Background: Tuberculosis is among the top ten cause of death (9th) from a single infectious agent worldwide. It even ranks above HIV/AIDS. It is among the top 10 causes of death among children. Globally there are estimates of one million cases of TB in children, 76% occur in 22 high-burden countries among which Ethiopia ranked 8th. Despite this fact, children with TB are given low priority in most national health programs. Moreover reports on childhood TB and its predictors are very limited. Therefore this study aimed to assess predictors of pediatric Tuberculosis in Public Health Facilities. Methods: Unmatched case control study among a total samples of 432 (144 cases and 288 controls) were done from August to December 2016 in Bale zone, South East Ethiopia. Pediatric TB patients who attended health facilities for DOTS and those who attended health facilities providing DOTS service for any health problem except for TB were the study population for cases and controls, respectively. For each case two consecutive controls were sampled systematically. Data were collected using pretested and structured questionnaire through face to face interview with parents. Binary and multivariable logistic regression analyses were employed to identify predictors of Tuberculosis. Result: Among cases there were equal number of male and female 71(50%). However among control 136 (47.9%) were male and the rest were female. The mean (standard deviation) of age among cases was 8.4 (±4.3) and controls were 7.3 (±4.1). The odds of TB were 2 times (AOR, 95% CI = 1.94(1.02–3.77)) more likely among 11–15 age group children when compared with children of age group ≤5. HIV status of the child, children who were fed raw milk and absence of BCG vaccination were the other predictors of pediatric TB with AOR 13.6(3.45–53.69), 4.23(2.26–7.88), and 5. 46(1.82–16.32) respectively. Conclusion: Children who were not BCG Vaccinated were at risk of developing TB. Furthermore, HIV status, age of the child and family practice of feeding children raw milk are the independent predicators of pediatric TB in the study area. Keywords: Tuberculosis, Pediatrics, Predictors of pediatric TB, Bale zone Background as one of the major public health problems worldwide. It Tuberculosis (TB) is a chronic infectious disease caused is a major cause of disease and death worldwide and has by Mycobacterium tuberculosis (MTB). It typically affects infected around one-third of the world population . In the lungs (pulmonary TB) but can affect other parts of 2015, there were an estimated 10.4 million new (incident) the body as well (extra pulmonary TB) . If properly TB cases worldwide among which 1.0 million (10%) were treated it is medicable in virtually all cases but it remains children. People living with HIV accounted for 1.2 mil- lion (11%) of all new TB cases. WHO South-East Asia and African region contributed for higher number * Correspondence: email@example.com (greater than 70%) of incident cases [3, 4]. College of Medicine and Health Sciences, Allied School of Health Science, Even though the proportion of TB in children is smaller, Addis Ababa University, Addis Ababa, Ethiopia Addis Ababa, Ethiopia the urgency of the problem of TB in children cannot be Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 2 of 9 underestimated. They are at high risk of developing TB Bale zone is one of the zones in Oromia Regional State due to their developing immune system. The majority of and it comprises of 21 districts. Robe is an administra- them tends to develop severe and disseminated form of tive town which is 423 km away from Addis Ababa, the TB within a year or two and could die even before their capital city of Ethiopia. According to the 2013 popula- diagnosis . Every day around 200 children die due to tu- tion estimation, the total population of the zone was berculosis: disease that can be prevented and treated . around 1,661,818 among this 791,024 (47.6%) were chil- According to the 2015 WHO estimate and study on the dren below 15 years of age. In bale zone there are global burden of tuberculosis mortality in children, the an- around 84 health centers and four hospitals that are pro- nual burden of childhood mortality were over 200,000 viding DOTS both for adult and children . worldwide [7, 8]. Given the challenge in diagnosing child- hood TB, the actual burden of TB in children is likely Study design higher than the estimate [6, 9]. Institution based unmatched case control study was con- In the last 10 years tuberculosis has reemerged as a major ducted among cases or children with TB and controls or worldwide public health hazard with increasing