Lo et al. in compounds of villagers who were actively participating in gold ore processing. We did not give first priority to sick children in ore- processing compounds because we did not want to oversample children with malaria and other infectious diseases that are endemic in the area. If no villagers actively participated in gold ore processing, the team first requested blood sampling from sick children, prefer- entially children with a history of convul- sions. Finally, if no children met these criteria after repeat inquiries to the villagers, the team then requested blood samples from any five children ages 2 months to 5 years. Teams obtained informed consent from a child’s par- ents before drawing blood. Product lots of all blood collection supplies used in this investigation were prescreened for lead contamination by CDC laboratories. Blood collection supplies were stored in plas- tic gallon-size bags before blood collection to prevent lead contamination in the field. Venipuncture sites were thoroughly cleaned with alcohol wipes, and trained team members collected 1–3 mL of venous blood from each child in a tube containing ethylenediamine tetraacetic acid. Blood samples were analyzed within 8–72 hr of collection at the Blood Lead and Inorganic Metals Laboratory in Gusau, Zamfara, using a portable blood lead ana- lyzer, LeadCare II® (Magellan Biosciences, Chelmsford, MA, USA), which can quantify BLLs registering 3.3–65 µg/dL with an average N bias from reference of 4.7–5.0% (Freeney and Zink 2007). Environmental specimen collection and analysis. Teams collected two types of envi- ronmental samples for lead testing. In each compound where a child’s blood was sampled, household dust samples were collected from piles created by sweeping or scooping loose floor dust, preferentially from areas where children ate or slept. In each village, surface soil was collected from at least one public area. To increase the chance of identifying lead con- tamination, the team preferentially sampled soil from public areas near a large centrally located shade tree, a typical location for break- ing rocks (an early ore-processing activity), or near accessible water sites that might have been used for washing ore. Among villages that reported having processed ore, the team identified ore-processing sites by conducting a walk-through visual assessment and interview- ing villagers who were familiar with the ore- processing practices of the village. The team collected surface soil samples from as many as five ore-processing locations, with priority given to grinding, washing, and drying sites because these activities are most likely to gen- erate dust or waste and contaminate the soil (Dooyema et al. 2012). All soil and household dust samples were placed in separate, clean, zipped plas- tic bags and later analyzed at the Blood Lead and Inorganic Metals Laboratory in Gusau, 0 Kebbi State 40 Kilometers Bukkuyum LGA Anka LGA 80 Niger State Maru LGA Maru LGA Kaduna State Zamfara, for lead levels using a portable, hand-held X-ray fluorescence spectrometer (NITON® XL3; Thermo Fisher Scientific, Billerica, MA, USA). The minimum detec- tion limit for lead in the soil and dust samples ranged from 15 to 20 ppm. Consistent with U.S. EPA guidelines on initial assessment of lead-contaminated residential properties, the team categorized soil and dust lead levels using 400 ppm and 1,200 ppm as thresholds to pri- oritize response actions (U.S. EPA 2003). Outcome and exposure variables. Village- level outcome variables were examined as follows: ≥ 1 child < 5 years of age who had convulsions during the previous 12 months; ≥ 1 child < 5 years of age who had convul- sions and died during the previous 12 months; ≥ 1 child < 5 years of age with a BLL ≥ 10 µg/dL; ≥ 1 child < 5 years of age with a BLL ≥ 45 µg/dL; ≥ 1 soil/dust sample with a lead level > 400 ppm; and ≥ 1 soil/dust sample with a lead level > 1,200 ppm. A village with childhood lead poisoning was defined as a vil- lage with ≥ 1 child with a BLL ≥ 10 µg/dL. A village with lead contamination was defined as a village with ≥ 1 soil/dust sample with a lead level > 400 ppm. Villages that reported partici- pation in any gold ore–processing activity dur- ing the previous 12 months were classified as ore-processing villages. Villages that reported no participation in gold ore–processing activ- ity during the previous 12 months were classi- fied as non-ore-processing villages. Statistical analysis. Variables were analyzed using SAS version 9.2® (SAS Institute Inc., Cary, NC, USA). Medians and ranges were calculated for population estimates with skewed distributions. The village was the unit of analy- sis, rather than the children or soil samples. We conducted bivariate analyses using chi-square analysis or Fisher’s exact test to compare cat- egorical outcome variables at the village level between ore-processing villages and non-ore- processing villages, and estimated unadjusted odds ratios (OR) and 95% confidence intervals (CI). All comparisons were two-tailed, and a p-value < 0.05 was considered statistically significant. Results We identified 131 villages of interest located in 10 of the 14 LGAs in Zamfara State. Because of time and logistic constraints, the team focused on the 114 (87%) villages of interest located within three LGAs: Anka, Bukkuyum, and Maru. All three LGAs are located in the southwestern region of Zamfara State and are bordered by Kebbi, Niger, and Kaduna States (Figure 1). During 15 October–18 November 2010, we visited 74 of 114 (65%) villages of interest, including 32 of 50 (64%) vil- lages of interest in Anka LGA, 4 of 9 (44%) villages of interest in Bukkuyum LGA, and Figure 1. Map of Zamfara state by administrative boundaries of Local Government Areas (LGA), highlight- ing Anka, Bukkuyum, and Maru LGAs and their neighboring states. The jurisdiction of Maru LGA comprises discrete northern and southern areas. 1452 ovlume 120 | number 10 | October 2012 • Environmental Health Perspectives