Predictors of undiagnosed prevalent type 2 diabetes - The Danish General Suburban Population Study

Undiagnosed type 2 diabetes is common - intensified screening of established risk groups is imperative in Sweden: the SDPP cohort

BACKGROUND

Undiagnosed type 2 diabetes (T2D) is a global problem. Current strategies for diagnosis in Sweden include screening individuals within primary healthcare who are of high risk, such as those with hypertension, obesity, prediabetes, family history of diabetes, or those who smoke daily. In this study, we aimed to estimate the proportion of individuals with undiagnosed T2D in Stockholm County and factors associated with T2D being diagnosed by healthcare. This information could improve strategies for detection.

METHODS

We used data from the Stockholm Diabetes Prevention Programme (SDPP) cohort together with information from national and regional registers. Individuals without T2D aged 35-56 years at baseline were followed up after two ten-year periods. The proportion of diagnosed T2D was based on register information for 7664 individuals during period 1 and for 5148 during period 2. Undiagnosed T2D was assessed by oral glucose tolerance tests at the end of each period. With logistic regression, we analysed factors associated with being diagnosed among individuals with T2D.

RESULTS

At the end of the first period, the proportion of individuals with T2D who had been diagnosed with T2D or not was similar (54.0% undiagnosed). At the end of the second period, the proportion of individuals with T2D was generally higher, but they were less likely to be undiagnosed (43.5%). The likelihood of being diagnosed was in adjusted analyses associated with overweight (OR=1.85; 95% CI 1.22-2.80), obesity (OR=2.73; 95% CI 1.76-4.23), higher fasting blood glucose (OR=2.11; 95% CI 1.67-2.66), and self-estimated poor general health (OR=2.42; 95% CI 1.07-5.45). Socioeconomic factors were not associated with being diagnosed among individuals with T2D. Most individuals (>71%) who developed T2D belonged to risk groups defined by having at least two of the prominent risk factors obesity, hypertension, daily smoking, prediabetes, or family history of T2D, including individuals with T2D who had not been diagnosed by healthcare.

CONCLUSIONS

Nearly half of individuals who develop T2D during 10 years in Stockholm County are undiagnosed, emphasizing a need for intensified screening of T2D within primary healthcare. Screening can be targeted to individuals who have at least two prominent risk factors.

Socio-economic gradients in diagnosed and undiagnosed Type 2 diabetes and its related health complications

BACKGROUND AND AIMS

Diagnosed and undiagnosed Type 2 Diabetes (T2D) remains a challenge in high-income countries. In addition, the presence of T2D can cause further disease burden because of its high susceptibility to complications. Nevertheless, there is limited evidence of socio-economic gradients in undiagnosed T2D and its complications in a large population cohort. We investigated this using the Dutch Lifelines Cohort Study (Lifelines).

METHODS AND RESULTS

Within Lifelines, baseline data of 102 163 adults aged 30 and above were collected from 2007 to 2013. The associations of Socio-Economic Status (SES), indicated by monthly household income, with the prevalence of T2D status and the number of T2D complications were assessed using multinomial Poisson and linear regressions with adjustments for age and sex. The prevalence of diagnosed and undiagnosed T2D was, respectively, 3.0% and 3.0% in the low SES group compared to 1.1% and 1.8% in the high SES group. Individuals with lower SES were at higher risk of having undiagnosed T2D (relative risk ratio (rrr) [95% CI]: 1.63 [1.47-1.81] for low SES and 1.16 [1.05-1.29] for middle SES) and diagnosed T2D, compared with those with high SES. Lower SES was positively associated with the number of T2D complications (low SES vs. high SES (ref); B [95% CI]: 0.15 [0.13-0.16]).

CONCLUSION

Complementing the known socio-economic gradients in diagnosed T2D, we document socio-economic gradients in undiagnosed T2D and T2D complications in a single, large general representative population. Furthermore, individuals with low SES with diagnosed or undiagnosed T2D were more susceptible to T2D complications.

