Introduction

The question of who should be targeted for diabetes risk reduction is not easy to answer because the effect of an intervention program to prevent type 2 diabetes (T2DM) in adulthood depends on the setting where the intervention is performed, the adequateness of the intervention in addressing the high-risk clientele, accessibility and affordability, and a variety of additional variables [1]. However, the main considerations when deciding who should be targeted for diabetes prevention are the adequateness and affordability of the interventions available after the high-risk person has been identified. Screening for diabetes risk makes no sense without the availability of a successful and sustainable intervention program [2]. Interventions can have various approaches, strategies and concepts. Furthermore, strategies for targeting people at high risk will vary significantly between different settings and different groups, such as adults and children/adolescents. In this article, we broadly highlight several of the most widely accepted and discussed risk factors for T2DM in both adults and children/adolescents along with clinically relevant methods of identifying high-risk individuals for referral into diabetes prevention programs. This will allow researchers, interventionists, and policy makers to consider approaches that are best suited to their circumstances.

It is acknowledged that along with strategies for identifying and intervening in those with a high risk of a widely prevalent condition such as T2DM, it is also fundamentally important to employ initiatives that are aimed at shifting the distribution of known risk factors, such as body mass index (BMI) in adults or BMI percentiles in childhood, within the entirety of the population. In that sense, we should all be considered targets of diabetes risk reduction. However, this article is intentionally focused on the identification of high-risk populations that will help to address the key issues around the prevention of T2DM in health care settings.

Risk Assessment in Clinical Practice

Because subjects with impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT) are at increased risk to develop T2DM, they have been the focus of most previous prevention studies [3–5]. However, in long-term follow-up studies, only about half of subjects with IFG and/or IGT develop T2DM [6]. Moreover, many subjects with normal glucose tolerance (NGT) develop T2DM [7], and, in longitudinal studies, about 40% of subjects who developed T2DM had NGT at baseline [6]. Thus, by solely relying on IFG and/or IGT to identify subjects at increased T2DM risk, many individuals who could have benefited from a prevention program will have been left unidentified. To overcome some of these limitations, several predictive models have been developed to identify subjects at increased risk for T2DM [8–16, 17•, 18•]. These models are based upon multivariate regression of risk factors of T2DM (i.e. age, gender, BMI, diabetes family history, fasting plasma glucose [FPG], and lipid profile). Although hemoglobin A1c (HbA1c) reflects long-term glycemic control, it never has been included in any of the multivariate predictive models. Recently, the American Diabetes Association (ADA) has changed the diagnostic criteria for diabetes (HbA1c > 6.5%) and high-risk individuals (HbA1c = 5.7% to 6.5%) [19].

Developing, evaluating and implementing systematic strategies for identifying those at risk of developing T2DM are a prerequisite for ensuring that national and regional health care authorities can meet the growing demand for initiatives and targets aimed at the prevention of T2DM. T2DM is preceded by a period of impaired glucose regulation (IGR), where glucose levels are above normal ranges but do not yet meet the diagnostic criteria for T2DM. This provides a window of opportunity in which to intervene and reduce the risk of progressing to T2DM through lifestyle or pharmaceutical intervention. It has been established through rigorous economic modeling that screening for both T2DM and IGR is likely to be cost-effective and is now recommended by a number of National and International Diabetes Associations [20–23, 24••]. However, detecting IGR within primary health care settings raises important issues that need to be addressed.

Successful diabetes prevention programs have included participants on the basis of having IGT [25], which is diagnosed through an oral glucose tolerance test (OGTT), traditionally viewed as the gold standard method of identifying an IGR. IGT, unlike other forms of IGR, is primarily characterized by peripheral insulin resistance and therefore highly modifiable through lifestyle change, such as increased physical activity [26]. However, there are important practical limitations that have to be considered when performing an OGTT within a routine health care setting. For example, OGTTs represent a significant burden on health care resources and patient time and are subject to a high level of measurement error when conducted outside the rigorous standardized setting of a research environment. Therefore, advocating the routine use of OGTTs as a screening tool in primary care is unlikely to be feasible in most health care settings.

