Person:

Tobias, Deirdre

OBJECTIVE Examine the association of prepregnancy habitual consumption of fruits and fruit juices and gestational diabetes mellitus (GDM) risk. RESEARCH DESIGN AND METHODS A prospective study among women with at least one singleton pregnancy in the Nurses’ Health Study II from 1991 to 2001. RESULTS Among 13,475 women, 860 reported a first diagnosis of GDM. The adjusted relative risks (RRs) for GDM from the lowest to highest quintile of whole fruit consumption were 1.00 (referent), 0.80 (95% CI 0.65–0.98), 0.90 (0.73–1.10), 0.80 (0.64–1.00), and 0.93 (0.76–1.16), respectively. The corresponding RRs for fruit juice were 1.00, 0.82 (0.66–1.01), 0.78 (0.63–0.96), 0.84 (0.68–1.04), and 1.00 (0.81–1.23). CONCLUSIONS These data suggest that prepregnancy higher consumption of whole fruits is not associated with an increased GDM risk. The association between fruit juices and GDM risk appears to be nonlinear.

OBJECTIVE: Whether a history of gestational diabetes mellitus (GDM) is associated with an increased risk of hypertension after the index pregnancy is not well established. RESEARCH DESIGN AND METHODS: We investigated the association between GDM and subsequent risk of hypertension after the index pregnancy among 25,305 women who reported at least one singleton pregnancy between 1991 and 2007 in the Nurses’ Health Study II. RESULTS: During 16 years of follow-up, GDM developed in 1,414 women (5.6%) and hypertension developed in 3,138. A multivariable Cox proportional hazards model showed women with a history of GDM had a 26% increased risk of developing hypertension compared with those without a history of GDM (hazard ratio 1.26 [95% CI 1.11–1.43]; P = 0.0004). These results were independent of pregnancy hypertension or subsequent type 2 diabetes. CONCLUSIONS: These results indicate that women with GDM are at a significant increased risk of developing hypertension after the index pregnancy.

OBJECTIVE It is important to identify modifiable factors that may lower gestational diabetes mellitus (GDM) risk. Dietary iron is of particular interest given that iron is a strong prooxidant, and high body iron levels can damage pancreatic β-cell function and impair glucose metabolism. The current study is to determine if prepregnancy dietary and supplemental iron intakes are associated with the risk of GDM. RESEARCH DESIGN AND METHODS A prospective study was conducted among 13,475 women who reported a singleton pregnancy between 1991 and 2001 in the Nurses’ Health Study II. A total of 867 incident GDM cases were reported. Pooled logistic regression was used to estimate the relative risk (RR) of GDM by quintiles of iron intake controlling for dietary and nondietary risk factors. RESULTS Dietary heme iron intake was positively and significantly associated with GDM risk. After adjusting for age, BMI, and other risk factors, RRs (95% CIs) across increasing quintiles of heme iron were 1.0 (reference), 1.11 (0.87–1.43), 1.31 (1.03–1.68), 1.51 (1.17–1.93), and 1.58 (1.21–2.08), respectively (P for linear trend 0.0001). The multivariate adjusted RR for GDM associated with every 0.5-mg per day of increase in intake was 1.22 (1.10–1.36). No significant associations were observed between total dietary, nonheme, or supplemental iron intake and GDM risk. CONCLUSIONS These findings suggest that higher prepregnancy intake of dietary heme iron is associated with an increased GDM risk.

OBJECTIVE: Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy and is associated with a substantially elevated risk of adverse health outcomes for both mothers and offspring. Physical activity may contribute to the prevention of GDM and thus is crucial for dissecting the vicious circle involving GDM, childhood obesity, and adulthood obesity, and diabetes. Therefore, we aimed to systematically review and synthesize the current evidence on the relation between physical activity and the development of GDM. RESEARCH DESIGN AND METHODS: Medline, EMBASE, and Cochrane Reviews were searched from inception to 31 March 2010. Studies assessing the relationship between physical activity and subsequent development of GDM were included. Characteristics including study design, country, GDM diagnostic criteria, ascertainment of physical activity, timing of exposure (prepregnancy or early pregnancy), adjusted relative risks, CIs, and statistical methods were extracted independently by two reviewers. RESULTS: Our search identified seven prepregnancy and five early pregnancy studies, including five prospective cohorts, two retrospective case-control studies, and two cross-sectional study designs. Prepregnancy physical activity was assessed in 34,929 total participants, which included 2,813 cases of GDM, giving a pooled odds ratio (OR) of 0.45 (95% CI 0.28–0.75) when the highest versus lowest categories were compared. Exercise in early pregnancy was assessed in 4,401 total participants, which included 361 cases of GDM, and was also significantly protective (0.76 [95% CI 0.70–0.83]). CONCLUSIONS: Higher levels of physical activity before pregnancy or in early pregnancy are associated with a significantly lower risk of developing GDM.