Prevalence and factors associated with undiagnosed type 2 diabetes among adults in Iraq: analysis of cross-sectional data from the 2015 STEPS survey

OBJECTIVE

The purpose of the study was to assess the prevalence and correlates of undiagnosed type 2 diabetes (UT2D) among adults (aged 18 years and older) in Iraq.

DESIGN

Cross-sectional, population-based study.

SETTING

Nationally representative sample of general community-dwelling adult population in Iraq from the 2015 Iraq STEPS survey.

PARTICIPANTS

The sample included 3853 adults (mean age 41.8 years, SD=15.8), with complete fasting blood glucose values, from the 2015 Iraq STEPS survey.

OUTCOME MEASURES

Data collection included: (1) social and behavioural information, (2) physical parameters and blood pressure measurements and (3) biochemical measurements. UT2D was classified as not being diagnosed with T2D and fasting plasma glucose level ≥126 mg/dL. Multivariable multinomial and logistic regression was used to identify factors associated with UT2D.

RESULTS

The prevalence of UT2D was 8.1% and the prevalence of diagnosed T2D (DT2D) was 8.9%. Participants aged 50 years and older (adjusted relative risk ratio (ARRR): 2.11, 95% CI 1.30 to 3.43) and those with high cholesterol (ARRR: 1.54, 95% CI 1.05 to 2.24) had a higher risk of UT2D. Older age (≥50 years) (ARRR: 17.90, 95% CI 8.42 to 38.06), receipt of healthcare advice (ARRR: 2.15, 95% CI 1.56 to 2.96), history of cholesterol testing (ARRR: 2.17, 95% CI 1.58 to 2.99), stroke or heart attack (ARRR: 1.81, 95% CI 1.13 to 2.92), and high cholesterol (ARRR: 1.55, 95% CI 1.17 to 2.06) were positively associated with DT2D, and high physical activity (ARRR: 0.57, 95% CI 0.38 to 0.84) was negatively associated with DT2D. Higher than primary education (adjusted OR (AOR): 2.02, 95% CI 1.21 to 3.37) was positively associated with UT2D versus DT2D, while older age (≥50 years) (AOR: 0.12, 95% CI 0.06 to 0.25), healthcare advice (AOR: 0.45, 95% CI 0.29 to 0.70), and history of cholesterol screening (AOR: 0.37, 95% CI 0.24 to 0.58) were inversely associated with UT2D versus DT2D.

CONCLUSION

Almost one in ten adults in Iraq had UT2D, and various associated factors were identified that could be useful in planning interventions.

Prevalence and correlates of undiagnosed, diagnosed, and total type 2 diabetes among adults in Morocco, 2017

The study aimed to estimate the prevalence and associated factors of undiagnosed type 2 diabetes (T2D) among adults in Morocco. Cross-sectional data were analyzed from 4779 people (≥ 18 years, mean age 41.7 years) who participated in the Morocco STEPS nationally representative survey in 2017 and had completed fasting blood glucose measurement. The results indicate that the prevalence of undiagnosed T2D was 5.9% (44.7% of total T2D), diagnosed T2D 7.3% and total T2D 13.2%. In the adjusted multinomial logistic regression analysis, older age (≥ 50 years), receipt of health care advice, and obesity were positively associated with undiagnosed T2D. Older age (≥ 50 years), urban residence, receipt of health care advice, ever cholesterol screening, moderate sedentary behaviour, obesity, hypertension, and elevated total cholesterol were positively associated with diagnosed T2D. In adjusted logistic regression analysis, older age (≥ 50 years), receipt of health care advice and cholesterol screening were negatively associated with undiagnosed T2D versus diagnosed T2D. A significant proportion of adults in Morocco had undiagnosed T2D and several associated factors were identified that can help guide interventions.

Undiagnosed diabetes based on HbA1c by socioeconomic status and healthcare consumption in the Tromsø Study 1994-2016

INTRODUCTION

We aimed to investigate whether the proportion of undiagnosed diabetes varies by socioeconomic status and healthcare consumption, in a Norwegian population screened with glycated hemoglobin (HbA_1c).

