Patterns of multiple chronic conditions in pregnancy: Population-based study using latent class analysis

Abstract

Background: Adults with multiple chronic conditions (MCC) are a heterogeneous population with elevated risk of future adverse health outcomes. Yet, despite the increasing prevalence of MCC globally, data about MCC in pregnancy are scarce.

Objectives: To estimate the population prevalence of MCC in pregnancy and determine whether certain types of chronic conditions cluster together among pregnant women with MCC.

Methods: We conducted a population-based cohort study in Ontario, Canada, of all 15-55-year-old women with a recognised pregnancy, from 2007 to 2020. MCC was assessed from a list of 22 conditions, identified using validated algorithms. We estimated the prevalence of MCC. Next, we used latent class analysis to identify classes of co-occurring chronic conditions in women with MCC, with model selection based on parsimony, clinical interpretability and statistical fit.

Results: Among 2,014,508 pregnancies, 324,735 had MCC (161.2 per 1000, 95% confidence interval [CI] 160.6, 161.8). Latent class analysis resulted in a five-class solution. In four classes, mood and anxiety disorders were prominent and clustered with one additional condition, as follows: Class 1 (22.4% of women with MCC), osteoarthritis; Class 2 (23.7%), obesity; Class 3 (15.8%), substance use disorders; and Class 4 (22.1%), asthma. In Class 5 (16.1%), four physical conditions clustered together: obesity, asthma, chronic hypertension and diabetes mellitus.

Conclusions: MCC is common in pregnancy, with sub-types dominated by co-occurring mental and physical health conditions. These data show the importance of preconception and perinatal interventions, particularly integrated care strategies, to optimise treatment and stabilisation of chronic conditions in women with MCC.

Keywords: cohort study; latent class analysis; multimorbidity; multiple chronic conditions; pregnancy; prevalence.