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Computational models of human glucose homeostasis can provide insight into the physiological processes underlying the observed inter-individual variability in glucose regulation. Modelling approaches ranging from "bottom-up" mechanistic models to "top-down" data-driven techniques have been applied to untangle the complex interactions underlying progressive disturbances in glucose homeostasis. While both approaches offer distinct benefits, a combined approach taking the best of both worlds has yet to be explored. Here, we propose a sequential combination of a mechanistic and a data-driven modeling approach to quantify individuals' glucose and insulin responses to an oral glucose tolerance test, using cross sectional data from 2968 individuals from a large observational prospective population-based cohort, the Maastricht Study. The best predictive performance, measured by R2 and mean squared error of prediction, was achieved with personalized mechanistic models alone. The addition of a data-driven model did not improve predictive performance. The personalized mechanistic models consistently outperformed the data-driven and the combined model approaches, demonstrating the strength and suitability of bottom-up mechanistic models in describing the dynamic glucose and insulin response to oral glucose tolerance tests., Competing Interests: This study received funding from Janssen-Cilag, Novo Nordisk Farma., Sanofi-Aventis Netherlands, DSM Nutritional products, FrieslandCampina, and Danone Nutricia Research. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Erdős et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Aims/hypothesis: Studies investigating associations between kynurenines and cognitive function have generally been small, restricted to clinical samples or have found inconsistent results, and associations in the general adult population, and in individuals with type 2 diabetes in particular, are not clear. Therefore, the aim of the present study was to investigate cross-sectional associations between plasma kynurenines and cognitive function in a cohort of middle-aged participants with normal glucose metabolism, prediabetes (defined as impaired fasting glucose and/or impaired glucose tolerance) and type 2 diabetes., Methods: Plasma kynurenines were quantified in 2358 participants aged 61 ± 8 years. Cross-sectional associations of kynurenines with cognitive impairment and cognitive domain scores were investigated using logistic, multiple linear and restricted cubic spline regression analyses adjusted for several confounders., Results: Effect modification by glucose metabolism status was found for several associations with cognitive impairment, hence analyses were stratified. In individuals with prediabetes, 3-hydroxykynurenine (OR per SD 0.59 [95% CI 0.37, 0.94]) and 3-hydroxyanthranilic acid (0.67 [0.47, 0.96]) were associated with lower odds of cognitive impairment after full adjustment. In individuals with type 2 diabetes, kynurenine (0.80 [0.66, 0.98]), 3-hydroxykynurenine (0.82 [0.68, 0.99]), kynurenic acid (0.81 [0.68, 0.96]), xanthurenic acid (0.73 [0.61, 0.87]) and 3-hydroxyanthranilic acid (0.73 [0.60, 0.87]) were all associated with lower odds of cognitive impairment. Kynurenic acid (β per SD 0.07 [95% CI 0.02, 0.13]) and xanthurenic acid (0.06 [0.01, 0.11]) were also associated with better executive function/attention. No associations were observed in individuals with normal glucose metabolism., Conclusions/interpretation: Several kynurenines were cross-sectionally associated with lower odds of cognitive impairment and better cognitive functioning in type 2 diabetes, while less widespread associations were seen in prediabetes. Low levels of kynurenines might be involved in the pathway of type 2 diabetes and cognitive decline but this needs further studies., (© 2021. The Author(s).)

