PREVALENCE, PATTERN, AND CORRELATES OF DEPRESSION AMONG DRUG-SUSCEPTIBLE TUBERCULOSIS PATIENT ENROLLEES IN OGBOMOSO, OYO STATE: A CROSS-SECTIONAL STUDY

PREVALENCE, PATTERN, AND CORRELATES OF DEPRESSION AMONG DRUG-SUSCEPTIBLE TUBERCULOSIS PATIENT ENROLLEES IN OGBOMOSO, OYO STATE: A CROSS-SECTIONAL STUDY | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search PREVALENCE, PATTERN, AND CORRELATES OF DEPRESSION AMONG DRUG-SUSCEPTIBLE TUBERCULOSIS PATIENT ENROLLEES IN OGBOMOSO, OYO STATE: A CROSS-SECTIONAL STUDY View ORCID Profile Sunday Olakunle Olarewaju , Sunday Charles Adeyemo , Ayomide Timilehin Kayode , Janet Oluwaseyi Ayinmodu , View ORCID Profile Olushina Ololade Oladeji , John Temitayo Odedele , Doyin Victoria Olaniyan , Oluwatoba Jeremiah Oyedeji , Zainab Adedamola Abdulsalam , Eniola Dorcas Olabode , Ayodele Raphael Ajayi doi: https://doi.org/10.1101/2025.02.26.25322944 Sunday Olakunle Olarewaju a Community Medicine Department, Osun State University , Osogbo, Osun State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sunday Olakunle Olarewaju For correspondence: sunday.olarewaju{at}uniosun.edu.ng Sunday Charles Adeyemo b Institut Superieur de Sante , Niamey, Niger Republic Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ayomide Timilehin Kayode c College of Health Sciences, Ladoke Akintola University , Ogbomosho, Oyo State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Janet Oluwaseyi Ayinmodu c College of Health Sciences, Ladoke Akintola University , Ogbomosho, Oyo State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Olushina Ololade Oladeji c College of Health Sciences, Ladoke Akintola University , Ogbomosho, Oyo State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Olushina Ololade Oladeji John Temitayo Odedele c College of Health Sciences, Ladoke Akintola University , Ogbomosho, Oyo State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Doyin Victoria Olaniyan c College of Health Sciences, Ladoke Akintola University , Ogbomosho, Oyo State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Oluwatoba Jeremiah Oyedeji c College of Health Sciences, Ladoke Akintola University , Ogbomosho, Oyo State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zainab Adedamola Abdulsalam c College of Health Sciences, Ladoke Akintola University , Ogbomosho, Oyo State, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Eniola Dorcas Olabode b Institut Superieur de Sante , Niamey, Niger Republic Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ayodele Raphael Ajayi d Department of psychiatry, Afe Babalola University Teaching Hospital , Ado-Ekiti, Nigeria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Data/Code Preview PDF ABSTRACT Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis is still one of the leading public health problems, despite advances in the effort to reduce its incidence, morbidity, and mortality. Studies have shown that the prevalence of depression correlated with the severity and duration of tuberculosis. Therefore this study aims to find out the prevalence and pattern of depression among drug-susceptible TB patients to improve treatment outcomes and thereby reduce morbidity and mortality from the disease. The study was a cross-sectional hospital-based survey. Sample size of 333 respondents was calculated using Leslie Fischer’s formula (n= z 2 pq /d 2 ). A multistage sampling technique was used to select respondents. Data was collected using a pre-tested semi-structured questionnaire and analyzed using Statistical Package for Social Sciences (SPSS) version 20. Descriptive analysis was done or all variables. Bivariate and multivariate analysis was done using chi-square and binomial regression respectively. The level of significance is set with a p-value less than 0.05. More than half of the respondents (186, 55.9%) of the respondents were depressed. The majority (122, 65.5%) of respondents had mild depression, 46 (24.7%) had moderate depression while 18(9.7%) had moderately severe depression. Sex, marital status, level of education and average monthly income were significantly associated with depression status at bivariate level. Multivariate analysis revealed that respondents with no