Prevalence of Psychiatric Comorbidity, Associated Socio-demographic Factors in Patients With Alcohol Use Disorder at Mathari National Teaching and Referral Hospital Centre for Substance Abuse Treatment

Abstract

Background: Alcohol use disorder is a major contributor of the increasing morbidity and mortality rates across the world. It has been estimated, for example, that AUD contributes approximately 3.3 million deaths in the world each year (NCDAS, 2022). Available international studies on AUD have linked its onset, progression, and relapse to psychiatric comorbidities (Pavkovic et al., 2018; Jung et al., 2020). However, information related to the contribution of psychiatric comorbidities to AUD in Kenya is limited. The paucity of information on the incidence and patterns of psychiatric comorbidities in AUD patients in Kenya warrants the proposed study. Objective: The objective of the study was to determine the prevalence of psychiatric comorbidity and associated socio-demographic factors in AUD patients receiving treatment at MNTRH’s CSAT. Methodology: A cross-sectional study was conducted to determine the prevalence and the socio-demographic factors that are associated with psychiatric disorders in a convenience sample of 202 AUD patients who were attending MNTRH’S CSAT program for treatment between 1st April 2023 and 31st June 2023. A socio-demographic survey, a health history questionnaire, and the Mini International Neuropsychiatric Interview (MINI) version 5.0 tool were used to gather data for the study. The MINI 5.0 tool was used to assess the presence or absence of seven selected psychiatric disorders, which include major depressive episode, panic disorder, obsessive compulsive disorder, post-traumatic stress disorder, generalized anxiety disorder, (Hypo)manic episode and psychotic disorders. Data from the survey was coded into R-Studio version 2023.06.1-524 statistical software for anlysis. For data analysis purposes, the participants were categorized into two groups, the co-morbid group and the non-comorbid group. Participants were included in the co-morbid group if they have co-occurring AUD and selected psychiatric disorders. The non-comorbid group comprised of AUD patients who have no indication of selected psychiatric disorders. The prevalence of selected psychiatry comorbidity in AUD patients attending MNTRH CSAT for treatment was summarized descriptively using frequencies and percentages. Socio-demographic characteristics associated with psychiatric comorbidities in AUD patients attending MNTRH’s CSAT was summarized into frequencies and percentages using n x 2 contingency tables; where n represented the categories within the categorical independent variables. Variables measured on a continuous scale were summarized in means and standard deviations. Bivariate analysis involving each of the psychiatric comorbidities against the socio-demograpgic factors was done through Fishers’ and Chi-Square tests. Furthermore, multivariate logistic regression models were fitted to control for the effects of potential modifying factors. Stepwise model selection process was used in determining the variables to be included in the model. The final parsimonious models were determined through comparison of the Akaike Information Criteria (AIC) value in each analysis. The model with the least AIC value was selected as the final model. Significance testing was done at 95% confidence level. Results: The prevalence of Major Depressive Episodes in AUD patients was 74.3% and was associated with a family history of alcohol use, unemployment and low income. The prevalence of hypomanic episodes in AUD patients was 27.7% and was associated with a family history of alcohol use. Psychotic disorders in AUD patients prevalence was 72.3% and was associated with male gender and an earlier age alcohol use debut. xii The prevalence of GAD in AUD patients was 49.5% and was associated with female gender The prevalence of OCD in AUD patients was 29.7% and was associated with unemployment and low income The prevalence of panic disorders in AUD patients was 21.3% and was associated with unemployment and low educational attainment The prevalence of PTSD in AUD patients was 44.6% and was associated with low income Conclusions: There were patients with multiple psychiatric comorbidities further contributing to the burden and worsening of outcomes in AUD. Several factors were associated with increased risk of developing comorbid psychiatric disorders in AUD patients including a family history of alcohol use, unemployed status, low income, low level of education and female gender. Further, health agencies can target these groups with comprehensive prevention and treatment programs to reduce the burden of disease comorbidity while designing management protocols