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The illicit drug trade generates billions of dollars and sustains transnational criminal organisations. Drug markets can destabilise governance and undermine development. Data indicate increasing drug use in South Africa. However, information on the size and value of the drug market is limited. This is the first study to estimate the market value of cocaine, heroin and methamphetamine in South Africa. People who use drugs were meaningfully involved in all aspects of implementation. We used focus group discussions, ethnographic mapping, brief interviews, and the Delphi method to estimate the number of users, volumes consumed, and price for each drug in South Africa in Nationally, we estimated there to be: , people who use heroin probability range PR ,—, consuming Findings can be used to stimulate engagement to reform drug policy and approaches to mitigate the impact of the illicit drug trade. Additional studies that include people who use drugs in research design and implementation are needed to improve our understanding of drug markets. The illicit drug market is big. Over the past decade there has been marked growth in the size of the drug market around the world United Nation Office on Drugs and Crime Prohibitionist approaches have had little to no meaningful impact on drug supply or demand The Global Commission on Drug Policy Between and , seizure of opioids and amphetamine type stimulants ATS increased more than two-fold, with less marked increases in cocaine seizures UNODC In comparison, global production of opium and cocaine roughly doubled over the past two decades and supply has remained relatively stable UNODC Paradoxically, efforts to control drug supply through seizures and drug-related arrests may increase profitability through reduced competition and increased demand Bouchard Flexible and changing transportation solutions are employed by actors involved in the illicit drug trade to mitigate the potential effects that geopolitical events and law enforcement may have on business UNODC ; Eligh , Globally, in an estimated 62 million people used opioids for non-medical purposes, 27 million people used ATS and 20 million people used cocaine UNODC In , the annual prevalence of cannabis use among people in Africa was 6. The valuation of drug markets requires data on volumes and price. However, the criminalised nature of drug use and the drug market complicates valuation. For example, the volume of drugs traded is sometimes calculated by extrapolating police seizure data Werb et al. Furthermore, estimates of the number of people who use drugs are largely lacking or inaccurate UNODC Many existing estimates are taken from household surveys. However, sub-populations of people with higher proportions of drug use e. Moreover, under reporting of drug use in household surveys is common due to fear of arrest, stigma, and poor questionnaire design Johnson ; Global HIV Strategic Information Working Group et al. Health service data can provide insights into trends, but it is limited to those who access treatment UNODC Drug-related arrest data is also of limited value to assist our understanding of drug demand. Incentives for arrest, the differential likelihood of detention based on demographic and socioeconomic characteristics, and political and legal factors influence policing practices, resulting in biased estimates Lukas Muntingh ; Mooney et al. Similarly, it is difficult to assess the amount of drugs consumed. Estimates may be based on data collected through the approaches noted above; however, the data would likely be affected by the same biases affecting other variables. Drug market valuation estimates are more easily based on consumer price, as wholesale prices are rarely known European Monitoring Centre for Drugs and Drug Addiction However, consumer prices may fluctuate and are influenced by purity and the addition of bulking agents Cole et al. Specialised methodologies can overcome the challenges noted above. For example, research conducted in partnership with people who use drugs and trusted organisations using recommended methods e. Novel analytical techniques, such as sewage epidemiology, can be used to assess drug metabolite levels in wastewater to provide empirical insights into the volume of drugs consumed Huizer et al. Emerging data point to a large, and growing drug market in South Africa Eligh Increasing flows of heroin, 1 cocaine, and methamphetamine have been documented over the past 20 years Haysom In , 0. A household survey found that 0. Drug market research reflects a net decrease in the price of heroin, cocaine, and methamphetamine between and Howell et al. In light of the increased volume of drugs flowing through the country, and increasing use, it is probable that the illicit drug economy is of significant size and value. This study aimed to estimate the retail market value of cocaine, heroin, and methamphetamine in South Africa from a demand side, with meaningful engagement and participation of people who use drugs. The study employed focus group discussions FGDs , ethnographic mapping, brief interviews, and the Delphi method to gather inputs to estimate the retail drug market value in South Africa in South Africa has nine provinces and is comprised of 52 districts. Districts are further divided into electoral wards. The most populous city in each selected province was selected for implementation. No cities were included from the North West and Northern Cape Provinces, which do not have metropolitan municipalities and are the third least and least populous provinces. Activities took place between May and November People who use drugs facilitated FGDs and ethnographic mapping activities, conducted interviews, validated the results, and participated in population size estimation workshops. Broadly, the procedures involved: 1 primary data collection FGDs, mapping and brief interviews with people who use drugs and validation sessions; 2 population size estimation using the Delphi Method provincial and national workshops and 3 market valuation. National and local stakeholders were informed of the project. In the cities where fieldwork took place, engagements