Elsevier

Primary Care Diabetes

Volume 12, Issue 1, February 2018, Pages 13-22
Primary Care Diabetes

Original research
Predictors of undiagnosed prevalent type 2 diabetes – The Danish General Suburban Population Study

https://doi.org/10.1016/j.pcd.2017.08.005Get rights and content

Highlights

  • BMI and self-reported cardiovascular disease predicts undiagnosed T2DM.

  • LRAS is superior than DDRS and FINDRISC in predicting undiagnosed T2DM and SCORE  5.

  • SCORE performed best in predicting pre-diabetes.

  • Low education level was a predictor of undiagnosed T2DM but seems of less importance.

Abstract

Aims

To investigate how self-reported risk factors (including socioeconomic status) predict undiagnosed, prevalent type 2 diabetes mellitus (T2DM). To externally validate Leicester Risk Assessment Score (LRAS), Finnish Diabetes Risk Score (FINDRISC) and Danish Diabetes Risk Score (DDRS), and to investigate how these predict a European Heart SCORE  5% in a Danish population study.

Methods

We included 21,205 adults from the Danish General Suburban Population Study. We used relative importance calculations of self-reported variables in prediction of undiagnosed T2DM. We externally validated established prediction models reporting ROC-curves for undiagnosed T2DM, pre-diabetes and SCORE.

Results

More than 20% of people with T2DM were undiagnosed. The 7 most important self-rated predictors in sequential order were high BMI, antihypertensive-therapy, age, cardiovascular disease, waist-circumference, fitness compared to peers and family disposition for T2DM. The Area Under the Curve for prediction of undiagnosed T2DM was 77.1 for LRAS; 75.4 for DDRS and 67.9 for FINDRISC. AUCs for SCORE was 75.1 for LRAS; 62.3 for DDRS and 54.3 for FINDRISC.

Conclusions

BMI and self-reported cardiovascular disease are important risk factors for undiagnosed T2DM. LRAS performed better than DDRS and FINDRISC in prediction of undiagnosed T2DM and SCORE  5%. SCORE performed best in predicting pre-diabetes.

Introduction

The number of patients with type 2 diabetes (T2DM) is increasing worldwide [1], [2] and studies suggest that up to 50% of prevalent T2DM are undiagnosed dependent on regional differences and diagnostic methods [3], [4], [5], [6]. Many newly diagnosed patients already have evidence of complications at diagnosis [7]. Pharmacological treatment and changes in lifestyle to prevent or postpone the onset of macro- and micro-vascular complications are important interventions [8]. As uncertainty persists concerning benefits of population-based screening for diabetes [6], [9] – opportunistic, targeted screening to detect undiagnosed T2DM [3], has been the recommended strategy [6], [10]. Several predictive risk-scoring tools are available, focusing on clinical observations and anamnestic information [11], [12]. But in order to enhance detection of undiagnosed T2DM, by encouraging initial response rate and reduce the number needed to investigate, targeted screening for undiagnosed T2DM, using self-assessment tools (Apps or questionnaires), have been suggested [13]. These scores have been reported to be efficient in detection of undiagnosed diabetes [6], [13], [14]. Two Scandinavian models have previously been validated, The Danish Diabetes Risk Score (DDRS) [6], [15], [16] and the Finnish Diabetes Risk Score (FINDRISC) [11], [17]. It has been argued, that moving to the Glycated Haemoglobin A1c (HbA1c) based testing and diagnosis have reduced the proficiency of some scores (e.g. FINDRISC) in the prediction of glucose abnormalities [18].

Self-assessment scores and clinical tools have included known risk factors (e.g. anthropometric, family disposition, medication and lifestyle predictors) [19] some also using self-rated health variables (e.g. physical exercise), which has been argued helpful in risk prediction in patients with undiagnosed T2DM [11], [15], [20], [21]. Studies have shown that ethnicity constitute a predictor for undiagnosed DM [22], [23]. In addition it has been shown that low socio-economic status (SES) is associated with higher incidence and mortality of T2DM [24] and associated with undiagnosed T2DM [25], [26], [27]. Therefore, new self-assessment scores have suggested questions of ethnicity and SES for better detection of DM [23], [28]. The “QD-Score” propose the inclusion of SES and ethnicity as risk factors for DM [23]. Unfortunately, the QD-Score is not directly applicable outside the UK, due to the use of the UK-based Townsend Deprivation Score. The Leicester Risk Assessment Score (LRAS) [28], which includes self-reported ethnicity, has only sparse validation outside the UK [29], [30] and validation in different settings has been advocated [31].

