Identifying risk factors associated with smear positivity of pulmonary tuberculosis in Kazakhstan.

BACKGROUND: Sputum smear-positive tuberculosis (TB) patients have a high risk of transmission and are of great epidemiological and infection control significance. Little is known about the smear-positive populations in high TB burden regions, such as Kazakhstan. The objective of this study is to characterize the smear-positive population in Kazakhstan and identify associated modifiable risk factors. METHODS: Data on incident TB cases' (identified between April 2012 and March 2014) socio-demographic, risk behavior, and comorbidity characteristics were collected in four regions of Kazakhstan through structured survey and medical record review. We used multivariable logistic regression to determine factors associated with smear positivity. RESULTS: Of the total sample, 193 (34.3%) of the 562 study participants tested smear-positive. In the final adjusted multivariable logistic regression model, sex (adjusted odds ratio (aOR) = 2.0, 95% CI:1.3-3.1, p < 0.01), incarceration (aOR = 3.6, 95% CI:1.2-11.1, p = 0.03), alcohol dependence (aOR = 2.6, 95% CI:1.2-5.7, p = 0.02), diabetes (aOR = 5.0, 95% CI:2.4-10.7, p < 0.01), and physician access (aOR = 2.7, 95% CI:1.3-5.5p < 0.01) were associated with smear-positivity. CONCLUSIONS: Incarceration, alcohol dependence, diabetes, and physician access are associated with smear positivity among incident TB cases in Kazakhstan. To stem the TB epidemic, screening, treatment and prevention policies should address these factors.

Risk Factors for Primary Pulmonary TB in Almaty Region, Kazakhstan: A Matched Case-Control Study.

BACKGROUND: This study examined the association between incident pulmonary tuberculosis (TB) and social and behavioral characteristics in Almaty Oblast, Kazakhstan from 2012 to 2013. METHODS: We used a matched case-control design to estimate the role of factors for acquiring pulmonary TB. Totally 324 individuals were recruited from Sep 2012 to Mar 2013. Participants included 110 TB index cases with newly detected pulmonary TB. Each case was matched with one household and one community control. A total of 107 household and 107 community controls were included to the study. Adjusted odds ratios measuring associations between TB and risk factors were calculated by using a conditional multiple logistic regression analysis. RESULTS: TB cases were more likely to be younger, recent smokers and have diabetes, when compared to household controls. Between TB cases and community controls, TB was significantly associated with age, non-married family status, living in a rented home, recent smoker, and having diabetes. Comparing TB cases with community controls, we found that foreign birth was marginally associated with incident TB case status. CONCLUSION: Our findings confirm the role of modifiable risk factors for TB in Kazakhstan; highlighting the importance of developing interventions addressing social determinants and proximate risk factors for high TB burden regions.

Tuberculosis in Kazakhstan: analysis of risk determinants in national surveillance data.

BACKGROUND: Development of tuberculosis (TB) is determined by various risk factors and the interactions of temporal and spatial distributions. The aim of this study was to identify the most salient risk factors for TB disease as well as multidrug resistant TB (MDR-TB) at the oblast (provincial) level in Kazakhstan. METHODS: Correlational and descriptive analyses were conducted at the oblast and national level using data provided by the country's National Institute of Geography (NIG) and the National Tuberculosis Program (NTP). Reported incident case notification rates (CNRs) and prevalence vary by oblast, thus the study investigated which determinants contributed to this regional variation and compared burdens among oblasts. RESULTS: The results showed that while tuberculosis CNRs decreased over the study period, MDR-TB conversely increased. Two oblasts -Atyrauskaya and Mangystauskaya - presented especially significant anomalies with large decreases in TB incident CNRs coupled with comparatively large increases in MDR-TB incident CNRs. CONCLUSION: Understanding the distribution of TB and MDR-TB cases and associated risk factors, especially the "unknown risk factor" categorization points to the need for future research.