In addition to issues around measurement, identifying those with IGR is also hampered by the sheer number of individuals meeting this risk factor within the population; for example, within some adult population groups prevalence rates can be as high as 50% [27]. Therefore, numbers with IGR in the population are likely to greatly exceed those that can be referred into prevention pathways considering the financial and infrastructure constraints inherent within primary care.

Given the two important considerations of measurement and prevalence, it is obvious that pragmatic strategies are needed to identify and prioritize those with the highest risk of T2DM within routine primary care for referral into prevention programs. There is now emerging international consensus (based on screening approaches used in practice in the United States, Germany, Australia, Finland, and other countries) that a targeted, staged approach is the most effective way of meeting this demand [24••, 28, 29••]. For the adult population, this commonly involves using a validated risk score in the first stage to identify those with the highest risk of progressing to T2DM and then using a single blood test to confirm classification of IGR and/or rule out T2DM [18•]. Recent pilot data have shown that this approach is likely to be more cost-effective than proceeding straight to a blood test in a high income country [30]. This approach has also been indorsed by the National Institute for Health and Clinical Excellence (NICE), United Kingdom.

NICE recently convened an expert panel to systematically review and evaluate the entirety of the available evidence in the formulation of new diabetes prevention recommendations; this process led to the recommendation that a stepped strategy involving risk scores followed by fasting glucose (5.7–6.9 mmol/L) or HbA1c (6.0–6.4%) testing should be used in the identification of IGR within the general adult population [20]. Using a large dataset of over 8000 adult individuals screened for T2DM through the Leicester arm of the ADDITION (Anglo-Danish-Dutch Study of Intensive Treatment and Complication Prevention in Type 2 Diabetic Patients Identified by Screening in Primary Care) study [31], 10% to 15% of the adult population within a multiethnic primary care–based population would typically meet this stepped criteria for IGR depending on the risk score and biochemical measure used (unreported observation: Melanie Davis). For childhood and adolescence, criteria when an OGTT should be performed are discussed later on.

Risk Scores

The Finnish Diabetes Risk Score (FINDRISC) questionnaire, developed and validated in Finland, is a practical screening tool to estimate the diabetes risk and the probability of asymptomatic T2DM in adults [17•]. Several risk assessment tools have been developed for a variety of different settings [18•]. The FINDRISC questionnaire is the most widely used risk tool internationally [17•]. It uses weighted scores from eight easily accessible risk characteristics to calculate an overall risk profile. It can be used as a method of identifying those with prevalent T2DM or IGR or those with a high risk of developing T2DM in the future. FINDRISC has been shown to have good sensitivity (~ 0.8) and specificity (~ 0.8) at predicting the 10-year absolute risk of T2DM in a European population [17•]. It is widely recognized that risk scores need to be tailored to the population in which they are to be used, as differing population characteristics and distribution of risk factors can affect the weighting assigned to each variable within the risk score [29••]. Therefore, risk scores that are based on, or similar to, FINDRISC have been developed and validated across different populations, including Germany, Denmark, and the United Kingdom [13, 32–35]. FINDRISC is currently evaluated in a large number of studies worldwide indicating differences in its performance and diabetes prediction but it reveals the most commonly used risk score, whereas in some populations modified FINDRISC scores perform better. The results of a recent study indicate that the FINDRISC also can be applied to detect insulin resistance in a population at high risk of T2DM and predict future impairment of glucose tolerance [14].

FINDRISC is typically used as method of self-assessing diabetes risk. However, given the need to incorporate risk identification strategies within routine care, risk scores, utilizing commonly collected and coded variables, have been developed for use within primary care. This allows automated platforms to be used on patient databases to quickly and easily rank individuals for diabetes risk. The United Kingdom has led this approach internationally where three different practice-based risk scores, of varying utility, have been developed [36, 37••, 38]. For example, the Leicester Diabetes Risk Score has been modified for use within general practice through the development of a software package that automatically ranks diabetes risk using commonly coded patient level variables [35, 38].

