Risk factors of incident type 2-diabetes mellitus over a 3-year follow-up: Results from a large Australian sample
Introduction
Diabetes is a rapidly growing epidemic worldwide and the World Health Organization predicts that unless appropriate action is taken, by 2030 there will be at least 350 million people with type 2 diabetes mellitus (T2DM) in the world [1]. Diabetes is associated with cardiovascular and renal disease, leading to further morbidity, disability, and premature mortality [1], [2]. In Australia, the age-standardized prevalence of diabetes has increased from 1.5% in 1989–1990 to 4.2% in 2011–2012 [3]. Based on current trends, the prevalence of diabetes among adult Australians aged ≥25 years is projected to rise to 17% in 2025 [4]. Diabetes poses a substantial economic burden. The total estimated annual costs of diabetes for Australian adults aged ≥30 years was $10.6 billion in 2005, which equated to $14.6 billion in 2010 [5].
Given the health and economic burden and the importance of early interventions in improving disease outcomes, it is important to identify individuals at risk for developing T2DM. Risk prediction models could potentially help classify those who are at increased risk of having an undiagnosed condition, which could help with early diagnosis and management of diabetes. Identifying modifiable risk factors could also guide lifestyle interventions for diabetes prevention [6]. A recent systematic review concluded that the most commonly identified risk predictors of type 2 diabetes are demographic characteristics (i.e., age, sex, ethnicity), family history of diabetes, and cardio-metabolic health indicators (e.g., body mass index, hypertension, waist circumference). Some prediction models also examined lifestyle behaviors, such as physical activity and smoking [6]. Few studies, however, have considered emerging lifestyle risk factors, such as sedentary behavior and sleep [7], [8]. Some studies have suggested a potential link between psychological stress and incident diabetes, but this evidence warrants additional investigation [9], [10]. Furthermore, only a small number of studies included social determinants of health, such as social deprivation, which may be associated with diabetes incidence [11], [12].
Using data from a large Australian cohort, the current study describes the incidence of T2DM among a large cohort of middle-aged and older Australian adults without a diagnosis of diabetes who were followed up for around three years. Further, this study examined a broad range of risk factors, including socio-demographic characteristics, health status, family history, and lifestyle behaviors. In particular we hypothesized that family history and age would act as effect modifiers for some of these risk factors.
Section snippets
Study population
The analyses are based on the Sax Institute's 45 and Up study, a large cohort study of men and women 45 years and older from the general population of New South Wales (NSW), Australia. Participants were randomly sampled from the Medicare Australia (national health insurance) database, which included information on all Australian citizens and permanent residents, and some temporary residents and refugees who were residents of NSW. Eligible individuals were mailed an invitation to participate, an
Results
Of the 60,404 who participated in the 45 and Up study and the SEEF study, 59,210 answered the question about diabetes in both surveys, 4213 (7.1%) of whom reported T2DM at baseline. Of the 54,997 without T2DM at baseline, 888 reported incident T2DM in the follow-up study, which resulted in a cumulative incidence of 1.6% over 3.4 years, and an incidence rate (based on person–years) of 0.44% (95% CI: 0.41–0.47%). Specifically, the incidence rate was 0.53% (95%CI: 0.48–0.58%) for men, 0.37%
Discussion
In a large population-based cohort of middle-aged and older Australian men and women, we examined the incidence of T2DM during 3.4 years of follow-up and explored a series of socio-demographic, health and family history, and lifestyle predictors of T2DM incidence. We found that between 2006–2008 and 2010, the cumulative incidence over the follow-up period was 1.6% and the person–year incidence rate was 0.44%. To our knowledge, this is the third and largest Australia-based cohort study that
Conclusions
This study examined predictors of incident T2DM among a large population sample of Australian middle-aged and older adults. The incidence of developing T2DM over an average follow up of 3.4 years was 1.6% and a number of socio-demographic, health, and lifestyle risk factors for incident diabetes were identified. Understanding risk factors for incident T2DM could help identify at-risk populations and develop upstream preventive strategies to combat the epidemic of diabetes.
Conflict of interest
There are no conflicts of interest.
Acknowledgement
This study is funded by an Early Career Fellowship from the National Health and Medical Research Council (Ding).
References (51)
- et al.
The cost of diabetes in adults in Australia
Diabetes Res Clin Pract
(2013) - et al.
The dynamics of the relationship between diabetes incidence and low income: longitudinal results from Canada's National Population Health Survey
Maturitas
(2012) - et al.
The impact of income on the incidence of diabetes: a population-based study
Diabetes Res Clin Pract
(2013) - et al.
Revisiting lifestyle risk index assessment in a large Australian sample: should sedentary behavior and sleep be included as additional risk factors?