RESEARCH DESIGN AND METHODS

In this cohort study, we studied age-standardized diabetes prevalence using data from men and women aged 40-89 years participating in four surveys of the Tromsø Study with available data on HbA_1c and self-reported diabetes: 1994-1995 (n=6720), 2001 (n=5831), 2007-2008 (n=11 987), and 2015-2016 (n=20 170). We defined undiagnosed diabetes as HbA_1c ≥6.5% (48 mmol/mol) and no self-reported diabetes. We studied the association of education, income and contact with a general practitioner on undiagnosed diabetes and estimated adjusted prevalence ratio (aPR) from multivariable adjusted (age, sex, body mass index) log-binomial regression.

RESULTS

Higher education was associated with lower prevalence of diagnosed and undiagnosed diabetes. Those with secondary and tertiary education had lower prevalence of undiagnosed diabetes (aPR for tertiary vs primary: 0.54, 95% CI: 0.44 to 0.66). Undiagnosed as a proportion of all diabetes was also significantly lower in those with tertiary education (aPR:0.78, 95% CI: 0.65 to 0.93). Household income was also negatively associated with prevalence of undiagnosed diabetes. Across the surveys, approximately 80% of those with undiagnosed diabetes had been in contact with a general practitioner the last year, similar to those without diabetes.

CONCLUSIONS

Undiagnosed diabetes was lower among participants with higher education. The hypothesis that those with undiagnosed diabetes had been less in contact with a general practitioner was not supported.

Who is getting screened for diabetes according to body mass index and waist circumference categories in Peru? a pooled analysis of national surveys between 2015 and 2019

BACKGROUND

At the population level we would expect that people with obesity undergo diabetes screening tests more often than people with overweight and much more often than people with normal weight. We described the trends of diabetes screening according to body mass index (BMI) and waist circumference (WC) in Peru.

METHODS

Pooled analysis of health national surveys (2015-2019); men and women aged 35-70 years. We used relative frequencies to study: among those who have had a glucose test in the last year, how many there were in each BMI and WC category. We fitted a Poisson model to study whether people with high BMI or WC were more likely to have had a glucose test.

RESULTS

People with overweight (PR = 1.34; 95% CI: 1.29-1.38), obesity (PR = 1.57; 95% CI: 1.51-1.63) and central obesity (PR = 1.63; 95% CI: 1.35-1.96) were more likely to have had a glucose test. At the sub-national level, there was one (of twenty-five) region in which men with obesity were more often screened for diabetes than men with overweight and much more than men with normal weight. There were seven regions in which women with obesity were the most often screened for diabetes.

CONCLUSIONS

Consistent with a risk-based prevention approach, people with obesity would be screened for diabetes more often than those with overweight and those with normal weight. This ideal profile was only observed in few regions. Diabetes screening strategies should be strengthened and homogenised, so that they reach those at high risk of diabetes.

Elevated levels of oxidized nucleosides in individuals with the JAK2V617F mutation from a general population study

It is unknown if the somatic mutations in chronic myeloproliferative neoplasms (MPNs), JAK2V617F and Calreticulin, are associated with oxidative stress, or impaired mitochondrial defense against reactive oxygen species. In the Danish General Suburban Population Study (GESUS), including 116 JAK2V617F-mutated, 8 CALR-mutated, and 3310 mutation-negative participants without overt MPN, and in a study of 39 patients with myelofibrosis, the most advances type of MPNs, and 179 matched controls, we compared the urinary concentration of oxidized nucleosides – 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) and 8-oxo-7,8-dihydroguanosine (8-oxoGuo) – as markers of oxidative stress. In GESUS, we performed Mendelian randomization analyses, using the Ala16Val single nucleotide polymorphism in the superoxide dismutase2 (SOD2) gene. In the multivariate analyses in GESUS, the 8-oxodG and 8-oxoGuo concentration were 13% (95%CI: 6–21%, p < 0.001) and 6% (95%CI: 0.4–11%, p = 0.035) higher in mutation-positive than in mutation-negative participants, respectively. Each SOD2 T allele was associated with an odds ratio of being mutation-positive of 1.69 (95%CI: 1.12–2.55, p = 0.013) through 8-oxodG. The 8-oxodG and 8-oxoGuo concentrations were 77% (95%CI: 49–110%, p < 0.001) and 105% (95%CI: 80–133%, p < 0.001) higher in myelofibrosis patients than in controls, respectively. In conclusion, an impaired mitochondrial antioxidative defense, that is causatively associated with markers of oxidative stress, may contribute to the development of mutations associated with MPNs.

