Prevalence of Mental Health Disorders and Predictors of Substance Use Disorders among Hospitalized Patients at the Sierra Leone Psychiatric Teaching Hospital, Freetown, Sierra Leone, 2020-2023

Mary Sinnah^1,2, Anna Jammeh³, Solomon Sogbeh³, Amara Sheriff³, Eric Ikoona¹, Gebrekrstos Negash Gebru^3,2,&

 

¹National Public Health Agency, Sierra Leone, ²African Field Epidemiology Training Program, ³Field Epidemiology Training Program, Sierra Leone

 

 

^&Corresponding author
Gebrekrstos Negash Gebru, Field Epidemiology Training Program, Sierra Leone, African Field Epidemiology Training Program.

 

 

 

 

Mental health disorders (MHDs) represent a significant global public health concern, affecting approximately one billion people worldwide [1]. Low- and middle-income countries (LMICs) bear a disproportionate burden of these disorders, often compounded by limited resources to address them effectively [2]. Sierra Leone, a country in West Africa, faces particularly acute challenges in mental health, with an estimated prevalence of mental disorders reaching 15% of the population [3]. Recent studies suggest that the prevalence of specific disorders such as depression and anxiety in Sierra Leone may be as high as 27% and 32%, respectively, highlighting the severity of the situation [3].

 

The mental health landscape in Sierra Leone has been shaped by a complex interplay of historical, social, and environmental factors. The country's protracted civil war (1991-2002) left enduring psychological scars on the population, with studies reporting high rates of post-traumatic stress disorder (PTSD) and depression among survivors [4,5]. The Ebola virus outbreak (2014-2015) further strained the country's fragile mental health infrastructure, leading to increased anxiety, depression, and substance use among affected communities [5,6].

 

Substance use disorders (SUDs) have emerged as a critical concern within this context. Global trends indicate a rising prevalence of SUDs, often co-occurring with other mental health conditions such as psychosis and depression [7]. In Sierra Leone, substance abuse has been linked to various socio-economic factors, including unemployment, poverty, and limited access to mental health services [8]. However, there remains a paucity of data on the specific predictors of MHDs, particularly SUDs, in the Sierra Leonean context. This study aimed to determine the burden of MHDs among hospitalized patients at Sierra Leone Psychiatric Teaching Hospital (SLPTH) and identify socio-demographic and clinical predictors of SUDs in this population. Also, this study provided actionable insights to inform targeted interventions and improve mental health outcomes in this resource-limited setting.

 

 

Study Period, Design, and Setting

 

This study employed a hospital-based retrospective cross-sectional design conducted at the SLPTH, the country´s primary mental health facility located in Freetown. The analysis covered all patient admissions with MHDs between January 1, 2020, and December 31, 2023. Data collection and analysis were performed in June 2024.

 

Study Population and Data Collection

 

We included all patients admitted to SLPTH during the study period with a primary diagnosis of a mental health disorder, defined as a clinically significant disturbance in cognition, emotional regulation, or behavior. Diagnoses were classified according to the International Classification of Diseases, 10th Revision (ICD-10) criteria.

 

Data were extracted from the hospital's digital patient management system using a pre-tested standardized data collection tool by trained research assistants. The tool was pre-tested on a random sample of 10% of the records to ensure reliability and validity. To maintain data quality, a senior researcher verified 10% of the extracted records.

 

The key variables collected included socio-demographic characteristics (age, gender, marital status, employment status), clinical diagnoses (psychosis, bipolar disorder, depression, SUDs, epilepsy), and treatment outcomes. The International Classification of Diseases, 10th revision (ICD-10) criteria were used for diagnostic classification [9].

 

Statistical Analysis

 

Descriptive statistics summarized patient characteristics and the prevalence of MHDs, including 95% confidence intervals (CI). Multivariable logistic regression was employed to identify predictors of SUDs, with adjusted odds ratios (AOR) and 95% CI computed for each variable. Variables included in the regression model were selected based on bivariate analysis results (p < 0.2) and relevant literature.

