孕前体质指数及孕期增重对新生儿出生体重影响的前瞻性队列研究

  目的   分析孕妇孕前体质指数(body mass index, BMI)及孕期增重(gestational weight gain, GWG)与新生儿出生体重的关联性, 并探究孕妇孕前及孕中体重动态变化对新生儿低出生体重(low birth weight, LBW)及巨大儿的影响。   方法   收集中国孕产妇队列·协和纳入的孕早期孕妇孕前体重, 并随访至分娩后, 收集分娩前体重及新生儿出生结局。将孕妇孕前BMI分为低体重组、正常体重组及超重/肥胖组, 将GWG分为适宜、不足及过多组。采用多因素多分类(多项)Logistic回归分析模型探讨孕前BMI及GWG与新生儿出生体重的关系。   结果   孕前BMI及GWG与子代出生体重相关(均有P < 0.05)。孕前超重/肥胖(OR=2.339, 95% CI:1.674~2.282, P < 0.001)、GWG过多(OR=1.398, 95% CI:1.188~1.978, P=0.048)显示为巨大儿的危险因素, GWG不足(OR=1.479, 95% CI:1.461~1.679, P=0.035)显示为LBW的危险因素, GWG过多会降低LBW的发生风险(OR=0.428, 95% CI:0.225~0.817, P=0.010)。低BMI-GWG不足(OR=1.335, 95% CI:1.048~2.319, P=0.048)是LBW的危险因素; 正常BMI-GWG过多(OR=1.088, 95% CI:1.016~1.675, P=0.038)和超重/肥胖-GWG过多(OR=1.498, 95% CI:1.244~2.017, P=0.046)是巨大儿的危险因素。   结论   孕前BMI及GWG是影响新生儿出生体重的重要因素, 提示女性应合理控制孕前及孕中体重变化。     

The Role of Maternal Weight in the Hierarchy of Macrosomia Predictors; Overall Effect of Analysis of Three Prediction Indicators

So far it has not been established which maternal features play the most important role in newborn macrosomia. The aim of this study is to provide assessment of a hierarchy of twenty six (26) maternal characteristics in macrosomia prediction. A Polish prospective cohort of women with singleton pregnancy (N = 912) which was recruited in the years 2015–2016 has been studied. Two analyses were performed: for probability of macrosomia > 4000 g (n = 97) (vs. 755 newborns 2500–4000 g); and for birthweight > 90th percentile (n = 99) (vs. 741 newborns 10–90th percentile). A multiple logistic regression was used (with 95% confidence intervals (CI)). A hierarchy of significance of potential predictors was established after summing up of three prediction indicators (NRI, IDI and AUC) calculated for the basic prediction model (maternal age + parity) extended with one (test) predictor. ‘Net reclassification improvement’ (NRI) focuses on the reclassification table describing the number of women in whom an upward or downward shift in the disease probability value occurred after a new factor had been added, including the results for healthy and ill women. ‘Integrated discrimination improvement’ (IDI) shows the difference between the value of mean change in predicted probability between the group of ill and healthy women when a new factor is added to the model. The area under curve (AUC) is a commonly used indicator. Results. The macrosomia risk was the highest for prior macrosomia (AOR = 7.53, 95%CI: 3.15–18.00, p < 0.001). A few maternal characteristics were associated with more than three times higher macrosomia odds ratios, e.g., maternal obesity and gestational age ≥ 38 weeks. A different hierarchy was shown by the prediction study. Compared to the basic prediction model (AUC = 0.564 (0.501–0.627), p = 0.04), AUC increased most when pre-pregnancy weight (kg) was added to the base model (AUC = 0.706 (0.649–0.764), p < 0.001). The values of IDI and NRI were also the highest for the model with maternal weight (IDI = 0.061 (0.039–0.083), p < 0.001), and (NRI = 0.538 (0.33–0.746), p < 0.001). Adding another factor to the base model was connected with significantly weaker prediction, e.g., for gestational age ≥ 38 weeks (AUC = 0.602 (0.543–0.662), p = 0.001), (IDI = 0.009 (0.004; 0.013), p < 0.001), and (NRI = 0.155 (0.073; 0.237), p < 0.001). After summing up the effects of NRI, IDI and AUC, the probability of macrosomia was most strongly improved (in order) by: pre-pregnancy weight, body mass index (BMI), excessive gestational weight gain (GWG) and BMI ≥ 25 kg/m². Maternal height, prior macrosomia, fetal sex-son, and gestational diabetes mellitus (GDM) occupied an intermediate place in the hierarchy. The main conclusions: newer prediction indicators showed that (among 26 features) excessive pre-pregnancy weight/BMI and excessive GWG played a much more important role in macrosomia prediction than other maternal characteristics. These indicators more strongly highlighted the differences between predictors than the results of commonly used odds ratios.     

Effects of Plant-Based Diets on Weight Status in Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomised Controlled Trials

Excessive adiposity is a major risk factor for type 2 diabetes (T2D), and dietary patterns are important determinants of weight status. Plant-based dietary patterns (PBDs) are known for their therapeutic effects on T2D. The aim is to systematically review RCTs to investigate the effects of various PBDs compared to regular meat-eating diets (RMDs), in individuals who normally consume a RMD on body weight, BMI, and waist circumference in T2D. RCTs investigating PBDs and body weight, BMI, WC for ≥6 weeks in adults with T2D since 1980 were eligible for inclusion. Seven trials (n = 269) were included in the meta-analysis using random-effects models and expressed as MD (95%Cls). Compared to RMDs, PBDs significantly lowered body weight (−2.35 kg, 95% CI: −3.51, −1.19, p < 0.001), BMI (−0.90 kg/m², 95% CI: −1.42, −0.38, p = 0.001) and WC (−2.41 cm, 95% CI: −3.72, −1.09, p < 0.001). PBDs alone significantly reduced body weight by 5.1% (−4.95 kg, 95% CI: −7.34, −2.55, p < 0.001), BMI by 5.4% (−1.87 kg/m², 95% CI: −2.78, −0.95, p < 0.001) and WC by 4.3%(−4.23, 95% CI: −6.38, −2.07, p < 0.001). Interventions not limiting energy intake led to a significant reduction in body weight (−2.54 kg, 95% CI: −4.16, −0.92, p < 0.005) and BMI (−0.91 kg/m², 95% CI: −1.56, −0.25, p < 0.005). Trials ≥16 weeks had a pronounced reduction in body weight (−2.93 kg, 95% CI: −5.00, −0.87, p = 0.005) and BMI (−1.13 kg/m², 95% CI: −1.89, −0.38, p < 0.005). These findings provide evidence for the implementation of PBDs for better management of central adiposity in individuals with T2D.     

Is Probiotic Supplementation Useful for the Management of Body Weight and Other Anthropometric Measures in Adults Affected by Overweight and Obesity with Metabolic Related Diseases? A Systematic Review and Meta-Analysis

The aim of this systematic review and meta-analysis is to assess the effectiveness of probiotics in inducing body weight loss in patients with overweight or obesity with related metabolic diseases. The research was carried out on PubMed and Scopus, focusing on studies reporting the effect on anthropometric measures (weight, body mass Index (BMI), waist circumference (WC), and hip circumference (HC) after administration of various probiotic strains compared to placebo. Twenty randomized controlled trials, that included 1411 patients, were considered. The meta-analyzed mean differences (MD) for random effects showed no significant decrease in body weight after probiotic supplementation (−0.26 kg [−075, 0.23], p = 0.30), while a significant BMI decrease was found (−0.73 kg/m² [−1.31, −0.16], p = 0.01). For WC and HC, the meta-analyzed MD for random effects showed a significant decrease (WC: −0.71 cm [−1.24; −0.19], p = 0.008 and HC: −0.73 cm [−1.16; −0.30], p = 0.0008). The risk of bias was also evaluated considering a high risk and a low risk according to PRISMA criteria. In conclusion, the results of this meta-analysis highlight a positive trend of probiotics supplementation on the amelioration of anthropometric measures of overweight and obese patients with related metabolic diseases. However, further research is needed before recommending the use of probiotics as a therapeutic strategy for these patients. The focus of the future research should be to evaluate the efficacy of different probiotic strains, the quantities to be administered, and the duration of the intervention.     

Impact of Diet Quality during Pregnancy on Gestational Weight Gain and Selected Adipokines—Results of a German Cross-Sectional Study

While nutrition during pregnancy is critical for the health of both mother and child, little is known about the diet quality of women during pregnancy, its correlation with gestational weight gain (GWG)/body composition, and chosen maternal adipokines. Therefore, we evaluated the Healthy Eating Index (HEI) of 110 pregnant women and analyzed its correlation with GWG/body composition, physical activity, leptin, resistin, adiponectin, and interleukin 6 (IL-6), respectively. Diet quality was medium in 63% of women, characterized by a high intake of animal-based products. HEI was negatively influenced by pre-pregnancy obesity (β = −0.335, p = 0.004), and positively influenced by higher age (>35 yrs., β = 0.365, p ≤ 0.001), upper arm circumference (β = 0.222, p = 0.052), and total activity during the third trimester (β = 0.258, p = 0.008). GWG was associated with pre-pregnancy obesity (β = −0.512, p ≤ 0.001), thigh circumference (β = 0.342, p = 0.007), upper arm fat area (β = 0.208, p = 0.092), and maternal age group (>35 yrs. β = −0.166, p = 0.082), but not with HEI. Leptin and IL-6 displayed associations with variables representative of body composition, such as pre-pregnancy BMI, thigh circumference, upper arm fat area, and upper arm circumference, but were not influenced by HEI. Neither were adiponectin and resistin. IL-6 was also associated with total activity. In conclusion, GWG, leptin, and IL-6 were influenced by nutritional status (body composition/pre-pregnancy BMI), not by maternal diet. Physical activity level also had an impact on IL-6. Thus, efforts should be intensified to improve diet quality and participation in sports before and during pregnancy, particularly in overweight or obese women.     

Perinatal weight and risk of prenatal and postpartum depressive symptoms

PurposePrepregnancy obesity and weight changes accompanying pregnancy (gestational weight gain and postpartum weight retention) may be associated with risk of maternal depressive symptoms during pregnancy and in the postpartum. The few studies that have examined these relationships report conflicting findings.MethodsWe studied pregnant (n = 2112) and postpartum (n = 1686) women enrolled in Project Viva. We used self-reported prepregnancy and postpartum weight and measured prenatal weight to calculate prepregnancy body mass index (BMI), gestational weight gain (GWG), and postpartum weight retention at 6 months after birth. We assessed elevated depressive symptoms (EDS) with the Edinburgh Postnatal Depression Scale (≥13 on 0–30 scale) at midpregnancy and 6 months postpartum. We used logistic regression to estimate the odds of prenatal and postpartum EDS in relation to prepregnancy BMI, GWG, and postpartum weight retention.ResultsA total of 214 (10%) participants experienced prenatal EDS and 151 (9%) postpartum EDS. Neither prepregnancy BMI nor GWG was associated with prenatal EDS. Prepregnancy obesity (BMI ≥ 30 kg per m²) was associated with higher odds of postpartum EDS (odds ratio = 1.69, 95% confidence interval, 1.01–2.83) compared to normal prepregnancy weight in a model adjusted for age, race/ethnicity, nativity, education, marital status, household income, parity, pregnancy intention, and smoking.ConclusionsPrepregnancy obesity is associated with elevated depressive symptoms in the postpartum period. Given the current obesity epidemic in the US and the consequences of perinatal depression, additional prevention and screening efforts in this population may be warranted.     

Underreporting of Energy Intake Increases over Pregnancy: An Intensive Longitudinal Study of Women with Overweight and Obesity

(1) Background: Energy intake (EI) underreporting is a widespread problem of great relevance to public health, yet is poorly described among pregnant women. This study aimed to describe and predict error in self-reported EI across pregnancy among women with overweight or obesity. (2) Methods: Participants were from the Healthy Mom Zone study, an adaptive intervention to regulate gestational weight gain (GWG) tested in a feasibility RCT and followed women (n = 21) with body mass index (BMI) ≥25 from 8–12 weeks to ~36 weeks gestation. Mobile health technology was used to measure daily weight (Wi-Fi Smart Scale), physical activity (activity monitor), and self-reported EI (MyFitnessPal App). Estimated EI was back-calculated daily from measured weight and physical activity data. Associations between underreporting and gestational age, demographics, pre-pregnancy BMI, GWG, perceived stress, and eating behaviors were tested. (3) Results: On average, women were 30.7 years old and primiparous (62%); reporting error was −38% ± 26 (range: −134% (underreporting) to 97% (overreporting)), representing an ~1134 kcal daily underestimation of EI (1404 observations). Estimated (back-calculated), but not self-reported, EI increased across gestation (p < 0.0001). Higher pre-pregnancy BMI (p = 0.01) and weekly GWG (p = 0.0007) was associated with greater underreporting. Underreporting was lower when participants reported higher stress (p = 0.02) and emotional eating (p < 0.0001) compared with their own average. (4) Conclusions: These findings suggest systemic underreporting in pregnant women with elevated BMI using a popular mobile app to monitor diet. Advances in technology that allow estimation of EI from weight and physical activity data may provide more accurate dietary self-monitoring during pregnancy.     

Carrot Consumption Frequency Associated with Reduced BMI and Obesity through the SNP Intermediary rs4445711

It is unclear whether genetic interactions are involved in the association between vegetable intake and reduced body mass index (BMI) or obesity. We conducted a comprehensive search for single nucleotide polymorphisms (SNPs) which are associated with the interaction between vegetable intake frequency and BMI or obesity. We performed a genome-wide association analysis to evaluate the genetic interactions between self-reported intake of vegetables such as carrot, broccoli, spinach, other green vegetables (green pepper and green beans), pumpkin, and cabbage with BMI and obesity, which is defined as a BMI ≥ 25.0 kg/m² in the Japanese population (n = 12,225). The mean BMI and prevalence of obesity was 23.9 ± 3.4 kg/m² and 32.3% in men and 22.1 ± 3.8 kg/m² and 17.3% in in women, respectively. A significant interaction was observed between rs4445711 and frequency of carrot intake on BMI (p = 4.5 × 10⁻⁸). This interaction was slightly attenuated after adjustment for age, sex, alcohol intake, smoking, physical activity and the frequency of total vegetable intake (p = 2.1 × 10⁻⁷). A significant interaction was also observed between rs4445711 and frequency of carrot intake on obesity (p = 2.5 × 10⁻⁸). No significant interactions that were the same as the interaction between frequency of carrot intake and rs4445711 were observed between the intake frequency of broccoli, spinach, other green vegetables, pumpkin or cabbage and BMI or obesity. The frequency of carrot consumption is implicated in reducing BMI by the intermediary of rs4445711. This novel genetic association may provide new clues to clarify the association between vegetable intake and BMI or obesity.     

Interactions between Polygenic Risk Scores,Dietary Pattern,and Menarche Age with the Obesity Risk in a Large Hospital-Based Cohort

Obese Asians are more susceptible to metabolic diseases than obese Caucasians of the same body mass index (BMI). We hypothesized that the genetic variants associated with obesity risk interact with the lifestyles of middle-aged and elderly adults, possibly allowing the development of personalized interventions based on genotype. We aimed to examine this hypothesis in a large city hospital-based cohort in Korea. The participants with cancers, thyroid diseases, chronic kidney disease, or brain-related diseases were excluded. The participants were divided into case and control according to their BMI: ≥25 kg/m² (case; n = 17,545) and <25 kg/m² (control; n = 36,283). The genetic variants that affected obesity risk were selected using a genome-wide association study, and the genetic variants that interacted with each other were identified by generalized multifactor dimensionality reduction analysis. The selected genetic variants were confirmed in the Ansan/Ansung cohort, and polygenetic risk scores (PRS)−nutrient interactions for obesity risk were determined. A high BMI was associated with a high-fat mass (odds ratio (OR) = 20.71) and a high skeletal muscle-mass index (OR = 3.38). A high BMI was positively related to metabolic syndrome and its components, including lipid profiles, whereas the initial menstruation age was inversely associated with a high BMI (OR = 0.78). The best model with 5-SNPs included SEC16B_rs543874, DNAJC27_rs713586, BDNF_rs6265, MC4R_rs6567160, and GIPR_rs1444988703. The high PRS with the 5-SNP model was positively associated with an obesity risk of 1.629 (1.475–1.798) after adjusting for the covariates. The 5-SNP model interacted with the initial menstruation age, fried foods, and plant-based diet for BMI risk. The participants with a high PRS also had a higher obesity risk when combined with early menarche, low plant-based diet, and a high fried-food intake than in participants with late menarche, high plant-based diet, and low fried-food intake. In conclusion, people with a high PRS and earlier menarche age are recommended to consume fewer fried foods and a more plant-based diet to decrease obesity risk. This result can be applied to personalized nutrition for preventing obesity.     

Overweight, Gestational Weight Gain and Elevated Fasting Plasma Glucose and Their Association with Macrosomia in Chinese Pregnant Women

To provide a current estimation of overweight, gestational weight gain(GWG), elevated fasting plasma glucose (FPG) in pregnant women in Kunshan, China and investigate their association with macrosomia using recommendations of IOM and International Association of Diabetes and Pregnancy Study Groups. We conducted a population-based retrospective study and analyzed routine data from Kunshan Maternity and Child Care Surveillance System of 27,322 women with singleton full-term birth from 2006 to 2010. The prevalence of maternal overweight at early pregnancy according to WHO BMI categories (BMI: 25.0–29.9 kg/m²) or the cutoffs for Chinese (BMI:24.0–27.9 kg/m²), elevated FPG (≥5.1 mmol/L) were estimated. Proportions of women with GWG below, within and above 2009 IOM recommendations were used to evaluate the adequacy of GWG. The association between maternal overweight, GWG, elevated FPG and macrosomia was analyzed by multiple logistic regression. The prevalence of maternal overweight was 8.9 % according to WHO BMI categories and 11.9 % according to Chinese cutoffs. The rate of elevated FPG at first prenatal visit was 19.4 %. Overweight women gained, on average, 12.2 ± 5.3 or 13.0 ± 5.2 (kg) during gestation, 57.1 or 63.93 % of which had excessive weight gain above IOM recommendations (6.8–11.4 kg) according to WHO BMI categories or Chinese cutoffs, respectively. Maternal overweight, GWG and elevated FPG were positively and significantly associated with macrosomia after adjusting for maternal age and gestational weeks at delivery. Maternal overweight, excessive weight gain, elevated FPG are common in the Chinese population in Kunshan. These metabolic risk factors associated with macrosomia should be controlled under the recommendations for Chinese pregnant population.     

Improvement in Eating Disorder Risk and Psychological Health in People with Class 3 Obesity: Effects of a Multidisciplinary Weight Management Program

This study aimed to evaluate the risk of eating disorders, psychological distress, and health-related quality of life (HRQoL) in people with class 3 obesity (body mass index (BMI) ≥ 40 kg/m²), and the effect of multidisciplinary weight management over 12 months. This retrospective cohort study included all adults with class 3 obesity who enrolled in a weight management program from March 2018 to December 2019. Questionnaires included the Eating Disorder Examination Questionnaire Short (EDE-QS), Kessler Psychological Distress Scale (K10), and 36-Item Short Form Survey (SF-36) for HRQoL. Physical and Mental Component Summary scores (PCS and MCS) were derived from the SF-36. Of 169 participants who completed 12 months in the program, 65.7% (n = 111) completed questionnaires at baseline and 12 months, with 6.0 ± 6.8% weight loss over this period. Compared to baseline, there was significant improvement at 12 months in EDE-QS (15.7 ± 6.6 vs. 13.6 ± 6.2, p = 0.002), K10 (25.7 ± 9.7 vs. 21.2 ± 9.4, p < 0.001), PCS (29.4 ± 10.1 vs. 36.1 ± 10.9, p < 0.001), and MCS scores (40.2 ± 12.4 vs. 44.0 ± 13.4, p = 0.001). All, apart from EDE-QS scores, remained significant after adjusting for weight change. This study highlights the importance of multidisciplinary management in people with class 3 obesity to help reduce eating disorder risk and psychological distress, and improve HRQoL, in addition to weight loss.     

Efficacy of Telephone Health Coaching Integration with Standard Multidisciplinary Care for Adults with Obesity Attending a Weight Management Service: A Pilot Study

Australia has one of the highest prevalences of obesity in the developed world with recognised gaps in patient access to obesity services. This non-randomised before and after study investigated the health benefits and patient acceptability of integrating the Get Healthy Service, a state-funded telephone-delivered coaching service in Australia, as an adjunct to multidisciplinary care for adults attending a public obesity service. Forty-one participants received multidisciplinary care alone while 39 participants were subsequently allocated to receive adjunctive treatment with the Get Healthy Service. Weight, body mass index, glycosylated haemoglobin, measurement of hepatic steatosis and liver enzymes were collected at baseline and 6 months. Participant evaluation was obtained post intervention. Statistically significant reductions from baseline were achieved for both control and intervention with respect to weight (−6.7 ± 2.2 kg, p = 0.01; −12.6 ± 3.2, p = 0.002), body mass index (−2.3 ± 0.8, p = 0.01; −4.8 ± 1.2 kg/m², p = 0.002) and glycosylated haemoglobin (−0.2 ± 0.2%, p = 0.2 (NS); −0.7 ± 0.2%, p = 0.02), respectively. There were no significant differences in steatosis or liver enzymes or in outcomes between control and intervention cohorts. A high level of patient acceptability was reported. Integrating telephone-delivered coaching provided non-inferior care and high levels of patient satisfaction. Telephone coaching aligned with the principles of an obesity service should be trialled to improve patient access to obesity interventions.     

Postpartum weight retention in relation to gestational weight gain and pre-pregnancy body mass index: A prospective cohort study in Vietnam

