OBJECTIVES: To describe the socio-demographic correlates of bipolar disorder and their interactions. DESIGN: Cross sectional study. SETTING: Rural population in Ethiopia. SUBJECTS: We conducted a door-to-door survey of a predominantly rural population of close to 70,000 individuals. A total of 315 cases of bipolar disorder were identified by use of the SCAN and clinical assessment. RESULTS: The lifetime prevalence of biopolar disorder in this population was 0.5% (0.6% for men and 0.4%) for women. Adjusted odds ratios show that males had 80% higher risk of bipolar disoder: OR (95% CI) = 1.81 (1.42, 2.32). Those aged 25-34 years had 45% higher risk than those aged under 25: adjusted OR (95% CI) = 1.45 (1.03, 2.06). Area of residence and educational level were not associated with the disorder. The association of marital status with bipolar disorder was modified by age and sex. Among males the odds of bipolar disorder among the married was 3.6 times higher than those who have never married. Among the age group of 15 to 24 years, those married had a 84% higher risk of disease, while those previously married had a 55% increase. On the other hand the association between marital status and bipolar disorder is reversed in older age groups, with those who have never married having a higher risk compared to those married. CONCLUSION: The study shows that the prevalence of bipolar disorder in this population is within ranges of prevalence reported in the literature, although on the lower side. It also shows that age, sex and marital status are associated with bipolar disorder and these variables interacts with each other.
OBJECTIVES: To describe the socio-demographic correlates of bipolar disorder and their interactions. DESIGN: Cross sectional study. SETTING: Rural population in Ethiopia. SUBJECTS: We conducted a door-to-door survey of a predominantly rural population of close to 70,000 individuals. A total of 315 cases of bipolar disorder were identified by use of the SCAN and clinical assessment. RESULTS: The lifetime prevalence of biopolar disorder in this population was 0.5% (0.6% for men and 0.4%) for women. Adjusted odds ratios show that males had 80% higher risk of bipolar disoder: OR (95% CI) = 1.81 (1.42, 2.32). Those aged 25-34 years had 45% higher risk than those aged under 25: adjusted OR (95% CI) = 1.45 (1.03, 2.06). Area of residence and educational level were not associated with the disorder. The association of marital status with bipolar disorder was modified by age and sex. Among males the odds of bipolar disorder among the married was 3.6 times higher than those who have never married. Among the age group of 15 to 24 years, those married had a 84% higher risk of disease, while those previously married had a 55% increase. On the other hand the association between marital status and bipolar disorder is reversed in older age groups, with those who have never married having a higher risk compared to those married. CONCLUSION: The study shows that the prevalence of bipolar disorder in this population is within ranges of prevalence reported in the literature, although on the lower side. It also shows that age, sex and marital status are associated with bipolar disorder and these variables interacts with each other.
Authors: Charlotte Hanlon; Atalay Alem; Crick Lund; Damen Hailemariam; Esubalew Assefa; Tedla W Giorgis; Dan Chisholm Journal: Int J Ment Health Syst Date: 2019-02-25
Authors: M Claire Greene; Tenzin Yangchen; Thomas Lehner; Patrick F Sullivan; Carlos N Pato; Andrew McIntosh; James Walters; Lidia C Gouveia; Chisomo L Msefula; Wilza Fumo; Taiwo L Sheikh; Melissa A Stockton; Milton L Wainberg; Myrna M Weissman Journal: Lancet Psychiatry Date: 2021-06-08 Impact factor: 77.056
Authors: Charlotte Hanlon; Nagendra P Luitel; Tasneem Kathree; Vaibhav Murhar; Sanjay Shrivasta; Girmay Medhin; Joshua Ssebunnya; Abebaw Fekadu; Rahul Shidhaye; Inge Petersen; Mark Jordans; Fred Kigozi; Graham Thornicroft; Vikram Patel; Mark Tomlinson; Crick Lund; Erica Breuer; Mary De Silva; Martin Prince Journal: PLoS One Date: 2014-02-18 Impact factor: 3.240