focused on networks of people who use drugs and organisations providing health and harm-reduction services for people who use drugs, men who have sex with men, transgender people, and sex workers key populations. Engagement activities sought to obtain support for the study. Engagement with other stakeholders e. Primary data collection and validation sessions were held in each city. Table 1 provides details of primary data collection and validation activities. Fieldwork was done sequentially over 3—5 days in each city. Fieldworkers, identified during FGDs, underwent a half-day training on the study, covering: conducting brief interviews with their peers using standard tools; data quality; ethical considerations; safety and COVID mitigation strategies. Activities were piloted in each city before implementation. At the end of the fieldwork in each city, structured validation sessions were held to reach agreement on 1 the cost of each drug per gram ; 2 average amount a range, in grams of each drug used in a hour period; 3 proportion of daily and infrequent monthly users of each drug, and 4 population size estimates for each drug and for people who inject for the city. This process involved a bottom up-approach, building on the city-level estimates from the fieldwork to develop district, then provincial and finally national population estimates. Provincial workshops : Fieldwork team members, representatives of people who use drugs networks and local stakeholders including health service providers participated in virtual provincial estimation workshops. Seven workshops were held. Participants interrogated the city-level estimates from the validation sessions in light of programmatic and research data and their experience. The group reached consensus on district-level estimates and upper and lower plausibility bounds using the Delphi Method Jorm This method employs four rounds of facilitated engagement among experts to reach consensus on estimates. Estimates were generated for the number of people who use cocaine, heroin, and methamphetamine, and the number who inject drugs in the respective fieldwork district reference district. The district-level estimates were then used to generate proportions of people in that district aged 15—64 who use each drug and those who inject drugs using the most recent census data Statistics South Africa Provincial workshop participants ordered the districts in their province from the district with the largest population of people who use drugs to the smallest. Agreement was reached on the relative size of each district in relation to the reference district in that province. The relevant size was calculated as an adjustment proportion. Adjustment proportions were then applied to the general population estimate 15—64 years of the districts that were not visited in that province. The same adjustment factor was applied across each drug type. This process resulted in district-level estimates for each drug and for people who inject drugs in the province. All of the district estimates were summed to generate initial national population estimates point estimates and lower and upper plausibility bounds. National workshops: The research team convened a virtual national size estimation workshop over two sessions held a week apart. Participants included people who use drugs, key population representatives, development partners, researchers, health workers, social workers, government representatives, and civil society service providers. The first session was used to review the process and participants interrogated the findings of the fieldwork and the initial national population estimates i. During the second workshop, the process, fieldwork findings, and other available data were recapped and the Delphi method was used to obtain revised national population estimates. The retail market value was calculated by multiplying total annual consumption by price European Monitoring Centre for Drugs and Drug Addiction Annual consumption was calculated separately for the population of people who used drugs daily and those who used drugs infrequently assumed to be once a month. These values were added to estimate total annual consumption. Figure 1 provides the formula used and data inputs. Formula and data inputs to calculate the retail drug market value European Monitoring Centre for Drugs and Drug Addiction, Procedures, tools, and training were standardised. Fieldworkers and the research coordinator completed reviews of forms for completeness. Paper forms and written notes were concealed while in the field and securely stored. Neither personal nor detailed location data was captured. Summary statistics were generated to describe fieldwork participants and quantitative indicators. The market value was calculated using the formula outlined above. Verbal informed consent was obtained. Overall, people who use drugs men, women, and 14 transgender people participated in brief interviews across locations in wards. People who used heroin had the largest peer network median of 40 people , and people who used methamphetamine had the smallest median of 20 people. A total of people who use drugs participated in validation workshops. A validation workshop was not completed in Pietermaritzburg due to logistical complications. Table 2 outlines fieldwork participant characteristics. FGD participants reported that heroin, crack, and powder cocaine and methamphetamine were available and used in all the cities where fieldwork was conducted. They suggested that most people who use heroin concurrently used stimulants, either methamphetamine in Cape Town and Port Elizabeth or crack cocaine in the other cities. FGD participants believed that more than half the people who use heroin inject it, while crack cocaine and methamphetamine are mostly smoked, and powder cocaine snorted. Injecting methamphetamine was reported to be more common when mixed with heroin. However, some people were reported to inject methamphetamine on its own. Across the cities, an average of 10—30 people were observed at each hotspot where brief interviews were conducted. Generally speaking, interviewees reported that between 25 and 60 people congregated at these locations at