incidence children without TB in selected public health facilities of among adults and children. Even though cases among chil- Bale Zone, south east Ethiopia. dren are not as prevalent as adult, infected children are a reservoir from which many adult cases will arise . Population Ethiopia is among the 22 high burden countries ranked Source and study population eighth in the world with an estimated TB incidence (all All patients ≤ 15 years of age who came to public health forms) of 378 new cases per 100,000 persons. It is not sur- facilities in Bale Zone were the source population and prising if the country is also among high burden countries the study population wereall patients ≤ 15 years of age with childhood TB. Children are at high risk of developing who came to the selected Public health Facilities. TB due to their un matured immune system. In Ethiopia, close to 13% of notified TB cases were children . TB is one of the top ten diseases that cause childhood Cases morbidity and mortality in Oromia regional state and All children ≤ 15 years of age who were on anti TB specifically in Bale Zone. In 2014/15 G.C around 3345 treatment. TB diagnosis was made based on the na- population were on DOTS among which pediatric cases tional comprehensive Tuberculosis, Leprosy, TB/HIV were around 628 which account around 18.77% . diagnosis and treatment manual . The standard is According to studies done in different areas, different applicable in every part of the country. Children who factors that are directly and indirectly related to poverty had TB but were attending OPD for health problems like malnutrition, living standard and style, some demo- other than TB were excluded because one subject graphic characteristics are assumed to be independent might have been selected twice since TB treatment is predictors of childhood tuberculosis [12, 13–16]. Even given in separate TB clinic. though there are studies that focus on childhood TB done in Ethiopia, they only focus on prevalence and Controls treatment outcome and most of the studies were cross All children ≤ 15 years of age who were on outpatient sectional in their design [10, 17, 18, 19]. Very few studies department and who were not diagnosed for TB. were done on risk factors of TB but they were done on the general population or focus on the adult population even though the case of pediatric TB should be consid- Exclusion criteria ered alone [15, 16, 19]. Moreover children are the most Respondents who were critically ill during the data vulnerable group for any health related problem. In collection, those who come without parents were ex- addition there is very limited study done in Ethiopia, cluded because they were assumed unable to re- particularly in this study area on factors associated with spond to the questions accordingly. Children who the development of TB among children. Therefore this had the following symptoms during the immediate study was aimed to asses’ predictors of tuberculosis weeks before data collection, cough for more than among children in public health facilities of Bale Zone, 2 weeks duration, weight loss, night sweating and south east Ethiopia. cervical & inguinal lymph node swelling were also excluded from cases and controls.. Those with the Methods above symptom were excluded because we assume Study area and period that diseases that have relatively the same symptoms The study was conducted in public health institutions of with TB might be included in the case and might Bale Zone, from January to June 2016. affect the study findings. Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 3 of 9 Sample size and sampling procedure Afaan Oromo language experts and health professionals Sample size determination for consistency of translation of the language. Data was Sample size was calculated using Epi info version 3.5.1 collected using face to face interview methods with the software by employing proportion difference approach. parents of children. Both cases and controls were inter- Proportion difference approach is used because we as- viewed by a person working on TB clinic of respective sume that there is an exposure difference on risk factor health facility after confirming their medical diagnosis among cases and controls. To detect whether the as- from clients’ medical card. The data collectors conducted sumed difference exists between the two the following the interview after providing respondents a brief orienta- assumption were used. Since there were no study found tion on the purpose of the study and its significance. in the study area and similar population: 1 to 2 cases to controls ratio was recruited