Dataset Information

Individual- and neighborhood-level contextual factors are associated with Mycobacterium tuberculosis transmission: genotypic clustering of cases in Michigan, 2004-2012.

ABSTRACT:

Purpose

Using genotyping data of Mycobacterium tuberculosis isolates from new cases reported to the tuberculosis (TB) surveillance program, we evaluated risk factors for recent TB transmission at both the individual- and neighborhood- levels among U.S.-born and foreign-born populations.

Methods

TB cases (N = 1236) reported in Michigan during 2004 to 2012 were analyzed using multivariable Poisson regression models to examine risk factors for recent transmission cross-sectionally for U.S.-born and foreign-born populations separately. Recent transmission was defined based on spoligotype and 12-locus-mycobacterial interspersed repetitive unit-variable number tandem repeat typing matches of bacteria from cases that were diagnosed within 1 year of each other. Four classes of predictor variables were examined: demographic factors, known TB risk factors, clinical characteristics, and neighborhood-level factors.

Results

Overall, 22% of the foreign-born cases resulted from recent transmission. Among the foreign-born, race and being a contact of an infectious TB case were significant predictors of recent transmission. More than half (52%) of U.S.-born cases resulted from recent transmission. Among the U.S.-born, recent transmission was predicted by both individual- and neighborhood-level sociodemographic characteristics.

Conclusions

Interventions aimed at reducing TB incidence among foreign-born should focus on reducing reactivation of latent infection. However, reducing TB incidence among the U.S.-born will require decreasing transmission among socially disadvantaged groups at the individual- and neighborhood- levels. This report fills an important knowledge gap regarding the contemporary social context of TB in the United States, thereby providing a foundation for future studies of public health policies that can lead to the development of more targeted, effective TB control.

SUBMITTER: Noppert GA

PROVIDER: S-EPMC5583706 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Individual- and neighborhood-level contextual factors are associated with Mycobacterium tuberculosis transmission: genotypic clustering of cases in Michigan, 2004-2012.

Noppert Grace A GA Yang Zhenhua Z Clarke Philippa P Ye Wen W Davidson Peter P Wilson Mark L ML

Annals of epidemiology 20170515 6

<h4>Purpose</h4>Using genotyping data of Mycobacterium tuberculosis isolates from new cases reported to the tuberculosis (TB) surveillance program, we evaluated risk factors for recent TB transmission at both the individual- and neighborhood- levels among U.S.-born and foreign-born populations.<h4>Methods</h4>TB cases (N = 1236) reported in Michigan during 2004 to 2012 were analyzed using multivariable Poisson regression models to examine risk factors for recent transmission cross-sectionally fo ...[more]

PMID: 28571914

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Project description:BackgroundThe incidence of TB in Michigan was 1.5 per 100,000 people in 2012, roughly half the U.S. incidence. Despite successes in TB control, disparities in TB still exist in Michigan, particularly by race, age, and nativity. A major challenge in understanding disparities in TB burden is distinguishing between TB cases resulting from recent transmission and those resulting from reactivation of latent TB infection, information critical to tailoring control strategies. We examined nine-year trends in tuberculosis (TB) incidence patterns for the entire population of Michigan, and within demographic subgroups.MethodsUsing a cross-sectional study of TB surveillance data, we analyzed 1254 TB cases reported in Michigan during 2004-2012. Cases included were those for whom both spoligotyping and 12-locus-MIRU-VNTR results were available. Using a combination of the genotyping information and time of diagnosis, we then classified cases as resulting from either recent transmission or reactivation of latent TB infection. We used multivariable negative binomial regression models to study trends in the TB incidence rate for the entire population and by race, nativity, gender, and age.ResultsOverall, the incidence rate of TB declined by an average of 8% per year-11% among recently transmitted cases, and 9% among reactivation cases. For recently transmitted disease, Blacks had an average incidence rate 25 times greater than Whites, after controlling for nativity, gender, and age. For disease resulting from latent TB infection Asians had an average incidence rate 24 times greater than Whites, after controlling for nativity, gender, and age.ConclusionsDisparities in incidence persist despite ongoing TB control efforts. Greater disparities were observed by race and nativity demonstrating some of the ways that TB incidence is socially patterned. Reducing these disparities will require a multi-faceted approach encompassing the social and environmental contexts of high-risk populations.

