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OBJECTIVE To determine whether metformin or lifestyle modification can lower rates of all-cause and cause-specific mortality in the Diabetes Prevention Program and Diabetes Prevention Program Outcomes Study. RESEARCH DESIGN AND METHODS From 1996 to 1999, 3,234 adults at high risk for type 2 diabetes were randomized to an intensive lifestyle intervention, masked metformin, or placebo. Placebo and lifestyle interventions stopped in 2001, and a modified lifestyle program was offered to everyone, but unmasked study metformin continued in those originally randomized. Causes of deaths through 31 December 2018 were adjudicated by blinded reviews. All-cause and cause-specific mortality hazard ratios (HRs) were estimated from Cox proportional hazards regression models and Fine-Gray models, respectively. RESULTS Over a median of 21 years (interquartile range 20–21), 453 participants died. Cancer was the leading cause of death (n = 170), followed by cardiovascular disease (n = 131). Compared with placebo, metformin did not influence mortality from all causes (HR 0.99 [95% CI 0.79, 1.25]), cancer (HR 1.04 [95% CI 0.72, 1.52]), or cardiovascular disease (HR 1.08 [95% CI 0.70, 1.66]). Similarly, lifestyle modification did not impact all-cause (HR 1.02 [95% CI 0.81, 1.28]), cancer (HR 1.07 [95% CI 0.74, 1.55]), or cardiovascular disease (HR 1.18 [95% CI 0.77, 1.81]) mortality. Analyses adjusted for diabetes status and duration, BMI, cumulative glycemic exposure, and cardiovascular risks yielded results similar to those for all-cause mortality. CONCLUSIONS Cancer was the leading cause of mortality among adults at high risk for type 2 diabetes. Although metformin and lifestyle modification prevented diabetes, neither strategy reduced all-cause, cancer, or cardiovascular mortality rates.

Albuminuria is an under-recognized component of chronic kidney disease definition, staging, and prognosis. Guidelines, particularly for hypertension, conflict on recommendations for urine albumin-to-creatinine ratio (ACR) measurement. Separately among 1 344 594 adults with diabetes and 2 334 461 nondiabetic adults with hypertension from the chronic kidney disease Prognosis Consortium, we assessed ACR testing, estimated the prevalence and incidence of ACR ≥30 mg/g and developed risk models for ACR ≥30 mg/g. The ACR screening rate (cohort range) was 35.1% (12.3%–74.5%) in diabetes and 4.1% (1.3%–20.7%) in hypertension. Screening was largely unrelated to the predicted risk of prevalent albuminuria. The median prevalence of ACR ≥30 mg/g across cohorts was 32.1% in diabetes and 21.8% in hypertension. Higher systolic blood pressure was associated with a higher prevalence of albuminuria (odds ratio [95% CI] per 20 mm Hg in diabetes, 1.50 [1.42–1.60]; in hypertension, 1.36 [1.28–1.45]). The ratio of undetected (due to lack of screening) to detected ACR ≥30 mg/g was estimated at 1.8 in diabetes and 19.5 in hypertension. Among those with ACR

BACKGROUND AND OBJECTIVES: Low serum 25-hydroxyvitamin D (25[OH]D) concentration has been associated with higher levels of proteinuria and lower levels of eGFR in observational studies. In the Vitamin D and Type 2 Diabetes (D2d) study, we investigated the effect of vitamin D supplementation on kidney outcomes in a population with prediabetes. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Overweight/obese adults with high risk for type 2 diabetes (defined by meeting two of three glycemic criteria for prediabetes) were randomized to vitamin D(3) 4000 IU per day versus placebo. Median duration of treatment was 2.9 years (interquartile range 2.0–3.5 years). Kidney outcomes included (1) worsening in Kidney Disease: Improving Global Outcomes (KDIGO ) risk score (low, moderate, high, very high) on two consecutive follow-up visits after the baseline visit and (2) mean changes in eGFR and urine albumin-to-creatinine ratio (UACR). RESULTS: Among 2166 participants (mean age 60 years, body mass index 32 kg/m(2), serum 25(OH)D 28 ng/ml, eGFR 87 ml/min per 1.73 m(2), UACR 11 mg/g, 79% with hypertension), 10% had moderate, high, or very high KDIGO risk score. Over a median follow-up of 2.9 years, there were 28 cases of KDIGO worsening in the vitamin D group and 30 in the placebo group (hazard ratio, 0.89; 95% confidence interval [95% CI], 0.52 to 1.52]). Mean difference in eGFR from baseline was −1.0 ml/min per 1.73 m(2) (95% CI, −1.3 to −0.7) in the vitamin D group and −0.1 ml/min per 1.73 m(2) (95% CI, −0.4 to 0.2) in the placebo group; between-group difference was −1.0 ml/min per 1.73 m(2) (95% CI, −1.4 to −0.6). Mean difference in UACR was 2.7 mg/g (95% CI, 1.2 to 4.3) in the vitamin D group and 2.0 (95% CI, 0.5 to 3.6) in the placebo group; between-group difference was 0.7 mg/g (95% CI, −1.5 to 2.9). CONCLUSIONS: Among persons with prediabetes, who were not preselected on the basis of serum 25(OH)D concentration, vitamin D supplementation did not affect progression of KDIGO risk scores and did not have a meaningful effect on change in UACR or eGFR.

Objective The Action for Health in Diabetes (Look AHEAD) study previously reported that intensive lifestyle intervention (ILI) reduced incident depressive symptoms and improved health-related quality of life (HRQOL) over nearly 10 years of intervention compared with a control group (the diabetes support and education group [DSE]) in participants with type 2 diabetes and overweight or obesity. The present study compared incident depressive symptoms and changes in HRQOL in these groups for an additional 6 years following termination of the ILI in September 2012. Methods A total of 1,945 ILI participants and 1,900 DSE participants completed at least one of four planned postintervention assessments at which weight, mood (via the Patient Health Questionnaire-9), antidepressant medication use, and HRQOL (via the Medical Outcomes Scale, Short Form-36) were measured. Results ILI participants and DSE participants lost 3.1 (0.3) and 3.8 (0.3) kg [represented as mean (SE); p = 0.10], respectively, during the 6-year postintervention follow-up. No significant differences were observed between groups during this time in incident mild or greater symptoms of depression, antidepressant medication use, or in changes on the physical component summary or mental component summary scores of the Short Form-36. In both groups, mental component summary scores were higher than physical component summary scores. Conclusions Prior participation in the ILI, compared with the DSE group, did not appear to improve subsequent mood or HRQOL during 6 years of postintervention follow-up.

Context Observational studies suggest that low vitamin D status may be a risk factor for cancer. Objective In a population with prediabetes and overweight/obesity that is at higher risk of cancer than the general population, we sought to determine if vitamin D supplementation lowers the risk of cancer and precancers. Methods The Vitamin D and type 2 diabetes (D2d) cancer outcomes study (D2dCA) is an ancillary study to the D2d study, which was conducted at 22 academic medical centers in the United States. Participants had prediabetes and overweight/obesity and were free of cancer for the previous 5 years. Participants were randomized to receive vitamin D3 4000 IU daily or placebo. At scheduled study visits (4 times/year), cancer and precancer events were identified by questionnaires. Clinical data were collected and adjudicated for all reported events. Cox proportional hazard models compared the hazard ratio (HR) of incident cancers and precancers between groups. Results Over a median follow-up period of 2.9 years, among 2385 participants (mean age 60 years and 25-hydroxyvitamin D 28 ng/mL), there were 89 cases of cancer. The HR of incident cancer for vitamin D vs placebo was 1.07 (95% CI 0.70, 1.62). Of 241 participants with incident precancers, 239 had colorectal adenomatous polyps. The HR for colorectal polyps for vitamin D vs placebo was 0.83 (95% CI 0.64, 1.07). Conclusion In the D2d population of participants with prediabetes and overweight/obesity, not selected for vitamin D insufficiency, vitamin D supplementation did not have a significant effect on risk of incident cancer or colorectal polyps.

