Familial aggregation of multimorbidity in Sweden: national explorative family study

Bengt Zöller; MirNabi Pirouzifard; Björn Holmquist; Jan Sundquist; Anders Halling; Kristina Sundquist

doi:10.1136/bmjmed-2021-000070

Familial aggregation of multimorbidity in Sweden: national explorative family study

BMJ Med. 2023 Jul 14;2(1):e000070. doi: 10.1136/bmjmed-2021-000070. eCollection 2023.

Authors

Bengt Zöller^{1

2}, MirNabi Pirouzifard^{1

2}, Björn Holmquist³, Jan Sundquist^{1

2}, Anders Halling^{1

2}, Kristina Sundquist^{1

2}

Affiliations

¹ Department of Clinical Science, Lund University, Malmö, Sweden.
² Centre for Primary Health Care Research, Lund University, Malmö, Sweden.
³ Department of Statistics, Lund University, Lund, Sweden.

Abstract

Objectives: To examine whether multimorbidity aggregates in families in Sweden.

Design: National explorative family study.

Setting: Swedish Multigeneration Register linked to the National Patient Register, 1997-2015. Multimorbidity was assessed with a modified counting method of 45 chronic non-communicable diseases according to ICD-10 (international classification of diseases, 10th revision) diagnoses.

Participants: 2 694 442 Swedish born individuals (48.73% women) who could be linked to their Swedish born first, second, and third degree relatives. Twins were defined as full siblings born on the same date.

Main outcome measures: Multimorbidity was defined as two or more non-communicable diseases. Familial associations for one, two, three, four, and five or more non-communicable diseases were assessed to examine risks depending on the number of non-communicable diseases. Familial adjusted odds ratios for multimorbidity were calculated for individuals with a diagnosis of multimorbidity compared with relatives of individuals unaffected by multimorbidity (reference). An initial principal component decomposition followed by a factor analysis with a principal factor method and an oblique promax rotation was used on the correlation matrix of tetrachoric correlations between 45 diagnoses in patients to identify disease clusters.

Results: The odds ratios for multimorbidity were 2.89 in twins (95% confidence interval 2.56 to 3.25), 1.81 in full siblings (1.78 to 1.84), 1.26 in half siblings (1.24 to 1.28), and 1.13 in cousins (1.12 to 1.14) of relatives with a diagnosis of multimorbidity. The odds ratios for multimorbidity increased with the number of diseases in relatives. For example, among twins, the odds ratios for multimorbidity were 1.73, 2.84, 4.09, 4.63, and 6.66 for an increasing number of diseases in relatives, from one to five or more, respectively. Odds ratios were highest at younger ages: in twins, the odds ratio was 3.22 for those aged ≤20 years, 3.14 for those aged 21-30 years, and 2.29 for those aged >30 years at the end of follow-up. Nine disease clusters (factor clusters 1-9) were identified, of which seven aggregated in families. The first three disease clusters in the principal component decomposition were cardiometabolic disease (factor 1), mental health disorders (factor 2), and disorders of the digestive system (factor 3). Odds ratios for multimorbidity in twins, siblings, half siblings, and cousins for the factor 1 cluster were 2.79 (95% confidence interval 0.97 to 8.06), 2.62 (2.39 to 2.88), 1.52 (1.34 to 1.73), and 1.31 (1.23 to 1.39), and for the factor 2 cluster, 5.79 (4.48 to 7.48) 3.24 (3.13 to 3.36), 1.51 (1.45 to 1.57), and 1.37 (1.341.40).

Conclusions: The results of this explorative family study indicated that multimorbidity aggregated in Swedish families. The findings suggest that map clusters of diseases should be used for the genetic study of common diseases to show new genetic patterns of non-communicable diseases.

Keywords: epidemiology; genetics; genetics, medical; medicine; public health.