formal education were 6 times less likely to develop depression (AOR = 0.175, P = 0.001). Respondents with Primary level of education were 2 times less likely to develop depression (AOR = 0.427, P = 0.023). Respondents with Secondary level of education were 3 times less likely to develop depression compared to Tertiary level of education. Respondents living with HIV were 35 times more likely to develop depression (AOR = 35.303, P = 0.017) compared to those who were HIV negative. INTRODUCTION Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis is still one of the leading public health problems, despite advances in the effort to reduce its incidence, morbidity, and mortality. 1 – 5 In 2021, about 10.6 million people were reported by the World Health Organisation (WHO) to be infected with Tuberculosis, 6 with an estimated 23% of the global burden and 33% of the global TB death in Africa. 7 Nigeria ranks first in Africa, one of the 10 countries with the highest number of missing TB cases, the sixth in the world, contributing to almost 4.6% of the global burden. It is also responsible for a high triple burden of Drug-susceptible TB; a bacteriologically confirmed or clinically diagnosed case of TB without evidence of infection with strains resistant to rifampicin and isoniazid. 8 Depression is a mental state characterized by loss of interest, feelings of guilt, disturbed sleep or appetite, loss of self-worth, and usually suicidal thoughts. 1 , 2 Chronic pain, frequent hospital admissions, and dependency on the hospital found in patients with Tuberculosis have been reported to be associated with depression. 5 , 9 Depression is a common mental disorder, about 5% of adults suffer from depression globally (WHO 2023). Depression is a major cause of suicide with more than 700,000 people dying due to suicide every year. 10 Studies have shown that the prevalence of depression correlated with the severity and duration of tuberculosis. 11 Depression that accompanies the disease is often due to the nature of the infection, side effects of medications, and other social determinants of health. Several studies have shown a higher prevalence of depression among patients with Tuberculosis as compared to the general population. A study done in Nigeria by Ige and Lasebikan showed a prevalence of about 45. 5%. 9 When TB and depression co-exist, patients tend to suffer in silence and when accompanied by poor compliance to medication, the mortality rate also increases. Some previous studies identified a poor degree of suspicion of depression in patients being managed for TB by clinicians, 3 , 11 , 12 therefore, paying attention to some of the psychosocial issues that patients under treatment for tuberculosis experience and the improvement of consultation-liaison psychiatric services may optimise adherence and increase the success of treatment. It is therefore important to find out the prevalence and pattern of depression among drug-susceptible TB patients to improve treatment outcomes and thereby reduce morbidity and mortality from the disease, hence this study. METHODOLOGY This study was carried out in Ogbomoso, Southwestern Nigeria. The study was a cross-sectional hospital-based survey involving quantitative methods of data collection. The study was conducted across the Direct Observed Therapy (DOT) centres in selected local governments in Ogbomoso. The DOT centres owned by both state and local governments were used for the study. TB patients, aged 18 years and above, who have been on drugs for two months and there’s proof of drug susceptibility, and who are mentally capable of providing consent were included in the study while newly diagnosed and unregistered pulmonary tuberculosis patients, pregnant women with pulmonary TB, severely ill or debilitated patients, patients with extra-pulmonary TB and patients who cannot give consent were not included. A written consent form was signed by each respondent. Sample size was calculated using Leslie Fischer’s formula (n= z 2 pq /d 2 ) using the proportion for the prevalence of depression among DS TB patients in the previous study which was 27% (0.27). 