. 170, 536–543 (1982).

    Article  CAS  PubMed  Google Scholar 

  12. Kessler, R. C. & Essex, M. Marital status and depression: the importance of coping resources. Soc. Forces 61, 484–507 (1982).

    Article  Google Scholar 

  13. Bebbington, P. Marital status and depression: a study of English national admission statistics. Acta Psychiatr. Scand. 75, 640–650 (1987).

    Article  CAS  PubMed  Google Scholar 

  14. Giannelis, A. et al. Examining the association between family status and depression in the UK Biobank. J. Affect. Disord. 279, 585–598 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Karney, B. R. Socioeconomic status and intimate relationships. Annu. Rev. Psychol. 72, 391–414 (2021).

    Article  PubMed  Google Scholar 

  16. Jang, S. N. et al. Marital status, gender, and depression: analysis of the baseline survey of the Korean Longitudinal Study of Ageing (KLoSA). Soc. Sci. Med. 69, 1608–1615 (2009).

    Article  PubMed  Google Scholar 

  17. Ambugo, E. A. Cross-country variation in the sociodemographic factors associated with major depressive episode in Norway, the United Kingdom, Ghana, and Kenya. Soc. Sci. Med. 113, 154–160 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Schaan, B. Widowhood and depression among older Europeans-the role of gender, caregiving, marital quality, and regional context. J. Gerontol. B 68, 431–442 (2013).

    Article  Google Scholar 

  19. Bulloch, A. G. M., Williams, J. V. A., Lavorato, D. H. & Patten, S. B. The depression and marital status relationship is modified by both age and gender. J. Affect. Disord. 223, 65–68 (2017).

    Article  PubMed  Google Scholar 

  20. Prince, M. J. et al. Depression symptoms in late life assessed using the EURO-D scale: effect of age, gender and marital status in 14 European centres. Br. J. Psychiatry 174, 339–345 (1999).

    Article  CAS  PubMed  Google Scholar 

  21. St John, P. D. & Montgomery, P. R. Marital status, partner satisfaction, and depressive symptoms in older men and women. Can. J. Psychiatry 54, 487–492 (2009).

    Article  Google Scholar 

  22. Shmulewitz, D. et al. The World Health Organization risk drinking levels measure of alcohol consumption: prevalence and health correlates in nationally representative surveys of U.S. adults, 2001–2002 and 2012–2013. Am. J. Psychiatry 178, 548–559 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Li, Y. et al. Physical activity, smoking, alcohol consumption and depressive symptoms among young, early mature and late mature people: a cross-sectional study of 76,223 in China. J. Affect. Disord. 299, 60–66 (2022).

    Article  PubMed  Google Scholar 

  24. Hinata, A. et al. Education, household income, and depressive symptoms in middle-aged and older Japanese adults. BMC Public Health 21, 2120 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Zhang, H. et al. The applied principles of EEG analysis methods in neuroscience and clinical neurology. Mil. Med. Res. 10, 67 (2023).

    PubMed  PubMed Central  Google Scholar 

  26. Herhaus, B., Kersting, A., Brahler, E. & Petrowski, K. Depression, anxiety and health status across different BMI classes: a representative study in Germany. J. Affect. Disord. 276, 45–52 (2020).

    Article  PubMed  Google Scholar 

  27. Lee, J. W., Shin, W. K. & Kim, Y. Impact of sex and marital status on the prevalence of perceived depression in association with food insecurity. PLoS ONE 15, e0234105 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Srivastava, S., Debnath, P., Shri, N. & Muhammad, T. The association of widowhood and living alone with depression among older adults in India. Sci. Rep. 11, 21641 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Pan, L. et al. Association of depressive symptoms with marital status among the middle-aged and elderly in rural China—serial mediating effects of sleep time, pain and life satisfaction. J. Affect. Disord. 303, 52–57 (2022).

    Article  PubMed  Google Scholar 

  30. Yan, X. Y., Huang, S. M., Huang, C. Q., Wu, W. H. & Qin, Y. Marital status and risk for late life depression: a meta-analysis of the published literature. J. Int. Med. Res. 39, 1142–1154 (2011).

    Article  PubMed  Google Scholar 

  31. Zhang, H. & Li, T. The role of willingness to sacrifice on the relationship between urban Chinese wives’ relative income and marital quality. J. Sex. Marital Ther. 41, 314–324 (2015).

    Article  PubMed  Google Scholar 

  32. Rostami, A., Ghazinour, M. & Richter, J. Marital satisfaction: the differential impact of social support dependent on situation and gender in medical staff in Iran. Glob. J. Health Sci. 5, 151–164 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Freak-Poli, R., Kung, C. S. J., Ryan, J. & Shields, M. A. Social isolation, social support, and loneliness profiles before and after spousal death and the buffering role of financial resources. J. Gerontol. B 77, 956–971 (2022).