to achieve 80% power and Data quality control detect an odds ratio of 2.0 at 5% significance level if 20% Before data collection, pretest was be done in 5% of the or more of the general population was exposed to the sample size population in Robe health center which were risk factors at 95% confidence level. Then Total Esti- not included in the actual sampling before the actual mated sample size was 411, (137 cases and 274 controls). data collection period and necessary adjustments were Adding a 5% nonresponse rate, a total of 144 cases and made on the tool. 288 controls were the enrolment target. Three days training was given to data collectors and supervisors about the objectives of the study, data col- Sampling procedures lection instruments, data collection procedures, and the As it is described in the study area section, there are 4 ethical consideration during data collection. The investi- hospitals and 84 health centers that are providing DOTS gators supervised and reviewed every questionnaire for service in Bale Zone. The 4 hospitals were purposively completeness and logical consistency and corrections selected. In addition around 1/5th of the health centers were made at the data collection site. Data coding, entry (16 health centers) were randomly selected by first and cleaning was performed by the investigators. stratifying all the districts in to three agro ecological classification; Highland, Mid land and Low land. From Highland, Midland and Low land agro ecologic strata 5, Data processing, analysis and presentation 5 and 6 health centers were randomly selected respect- The data was checked for completeness and consisten- ively. Health centers were proportionally allocated to the cies, and cleaned, coded and entered using Epi Info ver- number of health center in each agro ecologic strata. sion 3.5.4 and was exported to statistical package for To decrease the exposure disease relationship that can social sciences (SPSS) software version 20 for analysis. be due to the duration or prognosis of the disease, TB Descriptive statistics was performed to describe the patients on intensive phase (patient on the first 8 weeks study population in relation to relevant variable and of treatment when the treatment is given under direct findings were presented as proportions. supervision of health care worker) were selected. For Multiple logistic regression model was fitted to find fac- each case two consecutive controls that fulfill the inclu- tors associated with pediatrics TB. The candidate variables sion criteria were sampled systematically from OPD of considered were age of the child, religion, ethnicity, educa- the same health facilities from which cases were drawn. tional status of the mother, educational status of the father, Controls were selected by using systematic random sam- family size, availability of separate kitchen and window, pling method. In order to determine the interval to se- family practice of feeding children raw milk, BCG vaccin- lect controls for each case, the 3 days average patient ation status, HIV status of the child, family history of TB, flow was fixed. The interval was calculated for every occupation of the father, occupation of the mother and health facilities specifically. family size. BCG vaccination status of the children was assessed based on the presence of scar the right upper Data collection tools and procedures arm. In addition, the national average individual size per Data were collected on the socio demographic, environ- household was used to classify family size. mental, health related characteristics of the study partici- Firstly all variables were screened by carrying-out uni- pants. Semi structured questionnaires were used to collect variable analyses using a liberal p-value of 0.20. All vari- the data. Most of the questions were adapted and modi- ables significant at the 20% level were included in the fied from previous study and reviewing of different litera- multivariable analysis control confounders and identify tures [12, 21, 13–15, 22]. The questionnaires were first independent effect of different factors for occurrence of developed in English and were translated in to local lan- TB. Afterwards, stepwise logistic regression model was guage (Amharic and Afaan Oromo) and were translated used to remove variables not significant at 5% signifi- back to English. Review was made by Amharic, English, cance level. The goodness of fit test was investigated Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 4 of 9 using Hosmer and Lemeshow good-ness of fit test. All Factors associated with pediatrics TB analyses were done using SPSS version 