Background Among patients with type 2 diabetes, minority racial/ethnic groups have a higher burden of cardiovascular disease, chronic kidney disease, and hypoglycaemia. These groups may especially benefit from newer diabetes medication classes, but high cost may limit access. We examined the association of race/ethnicity with the initiation of newer diabetes medications (GLP-1 receptor agonists, DPP-4 inhibitors, SGLT-2 inhibitors). Methods We conducted a secondary analysis of the Look AHEAD (Action for Health in Diabetes) trial including participants with at least one study visit after April 28, 2005. Cox proportional hazards models were used to estimate the association between race/ethnicity and socioeconomic factors with time to initiation of any newer diabetes medication from April 2005 to February 2020. Models were adjusted for demographic and clinical characteristics. Findings Among 4,892 participants, 63.6%, 15.7%, 12.6%, 5.2%, and 2.9% were White, Black, Hispanic, American Indian or Alaskan Native (AI/AN), or other race/ethnicity, respectively. During a median follow-up of 8.3 years, 2,180 (45.2%) participants were initiated on newer diabetes medications. Race/ethnicity was associated with newer diabetes medication initiation (p=.019). Specifically, initiation was lower among Black (HR 0.81, 95% CI 0.70–0.94) and AI/AN participants (HR 0.51, 95% CI 0.26–0.99). Yearly family income was inversely associated with initiation of newer diabetes medications (HR 0.78, 95% CI 0.62–0.98) comparing the lowest and highest income groups. Findings were mostly driven by GLP-1 receptor agonists. Interpretation These findings provide evidence of racial/ethnic disparities in the initiation of newer diabetes medications, independent of socioeconomic factors, which may contribute to worse health outcomes. Funding source NIDDK, NIH

OBJECTIVE Across the Diabetes Prevention Program (DPP) follow-up, cumulative diabetes incidence remained lower in the lifestyle compared with the placebo and metformin randomized groups and could not be explained by weight. Collection of self-reported physical activity (PA) (yearly) with cross-sectional objective PA (in follow-up) allowed for examination of PA and its long-term impact on diabetes prevention. RESEARCH DESIGN AND METHODS Yearly self-reported PA and diabetes assessment and oral glucose tolerance test results (fasting glucose semiannually) were collected for 3,232 participants with one accelerometry assessment 11–13 years after randomization (n = 1,793). Mixed models determined PA differences across treatment groups. The association between PA and diabetes incidence was examined using Cox proportional hazards models. RESULTS There was a 6% decrease (Cox proportional hazard ratio 0.94 [95% CI 0.92, 0.96]; P < 0.001) in diabetes incidence per 6 MET-h/week increase in time-dependent PA for the entire cohort over an average of 12 years (controlled for age, sex, baseline PA, and weight). The effect of PA was greater (12% decrease) among participants less active at baseline ( CONCLUSIONS PA was inversely related to incident diabetes in the entire cohort across the study, with cross-sectional accelerometry results supporting these findings. This highlights the importance of PA within lifestyle intervention efforts designed to prevent diabetes and urges health care providers to consider both PA and weight when counseling high-risk patients.

OBJECTIVE Postrandomization biases may influence the estimate of efficacy of supplemental vitamin D in diabetes prevention trials. In the Vitamin D and Type 2 Diabetes (D2d) study, repeated measures of serum 25-hydroxyvitamin D [25(OH)D] level provided an opportunity to test whether intratrial vitamin D exposure affected diabetes risk and whether the effect was modified by trial assignment (vitamin D vs. placebo). RESEARCH DESIGN AND METHODS The D2d study compared the effect of daily supplementation with 100 μg (4,000 units) of vitamin D3 versus placebo on new-onset diabetes in adults with prediabetes. Intratrial vitamin D exposure was calculated as the cumulative rolling mean of annual serum 25(OH)D measurements. Hazard ratios for diabetes among participants who had intratrial 25(OH)D levels of RESULTS There was an interaction of trial assignment with intratrial 25(OH)D level in predicting diabetes risk (interaction P = 0.018). The hazard ratio for diabetes for an increase of 25 nmol/L in intratrial 25(OH)D level was 0.75 (95% CI 0.68–0.82) among those assigned to vitamin D and 0.90 (0.80–1.02) among those assigned to placebo. The hazard ratios for diabetes among participants treated with vitamin D who maintained intratrial 25(OH)D levels of 100–124 and ≥125 nmol/L were 0.48 (0.29–0.80) and 0.29 (0.17–0.50), respectively, compared with those who maintained a level of 50–74 nmol/L. CONCLUSIONS Daily vitamin D supplementation to maintain a serum 25(OH)D level ≥100 nmol/L is a promising approach to reducing the risk of diabetes in adults with prediabetes.

AIMS/HYPOTHESIS: Prevalence of type 2 diabetes differs among human ancestry groups, and many hypotheses invoke differential natural selection to account for these differences. We sought to assess the potential role of differential natural selection across major continental ancestry groups for diabetes and related traits, by comparison of genetic and phenotypic differences. METHODS: This was a cross-sectional comparison among 734 individuals from an urban sample (none of whom was more closely related to another than third-degree relatives), including 83 African Americans, 523 American Indians and 128 European Americans. Participants were not recruited based on diabetes status or other traits. BMI was calculated, and diabetes was diagnosed by a 75 g oral glucose tolerance test. In those with normal glucose tolerance (n=434), fasting insulin and 30 min post-load insulin, adjusted for 30 min glucose, were taken as measures of insulin resistance and secretion, respectively. Whole exome sequencing was performed, resulting in 97,388 common (minor allele frequency >5%) variants; the coancestry coefficient (F(ST)) was calculated across all markers as a measure of genetic divergence among ancestry groups. The phenotypic divergence index (P(ST)) was also calculated from the phenotypic differences and heritability (which was estimated from genetic relatedness calculated empirically across all markers in 761 American Indian participants prior to the exclusion of close relatives). Under evolutionary neutrality, the expectation is P(ST)=F(ST), while for traits under differential selection P(ST) is expected to be significantly greater than F(ST.) A bootstrap procedure was used to test the hypothesis P(ST)=F(ST.) RESULTS: With adjustment for age and sex, prevalence of type 2 diabetes was 34.0% in American Indians, 12.4% in African Americans and 10.4% in European Americans (p=2.9×10(−10) for difference among groups). Mean BMI was 36.3, 33.4 and 33.0 kg/m(2), respectively (p=1.9×10(−7)). Mean fasting insulin was 63.8, 48.4 and 45.2 pmol/l (p=9.2×10(−5)), while mean 30 min insulin was 559.8, 553.5 and 358.8 pmol/l, respectively (p=5.7×10(−8)). F(ST) across all markers was 0.130, while P(ST) for liability to diabetes, adjusted for age and sex, was 0.149 (p=0.35 for difference with F(ST)). P(ST) was 0.094 for BMI (p=0.54), 0.095 for fasting insulin (p=0.54) and 0.216 (p=0.18) for 30 min insulin. For type 2 diabetes and BMI, the maximum divergence between populations was observed between American Indians and European Americans (P(ST-MAX)=0.22, p=0.37, and P(ST-MAX)=0.14, p=0.61), which suggests that a relatively modest 22% or 14% of the genetic variance, respectively, can potentially be explained by differential selection (assuming the absence of neutral drift). CONCLUSIONS/INTERPRETATION: These analyses suggest that while type 2 diabetes and related traits differ significantly among continental ancestry groups, the differences are consistent with neutral expectations based on heritability and genetic distances. While these analyses do not exclude a modest role for natural selection, they do not support the hypothesis that differential natural selection is necessary to explain the phenotypic differences among these ancestry groups.

Objective This study was designed to determine whether intensive lifestyle intervention (ILI) aimed at weight loss lowers cancer incidence and mortality. Methods Data from the Look AHEAD trial were examined to investigate whether participants randomized to ILI designed for weight loss would have reduced overall cancer incidence, obesity-related cancer incidence, and cancer mortality, as compared with the diabetes support and education (DSE) comparison group. This analysis included 4,859 participants without a cancer diagnosis at baseline except for nonmelanoma skin cancer. Results After a median follow-up of 11 years, 684 participants (332 in ILI and 352 in DSE) were diagnosed with cancer. The incidence rates of obesity-related cancers were 6.1 and 7.3 per 1,000 person-years in ILI and DSE, respectively, with a hazard ratio (HR) of 0.84 (95% CI: 0.68-1.04). There was no significant difference between the two groups in total cancer incidence (HR, 0.93; 95% CI: 0.80-1.08), incidence of nonobesity-related cancers (HR, 1.02; 95% CI: 0.83-1.27), or total cancer mortality (HR, 0.92; 95% CI: 0.68-1.25). Conclusions An ILI aimed at weight loss lowered incidence of obesity-related cancers by 16% in adults with overweight or obesity and type 2 diabetes. The study sample size likely lacked power to determine effect sizes of this magnitude and smaller.

AIMS: To examine the associations of average weight and weight velocity in three growth periods from birth through adolescence with type 2 diabetes incidence. METHODS: Child participants representing three growth periods- pre-adolescence (birth to ~8 years), early adolescence (~8 to ~13 years), and late adolescence (~13 to ~18 years) -were selected from a 43-year longitudinal study of American Indians. Age-sex-height-standardized average weight z score and weight z score velocity (change/year) were computed in each period. Participants were followed for up to 25 years from the end of each growth period until they developed diabetes. Associations of average weight z score or weight z score velocity with diabetes incidence were determined with sex-, birth date- and maternal diabetes-adjusted Poisson regression models. RESULTS: Among 2,100 participants representing the pre-adolescence growth period, 1,558 representing the early adolescence period, and 1,418 representing the late adolescence period, there were 290, 315, and 380 incident diabetes cases, respectively. During the first 10 years of follow-up, diabetes incidence rate ratio was 1.72 (95% CI 1.40–2.11)/standard deviation (SD) of log(10)weight z score mean in pre-adolescence, 2.09 (1.68–2.60)/SD of log(10)weight z score mean in early adolescence, and 1.85 (1.58–2.17)/SD of log(10)weight z score mean in late adolescence. Diabetes incidence rate ratio was 1.79 (1.49–2.17)/SD of log(10)weight z score velocity pre-adolescence, 1.13 (0.91–1.41)/SD log(10)weight z score velocity in early adolescence, and 1.29 (1.09–1.51)/SD log(10)weight z score velocity in late adolescence. There were strong correlations in the average weight z scores and weak correlations in the weight z score velocities between successive periods. CONCLUSIONS: Higher weight and accelerated weight gain in all growth periods associates with increased type 2 diabetes risk. Importantly, higher weight and greater weight velocity pre-adolescence jointly associate with the highest type 2 diabetes risk.

