Research Article, J Infect Dis Immune Ther Vol: 2 Issue: 1
Effects of Poor Protein Intake and In-House Overcrowding On Childhood Tuberculosis in a Low-Income Bangladeshi Rural Community: A Case-Control Study
Received: March 28, 2018 Accepted: May 08, 2018 Published: May 15, 2018
Citation: Rahman T, Kaiser I, Saba S, Irfan S, Akter A, et al. (2018) Effects of Poor Protein Intake and In-House Overcrowding On Childhood Tuberculosis in a Low-Income Bangladeshi Rural Community: A Case-Control Study. J Infect Dis Immune Ther 2:1.
Despite a well-functioning tuberculosis (TB) control program in Bangladesh, tuberculosis (TB) contributes to an unacceptably high rate of morbidity and mortality among children. We identify the risk factors of childhood TB in a tea garden based area of Bangladesh. A case control study with 216 cases and 216 controls was conducted at seven sub-districts of Moulvibazar district in Bangladesh during the period of March 2016 to September 2016. Socio demographic and clinical data were obtained from each participant via face-to-face interview using a standard semi-structured questionnaire. Data was collected from the patient’s relative who came to the DOT’S center along with the children. Crude and multivariate logistic regression analyses were used to analyze the data. The multivariate logistic regression analysis indicated that over-crowding (>4 persons per bedroom) in the house (OR = 2.64, 95% CI = 1.66-4.25), positive history of TB in the family (OR = 1.87, CI = 1.19-2.95) and poor protein intake (OR = 1.72, CI = 1.07-2.77) are the significant risk factors for childhood TB. Besides, poor monthly income (<10000 taka) (OR = 0.58, CI = 0.30-1.10) and younger child (<10 years of age) are found nearly significant for childhood TB. To conclude, improvement in the living standard of children will help in reducing childhood TB in the community. The identified risk factors for the childhood tuberculosis reflect a complex interaction among sociodemographic conditions. The control program for the childhood TB would benefit from a collaboration of broad public health activities in improving the socio-demographic factors in the rural community.
Keywords: Childhood tuberculosis; Case-control study; Crowding; Multivariate analysis; Bangladesh
Despite a well-functioning tuberculosis (TB) control program in Bangladesh, tuberculosis (TB) contributes to an alarmingly high rate of morbidity and mortality among children. According to WHO (2016) report, approximately one million (11%) are children from the 9.2 million new tuberculosis cases worldwide . It is estimated that with accurate diagnosis and good reporting systems, children less than 15 years of age are likely to contribute to 4-22% of the disease burden in 22 high-risk countries . With excellent TB control and active provision of preventive therapy to child contacts, the burden of childhood TB can be reduced to below 5%, which is the case in many developed countries. Because children acquire TB from the infectious adult cases, the incidence of pediatric TB provides an accurate measure of ongoing transmission within communities, a key indicator of epidemic control [3-6].
In Bangladesh, childhood TB is a highly neglected public health phenomenon. Bangladesh ranks seventh among the world’s 30 high TB burden countries. The incidence and prevalence of all forms of TB for all age groups was 224/100,000 and 402/100,000 population in 2013, respectively [2,7]. In 2015, among all 199,001 TB cases, a total of 7984 (4.01%) TB cases were children . In fact, the actual burden of TB in children is likely higher, especially given the challenge in diagnosing childhood TB.
In developing countries, the number of childhood TB cases are heavily found in low-income rural compared to the urban areas. Studies showed that the TB proliferation risk is reduced when availability of a separate kitchen, house type, indoor crowding, age, gender, urban or rural residence are adjusted [8-12]. A household TB case is most commonly implicated for infection among young children. Older children are increasingly likely to be infected from outside the household. Poor nutrition is also a predominant risk factor for contracting TB and mortality [13-16]. Malnutrition increases the host’s susceptibility to infection especially in case of children. Both, protein-energy malnutrition and nutrient deficiencies increase the risk of tuberculosis.
Knowing the underlying risk factors of childhood TB in rural areas could be helpful in terms of devising preventive measures against childhood TB in order to reduce the morbidity and the mortality associated with TB. In Bangladesh, childhood tuberculosis is a relatively neglected problem and factors responsible for its aggravation have not been studied adequately. This study will be conduct to determine the socio-demographic features in a lowincome rural community that may be in taking preventive measures against tuberculosis to reduce morbidity and mortality related to this disease.
