OBJECTIVE To study incident diabetic polyneuropathy (DPN) prospectively during the first 13 years after a screening-based diagnosis of type 2 diabetes and determine the associated risk factors for the development of DPN. RESEARCH DESIGN AND METHODS We assessed DPN longitudinally in the Danish arm of the Anglo-Danish-Dutch study of Intensive Treatment of Diabetes in Primary Care (ADDITION) using the Michigan Neuropathy Screening Instrument questionnaire (MNSIQ), defining DPN with scores ≥4. Risk factors present at the diabetes diagnosis associated with the risk of incident DPN were estimated using Cox proportional hazard models adjusted for trial randomization group, sex, and age. RESULTS Of the total cohort of 1,533 people, 1,445 completed the MNSIQ at baseline and 189 (13.1%) had DPN at baseline. The remaining 1,256 without DPN entered this study (median age 60.8 years [interquartile range 55.6; 65.6], 59% of whom were men). The cumulative incidence of DPN was 10% during 13 years of diabetes. Age (hazard ratio [HR] 1.03 [95% CI 1.00; 1.07]) (unit = 1 year), weight (HR 1.09 [95% CI 1.03; 1.16]) (unit = 5 kg), waist circumference (HR 1.14 [95% CI 1.05; 1.24]) (unit = 5 cm), BMI (HR 1.14 [95% CI 1.06; 1.23]) (unit = 2 kg/m²), log₂ methylglyoxal (HR 1.45 [95% CI 1.12; 1.89]) (unit = doubling), HDL cholesterol (HR 0.82 [95% CI 0.69; 0.99]) (unit = 0.25 mmol/L), and LDL cholesterol (HR 0.92 [95% CI 0.86; 0.98]) (unit = 0.25 mmol/L) at baseline were significantly associated with the risk of incident DPN. CONCLUSIONS This study provides further epidemiological evidence for obesity as a risk factor for DPN. Moreover, low HDL cholesterol levels and higher levels of methylglyoxal, a marker of dicarbonyl stress, are identified as risk factors for the development of DPN.

Background: Screening programmes for type 2 diabetes inevitably find more individuals at high risk for diabetes than people with undiagnosed prevalent disease. While well established guidelines for the treatment of diabetes exist, less is known about treatment or prevention strategies for individuals found at high risk following screening. In order to make better use of the opportunities for primary prevention of diabetes and its complications among this high risk group, it is important to quantify diabetes progression rates and to examine the development of early markers of cardiovascular disease and microvascular diabetic complications. We also require a better understanding of the mechanisms that underlie and drive early changes in cardiometabolic physiology. The ADDITION-PRO study was designed to address these issues among individuals at different levels of diabetes risk recruited from Danish primary care. Methods/Design: ADDITION-PRO is a population-based, longitudinal cohort study of individuals at high risk for diabetes. 16,136 eligible individuals were identified at high risk following participation in a stepwise screening programme in Danish general practice between 2001 and 2006. All individuals with impaired glucose regulation at screening, those who developed diabetes following screening, and a random sub-sample of those at lower levels of diabetes risk were invited to attend a follow-up health assessment in 2009–2011 (n = 4,188), of whom 2,082 (50%) attended. The health assessment included detailed measurement of anthropometry, body composition, biochemistry, physical activity and cardiovascular risk factors including aortic stiffness and central blood pressure. All ADDITION-PRO participants are being followed for incident cardiovascular disease and death. Discussion: The ADDITION-PRO study is designed to increase understanding of cardiovascular risk and its underlying mechanisms among individuals at high risk of diabetes. Key features of this study include (i) a carefully characterised cohort at different levels of diabetes risk; (ii) detailed measurement of cardiovascular and metabolic risk factors; (iii) objective measurement of physical activity behaviour; and (iv) long-term follow-up of hard clinical outcomes including mortality and cardiovascular disease. Results will inform policy recommendations concerning cardiovascular risk reduction and treatment among individuals at high risk for diabetes. The detailed phenotyping of this cohort will also allow a number of research questions concerning early changes in cardiometabolic physiology to be addressed.

Recent evidence links the soluble urokinase plasminogen activator receptor (suPAR), a stable biomarker of systemic immune activation, to several chronic diseases, including type 2 diabetes. suPAR is also associated with adiposity and smoking. We hypothesised that this biomarker would be linked to incident type 2 diabetes in individuals with impaired glucose regulation and that this association would be modified by smoking and body weight status.

Aims: We estimated and compared health‐related quality of life for individuals with normal glucose tolerance, prediabetes and diabetes.Methods: Participants in the ADDITION‐PRO study, Denmark, who attended a health assessment between 2009 and 2011, and who completed the 3‐level EuroQoL 5‐dimensions (EQ‐5D‐3L) questionnaire were included. For the present study, they were classified as normal glucose tolerance, prediabetes and diabetes (screen‐detected and known) using the 2019 American Diabetes Association criteria. Prediabetes was defined as impaired fasting glucose, impaired glucose tolerance or HbA1c between 5.7–6.4% (39–47 mmol/mol). EQ‐5D‐3L data were converted into utility scores using Danish and UK values, where ‘1’ equals full health and ‘0’ equals death. Regression models estimated the association between utility and the different glucose health states.Results: The mean EQ‐5D‐3L score in the sample population was 0.86 ± 0.17 (median 0.85, interquartile range 0.76 to 1) using UK values. Almost half of the sample (48%) reported full health with an EQ‐5D score of ‘1’. Individuals with known diabetes reported the lowest EQ‐5D‐3L utility scores (0.81 ± 0.20), followed by individuals with screen‐detected diabetes (0.85 ± 0.19), prediabetes (0.86 ± 0.17) and normal glucose tolerance (0.90 ± 0.15). The differences were statistically significant for normal glucose and known diabetes relative to prediabetes, after adjusting for sex, age, smoking, BMI and physical activity. These findings also held using Danish values albeit the differences were of smaller magnitude.Conclusions: Having prediabetes and diabetes was significantly associated with lower health‐related quality of life relative to normal glucose tolerance. Our estimates will be useful to inform the value of interventions to prevent diabetes or prediabetes.