Impact of Parental or First-Degree Family History of Diabetes on Diabetes Incidence and Progression During Long-term Follow-up in the Diabetes Prevention Program Outcomes Study.

ObjectiveTo investigate the association between a parental and/or sibling history of diabetes and clinical characteristics.DesignA cross-sectional study.SettingThe data were collected from the endocrinology department of The Second Xiangya Hospital of...

Reducing the Risk of Developing Diabetes.

Diabetes update: Key research at 2014 ADA meeting

Long-term effects and effect heterogeneity of lifestyle and metformin interventions on type 2 diabetes incidence over 21 years in the US Diabetes Prevention Program randomised clinical trial.

Effect of regression from prediabetes to normal glucose regulation on long-term reduction in diabetes risk: results from the Diabetes Prevention Program Outcomes Study

To compare the ability of the metabolic syndrome (MetS), a diabetes prediction model (DPM), a noninvasive risk questionnaire and individual glucose measurements to predict future diabetes. Five-year longitudinal cohort study. Tools tested included MetS definitions [World Health Organization, International Diabetes Federation, ATPIII and European Group for the study of Insulin Resistance (EGIR)], the FINnish Diabetes RIsk SCore risk questionnaire, the DPM, fasting and 2-h post load plasma glucose. Adult Australian population. A total of 5842 men and women without diabetes > or =25 years. Response 58%. A total of 224 incident cases of diabetes. In receiver operating characteristic curve analysis, the MetS was not a better predictor of incident diabetes than the DPM or measurement of glucose. The risk for diabetes among those with prediabetes but not MetS was almost triple that of those with MetS but not prediabetes (9.0% vs. 3.4%). Adjusted for component parts, the MetS was not a significant predictor of incident diabetes, except for EGIR in men [OR 2.1 (95% CI 1.2-3.7)]. A single fasting glucose measurement may be more effective and efficient than published definitions of the MetS or other risk constructs in predicting incident diabetes. Diagnosis of the MetS did not confer increased risk for incident diabetes independent of its individual components, with an exception for EGIR in men. Given these results, debate surrounding the public health utility of a MetS diagnosis, at least for identification of incident diabetes, is required.

Longevity clusters in families, and parental longevity may be associated with lower risk of chronic diseases in their children. It is unknown if diabetes risk is associated with parental longevity. We evaluated participants in the Diabetes Prevention Program with a parental history questionnaire at study entry. We classified them into five groups: premature death (parental death at age < 50 years), parental longevity (living to at least 80 years), and three intermediate groups (alive by age 49 but dying at age 50-59, 60-69, or 70-79). Those with alive parents and younger than 80 years were excluded. We analyzed separately effects of paternal (n = 2,165) and maternal (n = 1,739) longevity on diabetes incidence and risk after an average follow-up of 3.2 years. At baseline, more diabetes risk factors (parental history of diabetes, coronary heart disease, higher body mass index, homeostasis model assessment for insulin resistance, and corrected insulin response) were found in participants whose parents died prematurely. Diabetes incidence was 9.5 cases/100 person-years in the 229 whose fathers died prematurely. In the 618 with paternal longevity, the rate was 6.6 cases/100 person-years (hazard ratio [95% confidence interval] = 0.68 [0.49-0.94]). The rates were 10.7 cases/100 person-years (n = 156) and 7.3 cases/100 person-years (n = 699, hazard ratio = 0.67 [95% confidence interval 0.47-0.95]) for those with maternal premature death or longevity, respectively. Associations with demographic and diabetes risk factors had minimal influence on the reduced risk found in those with paternal (adjusted hazard ratio = 0.78, 95% confidence interval 0.52-1.16) and maternal (adjusted hazard ratio = 0.64, 95% confidence interval 0.41-1.01) longevity. Parental longevity is associated with lower diabetes incidence in adults at high risk of type 2 diabetes.

During the first 7 years of the Diabetes Prevention Program Outcomes Study (DPPOS), diabetes incidence rates, when compared with the Diabetes Prevention Program (DPP), decreased in the placebo (-42%) and metformin (-25%), groups compared with the rates in the intensive lifestyle intervention (+31%) group. Participants in the placebo and metformin groups were offered group intensive lifestyle intervention prior to entering the DPPOS. The following two hypotheses were explored to explain the rate differences: "effective intervention" (changes in weight and other factors due to intensive lifestyle intervention) and "exhaustion of susceptible" (changes in mean genetic and diabetes risk scores). No combination of behavioral risk factors (weight, physical activity, diet, smoking, and antidepressant or statin use) explained the lower DPPOS rates of diabetes progression in the placebo and metformin groups, whereas weight gain was the factor associated with higher rates of progression in the intensive lifestyle intervention group. Different patterns in the average genetic risk score over time were consistent with exhaustion of susceptibles. Results were consistent with exhaustion of susceptibles for the change in incidence rates, but not the availability of intensive lifestyle intervention to all persons before the beginning of the DPPOS. Thus, effective intervention did not explain the lower diabetes rates in the DPPOS among subjects in the placebo and metformin groups compared with those in the DPP.

