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Vars buying Heroin

Official websites use. Share sensitive information only on official, secure websites. Address correspondence to Juliette Roddy, Ph. Weekly heroin purchasing frequency was positively related to income and number of suppliers, and negatively related to time cost min from primary supplier. Daily heroin consumption was positively related to income and injection heroin use, and negatively related to unit cost of heroin. Implications and limitations are noted. Simulations are underway to assess within-subject changes in drug demand. Funds State of Michigan. Heroin abuse 1 produces substantial costs at a macroeconomic level Healey et al. In the few extant studies, criminal behavior is often examined as an income generator Brown and Silverman, ; Silverman and Spruill, In an ethnographic study of Harlem heroin users not in treatment, Johnson et al. Because there are few detailed analyses of income-generating and -spending patterns in the literature, the present study examined specific economic behaviors among out-of-treatment heroin users. Evaluating the income and expense profile of heroin users who are not presently seeking treatment may be useful to assess which factors maintain drug use. Two Northern European studies Bretteville-Jensen and Sutton, ; Grapendaal, Leuw, and Nelen, have described the income-generating activity of out-of-treatment heroin users. Bretteville-Jensen also described gender differences in consumption and economic behavior among heroin users in a large urban Norwegian sample; females consumed heroin in larger amounts and more frequently than their male counterparts. However, other salient factors such as primary route of heroin administration, poly-substance use, duration of drug use, and income level may play a role in heroin purchasing and consumption. Empirical analysis of subgroup differences may help tailor treatment and policy approaches. The present study provides systematic and quantitative evidence on Detroit metropolitan area heroin consumption among out-of-treatment users, focusing on income-generating and -spending behaviors in this population. Semistructured interview methods were used to address three aims. First, we characterized the population according to the economic variables and compared it to two previous European samples Bretteville-Jensen and Sutton, ; Grapendaal et al. Second, we examined the relationship between economic variables and heroin purchasing and consumption. Third, we explored individual differences in economic behavior based on patterns of drug use. This investigation was part of a larger study approved by the local Investigational Review Board. Male and female volunteers, 18—55 years old, were recruited from the Detroit area by newspaper advertisements and word-of-mouth. Those identifying themselves as heroin-dependent were instructed to call for a telephone interview, which excluded individuals seeking drug abuse treatment. This study sample comprises volunteers who completed the first screening visit from February to July at a downtown Detroit outpatient clinical research program. This included written informed consent, providing demographic information, a complete medical and drug use history, and a semistructured interview lasting about 20—30 min that was designed to obtain specific information about factors influencing drug price, purchasing, and use. Participants were asked questions to ascertain past day income, heroin price, all drug and nondrug expenditures, and drug consumption. Before the interview, it was reemphasized that responses to all questions were confidential. The interview instrument is available upon request. Initial data analysis focused on describing characteristics of the participant sample. The means of most variables provided adequate representation of the group; however, medians and quartiles also yield insight. The data were first examined as a whole, then divided into groups based on injection noninjection heroin use and gender. Income was partitioned into percentages of total income for six a priori categories Figure 1. Multiple regression analyses were performed to determine which variables were significantly associated with purchasing and use of heroin. The independent variables listed in the leftmost column of Table 4 were used to predict dependent variables of bags consumed per day, number of bags purchased per week, percentage of income spent on heroin, and unit purchase amount. Cluster analysis was also conducted to identify subgroup differences in purchasing and consumption. This cohort was predominantly African-American, male and about 45 years old with a high school or equivalent education. Participants reported using heroin for about 20 years. Urinalysis results reflected poly-drug use with 45 participants testing positive for cocaine, 14 participants testing positive for marijuana, and 10 participants testing positive for benzodiazepines. Table 1 presents overall sample means, medians, and quartiles for selected responses. The sample mean was split based on current primary route of heroin use to assess differences between these subgroups. Of the respondents, 58 individuals reported they primarily injected heroin and 37 reported they did not inject. Primary route of heroin use was unavailable for five participants. Injection relative to noninjection heroin users reported significantly more time per episode purchasing heroin and consuming more bags of heroin per day. Chi-square analysis indicated that subject classification by route of administration was independent of gender. One participant believed her heroin had no additives. Although the response means represent the data reasonably well, a few notable differences between means and medians occurred in the heroin purchasing data. Figure 1 identifies sources and amounts of past-month income, and participation rates percent engaging in the behavior for the entire group. Injection and noninjection users did not significantly differ in mean income