 

Statistical significance was set at p < 0.05. Analyses were performed using STATA version 16.0 (StataCorp, College Station, TX, USA).

 

Ethical Considerations

 

This study was conducted in accordance with the MOH guidelines, which categorize routine surveillance data analyses as exempt from requiring approval by the Institutional Ethics and Scientific Review Committee. Nonetheless, permissions were obtained from the MOH and the management of the SLPTH prior to data collection and analysis.

 

To ensure data confidentiality, all records were anonymized before analysis, and access to the data was restricted to the research team. These measures were implemented to uphold ethical standards and protect patient privacy throughout the study.

 

 

Patient Selection

 

Out of the 3,584 patients records in the hospital registers between January 1, 2020, and December 31, 2023, 343 (9.6%) records were excluded due to incomplete data and therefore not meeting the inclusion criteria. This left 3,241 (90.4%) patients included in the study.

 

Socio-demographic Characteristics

 

Of the 3,241 patients included in this analysis, most patients were male (82.9%, 2,687/3,241), and between 14 and 35 years old (77.9%, 2,525/3,241) (Table 1). Most (78.0%, 2,526/3,241) resided in the Western Area Urban District. Most patients were single (74.7%, 2422/3,241), and unemployed (67.7%, 2,195/3,241). Just over half of the patients had primary education (52.0%, 1,684/3,241).

 

Prevalence of Mental Health Disorders

 

Of the 3,241 patients analyzed, in the study, SUDs were the most common diagnosis (60.7%, CI: 58.9-62.4, n=1,966), followed by acute psychosis (24.8%, 95% CI: 23.3-26.4 n=804). The remaining 14.5% of cases comprised bipolar disorder, depression, epilepsy, and other diagnoses (Table 2).

 

The trend of monthly distribution of admitted of mental health disorder cases at SLPTH from 2020 to 2023

 

Figure 1 presents a comparison of monthly admissions for MHDs at the SLPTH in Freetown, Sierra Leone, across the years 2020 to 2023. The graph depicts corresponding months (e.g., January 2020 compared to January 2021, January 2022, and January 2023). This analysis reveals a pattern of relatively consistent admissions across the corresponding months of each year. While there may be minor variations, no significant differences are observed between the years when compared month-to-month.

 

Trend of Admitted Cases by year and season, SLPTH 2020 to 2023

 

Cumulatively most of the cases occurred during the rainy season as compared to the dry season and the number of cases increased over time during the period under review with the highest number of cases in 2023 (Figure 2).

 

Patient Outcome of Hospitalized Patients, SLPTH, 2020-2023

 

Of the 3,241 patients included in the analysis, most were discharged (n=2,923, 90.2%), while 293 (9.0%) absconded against medical advice, and 25 (0.8%) died during hospitalization (Table 3). When examining the relationship between outcomes and substance use, there were no statistically significant differences in outcomes between patients with and without SUDs.

 

Predictors of Substance Use Disorders

 

At the bivariate level, four of eight factors included in the model were significantly associated with SUDs: age 14-35 years (COR: 1.75, 95% CI: 1.52-2.00, p<0.001), male sex (COR: 1.49, 95CI:1.28-1.79, p<0.001), being unmarried (COR: 1.82, 95% CI: 1.35-2.44, p<0.001), and being unemployed (COR: 1.96, 95% CI: 0.59-2.44, p<0.001) (Table 3).

 

In the multivariate analysis, after adjusting for potential confounders, these associations remained significant. Young adults aged 14-35 years had 2.5 times higher odds of SUDs compared to those aged 36 and older (AOR: 2.5, 95% CI: 2.04-3.06, p<0.001). Males demonstrated 2.5 times greater odds of SUDs compared to females (AOR: 2.50, 95% CI: 1.85-2.94, p<0.001). Being unmarried was associated with a 1.43 higher likelihood of SUDs compared to being married (AOR: 1.43, 95% CI: 1.10-2.00, p=0.0105). Unemployment emerged a significant predictor, with unemployed individuals having 1.72 higher odds of SUDs compared to those employed (AOR: 1.72, 95% CI: 1.37-2.13, p<0.001).