Project description:Tuberculosis disease (TB), caused by Mycobacterium tuberculosis, is a major global public health problem, resulting in more than 1 million deaths each year. Drug resistance (DR), including multi-drug (MDR-TB), is making TB control difficult and accounts for 16% of new and 48% of previously treated cases. To further complicate treatment decision-making, many clinical studies have reported patients harbouring multiple distinct strains of M. tuberculosis across the main lineages (L1 to L4). The extent to which drug-resistant strains can be deconvoluted within mixed strain infection samples is understudied. Here, we analysed M. tuberculosis isolates with whole genome sequencing data (n = 50,723), which covered the main lineages (L1 9.1%, L2 27.6%, L3 11.8%, L4 48.3%), with genotypic resistance to isoniazid (HR-TB; n = 9546 (29.2%)), rifampicin (RR-TB; n = 7974 (24.4%)), and at least MDR-TB (n = 5385 (16.5%)). TB-Profiler software revealed 531 (1.0%) isolates with potential mixed sub-lineage infections, including some with DR mutations (RR-TB 21/531; HR-TB 59/531; at least MDR-TB 173/531). To assist with the deconvolution of such mixtures, we adopted and evaluated a statistical Gaussian Mixture model (GMM) approach. By simulating 240 artificial mixtures of different ratios from empirical data across L1 to L4, a GMM approach was able to accurately estimate the DR profile of each lineage, with a low error rate for the estimated mixing proportions (mean squared error 0.012) and high accuracy for the DR predictions (93.5%). Application of the GMM model to the clinical mixtures (n = 531), found that 33.3% (188/531) of samples consisted of DR and sensitive lineages, 20.2% (114/531) consisted of lineages with only DR mutations, and 40.6% (229/531) consisted of lineages with genotypic pan-susceptibility. Overall, our work demonstrates the utility of combined whole genome sequencing data and GMM statistical analysis approaches for providing insights into mono and mixed M. tuberculosis infections, thereby potentially assisting diagnosis, treatment decision-making, drug resistance and transmission mapping for infection control.

Project description:Background: While obesity is well-understood to increase breast cancer risk, the role of the neighborhood obesogenic environment, encompassing social and built environment attributes that influence body size, is poorly understood.Methods: Using principal components factor analysis, five composite factors [neighborhood socioeconomic status (nSES), urban, mixed-land development, unhealthy food environment, parks] on the basis of geospatial data were developed to characterize the obesogenic environment for 48,247 postmenopausal women in the Multiethnic Cohort, residing predominately in Los Angeles County. We used Cox proportional hazards regression to examine the association between neighborhood obesogenic factors and breast cancer risk (n = 2,341 cases after 17 years of follow-up), adjusting for body mass index (BMI), weight gain since age 21, education, established risk factors, other neighborhood factors, and clustering by block group.Results: Lower nSES was associated with lower breast cancer risk [quintile 1 vs. 5: HR, 0.79; 95% confidence interval (CI), 0.66-0.95], with a more pronounced association observed in Latinos (quintile 1 vs. 5: HR, 0.60; 95% CI, 0.43-0.85). More urban environments were associated with lower breast cancer risk in Japanese Americans (quintile 5 vs. 1: HR, 0.49; 95% CI, 0.26-0.90), and lower mixed-land development was associated with higher breast cancer risk in Latinos (quintile 1 vs. 5: HR, 1.46; 95% CI, 1.10-1.93).Conclusions: Obesogenic neighborhood environment factors, especially nSES, urbanicity, and mixed-land development, were differentially and independently associated with breast cancer risk in this multiethnic population.Impact: These findings highlight the need for additional studies of the driving contextual aspects of nSES that influence breast cancer risk. Cancer Epidemiol Biomarkers Prev; 26(4); 480-9. ©2017 AACRSee all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences."

Dataset Information

Individual- and neighborhood-level contextual factors are associated with Mycobacterium tuberculosis transmission: genotypic clustering of cases in Michigan, 2004-2012.

Purpose

Methods

Results

Conclusions

Publications

Individual- and neighborhood-level contextual factors are associated with Mycobacterium tuberculosis transmission: genotypic clustering of cases in Michigan, 2004-2012.

Similar Datasets

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