13 After 10% non-response was calculated, a total of 333 questionnaires were administered. A multistage sampling technique was used to select respondents; First stage: From the list of urban and rural local government areas in Ogbomoso, Ogbomoso North and Ogooluwa Local Government Areas were chosen. Second stage: The list of all registered DOT centres in Ogbomoso was collected from the Tuberculosis and Leprosy Supervisor for each Local Government Areas. All DOT centres were included. Third Stage: Using proportional allocation based on sample size, clients were selected from each DOT centre using a systematic sampling approach until we recruited enough sample allocated percentage. Data was collected from 25th November, 2024 to 6th December, 2024 using a pre-tested semi-structured questionnaire. Questionnaires were sorted out to check for errors and omissions at the end of the collection of data. Thereafter, data were entered into the computer and analyzed using Statistical Package for Social Sciences (SPSS) version 20. Descriptive analysis was done or all variables. Bivariate and multivariate analysis was done using chi-square and binomial regression respectively. The level of significance was set with a p-value less than 0.05. RESULTS Sociodemographic characteristics of respondents Table 1 shows the socio-demographic characteristics of the respondents revealed that the majority, 109 (32.7%), were within the age range of 30–40 years. Most respondents, 216 (64.9%), were married. Regarding education, the largest proportion, 108 (32.4%), had tertiary education. The predominant ethnic group was Yoruba, 271 (81.4%). Most respondents, 174 (52.3%), were Christians. View this table: View inline View popup Table 1: Sociodemographic characteristics of respondents Medical history of respondents Table 2 shows the medical history of the respondents revealed that most respondents, 253 (76.0%), did not have diabetes, and 233 (70.0%) did not have hypertension. Concerning HIV status, the majority, 253 (76.0%), were HIV-negative. A large proportion, 282 (84.7%), had no history of mental illness, and 297 (89.2%) reported no family history of mental illness. View this table: View inline View popup Download powerpoint Table 2: Medical history of respondents Assessment of depression among respondents More than half of the respondents (186, 55.9%) of the respondents were depressed. Table 3 shows responses of respondents using the PHQ-9. The majority, 168 (50.5%), reported “not at all” for having little interest or pleasure in doing things. Similarly, 168 (50.5%) reported “not at all” for feeling down, depressed, or hopeless. For poor appetite or overeating, most respondents, 154 (46.2%), experienced this on “several days.” Trouble sleeping or sleeping too much was reported on “several days” by 171 (51.4%). The majority, 189 (56.8%), reported “not at all” for feeling bad about themselves or feeling like a failure. Similarly, 232 (69.7%) reported “not at all” for moving or speaking so slowly that others could have noticed or being restless. Regarding trouble concentrating, 154 (46.2%) reported experiencing it “not at all.” For thoughts of self-harm or being better off dead, the majority, 225 (67.6%), reported “not at all.” View this table: View inline View popup Download powerpoint Table 3: Assessment of depression among respondents Figure 1 shows the different categories of depression among respondents. The majority (122, 65.5%) of respondents had mild depression, 46 (24.7%) had moderate depression while 18(9.7%) had moderately severe depression. Download figure Open in new tab Association between socio-demographic characteristics and depression status Table 4 shows the relationship between socio-demographic characteristics and depression status revealed that sex (χ 2 = 6.633, P = 0.010), marital status (χ 2 = 23.948, P = <0.001), level of education (χ 2 = 11.810, P = 0.008) and average monthly income (χ 2 = 12.710, P = <0.001) were significantly associated with depression status among drug susceptible tuberculosis patient enrollees in Ogbomoso, Oyo state. View this table: View inline View popup TABLE 4: ASSOCIATION BETWEEN SOCIO-DEMOGRAPHIC STATUS AND DEPRESSION STATUS Association of HIV Status and Self-Reported Hypertension