20. For the multivariable logistic regression, the variables that were found to be significant in the univariable ana- Result lysis were considered. Sex of the child, family size, num- A total of 432 children from 20 health facilities were se- ber of rooms in the house, availability of latrine, lected to participate in the study, of which 426 partici- consumption of raw meat, previous history of TB, recent pated in the study which gives 98.6% response rate. history of diarrhea and hospitalization, and presence chronic disease were found not to be statistically signifi- Socio-demographic characteristics cant. Age of the child, mother’s educational status, num- Among the total 426 participants 142 were cases and 244 ber of people residing in the house, availability of were controls. There were equal number of male and fe- windows and separate kitchen, presence of waste dis- male 71 (50%) among cases and controls. Among the con- posal, presence of animals living in the house, consump- trols, 136 (47.9%) and 148 (52.1%) were males and females, tion of raw milk, BCG vaccination status and family respectively. The mean (standard deviation) of age among history of TB were found to be statistically associated cases was 8.4 (±4.3) and it was 7.3 (±4.1) among controls. with pediatrics TB. The results of the logistic regression With regard to occupational status of the mother are presented in Table 2. Higher odds of pediatrics TB among cases, 70 (49.3%) were housewives and 8 (5.6%) was associated with age group 11–15 compared children were government employees, while among controls 107 less than or equal to 5 years (odds ratio (OR) 1.94 95% (37.7%) were housewives and 47 (16.5) were government C.I. 1.02–3.77). employed (Table 1). Another important variable that shows strong associ- ation was family history of TB. The odds of TB among Environmental and house hold factors those who had recent family TB history was 10 times From a total of 426 participants 123 (86.6%) of cases and higher among those who didn’t have family history of 226 (79.4%) controls have privately owned house. TB with AOR 9.84 95% C.I. (4.22–22.92). Around 41 (28.9%) and 39 (13.7%) of cases and controls, Higher odds of pediatrics TB was also associated with respectively, has had more than six family members. Ac- child being infected with HIV compared to those who cording to this study, the availability and functionality of were uninfected (AOR = 13.6, 95% C.I: 3.45–53.69); windows among cases and controls were 120 (84.5%) those children who were fed raw milk compared to among which 109 (90.8%) were functional and 266 those who were not (AOR = 5.46, C.I: 1.82–16.32). (93.7) among which 257 (96.6%) were functional respect- Higher odds of TB were also associated with being vac- ively. With regard to availability of separate kitchen for cinated for BCG vaccine compared with absence of BCG cooking, 108 (76.1%) of cases and 253 (89.1%) of con- vaccination (AOR = 5.46, 95% C.I: 1.82–16.32). trols have separate kitchen for cooking. Among a total of 142 cases, majority 105 (73.9%) of Discussion them have a habit of feeding raw milk to their child This case control study assesses predictors for the occur- whereas only 86 (30.3%) of controls have a habit of feed- rence of TB among children in public health facilities. ing raw milk to their children. Age of the child, contact history with TB patient, ab- sence of BCG vaccination, presence HIV infection and Clinical characteristics of TB and co-morbid illness consumption of raw cow milk were independently asso- Of the total study participants, 12 (8.5%) of cases had ciated with increased risk of pediatrics TB. previous history of TB whereas only 6 (2.1%) of controls Despite previous perceptions that TB in pediatrics age had previous history of TB. do not pose greater risk, since children tend to acquire When asked about recent family history of TB, while mild disease, contribute less to transmission to other 45 (31.7%) of the cases responded positively only 10 people and do not impact epidemic control, pediatrics TB (3.5%) said they have had family history of TB. More has been considered as an important public health prob- than a quarter 39 (27.5%) of the cases and 7 (2.5%) of lem which is easily preventable cause of disease and death. the controls were not vaccinated for BCG. Our study identified several risk factors that contribute Co-morbid illnesses that are related with pediatric TB to the development of pediatrics TB. Some of these fac- were also assessed. Our study revealed that none of the tors have also been previously described [23, 24, 25, 26], cases were diabetic whereas 5 (1.8%) of the controls had and confirmed by our study. Studies indicated that vari- history of raised blood glucose level (BGL). Regarding ous factors contribute to the development of pediatrics HIV status of the study participants, 16 (11.3%) of the TB. The findings of our study indicated that the age of cases and 4 (1.4%) of the controls were infected with the child was one of the predictor for pediatric TB, in HIV (Table 2). which the risk was higher among 11–15 age group Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 5 of 9 Table 1 Socio demographic characteristics of pediatric patient with TB and Without TB in public health facilities of Bale zone, south east Ethiopia, 2016 Variable Level Disease status Case Control Frequency (%) Frequency (%) Age ≤5 39 (27.5) 106 (37.3) 5–10 50 (35.2) 105 (36.9) 10–15 53 (37.3) 73 (25.7) Sex Male 71 (50) 136 (47.9) Female 71 (50) 148 (52.1) Religion Muslim 102 (71.8) 142 (50) Orthodox 32 (22.5) 109 (38.4) Protestant 2 (1.4) 30 (10.6) Catholic 2 (1.4%) 2 (0.7) Wakefeta 4 (2.8%) 1 (0.4) Ethnicity Amhara 9 (6.3%) 62 (21.8) Oromo 121 (85.2%) 178 (62.7) Tigre 2 (1.4%) 13 (4.6) Gurage 2 (1.4%) 14 (4.9) Others 8 (5.6%) 17 (6.0) Child’s educational status Can’t read and write 13 (9.2%) 5 (1.8) Not enrolled 54 (38.0%) 135 (47.5) Primary school 68 (47.9%) 140 (49.3) Secondary school 7 (4.9%) 4 (1.4) Mother’s educational status Can’t read and write 69 (48.6%) 59 (20.8) Can read and write 29 (20.4%) 46 (16.2) Primary school 20 (14.1%) 71 (25.0) Secondary education 19 (13.4) 74 (26.1) Above secondary education 5 (3.5) 34 (12.0) Father’s educational status Can’t read and write 39 (27.5) 35 (12.3) Can read and write 45 (31.7) 46 (16.2) Primary school 26 (18.3) 48 (16.9) Secondary education 20 (14.1) 86 (30.3) Above secondary education 12 (8.5) 69 (24.3) Mother’s occupation Farmer 34 (23.9) 27 (9.5) Merchant 25 (17.6) 83 (29.5) Gov’t employee 8 (5.6) 47 (16.5) Non gov’t employee 2 (1.4) 15 (5.3) Day labor 3 (2.1) 5 (1.8) Housewife 70 (49.3) 107 (37.7) Father’s occupation Farmer 82 (57.7) 73 (25.7) Merchant 32 (22.5) 77 (27.1) Gov’t employee 13 (9.2) 84 (29.6) Non gov’t employee 6 (4.2) 28 (9.9) Day labor 3 (2.1) 13 (4.6) Pastoral 2 (1.4) 3 (1.1) Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 6 of 9 Table 1 Socio demographic characteristics of pediatric patient with TB and Without TB in public health facilities of Bale zone, south east Ethiopia, 2016 (Continued) Variable Level Disease status Case Control Frequency (%) Frequency (%) Others 4 (2.8) 6 (2.1) Family size ≤5 65 (45.8) 185 (65.1) > 5 77 (54.2) 99 (34.9) children when compared with children of age group ≤5. number of individuals with TB. TB is the leading This finding was supported by Federal Ministry of cause of death in HIV positive people, and HIV infec- Health 16th National Annual review Report on Tubercu- tion is a significant risk factor for TB . Our study losis, proportion of TB patients among older children found that HIV infected children are more likely to aged 5–14 were higher than those aged 0–4 years . be infected with TB. This could be explained by the fact that as the age of the Similarly, Investigators from a case control study con- child increase, the probability of the child to spend time ducted in Zambia , a study in Northwest Ethiopia outside his/her home is high which in-turn increases  and another study from South Africa  reported their chance of contact with infectious cases. that TB was associated with the increased HIV infection. Effective investigation of TB contacts is of great import- The current study also revealed that children who were ance in that they contribute greatly to early detection of ac- vaccinated for BCG have a reduced risk of TB. This was tive TB, thus decreasing its severity and transmission to evidenced by meta-analysis of available studies where others. Our study unsurprisingly revealed that TB disease BCG vaccine can reduce risk of TB infection by as much has a ten-fold increase among study participants with con- as 50% . tact history with TB patients. This finding was confirmed by several previous studies conducted elsewhere [23, 28, 29, Strengths 30], where they indicated contact history as an important We used case control study design which is appropriate risk factor for the transmission of childhood TB. In most to address the research question. The cases and controls low- and middle-income settings, even-though investigation were also taken from the same institutions which made of TB contact is included in the national TB control pro- it easy to identify controls. gram, it is rarely and consistently conducted due to resource