 

 

This study provides critical insights into the burden and predictors of MHDs, particularly SUDs, among hospitalized patients in Sierra Leone. Our findings reveal a high prevalence of SUDs, accounting for over half of the cases (60.7%), with younger age, male gender, unmarried status, and unemployment emerging as significant predictors.

 

Prevalence of Mental Health Disorders

 

The predominance of SUDs in our study population (60.7%) is notably higher than global estimates, which range from 10% to 20% in most populations [10]. This disparity may reflect the unique challenges faced by Sierra Leone, including the lingering effects of civil war, recurrent public health crises, and limited mental health resources [6]. The high prevalence of acute psychosis (24.8%) and bipolar disorder (9.0%) further underscores the significant burden of severe mental illnesses in this setting.

 

Predictors of Substance Use Disorders

 

The association between younger age and SUDs aligns with findings from other post-conflict settings, such as Liberia, where young adults exposed to war-related trauma were at significantly higher risk of substance abuse [11,12]. Our finding that individuals aged 14-35 years had 2.5 times higher odds of SUDs compared to older adults underscores this vulnerability. This vulnerability may stem from disrupted social structures, limited economic opportunities, and substance use as a coping mechanism for trauma and stress [13,14]. These findings underscore the need for targeted youth-focused interventions that address the socio-economic and psychological challenges faced by this demographic.

 

The observed gender disparity in SUD prevalence, where males had 2.5 times higher odds of SUDs compared to females, aligns with global patterns that consistently report higher rates of SUDs among males [15]. This finding may reflect both biological and sociocultural factors that influence substance use behaviors. Research indicates that men are more likely to engage in risk-taking behaviors, including substance use, and often face fewer societal barriers to substance use compared to women [16]. Additionally, stigma and traditional gender roles may reduce the likelihood of women seeking treatment or being diagnosed with SUDs potentially underestimating their true prevalence in some settings [10]. In the Sierra Leonean context, these trends appear consistent reinforcing the need for gender-specific prevention and treatment approaches to address the distinct needs of men and women.

 

The relationship between unemployment and SUDs highlights the intricate interplay between economic factors and mental health. This finding aligns with evidence linking unemployment to increased substance use, particularly in post-conflict and low-resource settings [13]. The association is likely bidirectional: unemployment may lead to substance use as a coping mechanism, while substance use can hinder employment prospects, perpetuating a cycle of economic instability and poor mental health. These findings emphasize the importance of integrating economic empowerment initiatives, such as vocational training and job placement programs, into SUD prevention and treatment strategies.

 

Finally, the protective effect of marriage against SUDs is consistent with prior research, suggesting that social support and familial responsibilities act as buffers against substance use [16,17]. These findings highlight the potential value of strengthening social and family support systems as part of comprehensive SUD prevention strategies. Social interventions that foster community connections and reduce isolation could play a pivotal role in mitigating the risk of SUDs.

 

Policy Implications

 

Our findings have several important implications for mental health policy in Sierra Leone:

 

Youth-focused interventions: Given the high prevalence of SUDs among younger individuals, there is a critical need for targeted prevention and early intervention programs for youth and young adults.

 

Gender-sensitive approaches: The finding that males are at greater risk than females for SUDs highlights the need for further research and the development of gender-specific prevention and treatment strategies.

 

Economic empowerment: The strong association between unemployment and SUDs suggests that integrating vocational training and job placement programs with mental health services could be beneficial.

 

Strengthening mental health services: The high prevalence of severe mental disorders underscores the need for increased investment in mental health infrastructure, training of mental health professionals, and integration of mental health services into primary care.

 

Community-based interventions: Given the protective effect of marriage, community-based programs that strengthen social support networks could be valuable in preventing and addressing SUDs.

