Eating Pattern Response to a Low-Fat Diet Intervention and Cardiovascular Outcomes in Normotensive Women: The Women's Health Initiative.

BackgroundWomen without cardiovascular disease (CVD) or hypertension at baseline assigned to intervention in the Women's Health Initiative Dietary Modification (DM) trial experienced 30% lower risk of coronary heart disease (CHD), whereas results in women with hypertension or prior CVD could have been confounded by postrandomization use of statins.ObjectivesIntervention participants reported various self-selected changes to achieve the 20% total fat goals. Reviewed are intervention compared with comparison group HRs for CHD, stroke, and total CVD in relation to specific dietary changes in normotensive participants.MethodsDietary change was assessed by comparing baseline with year 1 FFQ data in women (n = 10,371) without hypertension or CVD at baseline with intake of total fat above the median to minimize biases due to use of the FFQ in trial eligibility screening.ResultsIntervention participants self-reported compensating reduced energy intake from total fat by increasing carbohydrate and protein. Specifically they increased plant protein, with those in the upper quartile (increased total protein by ≥3.3% of energy) having a CHD HR of 0.39 (95% CI: 0.22, 0.71), compared with 0.92 (95% CI: 0.57, 1.48) for those in the lower quartile of change (decreased total protein ≥0.6% of energy), with P-trend of 0.04. CHD HR did not vary significantly with change in percentage energy from carbohydrate, and stroke HR did not vary significantly with any macronutrient changes. Scores reflecting adherence to recommended dietary patterns including the Dietary Approaches to Stop Hypertension Trial and the Healthy Eating Index showed favorable changes in the intervention group.ConclusionsIntervention group total fat reduction replaced with increased carbohydrate and some protein, especially plant-based protein, was related to lower CHD risk in normotensive women without CVD who reported high baseline total fat intake. This trial was registered at clinicaltrials.gov as NCT00000611. Link to the WHI trial protocol: https://www.whi.org/about/SitePages/Dietary%20Trial.aspx

Using HbA1c to improve efficacy of the American Diabetes Association fasting plasma glucose criterion in screening for new type 2 diabetes in American Indians. The Strong Heart Study