Objective: This study evaluated weight changes after cessation of the 10-year intensive lifestyle intervention (ILI) in the Look AHEAD (Action for Health in Diabetes) study. It was hypothesized that ILI participants would be more likely to gain weight during the 2-year observational period following termination of weight-loss-maintenance counseling than would participants in the diabetes support and education (DSE) control group. Methods: Look AHEAD was a randomized controlled trial that compared the effects of ILI and DSE on cardiovascular morbidity and mortality in participants with overweight/obesity and type 2 diabetes. Look AHEAD was converted to an observational study in September 2012. Results: Two years after the end of the intervention (EOI), ILI and DSE participants lost a mean (SE) of 1.2 (0.2) kg and 1.8 (0.2) kg, respectively (P = 0.003). In addition, 31% of ILI and 23.9% of DSE participants gained ≥ 2% (P < 0.001) of EOI weight, whereas 36.3% and 45.9% of the respective groups lost ≥ 2% of EOI weight (P = 0.001). Two years after the EOI, ILI participants reported greater use of weight-control behaviors than DSE participants. Conclusions: Both groups lost weight during the 2-year follow-up period, but more ILI than DSE participants gained ≥ 2% of EOI weight. Further understanding is needed of factors that affected long-term weight change in both groups.

Objective Fasting plasma glucose (FPG), 2-hour plasma glucose (2hPG) from a 75-g oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) can lead to different results when diagnosing prediabetes and diabetes. The Hemoglobin Glycation Index (HGI) quantifies the interindividual variation in glycation resulting in discrepancies between FPG and HbA1c. We used data from the Vitamin D and Type 2 Diabetes (D2d) study to calculate HGI, to identify HGI-associated variables, and to determine how HGI affects prediabetes and diabetes diagnosis. Measurements A linear regression equation [HbA1c (%) = 0.0164 × FPG (mg/dL) + 4.2] was derived using the screening cohort (n = 6829) and applied to calculate predicted HbA1c. This was subtracted from the observed HbA1c to determine HGI in the baseline cohort with 2hPG data (n = 3945). Baseline variables plus prediabetes and diabetes diagnosis by FPG, HbA1c, and 2hPG were compared among low, moderate, and high HGI subgroups. Results The proportion of women and Black/African American individuals increased from low to high HGI subgroups. Mean FPG decreased and mean HbA1c increased from low to high HGI subgroups, consistent with the HGI calculation; however, mean 2hPG was not significantly different among HGI subgroups. Conclusions High HGI was associated with Black race and female sex as reported previously. The observation that 2hPG was not different across HGI subgroups suggests that variation in postprandial glucose is not a significant source of population variation in HGI. Exclusive use of HbA1c for diagnosis will classify more Black individuals and women as having prediabetes compared with using FPG or 2hPG.

Objective The extent to which infertility and pregnancy independently increase risk of diabetes and subclinical atherosclerosis is not known. Research Design And Methods We conducted a secondary analysis of Diabetes Prevention Program (DPP) and the DPP Outcomes Study over a 15-year period. We included women who answered questions about gravidity and infertility at baseline (n = 2085). Infertility was defined as > 1 year of unsuccessful attempts to conceive; thus, women could have histories of infertility as well as pregnancy. Risk of diabetes associated with gravidity and infertility was calculated using Cox proportional hazards models adjusting for age, race/ethnicity, treatment arm, body mass index, and pregnancy during the study. Among women who underwent assessment of coronary artery calcification (CAC) (n = 1337), odds of CAC were calculated using logistic regression models with similar covariates. Results Among premenopausal women (n = 1075), women with histories of pregnancy and infertility (n = 147; hazard ratio [HR] 1.80; 95% confidence interval [CI] 1.30, 2.49) and women with histories of pregnancy without infertility (n = 736; HR 1.49; 95% CI 1.15, 1.93) had greater diabetes risk than nulligravid women without infertility (n = 173). Premenopausal nulligravid women with histories of infertility had a non-significant elevation in risk, although the number of these women was small (n = 19; HR 1.63; 95% CI 0.88, 3.03). Associations were not observed among postmenopausal women (n = 1010). No associations were observed between infertility or pregnancy with CAC. Conclusions Pregnancy, particularly combined with a history of infertility, confers increased risk of diabetes but not CAC among glucose-intolerant premenopausal women.

Objective To examine the effects of an intensive lifestyle intervention (ILI) on cardiovascular disease (CVD), the Action for Health in Diabetes (Look AHEAD) trial randomized 5,145 participants with type 2 diabetes and overweight/obesity to a ILI or diabetes support and education. Although the primary outcome did not differ between the groups, there was suggestive evidence of heterogeneity for prespecified baseline CVD history subgroups (interaction P = 0.063). Event rates were higher in the ILI group among those with a CVD history (hazard ratio 1.13 [95% CI: 0.90-1.41]) and lower among those without CVD (hazard ratio 0.86 [95% CI: 0.72-1.02]). Methods This study conducted post hoc analyses of the rates of the primary composite outcome and components, adjudicated cardiovascular death, nonfatal myocardial infarction (MI), stroke, and hospitalization for angina, as well as three secondary composite cardiovascular outcomes. Results Interaction P values for the primary and two secondary composites were similar (0.060-0.064). Of components, the interaction was significant for nonfatal MI (P = 0.035). This interaction was not due to confounding by baseline variables, different intervention responses for weight loss and physical fitness, or hypoglycemic events. In those with a CVD history, statin use was high and similar by group. In those without a CVD history, low-density lipoprotein cholesterol levels were higher (P = 0.003) and statin use was lower (P ≤ 0.001) in the ILI group. Conclusions Intervention response heterogeneity was significant for nonfatal MI. Response heterogeneity may need consideration in a CVD-outcome trial design.

PURPOSE OF REVIEW: The present review focuses on the epidemiology of type 2 diabetes (T2D) in Indigenous communities in the continental United States (U.S.)—including disease prevention and management—and discusses special considerations in conducting research with Indigenous communities. RECENT FINDINGS: Previous studies have reported the disparately high prevalence of diabetes, especially T2D, among Indigenous peoples in the U.S. The high prevalence and incidence of early-onset T2D in Indigenous youth relative to that of all youth in the U.S. population poses challenges to the prevention of complications of diabetes. SUMMARY: Behavioral, dietary, lifestyle and genetic factors associated with T2D in Indigenous communities are often investigated. More limited is discussion of the historical and ongoing consequences of colonization and displacement that impact the aforementioned risk factors. Future research is necessary to assess community-specific needs with respect to diabetes prevention and management across the diversity of Indigenous communities in the U.S.

Objective: This study investigated associations of adiposity and adiposity-related biomarkers with incident type 2 diabetes (T2D) among parous women. Methods: Among women in the Diabetes Prevention Program (DPP) who reported a previous live birth, circulating biomarkers (leptin, adiponectin, sex hormone-binding globulin, and alanine aminotransferase; n = 1,711) were measured at enrollment (average: 12 years post partum). Visceral (VAT) and subcutaneous adipose tissue areas at the L2-L3 region and the L3-L4 region were quantified by computed tomography (n = 477). Overall and stratified (by history of gestational diabetes mellitus [GDM]) adjusted Cox proportional hazards models were fit. Results: Alanine aminotransferase, L2-L3 VAT, and L3-L4 VAT were positively associated (hazard ratio [HR] for 1-SD increases: 1.073, p = 0.024; 1.251, p = 0.009; 1.272, p = 0.004, respectively), and adiponectin concentration was inversely associated with T2D (HR 0.762, p < 0.001). Whereas leptin concentration was not associated with T2D overall, in GDM-stratified models, a 1-SD higher leptin was positively associated with risk of T2D in women without GDM (HR: 1.126, p = 0.016) and inversely in women with a history of GDM (HR: 0.776, p = 0.013, interaction p = 0.002). Conclusions: Among parous women, alanine aminotransferase and VAT are positively associated with incident T2D, whereas adiponectin is inversely associated. Leptin is associated with higher risk of T2D in women with a history of GDM but a lower risk in women without a history of GDM. © 2021 The Obesity Society (TOS). This article has been contributed to by US Government employees and their work is in the public domain in the USA.

We assessed whether the relationship between insulin secretion and sensitivity predicted development of type 2 diabetes in American Indians participating in a longitudinal epidemiologic study. At baseline, when all participants did not have diabetes, 1,566 underwent oral tests and 420 had intravenous measures of glucose regulation, with estimates of insulin secretion and sensitivity. Standardized major axis regression was used to study the relationship between secretion and sensitivity. Distances away from and along the regression line estimated compensatory insulin secretion and secretory demand, respectively. This relationship differed according to glucose tolerance and BMI category. The distance away from the line is similar to the disposition index (DI), defined as the product of estimated secretion and sensitivity, but the regression line may differ from a line with constant DI (i.e., it is not necessarily hyperbolic). Participants with the same DI but different levels of insulin secretion and sensitivity had different incidence rates of diabetes; lower sensitivity with higher secretory demand was associated with greater diabetes risk. Insulin secretion and insulin sensitivity, analyzed together, predict diabetes better than DI alone. Physiologically, this may reflect long-term risk associated with increased allostatic load resulting from the stimulation of insulin hypersecretion by increased glycemia.