and Diabetes Status with Depression Table 5 shows the relationship between the presence of comorbidities and the depression status of the respondents revealed that HIV status (χ 2 = 61.381, P = <0.001) and Diabetes (χ 2 = 7.295, P = 0.026) were significantly associated with depression status among drug susceptible tuberculosis patient enrollees in Ogbomoso, Oyo state. View this table: View inline View popup Download powerpoint TABLE 5: ASSOCIATION OF HIV STATUS AND SELF-REPORTED HYPERTENSION AND DIABETES STATUS WITH DEPRESSION Table 6 above showing the predictors of depression status among the respondents revealed that respondents with no formal education were 6 times less likely to develop depression (AOR = 0.175, P = 0.001). Respondents with Primary level of education were 2 times less likely to develop depression (AOR = 0.427, P = 0.023). Respondents with Secondary level of education were 3 times less likely to develop depression compared to Tertiary level of education. Respondents living with HIV were 35 times more likely to develop depression (AOR = 35.303, P = 0.017) compared to those who were HIV negative. View this table: View inline View popup Download powerpoint TABLE 6: PREDICTORS OF DEPRESSION STATUS AMONG DRUG SUSCEPTIBLE TUBERCULOSIS PATIENT ENROLLEES IN OGBOMOSO, OYO STATE DISCUSSION The prevalence of depression among TB patients in this study was 51.8% which is found to be similar to the prevalence of 45.5%, 14 51.9%, 15 52.1%, 16 55.9%, 1 and 54.0%, 17 respectively from studies in Ethiopia, 45.5% in Southwest Nigeria, 13 and considerably lower to studies in South Africa (64.3%), 18 and Cameroon (61.1%). 2 The observed differences could be due to the difference in population characteristics, prevalence among MDR-TB, time of assessment or phase of TB treatment. This study observed that having no formal education, sex and marital status are statistically associated with depression, however, in contrast to many studies who have identified no formal education as a major predictor of depression, 3 , 5 patients with no formal education in this study were observed to be six times less likely to develop depression. This could be due to lack of access to DOTS or poor health seeking behaviour resulting in a reduced population among TB patients receiving treatment. Being a male which was statistically associated with depression is however, not identified as a predictor in the multivariate analysis, similar to other studies who have identified the female gender as a significant predictor. This could be as a result of the global prevalence of depression among women, 16 and other factors, including hormonal factors, household responsibilities and the social roles of women in the society have been mentioned. 2 , 16 There was no association between age, religion, ethnicity and depression among the respondents in this study, however, some studies report old age as a significant predictor of depression among TB patients. 9 , 16 Patients in the older age are believed to be prone to depression due to low financial status and susceptibility to TB stigma and the side effects of anti-TB drugs. 13 Low socio-economic status among drug-susceptible TB patients was also found to be statistically associated with depression as seen in some other studies conducted among TB patients. 3 , 13 , 15 Patients who received an average income less than the minimum wage were observed to be statistically associated with depression, however it was not identified as a predictor in the multivariate analysis. The presence of TB/HIV comorbidity and diabetes mellitus is found to be statistically associated with depression in this study, which is consistent with other studies, 5 , 16 and the TB-HIV coinfection may as a result of the stigma associated with HIV-positive patients, the depression associated with HIV infection. 16 Patients living with TB/HIV comorbidity were observed to be 35 times likely to develop depression. This is considered significantly higher than other studies that observed the prevalence of depression in TB/HIV coinfection. 