As well as forming part of a stepped strategy for assessing diabetes risk, self-assessment risk scores can be valuable in their own right in helping promote a wider agenda around the importance of assessing and monitoring diabetes risk within the general population. For example, the British-based charity Diabetes UK hosts an online diabetes risk assessment tool that has been extensively used and promoted alongside a wider public health agenda aimed at the prevention of chronic disease (http://www.diabetes.org.uk/riskscore) leading to increased awareness of personal disease susceptibility. In addition, given their pragmatic nature, risk scores can be used as the primary method of detecting diabetes risk where resources are scarce and the opportunity for blood testing is limited. However, it is important that risk scores are developed or modified and then validated for the population they are used in.

Blood Tests

Although a range and combination of blood tests for adults have been proposed for classifying diabetes risk, including 2-hour or 1-hour postchallenge values, in reality fasting blood glucose or HbA1c are the only values that are likely to fit the criteria of being pragmatic, clinically relevant, and valid. This is consistent with recent recommendations from the United Kingdom [20]. Fasting glucose is well recognized as a method of assessing T2DM risk; ranges of 5.5 to 6.9 mmol/L or 6.0 to 6.9 mmol/L have been proposed as high-risk categories by ADA and World Health Organization (WHO), respectively. The use of HbA1c is more controversial and less well defined. A consensus approach by WHO recently included the use of HbA1c greater than 6.5% as a diagnostic threshold for T2DM. However, there is no clear consensus on how or whether HbA1c should be used to classify diabetes risk below this level. The ADA tentatively suggested that an HbA1c value of between 5.7% to 6.4% indicates a high risk of T2DM, whereas an international expert committee suggested a range of 6.0% to 6.4% [19, 22]. Prospective data from the United Kingdom support the use of 6.0% to 6.4%, as those in this group were found to have a risk of future T2DM that was twice that in the range of 5.5% to 5.9%. However, other data from Germany suggest 5.7% is likely to have the best sensitivity and specificity at detecting future diabetes risk [39•] but demonstrate that the combination of HbA1c and the 1-hour plasma glucose concentration in predicting future diabetes risk was significantly better in a multivariate model than either one of them alone. The 1-hour plasma glucose concentrations have previously been shown to be strong predictors of T2DM risk [40–42] and also other chronic disease [43, 44]. Further, the optimal HbA1c cut point for identifying subjects at increased diabetes risk is 5.65% [39•, 45] and not 6.0% as originally suggested by the ADA expert committee [19]. If a HbA1c greater than 6% was used to identify subjects at increased risk for future T2DM, only about one third of subjects who developed T2DM would have been identified. Thus, use of a HbA1c cut point of 5.65% would identify many additional high-risk individuals who could benefit from an intervention program [39•, 46, 47].

Additional Risk Factors

Physical Inactivity

Epidemiologic, experimental, and randomized controlled clinical trial level evidence have all consistently demonstrated that levels of physical activity are centrally involved in the regulation of glucose homeostasis, independent of other factors including adiposity [25, 48–50]. A modest increase in walking activity, toward levels that are consistent with the minimum recommendations, significantly improved 2-hour glucose levels by 1.3 mmol/L over 12 months in high-risk overweight and obese individuals, despite no change was obvious in body weight or waist circumference [51]. This corresponded to a greater than 60% risk reduction of developing T2DM within 24 months [52] and was consistent with findings from other studies [53]. Therefore, physical activity promotion should be the cornerstone of any diabetes prevention program. However, the role of physical inactivity in helping identify diabetes risk is less clear and more problematic for several reasons.

First, physical inactivity is a nearly universal condition: it has consistently been shown that 50% to 80% of the population in both developed and developing countries fail to meet the minimum recommendations for health [54–56]. When physical activity levels are objectively measured, rather than by subjective self-report, as much as 95% of the population are considered inactive [56, 57]. Therefore, commonly used definitions of physical inactivity do not provide a clear mechanism for stratifying diabetes risk. Second, methods that rely on individuals self-reporting their activity levels are highly inaccurate and unreliable. For example, an internationally used and validated self-reported measure of physical activity described as little as 10% of the variation in objectively measured levels through accelerometry [58]; being in contrast to simple measures of adiposity, such as BMI or waist circumference, which are reasonably accurate on a population level. For these reasons, self-recording levels of physical (in)activity has not been shown to add to the predictive power of diabetes risk scores or to be usefully incorporated into other methods of quantifying diabetes risk. However, it is important that physical inactivity, as with other lifestyle variables, is considered for the individual assessments of diabetes risk.