Prev Med
(2014) - et al.
Validity of self-reported height and weight and derived body mass index in middle-aged and elderly individuals in Australia
Aust N Z J Public Health
(2011) - et al.
Estimating the direct and indirect pathways between education and diabetes incidence among Canadian men and women: a mediation analysis
Ann Epidemiol
(2013) - et al.
Socioeconomic status and diagnosed diabetes incidence
Diabetes Res Clin Pract
(2005) - et al.
Changing places. Do changes in the relative deprivation of areas influence limiting long-term illness and mortality among non-migrant people living in non-deprived households?
Soc Sci Med
(2004) - et al.
Locality deprivation and Type 2 diabetes incidence: a local test of relative inequalities
Soc Sci Med
(2007) - et al.
The cardiovascular toll of stress
Lancet
(2007)
Stress hormones in health and illness: the roles of work and gender
Psychoneuroendocrinology
Correlates of physical activity: why are some people physically active and others not?
Lancet
Epidemic obesity and type 2 diabetes in Asia
Lancet
Screening for type 2 diabetes: report of a World Health Organization and International Diabetes Federation meeting
Mortality in people with Type 2 diabetes in the UK
Diabet Med
Prevalence of diabetes
Lifetime risk and projected population prevalence of diabetes
Diabetologia
Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting
BMC Med
Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis
Diabetologia
Quantity and quality of sleep and incidence of type 2 diabetes: a systematic review and meta-analysis
Diabetes Care
An association of adverse psychosocial factors with diabetes mellitus: a meta-analytic review of longitudinal cohort studies
Diabetologia
Perceived stress and incidence of Type 2 diabetes: a 35-year follow-up study of middle-aged Swedish men
Diabet Med
Validating self-report of diabetes use by participants in the 45 and Up Study: a record linkage study
BMC Health Serv Res
Census of population and housing: socio-economic indexes for areas (SEIFA), Australia
Eat for health: Australian dietary guidelines
Cited by (48)
Trends in risk factors and management strategies used by people with type 2 diabetes in New South Wales, Australia
2022, Preventive MedicineCitation Excerpt :Sufficient fruit consumption was defined as 2 serves/day (National Health and Medical Research Council, 2013), and vegetable consumption ≥3 serves/day. Although the recommended vegetable intake is 5 serves/day, 3 serves has been used to monitor NSW trends due to the low prevalence of meeting the recommendations (Centre for Epidemiology and Research, 2009; Ding et al., 2015). Sufficient physical activity in the NSW survey was defined as ≥150 min/week on five separate occasions, and minutes spent in vigorous-intensity physical activity was weighted by a factor of two (NSW Ministry of Health, 2021).
Prevalence, incidence and risk factors of diabetes in Australian adults aged ≥45 years: A cohort study using linked routinely-collected data
2020, Journal of Clinical and Translational EndocrinologyInvestigating spatial convergence of diagnosed dementia, depression and type 2 diabetes prevalence in West Adelaide, Australia
2020, Journal of Affective DisordersCitation Excerpt :An Australian study suggests that a minimal 10% reduction in dementia diagnoses related to modifiable risk factors could save up to AUD$280 million dollars (Moore et al., 2015). Among modifiable risk factors for dementia, several studies have focused on T2D (Almeida et al., 2017; Ashby-Mitchell et al., 2017; Baumgart et al., 2015; Chatterjee et al., 2016; Cukierman et al., 2005; Davis et al., 2017; Ding et al., 2015; Kontari and Smith, 2019; Ravona-Springer and Schnaider-Beeri, 2011; Sutherland et al., 2017) and depression (Almeida et al., 2017; Hillen et al., 2017; Kontari and Smith, 2019; Norton et al., 2014). Both T2D and depression are each significant chronic diseases.
Predisposing factors of type 2 diabetes mellitus and the potential protective role of native plants with functional properties
2019, Journal of Functional FoodsIncident Type 2 Diabetes Among Individuals With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study
2019, American Journal of Kidney DiseasesCitation Excerpt :However, it should be noted that a significant association does not necessarily imply predictive utility, which seems to be the case here (Harrell C for the multivariable model including fasting blood glucose did not change when family history was excluded), suggesting that knowledge of family history of DM is of limited incremental value in making clinical decisions related to the prevention of T2DM among individuals with CKD. The lack of significant associations of other risk factors in multivariable models is at odds with the literature on T2DM risk tools developed in the general population, in which numerous risk factors, such as age, hypertension, smoking, and BMI, typically display significant adjusted associations with T2DM risk.4,9,30,31 The effects of these factors may be mediated by measures of glycemic control.