    Article  Google Scholar 

  34. Arias-de la Torre, J. et al. Prevalence and variability of current depressive disorder in 27 European countries: a population-based study. Lancet Public Health 6, e729–e738 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Rai, D., Zitko, P., Jones, K., Lynch, J. & Araya, R. Country- and individual-level socioeconomic determinants of depression: multilevel cross-national comparison. Br. J. Psychiatry 202, 195–203 (2013).

    Article  PubMed  Google Scholar 

  36. Curhan, K. B. et al. Just how bad negative affect is for your health depends on culture. Psychol. Sci. 25, 2277–2280 (2014).

    Article  PubMed  Google Scholar 

  37. De Vaus, J., Hornsey, M. J., Kuppens, P. & Bastian, B. Exploring the East–West divide in prevalence of affective disorder: a case for cultural differences in coping with negative emotion. Pers. Soc. Psychol. Rev. 22, 285–304 (2018).

    Article  PubMed  Google Scholar 

  38. Kross, E., Gard, D., Deldin, P., Clifton, J. & Ayduk, O. ‘Asking why’ from a distance: its cognitive and emotional consequences for people with major depressive disorder. J. Abnorm. Psychol. 121, 559–569 (2012).

    Article  PubMed  Google Scholar 

  39. Santini, Z. I. et al. Social disconnectedness, perceived isolation, and symptoms of depression and anxiety among older Americans (NSHAP): a longitudinal mediation analysis. Lancet Public Health 5, e62–e70 (2020).

    Article  PubMed  Google Scholar 

  40. Cohen, A. K., Nussbaum, J., Weintraub, M. L. R., Nichols, C. R. & Yen, I. H. Association of adult depression with educational attainment, aspirations, and expectations. Prev. Chronic Dis. 17, E94 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Patria, B. The longitudinal effects of education on depression: finding from the Indonesian National Survey. Front. Public Health 10, 1017995 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Molarius, A. & Granstrom, F. Educational differences in psychological distress? Results from a population-based sample of men and women in Sweden in 2012. BMJ Open 8, e021007 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Dinescu, D. et al. Is marriage a buzzkill? A twin study of marital status and alcohol consumption. J. Fam. Psychol. 30, 698–707 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Lindstrom, M. Social capital, economic conditions, marital status and daily smoking: a population-based study. Public Health 124, 71–77 (2010).

    Article  PubMed  Google Scholar 

  45. Romaniuk, M. et al. The relationship between chronic PTSD, cortical volumetry and white matter microstructure among Australian combat veterans. Mil. Med. Res. 9, 50 (2022).

    PubMed  PubMed Central  Google Scholar 

  46. Daviet, R. et al. Associations between alcohol consumption and gray and white matter volumes in the UK Biobank. Nat. Commun. 13, 1175 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Boksa, P. Smoking, psychiatric illness and the brain. J. Psychiatry Neurosci. 42, 147–149 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Jeong, J. E., Joo, S. H., Hahn, C., Kim, D. J. & Kim, T. S. Gender-specific association between alcohol consumption and stress perception, depressed mood, and suicidal ideation: the 2010–2015 KNHANES. Psychiatry Investig. 16, 386–396 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Horwitz, A. G., Zhao, Z. & Sen, S. Peak-end bias in retrospective recall of depressive symptoms on the PHQ-9. Psychol. Assess. 35, 378–381 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Salmon, C. et al. Marital status and prostate cancer incidence: a pooled analysis of 12 case–control studies from the PRACTICAL consortium. Eur. J. Epidemiol. 36, 913–925 (2021).

    Article  PubMed  Google Scholar 

  51. Kroenke, K., Spitzer, R. L. & Williams, J. B. The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 16, 606–613 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Radloff, L. S. The CES-D Scale: a self-report depression scale for research in the general population. Appl. Psychol. Meas. 1, e58067 (1977).

    Article  Google Scholar 

  53. Roberts, J., Lenton, P., Keetharuth, A. D. & Brazier, J. Quality of life impact of mental health conditions in England: results from the adult psychiatric morbidity surveys. Health Qual. Life Outcomes 12, 6 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Aguilar-Navarro, S. G., Fuentes-Cantu, A., Avila-Funes, J. A. & Garcia-Mayo, E. J. Validity and reliability of the screening questionnaire for geriatric depression used in the Mexican Health and Age Study. Salud Publica Mex. 49, 256–262 (2007).

    Article  PubMed  Google Scholar 

  55. Cho, M. J. & Kim, K. H. Use of the Center for Epidemiologic Studies Depression (CES-D) Scale in Korea. J. Nerv. Ment. Dis. 186, 304–310 (1998).