or participation in income-generating activities Table 1. The only significant gender difference involved employment income. To compare these income distribution data with two previous studies conducted in Oslo, Norway Bretteville-Jensen and Sutton, , and Amsterdam Grapendaal et al. Table 2 illustrates the income breakdown in the present study and the two other studies. The Oslo study was further compared to data from Scotland: however, the breakdowns included only males and a portion of those were institutionalized. Therefore, a comparison with the Scotland study does not seem prudent. The differences between the countries are noteworthy but generalizations are not warranted. Participants in the Oslo study may have been interviewed more than once and Norwegian policies regarding drug dealing and use vary dramatically from the United States. The Detroit sample appears to underrepresent the drug-dealing population. Bretteville-Jensen and Sutton Grapendaal et al. Eight males and no females reported income from selling drugs. Figure 2 reveals the common expense categories, the mean percentage of income devoted to each category, and the participation rate percent engaging in the behavior. Injection and noninjection heroin users did not significantly differ in their pattern of expenditures. The only significant gender difference was the percentage of income spent on alcohol, which—while accounting for a very small proportion—was 0. Females reported spending a higher percentage on shelter than males 6. Past-month spending distribution US dollars and participation percent of group for the aggregate sample. All other income categories were not significantly correlated with percentage of income spent on heroin. Regression analyses were conducted to predict four measures of heroin purchasing and consumption rightmost columns of Table 4. The independent variables were identical in each analysis left column of Table 4. Percentage of income spent on heroin and purchase of nonheroin opiates may be simultaneously determined, resulting in an endogeneity problem and erroneous estimates of coefficients. However, the regression coefficients change minimally nonsignificantly when nonheroin opiates are removed from the equation. Purchasing heroin more often was significantly predicted by three factors: a higher total monthly income, less time spent per purchase min , and more suppliers. Cluster analysis identified two subgroups Table 5. This study resulted in several primary findings. First, this Detroit-based sample of chronic heroin users reported habitual and efficient economic behaviors for obtaining income and expending this income primarily to obtain heroin. Second, the economic activity of this sample differed from that of two other non-US comparison samples. Third, this study found that total income was a significant and enabling predictor for purchasing and consuming opiates, but that other factors were differentially associated with purchasing versus consuming opiates. To the extent that participants can be described by group means they consumed 4. Owing to long individual histories of heroin use in this Detroit sample, projection of stated opiate consumption rates may be safe. However, such projections must be done with considerable caution. None of the survey questions asked for annual information. The interview was conducted in confidence with the participant, who was encouraged to provide accurate responses. While the researchers are reasonably certain in the accuracy of past-month responses, that certainty would be reduced considerably for extrapolations into the future. While characterizing the income-generating behavior of Detroit area heroin users it became evident that substantial differences existed between this group and other study samples. The difference in income generation activity may be secondary to the participant selection approach. The present Detroit area sample was recruited by word of mouth and through newspaper advertisements and required the participants to present at a research clinic. Furthermore, when systematically asked about motivations to participate in this type of laboratory research data to be reported elsewhere , the income earned from participation was ranked as the most important reason. It is possible that time away from dealing activity would produce an economic loss; therefore, dealers had minimal motivation to participate. However, the heroin users in this study are of particular interest due to their ability to earn legitimate income combined with their continued participation in criminal activity. Importantly, the two comparison studies involved only heroin injectors, whereas the present sample had a mixed composition of injecting and noninjecting users. To assess whether income differences between studies might be attributable to this factor, we separated Detroit income data according to primary route of heroin administration. However, there were few significant differences between the two Detroit groups. Only income from prostitution and lying significantly differed between the IV and non-IV users. An F test comparing demand regressions between IV and non-IV users led us to reject the null hypothesis and suggests there are differences among the demand determinants of distance to supplier, unit cost, purchase time, total income, and number of suppliers, but the test does not reveal which effects significantly differ across the two populations. One of the few gender differences in this Detroit sample involved income generation: females earned a significantly lower wage and significantly more income from prostitution than males. Bretteville-Jensen found that female addicts engage more in prostitution and less in criminal activity than their male counterparts. The fact that the female wage is lower than the male wage is certainly not unique to the opiate-using population; however, the wage differential in this population may have the additional detrimental effect of encouraging female participation in prostitution. Unstructured