Prospective studies in informative populations are crucial to increasing our knowledge of disease. In this perspective, we describe a half century of studies in an American Indian population that transformed our understanding of kidney disease in type 2 diabetes, now recognized as the leading cause of kidney failure worldwide. Serial examinations conducted for many years that included the collection of data and samples across multiple domains captured an unprecedented volume of clinical, physiologic, morphometric, genomic, and transcriptomic data. This work permitted us to extensively characterize the course and determinants of diabetic kidney disease, its pathophysiologic underpinnings, and important secular trends of urgent concern to populations worldwide, including the emergence of youth-onset type 2 diabetes and its effect on development of diabetic kidney disease in midlife. By combining these data using the tools of integrative biology, we are developing new mechanistic insights into the development and progression of diabetic kidney disease in type 2 diabetes. These insights have already contributed to the identification and successful therapeutic targeting of a novel pathway in DKD. We anticipate that this work will continue to expand our understanding of this complex disease and influence its management in the coming years.

Objective Prior studies identified single nucleotide polymorphisms (SNPs) associated with physical activity (PA) level in a natural environment and intervention study: rs978656-DNAPTP6, rs10887741-PAPSS2, rs7279064-C18orf2, and rs6265-BDNF. Using the four SNPs' polygenic score (PGS), we examined whether PGS moderates a life-style intervention's effect on changes in PA level and cardiorespiratory fitness (CRF). Methods This is a secondary analysis of Look AHEAD, a multicenter randomized controlled trial designed to test the health benefits of a life-style intervention among 2675 participants with overweight/obesity and type 2 diabetes (ages, 45-76 years). Using linear mixed-effects models, level of PA (Paffenbarger PA questionnaire) and treadmill-assessed CRF were each regressed on four SNPs' PGS, study time (baseline, year 1, and year 4), intervention arm, and interactions between the three. Models adjusted for age, sex, body mass index, ancestry principal components (population stratification), and study sites, with Bonferroni corrections for multiple testing (α Results PGS was not predictive of change in CRF or PA level in response to intervention. In analyses without PGS by intervention by time, the relationships between PGS and PA phenotypes were modified by age (p interaction = .048 for CRF and .058 for PA), such that a 1-unit increase in PGS was associated with 24 kcal · wk-1 more in moderate-intensity PA and 0.004 MET higher CRF only among older groups (age >55 years for CRF, >60 years for PA level). Conclusions The effects of the intervention on PA and CRF were not moderated by the four SNPs. Future studies with extended SNP list should confirm the findings on effect modification by age.

There is considerable evidence that birth weight is associated with increased risk of type 2 diabetes (T2D) in adulthood. However, evidence from populations with high prevalence of T2D on the genetic relationships between birth weight and T2D is limited. Data were obtained from a genome-wide association study (GWAS) in an Indigenous population from the Southwest US with high prevalence of T2D in which the relationship of T2D with birth weight is “U-shaped." Weighted polygenic scores (PSs) were constructed using imputed genotypes for genome-wide significant single-nucleotide polymorphisms (SNPs) from GWAS meta-analyses for birth weight (EGG Consortium, 126 SNPs) and T2D (DIAGRAM Consortium, 293 SNPs). Associations of birth weight PS and T2D PS with T2D and birth weight were calculated, accounting for participants’ pairwise relationships, using linear mixed models. Birth weight data (n=3700) were normalized separately by sex and analyzed for associations, adjusted for birth year, gestational age and the first 5 genetic principal components (PCs). T2D (n=7659) data were analyzed for associations, adjusted for age, sex, birth year and the first 5 genetic PCs. Birth weight PS had a significant, positive association with birth weight (β=0.134 SD birth weight per SD PS (95% CI 0.101, 0.168); p=4.1×10-15). The T2D PS was likewise significantly, positively associated with T2D (OR=1.48 per SD (1.38, 1.58); p=8.1×10-31). The birth weight PS was significantly, inversely associated with T2D (OR=0.91 (0.85, 0.97); p=0.0043); we found no evidence for a non-linear relationship between birth weight PS and T2D (p=0.80). The T2D PS was not significantly associated with birth weight (β=-0.005 (-0.040, 0.030); p=0.80). Results indicate that genetic variants that associate with birth weight and T2D from larger European GWAS largely also influence these traits in this Indigenous population. Current findings also support the notion that many variants conferring susceptibility to low birth weight also confer susceptibility to T2D. Disclosure L. E. Wedekind: None. W. Hsueh: None. M. Olaiya: None. S. Kobes: None. L. Baier: None. W. C. Knowler: None. A. Mahajan: Employee; Self; Genentech, Inc. M. Mccarthy: Employee; Self; Genentech, Inc. R. L. Hanson: None.

Genome-wide significant (GWS) loci for glycemic response to MET in type 2 diabetes (T2D) reported elsewhere have not replicated in the DPP. Thus, to assess whether pharmacogenetic interactions may differ in impaired glucose tolerance (IGT), we conducted a GWAS in the DPP for MET response, defined by diabetes incidence and change in quantitative traits (fasting glucose, 2-hour glucose on oral glucose tolerance test, hemoglobin A1c [HbA1c], fasting insulin, insulin sensitivity index, and weight). Samples were genotyped on the Illumina HumanCore Exome array and imputed on the 1000 Genomes Phase3 panel. Cox proportional hazards models tested associations with diabetes incidence in MET (n=876) and placebo (PBO, n=887) arms. Multiple linear regression using an additive model evaluated for association with 1-year change in quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-environment (G×E) interaction between MET and PBO. Results were filtered to minor allele frequency (MAF) >1% and imputation score >0.7. We identified 3 GWS variants after correcting for correlated traits (P In summary, a GWAS for MET response in participants with IGT revealed novel associations that require validation in ancestry-specific populations and may have implications for tailored therapy. Disclosure J. H. Li: None. R. L. Hanson: None. S. E. Kahn: Advisory Panel; Self; Bayer AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk, Pfizer Inc. W. C. Knowler: None. T. I. Pollin: None. J. C. Florez: Consultant; Self; Goldfinch Bio, Inc., Other Relationship; Self; Novo Nordisk. D. Research group: None. J. A. Perry: None. K. A. Jablonski: None. L. Chen: None. S. Srinivasan: None. J. N. Todd: None. M. Harden: None. J. M. Mercader: None. P. W. Franks: Advisory Panel; Self; Zoe Global Limited, Consultant; Self; Eli Lilly and Company, Novo Nordisk. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK048489)

Polygenic scores (PS) of T2D genetic variants based on pathophysiologic mechanisms underlying diabetes have been developed. We investigated whether T2D cluster PS influences response to interventions for diabetes prevention. We examined 2,647 DPP participants with impaired glucose tolerance and genetic data randomized to intensive lifestyle, metformin or placebo arms for diabetes prevention. We generated five PS clusters including β-cell related clusters (β-cell, proinsulin) and insulin resistance clusters (liver/lipid, obesity, lipodystrophy). We examined associations of PS with baseline and 1-year glycemic traits after intervention derived from oral glucose tolerance tests using general linear models, and with diabetes incidence over an average period of 3 years using Cox Regression Models. Models were adjusted for sex, age, and 10 principal components, respective baseline trait, and treatment group. At one-year follow-up, β-cell PS was associated with reduction in the insulinogenic index and corrected insulin response, in each treatment group and, statistically significant, in all combined (P We conclude that high genetic burden in β-cell cluster PS is associated with greater risk of diabetes and a decrease in insulin secretion, seen across all treatment groups. Despite interventions with intensive lifestyle and metformin, participants with high β-cell cluster genetic burden had an increased risk of diabetes and worsening in insulin secretion similar to placebo group. These data suggest that alternate therapies may be needed to prevent β-cell decline in this subset of prediabetes patients. Disclosure L. K. Billings: Advisory Panel; Self; Bayer Inc., Lilly Diabetes, Novo Nordisk, Sanofi. S. Raghavan: None. S. Srinivasan: None. J. Xu: None. J. C. Florez: Consultant; Self; Goldfinch Bio, Inc., Other Relationship; Self; Novo Nordisk. M. Udler: None. D. Research group: None. K. A. Jablonski: None. P. W. Franks: Advisory Panel; Self; Zoe Global Limited, Consultant; Self; Eli Lilly and Company, Novo Nordisk. R. B. Goldberg: None. M. Hivert: None. S. E. Kahn: Advisory Panel; Self; Bayer AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk, Pfizer Inc. W. C. Knowler: None. C. Lee: None. J. Merino: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK048489)

OBJECTIVE Regression from prediabetes to normal glucose regulation (NGR) was associated with reduced incidence of diabetes by 56% over 10 years in participants in the Diabetes Prevention Program Outcomes Study (DPPOS). In an observational analysis, we examined whether regression to NGR also reduced risk for microvascular disease (MVD). RESEARCH DESIGN AND METHODS Generalized estimating equations were used to examine the prevalence of aggregate MVD at DPPOS year 11 in people who regressed to NGR at least once (vs. never) during the Diabetes Prevention Program (DPP). Logistic regression assessed the relationship of NGR with retinopathy, nephropathy, and neuropathy, individually. Generalized additive models fit smoothing splines to describe the relationship between average A1C during follow-up and MVD (and its subtypes) at the end of follow-up. RESULTS Regression to NGR was associated with lower prevalence of aggregate MVD in models adjusted for age, sex, race/ethnicity, baseline A1C, and treatment arm (odds ratio [OR] 0.78, 95% CI 0.65–0.78, P = 0.011). However, this association was lost in models that included average A1C during follow-up (OR 0.95, 95% CI 0.78–1.16, P = 0.63) or diabetes status at the end of follow-up (OR 0.92, 95% CI 0.75–1.12, P = 0.40). Similar results were observed in examination of the association between regression to NGR and prevalence of nephropathy and retinopathy, individually. Risk for aggregate MVD, nephropathy, and retinopathy increased across the A1C range. CONCLUSIONS Regression to NGR is associated with a lower prevalence of aggregate MVD, nephropathy, and retinopathy, primarily due to lower glycemic exposure over time. Differential risk for the MVD subtypes begins in the prediabetes A1C range.