constraints. However, contact history investigation merits Limitations serious consideration as a means to improve early case de- One of the limitations of this study might be recall tection and prevent transmission of mycobacterium tuber- bias as study participants may not remember condi- culosis infection. tion of the past. Additional limitation was environ- In our study, family history of feeding children mental and house hold factors were assessed without raw cow milk was strongly associated with pediatric observation and this may have underestimated or TB where children who has history of consuming overestimated the effect in the findings. Although raw milk had 4 folds increase in the odds of devel- malnutrition is important factor that highly contrib- oping TB than those who don’t, where previous ute for the occurrence of TB in children, we were study in Russia  indicated similar finding. The unable to analyze it due to incompleteness of most association between consumption of raw milk and of the data. TB in this study can be explained the fact that TB can also be caused by mycobacterium bovis which is Conclusion found in unpasteurized milk. The consumption of The finding of this study has given insight on differ- unpasteurized milk in the study area is high. If the ent predictors of pediatric TB. Children that have association proves to be due to mycobacterium contact history with adult individual with TB are at bovis, which the current study has not identified, risk of acquiring the infection. BCG vaccination sta- ensuring milk safety would be a public health tus, HIV status, age of the child and family practice priority. of feeding children raw milk are the independent pre- In high HIV prevalence settings, tuberculosis (TB) dicators of pediatric TB. Therefore Bale Zonal health and HIV/AIDS cannot be considered in isolation from office is highly recommended to work with different each other. Co-infection with HIV, especially in stakeholders to increase public awareness on risk fac- sub-Saharan countries, has significantly increased the tors of pediatric TB and its transmission. Contact Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 7 of 9 Table 2 Logistic regression analysis of factors associated with pediatric TB in public health facilities of Bale Zone, south east Ethiopia, 2016 Variable Level Disease status COR (95% CI) AOR (95% CI) Control Case Frequency (%) Frequency (%) Sex Male 136 (47.9) 71 (50.0) 1 Female 148 (52.1) 71 (50.0) 1.08(0.72–1.63) – Age ≤5 106 (37.3) 39 (27.5) 1 1 6–10 105 (37.5) 50 (35.2) 1.29(0.78–3.18) 1.26(0.67–2.43) 11–15 73 (25.7) 53 (37.3) 1.97(1.18–3.18) 1.94(1.02–3.77) Mother’s educational status Can’t read and write 59 (20.8) 69 (48.6) 7.95(2.92–21.64) 2.35(0.68–5.05) Can read and write 46 (16.2) 29 (20.4) 4.28(1.50–12.22) 1.54(0.43–5.49) Primary 71 (25.0) 20 (14.1) 1.91(0.66–5.53) 1.68(0.49–5.72) Secondary 74 (26.1) 19 (13.4) 1.76(0.60–5.06) 1.14(0.62–2.17) Tertiary 34 (12.0) 5 (3.5) 1 Family size ≤5 185 (65.1) 65 (45.8) 1 > 5 99 (34.9) 77 (54.2) 2.21(0.46–3.33) – No of people living in the house ≤3 44 (15.5) 13 (9.2) 1 4–6 201 (70.8) 88 (62.0) 1.48(0.76–2.88) 1.55(0.63–3.81) > 6 39 (13.7) 41 (28.9) 3.56(1.66–7.56) 1.75(0.55–5.57) Number of rooms in the house 1–3 254 (89.4) 136 (95.8) 1 4–6 30 (10.6) 6 (4.2) 0.37(0.15–1.92) – Availability of windows Yes 266 (93.7) 120 (84.5) 1 No 18 (6.3) 22 (15.5) 2.7(1.40–5.32) 0.85(0.33–2.16) Availability of separate kitchen Yes 253 (89.1) 108 (76.1) 1 No 31 (10.9) 34 (23.9) 2.56(1.50–4.39) 0.53(0.20–1.22) Availability of latrine Yes 252 (88.7) 113 (79.6) 1 No 32 (11.3) 29 (20.4) 2.02(0.99–3.50) – Waste disposal In the compound 97 (34.2) 78 (54.9) 2.35(1.56–3.55) 1.03(0.59–1.81) Outside compound 187 (65.8) 64 (45.1) 1 Availability of tap water Yes 186 (65.5) 50 (35.2) 1 No 98 (34.5) 92 (64.8) 3.49(2.29–5.33) 1.27(0.66–2.44) Do animal live in your house Yes 34 (12.0) 54 (38.0) 4.51(2.76–7.39) 1.75(0.86–3.56) No 250 (88.0) 88 (62.0) 1 Do you feed your child row meat Yes 204 (71.8) 115 (81.0) 1.67(1.01–2.73) – No 80 (28.2) 27 (19.0) 1 Do you feed your child raw milk Yes 86 (30.3) 105 (73.9) 6.53(4.16–10.27) 4.23(2.26–7.88) No 196 (69.7) 37 (26.1) 1 Previous history of TB Yes 6 (2.1) 12 (8.5) 4.27(0.96–11.65) – No 278 (97.9) 130 (91.5) 1 BCG vaccination status Yes 277 (97.5) 103 (72.5) 1 No 7 (2.5) 39 (27.5) 13.52(6.13–29.88) 5.46(1.82–16.32) Family history of TB Yes 10 (3.5) 45 (31.7) 12.71(6.17–26.20) 9.84(4.22–22.92) No 274 (96.5) 97 (68.3) 1 Vaccination at 9 month Yes 254 (89.4) 87 (61.3) 1 Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 8 of 9 Table 2 Logistic regression analysis of factors associated with