Diabetes and cardiovascular disease share many common risk factors. The ADDITION Denmark study [32], showed that HbA1c  6.0% combined with an elevated cardiovascular disease (CVD) risk assessment (SCORE) [33] identifies 96.7% of patients from family practices in the age group 40–69 years old who would benefit from preventive antidiabetic lifestyle intervention and/or polypharmacy [32], [34].

In this study, we aim to investigate which self-reported predicting factors from common risk scores [11], [13], [15], [19], [21], [23], [28] and which socio-economic factors (including ethnicity) are the most important to unveil undiagnosed prevalent T2DM. Second, externally validate established prediction models (DDRS, LRAS and FINDRISC). Third, compare DDRS, LRAS and FINDRISC in prediction of SCORE (≥5%), and the performance of SCORE for prediction of undiagnosed T2DM and pre-diabetes. We use the Danish General Suburban Population Study (GESUS) (N = 21,205).

Section snippets

Setting

The Danish health care system is intended to provide impartial health care service, being mainly tax financed and based on an egalitarian principle. In Denmark diagnosis and routine care for T2DM is usually provided by GPs who act as gatekeepers for specialist care.

Study population

This study was part of GESUS [35], a representative sample of the adult population in the Danish Naestved Municipality with a mix of urban and more rural areas. In brief, between January 2010 and October 2013, 49,115 individuals, all

Results

Table 1 shows basic characteristics of the GESUS-cohort. Approximately 70% were 40–69 years and 10% above 60 years. Of the 21,205 participants responding, 969 (4.6%) reported a diagnosis of prevalent DM and were excluded from further analysis. Of the remaining participants (n = 20,236), 252 had undiagnosed prevalent T2DM (1.2%), and 1867 (8.8%) had pre-DM. In the age-group 40–69 years old, 1.4% had undiagnosed prevalent T2DM, and 9.5% had pre-diabetes. 17.6% of those with undiagnosed type 2

Discussion

In GESUS, we identified 969 (4.6%) subjects with a prevalent diagnosis of T2DM corresponding to earlier published data [40], [41]. 252 subjects had undiagnosed prevalent T2DM (1.2% of total population and 20.6% of all DM cases), and 1867 (9.2% of total population) subjects had pre-DM. Our results are concordant to earlier published European data [25], [42], [43], data from the National Danish Diabetes Registry [40], and data from a more urban, Danish setting [3] (Supplementary Table 4). In the

Conclusion

BMI and self-reported cardiovascular disease are important risk factors for undiagnosed T2DM. Low education level was a predictor of undiagnosed T2DM but seems of less importance than other risk factors.

LRAS performed better than DDRS and FINDRISC in prediction of undiagnosed T2DM and SCORE  5%. SCORE  5% performed best in predicting pre-diabetes.

Conflict of interest

All authors declare that they have no competing interest.

Availability of data and material

The data supporting the findings described in this article are currently not publicly available, but can be reviewed upon contacting the corresponding author, with respect to patient confidentiality, in concordance with guidelines from the Danish Data Protection Agency and conveying to Clinical Research Ethics Committee of Region Zealand: (SJ-113, SJ-114, SJ-147, SJ-278).

Consent for publication

Not applicable.

Registration number of trial if any

Not a trial.

Ethics approval and consent to participate

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and conforming to the Declaration of Helsinki 1975, as revised in 2008. Written, informed consent was obtained from all participants. The study protocol was approved by the Clinical Research Ethics Committee of Region Zealand (SJ-113, SJ-114, SJ-147, SJ-278). The study was reported to the Danish Data Protection Agency.

Acknowledgements

The authors extend their appreciation to participants of GESUS, the board and executive committee, and GESUS staff. Also thanks to MD, specialist Ole Heltberg and MD, Phd, Martin Mortensen for carefully reviewing the manuscript.

We acknowledge the funding received to support this project from the Region Zealand Research Fund, Copenhagen University Faculty of Health Sciences and by University of Copenhagen 2016 Excellence program to LIFESTAT.

The Danish General Suburban Population Study was

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