The global epidemic of type 2 diabetes has prompted numerous studies and public health efforts to reduce its development. A variety of interventions, including lifestyle modifications and pharmacological agents directed at ameliorating the major risk factors for type 2 diabetes, are of proven efficacy in reducing the development of type 2 diabetes in people with impaired glucose tolerance. While prevention of the hyperglycaemia characteristic of diabetes is arguably an important, clinically relevant outcome, a more compelling outcome with greater clinical significance is the prevention or reduction of the relatively diabetes-specific microvascular and less-specific cardiovascular disease (CVD) complications associated with diabetes. These complications cause the majority of morbidity and excess mortality associated with diabetes. Any reduction in diabetes should, logically, also reduce the occurrence of its long-term complications; however, most diabetes prevention trials have not been of sufficient duration to allow such an evaluation. The limited long-term data, largely from the Da Qing Diabetes Prevention Study (DQDPS) and the Diabetes Prevention Program (DPP) and their respective follow-up studies (DQDPOS and DPPOS), suggest a reduction in microvascular complications and amelioration of CVD risk factors. Only the DQDPOS and Study to Prevent Non-Insulin-Dependent Diabetes Mellitus (STOP-NIDDM) studies have shown a reduction in CVD events and only DQDPOS has demonstrated a decrease in CVD and overall mortality. While these limited data are promising, whether diabetes prevention directly reduces complication-related morbidity and mortality remains unclear. Longer follow-up of prevention studies is needed to supplement the limited current clinical trial data, to help differentiate the effects of diabetes prevention itself from the means used to reduce diabetes development and to understand the balance among benefits, risks and costs of prevention.

Context There is substantial heterogeneity in insulin sensitivity, and genetics may suggest possible mechanisms by which common variants influence this trait. Objectives We aimed to evaluate an 11-variant polygenic lipodystrophy genetic risk score (GRS) for association with anthropometric, glycemic and metabolic traits in the Diabetes Prevention Program (DPP). In secondary analyses, we tested the association of the GRS with cardiovascular risk factors in the DPP. Design In 2713 DPP participants, we evaluated a validated GRS of 11 common variants associated with fasting insulin-based measures of insulin sensitivity discovered through genome-wide association studies that cluster with a metabolic profile of lipodystrophy, conferring high metabolic risk despite low body mass index (BMI). Results At baseline, a higher polygenic lipodystrophy GRS was associated with lower weight, BMI, and waist circumference measurements, but with worse insulin sensitivity index (ISI) values. Despite starting at a lower weight and BMI, a higher GRS was associated with less weight and BMI reduction at one year and less improvement in ISI after adjusting for baseline values but was not associated with diabetes incidence. A higher GRS was also associated with more atherogenic low-density lipoprotein peak-particle-density at baseline but was not associated with coronary artery calcium scores in the Diabetes Prevention Program Outcomes Study. Conclusions In the DPP, a higher polygenic lipodystrophy GRS for insulin resistance with lower BMI was associated with diminished improvement in insulin sensitivity and potential higher cardiovascular disease risk. This GRS helps characterize insulin resistance in a cohort of individuals at high risk for diabetes, independent of adiposity.

Rationale & Objective - An elevated glomerular filtration rate (GFR), or renal hyperfiltration, may predispose individuals to subsequent rapid GFR decline in diabetes, obesity, and metabolic syndrome. Although this hypothesis is supported by results of experimental studies, the importance of hyperfiltration at the population level remains controversial. We investigated whether higher baseline GFR predicts a steeper decline in GFR. Study Design - Longitudinal cohort studies. Setting & Participants - 1,594 middle-aged Norwegians without diabetes (the Renal Iohexol Clearance Survey [RENIS]) and 319 Pima Indians (83% with type 2 diabetes). Predictor - Baseline measured GFR using exogenous clearance methods. Outcomes - Change in measured GFR over time. Analytical Approach - Linear mixed regression models fit to assess the correlation between the random intercept (reflecting baseline GFR) and random slope (change in GFR over time). Results - Mean baseline GFRs were 104.0 ± 20.1 (SD) and 149.4 ± 43.3 mL/min, and median follow-up durations were 5.6 (IQR, 5.2-6.0) and 9.1 (IQR, 4.0-15.0) years in the RENIS and Pima cohorts, respectively. Correlation between baseline GFR (random intercept) and slope of GFR decline was −0.31 (95% CI, −0.40 to −0.23) in the RENIS cohort and −0.41 (95% CI, −0.55 to −0.26) in the Pima cohort, adjusted for age, sex, height, and weight, suggesting that higher baseline GFRs were associated with steeper GFR decline rates. Limitations - Different methods for measuring GFR in the 2 cohorts. Renal hyperfiltration may not reflect higher single-nephron GFR. GFR decline is assumed to be linear, which may not match the actual pattern; observed correlations may arise from natural variation. Conclusions - Higher baseline GFR is associated with faster decline in GFR over time. If this relationship were causal, elevated GFR would represent a potentially modifiable risk factor for medium- to long-term GFR decline.

Background: The prevalence of obesity and severe obesity is increasing among minority youth. We examined the relationship between cognitive function, and obesity, obesity-risk behaviors, and quality of life in an inner-city primarily Hispanic youth cohort. Methods: A cross-sectional observational study of youth 13-18 years of age, visiting an inner-city hospital-based Adolescent Clinic was conducted between June 2019 – March 2020. Demographic data were obtained, and the Short Acculturation Scale for Hispanics (SASH) and the obesity risk behavior self-report questionnaire adapted from the Youth Risk Behavior Surveillance System (YRBSS) were administered. Blood pressure and anthropometrics were …

AIMS: Intensive lifestyle intervention (ILS) targeting health behaviors is efficacious for diabetes mellitus prevention, but there is heterogeneity in the effect of ILS. We tested whether diabetes genetic risk modifies the association of successful lifestyle changes with incident diabetes. MATERIALS AND METHODS: We studied 823 individuals randomized to the ILS arm of the Diabetes Prevention Program who were diabetes-free one year after enrollment. We tested additive and multiplicative interactions of a 67-variant diabetes genetic risk score (GRS) with achievement of three ILS goals at one year (≥7% weight loss, ≥150 minutes/week of moderate leisure-time physical activity, and/or a goal for self-reported total fat intake) on the primary outcome of incident diabetes over 3 years of follow-up. RESULTS: A lower GRS and achieving each or all three ILS goals were each associated with lower incidence of diabetes (all p

Background: There is limited information on how polygenic scores (PSs) — based on variants from genome-wide association studies (GWAS) of T2D — add to clinical variables in predicting T2D incidence. Methods: For participants in a longitudinal study in an Indigenous population from the Southwest United States (US) with high T2D prevalence, we analyzed 10 constructions of PS using publicly available GWAS summary statistics. T2D incidence was examined in three cohorts of individuals without T2D at baseline. The adult cohort, comprised of 2333 participants followed from age≥20y, had 640 T2D cases. The youth cohort was comprised of 2229 participants followed from age 5-19y (228 cases). The birth cohort was comprised of 2894 participants followed from birth (438 cases). We assessed contributions of the PS and clinical variables in predicting T2D incidence. Results: Of the 10 PS constructions, a PS using 293 genome-wide significant variants from a large T2D GWAS meta-analysis in European-ancestry populations performed best. In the adult cohort, area under the receiver operating characteristic curve (AUC) for clinical variables for prediction of T2D incidence was 0·728; with the PS, 0·735. The PS’s hazard ratio (HR) was 1.27 per SD (p=1·6×10-8; 95% CI 1·17-1·38). In the youth cohort, the analogous model’s AUC was 0·805; with the PS, 0·812. The PS’s HR was 1·49 (p=4·3×10-8; 95% CI 1·29-1·72). In the birth cohort, AUC for the clinical variables was 0·614; with the PS, 0·685. The PS’s HR was 1·48 (p=2·8×10-16; 95% CI 1·35-1·63). To further assess the potential impact of including PS for assessing individual T2D risk, the net reclassification improvement (NRI) was calculated: NRI for the PS was 0·264, 0·249, and 0·309 for adult, youth, and birth cohorts, respectively. For comparison, NRI for HbA1c was 0·292 and 0·150 for adult and youth cohorts, respectively. Across all cohorts, as estimated using decision curve analyses, the net benefit of including the PS in addition to clinical variables was most pronounced at moderately stringent threshold probability (pt) values for instituting a preventive intervention. Discussion: This study demonstrates that the PS contributes significantly to prediction of T2D incidence in addition to the information provided by clinical factors; however, overall improvement of the prediction model was modest. Discriminatory power of the PS for predicting incident T2D was similar to that of other commonly measured clinical factors (e.g. HbA1c). Including T2D PS in addition to clinical factors may be clinically beneficial for identifying individuals at higher risk for T2D, especially at younger ages. Funding Statement: This study used computational resources of the Biowulf system at the National Institutes of Health (NIH), Bethesda, MD. The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Intramural Research Program provided support for NIDDK-based coauthors. The NIH Oxford-Cambridge Scholars Program provided funding support for L.E.W.’s doctoral programme. M.I.M. was a Wellcome Senior Investigator and an NIHR Senior Investigator. This work was funded in Oxford by the Wellcome Trust (098381, 106130, 203141), NIH (U01- DK105535; U01-DK085545) and National Institute for Health Research (NIHR) (NF-SI-0617- 10090) and Oxford Biomedical Research Centre (BRC). Declaration of Interests: The views expressed in this article are those of the author(s) and not necessarily those of NIH, NHS, NIHR, or UK Department of Health. M.I.M. has served on advisory panels for Pfizer, Novo Nordisk, and Zoe Global; has received honoraria from Merck, Pfizer, Novo Nordisk, and Eli Lilly; and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, M.I.M. and A.M. are employees of Genentech and holders of Roche stock. Ethics Approval Statement: Protocols were approved by the institutional review board of the National Institute of Diabetes and Digestive and Kidney Diseases.

