Liu et al. to NYSDOH the primary diagnosis, and up to 14 other diagnoses, based on the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM; National Center for Health Statistics 2006). In this study, we selected hospital discharge data that had diag- nosis of a) asthma (ICD-9-CM code 493), b) acute respiratory infection (ARI; ICD-9-CM codes 460–466), and/or c) chronic obstructive pulmonary disease (COPD; ICD-9-CM codes 490–492 and 494–496) as either the primary or secondary diagnosis. in all of New York State except for New York City. Preliminary analyses of hospitalization rates associated with residence in a ZIP code with a power plant classified according to the type of fuel used as an energy source (coal, oil, natural gas, landfill gas, and/or solid waste) did not indicate clear or consistent patterns [see Supplemental Material, Table S1 (http:// dx.doi.org/10.1289/ehp.1104146)]. Therefore, we classified patients as exposed if they resided in a ZIP code with at least one fuel-fired power plant, regardless of the fuel used, at the time of The SPARCS data used included patient hospitalization. age, sex, race/ethnicity, and ZIP code of cur- rent residence. New York City was excluded from this analysis because it maintains its own hospitalization listing, which is separate from that maintained by NYSDOH. New York City also differs significantly in population density and composition and in social and economic status. There are approximately 2.5 million hospitalizations per year in New York State other than in New York City. This and other studies using the SPARCS data set have been reviewed by the institu- tional review board of the University at Albany and declared to be exempt because the data set does not include any unique identifiers. Demographic data. Our unit of anal- ysis was subpopulations within ZIP codes. Demographic data on New York State resi- dents [age, sex, race/ethnicity, median house- hold income (MHI), and population density for each ZIP code in New York State] was obtained from CLARITAS Inc. (http://www. claritas.com/sitereports/), a resource company that provides information derived from the 1990 and 2000 U.S. Census (Huang et al. 2006). In addition to excluding ZIP codes for New York City, we excluded 281 ZIP codes that included post boxes only or that had changed during 1993–2008, leaving 1,403 ZIP codes for analysis. We estimated person-years based on the number of residents in each eligible ZIP code during each year for 1993–2008. The analysis was restricted to Caucasians (white) and African Americans (black) because these groups account for > 95% of total hospital- izations. Age was divided into eight groups (0, 1–2, 3–5, 6–9, 10–24, 25–49, 50–74, and ≥ 75 years) or dichotomized as < 10 or ≥ 10 years. To control for population density, ZIP codes with ≥ 1,000 persons/mi2 were classified as urban, and those with < 1,000 persons/mi2 were classified as rural. Exposure assessment. We obtained a list of existing, operating power plants and electric generators in New York State for the years 1990–2008, including information on loca- tion, energy source, and operating period, from the U.S. Energy Information Administration (2010). Using this information, we identified ZIP codes that contained fuel-fired generators 808 Previous studies reported elevated rates of hospitalization for asthma and infectious respi- ratory diseases among people living near con- taminated waste sites (Carpenter et al. 2008; Ma et al. 2007). To mitigate confounding and identify interactions, we classified ZIP codes into four mutually exclusive groups: “fuel-only” ZIP codes contained one or more generators using coal, oil, natural gas, landfill gas, or solid waste as an energy source during the period of 1990–2008 but did not con- tain a hazardous waste site (n = 38); “waste- only” ZIP