Application of latent growth modeling to identify different working life trajectories: the case of the Spanish WORKss cohort

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• dc.contributor.author Serra Saurina, Lauraca
• dc.contributor.author López Gómez, María Andreé, 1985-ca
• dc.contributor.author Sánchez Niubò, Albertca
• dc.contributor.author Delclòs i Clanchet, Jordi, 1956-ca
• dc.contributor.author Benavides, Fernando G. (Fernando García)ca
• dc.date.accessioned 2017-11-29T09:15:47Z
• dc.date.issued 2017
• dc.description.abstract Objective The aim of this study was to describe the application of latent class growth analysis (LCGA) to identify different working life trajectories (WLT) using employed working time by year as a repeated measure. Methods Trajectories are estimated using LCGA, which considers all individuals within a trajectory to be homogeneous. The methodology was applied to a subsample of the Spanish WORKing life Social Security (WORKss) cohort, limited to persons born 1956-1965 (N=247 475). The number of days worked per year is used as a repeated measure across 32 time points (1981-2013). Results According to the model-fit results and further guided by expert knowledge, a four WTL model was selected as the optimal approach: WLT1 or "high labor force participation" (N=99 591; 40.2%); WLT2 or "decreased labor force participation" (N= 22 846; 9.2%); WLT3 or "increased labor force participation" (N=59 213; 23.9%); and WLT4 or "low labor force participation" (N=65 827; 26.6%). WLT1 consisted mainly of men with more years of work experience (>19 years) while WLT4 was mainly composed by women with <9 years. The other two trajectories had opposite trends and no sex differences. The occupational category variable had little influence in the trajectories. Conclusions Longitudinal data that are regularly collected by administrative systems can benefit from LCGA approaches to identify different trajectory patterns that may be associated with an outcome of interest. In occupational epidemiology, this study represents a step forward by using this modeling approach to identify different WLT.
• dc.description.sponsorship This work was supported by grants from the Instituto de Salud Carlos III-FEDER (FIS PI14/00057), the Spanish National Health Institute Carlos III (FIS 08/0914 and FIS 11/01470), and the CIBER of Epidemiology and Public Health
• dc.format.mimetype application/pdfca
• dc.identifier.citation Serra L, López Gómez MA, Sanchez-Niubo A, Delclos GL, Benavides FG. Application of latent growth modeling to identify different working life trajectories: the case of the Spanish WORKss cohort. Scand J Work Environ Health. 2017 Jan 1;43(1):42-9. DOI: 10.5271/sjweh.3606
• dc.identifier.doi http://dx.doi.org/10.5271/sjweh.3606
• dc.identifier.issn 0355-3140
• dc.identifier.uri http://hdl.handle.net/10230/33405
• dc.language.iso eng
• dc.publisher Nordic Association of Occupational Safety and Health (NOROSH)ca
• dc.relation.ispartof Scandinavian Journal of Work, Environment & Health. 2017 Jan 1;43(1):42-9
• dc.rights © Nordic Association of Occupational Safety and Health
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.other Treball -- Estadístiques
• dc.subject.other Professions -- Estadístiques
• dc.title Application of latent growth modeling to identify different working life trajectories: the case of the Spanish WORKss cohortca
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion