{"title":"Does partnership predict mortality? Evidence from a twin fixed effects study design","authors":"Øyvind Nicolay Wiborg , Alexi Gugushvili","doi":"10.1016/j.ssmph.2025.101805","DOIUrl":null,"url":null,"abstract":"<div><div>This study examines the association between partnership status and mortality, addressing methodological concerns such as selection effects and unobserved heterogeneity. Utilizing Norwegian administrative data on birth cohorts from 1955 to 1975, we analyze mortality outcomes using Kaplan-Meier survival analyses and Cox proportional hazards regression models. The dataset includes over 1.2 million individuals and distinguishes between partnered and non-partnered individuals. While results for the general population show that non-partnered individuals face significantly higher mortality risks, with hazard ratios of 1.59 for men and 1.47 for women, twin fixed effects models reveal no significant relationship between partnership status and mortality. This finding suggests that much of the observed association may be due to shared genetic and environmental factors rather than a direct causal effect of partnership status. By leveraging the twin fixed effects research design, this study provides a robust test of the partnership-mortality hypothesis, highlighting the importance of controlling for unobserved heterogeneity in observational research. Our results underscore the complexity of the partnership-health nexus and call for caution in interpreting simple associations as evidence of causality.</div></div>","PeriodicalId":47780,"journal":{"name":"Ssm-Population Health","volume":"30 ","pages":"Article 101805"},"PeriodicalIF":3.6000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ssm-Population Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S235282732500059X","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
This study examines the association between partnership status and mortality, addressing methodological concerns such as selection effects and unobserved heterogeneity. Utilizing Norwegian administrative data on birth cohorts from 1955 to 1975, we analyze mortality outcomes using Kaplan-Meier survival analyses and Cox proportional hazards regression models. The dataset includes over 1.2 million individuals and distinguishes between partnered and non-partnered individuals. While results for the general population show that non-partnered individuals face significantly higher mortality risks, with hazard ratios of 1.59 for men and 1.47 for women, twin fixed effects models reveal no significant relationship between partnership status and mortality. This finding suggests that much of the observed association may be due to shared genetic and environmental factors rather than a direct causal effect of partnership status. By leveraging the twin fixed effects research design, this study provides a robust test of the partnership-mortality hypothesis, highlighting the importance of controlling for unobserved heterogeneity in observational research. Our results underscore the complexity of the partnership-health nexus and call for caution in interpreting simple associations as evidence of causality.
期刊介绍:
SSM - Population Health. The new online only, open access, peer reviewed journal in all areas relating Social Science research to population health. SSM - Population Health shares the same Editors-in Chief and general approach to manuscripts as its sister journal, Social Science & Medicine. The journal takes a broad approach to the field especially welcoming interdisciplinary papers from across the Social Sciences and allied areas. SSM - Population Health offers an alternative outlet for work which might not be considered, or is classed as ''out of scope'' elsewhere, and prioritizes fast peer review and publication to the benefit of authors and readers. The journal welcomes all types of paper from traditional primary research articles, replication studies, short communications, methodological studies, instrument validation, opinion pieces, literature reviews, etc. SSM - Population Health also offers the opportunity to publish special issues or sections to reflect current interest and research in topical or developing areas. The journal fully supports authors wanting to present their research in an innovative fashion though the use of multimedia formats.