Waist Circumference

Waist circumference is a powerful indictor of metabolic dysfunction as it represents a surrogate indicator for the accumulation of visceral fat [59, 60]. It is well established that visceral fat not only plays a role in the human energy metabolism, but it also actively secrets hormones and peptides (adipocytokines), such as monocyte chemotactic protein-1, retinol-binding protein 4, as well as a variety of interleukins together with tumor necrosis factor-α, which enhance the development and/or the progression of chronic diseases, including insulin resistance and chronic inflammation. There is a strong risk association between an increase in visceral fat mass and risk of developing T2DM [61].

From a public health point of view, waist circumference presents a clinically valuable measure because of accessibility [62], as no laboratory investigation is needed and no invasive procedure is necessary. In addition, direct patient feedback during an intervention program is possible. As it is known that the metabolic activity of visceral fat is higher than that of subcutaneous fat, alterations in baseline metabolic turnover from an individual patient during an intervention associated with increased physical activity would predominantly reduce the visceral fat depot. It might be concluded that any reduction in the visceral fat depot is accompanied by a reduction in most of the visceral adipocyte-secreted hormones and therefore has beneficial effects for prevention of chronic diseases. Waist circumference provides a valid measure to predict diabetes risk in the adult population and has been included in the criteria to define the metabolic syndrome [63]. For consistency with the criteria for adults, the measurement of waist circumference has meanwhile also been included in the definition of the metabolic syndrome in children and adolescents [64••].

Genetic Factors

Another very hot topic in developing strategies for identifying people with increased risk for chronic diseases is genetic factors. Most of the processes involved in human, endocrine, and metabolic regulation involve enzymes and related receptors or cofactors that all correlate in an associated gene or act as gene regulators. From this point of view, we can expect a direct link to the influence onto metabolic and endocrine processes and by this with an association with increased diabetes risk. This by itself would be an attractive and easy to detect target for diabetes risk identification. Unfortunately, until today the genetic studies only show a very modest effect size suggesting that most of the studies were underpowered to detect an association between genetic variation and physiologic processes [65•, 66••]. Therefore, in the past, large consortia have been founded to combine the quality and power of a number of different clinical studies to explore the interaction between genetic variants and the detailed physiologic processes. Several research groups have together identified more than 100 loci for T2DM-related risk factors including for BMI (GIANT: 15 loci) [67, 68, 69•], quantitative glucose, proinsulin and insulin traits (MAGIC: 20 loci) [65•, 66••, 70–73], diabetes (DIAGRAM: 42 loci) [65•, 74–77] , lipids (Global Lipids Genetics Consortium: 94 loci) [68, 78], blood pressure (Global BPGen: 8 loci) [79–81], and cardiovascular disease (FUSION: 11 loci) [82]. This information helps to explore and describe new pathophysiologic mechanisms for diabetes risk development but this new information does not yet provide new and accurate diagnostic tools for diabetes risk detection in clinical practice. The future gain in knowledge about the association of genetic variability and physiologic processes together with environmental influences will provide a highly attractive tool for automated predictive risk detection by using genetic information to identify people with increased diabetes risk. Especially the cost reduction of genetic analysis might lead to a broader application of available genetic diagnostic tools as well as to the development of adequate ethics strategies and guidelines. Finally, the individual patient genetic characteristics will not only enable diabetes risk identification, but will also allow to identify the more effective individual intervention by identifying those who are more responsive to physical activity or nutritional intervention as well as pharmaco-preventive intervention.

