Demographic and mortality data were obtained from the Office of the Chief Medical Examiner of New York City (OCME), which is responsible for determining the cause of death for all individuals believed to have died from nonnatural causes in New York City. Through a manual review of OCME medical files, we identified all cases of non–overdose-related fatal accidents (classified under International Classification of Diseases, 10th Revision [ICD-10]⁶¹ codes V01–X39, X45–X59, and Y85–Y86) and unintentional poisoning deaths (ICD-10 codes X40–X44 and T40.0–T40.2) involving adults aged 15 to 64 years in New York City during the period 2000 through 2006. Because of our focus on this short time period, it is likely that factors such as the OCME’s classification of cases and toxicology remained consistent over the study period.

Trained abstractors used a standardized protocol and data collection forms developed by the OCME to collect data on cause of death, circumstances of death, and toxicology from the OCME files. OCME investigators used the decedent’s medical history, the circumstances and environment of the death, autopsy findings, and laboratory data to attribute cause of death for each case reviewed. Hence, classification of cause of death differed from the simple presence or absence of a drug in a toxicological screen. Deaths involving positive screens for an analgesic will not necessarily be classified as analgesic-induced deaths. The OCME’s attributions of drugs as a cause of death are not mutually exclusive: an overdose death may be attributed to more than one drug. We included only cases in which unintentional poisoning by drugs was listed as the primary cause of death.

OCME files also included information on decedents’ age, gender, race/ethnicity, and place of residence. Information derived from medical examiner databases has shown high sensitivity, specificity, and positive predictive value with respect to identifying external causes of death.^62–64 Further details on collection of data on overdoses have been provided by Galea et al.⁶⁵

We conducted a pair of case–control analyses. In the first analysis, unintentional deaths in which poisoning caused by analgesic opioids was cited as a cause of death were identified as cases, and deaths from other nonoverdose unintentional causes were considered controls. Analgesic opioids included codeine, fentanyl, hydromorphone, hydrocodone, meperidine, morphine, orphenadrine, oxycodone, and propoxyphene. Nonoverdose unintentional deaths included those caused by firearms, drownings, falls, stabbings, poisonings, and other accidents.

In the second analysis, we compared deaths in which poisoning from analgesic opioids was cited as a cause of death and heroin poisoning was not cited as an additional cause with deaths in which poisoning from heroin was cited as a cause of death but analgesic opioid poisoning was not cited as an additional cause. Hence, overlapping cases of analgesic and heroin poisoning (representing 38.4% of analgesic overdose cases and 6.3% of heroin overdose controls) were excluded from this analysis.

Risk of death from analgesic opiate overdose was concentrated in certain neighborhoods of New York City. The Moran’s I statistic was 0.15 (P < .05), indicating moderate spatial clustering of analgesic overdose fatalities. Figure 1 presents a series of maps depicting the spatial distributions of analgesic overdose fatalities, median incomes, income inequality, family disruption, percentages of dilapidated housing structures, and percentages of acceptably clean sidewalks. The highest rates of analgesic fatalities occurred in neighborhoods in northern Manhattan (East Harlem), Queens (Rockaway–Broadway Channel), and the Bronx (Throgs Neck–Co-op City, Belmont–East Tremont, Hunts Point–Longwood); these neighborhoods are characterized by low median incomes, low-quality built environments, and high levels of family fragmentation.

The spatial correlations between income inequality and analgesic overdose (I = 0.17; P = .02), family fragmentation and analgesic overdose (I = 0.14; P = .04), and housing dilapidation and analgesic overdose (I = 0.18; P = .02) were moderate and significant. We did not find a spatial correlation between median income or sidewalk cleanliness and analgesic overdose fatalities.

Table 1 presents data on the demographic characteristics of analgesic overdose decedents relative to those of individuals whose unintentional deaths were not attributed to drug overdose. Analgesic overdose decedents were older and more likely to be White and female, and overdose fatalities were more likely to occur in neighborhoods with low concentrations of Black residents and high rates of opiate use.

Table 2 compares the demographic variables associated with nonoverlapping cases of analgesic and heroin overdose deaths. Analgesic overdose decedents were more likely to be White and female than heroin decedents, and analgesic overdose deaths were concentrated in neighborhoods with lower concentrations of Black residents, higher median incomes, higher proportions of clean sidewalks, and lower concentrations of dilapidated housing structures and family fragmentation.