Objective: To quantify the association between a combination of healthy lifestyle factors before pregnancy (healthy body weight, healthy diet, regular exercise, and not smoking) and the risk of gestational diabetes. Design: Prospective cohort study. Setting: Nurses’ Health Study II, United States. Participants: 20 136 singleton live births in 14 437 women without chronic disease. Main outcome measure Self reported incident gestational diabetes diagnosed by a physician, validated by medical records in a previous study. Results: Incident first time gestational diabetes was reported in 823 pregnancies. Each lifestyle factor measured was independently and significantly associated with risk of gestational diabetes. The combination of three low risk factors (non-smoker, ≥150 minutes a week of moderate to vigorous physical activity, and healthy eating (top two fifths of Alternate Healthy Eating Index-2010 adherence score)) was associated with a 41% lower risk of gestational diabetes compared with all other pregnancies (relative risk 0.59, 95% confidence interval 0.48 to 0.71). Addition of body mass index (BMI) <25 before pregnancy (giving a combination of four low risk factors) was associated with a 52% lower risk of gestational diabetes compared with all other pregnancies (relative risk 0.48, 0.38 to 0.61). Compared with pregnancies in women who did not meet any of the low risk lifestyle factors, those meeting all four criteria had an 83% lower risk of gestational diabetes (relative risk 0.17, 0.12 to 0.25). The population attributable risk percentage of the four risk factors in combination (smoking, inactivity, overweight, and poor diet) was 47.5% (95% confidence interval 35.6% to 56.6%). A similar population attributable risk percentage (49.2%) was observed when the distributions of the four low risk factors from the US National Health and Nutrition Examination Survey (2007-10) data were applied to the calculation. Conclusions: Adherence to a low risk lifestyle before pregnancy is associated with a low risk of gestational diabetes and could be an effective strategy for the prevention of gestational diabetes.

Objectives To prospectively assess the joint association of birth weight and established lifestyle risk factors in adulthood with incident type 2 diabetes and to quantitatively decompose the attributing effects to birth weight only, to adulthood lifestyle only, and to their interaction. Design: Prospective cohort study. Setting: Health Professionals Follow-up Study (1986-2010), Nurses’ Health Study (1980-2010), and Nurses’ Health Study II (1991-2011). Participants: 149 794 men and women without diabetes, cardiovascular disease, or cancer at baseline. Main outcome measure Incident cases of type 2 diabetes, identified through self report and validated by a supplementary questionnaire. Unhealthy lifestyle was defined on the basis of body mass index, smoking, physical activity, alcohol consumption, and the alternate healthy eating index. Results: During 20-30 years of follow-up, 11 709 new cases of type 2 diabetes were documented. The multivariate adjusted relative risk of type 2 diabetes was 1.45 (95% confidence interval 1.32 to 1.59) per kg lower birth weight and 2.10 (1.71 to 2.58) per unhealthy lifestyle factor. The relative risk of type 2 diabetes associated with a combination of per kg lower birth weight and per unhealthy lifestyle factor was 2.86 (2.26 to 3.63), which was more than the addition of the risk associated with each individual factor, indicating a significant interaction on an additive scale (P for interaction<0.001). The attributable proportions of joint effect were 22% (95% confidence interval 18.3% to 26.4%) to lower birth weight alone, 59% (57.1% to 61.5%) to unhealthy lifestyle alone, and 18% (13.9% to 21.3%) to their interaction. Conclusion: Most cases of type 2 diabetes could be prevented by the adoption of a healthier lifestyle, but simultaneous improvement of both prenatal and postnatal factors could further prevent additional cases.

OBJECTIVE Dietary protein is an important modulator of glucose metabolism. However, studies regarding the association between dietary protein intake and gestational diabetes mellitus (GDM) risk are sparse. This study was to examine the association. RESEARCH DESIGN AND METHODS Our study included 21,457 singleton pregnancies reported among 15,294 participants of the Nurses' Health Study II cohort between 1991 and 2001. Included pregnancies were free of chronic diseases before pregnancy or previous GDM. Generalized estimating equations were used to estimate the relative risks (RRs) and 95% CIs. RESULTS After adjustment for age, parity, nondietary and dietary factors, and BMI, multivariable RRs (95% CIs) comparing the highest with lowest quintiles were 1.49 (1.03–2.17) for animal protein intake and 0.69 (0.50–0.97) for vegetable protein intake. The substitution of 5% energy from vegetable protein for animal protein was associated with a 51% lower risk of GDM (RR [95% CI], 0.49 [0.29–0.84]). For major dietary protein sources, multivariable RRs (95% CIs) comparing the highest with the lowest quintiles were 2.05 (1.55–2.73) for total red meat and 0.73 (0.56–0.95) for nuts, respectively. The substitution of red meat with poultry, fish, nuts, or legumes showed a significantly lower risk of GDM. CONCLUSIONS Higher intake of animal protein, in particular red meat, was significantly associated with a greater risk of GDM. By contrast, higher intake of vegetable protein, specifically nuts, was associated with a significantly lower risk. Substitution of vegetable protein for animal protein, as well as substitution of some healthy protein sources for red meat, was associated with a lower risk of GDM.