Aims: CVD is the main cause of morbidity and mortality in individuals with diabetes. It is currently unclear whether daily glucose variability contributes to CVD. Therefore, we investigated whether glucose variability is associated with arterial measures that are considered important in CVD pathogenesis., Methods: We included participants of The Maastricht Study, an observational population-based cohort, who underwent at least 48 h of continuous glucose monitoring (CGM) (n = 853; age: 59.9 ± 8.6 years; 49% women, 23% type 2 diabetes). We studied the cross-sectional associations of two glucose variability indices (CGM-assessed SD [SD CGM ] and CGM-assessed CV [CV CGM ]) and time in range (TIR CGM ) with carotid-femoral pulse wave velocity (cf-PWV), carotid distensibility coefficient, carotid intima-media thickness, ankle-brachial index and circumferential wall stress via multiple linear regression., Results: Higher SD CGM was associated with higher cf-PWV after adjusting for demographics, cardiovascular risk factors and lifestyle factors (regression coefficient [B] per 1 mmol/l SD CGM [and corresponding 95% CI]: 0.413 m/s [0.147, 0.679], p = 0.002). In the model additionally adjusted for CGM-assessed mean sensor glucose (MSG CGM ), SD CGM and MSG CGM contributed similarly to cf-PWV (respective standardised regression coefficients [st.βs] and 95% CIs of 0.065 [-0.018, 0.167], p = 0.160; and 0.059 [-0.043, 0.164], p = 0.272). In the fully adjusted models, both higher CV CGM (B [95% CI] per 10% CV CGM : 0.303 m/s [0.046, 0.559], p = 0.021) and lower TIR CGM (B [95% CI] per 10% TIR CGM : -0.145 m/s [-0.252, -0.038] p = 0.008) were statistically significantly associated with higher cf-PWV. Such consistent associations were not observed for the other arterial measures., Conclusions: Our findings show that greater daily glucose variability and lower TIR CGM are associated with greater aortic stiffness (cf-PWV) but not with other arterial measures. If corroborated in prospective studies, these results support the development of therapeutic agents that target both daily glucose variability and TIR CGM to prevent CVD.

Background This cross-sectional study evaluated associations between structural and functional measures of left ventricular diastolic function and cardiorespiratory fitness (CRF) in a well-characterized population-based cohort stratified according to glucose metabolism status. Methods and Results Six hundred seventy-two participants from The Maastricht Study (mean±SD age, 61±9 years; 17.4% prediabetes and 25.4% type 2 diabetes mellitus) underwent both echocardiography to determine left atrial volume index, left ventricular mass index, maximum tricuspid flow regurgitation, average e' and E/e' ratio; and submaximal cycle ergometer test to determine CRF as maximum power output per kilogram body mass. Associations were examined with linear regression adjusted for cardiovascular risk and lifestyle factors, and interaction terms. After adjustment, in normal glucose metabolism but not (pre)diabetes, higher left atrial volume index (per 1 mL/m 2 ), left ventricular mass index (per 1 g/m 2.7 ), maximum tricuspid regurgitation flow (per 1 m/s) were associated with higher CRF (maximum power output per kilogram body mass; β in normal glucose metabolism 0.015 [0.008-0.023], P interaction (pre)diabetes <0.10; 0.007 [-0.001 to 0.015], P interaction type 2 diabetes mellitus <0.10; 0.129 [0.011-0.246], P interaction >0.10; for left atrial volume index, left ventricular mass index, maximum tricuspid regurgitation flow, respectively). Furthermore, after adjustment, in all individuals, higher average E/e' ratio (per unit), but not average e', was associated with lower CRF (normal glucose metabolism -0.044 [-0.071 to -0.016]), P interaction >0.10). Conclusions In this population-based study, structural and functional measures of left ventricular diastolic function were independently differentially associated with CRF over the strata of glucose metabolism status. This suggests that deteriorating left ventricular diastolic function, although of small effect, may contribute to the pathophysiological process of impaired CRF in the general population. Moreover, the differential effects in these structural measures may be the consequence of cardiac structural adaptation to effectively increase CRF in normal glucose metabolism, which is absent in (pre)diabetes.