their busiest times. Heroin was reported to be used by almost all people at the hotspots, except in Cape Town, where methamphetamine was the most widely used drug. Injecting was reported across the hotspots in all visited cities except for Bloemfontein, although injecting practices were confirmed in the validation session in that city. The validated estimates for population sizes, proportion of people with daily and infrequent use, amounts used in a day and the cost of each drug arising from the fieldwork are provided in Table 3. Details of the fieldwork districts population proportions are in Supplementary Table S1 and the adjustment factors and the population size estimates for all districts and the initial and revised Delphi national population size estimates are provided in Supplementary Table S2. District-level estimates fieldwork districts : population size estimates, frequency and amounts used and unit cost per drug, by city. Among people who inject heroin, daily amounts were reported to range from 0. Amounts of reported cocaine used varied across cities. For crack cocaine, this ranged from 0. For powder cocaine, amounts used per day ranged from 0. Data was not obtained for the frequency of methamphetamine use in Pietermaritzburg. Amounts of methamphetamine reported to be used per day ranged from 0. The national level market value inputs and results are presented in Table 4. The median amount used in a hour period 0. For methamphetamine, two-thirds of users were assumed to use daily. The median amount used in 24 hours was assumed to be 0. Daily cocaine amounts is based on crack cocaine, which is around a third less than suggested daily powder cocaine amounts. The crack cocaine daily amount was chosen due to limited participation of powder cocaine users in the research. The national population size estimate of the number of people who use heroin was , probability range PR ,—, , consuming tonnes PR The population estimate for people who use cocaine was , including , daily users , consuming The number of people who use methamphetamine was estimated at , including , daily users consuming This study was designed to assess the retail value of a criminalised and unregulated market. To the best of our knowledge the research is the first of its kind in South Africa. The study used practical methods to gather inputs to impute into a recommended drug market valuation formula European Monitoring Centre for Drugs and Drug Addiction The study provides initial estimates which can be included in future studies towards an accurate estimation of the drug market value in the country. The findings suggest that the nature and size of the drug market in South Africa are significant. The International Narcotics Control Board notes that in there was limited data on drug trafficking in Africa, but it remains a major challenge on the continent International Narcotics Control Board The ongoing trafficking of cocaine mostly in West and North Africa and heroin in the Indian Ocean region and increasing market size is acknowledged, along with small drug seizures reported in International Narcotics Control Board There is little data on the value of drug markets in other African contexts. The International Narcotics Control Board estimated that 2. Superior data is available for Europe. Our estimates for South Africa have wide plausibility ranges. This is largely due to uncertainty around the population size estimates. The fieldwork identified widespread use of cocaine, heroin, and methamphetamine across the cities included in the study. Our best estimates for population size estimates for people who used drugs in was 3. The household survey is likely to be subject to selection and reporting bias, and therefore an underestimate. The degree of underestimation of drug use in household surveys in South Africa is difficult to assess as people who use heroin, methamphetamine, and cocaine face arrest and are affected by intersectional stigmas that create barriers to disclosing drug use Shelly et al. Estimating population sizes is known to be challenging, and recommended practice is for the use of multiple empirical methods Global HIV Strategic Information Working Group et al. Mapping with census and enumeration, capture-recapture, multiplier methods, and Wisdom of the Crowds are some of the recommended methods that can be integrated into biobehavioural surveys for people who use drugs Global HIV Strategic Information Working Group et al. We used the key informant-driven mapping and enumeration approach Ndayongeje et al. The fieldwork was based on the premise that meaningfully involving people who use drugs through a participatory action research approach would reduce some potential bias of household surveys Brown et al. Although limited in application, people who use drugs have generated bottom-up estimates in South Africa Scheibe et al. An increased number of studies has documented the spread and increased use of heroin in South Africa and the region since the early s Eligh The evidence base from research and programme data consistently shows upward trends in the prevalence of heroin use across the country. Increased cocaine use, particularly crack cocaine, has also been described. In the early s the use of methamphetamine started to increase Peltzer et al. Methamphetamine surpassed cocaine as a proportion of primary drug of use among people in drug treatment centres in Dada et al. Methamphetamine-related admissions to drug treatment centres have continued to rise Dada et al. The wide availability of methamphetamine was confirmed by our fieldwork. Data from sewage epidemiology in South Africa suggest notable underestimation of drug use. For example, the levels of methamphetamine metabolites in wastewater in Cape Town are among the highest levels documented, higher than cities in Europe and Malaysia Archer et al. Insights from a large number of people who currently use drugs elicited through focus groups and validation meetings give us confidence in the drug pricing estimates. The cost of drugs varied across cities and was generally lower than prices based on data from the police. The relative costs per gram of each drug is likely to reflect a combination of