Geographic Variation of Amyotrophic Lateral Sclerosis Incidence in New Jersey, 2009–2011

American Journal of Epidemiology © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact Vol. 182, No. 6 DOI: 10.1093/aje/kwv095 Advance Access publication: June 3, 2015 Original Contribution Geographic Variation of Amyotrophic Lateral Sclerosis Incidence in New Jersey, 2009–2011 Kevin A. Henry*, Jerald Fagliano, Heather M. Jordan, Lindsay Rechtman, and Wendy E. Kaye * Correspondence to Dr. Kevin A. Henry, Department of Geography and Urban Studies, College of Liberal Arts, Temple University, Gladfelter Hall, Room 313b, Philadelphia, PA 19122 (e-mail: ). Few analyses in the United States have examined geographic variation and socioeconomic disparities in amyotrophic lateral sclerosis (ALS) incidence, because of lack of population-based incidence data. In this analysis, we used population-based ALS data to identify whether ALS incidence clusters geographically and to determine whether ALS risk varies by area-based socioeconomic status (SES). This study included 493 incident ALS cases diagnosed (via El Escorial criteria) in New Jersey between 2009 and 2011. Geographic variation and clustering of ALS incidence was assessed using a spatial scan statistic and Bayesian geoadditive models. Poisson regression was used to estimate the associations between ALS risk and SES based on census-tract median income while controlling for age, sex, and race. ALS incidence varied across and within counties, but there were no statistically significant geographic clusters. SES was associated with ALS incidence. After adjustment for age, sex, and race, the relative risk of ALS was significantly higher (relative risk (RR) = 1.37, 95% confidence interval (CI): 1.02, 1.82) in the highest income quartile than in the lowest. The relative risk of ALS was significantly lower among blacks (RR = 0.57, 95% CI: 0.39, 0.83) and Asians (RR = 0.63, 95% CI: 0.41, 0.97) than among whites. Our findings suggest that ALS incidence in New Jersey appears to be associated with SES and race. amyotrophic lateral sclerosis; disease mapping; spatial analysis Abbreviations: ALS, amyotrophic lateral sclerosis; CI, confidence interval; SES, socioeconomic status. 75 years of age (12, 13). Men have higher incidence rates of ALS than women (13, 14), and data suggest a lower incidence of ALS in nonwhites and Hispanics compared with whites and non-Hispanics, respectively (15–17). Geographic areas with higher localized incidence rates of ALS (e.g., geographic clustering) have been reported in specific regions worldwide. The most notable examples include a higher incidence of the Western Pacific form of ALS in the 1950s on the island of Guam (18), on the Kii Peninsula in Japan (19), and in southwestern New Guinea (20). Motivated by investigations into potential environmental causes of ALS in the Western Pacific and other recent reports of localized clusters of ALS elsewhere in the world (21–30), researchers are increasingly using spatial analysis methods to map geographic variations in ALS incidence and to identify localized clusters of ALS (31). The main goal of these types of investigations has been to locate geographic clusters of Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig’s disease, is a rare and fatal neurological disease characterized by a progressive loss of motor neurons in the brain and spinal cord. Currently the cause of ALS is unknown; however, a small proportion of cases are familial (1). The remainder of the cases, accounting for 90%–95% of all observed cases worldwide, are referred to as sporadic ALS. Numerous possible risk factors for sporadic ALS have been studied, including environmental exposures (2–4), occupational exposures (4–6), physical activity and trauma (7), oxidative stress (8), nutritional intake (9), and smoking (10, 11), but results from these studies have thus far been inconsistent and inconclusive. Reported crude incidence rates of ALS worldwide currently range from 0.3 cases per 100,000 population to 3.6 cases per 100,000 (12). The incidence of ALS increases with age, with the majority of cases being diagnosed at 55– 512 Am J Epidemiol. 2015;182(6):512–519 Initially submitted January 28, 2015; accepted for publication April 3, 2015. Amyotrophic Lateral Sclerosis in New Jersey 513 METHODS Study population The case data included 493 New Jersey residents diagnosed with ALS from 2009 to 2011 that met the El Escorial criteria (41). Details about ALS case ascertainment in New Jersey and data collection efforts have been previously described (13). Information about patient demographic characteristics, including date of birth, sex, race, and ethnicity, was available. Race was classified into white, black/AfricanAmerican, Asian, and unknown/other. Ethnicity was classified into Hispanic, non-Hispanic, and unknown. Geocoding, area socioeconomic measures, and population data For each ALS case, the patient’s address as provided by the reporting neurologist was geocoded using both ArcGIS 10.1 software (ESRI, Redlands, California) and Google Earth software, version 7.1 (Google Inc., Mountain View, California). ArcGIS successfully geocoded the full addresses of 425 of the 493 cases with a perfect match score, and the remaining 68 addresses were manually geocoded using Google Earth. In total, 5 of the 493 addresses could not be geocoded based on the full address. All geocoded cases were assigned a 2010 census tract, and the remaining cases not geocoded (n = 5) were assigned a census tract based on their zip code using Am J Epidemiol. 2015;182(6):512–519 geographic imputation methods described previously by Henry and Boscoe (42). Census-tract median annual household income was used as the area-based SES measure (43) and was categorized into quartiles (1 = lowest, 4 = highest) on the basis of the statewide distribution among census tracts. A quartile value was assigned to each ALS case based on its census tract. For this analysis, census-tract median income was conceptualized as an area- or neighborhood-based socioeconomic measure. Areabased SES measures describe the neighborhood context in which an individual lives and could affect health through several pathways, including the physical conditions of the neighborhood (e.g., pollution levels), the material resources of the neighborhood (e.g., availability of healthy, affordable food options), and social capital and social networks (e.g., social contagion, similar norms of behavior) (32, 33, 44). Population counts by age, sex, race, and ethnicity for census tracts used in subsequent analyses were obtained from the 2010 US Census (Summary F (...truncated)