Background: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values can further optimize such devices. In this study, we used machine learning to train models in predicting future glucose levels based on prior CGM and accelerometry data., Methods: We used data from The Maastricht Study, an observational population-based cohort that comprises individuals with normal glucose metabolism, prediabetes, or type 2 diabetes. We included individuals who underwent >48h of CGM (n = 851), most of whom (n = 540) simultaneously wore an accelerometer to assess physical activity. A random subset of individuals was used to train models in predicting glucose levels at 15- and 60-minute intervals based on either CGM data or both CGM and accelerometer data. In the remaining individuals, model performance was evaluated with root-mean-square error (RMSE), Spearman's correlation coefficient (rho) and surveillance error grid. For a proof-of-concept translation, CGM-based prediction models were optimized and validated with the use of data from individuals with type 1 diabetes (OhioT1DM Dataset, n = 6)., Results: Models trained with CGM data were able to accurately predict glucose values at 15 (RMSE: 0.19mmol/L; rho: 0.96) and 60 minutes (RMSE: 0.59mmol/L, rho: 0.72). Model performance was comparable in individuals with type 2 diabetes. Incorporation of accelerometer data only slightly improved prediction. The error grid results indicated that model predictions were clinically safe (15 min: >99%, 60 min >98%). Our prediction models translated well to individuals with type 1 diabetes, which is reflected by high accuracy (RMSEs for 15 and 60 minutes of 0.43 and 1.73 mmol/L, respectively) and clinical safety (15 min: >99%, 60 min: >91%)., Conclusions: Machine learning-based models are able to accurately and safely predict glucose values at 15- and 60-minute intervals based on CGM data only. Future research should further optimize the models for implementation in closed-loop insulin delivery systems., Competing Interests: This study received funding from Janssen-Cilag B.V, Novo Nordisk Farma B.V., Sanofi-Aventis Netherlands B.V and Medtronic. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors. N.C. Schaper, R.M.A. Henry, and M.C.G.J. Brouwers were supported by Medtronic (External Research Program). Medtronic did not direct design, conduct, or outcomes of this study. The authors declare that there are no other relationships or activities that might bias, or be perceived to bias, their work.

Backgrounds: The role of right ventricular (RV) and atrial (RA) structure and function, in the increased heart failure risk in (pre)diabetes is incompletely understood. The purpose of this study is to investigate the associations between (pre)diabetes and RV and RA structure and function, and whether these are mediated by left ventricular (LV) alterations or pulmonary pressure., Methods: Participants of the Maastricht Study; a population-based cohort study (426 normal glucose metabolism (NGM), 142 prediabetes, 224 diabetes), underwent two-dimensional and tissue Doppler echocardiography. Multiple linear regression analyses with pairwise comparisons of (pre)diabetes versus NGM, adjusted for cardiovascular risk factors, and mediation analyses were used., Results: In general, differences were small. Nevertheless, in individuals with prediabetes and diabetes compared to NGM; RA volume index was lower (both p < 0.01, p trend  < 0.01), RV diameter was lower (both p < 0.01, p trend  < 0.01) and RV length was significantly smaller in diabetes (p = 0.67 and p = 0.03 respectively, p trend  = 0.04), TDI S'RV was lower (p = 0.08 and p < 0.01 respectively, p trend  < 0.01), TDI E'RV was lower (p = 0.01 and p = 0.02 respectively, p trend  = 0.01) and TDI A'RV was lower (p < 0.01 and p = 0.07 respectively, p trend  = 0.04). Only the differences in RA volume index (7.8%) and RV diameter (6.2%) were mediated by the maximum tricuspid gradient, but no other LV structure and function measurements., Conclusions: (Pre)diabetes is associated with structural RA and RV changes, and impaired RV systolic and diastolic function, independent of cardiovascular risk factors. These associations were largely not mediated by indices of LV structure, LV function or pulmonary pressure. This suggests that (pre)diabetes affects RA and RV structure and function due to direct myocardial involvement.

Background: Glucose variability (GV) measured by continuous glucose monitoring (CGM) has become an accepted marker of glycemic control. Nevertheless, several methodological aspects of GV assessment require further study. We, therefore, investigated the minimum number of days needed to reliably measure GV, assessed GV reference values, and studied the correlation of GV with established glycemic indices (i.e., HbA 1c , seven-point oral glucose tolerance test [OGTT]-derived indices). Methods: We used cross-sectional data from The Maastricht Study, an observational population-based cohort enriched with type 2 diabetes. Participants with more than 48 h of CGM (iPro2; Medtronic) were included for analysis ( n  = 851; age: 60 ± 9years; 49% women; 23% type 2 diabetes). We used mean sensor glucose (MSG), standard deviation (SD), and coefficient of variation (CV) as CGM-derived indices (the latter two for GV quantification). We calculated reliability using the Spearman-Brown prophecy formula, established reference values by calculating 2.5th-97.5th percentiles, and studied correlations using Spearman's rho. Results: Sufficient reliability ( R  > 0.80) was achieved with two (MSG and SD), or three monitoring days (CV). The reference ranges, assessed in individuals with normal glucose metabolism ( n  = 470), were 90.5-120.6 mg/dL (MSG), 7.9-24.8 mg/dL (SD), and 7.74%-22.45% (CV). For MSG, the strongest correlation was found with fasting plasma glucose (rho = 0.65 [0.61; 0.69]); for SD, with the 1-h OGTT value (rho = 0.61 [0.56; 0.65]); and for CV, with both the incremental glucose peak (IGP) during the OGTT (rho = 0.50 [0.45; 0.55]) and the 1-h OGTT value (rho = 0.50 [0.45; 0.55]). Conclusions: The reliability findings and reference values are relevant for studies that aim to investigate CGM-measured GV. One-hour OGTT and IGP values can be used as GV indices when CGM is unavailable.