factors, including the quantities available for sale, user preferences, and drug quality. The findings of this study suggest that larger volumes of heroin are used compared to the other drugs included in this study in South Africa. It is possible that we have over-estimated the number of people who use drugs and the proportion of people who use drugs daily. This may have resulted in over-valuation of the drug market. However, in light of the improbability and cost of implementing a national census of people who use drugs and the limited available quantitative data we believe the use of the Delphi Method was justifiable. Furthermore, the use of the Delphi Method in our study was efficient and enabled virtual participation. It also built on fieldwork and other limited data and inputs from experts in a range of fields, including people who use drugs and harm reduction service providers. This study did not measure perceived drug quality or drug purity. Drug quality and purity potentially influences drug cost in South Africa and may differ across the country and in relation to other countries Eligh Heroin prices in southern African have been found to be largely influenced by availability, transport costs, and to a lesser degree, perceived quality Eligh The resources available for implementation limited the number of implementation sites. The inclusion of more fieldwork sites would have provided additional primary data and reduced the degree of extrapolation applied to districts where primary data was not collected. Additional implementation sites and primary data would have likely increased the accuracy of the estimates. The fieldwork was designed to include people who are often missed or excluded from surveys, specifically people living on the street. Therefore, it is likely that more affluent people who use drugs were under-represented in data drawn from the fieldwork. Due to their higher income and the perceived relationship between quality and price, it is conceivable that the market value of this segment could be even higher than the total market size reported in this study. Potential under-representation of people who use drugs was taken into consideration in the Delphi process and was deemed to be of particular importance for powder cocaine. Participation of more affluent people in future drug market related research could be enhanced through the use of digital platforms to collect data, providing confidentiality is ensured. The participation of drug sellers could also provide additional insights into other segments of the population of people who use drugs. The concurrent COVID pandemic and associated lockdowns and restrictions affected study implementation. The local and national consensus workshops were conducted virtually. This created difficulties for a number of people who use drugs, as it required internet access, which was often not available to them. Attempts were made to include representatives from the SANPUD network to overcome these challenges through linking with local organisations or providing data where possible. Our study is the first of its kind in South Africa. It adds to the understanding of the drug economy by quantifying the market volumes and values for cocaine, heroin, and methamphetamine using data collected by and from people who use drugs. Despite the inherent limitations of the study, the results suggest that a large drug market exists in South Africa. Considering the size of the market and the substantial revenue generated, further consideration should be given to stakeholders in the value chain. Apart from the value and volume of the market, our research provides valuable insights into the way drug markets can be researched. People who use drugs are closest to the market, have valuable insights, and are arguably best positioned to identify potential sources of data and interpret its value, relevance, and validity in situ. Thus, people who use drugs have skills, capacity, and expertise that should be included in research teams investigating drug markets. Drug markets are complex and multi-faceted. Therefore, researchers should work across fields and disciplines to develop a more comprehensive understanding of the drug market and its role and impact on communities and the national economy. Importantly, studies related to the drug market should include people who use drugs in the design and implementation of the research. Subsequent studies with more accurate input estimates, particularly around population sizes, will improve the precision of the market value estimates. This could be done through conducting more city-level population size estimations increasing rigor and geographical coverage along with research that uses emergent data to refine national estimates. Future studies that measure drug purity would provide insights into comparative drug pricing and market valuation. Additional research into the flow of money in the market and how the trade in illicit drugs impacts individuals and communities would be important to inform policy and action. Supplementary Tables s1 and s2. Known locally as nyaope, whoonga, unga, sugars, pinch. AS developed the protocol and tools and led data analysis and developed the first draft of the manuscript. MJS led the implementation of the fieldwork and supported data analysis and drafting the manuscript. SS co-developed the protocol and supported implementation, analysis, and manuscript development. All authors reviewed and approved the final version of the manuscript. Archer, E, et al. Chemosphere , — Bouchard, M. On the resilience of illegal drug markets. Global Crime , 8 4 : — Brown, G, et al. Achieving meaningful participation of people who use drugs and their peer organizations in a strategic research partnership. Harm Reduction Journal , 16 1 : Cole, C, et al. Adulterants in illicit drugs: a review of empirical evidence. Drug Testing and Analysis , 3 2 : 89— Dada, S, et al. Monitoring alcohol, tobaccoe and other drug use trends South Africa : July—December Cape Town: MRC. Eligh, J. A shallow flood. The diffusion of heroin in eastern and southern Africa. A synthetic age: The evolution of methamphetamine markets in Eastern and Southern Africa. Euromonitor