Objective In an ongoing effort to identify the genetic variation that contributes to obesity in American Indians, known Bardet–Biedl syndrome (BBS) genes were analyzed for an effect on BMI and leptin signaling. Methods Potentially deleterious variants (Combined Annotation Dependent Depletion score > 20) in BBS genes were identified in whole‐exome sequence data from 6,851 American Indians informative for BMI. Common variants (detected in ≥ 10 individuals) were analyzed for association with BMI; rare variants (detected in 40 kg/m2), four were in BBS9. In vitro analysis of BBS9 found the Ile allele at Thr549Ile had a 20% increase in STAT3 activity compared with the Thr allele (P = 0.01). Western blot analysis showed the Ile allele had a 15% increase in STAT3 phosphorylation (P = 0.006). Comparable functional results were observed with Ser545Gly and Val209Leu but not Leu665Phe and Lys810Glu. Conclusions Potentially functional variants in BBS genes in American Indians are reported. However, functional evidence supporting a causal role for BBS9 in obesity is inconclusive.

Objective. Little is known about the impact of loneliness on physical health among elderly individuals with diabetes. Here, we examined the relationship of loneliness with disability, objective physical function, and other health outcomes in older individuals with type 2 diabetes and overweight or obesity. Method. Data are drawn from the Look AHEAD study, a diverse cohort of individuals (ages 61–92) with overweight or obesity and type 2 diabetes measured 5–6 years after a 10-year weight loss randomized, controlled trial. Results. Loneliness scores were significantly associated with greater disability symptoms and slower 4-meter gait speed (ps<0.01). Loneliness did not differ across treatment arms. Discussion. Overall, these results extend prior findings relating loneliness to disability and decreased mobility to older individuals with type 2 diabetes and overweight or obesity.

Background: Per- and polyfluoroalkyl substances (PFAS) are widely used chemicals, some of which have been linked to type 2 diabetes. We tested whether PFAS concentrations were cross-sectionally associated with metabolites previously shown to predict incident type 2 diabetes using the Diabetes Prevention Program (DPP), a trial of individuals at high risk of type 2 diabetes. Methods: We evaluated 691 participants enrolled in the DPP with baseline measures of 10 PFAS (including total perfluorooctanesulfonic acid (PFOS), total perfluorooctanoic acid (PFOA), and Sb-PFOA [branched isomers of PFOA]) and 77 metabolites. We used log2-transformed PFAS concentrations as exposures and standardized metabolite concentrations as outcomes in linear regression models adjusted for age, sex, race/ethnicity, use of anti-hyperlipidemic or triglyceride-lowering medication, income, years of education, marital status, smoking, and family history of diabetes, with Benjamini-Hochberg linear step-up false discovery rate correction. Results: Sb-PFOA was associated with the largest number of tested metabolites (29 of 77). Each doubling in Sb-PFOA was associated with higher leucine (β=0.07 [95%CI: 0.02, 0.11] SD) and lower glycine (-0.08 [95%CI: -0.03, -0.13] SD). Each doubling of either total PFOA or n-PFOA was associated with -0.13 [95%CI: -0.04, -0.22] SD lower glycine. PFOA and Sb-PFOA were positively associated with multiple triacylglycerols and diacylglycerols, and total PFOS, total PFOA, and Sb-PFOA were positively associated with phosphatidylethanolamines.Conclusions: PFAS concentrations are associated with metabolites linked to type 2 diabetes (particularly amino acid, glycerolipid and glycerophospholipid pathways). Further prospective research is needed to test whether these metabolites mediate associations of PFAS and type 2 diabetes.

Background: Despite the epidemic of pediatric obesity, the prevalence of type 2 diabetes (T2D) during childhood remains low. Although obesity in youth portends cardiometabolic disease later in life, longitudinal data describing the progression of T2D into young adulthood are scarce. Methods: We evaluated glycemic status (normal, prediabetes, or T2D) in a cohort of Latino youth with obesity (n=396; age 14.5±1.4; 55.6% male, BMI 33.9±5.3), and in a sub-set of participants who were re-engaged as young adults (n=39; age 20.8±1.0; 38.5% male, BMI 41.7±8.1). Glycemic status was determined from an oral glucose tolerance test with hyperglycemia classified according to ADA criteria. Results: Among adolescents, the prevalence rates for normal, prediabetes, and T2D were 69.9%, 28.1%, and 1.3% respectively; while prevalence rates in young adults after a 5-year follow-up period were 64.1%, 25.6%, and 10.3%, respectively. Of the adolescents with normal glucose status at baseline who returned as young adults (n=28), 5 (17.9%) developed prediabetes, and 1 (3.6%) developed T2D. Of those with prediabetes at baseline (n=11), 4 (36.4%) reverted to normal glucose status, 4 (36.4%) remained prediabetic, and 3 (27.3%) developed T2D. Young adults with T2D were more likely to have a parental history of T2D than those who did not develop T2D (50% vs. 11%, p=0.04). Conclusion: Despite strong risk factors, the prevalence of T2D among a cohort of Latino adolescents with obesity was low (1.3%). Of those who had normal glucose status during adolescence, the prevalence rate of T2D after a 5-year follow-up period was similarly low (3.6%), while for those with prediabetes during adolescence, the prevalence rate of T2D at follow-up was substantially higher (27.3%). Stratifying obese youth by glycemic status significantly affects the long-term prediction of developing T2D, which may have important implications for medical-decision making and resource allocation when managing youth with multiple T2D risk factors. Disclosure M. Olson: None. Y.P. Konopken: None. C. Keller: None. D.L. Patrick: None. A. Williams: None. S. Ayers: None. W.C. Knowler: None. A. Pena: None. E.G. Soltero: None. G.Q. Shaibi: None. Funding National Institute on Minority Health and Health Disparities (P20MD002316, U54MD002316); National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK107579)

Background: Diabetes disproportionately impacts Latino youth, yet few diabetes prevention programs (DPP) have prioritized inclusion of this vulnerable population. Recruitment is often the most challenging aspect of clinical trials and the optimal strategy to meet enrollment goals is unknown. This report describes the recruitment yields, costs, and baseline characteristics for a DPP focused on Latino youth. Methods: Recruitment methods included clinics, community efforts, media, and word-of-mouth with the goal of enrolling 120 Latino youth age 12-16 with obesity and prediabetes. Yields, costs, and baseline characteristics of youth were compared by recruitment method with final prediabetes eligibility determined by an Oral Glucose Tolerance Test (OGTT). Results: Recruitment spanned 47 months and yielded 655 referrals from clinics (N=344), community efforts (N=143), media (N=137), and word-of-mouth (N=31). From this pool, 50% (N=325) declined participation and 14% (N=93) were ineligible by general inclusion criteria. A screening OGTT was performed on 237 youth with 52% (N=122) meeting prediabetes eligibility and 117 subsequently randomized. The clinical sites yielded the highest number of total referrals (53%, N=344/655) while word-of-mouth yielded the highest proportion (35%, N=11/31) of randomized participants per referral. There were no significant differences in anthropologic or diabetes risk biomarkers between recruitment sources. Community recruitment efforts were the most costly ($486/randomized participant) followed by media ($236/randomized participant) and clinic ($248/randomized participant). Conclusions: These data suggest that yields and costs to recruit Latino youth into a DPP vary by method, and there were no differences in youth diabetes risk profiles. Recruiting hard-to-reach populations into clinical trials requires multiple strategies to meet target enrollment. Disclosure K.B. Vander Wyst: None. M. Olson: None. E.G. Soltero: None. Y.P. Konopken: None. C. Keller: None. F. González Castro: None. A. Williams: None. A.D.R. Fernandez: None. E. Hooker: None. D.L. Patrick: None. S. Ayers: None. H.H. Hu: None. A. Pena: None. W.C. Knowler: None. G.Q. Shaibi: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK10757901)