Background: Daily glucose variability may contribute to vascular complication development irrespective of mean glucose values. The incremental glucose peak (IGP) during an oral glucose tolerance test (OGTT) can be used as a proxy of glucose variability. We investigated the association of IGP with arterial stiffness, arterial remodeling, and microvascular function, independent of HbA 1c and other confounders., Methods: IGP was calculated as the peak minus baseline plasma glucose value during a seven-point OGTT in 2758 participants (age: 60 ± 8 years; 48% women) of The Maastricht Study, an observational population-based cohort. We assessed the cross-sectional associations between IGP and arterial stiffness (carotid-femoral pulse wave velocity [cf-PWV], carotid distensibility coefficient [carDC]), arterial remodeling (carotid intima-media thickness [cIMT]; mean [CWS mean ] and pulsatile [CWS puls ] circumferential wall stress), and microvascular function (retinal arteriolar average dilatation; heat-induced skin hyperemia) via multiple linear regression with adjustment for age, sex, HbA 1c , cardiovascular risk factors, lifestyle factors, and medication use., Results: Higher IGP was independently associated with higher cf-PWV (regression coefficient [B]: 0.054 m/s [0.020; 0.089]) and with higher CWS mean (B: 0.227 kPa [0.008; 0.446]). IGP was not independently associated with carDC (B: - 0.026 10 -3 /kPa [- 0.112; 0.060]), cIMT (B: - 2.745 µm [- 5.736; 0.245]), CWS puls (B: 0.108 kPa [- 0.054; 0.270]), retinal arteriolar average dilatation (B: - 0.022% [- 0.087; 0.043]), or heat-induced skin hyperemia (B: - 1.380% [- 22.273; 19.513])., Conclusions: IGP was independently associated with aortic stiffness and maladaptive carotid remodeling, but not with carotid stiffness, cIMT, and microvascular function measures. Future studies should investigate whether glucose variability is associated with cardiovascular disease.

Objective: We studied whether blood metabolomic measures in people with type 2 diabetes (T2D) are associated with insufficient glycemic control and whether this association is influenced differentially by various diabetes drugs. We then tested whether the same metabolomic profiles were associated with the initiation of insulin therapy., Methods: A total of 162 metabolomic measures were analyzed using a nuclear magnetic resonance-based method in people with T2D from four cohort studies (n = 2641) and one replication cohort (n = 395). Linear and logistic regression analyses with adjustment for potential confounders, followed by meta-analyses, were performed to analyze associations with hemoglobin A1c levels, six glucose-lowering drug categories, and insulin initiation during a 7-year follow-up period (n = 698)., Results: After Bonferroni correction, 26 measures were associated with insufficient glycemic control (HbA1c >53 mmol/mol). The strongest association was with glutamine (OR, 0.66; 95% CI, 0.61 to 0.73; P = 7.6 × 10-19). In addition, compared with treatment-naive patients, 31 metabolomic measures were associated with glucose-lowering drug use (representing various metabolite categories; P ≤ 3.1 × 10-4 for all). In drug-stratified analyses, associations with insufficient glycemic control were only mildly affected by different glucose-lowering drugs. Five of the 26 metabolomic measures (apolipoprotein A1 and medium high-density lipoprotein subclasses) were also associated with insulin initiation during follow-up in both discovery and replication. The strongest association was observed for medium high-density lipoprotein cholesteryl ester (OR, 0.54; 95% CI, 0.42 to 0.71; P = 4.5 × 10-6)., Conclusion: Blood metabolomic measures were associated with present and future glycemic control and might thus provide relevant cues to identify those at increased risk of treatment failure.