comments from these participants suggest that contributions of family and friends may be significantly underestimated in our survey due to food, clothing, and shelter subsidies that are provided but not recorded as income. One limitation of this study is that participants could not accurately estimate the amounts of food, clothing, and shelter subsidies despite our attempts , so we are unable to provide these data. Clearly, more income enables heroin users to purchase and consume more opiates. In fact, regression analyses showed that total past-month income significantly predicted both increased heroin purchasing frequency and daily consumption. However, past-month income did not significantly predict the percentage of income spent on heroin significantly and negatively correlated. In contrast, Petry found in a within-subject hypothetical simulation study that heroin consumption was income elastic, that is, a percentage increase in income brought about a larger percentage increase in heroin purchases. In the present study, income elasticity, measured at the sample mean of total past day income, was 0. The percentage change in quantity demanded of heroin for the past 30 days responded positively, but as a smaller percentage, to income. Again, this is inelastic. Cluster analysis of the present data revealed two subgroups that differ on both income and consumption. A minority of the present sample, who reported a higher mean income, purchased and consumed more bags per day of heroin while spending a smaller percentage of total income on heroin. The majority of the sample, who reported a lower mean income, purchased heroin less often and consumed fewer daily bags while spending a higher percentage of total income on heroin. Thus, while higher total income appears to enable significantly greater opiate purchasing, the extent of purchasing does not increase in proportion to income level—an inelastic response at the mean income and quantity level. However, demand curves typically experience changes in elasticity over the full range of quantity. The analyses included in this paper do not address the full cost of each heroin purchase. The regressions only reveal that purchase time is not a significant variable. The outcomes of the regression analyses suggest rational consumption. Increased time costs are related to fewer heroin purchases per week. Heroin users who report a higher number of suppliers also report more purchases per week. Higher unit cost is associated with lower consumption. Finally, higher income predicts more consumption. The signs on the regression coefficients are consistent with planned purchasing behavior and suggest areas for further research. In an independent sample, using a revised survey, we are now attempting to capture full price in a more meaningful fashion by analyzing reactions to hypothetical scenarios involving increased arrest probability and increased purchase time and distance variables. Theoretically, a new composite price variable could be constructed that combines monetary price, purity, distance, and time variables. The present data were captured in a to min interview while participants were screened for a separate study. The present data suggest that the complex economic profile of out-of-treatment heroin users parallels the complexity of addiction itself. The interrogative framework and analytic approach applied here offers useful clues about the price- and income-sensitivity of drug-dependent individuals, which could be translated into treatment and policy approaches Bickel and DeGrandpre, , while the basic factual information on income, expenditures, and prices contribute to overall knowledge of the market. Funds from the State of Michigan supported this research. Preliminary results of this study were presented at two annual meetings of the College on Problems of Drug Dependence in Orlando, Florida June 23, and Scottsdale, Arizona June 19, The authors thank Ken Bates for participant recruitment and Lark Cederlind for data entry and management. A field which applies scientific research on human and social cognitive and emotional biases to understand economic decisions and their outcomes. The research typically combines psychiatry, psychology and economics. The study of scarcity and how it affects decision making. Economics is a behavioral or social science. A concept used to quantify the response in one variable when another variable changes. Elasticity is measured by dividing the percentage change in one variable by the percentage change in the other. Measures the responsiveness of demand changes to changes in income. The income elasticity of demand is positive for normal goods. If demand is more responsive to a change in income, the Income Elasticity of demand is greater than one, and the response is considered elastic. If the income elasticity of demand is less than one it is considered inelastic. Measures the responsiveness of demand changes to changes in price of the good. The price elasticity of demand is always negative. If demand is more responsive to a price change, the absolute value of the price elasticity of demand is greater than one, and the response is considered elastic. If the absolute value of the price elasticity of demand is less than one it is considered inelastic. Juliette Roddy , Ph. She is a member of the Sault Ste. Her Ph. Allen Goodman. Mark Greenwald , Ph. Substances are used or misused; living organisms are and can be abused. The authors report no conflict of interest. The authors alone are responsible for the content and writing of the article. As a library, NLM provides access to scientific literature. Subst Use Misuse. Published in final edited form as: Subst Use Misuse. The publisher's version of this article is available at Subst Use Misuse. Open in a new tab. Regression results four models a. Total sample mean median First quartile value Third quartile value Heroin Declaration of Interest The authors report no conflict of interest. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel.