There is indisputable evidence from epidemiologic and clinical studies that being overweight and obese elevates the risk of developing debilitating and costly chronic diseases, including hypertension, hypercholesterolemia, type 2 diabetes, cardiovascular diseases (CVD), and cancer (1). Nonetheless, the relationship between body mass index (BMI) and mortality remains the subject of much debate. A recent meta-analysis concluded that compared to those of normal weight (BMI<25.0), overweight individuals (BMI 25.0–29.9) had a significantly lower mortality risk (2). Even Class 1 obesity (BMI 30–34.9) was associated with marginally reduced mortality. In this Perspective, we discuss why this finding is likely to be an artifact of methodological limitations and what the clinical and public health implications may be.

Background: The relation between body weight and mortality among persons with type 2 diabetes remains unresolved, with some studies suggesting decreased mortality among overweight or obese persons as compared with normal-weight persons (an “obesity paradox”). Methods: We studied participants with incident diabetes from the Nurses’ Health Study (8970 participants) and Health Professionals Follow-up Study (2457 participants) who were free of cardiovascular disease and cancer at the time of a diagnosis of diabetes. Body weight shortly before diagnosis and height were used to calculate the body-mass index (BMI, the weight in kilograms divided by the square of the height in meters). Multivariable Cox models were used to estimate the hazard ratios and 95% confidence intervals for mortality across BMI categories. Results: There were 3083 deaths during a mean period of 15.8 years of follow-up. A J-shaped association was observed across BMI categories (18.5 to 22.4, 22.5 to 24.9 [reference], 25.0 to 27.4, 27.5 to 29.9, 30.0 to 34.9, and ≥35.0) for all-cause mortality (hazard ratio, 1.29 [95% confidence interval {CI}, 1.05 to 1.59]; 1.00; 1.12 [95% CI, 0.98 to 1.29]; 1.09 [95% CI, 0.94 to 1.26]; 1.24 [95% CI, 1.08 to 1.42]; and 1.33 [95% CI, 1.14 to 1.55], respectively). This relationship was linear among participants who had never smoked (hazard ratios across BMI categories: 1.12, 1.00, 1.16, 1.21, 1.36, and 1.56, respectively) but was nonlinear among participants who had ever smoked (hazard ratios across BMI categories: 1.32, 1.00, 1.09, 1.04, 1.14, and 1.21) (P=0.04 for interaction). A direct linear trend was observed among participants younger than 65 years of age at the time of a diabetes diagnosis but not among those 65 years of age or older at the time of diagnosis (P<0.001 for interaction). Conclusions: We observed a J-shaped association between BMI and mortality among all partici- pants and among those who had ever smoked and a direct linear relationship among those who had never smoked. We found no evidence of lower mortality among patients with diabetes who were overweight or obese at diagnosis, as com- pared with their normal-weight counterparts, or of an obesity paradox.

Background: The effectiveness of low-fat diets for long-term weight loss has been debated for decades, with dozens of randomized trials (RCTs) and recent reviews giving mixed results. Methods: We conducted a random effects meta-analysis of RCTs to estimate the long-term effect of low-fat vs. higher fat dietary interventions on weight loss. Our search included RCTs conducted in adult populations reporting weight change outcomes at ≥1 year, comparing low-fat with higher fat interventions, published through July 2014. The primary outcome measure was mean difference in weight change between interventions. Findings: Fifty-three studies met inclusion criteria representing 68,128 participants. In the setting of weight loss trials, low-carbohydrate interventions led to significantly greater weight loss than low-fat interventions (n comparisons=18; weighted mean difference [WMD]=1.15 kg, 95% CI=0.52 to 1.79; I2=10%). Low-fat did not lead to differences in weight change compared with other moderate fat weight loss interventions (n=19; WMD=0.36, 95% CI=-0.66 to 1.37; I2=82%), and were superior only when compared with “usual diet” (n=8; WMD=-5.41, 95% CI=-7.29 to −3.54; I2=68%). Similarly, non-weight loss trials and weight maintenance trials, for which there were no low-carbohydrate comparisons, had similar effects for low-fat vs moderate fat interventions, and were superior compared with “usual diet”. Weight loss trials achieving a greater difference in fat intake at follow-up significantly favored the higher fat dietary interventions, as indicated by difference of ≥5% of calories from fat (n=18; WMD=1.04, 95% CI=0.06 to 2.03; I2=78%) or by difference in change serum triglycerides of ≥5 mg/dL (n=17; WMD=1.38, 95% CI=0.50 to 2.25; I2=62%). Interpretation These findings suggest that the long-term effect of low-fat diets on body weight depends on the intensity of intervention in the comparison group. When compared to dietary interventions of similar intensity, evidence from RCTs does not support low-fat diets over other dietary interventions.