WSTĘP. Celem badania jest określenie optymalnej krytycznej linii FPG-HbA1c, umożliwiającej rozpoznanie cukrzycy w grupie chorych z nieprawidłowym stężeniem glukozy na czczo (IFG, impaired fasting glucose) i poprawa skuteczności oznaczenia glikemii na czczo (FPG, fasting plasma glucose), stosowanego jako samodzielne badanie przesiewowe w kierunku cukrzycy u Indian amerykańskich. MATERIAŁ I METODY. Analizowano oznaczenia stężenia glukozy na czczo i 2 godziny po doustnym obciążeniu glukozą (2hPG) oraz HbA1c w grupie 2389 Indian amerykańskich w wieku 45-74 lat, którzy dotychczas nie byli leczeni z powodu cukrzycy, u których wcześniej nie rozpoznawano cukrzycy, a których poddano wyjściowej i powtórnej ocenie w ramach badania SHS (Strong Heart Study). Zgodnie z kryteriami American Diabetes Association cukrzycę rozpoznawano, gdy stężenie glukozy na czczo było równe lub wyższe niż 126 mg/dl lub gdy wartość 2hPG wynosiła 200 mg/dl lub więcej. Nieprawidłowe stężenie glukozy na czczo rozpoznawano, gdy mieściło się ono w przedziale 110 Ł FPG < 126 mg/dl, a jako wartość prawidłową (NFG, normal fasting glucose) przyjęto stężenie glukozy na czczo niższe niż 110 mg/dl. Do rozpoznawania cukrzycy w grupie badanych z IFG (2hPG ł 200 mg/dl) zastosowano modele regresji logistycznej. Najlepszy model wybrano na podstawie porównania pól pod krzywymi ROC (receiver operating characteristic) utworzonymi w oparciu o różne modele regresji logistycznej. Do wyznaczenia optymalnych wartości krytycznych użyto funkcji przydatności opartej na najlepszym modelu oraz współczynniku koszt/korzyść. Dane z drugiego badania wykorzystano do oceny wpływu czasu, jaki upłynął pomiędzy dwoma kolejnymi badaniami przesiewowymi, zarówno na kryterium FPG, jak i na optymalną krytyczną linię FPG-HbA1c. WYNIKI. W grupie chorych z nowo rozpoznaną cukrzycą, u 37% w badaniu wyjściowym oraz u 55,2% w badaniu powtórnym stwierdzono wartości 2hPG większe bądź równe 200 mg/dl, przy wartościach FPG mniejszych niż 126 mg/dl. Zarówno w wyjściowym, jak i w drugim oznaczeniu u znacznej części pacjentów z IFG rozpoznano cukrzycę (odpowiednio: 19,3 i 22,9%). Porównanie pól pod krzywymi ROC dla poszczególnych modeli regresji logistycznej wykazało, że największa wartość pola odpowiada łącznemu oznaczeniu FPG i HbA1c. Wartość ta była znamiennie wyższa od wartości pola dla oznaczenia FPG (p = 0,0008). Dla współczynnika koszt/korzyść = 0,23888 optymalna linia krytyczna o największej użyteczności miała wartość równą 0,89 × HbA1c + 0,11 × FPG = 17,92. U chorych, u których wartości FPG i HbA1c znajdowały się na tej linii lub powyżej, zalecano wykonanie doustnego testu tolerancji glukozy (OGTT, oral glucose tolerance test) w celu rozpoznania lub wykluczenia cukrzycy. Optymalne wartości krytyczne w badaniu powtórzonym po 4 latach były mniejsze. WNIOSKI. Według kryteriów American Diabetes Association cukrzycę rozpoznaje się, gdy wartość FPG jest większa lub równa 126 mg/dl albo gdy wartość 2hPG wynosi 200 mg/dl lub więcej. Wykonanie badania FPG jest proste i zaleca się je jako badanie przesiewowe. Natomiast stosowanie w praktyce OGTT w celu uzyskania wartości 2hPG jest kłopotliwe, szczególnie u chorych, u których stwierdza się wartość FPG poniżej 126 mg/dl. Wykonywanie OGTT jako badania przesiewowego u każdego pacjenta również jest niepraktyczne. Uzyskane dane wskazują, że u 37% osób z nowo wykrytą cukrzycą w badaniu wyjściowym i u 55,2% w oznaczeniu drugim stężenie glukozy w OGTT wynosiło 200 mg/dl lub więcej, podczas gdy wartość FPG była niższa niż 126 mg/dl. W takich wypadkach, na podstawie oznaczenia wyłącznie FPG jako badania przesiewowego, cukrzyca nie zostałaby rozpoznana. Mimo że odsetek chorych na cukrzycę w grupie NFG jest mały i może zostać zignorowany (4,7% w pierwszym i 6,5% w drugim oznaczeniu), to częstość przypadków cukrzycy stwierdzonych w grupie IFG w trakcie niniejszego badania (ok. 20%) wymaga uwzględnienia w dyskusji na temat metody badań przesiewowych. Wydaje się, że u części chorych z nieprawidłowym stężeniem glukozy na czczo, wybranych na podstawie optymalnych krytycznych wartości FPG-HbA1c, warto wykonać OGTT. Wyznaczenie optymalnej linii krytycznej i odstępu między kolejnymi testami przesiewowymi wymaga dalszych badań.INTRODUCTION. To find an optimal critical line in the fasting plasma glucose (FPG)-HbA1c plane for identifying diabetes in participants with impaired fasting glucose (IFG) and thereby improve the efficacy of using FPG alone in diabetes screening among American Indians. RESEARCH DESIGN AND METHODS. We used FPG, 2-h postload glucose (2hPG), and HbA1c measured in the 2,389 American Indians (aged 45&#8211;74 years, without diabetes treatment or prior history of diabetes) in the Strong Heart Study (SHS) baseline (second) examination. Participants were classified as having diabetes if they had either FPG &#163; 126 mg/dl or 2hPG &#8805; 200 mg/dl, as having IFG if they had 110 &#163; FPG < 126 mg/dl, and as having normal fasting glucose (NFG) if they had FPG < 110, according to the American Diabetes Association (ADA) definition. Logistic regression models were used for identifying diabetes (2hPG &#8805; 200 mg/dl) in IFG participants. The areas under the receiver operating characteristic (ROC) curves generated by different logistic regression models were evaluated and compared to select the best model. A utility function based on the best model and the cost-to-benefit ratio was used to find the optimal critical line. The data from the second examination were used to study the effect of the time interval between the successive diabetes screenings on both the FPG criterion and the optimal critical line. RESULTS. A total of 37% of all subjects with new diabetes at baseline and 55.2% of those in the second exam had 2hPG &#8805; 200 but FPG < 126. There was a very large portion of IFG participants with diabetes (19.3 and 22.9% in the baseline and second exam, respectively). Among the areas under the ROC curves, the area generated by the logistic regression model on FPG plus HbA1c is the largest and is significantly larger than that based on FPG (P = = 0.0008). For a cost-to-benefit ratio of 0.23888, the optimal critical line that has the highest utility is: 0.89 × HbA1c + 0.11 × FPG = 17.92. Those IFG participants whose FPG and HbA1c were above or on the line were referred to take an oral glucose tolerance test (OGTT) to diagnose diabetes. The optimal critical line is lower if a successive diabetes screening will be conducted 4 years after the previous screening. CONCLUSIONS. FPG &#8805; 126 and 2hPG &#8805; 200, as suggested by the ADA, are used in-dependently to define diabetes. The FPG level is easy to obtain, and using FPG alone is suggested for diabetes screening. It is difficult to get physicians and patients to perform an OGTT to get a 2hPG level because of the many drawbacks of the OGTT, especially in those patients who already have FPG < 126. It is also impractical to conduct an OGTT for everyone in a diabetes screening. Our data show that 37% of all subjects with new diabetes in the SHS baseline exam and 55.2% of those in the second exam have 2hPG &#8805; 200 but FPG < 126. These cases of diabetes cannot be detected if FPG is used alone in a diabetes screening. Therefore, although the small portion of diabetes in the NFG group (4.7% in the base-line and 6.9% in the second exam) may be ignored, those cases of diabetes among IFG participants (~20% in our data) need further consideration in a diabetes screening. It may be worthwhile for those IFG participants identified by the optimal critical line to take an OGTT. The optimal critical line and time interval between successive diabetes screenings need further study

Genetic Variants Related to Cardiometabolic Traits Are Associated to B Cell Function, Insulin Resistance, and Diabetes Among AmeriCan Indians: The Strong Heart Family Study

Background: Genetic research may inform underlying mechanisms for disparities in the burden of type 2 diabetes mellitus among American Indians. Our objective was to assess the association of genetic variants in cardiometabolic candidate genes with B cell dysfunction via HOMA-B, insulin resistance via HOMA-IR, and type 2 diabetes mellitus in the Strong Heart Family Study (SHFS). Methods and Results: We examined the association of variants, previously associated with cardiometabolic traits (∼200,000 from Illumina Cardio MetaboChip), using mixed models of HOMA-B residuals corrected for HOMA-IR (cHOMA-B), log transformed HOMA-IR, and incident diabetes, adjusted for age, sex, population stratification, and familial relatedness. Center-specific estimates were combined using fixed effect meta-analyses. We used Bonferroni correction to account for multiple testing (P \u3c 4.13 × 10−7). We also assessed the association between variants in candidate diabetes genes with these metabolic traits. We explored the top SNPs in an independent, replication sample from Southwestern Arizona. We identified significant associations with cHOMA-B for common variants at 26 loci of which 8 were novel (PRSS7, FCRL5, PEL1, LRP12, IGLL1, ARHGEF10, PARVA, FLJ16686). The most significant variant association with cHOMA-B was observed on chromosome 5 for an intergenic variant near PARP8 (rs2961831, P = 6.39 × 10−9). In the replication study, we found a signal at rs4607517 near GCK/YKT6 (P = 0.01). Variants near candidate diabetes genes (especially GCK and KCNQ1) were also nominally associated with HOMA-IR and cHOMA-B. Conclusion: We identified variants at novel loci and confirmed those at known candidate diabetes loci associations for cHOMA-B. This study also provided evidence for association of variants at KCNQ2, CTNAA2, and KCNQ1with cHOMA-B among American Indians. Further studies are needed to account for the high heritability of diabetes among the American Indian participants of the SHFS cohort

Evaluation of diet pattern and weight gain in postmenopausal women enrolled in the Women’s Health Initiative Observational Study

Abstract It is unclear which of four popular contemporary diet patterns is best for weight maintenance among postmenopausal women. Four dietary patterns were characterised among postmenopausal women aged 49–81 years (mean 63·6 ( sd 7·4) years) from the Women’s Health Initiative Observational Study: (1) a low-fat diet; (2) a reduced-carbohydrate diet; (3) a Mediterranean-style (Med) diet; and (4) a diet consistent with the US Department of Agriculture’s Dietary Guidelines for Americans (DGA). Discrete-time hazards models were used to compare the risk of weight gain (≥10 %) among high adherers of each diet pattern. In adjusted models, the reduced-carbohydrate diet was inversely related to weight gain (OR 0·71; 95 % CI 0·66, 0·76), whereas the low-fat (OR 1·43; 95 % CI 1·33, 1·54) and DGA (OR 1·24; 95 % CI 1·15, 1·33) diets were associated with increased risk of weight gain. By baseline weight status, the reduced-carbohydrate diet was inversely related to weight gain among women who were normal weight (OR 0·72; 95 % CI 0·63, 0·81), overweight (OR 0·67; 95 % CI 0·59, 0·76) or obese class I (OR 0·63; 95 % CI 0·53, 0·76) at baseline. The low-fat diet was associated with increased risk of weight gain in women who were normal weight (OR 1·28; 95 % CI 1·13, 1·46), overweight (OR 1·60; 95 % CI 1·40, 1·83), obese class I (OR 1·73; 95 % CI 1·43, 2·09) or obese class II (OR 1·44; 95 % CI 1·08, 1·92) at baseline. These findings suggest that a low-fat diet may promote weight gain, whereas a reduced-carbohydrate diet may decrease risk of postmenopausal weight gain