Prenatal Risk Factors

Both pregestational and gestational diabetes mellitus are associated with a variety of fetal, perinatal, and postnatal complications. If maternal blood glucose during pregnancy is not optimally controlled, fetal growth disturbances causing increased (i.e. macrosomia) or decreased (intrauterine growth retardation [IUGR] leading to small for gestational age [SGA]) birth weight may be a problem of major concern [83]. Epidemiologic studies performed in large cohorts have clearly shown that the prevalence of overweight and obesity in childhood and adolescence is significantly higher in children of diabetic mothers compared to healthy, normal weight mothers [84]. The Barker hypothesis of the “thrifty phenotype” suggests that IUGR and suboptimal postnatal catch-up growth are linked to a markedly higher risk for T2DM and hypertension later in life [85]. Meanwhile, an inverse relationship between birth weight and FPG, fasting plasma insulin, the prevalence of established or gestational T2DM, measures of insulin resistance, and measures of insulin secretion has been clearly shown [86]. It was already proposed in 1988 by Reaven and is now well established that among the long-lasting effects and the main complications of macrosomia and IUGR/SGA are an increased risk for overweight and obesity later in life, leading to a high tendency to develop complications associated with the metabolic syndrome (ie, cardiovascular disease and T2DM) [85, 86]. In addition, maternal overweight/obesity or excessive weight gain during pregnancy are also strong predictors for the development of obesity and the metabolic-cardiovascular syndrome in the offspring later in life [83].

Although IUGR and excessive fetal growth (macrosomia) originate from different causes, both phenomena show a clear association with features of the metabolic syndrome later in life as well as related long-term consequences. The exact pathophysiologic mechanisms underlying these long-term effects are not fully elucidated, but factors that seem to be involved include maternal insulin resistance and hyperinsulinemia during pregnancy [87], fetal hyperleptinemia caused by maternal obesity, increased maternal weight gain during pregnancy or maternal insulin treatment during pregnancy [88•], hypothalamic changes (i.e. fetal nutritional imbalances leading to long-lasting changes in hypothalamic centers that control energy and glucose homeostasis), [89] and, probably most importantly, epigenetic changes (i.e. the molecular mechanisms that govern gene expression in a time- and cell-type–dependent fashion) [88•]. For the latter, it has been suggested that early environmental exposures such as maternal hyperglycemia or obesity during pregnancy may alter the programming of genes by epigenetic marking, resulting in long-term changes of the expression of genes associated with energy and glucose homeostasis [85, 90].

Given the above, women, either planning or during pregnancy, are an important population to target in reducing the future burden of T2DM. In particular, women should be supported to avoid excessive weight gain during pregnancy, and those with any form of diabetes should be supported and tightly monitored to achieve optimal blood glucose levels. In addition, a tight regimen of dietary and glycemic control and physical activity in children born to obese or diabetic mothers or children who had antenatal growth disturbances is also urgently needed.

Diabetes Risk in Childhood and Adolescence

The prevalence of childhood obesity has increased dramatically during the past decades although there is emerging evidence that prevalence rates seem to have stabilized at present, albeit at high levels, especially in the younger age groups [91••, 92•] Overweight and obesity now affect between 15% to 30% of all children and adolescents in many industrialized countries. The rise in childhood overweight and obesity has dramatically altered the demographic profile of chronic disease in affected countries. For example, T2DM, once a clinical rarity in younger adults (<40 years) and children, now has prevalence rates estimated to have increased by up to 10-fold in recent decades [93]. This shift in the profile of T2DM has a serious consequence as its emergence in younger age groups represents an extreme phenotype that magnifies the disease profile observed in adults. Risk factors for the development of T2DM in childhood and adolescents include [94]:

  • T2DM of first- or second-degree relatives

  • Morbid obesity (BMI > 99.5 percentile)

  • Ethnic background (East Asians, African-American, Hispanics)

  • Clinical signs of insulin resistance or associated features (syndrome of polycystic ovaries, acanthosis nigricans, dyslipidemia, elevated liver enzymes)