Among patients with type 2 diabetes (T2D), racial/ethnic minorities and those of lower socioeconomic status (SES) have a higher burden of coronary artery disease, chronic kidney disease, and hypoglycemia. Therefore, these groups may especially benefit from newer diabetes medication classes (GLP-1 receptor agonists, DPP-4 inhibitors, SGLT2 inhibitors), but high cost may limit access. We conducted a secondary analysis of the Look AHEAD (Action for Health in Diabetes) randomized trial to assess the associations of race/ethnicity and SES with newer diabetes medication use. Look AHEAD compared an intensive lifestyle intervention to diabetes support and education among U.S. adults with obesity and T2D enrolled from 2001-2004. Medications, all prescribed outside of the study, were ascertained yearly. We used Cox proportional hazards models to estimate the association between self-reported race/ethnicity and SES factors and time to initiation of any newer diabetes medication through October 2019, adjusted for time-varying HbA1c, BMI, and number/type of diabetes medications; and baseline study arm, demographics, and comorbidities; fully-adjusted results are presented. Of 4,892 participants, 64%, 16%, 13%, and 8% were white, black, Hispanic, and other race/ethnicities, respectively. Over a median follow-up of 8.3 years, 44% initiated a newer diabetes medication. Black race was associated with significantly lower initiation of newer medications compared to whites (HR 0.81; 95% CI 0.80-0.94); there was no difference by other race/ethnic group. Yearly family income was inversely associated with the outcome: HR 0.69 (95% CI 0.55-0.87) comparing the lowest vs. the highest income group. Education, employment, and health insurance were not significantly associated with the outcome. These findings provide evidence of racial and SES disparities in use of newer diabetes medications, independent of glycemic control, that may impede access to these drugs for the individuals who need them most. Disclosure A. Elhussein: None. M. Bancks: None. W.C. Knowler: None. A.L. Peters: Advisory Panel; Self; Abbott, Bigfoot Biomedical, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, MannKind Corporation, Medscape, Novo Nordisk Inc., Sanofi US. Consultant; Self; Livongo Health. Research Support; Self; Dexcom, Inc., vTv Therapeutics. Other Relationship; Self; Livongo Health, Mellitus Health, Omada Health, Stability Healthcare, Whole Biome Inc. E.M. Vaughan: None. N.M. Maruthur: Other Relationship; Self; Johns Hopkins HealthCare Solutions. J. Clark: None. S.J. Pilla: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK057149)

Ecological studies have shown different risks for diabetes (DM) among many ethnic groups, but whether they are due to genetic or non-genetic factors is hard to dissect. We conducted a community-based study aimed at identifying risk factors for DM and related traits in Pacific Islanders from Guam and Saipan. We analyzed the genetic structure of our sample and estimated individual-level admixture using genome-wide SNP data (49,300 variants). We found that genetic ancestry largely derived from 5 populations, representing Marianas Islanders (MI) (mean % heritage, or μ=43%), East Asians (EA, μ=22%), Micronesians (MC, μ=19%), Europeans (EU, μ=13%), and Melanesians (ML, μ=3%). We then tested the association of ancestry estimates with DM, fasting glucose and fasting insulin levels in study participants (n=1,853). Covariates included age, sex and end-stage kidney disease. For fasting insulin, only nondiabetic subjects were used in analyses. All 3 traits were associated with genetic ancestry (p In summary, there were large and statistically significant differences in DM-related traits among Pacific Islanders with different genetic ancestral backgrounds. Although genetic ancestry estimates may still be confounded by shared environmental factors, the present findings suggest that admixture mapping may be a potentially powerful approach for identifying unique DM loci in Pacific Islanders. Disclosure W. Hsueh: None. P. Kumar: None. S. Safabakhsh: None. L. Jones: None. J. Curran: None. W.C. Knowler: None. R.G. Nelson: None. R.L. Hanson: None.

To identify variants that potentially impact human body fat via a role in adipogenesis, we analyzed whole-exome sequence data from a population-based sample of 6809 American Indians with longitudinal measures of BMI. A total of 623,236 exonic variants were detected and those that met the following criteria were prioritized for functional analysis: 1) non-synonymous, stop-gain or frameshift that occurred in ≥5 individuals; 2) a Combined Annotation Dependent Depletion (CADD) score ≥10 (top 10% of deleterious variants); 3) evidence for association with maximum BMI in adulthood (n=6002) or maximum BMI z-score in childhood (n=4882) (P In conclusion, whole-exome sequencing followed by in vitro analysis of lipid accumulation in OP9 cells has identified coding variants that may impact BMI via a role in adipogenesis. Disclosure Y.L. Muller: None. S.E. Day: None. C. Koroglu: None. S. Kobes: None. R.L. Hanson: None. W.C. Knowler: None. H. Kim: Employee; Self; Regeneron Pharmaceuticals. C. Van Hout: Employee; Self; Regeneron Genetics Center. N. Gosalia: None. A.R. Shuldiner: Employee; Self; Regeneron Genetics Center. Stock/Shareholder; Self; Regeneron Pharmaceuticals. C. Bogardus: None. L. Baier: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases

The Look AHEAD trial compared an intensive lifestyle intervention (ILI) for weight loss with diabetes support and education in adults with T2DM and BMI ≥ 25 kg/m2. During 10 years of follow-up, ILI had no significant effect on mortality or incidence of CVD. Here we present a secondary analysis of urine albumin/creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) as predictors of all-cause mortality (361 deaths among 4865 participants) using time varying covariates proportional hazards models adjusted for age, sex, race/ethnicity, and ILI. Both ACR and eGFR predicted mortality (Figure 1a/b, respectively). In a joint analysis of ACR and eGFR, mortality was highest among groups with low eGFR and high ACR. Interestingly, high eGFR was also associated with higher mortality (Figure 1c). Effects of eGFR on mortality were nonlinear, but in each eGFR group, ACR was positively associated with mortality. In each analysis, ILI was beneficial, but not significantly so. There were no significant interactions between ACR or eGFR and insulin treatment, history of CVD, beta-blocker treatment, or age at baseline on mortality. In conclusion, ACR and eGFR predicted mortality in time varying models. Results were similar for CVD mortality (106 deaths) and for the primary trial outcome of fatal or nonfatal CVD (796 events). Disclosure A.C. Wills: None. W.C. Knowler: None.

Look AHEAD found no difference between intensive lifestyle intervention (ILI) for weight loss and diabetes support and education (DSE; control) in cardiovascular (CVD) outcomes among individuals with overweight or obesity and type 2 diabetes (T2DM). This secondary analysis evaluated the association between change in weight and waist circumference (WC), a possible proxy for visceral adiposity, and risk for CVD outcomes. We classified Look AHEAD participants (n=4590) into one of four categories based on change in weight and WC from baseline to Year 1 (increase/increase, etc.) to examine the association between the categories and primary (myocardial infarction, stroke, hospitalized angina, CVD death) and secondary (primary outcomes and CABG/PTCA, hospitalized congestive heart failure, carotid endarterectomy, PVD, and total mortality) CVD outcomes from Year 1 to end of active treatment (median of 9 years). Cox proportional-hazards regression models were used to 1) compare ILI participants in the four categories to DSE and 2) evaluate the four categories within treatment groups using the group that decreased WC and weight as the reference. Compared to DSE, individuals in ILI who increased WC and weight and individuals who increased WC but decreased weight both had greater risk of secondary CVD outcomes (HR[95%CI]: 1.95 [1.33, 2.86] and 1.35 [1.02, 1.80] respectively). In analyses stratified by randomization group, DSE participants did not differ in cardiovascular events across categories. Individuals in ILI who gained WC (regardless of weight loss or gain), had increased risk of primary and secondary CVD outcomes compared to individuals in ILI who decreased weight and WC. Increased WC during weight loss treatment, regardless of weight loss or gain, is associated with greater risk for CVD outcomes in individuals with T2DM. This emphasizes the importance of measuring WC in clinical practice and testing interventions focused on decreasing WC. Disclosure K.L. Olson: None. R.H. Neiberg: None. M. Espeland: Other Relationship; Self; Boehringer Ingelheim International GmbH, Ironwood Pharmaceuticals. K.C. Johnson: None. W.C. Knowler: None. A.E. Staiano: None. L.E. Wagenknecht: None. R.R. Wing: None. Funding National Institutes of Health

The health effects of weight loss in older individuals with diabetes is unclear, perhaps related to intentionality of the weight loss. Look AHEAD (LA) is a randomized trial comparing intensive lifestyle intervention for intentional weight loss with diabetes support and education (control) in 5145 individuals (age 45-76 at baseline) with overweight/obesity and type 2 diabetes. We examined the association of weight change trajectories post-intervention (i.e., yrs 8 to 16; M± SD percent weight change= -3.10% ±10.1), and concurrent risk of mortality by comparing weight gainers (N=226), maintainers (N=1459), modest losers (N=2206), and steep losers (N=415). Both weight loss groups were older, more likely to be in DSE, and lost less weight in yrs 1-8. In Cox proportional hazards regression models, adjusted for sex, race, baseline obesity, age, and treatment, mortality risk among the 4 weight change categories differed significantly (p10 lb over 2 most recent 6-month assessments intentionally, unintentionally, or through the combination (intentional + unintentional), relative to maintainers (no weight loss>10 lb). Adjusted analyses showed that the HR for mortality was significantly greater in both the unintentional (HR=3.26, 95%CI 2.35,5.01) and the combination (HR=2.63, 95%CI 1.28,5.39), but not different in the intentional weight loss group (HR=1.05, 95%CI 0.61,1.81) relative to maintainers. These data suggest that unintentional weight loss is associated with increased risk of mortality in older individuals with diabetes. Disclosure R.R. Wing: None. J. Clark: None. M. Espeland: Other Relationship; Self; Boehringer Ingelheim International GmbH, Ironwood Pharmaceuticals. J.O. Hill: Stock/Shareholder; Self; Gelesis, Shakabuku LLC. R.W. Jeffery: None. K.C. Johnson: None. W.C. Knowler: None. R.H. Neiberg: None. K. Olson: None. H.O. Steinberg: None. H. Wyatt: Research Support; Self; National Cattleman’s Association, Novo Nordisk Inc. Stock/Shareholder; Self; Shakabuku LLC. Other Relationship; Self; FoodMinds. Funding National Institutes of Health