pediatric TB in public health facilities of Bale Zone, south east Ethiopia, 2016 (Continued) Variable Level Disease status COR (95% CI) AOR (95% CI) Control Case Frequency (%) Frequency (%) No 30 (10.6) 55 (38.7) 5.35(3.22–8.89) 0.98(0.44–2.19) Resent history of diarrheal disease Yes 51 (18.0) 16 (11.3) 0.58(0.32–1.06) – No 233 (82.0) 126 (88.7) 1 Resent history of hospitalization Yes 37 (13.0) 31 (21.8) 1.86(1.01–3.16) – No 247 (87.0) 111 (78.2) 1 HIV status of the child Positive 4 (1.4) 16 (11.3) 8.89(2.91–27.12) 13.61(3.45–53.69) Negative/unknown 280 (98.6) 126 (88.7) 1 Does the child has any chronic disease Yes 14 (4.9) 12 (8.5) 1.78(0.8–3.96) – No 270 (95.1) 130 (91.5) 1 tracing and contact screening should be correctly im- verbal consent by explaining objectives of the study and its significance. In addition ascent was asked from children who can speak and understand. plemented to prevent transmission of the infection Parents were informed that their participation in the study was voluntary and early diagnosis. Further research should be done and they were free to withdraw their participation at any time they want. to investigate if bovine TB is dominant in the area to Participant’s confidentiality were maintained by omitting the respondents name and address in the questionnaire. Study respondents were given take appropriate measure. assurance that there were no physical and emotional harm resulting from participating in the study. Abbreviations AIDS: Acquired immune deficiency syndrome; BZHB: Bale zone health Competing interests bureau; CI: Confidence interval; DOTS: Directly observed treatment, short The authors declare that they have no competing interests. course; EPI: Expanded program of immunization; EPTB: Extra-pulmonary tuberculosis; FMOH: Federal Ministry of Health; HIV: Human immunodeficiency virus; MDR-TB: Multidrug resistant tuberculosis; Publisher’sNote MWU: MaddaWalabu University; OR: Odds Ratio; PTB: Pulmonary tuberculosis; Springer Nature remains neutral with regard to jurisdictional claims in TB: Tuberculosis; TB/HIV: Tuberculosis and HIV co-infection; TBIC: Tuberculosis published maps and institutional affiliations. infection control; WHO: World Health Organization; XDR-TB: Extensively drug resistant tuberculosis Author details College of Medicine and Health Sciences, Allied School of Health Science, Acknowledgements 2 Addis Ababa University, Addis Ababa, Ethiopia. Department of Occupational We would like to express our deepest gratitude to MaddaWalabu University Health, Higher Education Relevance and Quality Agency, Addis Ababa, for funding this research. We would also like to extend our appreciation to 3 Ethiopia. Ethiopian Public Health Institute, Food Science and Nutrition the data collectors who participated in the study. We are also grateful to all 4 Directorate, Addis Ababa, Ethiopia. College of Health and Medical Sciences, hospital, health center administration and study subjects. 5 School of public health, Haramaya University, Harar, Ethiopia. Addis Ababa, Ethiopia. Harar, Ethiopia. Funding The study was funded by MaddaWalabu University, Ethiopia. The funder has Received: 14 December 2017 Accepted: 24 May 2018 no role in study design, data collection and analysis, interpretation of data, decision to publish, or preparation of the manuscript. References Availability of data and materials 1. World Health Organization Fact Sheet No.104: Tuberculosis. Geneva: WHO; Data is available and it can be accessed from the corresponding author 2010. Available from: http://www.who.int/mediacentre/factsheets/fs104/en/ when asked with reasonable inquiry. print.html. 2. Fauci B, Kasperetal H. Principle of Internal Medicine. United States of th Authors’ contributions America: McGraw-Hill Medical Publishing Devision; 2008. 17 edition, BG conceived and designed the study, performed data analysis, compiled chapter 38. the whole work and prepared the manuscript. TA, TM, participated in design, 3. WHO. Global tuberculosis report. Geneva: WHO; 2015. www.who.int/tb/data analysis, reviewing the main document and took part in the critical revision 4. WHO. Global tuberculosis report. 2014.http://www.who.int/tb/publications/ of the manuscript. AAA, NW participated in analysis, reviewing the main global_report/en/ document and took part in the critical revision of the manuscript. All authors 5. FMOH. Ethiopian Population Based National TB Prevalence Survey Research read and approved the final manuscript. Protocol. Addis Ababa: FMOH; 2010. 