Consulting. Estimating the size of the main illicit retail drug markets in Europe: an update. Technical report. Luxemborg: Publications Office of the European Union. Interdicting international drug trafficking: a network approach for coordinated and targeted interventions. European Journal on Criminal Policy and Research , 28 4 : — Biobehavioural survey guidelines for populations at risk for HIV. Geneva: WHO, pp. Harker, N, et al. Is South Africa being spared the global opioid crisis? A review of trends in drug treatment demand for heroin, nyaope and codeine-related medicines in South Africa — International Journal of Drug Policy , Haysom, S. Hiding in plain sight. Policy Brief. The heroin coast. Howell, S, et al. The wrong type of decline: fluctuations in price and value of illegal substances in Cape Town. SA Crime Quarterly , 43— Huizer, M, et al. Wastewater-based epidemiology for illicit drugs: a critical review on global data. Water Research , International Narcotics Control Board. Vienna: United Nations. Johnson, TP. Sources of error in substance use prevalence surveys. International Scholarly Research Notices. Hindawi Publishing Corporation. Jorm, AF. Using the Delphi expert consensus method in mental health research. Konstant, TL, et al. Estimating the number of sex workers in South Africa: rapid population size estimation. Machethe, P and Mofokeng, JT. The impact of illicit drug networks on the effectiveness of law enforcement in South Africa. Technium Social Sciences Journal , — May, C. Transnational Crime and the Developing World. Global Financial Integrity , June Washington, DC. Medical Research Council. Mooney, AC, et al. American Journal of Public Health , 8 : — Muntingh, L. Race, gender and socio-economic status in law enforcement in South Africa — are there worrying signs? Ndayongeje, J, et al. Illicit drug users in the Tanzanian Hinterland: population size estimation through key informant-driven hot spot mapping. Cocaine treatment admissions at three sentinel sites in South Africa — : findings and implications for policy, practice and research. Substance Abuse Treatment, Prevention, and Policy , 2: Peltzer, K, et al. Journal of Social Sciences , 18 2 : — Illicit drug use and treatment in South Africa: a review. Substance Use and Misuse , — Peltzer, K and Phaswana-Mafuya, N. Drug use among youth and adults in a population-based survey in South Africa. South African Journal of Psychiatry , 24 1 : 1—6. Scheibe, A, et al. Using a programmatic mapping approach to plan for HIV prevention and harm reduction interventions for people who inject drugs in three South African cities. Harm Reduction Journal , 14 1 : Setswe, G, et al. Programmatic mapping and size estimation study of key populations in South Africa: sex workers male and female , men who have sex with men, persons who inject drugs and transgender people. Shelly, S, et al. Every single person looks at us bad. Stanyard, J. Shaping crime. Statistics South Africa. Census factsheet. Pretoria: Statistics South Africa. GDP, Find statistics. The Global Commission on Drug Policy. Time to end prohibition. Geneva: Global Commission on Drug Policy. United Nations Office on Drugs and Crime. Drug purity, Drug trafficking and cultivation. United Nation Office on Drugs and Crime. World Drug Report Brief report of the TipVal study: an integrated bio-behavioral surveillance survey among people who inject drugs. Afghan opiate trafficking through the Southern route. World drug report. Werb, D, et al. The temporal relationship between drug supply indicators: an audit of international government surveillance systems. BMJ Open , 3 9 : e A Bayesian approach to synthesize estimates of the size of hidden populations: the Anchored Multiplier. International Journal of Epidemiology , 47 5 : — Estimating sizes of key populations. Cairo: WHO. Home About. Research Integrity. Crime Beyond Borders. Abstract The illicit drug trade generates billions of dollars and sustains transnational criminal organisations. Keywords: Drug market illicit markets valuation South Africa. Year: Submitted on May 5, Accepted on May 12, Published on Feb 14, Peer Reviewed. CC Attribution 4. Introduction Global context The illicit drug market is big. Drug market valuation The valuation of drug markets requires data on volumes and price. Methods The study employed focus group discussions FGDs , ethnographic mapping, brief interviews, and the Delphi method to gather inputs to estimate the retail drug market value in South Africa in Setting South Africa has nine provinces and is comprised of 52 districts. Procedures Activities took place between May and November Primary data collection National and local stakeholders were informed of the project. Table 1 Primary data collection activities in each city. FGDs and mapping Between 6 and 12 people, purposively sampled for diversity representing men, women, sex workers, men who have sex with men, and transgender people who use drugs , participated in a FGD at the start of fieldwork. The FGDs followed a structured guide that explored drug usage methods, frequency, volume and drug market characteristics number of users, hotspots, and drug unit cost. The mapping component included the use of stickers to plot drug use hotspots on city maps. FGDs were held in private safe spaces and were co-facilitated by the research coordinator and a person with lived experience of drug use from that city. Information was captured using a FGD guide and written notes. The FGDs each took between two and three hours. The informed consent and FGD guide were in English with translations provided by the co-facilitator. Brief interviews Brief interviews were conducted with people who use drugs in locations where people who use drugs congregate or were accessible hotspots across diverse areas in each city. Feedback from the FGDs and mapping were used to identify locations to conduct interviews and for fieldwork planning. Based on available time and resources, as many interviews and location visits were done in each city as possible. Teams convened at the beginning and end of each day to plan and reflect on the fieldwork. Working in pairs, the fieldworkers conducted up to 20 brief interviews per day lasting