The 2018 World Cancer Research Fund/American Institute for Cancer Research Score and Cancer Risk: results from the diabetes prevention program outcomes study.

Lifestyle changes may reduce the burdens of diabetes and cancer. We examined how changes in the 2018 WCRF/AICR Score, reflecting key cancer prevention recommendations, are associated with diabetes risk. The Diabetes Prevention Program (DPP) randomized adults with prediabetes to a lifestyle intervention (ILS), metformin (MET), or placebo (PLB) for a mean of 3.2 years, with follow-up in DPPOS for 11 years. The Score includes 7 components: weight, physical activity, plant-based diet, red/processed meat, sugar-sweetened drinks, fast foods, and alcohol (0-7 points, with 7 as the best total score). Scores were estimated at years 0, 1, 5, 6, 9, and 15 for participants with complete baseline data (N = 3,147). Covariates included sex, age, race/ethnicity, marital status, education, family history of diabetes, hormone therapy (females), and energy intake. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) stratified by treatment group estimated the association of Score changes with diabetes risk in DPP and DPPOS within and between groups. There were significant Score improvements within all groups over 15 years (p &amp;lt; 0.001); the differences between groups were only significant after 1 year (p &amp;lt; 0.001; 15 years: p = 0.137). For every 1-unit improvement in Score during DPP, there was a 29% and 16% lower diabetes risk in ILS (95% CI: 0.58 - 0.88) and PLB (95% CI: 0.72 - 0.99), respectively, and no significant association in MET. The time-dependent Score improvements in ILS and PLB were significantly associated with lower diabetes risk through year 15 (ILS HR: 0.86, 95% CI 0.77 - 0.96; PLB HR: 0.85, 95% CI 0.76 - 0.95). Changes in weight, physical activity, and plant-based diet appeared to be drivers of the Score’s effect. Findings suggest that Score improvements are associated with a long-term, lower risk for diabetes among adults with prediabetes. Future research can explore how this risk reduction impacts cancer risk. Disclosure M. M. M. Shams-white: None. B. M. Heckman-stoddard: None. D. Research group: None. A. H. Tjaden: None. S. Edelstein: None. S. Bassiouni: None. C. Kim: None. X. Pi-sunyer: None. K. A. Temple: None. E. M. Venditti: None. J. Reedy: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK048489)

Objective: To examine whether odds of frailty differ by DPP intervention arms (intensive lifestyle intervention [ILS], metformin [MET], placebo [PLB] after long-term follow-up in the DPPOS. Methods: DPP, a randomized trial of individuals at high risk of diabetes, lasted 2.8 years, after which there was a 13-month bridge period in which 16 sessions of group ILS was offered to all participants. During DPPOS, ILS was offered lifestyle reinforcement semi-annually and MET received unmasked metformin. Frailty was measured initially in DPPOS Year 8 in 2385 participants and repeated in 2264 of these in Year 10 (12 and 14 years after randomization). Using Fried criteria, presence of 3 of 5 characteristics (slow walking speed, weak grip strength, unintentional weight loss, low physical activity, and exhaustion) was classified as frail, 1 or 2 pre-frail, and 0 non-frail.: GEE models adjusting for visit year were employed with repeated measures pooled from Years 8 and 10 to estimate pairwise odds ratios between ILS, MET and PLB for the outcomes of frail and pre-frail vs. non-frail. Results: Odds of frailty vs. non-frailty were 37% lower in ILS compared to PLB (Table) and MET (OR=0.629, CI= 0.420-0.942, p=0.024). There were no significant treatment group differences in odds of pre-frailty. Conclusion: ILS intervention in persons at high risk of diabetes may reduce frailty in later life.12 years Post-randomization14 years post-randomizationOdds of Frailty vs. Non-Frailty Pooled over both examsTreatment GroupPrevalencePrevalence OR (95% CI) compared with placeboP-valuePre-FrailtyFrailtyPre-FrailtyFrailtyPlacebo42.8%5.7%43.7%5.4%1 (referent)n/aMetformin45.8%5.4%42.5%5.3%0.994 (0.694-1.424)0.976Lifestyle46.8%3.0%46.3%3.6%0.625 (0.419-0.934)0.022 Disclosure H.P. Hazuda: None. Q. Pan: None. J.P. Crandall: None. H. Florez: Advisory Panel; Self; Sanofi. J.A. Luchsinger: None. E.M. Venditti: None. A. Kriska: None. S. Golden: None. G. Bray: Advisory Panel; Self; Herbalife International of America, Inc., Novo Nordisk A/S. D. Research Group: None.