Aims: Subclinical systemic inflammation may contribute to the development of type 2 diabetes, but its association with early progression of glycaemic deterioration in persons without diabetes has not been fully investigated. Our primary aim was to assess longitudinal associations of changes in pro-inflammatory (leukocytes, high-sensitivity C-reactive protein (hsCRP)) and anti-inflammatory (adiponectin) markers with changes in markers that assessed glycaemia, insulin resistance, and secretion (HbA 1c , HOMA-IR, and HOMA-ß). Furthermore, we aimed to directly compare longitudinal with cross-sectional associations., Materials and Methods: This study includes 819 initially nondiabetic individuals with repeated measurements from the Cooperative Health Research in the Region of Augsburg (KORA) S4/F4 cohort study (median follow-up: 7.1 years). Longitudinal and cross-sectional associations were simultaneously examined using linear mixed growth models. Changes in markers of inflammation were used as independent and changes in markers of glycaemia/insulin resistance/insulin secretion as dependent variables. Models were adjusted for age, sex, major lifestyle and metabolic risk factors for diabetes using time-varying variables in the final model., Results: Changes of leukocyte count were positively associated with changes in HbA 1c and HOMA-ß while changes in adiponectin were inversely associated with changes in HbA 1c . All examined cross-sectional associations were statistically significant; they were generally stronger and mostly directionally consistent to the longitudinal association estimates., Conclusions: Adverse changes in low-grade systemic inflammation go along with glycaemic deterioration and increased insulin secretion independently of changes in other risk factors, suggesting that low-grade inflammation may contribute to the development of hyperglycaemia and a compensatory increase in insulin secretion., (© 2018 John Wiley & Sons, Ltd.)

Objective: Diabetes distress among patients from ethnic minorities is still poorly understood. We investigated the association between ethnicity and diabetes distress among ethnic minority groups of people with type 2 diabetes in the Netherlands, focusing on the possible effects of glycemic control, lifestyle factors, cardiovascular risk factors, and diabetes complications., Research Design and Methods: Cross-sectional data from the Dutch Diabetes Pearl cohort included people with type 2 diabetes from primary, secondary, and tertiary diabetes care programs. We used the 20-item Problem Areas in Diabetes Survey (PAID) scale to assess diabetes distress; a score ≥40 is considered to represent high distress. Ethnicity was estimated on the basis of country of birth. Sociodemographic and lifestyle data were self-reported; cardiovascular and metabolic data were retrieved from medical charts. Logistic regression analysis determined the association between ethnicity and diabetes distress, with Caucasians as the reference group., Results: Diabetes distress scores and ethnicity were available for 4,191 people with type 2 diabetes: 3,684 were Caucasian, 83 were Asian, 51 were Moroccan, 92 were African, 134 were Latin American, 46 were Turkish, and 101 were Hindustani-Surinamese. Overall, participants in minority groups had worse health outcomes than those of Caucasian descent, and diabetes distress was more prevalent (ranging from 9.6 to 31.7%, compared with 5.8% among Caucasians), even after adjusting for age, sex, education level, alcohol use, smoking, BMI, lipid profile, HbA 1c , medication use, and the presence of diabetes complications., Conclusions: Among people with type 2 diabetes in the Netherlands, ethnicity is independently associated with high diabetes distress. Further research is warranted to explain the higher prevalence of diabetes distress in minority groups and to develop effective interventions., (© 2018 by the American Diabetes Association.)

Purpose: Data on the relation between linoleic acid (LA) and alpha-linolenic acid (ALA) and type 2 diabetes mellitus (T2DM) risk are scarce and inconsistent. The aim of this study was to investigate the association of serum LA and ALA with fasting and 2 h post-load plasma glucose and glycated hemoglobin (HbA1c)., Method: This study included 667 participants from third examination (2000) of the population-based Hoorn study in which individuals with glucose intolerance were overrepresented. Fatty acid profiles in serum total lipids were measured at baseline, in 2000. Diabetes risk markers were measured at baseline and follow-up in 2008. Linear regression models were used in cross-sectional and prospective analyses., Results: In cross-sectional analyses (n = 667), serum LA was inversely associated with plasma glucose, both in fasting conditions (B = -0.024 [-0.045, -0.002]) and 2 h after glucose tolerance test (B = -0.099 [-0.158, -0.039]), but not with HbA1c (B = 0.000 [-0.014, 0.013]), after adjustment for relevant factors. In prospective analyses (n = 257), serum LA was not associated with fasting (B = 0.003 [-0.019, 0.025]) or post-load glucose (B = -0.026 [-0.100, 0.049]). Furthermore, no significant associations were found between serum ALA and glucose metabolism in cross-sectional or prospective analyses., Conclusions: In this study, serum LA was inversely associated with fasting and post-load glucose in cross-sectional, but not in prospective analyses. Further studies are needed to elucidate the exact role of serum LA and ALA levels and dietary polyunsaturated fatty acids in glucose metabolism.