approximately 10—15 minutes each. The informed consent and questions were in English with translations provided by fieldworkers. Validation sessions with people who use drugs Sessions took place at the end of the fieldwork in each city. FGD participants were invited, as well as up to five people who use drugs who had insights into drug use in that city Konstant et al. The research coordinator led the sessions, which were structured and standardised. Clarity around conflicting or missing information was obtained. The research coordinator facilitated a discussion to validate the results and reach agreement on estimates. Data on the most commonly purchased form of each drug, and perceived weight of units of purchase, was obtained in each city. Considering the locations that were visited, the findings were extrapolated to the whole city. The research coordinator facilitated these sessions in English, which each took 2 to 3 hours. Population size estimation of people who use drugs This process involved a bottom up-approach, building on the city-level estimates from the fieldwork to develop district, then provincial and finally national population estimates. Retail drug market valuation The retail market value was calculated by multiplying total annual consumption by price European Monitoring Centre for Drugs and Drug Addiction Figure 1 Formula and data inputs to calculate the retail drug market value European Monitoring Centre for Drugs and Drug Addiction, Data management and analysis Procedures, tools, and training were standardised. Table 2 Fieldwork participant characteristics. Retail market valuation The validated estimates for population sizes, proportion of people with daily and infrequent use, amounts used in a day and the cost of each drug arising from the fieldwork are provided in Table 3. Table 3 District-level estimates fieldwork districts : population size estimates, frequency and amounts used and unit cost per drug, by city. Table 4 Retail market valuation: inputs and results. PR Plausibility range. Percent of daily cocaine users is the median of daily crack and daily powder cocaine users. Discussion This study was designed to assess the retail value of a criminalised and unregulated market. Limitations It is possible that we have over-estimated the number of people who use drugs and the proportion of people who use drugs daily. Conclusion Our study is the first of its kind in South Africa. Additional File The additional file for this article can be found as follows: Supplementary Tables Supplementary Tables s1 and s2. Notes Known locally as nyaope, whoonga, unga, sugars, pinch. Competing Interests The authors have no competing interests to declare. Author Contributions AS developed the protocol and tools and led data analysis and developed the first draft of the manuscript. References Archer, E, et al. Between 6 and 12 people, purposively sampled for diversity representing men, women, sex workers, men who have sex with men, and transgender people who use drugs , participated in a FGD at the start of fieldwork. Brief interviews were conducted with people who use drugs in locations where people who use drugs congregate or were accessible hotspots across diverse areas in each city. Sessions took place at the end of the fieldwork in each city.

Patterns of substance use in South Africa: Results from the South African Stress and Health study

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Official websites use. Share sensitive information only on official, secure websites. There are limited data on substance use in South Africa. We describe patterns of substance use based on recent, nationally representative data. A nationally representative household probability sample of 4 adults was interviewed using the paper and pencil version of the World Health Organization Composite International Diagnostic Interview CIDI. Data are reported for lifetime use, socio-demographic correlates of use, and age of cohort predicting lifetime use for four classes of drugs. The estimate for cumulative occurrence of alcohol use was There were statistically significant associations between male gender and alcohol, tobacco, cannabis and other drug use. Coloureds and whites were more likely than blacks to have used alcohol, tobacco and other drugs. Clear cohort variations existed in the age of initiation of drug use; these were most marked for other drugs and for extra-medical drug use. Use of all drug types was much more common in recent cohorts, with a similar cumulative incidence of tobacco, alcohol and cannabis use across age cohorts. Epidemiological patterns of use for alcohol, tobacco, cannabis, other drugs and extra-medical drugs provide the first nationally representative data. New findings on race and exploratory data on time trends provide a foundation for future epidemiological work on drug use patterns across birth cohorts and population subgroups in South Africa. During the apartheid years South Africa was relatively isolated from the rest of the world and substance use primarily revolved around locally produced substances, notably alcohol, tobacco and cannabis. During the s and early s South Africa went through major social and political transformation. During this period links and trade with the rest of the world opened. Law authorities, social services and service providers agree that substance-related problems have increased dramatically over the past 10 years. These include road traffic accidents, mental illness and, most worrying, violence and severe crime committed under the influence of substances. Historically substance abuse data in South Africa have been limited. Until the late s information came mostly from ad hoc cross-sectional studies, often conducted in a single location, and from information on police arrests and drug seizures, mortuaries and school surveys. This has since been supplemented by national surveys. Cape Town continues to experience a dramatic increase in the use of crystal methamphetamine known as Tik , which has become the primary substance of abuse. Whites appear to be the highest users of substances, followed by blacks, coloureds and Indians in Gauteng and Mpumalanga, while coloureds are the highest