In addition to the development of T2DM, affected individuals are also at higher risk for the development of significant cardiovascular comorbidities early in life: Compared to age-matched healthy controls, incidence of myocardial infarct in younger people with T2DM has been shown to be fourfold higher than in late-onset type 2 diabetics and 14-fold higher than in people without diabetes [95]. Preliminary data from adolescents with T2DM in Canada, followed up for 9 years, found that the mortality during this period was almost 10%. Along with increasing the prevalence of chronic disease and mortality rates in younger age ranges, childhood obesity also significantly increases the risk of chronic disease into adulthood [96]. Thus, the emergence of deleterious lifestyle practices and obesity in younger age ranges will have a devastating clinical and societal legacy that is only just beginning to emerge. The focus of health care policy and research, which has commonly targeted those over 40 years of age, has lagged behind this substantive shift in the demographic profile of obesity and chronic disease. However, if left unconsidered, it is clear that this will become one of the primary clinical priorities within the next couple of decades. Therefore, high-quality research is urgently needed to investigate optimal methods of identifying and treating diabetes risk in children and adolescents. This includes the development of integrated risk scores that are lacking in this group. However, at present the WHO recommends that, starting at 10 years of age, an OGTT should be performed in overweight (BMI > 90th percentile) children or adolescents who present with at least two additional risk factors mentioned above or several clinical signs or associated sequelae of insulin resistance [94]. Once diagnosed, “conservative” approaches including lifestyle changes, promoting physical activity, and assessing and optimizing dietary habits should be the main focus of intervention at that age group. Metformin [97], a common first- or second-line therapy for adults, may also be appropriate for children and adolescents with diagnosed T2DM, and clinical studies for the use of metformin in IGT in the pediatric population are underway. It is crucial that children and adolescents with T2DM are seen by a pediatric endocrinologist/diabetologist to receive comprehensive diabetes health education and long-term clinical care within a specialized center.

Conclusions: Who Should Be Targeted for Diabetes Prevention and Diabetes Risk Reduction?

In this article we discussed the relevance of several risk factors to develop T2DM and its potential as an indicator for diabetes risk reduction. But how should this procedure be implemented into clinical practice? The clinical environment sets a number of limitations because only a selective clientele of adult patients is accessible—those who go to a physician due to disease burden, whereas the majority of the pediatric population is regularly seen by a pediatrician for routine medical checkups, vaccinations, or other reasons and might then be screened for relevant risk factors. Conversely, the clinical environment enables a more comprehensive and targeted approach due to the availability of diagnostic and treatment as well as intervention procedures. The public health environment offers a more widespread accessibility to target populations and to identify people at risk. The public health strategy is more related to address population-embedded risk behavior to be addressed by comprehensive health policy.

For a clinical applicable approach to target diabetes risk reduction we recommend the following:

  1. 1.

    Screen the adult population by using the FINDRISC score or a comparable risk score as well as available clinical data by screening computer databases.

  2. 2.

    Where possible, those above a predefined high-risk threshold level should have their risk status confirmed, and the presence of T2DM ruled out, by a simple measure of glycemia, such as fasting glucose or HbA1c.

  3. 3.

    In children older than 10 years of age, an OGTT should be performed in overweight (BMI > 90th percentile) subjects who present with at least two additional risk factors: T2DM of first- or second-degree relatives; morbid obesity (BMI > 99.5 percentile); ethnic background (East Asians, African-American, Hispanics); and clinical signs of insulin resistance or associated features (syndrome of polycystic ovaries, acanthosis nigricans, dyslipidemia, elevated liver enzymes).

  4. 4.

    Those children/adolescents and adults confirmed to have a high-risk status, or even confirmed IGT/T2DM, are eligible for lifestyle intervention programs (all age groups) or pharmaco-preventive strategies (mainly adults).

A recommendation for the adult population from a public health perspective can be the following:

  1. 1.

    Screening by using the FINDRISC score (or comparable risk scores) to increase awareness for diabetes risk factors in the population and allowing multiple pathways for confirmation of risk status by biochemical measure (ie, through pharmacies).

  2. 2.

    Enabling the accessibility and availability of lifestyle intervention programs on a population level for those persons interested in an structured lifestyle intervention program.

There are no validated diabetes prevention strategies/guidelines in childhood and adolescence as there are for the adult population. However, several risk factors toward the development of the metabolic syndrome and T2DM in the pediatric population have been identified. These factors present potential/crucial targets for the development of effective measures/methods to prevent onset of pediatric diabetic disease.

In summary, preventive measures for candidates at risk to develop T2DM are crucial and should aim at reducing the occurrence of excessive weight gain in children and adults by including tight dietary control and promotion of physical activity.