6. WHO. Global tuberculosis report. Library cataloguing-in-publication data. Ethics approval and consent to participate 2014. Ethical clearance was obtained from MaddaWalabu University (MWU) 7. Dodd PJ, et al. The global burden of tuberculosis mortality in children: a research ethical committee and support letter was taken from zonal health mathematical modeling study. Lancet Glob Health. 2017;5(9):e898–906. bureau. Permission was asked from each selected health facility principal. 8. WHO. Global tuberculosis report 2016. Geneva: World health The ethics committee approved obtaining informed consent verbally organization; 2016. because most of the study participants have no formal education and are 9. Tsai K, Chang H, et al. Childhood tuberculosis: epidemiology, diagnosis, unable to read and write. Each study subject’s parents were asked their treatment and vaccination. Pediatr Neonatol. 2013;54(5):295–302. Gebremichael et al. BMC Infectious Diseases (2018) 18:252 Page 9 of 9 10. Jamie C, Jessica G. Assessing Tuberculosis Management and Prevention in Rural and Semi-urban Ethiopia. USA: University of Washington; 2009. 11. Bale Zone Health Bureau. Annual report. Bale Robe: Bale Zone Health Bureau; 2015. 12. Anamarija J, et al. Risk factors for pulmonary tuberculosis in Croatia: a matched case control study. BMC Public Health. 2013;13:991. 13. Kirenga BJ, et al. Tuberculosis risk factors among tuberculosis patients in Kampala, Uganda: implications for tuberculosis control. BMC Public Health. 2015;15:13. https://doi.org/10.1186/s12889-015-1376-3. 14. Mohamed R, Mohamed A, et al. Risk factors of childhood tuberculosis in rural Bangladesh. WHO South-East Asia J Public Health. 2012;1(1):76–84. 15. Kefyalew T. Risk Factors for Active Tuberculosis in Children in Contact with Smear Positive Cases in Southern Ethiopia: Maters Thesis University of Liverpool; 2010. p. 57–9. http://www.academia.edu/2492196/. 16. Cheru T, Takele T, et al. Environmental and host-related determinants of tuberculosis in Metema district, north-West Ethiopia. Drug Healthcare Patient Saf. 2015;7:87–95. 17. Moges B, et al. Prevalence of smear positive pulmonary tuberculosis among prisoners in North Gondar zone prison, Northwest Ethiopia. BMC Infect Dis. 2012;12:352. https://doi.org/10.1186/1471-2334-12-352 18. Muñoz-Sellart M, et al. Treatment outcome in children with tuberculosis in southern Ethiopia. Scand J Infect Dis. 2009;41:4505. 19. Ramos A, et al. Childhood and adult tuberculosis in a rural hospital in Southeast Ethiopia: a ten-year retrospective study. BMC Public Health. 2010;10:215. 20. FMOH. Ethiopia National comprehensive Tuberculosis, Leprosy, TB/HIV diagnosis and treatment manual. Addis Ababa: FMOH; 2016. 21. Marais B, et al. The natural history of childhood intra thoracic tuberculosis, a critical review of the pre-chemotherapy literature. Cold Spring HarbPerspect Med. 2014;4:a017855. 22. FMOH. Ethiopian National Population Based Tuberculosis Prevalence Survey. Addis Ababa: FMOH; 2011. 23. Karim M, et al. What cannot be measured cannot be done; risk factors for childhoodtuberculosis: a case control study. Bangladesh Med Res Counc Bull. 2012;38:27–32. 24. Coker R, et al. Risk factors for pulmonary tuberculosis in Russia: case-control study. BMJ. 2006;332:85–7. 25. Singh M, et al. Prevalence and risk factors for transmission of infection among children in household contact with adults having pulmonary tuberculosis. Arch Dis Child. 2005;90:624–8. 26. Colditz GA, et al. Efficacy of BCG vaccine in the prevention of tuberculosis meta-analysis of the published literature. JAMA. 1994;271(9):698–702. https://doi.org/10.1001/jama.1994.03510330076038. 27. FMOH. Evaluating the National TB Control Program: Challenges and ways forward Disease Prevention and Control. 16th National Annual Review Meeting Group Discussion. Ethiopia: FMOH; 2014. 28. Simon S, Ben JM, et al. Culture-confirmed childhood tuberculosis in cape town, South Africa: a review of 596 cases. BMC Infect Dis. 2007;7:140. 29. Jurcev-Savicevic A, et al. Risk factors for pulmonary tuberculosis in Croatia: a matched case– control study. BMC Public Health. 2013;13:991. 30. Morrison J, Pai M, Hopewell PC. Tuberculosis and latent tuberculosis infection in close contacts of people with pulmonary tuberculosis in low- income and middle-income countries: a systematic review and meta- analysis. Lancet Infect Dis. 2008;8(6):359–68. 31. Ashley K. TB, HIV, and TB/HIV co-infection: community knowledge and stigma in western Uganda by maters thesis 2012. 32. Boccia D, Hargreaves J, De Stavola BL, Fielding K, Schaap A, Godfrey- Faussett P, et al. 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BMC Infectious Diseases – Springer Journals
Published: Jun 4, 2018
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