 

Strengths and Limitations

 

This study has several strengths. It provides a comprehensive analysis of MHDs in a large, hospital-based sample over a four-year period. The use of standardized diagnostic criteria (ICD-10) enhances the reliability of our findings. Additionally, the inclusion of both bivariate and multivariate analyses allows for a nuanced understanding of the factors associated with SUDs.

 

However, our study also has limitations that should be considered when interpreting the results. The focus on hospitalized patients may not represent the broader population, potentially overestimating the prevalence of severe MHDs. The retrospective nature of the study relies on the accuracy of hospital records, which may be incomplete or contain errors. Additionally, our analysis did not account for potential comorbidities or the duration of substance use, which could provide a more nuanced understanding of the relationships between different MHDs.

 

 

This study highlights the significant burden of MHDs, particularly SUDs, among hospitalized patients in Sierra Leone. Substance use disorders accounted for the majority of cases, and key predictors included younger age, male gender, unmarried status, and unemployment. The increasing trend in mental health disorder cases over time, particularly among the most productive age groups, underscores the urgent need for targeted interventions to address this growing public health concern.

 

Recommendations

 

Based on our findings, we propose the following actions:

 

Implement youth-focused prevention programs: Develop and implement targeted prevention and early intervention strategies for youth and young adults, focusing on substance abuse education, healthy coping mechanisms, and psychosocial support.

 

Develop gender-sensitive approaches: Address gender-specific risk factors and barriers to care, tailoring mental health services to meet the unique needs of both men and women. Integrate economic empowerment initiatives: Combine mental health services with vocational training and job placement programs to address the strong link between unemployment and SUDs.

 

Strengthen mental health infrastructure: Expand and modernize mental health facilities, increasing accessibility and capacity while ensuring sufficient funding and professional training for healthcare workers.

 

Promote community-based mental health awareness programs: Reduce stigma and encourage early help-seeking behaviors through family and community engagement initiatives.

 

Enhance research and monitoring: Conduct further studies to understand gender disparities in SUD prevalence, evaluate intervention effectiveness, and explore long-term outcomes of individuals with MHDs.

 

Research Directions

 

Future research efforts should prioritize community-based studies to ascertain the true prevalence of MHDs across the general population in Sierra Leone. Additionally, longitudinal and intervention-based studies will be essential to refine and enhance mental health policies, programs, and resource allocation in the country. These steps are critical to building a more resilient and responsive healthcare system capable of addressing the growing burden of MHDs.

 

 

The authors declare no competing interests.

 

Funding

 

This study was not supported by any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

 

 

Mary Magdalene Sinnah: Conceptualization, methodology, data collection, analysis, manuscript review, and final approval. Anna Jammeh: Literature review, data collection, analysis, manuscript drafting, and final approval. Solomon Aiah Sogbeh: Literature review, analysis, manuscript drafting, and final approval. Amara Alhaji Sheriff: Analysis, manuscript review, and final approval. Adel Hussein Elduma: Conceptualization, methodology, analysis, manuscript review, and final approval Eric Ikoona: Literature review, data collection, analysis, manuscript editing and final approval. Gebrekrstos Negash Gebru: Conceptualization, methodology, analysis, manuscript review, and final approval.

 

 

The authors would like to thank the management and staff of Sierra Leone Psychiatric Teaching Hospital for their support and cooperation during the study. We also thank the healthcare workers who participated in the study for their time and valuable insights. Special thanks to the Sierra Leone Ministry of Health for their support and the Sierra Leone Research and Ethics Review Board for their guidance and approval.

 

 

Table 1: Socio-demographic Characteristics of Patients Admitted to Sierra Leone Psychiatric Teaching Hospital, 2020-2023 (N=3241)

Table 2: Distribution of Mental Health Diagnoses Among Patients Admitted to SLPTH, 2020-2023 (N=3,241)

Table 3: Bivariate and Multivariate Analysis of Factors Associated with Substance Abuse at SLPH, 2020-2023 (N=3241)

Figure 1: Trend of Monthly Distribution of Admission Cases at SLPTH from 2020 to 2023

Figure 2: Trend of Admitted Cases by year per season, SLPTH 2020 to 2023

 

 

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