Factors associated with undiagnosed type 2 diabetes in Germany: results from German Health Interview and Examination Survey for Adults 2008-2011

INTRODUCTION

To identify characteristics of people with undiagnosed type 2 diabetes (T2D) among adults in Germany.

RESEARCH DESIGN AND METHODS

The study population comprised participants aged 40-79 years of the German Health Interview and Examination Survey for Adults 2008-2011. Glycemic status was categorized as undiagnosed T2D (glycated hemoglobin A1c (HbA1c) ≥48 mmol/mol (6.5%), n=135), diagnosed T2D (n=518) and normoglycemia (HbA1c<48 mmol/mol (6.5%), n=4451). Multinomial logistic regression models including glycemic status as the outcome variable and sociodemographic characteristics, living alone, diabetes risk factors and healthcare services utilization as independent variables were used to identify factors associated with undiagnosed T2D compared with normoglycemia and diagnosed T2D. Odds ratios (ORs) and 95% confidence intervals (CIs) are reported as measure of association between the outcome and independent variables.

RESULTS

The prevalence of undiagnosed T2D was 2.9% (95% CI 2.2% to 3.9%) at an overall prevalence of 12.3% (11.0% to 13.6%) of persons with undiagnosed or diagnosed T2D. In multivariable analyses, factors associated with undiagnosed as well as diagnosed T2D in comparison to normoglycemia were older age (OR 1.04, 95% CI 1.01 to 1.06, per year, for undiagnosed T2D; OR 1.08, 1.07 to 1.10 for diagnosed T2D), male sex (3.33, 2.18 to 5.07; 1.91, 1.43 to 2.56), obesity (3.47, 2.17 to 5.56; 2.68, 2.04 to 3.52), hypertension (1.66, 1.09 to 2.53; 2.04, 1.42 to 2.95) and parental history of diabetes (2.04, 1.24 to 3.35; 3.16, 2.30 to 4.34). Variables independently associated with undiagnosed T2D but not diagnosed T2D included living alone (2.20; 1.36 to 3.56) and not seeing a doctor within the past year (2.57; 1.34 to 4.93). People with undiagnosed T2D were further younger and more likely to be male sex and reside in the western part of Germany than people with diagnosed T2D.

CONCLUSION

Apart from major known risk factors of diabetes, characteristics specific to undiagnosed diabetes among adults in Germany will serve to inform the national education and communication strategy on diabetes mellitus in Germany.

Type 1 and type 2 diabetes after gestational diabetes: a 23 year cohort study

AIMS/HYPOTHESIS

The aim of this work was to examine the progression to type 1 and type 2 diabetes after gestational diabetes mellitus (GDM) in a 23 year follow-up study.

METHODS

We carried out a cohort study of 391 women with GDM diagnosed by an OGTT or the use of insulin treatment during pregnancy, and 391 age- and parity-matched control participants, who delivered in 1984-1994 at the Oulu University Hospital, Finland. Diagnostic cut-off levels for glucose were as follows: fasting, ≥4.8 mmol/l; 1 h, ≥10.0 mmol/l; and 2 h, ≥8.7 mmol/l. Two follow-up questionnaires were sent (in 1995-1996 and 2012-2013) to assess the progression to type 1 and type 2 diabetes. Mean follow-up time was 23.1 (range 18.7-28.8) years.

RESULTS

Type 1 diabetes developed (5.7%) during the first 7 years after GDM pregnancy and was predictable at a 2 h OGTT value of 11.9 mmol/l during pregnancy (receiver operating characteristic analysis: AUC 0.91, sensitivity 76.5%, specificity 96.0%). Type 2 diabetes increased linearly to 50.4% by the end of the follow-up period and was moderately predictable with fasting glucose (AUC 0.69, sensitivity 63.5%, specificity 68.2%) at a level of 5.1 mmol/l (identical to the fasting glucose cut-off recommended by the International Association of Diabetes and Pregnancy Study Groups [IADPSG) and WHO]).