users, relative to other race groups, in Port Elizabeth and Cape Town. Black substance abusers far outnumber any other group in the East London area. Although systems such as SACENDU provide valuable information on substance abuse trends, there have been no systematic data available that are fully representative of the diverse South African population. A sample of 4 adults aged 18 and older, drawn from a nationally representative, household probability sample, were interviewed. Households and hostel quarters were included. Sampled residences were stratified into 10 diverse household categories, including rural-commercial, agricultural, rural traditional subsistence areas, black townships, informal urban or peri-urban shack areas, coloured townships, Indian townships, general metropolitan residential areas, general large metropolitan residential areas and urban domestic servant accommodation. Within each of these strata, households were listed from maps, census data or aerial photographs. A probability sample of households was selected and screened to determine eligibility. A singe adult respondent from each selected dwelling was drawn randomly using the Kish method. Discrepancies found in the back-translation were resolved by an expert consensus panel. Evaluated in cross-section, this is a cumulative incidence proportion among cohort members who have survived to the age of assessment — i. Alcohol use was defined as ever had a drink, and age of onset as the age at which the respondent had his or her first drink, and the age at which he or she started drinking at least 12 drinks a year. The combined number of respondents for the above questions was used to determine the prevalence of alcohol use. Tobacco users were defined as those reporting smoking more than cigarettes in their lifetime. Onset of use was defined as the age at which a respondent started smoking. Cannabis use was defined as having ever used cannabis and its onset as at what age use commenced. Extra-medical drug use comprised the use of sedatives or tranquillisers, stimulants, analgesics or any other psychoactive over-the-counter compound. The age of onset was defined as the age at which the first of these drugs was used. Age of onset of use was defined as the age of first use. Similar to other WMH countries, our measure of income was calculated by dividing household income by the number of household members and defining four income categories. The two lowest quartiles of per capita income were called low income and low-average income. High average income was defined as income between one and two times the median per capita income and high income was defined as more than twice the median; v residence in an urban or rural area; vi asset index we used an asset index based on 17 items reflecting individual and household wealth. These measures of asset ownership were used to construct an aggregate asset score, which was categorised into categories for low, medium and high assets. To account for the stratified multi-stage sample design, the data were weighted to adjust for differential probability of selection within households as a function of household size and clustering of the data, and for differential non-response. A post-stratification weight was also used to make the sample distribution comparable to the population distribution in the South African census for age, sex, and province. Logistic regression analysis was used to study socio-demographic correlates. Statistical significance was consistently evaluated using 0. Table I presents frequency distributions for covariates and response variables. Unweighted sample sizes are followed by weighted estimated proportions and Taylor series linearisation derived SEs for the proportions. Aside from the unweighted sample frequencies, all results are based on conventional analytical methods for complex survey data. The SE of a method of measurement or estimation is the estimated SD of the error in that method. Namely, it is the SD of the difference between the measured or estimated values and the true values. Notice that the true value is, by definition, unknown and this implies that the SE of an estimate is itself an estimated value. More than half the sample was female, only Use of alcohol was most common Table II shows the estimated cumulative incidence proportions and ORs of cumulative occurrence. Alcohol was used by the majority of participants with the proportions using alcohol similar among younger birth cohorts These were slightly lower than estimates for the older — cohort The — birth cohort was 1. Estimated cumulative occurrence of drug use by birth cohort, and estimates from discrete time survival analysis models. Estimated cumulative incidence proportions for cannabis were lowest for the oldest cohort, born — 5. Larger proportions were observed in the most recent cohort, born — The most recent cohort was 1. Although not statistically significant, the cumulative incidence proportions for other drugs, including cocaine, and extra-medical drug use were again slightly higher in the two more recent cohorts. Relatively high rates of extra-medical drug use were reported across age cohorts, ranging from a cumulative incidence of Table III presents estimated ORs for selected covariates bivariate and cumulative occurrence of drug use, and Table IV shows covariate-adjusted multivariate estimates of the strength of these associations. While trends showed an increase in the use of cannabis, other drugs and extra-medical drugs in younger age groups, this was only significant for cannabis use on bivariate analysis Table III. While the same trends were observed on multivariate analysis, there were no significant associations between age and drug use Table IV. Estimated strength of association between selected covariates and cumulative occurrence of drug use. Covariate-adjusted estimates of strength of association between selected covariates and cumulative occurrence of drug use. On both bivariate and covariate estimates, gender was the most significant indicator of substance use — males were generally 8 — 9 times more likely than females to have become users of all drug types, except for extra-medical drugs. On bivariate