In Bangladesh, there is yet to be a formal study conducted about the effect of the in-house crowding on the susceptibility to childhood TB. Our main interest of the study is to gain a understanding of the risk factors of childhood TB and how crowding affects on it.
Study design, site and population
We conducted a case-control study in seven sub-districts of Moulovibazar, Bangladesh. Cases were the children who diagnosed as TB patients by the laboratory test of sputum-positive. Children who visited the DOTS centers but were sputum-negative during the same time period were taken as controls. The children from the tea-garden workers were chosen because they live in tight-knit communities in smaller houses and belong to the low-income family group. The maximum family income was found around 20000 taka (or approximately $250 U.S.) per month. The highest education of the participants father is relatively low with few of them went secondary schools but didn’t complete it. They originate from lower socio-economic backgrounds therefore they live in smaller and more crowded residences.
The data was collected via face-to-face in-depth interviews from the adult relatives of children that followed a semi-structured questionnaire. The questionnaire comprised comprehensive questions about study participants’ socio-demographic characteristics, lifestylerelated factors and clinical factors.
Ethical approval for the study protocol was obtained from the North South University Ethics Review Committee, while a written consent was obtained from each study participant.
We analyzed the data using the software R. Descriptive statistics were calculated for all of the categorical variables (presented as frequencies and percentages). We fitted a multivariate logistic regression model with the case-controls. The results are reported by the adjusted odds ratios (ORs) and corresponding p-values are also presented in a (Table 1). p-values less than 0.05 were considered statistically significant.
The data were comprised of 216 cases and 216 controls. Table 1 shows the participants characteristics corresponding to the TB status. Among these covariates, age, sex, crowding (4+), family history of TB during the last 6 months and protein intake per week were found significantly associated with the TB status according to the values of unadjusted odds ratios. It appears that the 56% of the male children were found from TB cases whereas 46% of the female children were found from TB cases. Besides, increasing age of the child was found associated with increasing odds of infection of TB (57% of the cases are from above 10 years of age while 44% of the cases are from less than or equal to 10 years of age). The variable crowding reflects that 64% of the cases are from the participants who lived in a over-crowed room (>4 persons per room) whereas 44% of the cases are from the participants who lived in a less crowded room (<=4 persons per room).
|Factors||Categories||Case (row %)||Control||OR (CI)||P-Value|
|Age||2-6||38 (44%)||49||0.59 (0.36-0.97)||0.040|
|7-10||55 (43%)||73||0.57 (0.37-0.89)||0.014|
|Male||116 (56%)||93||1.53 (1.05-2.25)||0.027|
|Family income||<10000||190 (51%)||182||Ref|
|>=10000||26 (43%)||34||0.73 (0.42-1.26)||0.267|
|> 4||78 (64%)||43||2.27 (1.48-3.53)||<0.001|
|Mother education||11+||13 (54%)||11||1.19 (0.51-2.78)||0.683|
|1-10 Years||43 (50%)||44||0.98 (0.61-1.58)||0.945|
|No schooling||160 (50%)||161||Ref|
|Father education||11+||22 (61%)||14||1.61 (0.80-3.34)||0.185|
|1-10 Years||46 (48%)||50||0.94 (0.59-1.50)||0.809|
|No schooling||148 (49%)||152||Ref|
|Mother occupation||House wife||152 (48%)||166||Ref|
|Working||64 (56%)||50||1.39 (0.91-2.15)||0.127|
|Father Occupation||Day labor||145 (51%)||137||Ref|
|Garden worker||71 (47%)||79||0.85 (0.57-1.26)||0.419|
|Distance from DOTS center||<=5 km||77 (49%)||79||Ref|
|5+ km||139 (50%)||137||1.04 (0.70-1.54)||0.841|
|Family History of TB (last 6 months)||No||139 (45%)||169||Ref|
|Protein Intake||<=2 per week||169 (53%)||149||1.62
|>2 per week||47 (41%)||67||Ref|
|Neighbor TB||No||118 (49%)||123||Ref|
|Yes||98 (51%)||93||1.09 (0.75-1.61)||0.628|
|BCG was given||No||19 (58%)||14||Ref|
|Yes||197 (49%)||202||0.72 (0.34-1.46)||0.367|
Ref is reference. OR is the crude odds ratio. * Family members to room ratio
Table 1: Patient’s characteristic and unadjusted odds ratio of each covariates and case control.
