Risk factors for type 2 diabetes

Research in risk factors for type 2 diabetes is moving at a breath-taking pace, and hundreds of risk factors have been identified. Age is the single most important risk factor for type 2 diabetes, and a large part of the current epidemic of type 2 diabetes seen in low-income countries is primarily explained by demographic changes, aging of the populations and declining mortality. However, the rapid global increase in incidence clearly supports that also biological, environmental and lifestyle-related factors play a major role for the development of type 2 diabetes. The current section summarises information on the most established risk factors for type 2 diabetes.

Association and causation in type 2 diabetes

An important use of epidemiological studies is the identification of modifiable causes of common diseases such as diabetes. In order to have firm evidence that a recommended intervention will have the expected beneficial effect, the observed association between the identified risk factor and the outcome must imply that the risk factor actually causes the disease. However, a statistical association does not necessarily infer causality. Some prefer the term risk marker for a variable that is quantitatively associated with a disease, but modification of the risk marker does not necessarily modify the risk of the outcome. Most likely, unmeasured confounding explains why a strong association may appear, even if no causal relationship exists between two variables.

During the last decade, a substantial number of biomarkers for diabetes have been discovered. Well-known examples include a strong association of non-alcoholic fatty liver disease or inflammatory markers with type 2 diabetes. Nevertheless, the extent to which these biomarkers are causally related to diabetes remains unclear.

Ideally, a causal association should be proved by randomized controlled trials, but this is not always possible due to ethical reasons. For instance, testing of toxic agents such as tobacco, alcohol and persistant organic pollutants that may cause diabetes is not possible in a controlled design. One way to deal with this problem in epidemiological research is to apply the “Mendelian Randomization” approach to analyses of possible risk factors and outcomes. The method uses the information that variants of the gene that encodes the particular risk factor, also increase the amount of the risk factor in the blood. Because these variants are inherited randomly, there is no likelihood of confounding factors, and an association between these variants and the developments of e.g. diabetes indicates, therefore, that increased risk factor levels cause diabetes. In this regard, Mendelian Randomization can be thought of as a natural randomized controlled trial. This method has been used for the study of CRP and diabetes [1], and findings from the study suggest, that increased blood CRP levels are not responsible for the development of insulin resistance or diabetes.

The high risk approach

The classical way to study risk factors for type 2 diabetes focuses on high-risk groups, because these individuals are driving the strongest associations between risk factors and disease. However, recent studies have shown that more than 90% of those developing diabetes are only slightly overweight, but not obese, before and at the time of diagnosis[2]. Identification of risk factors and evaluation of their impact may consequently not be the same for the individual person as for the society. Such findings support the ‘prevention paradox’, proposed by Geoffrey Rose more than 30 years ago, in which he stated that “a large number of people exposed to a low risk is likely to produce more cases than a small number of people exposed to a high risk” [3]. In the context of diabetes prevention, it may therefore not be optimal e.g. to focus only on promoting weight loss in the most obese individuals, but also aiming at prevention of small weight gains in the entire population (i.e. shifting the entire BMI distribution to the left).

Risk factors for diabetes are not the same in all groups

A large number of risk factors have consistently shown an association with diabetes across populations, such as age, obesity, and physical inactivity. However, for many risk factors with diabetes is not the same in all groups, and it is well known, that e.g. Mexican Hispanics and Asian populations are experiencing high levels of diabetes at much lower levels of BMI than European populations. These ethnic differences presumably depend on differences in body composition, as well as differences in energy intake, physical activity and genetic factors. Such data do raise concern about the ‘one-size-fits-all’ approach in evaluation of diabetes risk.

The impact of social change on health is relevant for majority populations in Europe and North America, but it is more transparent in populations where changes are more recent and dramatic such as Asian and many indigenous populations. Urbanisation is a strong risk factor for type 2 diabetes, and this variable is often included in prediction models of future diabetes. In low-income countries, urbanisation is strongly associated with diabetes, whereas this pattern is typically not seen in middle- and high income countries. Urbanisation is a complex process, which includes among other things dietary change, decreased physical activity, and socio-economic changes. But urbanisation is also a selective process where people, especially young people, move for many reasons, e.g., social, economic, educational, and health related reasons. It is most likely, that urbanisation will not imply the same risk of diabetes in all regions, and moreover, it is questionable whether the ongoing social transition can mirror the secular changes in diabetes risk.

Consequently, when assessing the relation between risk factors and diabetes, it is important to keep in mind that the size and direction of the association may vary not only across individuals and populations, but also over time.


  1. ^ Brunner EJ, Kivimäki M, Witte DR, Lawlor DA, Davey Smith G, Cooper JA, Miller M, Lowe GD, Rumley A, Casas JP, Shah T, Humphries SE, Hingorani AD, Marmot MG, Timpson NJ, Kumari M. Inflammation, insulin resistance, and diabetes--Mendelian randomization using CRP haplotypes points upstream. PLoS Med. 2008 Aug 12;5(8):e155. doi: 10.1371/journal.pmed.0050155.

  2. ^ Vistisen D, Witte DR, Tabák AG, Herder C, Brunner EJ, et al. (2014) Patterns of Obesity Development before the Diagnosis of Type 2 Diabetes: The Whitehall II Cohort Study. PLoS Med 11(2): e1001602. doi:10.1371/journal.pmed.1001602

  3. ^ Rose G. Strategy of prevention: lessons from cardiovascular disease. Br Med J (Clin Res Ed) 1981; 282(6279):1847-1851.


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