Vital Signs: Demographic and Substance Use Trends Among Heroin Users — United States, 2002–2013

Vars buying Heroin

Official websites use. Share sensitive information only on official, secure websites. Semi-structured interviews were used to assess behavioral economic drug demand in heroin dependent research volunteers. Findings on drug price, competing purchases, and past day income and consumption, established in a previous study, are replicated. We extended these findings by having participants indicate whether hypothetical environmental changes would alter heroin purchasing. Participants in higher income quartiles who purchase more heroin show greater DPA reductions but would still buy more heroin than those in lower income quartiles. Although a single survey of self-reports of behavior and economic activity cannot settle these debates, studying entrenched behaviors of drug abusers coupled with their economic profiles may help predict unintended side effects of policy and treatment. Most studies assess willingness to pay WTP for non-market benefits or willingness to accept WTA the loss of some benefit expressed in dollars. The present study provides quantitative data on heroin consumption among out-of-treatment users, focusing on income generating and spending behaviors. Semi-structured interview methods were used to address three aims. First, we characterized baseline past day economic behaviors. Second, contingent valuation was used to assess the impact of prices, arrest rates, transfer incomes and supply availability on purchasing. Third, we examined individual differences. Many variables can simulate price increases and we directly assessed WTA these increases by calculating a difference in daily purchasing amount of heroin. Male and female heroin-dependent volunteers from 18 to 55 years old were recruited by newspaper ads and word-of-mouth. Participants were paid U. Participants were asked questions to ascertain past day income, heroin price, all drug and non-drug expenditures, and drug consumption. A confidentiality certificate was obtained from the U. National Institute on Drug Abuse prior to the study. Table 1 lists descriptive characteristics for the entire group and by route of heroin use. Figure 1 breaks income into eight categories; dollar values and participation rates are presented. Figure 2 displays mean expenditures; mean percentages of income and participation rates are reported. Multiple regression analyses were used to evaluate predictors of heroin purchasing and use. A common set of independent variables leftmost column of Table 2 were used to predict bags consumed per day, number of bags purchased per week, percent of income spent on heroin, and unit purchase amount columns of Table 2. Table 3 reports the effects of hypothetical variations of income, subsidy, arrest rates and price on the demand variable daily purchasing amount DPA. These results were examined further by stratifying on group differences in income Table 4. Distribution of past-month income U. Distribution of past-month spending U. This cohort was predominantly African-American, male and about 45 years old with a high school or equivalent education and actively using heroin for a mean of 23 years. Polydrug use was determined through urinalysis and self-report. Urinalysis results revealed 56 positives for cocaine, 27 positives for marijuana and 17 positives for benzodiazepines. Injection relative to non-injection heroin users reported significantly more time per episode purchasing heroin and consuming more bags of heroin per day. Chi square analysis indicates that route of administration was independent of gender. Participants who suspected additives listed one or more substances, including total number of mentions : lactose 32 ; mannitol 17 ; sedative 17 ; and vitamins Figure 1 identifies sources, amounts and participation in past-month income acquisition. The only significant gender differences involved employment income. Figure 2 reveals common expenses, the mean percentage of income devoted to each category and the participation rate percent of sample engaging in the behavior. The only significant gender difference was the percent of income spent on alcohol where the mean for males was 0. Regression analyses were conducted to predict four dependent measures of heroin purchasing and consumption rightmost columns of Table 2. The independent variables were identical in each analysis left column of Table 2. Participants were asked how they would vary daily purchasing amount DPA of heroin in response to several hypothetical scenarios. Each respondent was instructed to consider how much their DPA would change due to a sudden change in dealer, direct reductions in income or elimination of subsidies, and increased likelihood of arrest. Table 3 presents these data for the overall sample and by gender and route of administration. The impact of income quartile on responses is presented in Table 4. The absolute dollar reduction in heroin expenditure increases within higher income quartiles. This study yielded three primary findings. Second, we established group differences in contingent valuation of heroin based on hypothetical variations in pricing and policy variables. Third, we discovered some purchasing differences among consumers that might support spatial mismatch or efficiency purchasing. This category includes, but is not limited to, criminal activities such as drug selling and prostitution. Regression results verified factors that we had observed to be significant predictors of drug seeking, purchasing and consumption. The results therefore appear to be reliable. Both studies indicated that more income was related to more purchasing. Higher past-month income did not predict a greater percentage of income devoted to heroin in our recent study and the present