Aims: Tailored, patient-centred innovations are needed in the care for persons with type 2 diabetes mellitus (T2DM), in particular those with insufficient glycaemic control. Therefore, this study sought to assess their biopsychosocial characteristics and explore whether distinct biopsychosocial profiles exist within this subpopulation, which differ in health-related quality of life (HRQoL)., Methods: Cross-sectional study based on data from The Maastricht Study, a population-based cohort study focused on the aetiology, pathophysiology, complications, and comorbidities of T2DM. We analysed associations and clustering of glycaemic control and HRQoL with 38 independent variables (i.e. biopsychosocial characteristics) in different subgroups and using descriptive analyses, latent class analysis (LCA), and logistic regressions., Results: Included were 840 persons with T2DM, mostly men (68.6%) and with a mean age of 62.6 (±7.7) years. Mean HbA1c was 7.1% (±3.2%); 308 patients (36.7%) had insufficient glycaemic control (HbA1c>7.0% [53 mmol/mol]). Compared to those with sufficient control, these patients had a significantly worse-off status on multiple biopsychosocial factors, including self-efficacy, income, education and several health-related characteristics. Two 'latent classes' were identified in the insufficient glycaemic control subgroup: with low respectively high HRQoL. Of the two, the low HRQoL class comprised about one-fourth of patients and had a significantly worse biopsychosocial profile., Conclusions: Insufficient glycaemic control, particularly in combination with low HRQoL, is associated with a generally worse biopsychosocial profile. Further research is needed into the complex and multidimensional causal pathways explored in this study, so as to increase our understanding of the heterogeneous care needs and preferences of persons with T2DM, and translate this knowledge into tailored care and support arrangements.

In this cohort of relatively young and well-treated participants with type 2 diabetes, we found no association between diabetes status and a history of previous fractures and recent falls. Furthermore, no association between diabetes severity and previous fractures or recent falls was found., Introduction: In this study, we examined the association between glucose metabolism status and historical fractures or recent falls and the effect of diabetes severity (glucose control, insulin use, and diabetes duration) on falls and fractures in the participants with type 2 diabetes., Methods: Cross-sectional data from 2005 participants of the Maastricht Study. Falls in the past 6 months and fractures ≥age 50 were assessed by questionnaire. Glucose metabolism status (normal glucose metabolism, impaired glucose metabolism, or type 2 diabetes) was based on the oral glucose tolerance test and medication use., Results: In the completely adjusted model, the odds for a fall were not significantly higher in those with impaired glucose metabolism status (OR (95%CI) 1.28 (0.93-1.77)) or with type 2 diabetes (OR (95%CI) 1.21 (0.80-1.81)) compared with the group with normal glucose metabolism. Within the group with type 2 diabetes, there were no significant differences with regard to reported falls between participants with HbA1c >7 % (53 mmol/mol) versus HbA1c ≤7 % (OR (95%CI) 1.05 (0.58-1.90)), insulin users versus non-insulin users (OR (95%CI) 1.51 (0.79-2.89)), and with a diabetes duration >5 versus ≤5 years (OR (95%CI) 0.52 (0.46-1.47)). Similarly, neither glucose metabolism status nor diabetes severity was associated with prior fractures., Conclusions: Glucose metabolism status was not significantly associated with previous fractures and recent falls. In addition, in this cohort of relatively young and well-treated participants with type 2 diabetes, diabetes severity was not associated with previous fractures and recent falls., Competing Interests: Compliance with ethical standards The study has been approved by the institutional medical ethical committee (NL31329.068.10) and the Minister of Health, Welfare and Sports of the Netherlands, on the basis of the Health Council’s opinion (Permit 131088-105234-PG). All participants gave written informed consent. Conflict of interest None.