High-risk groups approaches and population stratification
The high-risk approach is based on establishing a cut-off point for one or multiple risk factors, and then focusing on the people at greatest risk of a condition, although the contribution of this group of people to the overall population burden of the condition may, in fact, be little. This may, however, not be case if the high-risk group includes people with established disease who contribute a large fraction to the overall burden of a disease. High-risk individuals, in particular those diagnosed with a condition, are usually motivated to change and also rely on the immediate motivation of health professionals.
The high-risk strategy is expected to be more efficient when targeting people at high overall risk rather than focusing on high risk in terms of single risk factors. Interventions in addictive substance use need to account for a number of determinants in addition to the amount of substance intake, including variables such as age, gender, cultural context, socioeconomic situation, and so on (see also Chapter 4 on drivers of harm) that influence substance use patterns in individuals and consumption trends in the population (see Box 5.2).
Box 5.2 Risk function and prevention strategies
The validity of the prevention paradox depends on the shape of the risk function; therefore, the contribution of moderate drinkers to the overall burden of alcohol is expected to vary across the spectrum of alcohol-attributable disabilities. If the risk function for a given disability is linear (Figure 5.1), moderate drinkers contribute the largest fraction to population-level harm. For disabilities with a threshold-like shape, the prevention paradox does not seem to apply, such as the case of alcohol-attributable liver cirrhosis. In contrast, alcohol- related accidents have been found to show a smoother and less convex risk curve, and can mostly be related to occasional intoxication rather than to overall annual intake of alcohol; hence the contribution of moderate drinkers to this set of problems is expected to be more significant (Skog, 1999). Identifying the underlying causes of the population distribution of a risk factor, and combining the population strategy with a high-risk strategy is the most efficient approach in most situations.
Segmenting the population into different strata according to the level of exposure to predictive risk factors is increasingly being considered as a ‘third way’ between high-risk and whole-population approaches (Burton et al., 2012; Garcia-Closas et al., 2014). A stratified approach is expected to optimize the potential of preventive interventions at whole-population level and to moderate the stigmatization of high-risk groups (see Figure 5.3). It assumes that the population can be divided into multiple
Figure 5.3 Stratified prevention strategies.
Reproduced with permission from Burton H, Sagoo GS, Pharoah P, and Zimmern RL. Time to revisit Geoffrey Rose: strategies for prevention in the genomic era?. Italian Journal of Public Health, volume 9, issue 4, Copyright © 2012 Epidemiology, Biostatistics and Public Health.
Box 5.3 The potential of a stratified approach for risk profile-specific prevention
The stratified approach is based on the assumption that the population can be divided into multiple groups based on the identification, measurement, and stratification of risk determinants for a given condition. This approach is applicable to the entire population and allows for the identification of specific preventive strategies throughout the continuum of risk for addictive substance use and behaviours, in addition to the traditional high risk vs. whole-population dichotomy (Burton et al., 2012).
groups based on the identification, measurement, and stratification of risk determinants for a given condition (see Box 5.3).
Genome-wide association studies have contributed to a better understanding of the genetic predisposition and biological pathways to complex diseases. It is also recognized that the onset of common chronic disorders results from a combination of genetic, environmental, and lifestyle factors. It is known that populations and individuals with the same genetic profile show varying prevalence rates of a disease under different environmental conditions. The variations in gene expression may be explained by the variations in exposure to specific environmental factors and in lifestyle behaviours; hence, it is crucial to identify those factors and behaviours determining the population’s overall risk exposure. Determinants used for stratification should optimally include the three types of factors. One core assumption of the current conceptualization of the stratified approach is that the associations between genetic and environmental factors are multiplicative (Garcia-Closas et al., 2014). The use of genetic screening at population level is considered as a tool for risk stratification across the whole population in order to provide differentiated prevention programmes to each population stratum (Burton et al., 2012). However, the implementation of genetic testing in healthcare is still facing a number of relevant challenges, including false-positive results, incidental findings, and ethical, legal, and social implications (van El et al., 2013).
Gene mapping studies have also been applied to identify risk genes for nicotine, alcohol, cocaine, and opiates (Thorgeirsson et al., 2008; Gelernter et al., 2014a, 2014b, 2014c). In the case of addictive substance use and behaviours, the impact of genetics has been recognized to be modulated by the environmental exposure, indicating, for instance, that being exposed to a context where availability is being controlled and use is being supervised lowers the expression of genetic predisposition to alcohol use (Dick et al., 2009). Substance use should be seen as occuring along a continuum from non-problematic to problematic use covering potentially harmful use and addictive substance use, where transition, both back and forth, along the continuum is possible. Initiation in use is more influenced by environmental factors, while transition to problem use is more influenced by individual and genetic factors (Gell et al., 2016). Thus, it can be argued that measures targeting socioenvironmental changes,
Box 5.4 Environmental and lifestyle exposure impact on gene expression
The variations in gene expression may be explained by the variations in exposure to specific environmental factors and in lifestyle behaviours that determine the overall risk exposure. Although genetic screening is considered as an effective tool for population-level risk stratification, it is yet to overcome a number of relevant technological and implementation challenges, including overlapping genetic influences across a variety of addictive substances, false-positive results, incidental findings, and ethical, legal, and social implications.
including monitoring of use, urban planning, and leisure and peer group alternatives, are expected to have a harm-preventive impact at the population level. The use of genetic testing may not actually increase the impact of such measures, while it would certainly result in relevant additional costs and raise relevant ethical and social issues.
Stratification of the population according to meso- and macro-level variables such as socioeconomic conditions, social and physical environmental contexts, and access to welfare resources may result in effective and cost-effective differentiated prevention strategies in addictive substance use. The need for contextualizing population strategies at meso- and macro-levels is supported by evidence showing that the social welfare system and gender equity of a country seems to determine to a large extent how education, employment, and family roles are associated with, for instance, heavy drinking (Kuntsche et al., 2006), and that consequences of similar drinking patterns are more severe for those with lower socioeconomic status (Makela and Paljarvi, 2008) (see Box 5.4).