codes did not contain a fuel-fired power plant but did have a National Priority List site or state Superfund site, including ZIP codes that abutted bodies of water known to be contaminated with persistent organic pollutants (the lower Hudson River and six “areas of concern”; n = 347) (Carpenter et al. 2001); “fuel-and-waste” ZIP codes contained fuel-fired power plant(s) and hazardous waste site(s) (n = 84); and the remaining “clean” ZIP codes did not contain a fuel-fired power plant or a hazardous waste site (n = 934). Although hospitalization rates for the different diseases have changed over time (with asthma and Table 1. Demographic characteristics and hospitalizations of the studied population [n (%)]. Asthma Hospitalizations Characteristic Person-yearsa ARI Total population 164,289,936 (100.0) 911,444 (100.0) 331,469 (100.0) 1,948,903 (100.0) Exposure Clean 65,271,804 (39.7) 320,693 (35.2) 118,239 (35.7) 692,247 (35.5) Fuel only 4,529,951 (2.8) 24,765 (2.7) 8,466 (2.6) 55,126 (2.8) Waste only 69,479,535 (42.3) 403,334 (44.3) 144,613 (43.6) 848,798 (43.6) Fuel and waste 25,008,646 (15.2) 162,652 (17.8) 60,151 (18.1) 352,732 (18.1) Sex Female 84,417,102 (51.4) 600,327 (65.9) 179,061 (54.0) 995,977 (51.1) Male 79,872,834 (48.6) 311,117 (34.1) 152,408 (46.0) 952,926 (48.9) Race African American 14,339,797 (8.7) 162,482 (17.8) 45,357 (13.7) 100,906 (5.2) Caucasian 149,950,139 (91.3) 748,962 (82.2) 286,112 (86.3) 1,847,997 (94.8) Age group (years) 0 2,057,008 (1.3) 13,340 (1.5) 55,502 (16.7) 446 (0.0) 1–2 4,263,638 (2.6) 31,052 (3.4) 26,302 (7.9) 520 (0.0) 3–5 6,456,134 (3.9) 25,724 (2.8) 10,505 (3.2) 392 (0.0) 6–9 8,747,610 (5.3) 20,657 (2.3) 5,989 (1.8) 349 (0.0) 10–24 33,073,852 (20.1) 96,648 (10.6) 24,247 (7.3) 4,447 (0.2) 25–49 58,830,783 (35.8) 297,430 (32.6) 62,607 (18.9) 98,675 (5.1) 50–74 39,683,599 (24.2) 290,371 (31.9) 74,766 (22.6) 928,603 (47.6) ≥ 75 11,177,312 (6.8) 136,222 (14.9) 71,551 (21.6) 915,471 (47.0) aPerson-years determined by the numbers of residents in the study ZIP codes during each year (1993–2008) according to characteristic. COPD ovlume 120 | number 6 | June 2012 • Environmental Health Perspectives COPD tending to increase, and ARIs tending to decrease), trends did not appear to differ by exposure status [see Supplemental Material, Figure S1 (http://dx.doi.org/10.1289/ ehp.1104146)]. Therefore, we did not consider year-by-year data in this study. We used MHI as a proxy measure of socioeconomic status (SES), another poten- tial confounder in our study. Although there were no significant differences in mean MHI among the four classes of ZIP codes, their dis- tributions varied [See Supplemental Material, Figure S2 (http://dx.doi.org/10.1289/ ehp.1104146)]. In addition, preliminary analyses indicated substantial differences in crude hospitalization rates for ZIP codes with very high or very low MHI [See Supplemental Material, Table S2 (http://dx.doi.org/10.1289/ ehp.1104146)]. Therefore, we restricted the analysis to ZIP codes with year 2000 MHI ranging from $23,057.4 (the 5th percentile of MHI) to $71,506.6 (the 95th percentile of MHI), leaving 841 clean, 32 fuel-only, 301 waste-only, and 78 fuel-and-waste ZIP codes for analysis (total n = 1,252). MHI in the remaining ZIP codes was cat- egorized into quartiles: $23,057.4–31,069.3, $31,069.3–36,179.9, $36,179.9–44,204.4, and $44,204.4–71,506.6. Statistical analysis. We calculated hospi- talization rates per 100,000 person-years as the number of discharge diagnoses for each out- come of interest divided by the total person- years for the population residing in each ZIP code category for the years 1993–2008. Rate ratios (RRs) of hospitalization and their 95% CIs were calculated for fuel-only, waste-only, and fuel-and-waste ZIP codes, with clean ZIP codes as the common referent exposure group.