14 Data Availability The data for this study is available on reasonable request from the corresponding author. ETHICAL CONSIDERATION Ethical approval for the study was obtained from the LAUTECH Teaching Hospital Ethical Review Committee and permission to carry out the study was obtained from the State Coordinator, Tuberculosis and Leprosy Control, Oyo State and from the Tuberculosis and Leprosy Control Supervisors in the chosen Local Government Areas. Right of decline/withdraw from study: Respondents were told that participation is voluntary and they will not suffer any consequences if they chose not to participate. Confidentiality of data: All information gathered were kept confidential and participants were identified using serial numbers. Consent form: A written consent form signed by each respondent was included in the questionnaires. Non-maleficence: No harm is intended nor befell any respondent in the course of the research study. Respondents were reassured of this. Categories of depression among drug susceptible Tuberculosis patient enrollees in Ogbomoso, Oyo state ACKNOWLEDGEMENTS The authors acknowledge the support of Professor Parakoyi, the laboratory scientists, research assistants and others who contributed to the success of the project. Footnotes charlespatho{at}gmail.com oluwafemieniola.ed{at}gmail.com kayodeoluwatimilehin{at}gmail.com marvelayinmodu{at}gmail.com ololadeolushina{at}gmail.com temitayor159{at}gmail.com doyinvictoria2016{at}gmail.com oyedejioluwatoba{at}gmail.com abddamola{at}gmail.com ajayiayodeleraphael{at}gmail.com REFERENCES 1. ↵ Assefa S , Boru B , Gebeyehu DA , Terefe B. Depression, anxiety and their associated factors among patients with tuberculosis attending in Gondar city health facilities, North West Ethiopia . BMC Psychiatry [Internet] . 2023 ;1–9. Available from : doi: 10.1186/s12888-023-04573-7 OpenUrl CrossRef 2. ↵ Kehbila J , Ekabe CJ , Aminde LN , Noubiap JJN , Fon PN . Prevalence and correlates of depressive symptoms in adult patients with pulmonary tuberculosis in the Southwest Region of Cameroon . Infect Dis Poverty [Internet] . 2016 ; 1 – 8 . Available from : doi: 10.1186/s40249-016-0145-6 OpenUrl CrossRef 3. ↵ Aghanwa HS , Erhabor GE . DEMOGRAPHIC / SOCIOECONOMIC FACTORS IN MENTAL DISORDERS ASSOCIATED WITH TUBERCULOSIS IN SOUTHWEST NIGERIA . J Psychosom Res . 1998 ; 45 ( 4 ): 353 – 60 . OpenUrl CrossRef PubMed Web of Science 4. Yorke E , Acquaye K , Nkornu N , Boima V , Dey ID , Ganu V. Neuropsychological Changes in Tuberculosis Patients following Treatment : A preliminary study . Afr J Health Sci . 34 ( 2 ): 240 – 9 . 5. ↵ Amole TG , Yusuf AH , Salihu AS , Ismail F , Ahmed T. Prevalence and Predictors of Depression among Tuberculosis Patients in Kano, North-West Nigeria . Niger J Med . 2020 ; 29 ( 3 ): 369 – 76 . OpenUrl 6. ↵ Tuberculosis [Internet] . [cited 2023 Jul 18]. Available from: https://www.who.int/news-room/fact-sheets/detail/tuberculosis 7. ↵ Africa’s TB reduction rate falls short amid slowing global progress | WHO | Regional Office for Africa [Internet] . [cited 2023 Jul 18]. Available from: https://www.afro.who.int/news/africas-tb-reduction-rate-falls-short-amid-slowing-global-progress 8. ↵ World Health Organisation . WHO TB Knowledge Sharing Platform [Internet] . 2024 [cited 2024 Dec 4]. Available from: https://tbksp.who.int/en/node/1882 9. ↵ Ige OM , Lasebikan VO . Prevalence of depression in tuberculosis patients in comparison with non-tuberculosis family contacts visiting the DOTS clinic in a Nigerian tertiary care hospital and its correlation with disease pattern . Ment Health Fam Med . 2011 ; 8 : 235 – 42 . OpenUrl PubMed 10. ↵ World Health Organisation . Depressive disorder [Internet] . Available from: https://www.who.int/news-room/fact-sheets/detail/depression 11. ↵ Pachi A , Bratis D , Moussas G , Tselebis A. Psychiatric Morbidity and Other Factors Affecting Treatment Adherence in Pulmonary Tuberculosis Patients . Tuberc Res Treat . 2013 ; 2013 . 12. ↵ Koyanagi A , Vancampfort D , Carvalho AF , Devylder JE , Haro JM . Depression comorbid with tuberculosis and its impact on health status : cross-sectional analysis of community-based data from 48 low- and middle-income countries . BMC Med . 