Aims To assess whether meeting both fasting plasma glucose (FPG) and HbA1c criteria for prediabetes in people at high risk indicates with near certainty the presence of dysglycemia on repeat testing. Methods Observational study using data from Vitamin D and Type 2 Diabetes (D2d) study. HbA1c, FPG were measured at screening visit 1; FPG, HbA1c and 2 h plasma glucose (2hPG) measured at screening visit 2 (a median of 21 days later); participants classified as having normal glucose regulation (all 3 tests in normal range), prediabetes or diabetes (at least 1 of 3 tests in diabetes range). A predictive model was developed to estimate the probability of confirming dysglycemia and for detecting diabetes at screening visit 2 based on values of FPG and HbA1c at screening visit 1. Results Of 1271 participants who met both FPG and HbA1c criteria for prediabetes at screening visit 1, 98.6% exhibited dysglycemia (defined as prediabetes or diabetes) on repeat testing (84.5% were classified as having prediabetes, 14.1% were reclassified as having diabetes). Of those with diabetes, 62.6% were identified by 2hPG alone. Conclusions Combined measurement of FPG and HbA1c is a reliable and reproducible measure to identify presence of dysglycemia among people at high risk. A prediction model is provided to help clinicians decide whether an oral glucose tolerance test will provide value in detecting diabetes based on the 2hPG criterion., Highlights • FPG and HbA1c were tested simultaneously to identify patients with prediabetes. • Median 21 days later, repeat evaluation with FPG, HbA1c and an OGTT to measure the 2hPG criterion was done. • 98.6% of the subjects exhibited dysglycemia (prediabetes (84.5%) or diabetes (14.1%)) on repeat testing. • A prediction model to assess additional value of OGTT in detecting diabetes based on the 2hPG criterion is provided.

Epidemic infections have frightened and harmed people for millennia. Plague (1) and typhus (2), bacterial infections associated with poor sanitation and high mortality, have devastated populations. Both still reappear intermittently, but they are generally contained with better sanitation and control of rodent and insect vectors along with antibiotics. In contrast, viral epidemics persist. A unique strain of influenza caused a global epidemic (pandemic) in 1918 resulting in millions of deaths (3). Among recent outbreaks of viral infections, several have been caused by coronaviruses (4). One of these, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is now causing a pandemic illness termed coronavirus disease 2019 (COVID-19) that poses unique challenges. This novel coronavirus is readily transmitted from person-to-person, even by those who are infected but without symptoms. In susceptible people it causes severe illness and often death from pulmonary and systemic injuries. At present, we have neither a preventive vaccine nor well-studied pharmacotherapy, although work to develop these is vigorously underway. Certain groups are more vulnerable to COVID-19, notably older people and those with underlying medical conditions. Because diabetes is one of the conditions associated with high risk, the diabetes community urgently needs to know more about COVID-19 and its effects on people with diabetes. Between the first appearance of this illness in December 2019 and the time of writing this commentary, several detailed clinical descriptions have been published. Among 44,672 patients in China with infection confirmed by nucleic acid testing up to mid-February (5), most (87%) were between 30 and 79 years old. A large majority (81%) were considered to have mild illness, but in 14% it was judged to be severe and in 5% critical. Of all confirmed cases, 2.3% of patients died. Higher mortality rates were found among those ≥80 years old (14.8%), in those with preexisting cardiovascular …

Background/aimsPrediabetes and diabetes disproportionately impact Latino youth, yet few diabetes prevention programs have prioritized inclusion of this underrepresented population. This report describes the recruitment process, yields, associated costs, and phenotypic characteristics of Latino youth with obesity and prediabetes enrolled in a randomized controlled diabetes prevention study in the USA.MethodsRecruitment efforts included referrals from clinics, community outlets, local media, and word of mouth with the goal of enrolling 120 Latino adolescents aged 12–16 with obesity (BMI> 95th percentile) and prediabetes. Prediabetes eligibility was determined by any of the following: HbA1c between 5.7 and 6.5%, fasting glucose between 100 and 125 mg/dL, or a 2-h glucose between 120 and 199 mg/dL following a 75-g oral glucose tolerance test (OGTT), but not meeting any of the diagnostic criteria for diabetes. Eligible participants were randomized 2:1 to either a 6-month community-based lifestyle intervention that included group nutrition and health education classes (1 day/week) and group exercise classes (2 days/week) or usual care control arm. Recruitment yields were determined by review of referral source in the study screening database. Recruitment costs were determined by an after-the-fact financial review of actual and in-kind costs. Participant phenotypic characteristics (i.e., demographics, anthropometrics, and biochemical data) were compared by recruitment strategy using a one-way ANOVA.ResultsRecruitment efforts covered 160 mile2(414 km2) across 26 ZIP codes (postcode) in the Phoenix Metropolitan Area and yielded 655 referrals from clinics (n = 344), community (n = 143), media (n = 137), and word-of-mouth (n = 31). From this pool, 26% (n = 167) did not meet general, pre-screening eligibility criteria; 29% (n = 187) declined participation; and 10% (n = 64) were unable to be contacted. A total of 237 youth were invited to the clinical research unit to determine final eligibility. Following the OGTT, 52% (n = 122) met prediabetes criteria and 117 were subsequently randomized. Clinical recruitment yielded the highest number of referrals (53%;n = 344) while word-of-mouth yielded the highest proportion (35%;n = 11) of randomized participants per referred youth. There were no significant differences in anthropometric or biochemical measures among youth by recruitment strategy. Based upon final enrollment numbers, community recruitment was the costliest approach ($486/randomized participant) followed by clinical ($248/randomized participant) and media ($236/randomized participant).ConclusionsThe ability to meet enrollment goals for a clinical trial of an underrepresented population required multiple recruitment strategies. Although strategies vary in yields and costs, it appears they produce similar phenotypical risk profiles of eligible youth.Trial registrationClinicalTrials.govNCT02615353. Registered on 26 November 2015

OBJECTIVE The Action for Health in Diabetes (Look AHEAD) trial was a randomized trial comparing effects of intensive lifestyle intervention (ILI) and diabetes support and education (DSE) on cardiovascular disease (CVD) among individuals with overweight/obesity and type 2 diabetes. A secondary analysis was conducted to evaluate the association between change in weight and waist circumference (WC) and CVD outcomes. METHODS Participants (N = 5,490) were classified into four categories based on change in weight and WC between baseline and year 1 (both increased, both decreased, etc.). Separate Cox proportional hazards regression models were fit for ILI and DSE (using group that reduced weight/WC as reference), and time to first occurrence of primary and secondary CVD outcomes from year 1 through a median of almost 10 years were compared. Second, time to first event among all four ILI groups relative to DSE was evaluated. RESULTS Within DSE, CVD outcomes did not differ. ILI participants with increased WC had increased risk of primary outcomes, regardless of weight loss (hazard ratio: 1.55 [95% CI: 1.11-2.17]) or weight gain (hazard ratio: 1.76 [95% CI: 1.07-2.89]), and had increased risk of secondary outcomes (overall P

OBJECTIVE To assess the cost-effectiveness (CE) of an intensive lifestyle intervention (ILI) compared with standard diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, as implemented in the Action for Health in Diabetes study. RESEARCH DESIGN AND METHODS Data were from 4,827 participants during their first 9 years of study participation from 2001 to 2012. Information on Health Utilities Index Mark 2 (HUI-2) and HUI-3, Short-Form 6D (SF-6D), and Feeling Thermometer (FT), cost of delivering the interventions, and health expenditures was collected during the study. CE was measured by incremental CE ratios (ICERs) in costs per quality-adjusted life year (QALY). Future costs and QALYs were discounted at 3% annually. Costs were in 2012 U.S. dollars. RESULTS Over the 9 years studied, the mean cumulative intervention costs and mean cumulative health care expenditures were $11,275 and $64,453 per person for ILI and $887 and $68,174 for DSE. Thus, ILI cost $6,666 more per person than DSE. Additional QALYs gained by ILI were not statistically significant measured by the HUIs and were 0.07 and 0.15, respectively, measured by SF-6D and FT. The ICERs ranged from no health benefit with a higher cost based on HUIs to $96,458/QALY and $43,169/QALY, respectively, based on SF-6D and FT. CONCLUSIONS Whether ILI was cost-effective over the 9-year period is unclear because different health utility measures led to different conclusions.

A web-based survey of pediatric care providers revealed differences in their preference for clinical charts that monitor growth in children with obesity. These findings are attributed to pediatric specialty training. Very few providers believe the currently available Centers for Disease Control and Prevention 2000 body mass index-for-age charts adequately track growth in children with obesity.