According to the adjusted multivariate analysis, crowding (>4 persons per bedroom) in the house (OR = 2.64, 95% CI = 1.66-4.25), positive history of TB in the family (OR = 1.87, CI = 1.19-2.95) and poor protein intake (OR = 1.72, CI = 1.07-2.77) are found positively associated with childhood TB. The results indicate that the children who live in a over-crowded room (>4 persons in a room) are 2.64 times more likely to be in the TB case group compared to the children who live in a less crowded room (<=4 persons in a room). Besides, poor monthly income (<10000 taka) (OR = 0.58, CI = 0.30-1.10) and younger child (< 10 years of age) are found nearly significant for childhood TB. Father’s educational status, mother’s educational status, as well as occupational status did not have a significant association. The propensity to contract childhood TB is almost 2 times higher in families that have previous positive family TB history. The association between contracting TB and family history is highly significant (p=0.001) (Table 2).
|Family income- 10000+||<10000||-0.53||0.58||0.30||1.10||0.098|
|Mother Education 11+||No Schooling||0.04||1.04||0.34||3.17||0.946|
|Distance from DOTS center
|Family History TB-Yes||No||0.63||1.87||1.19||2.95||0.006|
|Neighborhood TB- Y||No||0.10||1.10||0.73||1.67||0.639|
|Protein Intake per week (<=2)||>2||0.54||1.72||1.07||2.77||0.025|
Table 2: Adjusted relationship between covariates and case control that is analysed using multivariate logistic regression model.
In the multivariate model, Crowding 4+ (Ref: <4): OR (95% CI)=2.64 (1.66-4.25); p<0.001. The odds of being infected with childhood TB was more likely (2.64 times higher) among those participants having crowding of 4 and more compared, with the children who lived in relatively less crowded residences.
This study shows a highly significant association between childhood tuberculosis and crowding. National statistics of Bangladesh showed male to female ratio is 2:1 among TB patients below 14 years of age. In this study, we saw male child aged between 7-10 years are likely to develop tuberculosis (TB) 1.5 times more than girls of the same age.
Socioeconomic conditions have traditionally been cited as risk factors for developing TB. Several studies have shown a correlation between the rate of infection in households, crowding, and poverty (US), between TB case notification rate, income, and socioeconomic characteristics (Canada), and between prevalence of infection, social, and economic environment (Panama). The case notification rate of childhood TB has been reported to be related to crowding (US), income (US), rate of unemployment (US), infant mortality (US), and social deprivation (UK). That all three factors studied by us (crowding, economic status, and parental education) were significantly correlated with the case notification rate of TB in children was thus expected. The correlation between maternal literacy and childhood morbidity and mortality is well known [17-20].
This study showed household contact as an important risk factor for tuberculosis which is consistent with the findings of some previous studies in West Africa and Lao People’s Democratic Republic where family history of TB was two to three times more frequent among childhood TB cases compared to the controls. We saw its alomost 2 times higher in families that have previous positive family TB history. The association is highly significant [21-22]. The findings suggest that there are highly positive association (P<0.001) between crowing 4 and more with childhood TB.
Increased size of the household was found to be important and overcrowding has been documented as a risk factor for TB in several studies in a variety of settings. Measurement of the bedroom area may not reflect the actual usable bedroom space because in a rural setting, it is always occupied by some furniture, utensils, stored crops, agricultural tools, bundles of firewood, jute-straw, and sometimes pet animals. The number of windows reflects a vague expression of ventilation status (there are many variables regarding window(s), such as: size of the window, position or placement, how often it is kept open, window material – glass, wood or metal, etc.). Children living in households with a separate kitchen were less likely to have active TB as was also found in India .
One of the major limitations of this study was that, due to the small sample size, it is difficult to adequately represent the scenario about the underlying risk factors of childhood TB. Moreover, since this study was also conducted in one catchment area, it may not have been entirely representative of the Bangladeshi childhood TBpositive population.
To conclude, improvement in the living standard of children (housing condition etc.) will help in reducing childhood TB in the community. The tuberculosis prevention programme in Bangladesh mostly focuses on detecting and treating index cases. Contact tracing and contact screening should also be incorporated as part of the National TB Control Programme for early diagnosis and treatment. Poverty, lack of education, poor housing, urban environments and overcrowding are all associated with increased transmission.
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