CONCLUSIONS/INTERPRETATION

All women with GDM should be intensively monitored for a decade, after which the risk for type 1 diabetes is minimal. However, the incidence of type 2 diabetes remains linear, and therefore individualised lifelong follow-up is recommended.

Lifestyle factors do not explain the difference on diabetes progression according to type of prediabetes: Results from a Spanish prospective cohort of prediabetic patients

AIMS

We studied the role of lifestyle factors associated to type 2 diabetes (T2DM) onset according to type of prediabetes.

METHODS

We used data from the observational prospective cohort study in Primary Health Care on the Evolution of Patients with Prediabetes in Spain (PREDAPS). Participants were classified by American Diabetes Association criteria using either fasting plasma glucose levels (100-125 mg/dL) (group 1), HbA1c (5.7%-6.4%) (group 2) or both impaired parameters (group 3). Relationship between lifestyles and diabetes onset according to prediabetes at third year of follow up were estimated by Hazard Ratios (HRs) using three sequential models.

RESULTS

Incidence rate of diabetes was 2.27 cases per 1000 person-years (95% CI: 1.4-3.6) for group 1, 1.18 (95% CI: 0.65-2.13) for group 2 and 6.68 (95% CI: 5.71-8.23) for group 3. The most important risk factors were: abdominal obesity (HR: 2.29 (95% CI: 1.49-3.52)) and hypertension (HR: 2.16 (95% CI: 1.41-3.30)). Using as reference group 2, group 3 had a HR of 5.82 (3.13-10.82) and 1.83 (95% CI: 0.85-3.93) for group 1, estimates remained constant when adjusting by lifestyle and metabolic factors.

CONCLUSIONS

Lifestyle and metabolic do not seem to explain the differences on T2DM onset by type of prediabetes.

Statin treatment, oxidative stress and inflammation in a Danish population

Background

While statins may have anti-inflammatory effects, anti-oxidative effects are controversial. We investigated if statin treatment is associated with differences in oxidatively generated nucleotide damage and chronic inflammation, and the relationship between nucleotide damage and chronic inflammation.

Methods

We included 19,795 participants from the Danish General Suburban Population Study. In 3420 participants, we measured urinary 8-oxodG and 8-oxoGuo by liquid chromatography-tandem mass spectrometry as markers of oxidatively generated damage to DNA and RNA, respectively. We used a composite score for chronic inflammation (INFLA score) of hsCRP, WBC, platelet count, and neutrophil granulocyte to lymphocyte ratio. Associations were assessed using multivariate linear regression models.

Results

Compared with non-users, statin users had 4.3–6.0% lower 8-oxodG in three separate models (p < 0.05); there were no differences in 8-oxoGuo. Among participants aged > 60 y, statin users had 11.4% lower 8-oxodG (95%CI: 6.7–15.9%, p_interaction<0.001) and 3.9% lower 8-oxoGuo (95%CI: 0.1–7.5%, p_interaction = 0.002), compared with non-users. Compared with non-users, statin users had 11.1% (95%CI: 5.4–16.5%, p_interaction<0.001) lower 8-oxodG in participants treated for hypertension, and 18.6% (95%CI: 6.8–28.9%, p_interaction<0.001) lower 8-oxodG in participants with decreased renal function. Compared with non-users, statin users had significantly lower INFLA score (p < 0.001). 8-oxodG and 8-oxoGuo associated positively with markers of chronic inflammation.

Conclusions

Oxidatively generated DNA damage and inflammatory burden are lower in statin users compared with non-users. Together, anti-oxidative and anti-inflammatory effects may contribute to the beneficial effects of statins.

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Statin users have lower oxidatively generated DNA damage than non-users.

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The protective effect of statins is more pronounced in high-risk groups.

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Statin users have lower levels of chronic inflammation than non-users.

Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study

Background

A 75-g oral glucose tolerance test (OGTT) provides important information about glucose metabolism, although the test is expensive and invasive. Complete OGTT information, such as 1-hour and 2-hour postloading plasma glucose and immunoreactive insulin levels, may be useful for predicting the future risk of diabetes or glucose metabolism disorders (GMD), which includes both diabetes and prediabetes.

Objective

We trained several classification models for predicting the risk of developing diabetes or GMD using data from thousands of OGTTs and a machine learning technique (XGBoost). The receiver operating characteristic (ROC) curves and their area under the curve (AUC) values for the trained classification models are reported, along with the sensitivity and specificity determined by the cutoff values of the Youden index. We compared the performance of the machine learning techniques with logistic regressions (LR), which are traditionally used in medical research studies.

Methods

Data were collected from subjects who underwent multiple OGTTs during comprehensive check-up medical examinations conducted at a single facility in Tokyo, Japan, from May 2006 to April 2017. For each examination, a subject was diagnosed with diabetes or prediabetes according to the American Diabetes Association guidelines. Given the data, 2 studies were conducted: predicting the risk of developing diabetes (study 1) or GMD (study 2). For each study, to apply supervised machine learning methods, the required label data was prepared. If a subject was diagnosed with diabetes or GMD at least once during the period, then that subject’s data obtained in previous trials were classified into the risk group (y=1). After data processing, 13,581 and 6760 OGTTs were analyzed for study 1 and study 2, respectively. For each study, a randomly chosen subset representing 80% of the data was used for training 9 classification models and the remaining 20% was used for evaluating the models. Three classification models, A to C, used XGBoost with various input variables, some including OGTT data. The other 6 classification models, D to I, used LR for comparison.

Results

For study 1, the AUC values ranged from 0.78 to 0.93. For study 2, the AUC values ranged from 0.63 to 0.78. The machine learning approach using XGBoost showed better performance compared with traditional LR methods. The AUC values increased when the full OGTT variables were included. In our analysis using a particular setting of input variables, XGBoost showed that the OGTT variables were more important than fasting plasma glucose or glycated hemoglobin.

Conclusions

A machine learning approach, XGBoost, showed better prediction accuracy compared with LR, suggesting that advanced machine learning methods are useful for detecting the early signs of diabetes or GMD. The prediction accuracy increased when all OGTT variables were added. This indicates that complete OGTT information is important for predicting the future risk of diabetes and GMD accurately.

Socio-demographic determinants and effect of structured personal diabetes care: a 19-year follow-up of the randomized controlled study diabetes Care in General Practice (DCGP)

BACKGROUND

We investigated how four aspects of socio-demography influence the effectiveness of an intervention with structured personal diabetes care on long-term outcomes.

METHODS

The Diabetes Care in General Practice (DCGP) study is a cluster-randomized trial involving a population-based sample of 1381 patients with newly diagnosed type 2-diabetes mellitus. We investigated how education, employment, cohabitation status and residence influenced the effectiveness of 6 years of intervention with structured personal diabetes care, resembling present day recommendations. Outcomes were incidence of any diabetes-related endpoint and death during 19 years after diagnosis, and cardiovascular risk factors, behaviour, attitudes and process-of-care variables 6 years after diagnosis.

RESULTS

Structured personal care reduced the risk of any diabetes-related endpoint and the effect of the intervention was modified by geographical area (interaction p = 0.034) with HR of 0.71 (95%CI: 0.60-0.85) and of 1.07 (95%CI: 0.77-1.48), for patients in urban and rural areas, respectively. Otherwise, there was no effect modification of education, employment and civil status on the intervention for the final endpoints. There were no noticeable socio-demographic differences in the effect of the intervention on cardiovascular risk factors, behaviour, attitudes, and process-of-care.

CONCLUSION

Structured personal care reduced the aggregate outcome of any diabetes-related endpoint and independent of socio-demographic factors similar effect on cardiovascular risk factors, behaviour, attitudes and process of care, but the intervention did not change the existing inequity in mortality and morbidity. Residence modified the uptake of the intervention with patients living in urban areas having more to gain of the intervention than rural patients, further investigations is warranted.

TRIAL REGISTRATION

ClinicalTrials.gov registration no. NCT01074762 (February 24, 2010).