Laskarzewski P., J. A. Morrison, R. Horvitz, P. Khoury, K. Kelly, M. Mellles and C. J. Glueck (U. of Cincinnati, College of Medicine, Cincinnati, OH 45267). The relationship of parental history of myocardial infarction, hypertension, diabetes and stroke to coronary heart disease risk factors In their adult progeny. Am J Epidemiol 1981; 113: 290–306. Both univariate and multivariate analysis of covariance were used to assess the relationships of parental history of myocardial infarction (Ml), hypertension, stroke, and diabetes to coronary heart disease (CHD) risk factors of their 556 adult progeny (≧24 years old) including 200 white males, 257 white females, 30 black males, and 69 black females in the Princeton School study. The CHD risk factors considered were plasma cholesterol (CHOL), tri-glycerlde (TG), high and low density lipoprotein cholesterol (C-HDL, C-LDL), Quetelet index, and systolic and diastolic blood pressure (SBP and DBP). Fewer than half of the univariate comparisons appeared to be consistent with the hypothesis that positive family history is associated with a greater tendency toward CHD as measured by known risk factors. By univariate analysis, a history of paternal, but not maternal Ml was associated with higher C-LDL and TG in their offspring. There were also several significant univariate interactions of risk factors with age in progeny of fathers with Ml; the offsprings' increase in C-LDL and total CHOL with age was greater than that observed in subjects whose fathers did not have a Ml. By multlvariate analysis, neither paternal nor maternal history of Ml played a significant role relative to risk factor levels in their progeny. By multivariate analysis, maternal history of stroke was significant when all seven risk factors in their off-spring were viewed collectively, including higher CHOL, TG, C-LDL, and, in black kindreds, higher SBP and DBP. By multivariate analysis, maternal history of hypertension was significant; offspring of hypertensive mothers had Increased TG and Quetelet levels, lower C-HDL, and higher SBP and DBP. While parental diabetes had few significant univariate and no multivariate relationships with CHD risk factors in their progeny, parental history of diabetes had considerable interaction with other parental history information (parental stroke, Ml and hypertension). Using multivariate analysis, the existence of two affirmative answers to parental history questions did not cause a difference in their offspring's risk factors above that difference caused by the existence of one affirmative answer. In the multivariate model, the significance of interaction terms between covariables and main effects implies that the offspring's characteristics, such as race group, are more important in detecting differences in risk factors than one piece of additional information of parental history. Univariate and multivariate analysis of covariance may provide for somewhat different patterns of risk factor aggregations; the differing results can probably be attributed to the correlations which exist between the CHD risk factors themselves. In a cohort of adults, average age 40 years, while parental health history of Ml, hypertension, stroke and diabetes may facilitate identification of CHD risk factors in progeny, its utility will be circumscribed for primary care physicians who must rely on univariate comparisons.

The aim of this study was to investigate the associations between sibling history, parental history and simultaneous sibling and parental history of diabetes, and the presence of the metabolic syndrome (MetS) and its components. Our study comprised 5000 participants from Taiwan Biobank until April, 2014. The participants were stratified into four groups according to sibling and/or parental family history (FH) of DM. MetS was defined as having 3 of the following 5 abnormalities based on the standard of the NCEP ATP III and modified criteria for Asians. The prevalence of MetS and its traits was estimated and compared among the four familial risk strata. Multivariate logistic regression analysis showed participants with sibling FH of DM [vs. no FH of DM; odds ratio (OR) 1.815; 95% confidence interval (CI) 1.293 to 2.548; p = 0.001], participants with parental FH of DM (vs. no FH of DM; OR 1.771; 95% CI 1.468 to 2.135; p < 0.001), and participants with simultaneous sibling and parental FH of DM (vs. no FH of DM; OR 2.961; 95% CI 2.108 to 4.161; p < 0.001) were significantly associated with MetS. A synergistic effect of sibling FH of DM and parental FH of DM on the association of MetS was also observed. In a nationally representative sample of Taiwan adults, a simultaneous sibling and parental history of diabetes shows a significant, independent association with MetS and its components, except for abdominal obesity. The association highlights the importance of obtaining stratified FH information in clinical practice and may help to identify individuals who should be targeted for screening and early prevention of MetS.

During the three years of the DPP, ILS reduced incidence of diabetes compared with placebo in high-risk adults. Diabetes was defined using ADA criteria based on 1) annual OGTT or semi-annual fasting glucose (the primary DPP outcome, diab-G, hazard ratio (HR) =0.42 and rate difference (RD) = -6.2 cases/100 person-years) or 2) annual HbA1c ≥ 6.5% (diab‑A1C, HR=0.51 and RD = -4.2) . After DPP ended, participants were unmasked, placebo was discontinued, and all participants were offered group-based ILS and followed in the DPP Outcomes Study. We now compare the original ILS and placebo groups over a mean of 21 years since randomization. We test heterogeneity across subgroups defined by demographics and baseline glucose, HbA1c, BMI, and history of gestational diabetes and express it by interaction p-values (P-het) . During the total follow-up, ILS, compared with placebo, significantly reduced incidence of diab‑G: HR=0.76 (95% CI=0.68, 0.85) , RD= -1.62 (-2.28, -0.97) and of diab-A1C: HR=0.80 (0.70, 0.92) , RD= -1.67 (‑2.24, -1.10) . Effects on diab-G were homogenous across subgroups except for fasting glucose (P-het &amp;lt;0.01) and HbA1c (P-het &amp;lt;0.02) with greater effects at higher baseline values. By contrast, ILS reduced incidence of diab-A1C more in older than younger persons (P-het &amp;lt;0.02) , and more in men than women (P-het &amp;lt;0.03) . Notably, ILS was highly effective in reducing incidence of diab‑A1C if baseline HbA1c was already elevated (HbA1c=6.0-6.4%: HR=0.62, RD= -3.27) but ineffective if baseline HbA1c was normal by ADA criteria (HbA1c &amp;lt;5.7%: HR=1.09, RD= +0.19; P-het &amp;lt;0.001) . In sum, ILS effects on reducing incidence of diab-G and diab-A1C persisted but decreased during total follow-up from that observed during DPP (i.e., HRs and RDs closer to 1 and 0) . ILS effects on diab-G were greater in those with higher baseline fasting glucose or HbA1c. Effects on diab-A1C were greater in men, older participants, and those with higher baseline HbA1c. Disclosure W.C. Knowler: None. S. Edelstein: None. P.H. Bennett: Stock/Shareholder; Baxter INTERNTN Health Care, Merck &amp; Co., Inc., UnitedHealth Group. D. Dabelea: None. M.A. Hoskin: None. S.E. Kahn: Advisory Panel; Bayer AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Intarcia Therapeutics, Inc., Merck &amp; Co., Inc., Novo Nordisk, Pfizer Inc. R. Kalyani: None. C. Kim: None. S. Raghavan: None. M. Temprosa: None. E.M. Venditti: Advisory Panel; PeopleOne Health. D.M. Nathan: None. D. Research Group: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (UDK048489, UDK048339, UDK048377, UDK048349, UDK048381, UDK048468, UDK048434, UDK048485, UDK048375, UDK048514, UDK048437, UDK048413, UDK048411, UDK048406, UDK048380, UDK048397, UDK048412, UDK048404, UDK048387, UDK048407, UDK048443, and UDK048400)

BackgroundThe 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) 3rd expert report highlights up-to-date Cancer Prevention Recommendations that may reduce burdens of many chronic diseases, including diabetes. This study examined if following a lifestyle that aligns with the recommendations – assessed via the 2018 WCRF/AICR Score – was associated with lower risk of type 2 diabetes in high-risk adults participating in the Diabetes Prevention Program Outcomes Study (DPPOS).MethodsThe Diabetes Prevention Program (DPP) randomized adults at high risk for diabetes to receive a lifestyle intervention (ILS), metformin (MET) or a placebo (PLB) (mean: 3.2 years), with additional follow-up in DPPOS for 11 years (mean: 15 years total). 2018 WCRF/AICR Scores included seven components: body weight, physical activity, plant-based foods, fast foods, red and processed meat, sugar-sweetened beverages, and alcohol; the optional breastfeeding component was excluded. Scores ranged 0-7 points (with greater scores indicating greater alignment with the recommendations) and were estimated at years 0, 1, 5, 6, 9, and 15 (N=3,147). Fasting glucose and HbA1c were measured every six months and oral glucose tolerance tests were performed annually. Adjusted Cox proportional hazard ratios (HRs) and 95% confidence intervals (CIs) were used to examine the association of both Score changes from years 0-1 and time-dependent Score changes on diabetes risk through DPP and year 15.ResultsScores improved within all groups over 15 years (p<0.001); ILS Scores improved more than MET or PLB Scores after 1 year (p<0.001). For every 1-unit improvement from years 0-1, there was a 31% and 15% lower diabetes risk in ILS (95% CI: 0.56-0.84) and PLB (95% CI: 0.72-0.97) through DPP, and no significant association in MET. Associations were greatest among American Indian participants, followed by non-Hispanic White and Hispanic participants. Score changes from years 0-1 and time-dependent Score changes in ILS and PLB remained associated with lower risk through year 15.ConclusionsScore improvements were associated with long-term, lower diabetes risk among high-risk adults randomized to ILS and PLB, but not MET. Future research should explore impact of the Score on cancer risk.Trial registrationDiabetes Prevention Program: NCT00004992; Diabetes Prevention Program Outcomes Study: NCT00038727