Approaches to triangulation of alcohol data in Scotland: Commentary on Rehm et al

Bayesian modelling of population trends in alcohol consumption provides empirically based country estimates for South Africa

Background

Alcohol use has widespread effects on health and contributes to over 200 detrimental conditions. Although the pattern of heavy episodic drinking independently increases the risk for injuries and transmission of some infectious diseases, long-term average consumption is the fundamental predictor of risk for most conditions. Population surveys, which are the main source of data on alcohol exposure, suffer from bias and uncertainty. This article proposes a novel triangulation method to reduce bias by rescaling consumption estimates by sex and age to match country-level consumption from administrative data.

Methods

We used data from 17 population surveys to estimate age- and sex-specific trends in alcohol consumption in the adult population of South Africa between 1998 and 2016. Independently for each survey, we calculated sex- and age-specific estimates of the prevalence of drinkers and the distribution of individuals across consumption categories. We used these aggregated results, together with data on alcohol production, sales and import/export, as inputs of a Bayesian model and generated yearly estimates of the prevalence of drinkers in the population and the parameters that characterise the distribution of the average consumption among drinkers.

Results

Among males, the prevalence of drinkers decreased between 1998 and 2009, from 56.2% (95% CI 53.7%; 58.7%) to 50.6% (49.3%; 52.0%), and increased afterwards to 53.9% (51.5%; 56.2%) in 2016. The average consumption from 52.1 g/day (49.1; 55.6) in 1998 to 42.8 g/day (40.0; 45.7) in 2016. Among females the prevalence of current drinkers rose from 19.0% (17.2%; 20.8%) in 1998 to 20.0% (18.3%; 21.7%) in 2016 while average consumption decreased from 32.7 g/day (30.2; 35.0) to 26.4 g/day (23.8; 28.9).

Conclusions

The methodology provides a viable alternative to current approaches to reconcile survey estimates of individual alcohol consumption patterns with aggregate administrative data. It provides sex- and age-specific estimates of prevalence of drinkers and distribution of average daily consumption among drinkers in populations. Reliance on locally sourced data instead of global and regional trend estimates better reflects local nuances and is adaptable to the inclusion of additional data. This provides a powerful tool to monitor consumption, develop burden of disease estimates and inform and evaluate public health interventions.

Heroin use cannot be measured adequately with a general population survey

BACKGROUND

Globally, heroin and other opioids account for more than half of deaths and years-of-life-lost due to drug use and comprise one of the four major markets for illegal drugs. Having sound estimates of the number of problematic heroin users is fundamental to formulating sound health and criminal justice policies. Researchers and policymakers rely heavily upon general population surveys (GPS), such as the US National Survey on Drug Use and Health (NSDUH), to estimate heroin use, without confronting their limitations. GPS-based estimates are also ubiquitous for cocaine and methamphetamine, so insights pertaining to GPS for estimating heroin use are also relevant for those drug markets.

ANALYSIS

Four sources of potential errors in NSDUH are assessed: selective non-response, small sample size, sampling frame omissions and under-reporting. An alternative estimate drawing on a variety of sources including a survey of adult male arrestees is presented and explained. Other approaches to prevalence estimation are discussed.

FINDINGS

Under-reporting and selective non-response in NSDUH are likely to lead to substantial underestimation. Small sample size leads to imprecise estimates and erratic year-to-year fluctuations. The alternative estimate provides credible evidence that NSDUH underestimates the number of frequent heroin users by at least three-quarters and perhaps much more.

IMPLICATIONS

GPS, even those as strong as NSDUH, are doomed by their nature to estimate poorly a rare and stigmatized behavior concentrated in a hard-to-track population. Although many European nations avoid reliance upon these surveys, many others follow the US model. Better estimation requires models that draw upon a variety of data sources, including GPS, to provide credible estimates. Recent methodological developments in selected countries can provide guidance. Journals should require researchers to critically assess the soundness of GPS estimates for any stigmatized drug-related behaviors with low prevalence rates.