    Article  CAS  PubMed  Google Scholar 

  56. Kilburn, K. et al. Examination of performance of the Center for Epidemiologic Studies Depression Scale Short Form 10 among African youth in poor, rural households. BMC Psychiatry 18, 201 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Boey, K. W. Cross-validation of a short form of the CES-D in Chinese elderly. Int. J. Geriatr. Psychiatry 14, 608–617 (1999).

    Article  CAS  PubMed  Google Scholar 

  58. Cristobal-Narvaez, P., Haro, J. M. & Koyanagi, A. Longitudinal association between perceived stress and depression among community-dwelling older adults: findings from the Irish Longitudinal Study on Ageing. J. Affect. Disord. 299, 457–462 (2022).

    Article  PubMed  Google Scholar 

  59. Andresen, E. M., Malmgren, J. A., Carter, W. B. & Patrick, D. L. Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale). Am. J. Prev. Med. 10, 77–84 (1994).

    Article  CAS  PubMed  Google Scholar 

  60. Peltzer, K. & Pengpid, S. The prevalence and social determinants of hypertension among adults in Indonesia: a cross-sectional population-based national survey. Int. J. Hypertens. 2018, 5610725 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Higgins, J. P., Thompson, S. G., Deeks, J. J. & Altman, D. G. Measuring inconsistency in meta-analyses. Br. Med. J. 327, 557–560 (2003).

    Article  Google Scholar 

  62. Valente, M. J., Rijnhart, J. J. M., Smyth, H. L., Muniz, F. B. & MacKinnon, D. P. Causal mediation programs in R, Mplus, SAS, SPSS, and Stata. Struct. Equ. Model. 27, 975–984 (2020).

    Article  Google Scholar 

Download references

Acknowledgements

We thank each of the survey teams and study participants who made this analysis possible. This study was supported by grants from Macao Polytechnic University (RP/FCSD-02/2022 and RP/FCA-14/2023, H.H.Y.T. and K.L.) and a special grant for COVID-19 prevention and control from the Department of Education, Shanxi Province (J.L.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Xiaobing Zhai, Henry H. Y. Tong.

Authors and Affiliations

  1. Faculty of Applied Sciences, Macao Polytechnic University, Macau, Macau SAR

    Xiaobing Zhai, Henry H. Y. Tong, Chi Kin Lam, Abao Xing, Yuyang Sha, Gang Luo, Weiyu Meng & Kefeng Li

  2. Department of Radiology, Changzhi Medical College, Changzhi, China

    Junfeng Li

  3. Changzhi Key Lab of Functional Imaging for Brain Diseases, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, China

    Junfeng Li

  4. Vanke School of Public Health, Tsinghua University, Beijing, China

    Miao Zhou

  5. School of Nursing, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, Hong Kong SAR

    Yangxi Huang

  6. Faculty of Health and Life Sciences, INTI International University, Nilai, Malaysia

    Ling Shing Wong

  7. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Cuicui Wang

Authors
  1. Xiaobing Zhai
    View author publications

    Search author on:PubMed Google Scholar

  2. Henry H. Y. Tong
    View author publications

    Search author on:PubMed Google Scholar

  3. Chi Kin Lam
    View author publications

    Search author on:PubMed Google Scholar

  4. Abao Xing
    View author publications

    Search author on:PubMed Google Scholar

  5. Yuyang Sha
    View author publications

    Search author on:PubMed Google Scholar

  6. Gang Luo
    View author publications

    Search author on:PubMed Google Scholar

  7. Weiyu Meng
    View author publications

    Search author on:PubMed Google Scholar

  8. Junfeng Li
    View author publications

    Search author on:PubMed Google Scholar

  9. Miao Zhou
    View author publications

    Search author on:PubMed Google Scholar

  10. Yangxi Huang
    View author publications

    Search author on:PubMed Google Scholar

  11. Ling Shing Wong
    View author publications

    Search author on:PubMed Google Scholar

  12. Cuicui Wang
    View author publications

    Search author on:PubMed Google Scholar

  13. Kefeng Li
    View author publications

    Search author on:PubMed Google Scholar

Contributions

X.Z., L.S.W., C.W. and K.L. conceived and designed the study. X.Z., H.H.Y.T., A.X., C.K.L., Y.S., G.L., W.M., M.Z., Y.H. and J.L. collected and analysed the data. X.Z., H.H.Y.T., A.X. and K.L. drafted the paper. M.Z., Y.H., L.S.W., C.W. and K.L. critically reviewed and edited the paper. All authors reviewed and approved the final version.

Corresponding authors

Correspondence to Cuicui Wang or Kefeng Li.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Human Behaviour thanks Amanda Hughes, Azra Ramezankhani and Fan Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–14 and Tables 1–9.

Reporting Summary

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhai, X., Tong, H.H.Y., Lam, C.K. et al. Association and causal mediation between marital status and depression in seven countries. Nat Hum Behav 8, 2392–2405 (2024). https://doi.org/10.1038/s41562-024-02033-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-024-02033-0

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing