An Observational Analysis of Meal Patterns in Overweight and Obese Pregnancy

Background Nutrient intakes are known to be poorer among pregnant women with raised body mass index (BMI) than those with a healthy BMI. While meal patterns have the potential to influence obstetric, metabolic and anthropometric measures for mother and infant, limited data exists regarding meal patterns among pregnant women with raised BMI. Aim To identify categories of meal patterns among pregnant women with overweight and obesity and determine whether patterns change with advancing gestation. To determine if maternal meal patterns are associated with dietary intakes and pregnancy outcomes. Methods Prospective, observational analysis of pregnant women (n = 143) (BMI 25–39.9 kg/m2). Meal pattern data were analysed from 3-day food diaries at 16 and 28 weeks’ gestation. Outcomes include maternal blood glucose, insulin resistance, gestational diabetes, gestational weight gain and infant anthropometry. Results Three meal pattern categories were identified: ‘main meal dominant’ (3 main eating occasions + 0–3 snacks), ‘large meal dominant’ (≤ 2 main eating occasions + \u3c 2 snacks), and ‘snack dominant’ (3 main eating occasions + \u3e 3 snacks and ≤2main + ≥ 2 snacks). A main meal–dominant pattern prevailed at 16 weeks’ (85.3%) and a snack-dominant pattern at 28 weeks’ (68.5%). Dietary glycaemic index was lower among the main meal versus large meal–dominant pattern at 28 weeks (P = 0.018). Infant birth weight (kg) and macrosomia were highest among participants with a large meal–dominant pattern at 28 weeks (P = 0.030 and P = 0.008, respectively). Conclusion Women with raised BMI changed eating patterns as pregnancy progressed, moving from main meal–dominant to snack-dominant patterns. Large meal–dominant meal patterns in later pregnancy were associated with higher glycaemic index and greater prevalence of macrosomia

Nutrition, Behavior Change and Physical Activity Outcomes From the PEARS RCT—An mHealth-Supported, Lifestyle Intervention Among Pregnant Women With Overweight and Obesity

Background: Diet quality and physical activity positively impact pregnancy outcomes among women with obesity, but successful lifestyle interventions require intense clinician time. We aimed to investigate the impact of a behavioral-lifestyle intervention (PEARS) supported by a smartphone app among pregnant women with overweight and obesity, on nutrient intake, behavioral stage-of-change and physical activity. Methods: Pregnant women (BMI 25–39.9 kg/m2, measured, n = 565) were randomized at 15.6 weeks\u27 gestation to the intervention (n = 278), or a control group (n = 287) (ISRCTN29316280). The intervention was grounded in behavior-change theory. Participants received nutrition (low glycaemic index and healthy eating) and exercise advice, a smartphone app and fortnightly emails. The control group received usual care which does not include dietary advice. At baseline and 28 weeks\u27 gestation, dietary data were obtained through 3-day food diaries (n = 290 matched), and stage-of-change and physical activity data were self-reported. App usage data were collected. Results: There were no differences between the groups at baseline. Compared with the control group, the intervention group had improved dietary intakes post-intervention with; lower glycaemic index (MD −1.75); free sugars (%TE) (MD −0.98); fat (%TE) (MD −1.80); and sodium (mg) (MD −183.49). Physical activity (MET-minutes/week) was higher in the intervention group post-intervention (MD 141.4; 95% CI 62.9, 219.9). The proportion of participants at “maintenance” stage-of-change for physical activity was higher in the intervention group (56.3 vs. 31.2%). App use was associated with lower glycaemic index and less energy from free sugars, but not with physical activity. Conclusion: A behavioral-lifestyle intervention in pregnancy supported by a smartphone app improved dietary intakes, physical activity, and motivation to engage in exercise

Non-standard neutrino interactions in IceCube

Non-standard neutrino interactions (NSI) may arise in various types of new physics. Their existence would change the potential that atmospheric neutrinos encounter when traversing Earth matter and hence alter their oscillation behavior. This imprint on coherent neutrino forward scattering can be probed using high-statistics neutrino experiments such as IceCube and its low-energy extension, DeepCore. Both provide extensive data samples that include all neutrino flavors, with oscillation baselines between tens of kilometers and the diameter of the Earth. DeepCore event energies reach from a few GeV up to the order of 100 GeV - which marks the lower threshold for higher energy IceCube atmospheric samples, ranging up to 10 TeV. In DeepCore data, the large sample size and energy range allow us to consider not only flavor-violating and flavor-nonuniversal NSI in the μ−τ sector, but also those involving electron flavor. The effective parameterization used in our analyses is independent of the underlying model and the new physics mass scale. In this way, competitive limits on several NSI parameters have been set in the past. The 8 years of data available now result in significantly improved sensitivities. This improvement stems not only from the increase in statistics but also from substantial improvement in the treatment of systematic uncertainties, background rejection and event reconstruction

IceCube Search for Earth-traversing ultra-high energy Neutrinos

The search for ultra-high energy neutrinos is more than half a century old. While the hunt for these neutrinos has led to major leaps in neutrino physics, including the detection of astrophysical neutrinos, neutrinos at the EeV energy scale remain undetected. Proposed strategies for the future have mostly been focused on direct detection of the first neutrino interaction, or the decay shower of the resulting charged particle. Here we present an analysis that uses, for the first time, an indirect detection strategy for EeV neutrinos. We focus on tau neutrinos that have traversed Earth, and show that they reach the IceCube detector, unabsorbed, at energies greater than 100 TeV for most trajectories. This opens up the search for ultra-high energy neutrinos to the entire sky. We use ten years of IceCube data to perform an analysis that looks for secondary neutrinos in the northern sky, and highlight the promise such a strategy can have in the next generation of experiments when combined with direct detection techniques