Few differences emerged between analgesic overdoses and nonoverdose unintentional injuries with respect to neighborhood characteristics associated with the odds of death (Table 3). Controlling only for individual decedent characteristics, a higher median income was associated with lower odds of dying from an analgesic overdose than from a nonoverdose unintentional injury (OR = 0.83; 95% CI = 0.71, 0.97), whereas a higher level of family fragmentation was associated with a higher risk of death from analgesic overdose (OR = 1.30; 95% CI = 1.13, 1.50). The association between median income and analgesic overdose decreased in magnitude and became nonsignificant once we controlled for family fragmentation (Table 3, model 4). Income inequality and dilapidated housing were marginally and positively associated with analgesic overdose, whereas sidewalk cleanliness was marginally and negatively associated with overdose. However, these associations became null once we controlled for confounders (models 1–3).

Analgesic opiate and heroin overdose fatalities occurred in distinct types of neighborhoods (Table 4). After control for individual decedent characteristics, higher median incomes (OR = 1.40; 95% CI = 1.20, 1.65) and higher concentrations of clean sidewalks (OR = 1.48; 95% CI = 1.22, 1.79) were associated with higher odds of dying from an analgesic versus a heroin overdose. By contrast, higher levels of income inequality (OR = 0.74; 95% CI = 0.61, 0.91) and family fragmentation (OR = 0.65; 95% CI = 0.55, 0.78) were associated with lower odds of dying from an analgesic versus a heroin overdose. Income inequality and concentration of clean sidewalks became marginally significant once we adjusted for confounders (models 1 and 2). Median income became nonsignificant once we adjusted for family fragmentation.

Two key conclusions emerge from this study. First, neighborhood economic disadvantage is associated with higher odds of analgesic overdose fatalities than nonoverdose unintentional fatalities.^13,27 Neighborhood level of family fragmentation partially explained this association. Second, analgesic overdose fatalities occur in different neighborhoods than the neighborhoods where heroin overdose fatalities occur. Whereas analgesic overdose fatalities tend to occur in lower-income, more fragmented neighborhoods than nonoverdose unintentional fatalities, they typically occur in higher-income, less unequal, and less fragmented neighborhoods than heroin overdose fatalities.

The relationship observed between neighborhood income and analgesic drug overdose is consistent with the findings of previous studies on illicit drug overdose.^35,78,79 Lower-income neighborhoods may shape the risk of drug overdose through a variety of mechanisms, including disproportionate exposure of residents to psychosocial stress, eroded social trust and social capital, and limited access to health and social services.

The particular role of family disruption as a mechanism through which lower-income neighborhoods shape the risk of analgesic overdose^53–55 may be attributable to several factors. Neighborhoods where fragmented families are common may have lower levels of collective social control and oversight of delinquent activity, and thus a larger pool of one’s peers are involved in delinquent activities such as use of recreational analgesic opiates.⁵⁷ Larger drug-using networks are a documented risk factor for drug use.⁴⁰ Limited collective oversight may also provide the opportunity for the diversion and trafficking of analgesics obtained from legitimate prescription users.⁸⁰ Finally, socially disrupted contexts may inhibit residents from intervening or calling for help when witnessing an overdose.^15,44

Analgesic overdose fatalities occurred in different neighborhoods than overdose fatalities caused by heroin, the main type of illicit opiate. The concentration of analgesic overdoses in higher-income, less fragmented neighborhoods may be attributable to several factors. First, higher-income neighborhoods offer a formal supply of analgesics, through pharmacies and physicians, that is not present in highly disadvantaged, primarily minority neighborhoods where heroin may be the drug of choice. Indeed, several studies, including one conducted in New York City, have shown that pharmacies in disadvantaged, non-White neighborhoods do not have sufficient analgesic supplies to meet legitimate demand.^81–83

Second, a certain level of family cohesion may facilitate the informal diffusion of analgesics through friend and kinship networks. Several studies indicate that a key source of illicit analgesics is diversion of prescriptions legitimately filled by parents, relatives, friends, or acquaintances.^84–89

Third, neighborhoods with higher concentrations of legitimate analgesic users may have more favorable social norms supporting the use of analgesics. A key motivation for nonmedical analgesic drug use (rather than use of illicit drugs) seems to be the belief that such drugs are less stigmatizing, less dangerous, and less affected by legal consequences than illicit drugs.^41,84

Fourth, price may shape drug-specific patterns of demand across neighborhoods⁹⁰: the lower price of heroin relative to analgesics may create an economic disincentive to consume analgesics in lower-income neighborhoods. Future studies need to examine whether increased access to legal sources of analgesics, weak ties among potential providers (i.e., the elderly and patients with pain) and nonmedical consumers of analgesic opiates, and social norms supportive of nonmedical analgesic drug use contribute to the specific contextual risk of analgesic rather than illicit drug overdose.