oses a major health risk, it is essential to delineate the role of these environmental factors in the etiology and epidemiology of TB. Previous reviews have addressed qualitatively the epidemiologic and biologic link between tobacco smoke and TB, but have not systematically reviewed the epidemiologic data on this association [3,4]. We therefore undertook to quantitatively assess the association between smoking, passive smoking, and IAP, and the risk of infection, disease, and death from TB. We have considered smoking, passive smoking, and IAP together because these sources result in exposure to common set of respirable pollutants, and because their effects are currently or increasingly found in the developing countries.
We searched the PubMed via the NCBI Entrez system (1950 to February 1, 2006) (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi) and the EMBASE via Ovid (1988 to 2003) (http://www.ovid.com) for studies of the association between smoking, passive smoking, and indoor air pollution and TB infection, disease, and mortality. We also searched bibliographies of identified reports for additional references. Our search strategy is described in Box 1.
We limited our search to studies published in English, Russian, and Chinese. Studies were included if they involved human participants with TB or at risk from TB. We included studies if a quantitative effect estimate of the association between ever, former, or current tobacco smoking, passive smoking, or IAP, and TST positivity, clinical TB disease, or TB mortality was presented or could be estimated from the data provided in the paper or through contact with the authors. Studies were included in the review if they were full-length peer-reviewed reports of cohort studies, case-control studies, or cross-sectional studies, if they controlled for possible confounding by age or age group, and if they screened for the presence of TB among exposed and unexposed study participants in the same way. For analyses of the effect of passive smoking on TB outcomes, we excluded studies if they did not restrict the population under study to nonsmokers. If multiple published reports from the same study participants were available, we included only the one with the most detailed information for both outcome and exposure.
Search Strategy and Terms Used to Identify Studies on Smoking and TB
MeSH term search
3. “air pollution, indoor”
5. “fuel oils”
6. “(1) AND (2)” OR “(1) AND (3)” OR “(1) AND (4)” OR “(1) AND (5)”
Direct keyword search:
9. “indoor air pollution”
10. “cooking fuel”
12. “(7) AND (8)” OR “(7) AND (9)” OR “(7) AND (10)” OR “(7) AND (11)”
13. (6) OR (12)
Data Extraction and Quality Assessment
For every eligible study, we collected detailed information on year and country of study, study design, study population, sample size, choice of controls, definition and measurement of tobacco smoking or IAP, type of TB outcome, confounders adjusted for, effect sizes and 95% confidence intervals (CIs), and dose-response relationships. Since TB disease and death are relatively rare events, even in high-incidence areas, we assumed that odds ratios (ORs), risk ratios, and rate ratios all provided an equivalent estimate of risk and therefore reported them as ORs . Although latent TB infection is not a rare event, each of the studies of latent TB infection estimated ORs and we therefore reported ORs for this outcome as well. Data were extracted independently by two of the investigators (HL and MM), and differences were resolved by discussion with a third (ME).
We performed separate analyses for each exposure-outcome association that had been studied. Within each subanalysis we further stratified on different study designs. When more than one study used a specific study design, we assessed heterogeneity using the I2 statistic described by Higgins et al. . Because of the significant heterogeneity and different study designs within subgroups, we did not compute pooled effect measures . Instead, we graphically presented each of the weighted point estimates and 95% CIs of effect estimates for individ