analysis, participants identified as black were less likely than whites and coloureds to be users of alcohol OR 3. After adjustment for other demographic and socio-economic factors, coloureds were 3. Whites used significantly more alcohol, tobacco, cannabis and other drugs compared with blacks. Estimated associations with educational attainment differed across drug types. Based upon estimates from the bivariate analyses, persons with post-matric education were more likely to have used cannabis OR 2. Other drug use e. These crude associations did not persist in multivariate models. On bivariate analysis, those who were employed were more likely to have tried all classes of drugs compared with the unemployed Table III. This was only significant for alcohol and tobacco use. On bivariate analysis only, respondents with low income used significantly more alcohol compared with those with no income. No association was found between marital status and drug use. Strong associations were found on bivariate analysis Table III between urban residence and alcohol, tobacco, cannabis and other drug use, but not extra-medical drug use. Those living in urban areas were more than twice as likely to have used cannabis OR 2. On bivariate analysis, possessing more assets was associated with a higher prevalence of substance use. On multivariate analysis, respondents with an average number of assets showed statistically higher use of alcohol compared with those with no income. Of those in the youngest cohort 18 — 29 years who had used alcohol, More pronounced cohort-associated variations were found when cumulative proportions of those who had used other drugs stimulants, cocaine, etc. These findings are in keeping with countrywide estimates of alcohol, tobacco and cannabis use. Alcohol remains the substance most often used by South Africans During , after this survey was conducted, methamphetamine was documented as the primary drug of abuse in the Western Cape, replacing alcohol and overtaking cannabis. Limitations of this study deserve mention. First, a cross-sectional survey does not include drug-related deaths, i. In addition, tobacco-associated mortality should have been especially high; however, this was the drug with the smallest cohort-associated variations. However, such a bias is not relevant for estimates of the cumulative incidence proportion for ages through which all cohorts have passed, since comparisons are made across cohorts for a given age in the lifespan e. A third possible bias is that older respondents may have struggled to remember events long ago. It is therefore unlikely that response or other biases completely account for the trends observed here. Similar birth cohort trends in the age of initiation of illegal drug use have been observed in surveys in the USA 11 and Australia, 12 some of which used data collected across time rather than relying solely on retrospective reports. The trends are also consistent with data concerning illegal drug markets in South Africa. There is good evidence that drug availability and drug use in the general population co-vary. For example, since the first democratic elections in South Africa in there has been an increase in the trafficking and use of heroin, cocaine, and amphetamine-type stimulants in the country. A fourth limitation might be that drug availability simply changes patterns of use in a given population. Since there is no simple relationship between drug availability and drug use in a population, drug availability cannot be the sole cause for changes in the cumulative incidence of drug use. The country has gone through major political, economic and cultural changes. There has been an influx of foreign people, trade and culture into and through South Africa with transitions in several provinces from a predominantly rural-cultural society into an urban westernised society, all of which could play a role in the trends described here. Finally, these data do not capture the dramatic increase in the use of methamphetamine and other drugs. Since , methamphetamine has become the primary drug of abuse in the Western Cape. It is therefore vital to replicate the present survey. Despite these limitations, the following findings are notable. Males as well as whites and coloureds had a considerably higher prevalence of substance use compared with females and blacks and Indians. Compared with blacks, coloureds were 8. Whites were consistently the second-highest users, with the exception of cannabis, for which they were the highest users. Indians were least likely to have used any type of substance. These and other socio-demographic correlates — substance use being more common in males 13 and in urban populations 14 — are consistent with previous reports. Whereas early cohorts had a particularly higher prevalence of alcohol use, more recent cohorts demonstrated a particularly high prevalence of cannabis use. More recent cohorts were much more likely to start drug use, particularly extra-medical and other drug use, in childhood and in early to mid-adolescence. Substance use has multiple adverse consequences for individuals and for society in general. Prior work has demonstrated associations between substance use and health, crime and sexual behaviour. Substance abuse and its many interactions with the aforementioned and with mental illness must be taken into account in the allocation of resources and in the planning of health services. We thank the WMH staff for assistance with instrumentation, fieldwork, and data analysis. Ms K Cloete, science writer, Department of Psychiatry, Stellenbosch University, is thanked for her contribution to the preparation and formatting of this manuscript. As a library, NLM provides access to scientific literature. S Afr Med J. Find articles by Margaretha S van Heerden. Find articles by Anna T Grimsrud. Find articles by Soraya Seedat. Find articles by Landon Myer. Find articles by David R Williams. Find articles by Dan J Stein. PMC Copyright notice. Open in a new tab. Birth cohort Alcohol Tobacco Cannabis Other drugs e. Alcohol Tobacco Cannabis Other drugs e. 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.

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