Elevated blood lead levels in adults-Missouri, 2013.

BACKGROUND: Over 90% of adults with elevated blood lead levels (BLLs) in the United States are exposed occupationally. Missouri historically has been among the states with the highest prevalence rates of elevated BLLs. We characterized cases of elevated BLLs among Missouri adults to target preventive interventions. METHODS: We reviewed 2013 data on Missouri residents ≥16 years from the Missouri Adult Blood Lead Epidemiology and Surveillance system and analyzed characteristics of those with elevated BLLs. We used the contemporaneous CDC definition of elevated BLL as ≥10 µg/dL. RESULTS: Of the 15 123 residents with a BLL in 2013 (median: 1.5 µg/dL, range: 0-151 µg/dL), 3145 (21%) had BLLs ≥10 µg/dL. Occupational exposures accounted for the majority of residents (n = 3099, 98%) with elevated BLLs, mostly in battery manufacturing (n = 1373, 44%) and lead mining (n = 821, 26%) industries. CONCLUSIONS: Our findings highlight the need for focused interventions targeting battery manufacturing and lead mining, the high-risk industries, to further reduce overexposures to lead.

Evaluation of a Novel Syndromic Surveillance Query for Heat-Related Illness Using Hospital Data From Maricopa County, Arizona, 2015.

OBJECTIVES: We evaluated a novel syndromic surveillance query, developed by the Council of State and Territorial Epidemiologists (CSTE) Heat Syndrome Workgroup, for identifying heat-related illness cases in near real time, using emergency department and inpatient hospital data from Maricopa County, Arizona, in 2015. METHODS: The Maricopa County Department of Public Health applied 2 queries for heat-related illness to area hospital data transmitted to the National Syndromic Surveillance Program BioSense Platform: the BioSense "heat, excessive" query and the novel CSTE query. We reviewed the line lists generated by each query and used the diagnosis code and chief complaint text fields to find probable cases of heat-related illness. For each query, we calculated positive predictive values (PPVs) for heat-related illness. RESULTS: The CSTE query identified 674 records, of which 591 were categorized as probable heat-related illness, demonstrating a PPV of 88% for heat-related illness. The BioSense query identified 791 patient records, of which 589 were probable heat-related illness, demonstrating a PPV of 74% for heat-related illness. The PPV was substantially higher for the CSTE novel and BioSense queries during the heat season (May 1 to September 30; 92% and 85%, respectively) than during the cooler seasons (55% and 29%, respectively). CONCLUSION: A novel query for heat-related illness that combined diagnosis codes, chief complaint text terms, and exclusion criteria had a high PPV for heat-related illness, particularly during the heat season. Public health departments can use this query to meet local needs; however, use of this novel query to substantially improve public health heat-related illness prevention remains to be seen.