one. As explained below, both studies provided some evidence of rational consumption with unit cost and time spent on purchasing significant predictors of purchasing and consumption of heroin. This study was enhanced with contingent valuation questions that established consumption changes in reaction to pricing and policy variables that contributed to our second primary finding. Participants were asked to imagine change that might occur in their daily purchasing of heroin brought about by alterations in income including elimination of subsidies, changes in dealer, and changes in arrest rates. Although the change in purchasing due to an increase in income was not significant, it was positive. These responses suggest a forward-looking consumer sensitive to perturbations in the environment. In addition, extreme consumption i. When a reduction in income is anticipated, it is predicted that consumption will decrease. When subsidies are eliminated, the reaction is similar to a decrease in income. When negative consequences of purchasing escalate greatly , daily purchasing decreases. Rational addiction studies use inter-temporal change as evidence that the consumer considers all time periods in making decisions. Our study did not use this approach; our questionnaire was grounded in the present time. However, our heroin dependent non-treatment seeking volunteers clearly showed capability of considering future hypothetical events and offering consistent responses. Our study begins to establish the role of hypothetical policy and environmental variables—the direction and relative influences on purchasing and consumption of heroin by those with entrenched habits. Nonetheless, one may question whether the changes that respondent predicted when faced with hypothetical decreases in their income represented choice or constraint. Economists usually regard income as a constraint on choices. Microeconomic studies consistently maximize utility subject to a variety of constraints, the most common of which is income. It may be most accurate to label this hypothetical response an instance of constrained choice. We also hasten to add that the hypothetical responses of these volunteers were not intended to elicit or represent long-term responses to policy changes, i. Furthermore, many researchers e. Our third finding resulted from an examination of efficiency purchasing and spatial mismatch. We hypothesized that those with more severe addiction would purchase and consume heroin differently than those whose addiction is less severe. We therefore separated the sample by route of administration and identified differences related to purchasing and consumption Table 1. In addition, the data were examined for evidence of spatial mismatch for heroin purchasing. African American heroin users in our study experienced a mean travel distance of 1. The present study has several limitations. First, the sample may not represent all heroin abusers. These subjects may have responded to the modest incentive of the stipend; thus, dealers or users with significant criminal income may be under-represented. Second, self-report of behaviors may not reflect actual current or predicted contingent valuation levels. However, self reported use of cigarettes Hatziandreu et al. Furthermore, studies have shown actual consumptive reaction negative to price increases in drug, alcohol and cigarette use Chambers et al. Our interview had internal checks to ascertain consistency of the responses. The data reveal that those who purchase small amounts frequently live closer to their dealers than those who purchase larger amounts less frequently. A third limitation is that interview questions required the participant only to consider the past 30 days; therefore the results cannot be extrapolated for long term analysis. Lastly, contingent valuation is a direct method of obtaining responses however the situations presented are necessarily hypothetical. Hypothetical questions yield hypothetical responses. The present data suggest that consideration of price and income arrest rates, subsidies, variability of dealers and location measured in time and distance affects both consumption and purchasing behaviors. Those who face greater travel distance or time per purchase may purchase in larger quantities; those with more severe addiction may purchase more frequently, those who face lower prices will consume more. It also appears that environmental perturbations need to be fairly severe to reduce heroin use behavior. Each policy that potentially influences the variables of income, available to drug users, full price of purchasing, and location of the sale, purchase and consumption of drugs is likely to influence different groups of drug users differently Chaloupka, Further research that combines the market variables of pricing and location and examines the group differences in addiction severity, race, gender, income and location is suggested. Funds from the State of Michigan supported this research. Preliminary results of this study were presented at two annual meetings of the College on Problems of Drug Dependence in Orlando, Florida June 23, and Scottsdale, Arizona June 19, The authors thank Kendrich Bates for participant recruitment and Lark Cederlind and Debra Kish for data entry and management. As a library, NLM provides access to scientific literature. Psychol Addict Behav. Published in final edited form as: Psychol Addict Behav. Find articles by Juliette Roddy. Bancroft St. Find articles by Caren L Steinmiller. Find articles by Mark K Greenwald. PMC Copyright notice. The publisher's version of this article is available at Psychol Addict Behav. Open in a new tab. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel. Non- heroin opiates weekly purchases. Present DPA Baseline. Forced Change in Dealer.

Vars buying Heroin