2017 ; 15 : 1 – 10 . OpenUrl CrossRef PubMed 13. ↵ Issa BA , Yussuf AD , Kuranga SI . Depression comorbidity among patients with tuberculosis in a university teaching hospital outpatient clinic in Nigeria . Ment Health Fam Med . 2009 ; 133 – 8 . 14. ↵ Yohannes K , Mokona H , Abebe L , Feyisso M , Tesfaye A , Tesfaw G , et al. Prevalence of depressive symptoms and associated factors among patients with tuberculosis attending public health institutions in Gede ‘ o zone, South Ethiopia . BMC Public Health . 2020 ; 20 : 1 – 9 . OpenUrl CrossRef PubMed 15. ↵ Dasa TT , Roba AA , Weldegebreal F , Mesfin F , Asfaw A , Mitiku H , et al. Prevalence and associated factors of depression among tuberculosis patients in Eastern Ethiopia . BMC Psychiatry . 2019 ; 19 ( 82 ): 1 – 7 . OpenUrl CrossRef PubMed 16. ↵ Abdurahman S , Yadeta TA , Ayana DA , Kure MA , Ahmed J , Mehadi A. Magnitude of Depression and Associated Factors Among Patients on Tuberculosis Treatment at Public Health Facilities in Harari Regional State, Eastern Ethiopia : Multi-Center Cross-Sectional Study . Neuropsychiatr Dis Treat . 2022 ; 18 ( June ): 1405 – 19 . OpenUrl PubMed 17. ↵ Ambaw F , Mayston R , Hanlon C , Alem A. Burden and presentation of depression among newly diagnosed individuals with TB in primary care settings in Ethiopia . BMC Psychiatry . 2017 ; 1 – 10 . 18. ↵ Thungana Y , Wilkinson R , Zingela Z. Comorbidity of mental ill--health in tuberculosis patients under treatment in a rural province of South Africa : a cross--sectional survey . BMJ Open . 2022 ; 12 : 1 – 8 . OpenUrl CrossRef View the discussion thread. Back to top Previous Next Posted February 27, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. 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Share PREVALENCE, PATTERN, AND CORRELATES OF DEPRESSION AMONG DRUG-SUSCEPTIBLE TUBERCULOSIS PATIENT ENROLLEES IN OGBOMOSO, OYO STATE: A CROSS-SECTIONAL STUDY Sunday Olakunle Olarewaju , Sunday Charles Adeyemo , Ayomide Timilehin Kayode , Janet Oluwaseyi Ayinmodu , Olushina Ololade Oladeji , John Temitayo Odedele , Doyin Victoria Olaniyan , Oluwatoba Jeremiah Oyedeji , Zainab Adedamola Abdulsalam , Eniola Dorcas Olabode , Ayodele Raphael Ajayi medRxiv 2025.02.26.25322944; doi: https://doi.org/10.1101/2025.02.26.25322944 Share This Article: Copy Citation Tools PREVALENCE, PATTERN, AND CORRELATES OF DEPRESSION AMONG DRUG-SUSCEPTIBLE TUBERCULOSIS PATIENT ENROLLEES IN OGBOMOSO, OYO STATE: A CROSS-SECTIONAL STUDY Sunday Olakunle Olarewaju , Sunday Charles Adeyemo , Ayomide Timilehin Kayode , Janet Oluwaseyi Ayinmodu , Olushina Ololade Oladeji , John Temitayo Odedele , Doyin Victoria Olaniyan , Oluwatoba Jeremiah Oyedeji , Zainab Adedamola Abdulsalam , Eniola Dorcas Olabode , Ayodele Raphael Ajayi medRxiv 2025.02.26.25322944; doi: https://doi.org/10.1101/2025.02.26.25322944 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Infectious Diseases (except HIV/AIDS) Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (300) Cardiovascular Medicine (4436) Dentistry and Oral Medicine (444) Dermatology (382) Emergency Medicine (608) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1509) Epidemiology (15229) Forensic Medicine (30) Gastroenterology (1124) Genetic and Genomic Medicine (6600) Geriatric Medicine (668) Health Economics (997) Health Informatics (4538) Health Policy (1368) Health Systems and Quality Improvement (1613) Hematology (542) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15916) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (146) Nephrology (667) Neurology (6599) Nursing (346) Nutrition (998) Obstetrics and Gynecology (1144) Occupational and Environmental Health (957) Oncology (3333) Ophthalmology (974) Orthopedics (369) Otolaryngology (420) Pain Medicine (436) Palliative Medicine (130) Pathology (663) Pediatrics (1693) Pharmacology and Therapeutics (691) Primary Care Research (711) Psychiatry and Clinical Psychology (5447) Public and Global Health (9232) Radiology and Imaging (2198) Rehabilitation Medicine and Physical Therapy (1370) Respiratory Medicine (1196) Rheumatology (593) Sexual and Reproductive Health (712) Sports Medicine (530) Surgery (712) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a00f9c944d0f41e2',t:'MTc3OTY2MDQyOQ=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();