RATIONALE: Prevalence of pulmonary nontuberculous mycobacterial (PNTM) disease varies by geographic region, yet the factors driving these differences remain largely unknown. OBJECTIVES: To identify spatial clusters of PNTM disease at the county level and to describe environmental and sociodemographic factors predictive of disease. METHODS: PNTM cases identified from a nationally representative sample of Medicare Part B beneficiaries from 1997 to 2007 were geocoded by county and state of residence. County-level PNTM case counts and Medicare population data were then uploaded into SaTScan to identify significant spatial clusters and low-risk areas of disease. High-risk and low-risk counties were then compared to identify significant sociodemographic and environmental differences. MEASUREMENTS AND MAIN RESULTS: We identified seven significant (P < 0.05) clusters of PNTM cases. These high-risk areas encompassed 55 counties in 8 states, including parts of California, Florida, Hawaii, Louisiana, New York, Oklahoma, Pennsylvania, and Wisconsin. Five low-risk areas were also identified, which encompassed 746 counties in 23 states, mostly in the Midwest. Counties in high-risk areas were significantly larger, had greater population densities, and higher education and income levels than low-risk counties. High-risk counties also had higher mean daily potential evapotranspiration levels and percentages covered by surface water, and were more likely to have greater copper and sodium levels in the soil, although lower manganese levels. CONCLUSIONS: Specific environmental factors related to soil and water exposure appear to increase the risk of PNTM infection. Still, given that environmental sources of NTM are ubiquitous and PNTM disease is rare, both host susceptibility and environmental factors must be considered in explaining disease development.
RATIONALE: Prevalence of pulmonary nontuberculous mycobacterial (PNTM) disease varies by geographic region, yet the factors driving these differences remain largely unknown. OBJECTIVES: To identify spatial clusters of PNTM disease at the county level and to describe environmental and sociodemographic factors predictive of disease. METHODS: PNTM cases identified from a nationally representative sample of Medicare Part B beneficiaries from 1997 to 2007 were geocoded by county and state of residence. County-level PNTM case counts and Medicare population data were then uploaded into SaTScan to identify significant spatial clusters and low-risk areas of disease. High-risk and low-risk counties were then compared to identify significant sociodemographic and environmental differences. MEASUREMENTS AND MAIN RESULTS: We identified seven significant (P < 0.05) clusters of PNTM cases. These high-risk areas encompassed 55 counties in 8 states, including parts of California, Florida, Hawaii, Louisiana, New York, Oklahoma, Pennsylvania, and Wisconsin. Five low-risk areas were also identified, which encompassed 746 counties in 23 states, mostly in the Midwest. Counties in high-risk areas were significantly larger, had greater population densities, and higher education and income levels than low-risk counties. High-risk counties also had higher mean daily potential evapotranspiration levels and percentages covered by surface water, and were more likely to have greater copper and sodium levels in the soil, although lower manganese levels. CONCLUSIONS: Specific environmental factors related to soil and water exposure appear to increase the risk of PNTM infection. Still, given that environmental sources of NTM are ubiquitous and PNTM disease is rare, both host susceptibility and environmental factors must be considered in explaining disease development.
Authors: D Rebecca Prevots; Pamela A Shaw; Daniel Strickland; Lisa A Jackson; Marsha A Raebel; Mary Ann Blosky; Ruben Montes de Oca; Yvonne R Shea; Amy E Seitz; Steven M Holland; Kenneth N Olivier Journal: Am J Respir Crit Care Med Date: 2010-06-10 Impact factor: 21.405
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Authors: Eva P Szymanski; Janice M Leung; Cedar J Fowler; Carissa Haney; Amy P Hsu; Fei Chen; Priya Duggal; Andrew J Oler; Ryan McCormack; Eckhard Podack; Rebecca A Drummond; Michail S Lionakis; Sarah K Browne; D Rebecca Prevots; Michael Knowles; Gary Cutting; Xinyue Liu; Scott E Devine; Claire M Fraser; Hervé Tettelin; Kenneth N Olivier; Steven M Holland Journal: Am J Respir Crit Care Med Date: 2015-09-01 Impact factor: 21.405