Pregnant Women with Multiple Long-term Conditions Involving Mental Health in Wales, UK (2000-2019): Sequence Clustering Approach in SQL Server Data Mining Using SAIL Databank

BackgroundOne in five pregnant women in the UK has multiple long-term conditions (MLTCs), 70% of whom have a mental health condition. MLTCs and mental disorders are independently associated with adverse pregnancy outcomes. Little is known about the sequence in which these conditions develop. Identifying patterns in the accumulation of health conditions can provide valuable insights into disease progression, and potential interaction between conditions, ultimately enhancing our understanding of the complexity of MLTCs in pregnancy. MethodsThis retrospective cohort study utilised routinely collected data from the Welsh Secure Anonymised Information Linkage (SAIL) Databank. Eligible women were aged 15 to 49, gave birth in Wales, with a pregnancy start date between 1/1/2000 and 31/12/2019; had pre-existing MLTCs, with at least one mental health condition. MLTCs were defined as having [&ge;] two out of a predefined list of 22 long-term physical or mental health conditions. The sequence clustering combined sequence analysis (first-order Markov chains) with clustering of sequence of conditions (using Expectation Maximisation) and maternal factors including age, socioeconomic status, BMI and ethnicity. ResultsThe population cohort included 39,679 women. The most prevalent physical conditions were atopic eczema (33.51%), asthma (33.38%), and allergic rhinoconjunctivitis (30.75%). The most prevalent mental health conditions were depression (27.09%), anxiety (23.01%). The algorithm allocated 35,711 women into 11 sequence clusters. The three most common sequences in the entire cohort were: (i) asthma, depression, other mental health conditions (n=6235, 17.46%); (ii) atopic eczema, depression, other mental health conditions (n=4581, 13%); (iii) other mental health conditions, depression, mixed anxiety and depression (n=3914, 11%). The 11 sequence clusters were predominantly driven by (i) the ordering and (ii) the frequency of the second and third occurring health condition. Within the largest sequence cluster (mental health disorders with subsequent atopic eczema, n=6434, 18.02%), the three most common sequences were: (i) mixed anxiety and depression, depression, atopic eczema; (ii) other mental health conditions, depression, mixed anxiety and depression; (iii) anxiety, depression, atopic eczema. Demographic differences were observed within a few clusters. Younger women aged < 25 (n=4560) were more likely to experience sequences that started with atopic conditions, followed by other mental health conditions and subsequently depression. Women with a BMI over 30 kg/m2 (n=534) were more likely to experience sequences involving conditions such as atopic conditions followed by asthma and depression. A cluster of women with a BMI under 18.5 kg/m{superscript 2} (n=264), from most deprived areas and predominantly White, often started with substance misuse or eating disorders, followed by other mental health conditions and depression. ConclusionsThe sequence in which conditions accumulate in this cohort of women with multiple long-term conditions, including mental health disorders, is primarily dominated by mental health and atopic conditions. Women with pre-existing mental illness tend to accumulate both atopic and other mental health conditions throughout their lifetime, contributing to the development of multiple long-term conditions.