Patterns of psychiatric morbidity among patients in Ndera Neuropsychiatric Hospital Kigali - Rwanda
introduction: According to the World Health Organization (WHO), mental health is defined as an essential and integral part of health as a whole. The 1994 war and Genocide, which took place in Rwanda, left many people physically and psychologically traumatized. This led to an increment in psychiatric disorders within the country. However, few studies have been done to assess the prevalence of psychiatric morbidity in the country. Objectives: To determine the socio-demographic variables of mentally ill patients, determine the source of referral of the patients, determine the duration of hospital stay, to determine patterns of psychiatric morbidity and the assigned clinical diagnosis, to determine relationship between socio-demographic variables with psychiatric morbidity. Methods: Study design was Cross-section descriptive study. Settings: The study sample came from Ndera Neuropsychiatric Hospital Kigali -Rwanda. Systematic and consecutive sampling by choosing every 3,d patients was employed, 384 patients meeting the inclusion criteria were interviewed using Socio-demographic questionnaires and SClD-l for DSM-IV TR diagnosis. Data was analyzed using the Statistical package for Social Sciences (SPSS) version 12 Results: Three hundred and eighty four patients participated in the study. And 58% percent were males. Majority of these patients were aged between 21 and 30 years. And 51% Fifty one percent were single. The highest level of education was primary (44%). Majority of the patients were unemployed earning less ten US dollars per month. In this study population, majority were Protestants comprising of (45%). As regards to the province of origin, majority of the patients came from Kigali town (46%). Forty three percent had a family history of mental illness. Night five percent were admitted involuntarily and 70.3% were referred by relatives. More than 46% of the patients had been admitted more than two times and majority stayed in the hospital for more than two weeks (35%). Schizophrenia, mania, major depression, brief psychosis, cannabis, acute psychosis, Post-traumatic stress disorder and alcoholism in order of priority, were the most commonly assigned clinical diagnosis. Twenty eight percent of patients had no defined clinical diagnosis. Structured clinical interview for DSM-IV Axis I disorders clinical version (SCID-I) showed th'at Schizophrenia was the most frequent diagnosis (39.3%), followed by current manic episode (38.5%,) Depressive episode (8%), Substance abuse (6.7%) and Post-traumatic stress disorder (5.2%) , least being Acute stress disorder and generalized anxiety disorder (1.3%) and (0.7%) respectively. There was a difference between assigned clinical diagnosis and structured clinical interview for DSM-IV diagnosis where (SCID-I) picked more Psychiatric morbidity compared with assigned clinical diagnosis. There was some variation in the number of patients assigned clinical diagnosed of current manic episode and SCID-I diagnosis accounting for 83 while that of schizophrenia was 51 patients The SCID- I is therefore more precise in making diagnosis. Relationship between severe Psychiatric disorder and Socia-demographic variables Schizophrenia and Gender; (males, n=93, 6l.5%, p = 0.0178, x2=l.456), Marital status (unmarried, n=99, 65.5%, p =0.001, x2=1.456), level of education (primary, n=81, 53.6%, p=0.046, x2=10.411) and Occupation (informal, n=135, 89.4%, p = 0.002, x2=11.801) xii Current manic episode Gender; (males, n=85, 56.2% p= 0.014, X2= 0.128), Marital status (unmarried, n=98, 66.2%, P= 0.014, x2=8.826), level of education (primary, n=83, 56.0%, p=0.049, x2=4.l34) Occupation; (informal, n=126, 85.1%, p =0.001, x2=8.542). Income per month in USD (below 40 0=107,72.2%, p= 0.020, x2=9.531) Depressive episode; Gender (female n=24, 77.4%, p = 0.036, x2=17.118), Marital status (females, n=21, 67.7%, p=0.042, X2 =6.432), Income per month (P = 0.002), Occupation (informal n=26, 83.8%, P =0.036, X2=19568) and province (Kigali, n=11, 35.4%, p = 0.046, x2=4.082). . -- PTSD; Gender (female, n=17, 65%, p = 0.025, X2=0.528), Marital status (unmarried, n=17, 85% p = 0.032, X2 =4.886) and occupation (informal n=15, 75%, p = 0.04, X2=3.533) Conclusions: The study revealed different types and patterns of Psychiatric morbidity in Ndera Neuropsychiatric Hospital, Kigali-Rwanda. This confirms the alternative hypothesis, which states that there are variations in patterns of different Psychiatric disorders among patients in Ndera europsychiatric Hospital. SCID- I diagnosis picked more Psychi atric disorders s compared to assigned clinical diagnosis raising the question of subjective Clinician impression. Majority of the patients were admitted involuntary and were referred by relatives. The following Socio-demographic variables; Gender, Marital status, occupation, Income per month, and Level of education and province of residence were statistically significant and were related to a diagnosis of severe psychiatric disorder with P value ≤ 0.05. Recommendations: -There is need to; train hospital physicians, psychologists, and nurses on how to use specific structured diagnostic instruments such as the SCID-I which is a precise diagnostic tool for psychiatric disorders and also to strengthen family support in caring for mentally ill patients in the community. -A further study to determine psychiatric morbidity in general population is recommended as a future project. Conduct a study on how best the low levels of substance abuse can be maintained. Study limitations: -The first limitation was language; it was challenging to translate some scientific words to fit the local dialect during the interviews. -The interview were based on information at the time of admission and therefore some patients could not recall all the details, regarding the past events.