BACKGROUND: Back pain and common mental disorders are often comorbid and known risk factors for future disability pension. However, the reason for the covariation is not known. The aim was to investigate the common genetic and environmental influences on the covariation between sick leave due to back pain, sick leave due to common mental disorders and disability pension. METHODS: Register data from the Swedish Social Insurance Agency on sick leave due to back pain, common mental disorders and disability pension between 2005 and 2018, in a population-based sample of 56,686 working age twins was used to construct biometric twin models to calculate if the covariation between the traits were due to Additive (A) or Dominant (D) genetic factors, Common environmental factors (C) or unique Environmental factors (E), for women and men. RESULTS: The phenotypic correlations ranged between 0.17 and 0.25. A common factor common pathway AE model fitted best for both women and men. The latent underlying common factor, that explained the covariation was mostly explained by genetic factors (87% for women and 90% for men). Each trait was also influenced by its own unique genetic and unique environment factors. A higher heritability was found for disability pension than for sick leave. CONCLUSIONS: The covariation between sick leave due to back pain and common mental disorders, and disability pension were mostly explained by common genetic factors, while the unique variation in each trait was influenced by both genetic and environmental factors not shared within the twin pairs. SIGNIFICANCE: A common genetic liability seems to be of importance in the comorbidity of sick leave due to back pain and common mental disorders and the transition to disability pension, both among women and men. However, the proportion in each trait that was explained by genetic factors was somewhat higher for men than for women in all traits. This may be of importance to consider in intervention or prevention efforts.
BACKGROUND:Back pain and common mental disorders are often comorbid and known risk factors for future disability pension. However, the reason for the covariation is not known. The aim was to investigate the common genetic and environmental influences on the covariation between sick leave due to back pain, sick leave due to common mental disorders and disability pension. METHODS: Register data from the Swedish Social Insurance Agency on sick leave due to back pain, common mental disorders and disability pension between 2005 and 2018, in a population-based sample of 56,686 working age twins was used to construct biometric twin models to calculate if the covariation between the traits were due to Additive (A) or Dominant (D) genetic factors, Common environmental factors (C) or unique Environmental factors (E), for women and men. RESULTS: The phenotypic correlations ranged between 0.17 and 0.25. A common factor common pathway AE model fitted best for both women and men. The latent underlying common factor, that explained the covariation was mostly explained by genetic factors (87% for women and 90% for men). Each trait was also influenced by its own unique genetic and unique environment factors. A higher heritability was found for disability pension than for sick leave. CONCLUSIONS: The covariation between sick leave due to back pain and common mental disorders, and disability pension were mostly explained by common genetic factors, while the unique variation in each trait was influenced by both genetic and environmental factors not shared within the twin pairs. SIGNIFICANCE: A common genetic liability seems to be of importance in the comorbidity of sick leave due to back pain and common mental disorders and the transition to disability pension, both among women and men. However, the proportion in each trait that was explained by genetic factors was somewhat higher for men than for women in all traits. This may be of importance to consider in intervention or prevention efforts.
Authors: Annina Ropponen; Mo Wang; Jurgita Narusyte; Sanna Kärkkäinen; Victoria Blom; Pia Svedberg Journal: BMC Public Health Date: 2021-05-20 Impact factor: 3.295
Authors: Annina Ropponen; Mo Wang; Jurgita Narusyte; Sanna Kärkkäinen; Victoria Blom; Pia Svedberg Journal: BMC Health Serv Res Date: 2021-04-07 Impact factor: 2.655
Authors: Annina Ropponen; Jurgita Narusyte; Mo Wang; Sanna Kärkkäinen; Lisa Mather; Victoria Blom; Gunnar Bergström; Pia Svedberg Journal: Int Arch Occup Environ Health Date: 2021-12-28 Impact factor: 2.851