BackgroundThe prevalence of maternal overweight and obesity is increasing in Asia. This study prospectively investigated the association between pre-pregnancy body mass index (BMI), gestational weight gain (GWG) and 12-month postpartum weight retention (PPWR) in a large cohort of Vietnamese mothers.MethodsOf the 2030 pregnant women recruited from three cities in Vietnam at 24–28 weeks of gestation, a total of 1666 mothers were followed up for 12 months after delivery and available for analysis. The outcome variable PPWR was determined by subtracting the pre-pregnancy weight from the 12-month postpartum measured weight, while GWG and pre-pregnancy BMI were classified according to the Institute of Medicine and WHO criteria for adults, respectively. Linear regression models were used to ascertain the association between pre-pregnancy BMI, GWG and PPWR accounting for the effects of plausible confounding factors.ResultsBoth pre-pregnancy BMI and GWG were significantly associated with PPWR (P < 0.001). The adjusted mean weight retention in underweight women before pregnancy (3.71 kg, 95% confidence interval (CI) 3.37–4.05) was significantly higher than that in those with normal pre-pregnancy weight (2.34 kg, 95% CI 2.13–2.54). Women with excessive GWG retained significantly more weight (5.07 kg, 95% CI 4.63–5.50) on average at 12 months, when compared to mothers with adequate GWG (2.92 kg, 95% CI 2.67–3.17).ConclusionsBeing underweight before pregnancy and excessive GWG contribute to greater weight retention twelve months after giving birth. Interventions to prevent postpartum maternal obesity should target at risk women at the first antenatal visit and control their weight gain during the course of pregnancy.     

The Influence of Obesity on Nutrition and Physical Activity during COVID-19 Pandemic: A Case-Control Study

Obesity is one of the important risk factors for a severe course of COVID-19. Maintaining a healthy body weight through diet and physical activity is a reasonable approach to preventing a SARS-CoV-2 infection or in alleviating its course. The goal of the study was to determine the influence of obesity on nutrition and physical activity during the COVID-19 pandemic. A total of 964 respondents, including 227 individuals with a body mass index (BMI) ≥30 kg/m² were evaluated in this study. In the case of 482 respondents, including 105 individuals (21.8%) with BMI ≥ 30 kg/m², the data were collected during the pandemic period from 1 June to 31 August 2020. The remaining 482 individuals were the “pre-pandemic” group, selected via propensity score matching (PSM) out of the 723 National Health Program study participants whose data was collected in 2017–2019. The evaluated dietary health factors were quantitatively similar in patients with BMI of either <30 kg/m² or ≥30 kg/m² and showed no significant changes during the pandemic. The diets of those who suffered from obesity prior to the pandemic showed the evaluated unhealthy nutritional factors to be less pronounced in comparison with those of individuals with BMI < 30 kg/m². During the pandemic, the BMI ≥ 30 kg/m² group showed a significant increase in the overall calorie intake (by 319 kcal; p = 0.001) and an increased consumption of total carbohydrates 299.3 ± 83.8 vs. 252.0 ± 101.5; p = 0.000), sucrose (51.7 ± 30.0 vs. 71.6 ± 49.9; p = 0.000), plant protein (26.3 ± 12.1 vs. 29.3 ± 8.3; p = 0.040), total fat (73.1 ± 42.6 vs. 84.9 ± 29.6; p = 0.011) and saturated fatty acids (29.5 ± 16.4 vs. 34.3 ± 13.9; p = 0.014) in comparison with the pre-pandemic period. The energy and nutritional value of the diets of BMI < 30 kg/m² individuals did not change between the pre-pandemic and pandemic period. Before the pandemic, the level of leisure physical activity of the BMI ≥ 30 kg/m² group was significantly lower than of those with BMI < 30 kg/m². Such differences were not observed in the levels of physical activity at work or school. The pandemic did not alter the amount of physical activity either during leisure time or at work/school in individuals with BMI ≥ 30 kg/m². However, respondents without obesity exercised significantly less during the pandemic than before. In conclusion, the pandemic altered the diets and levels of physical activity in the Polish population, with dietary changes observed in individuals with BMI ≥ 30 kg/m² and changes in physical activity observed in those with BMI < 30 kg/m².     

Randomized Clinical Trial to Evaluate the Morphological Changes in the Adventitial Vasa Vasorum Density and Biological Markers of Endothelial Dysfunction in Subjects with Moderate Obesity Undergoing a Very Low-Calorie Ketogenic Diet

Weight loss after bariatric surgery decreases the earlier expansion of the adventitial vasa vasorum (VV), a biomarker of early atheromatous disease. However, no data are available regarding weight loss achieved by very low calorie ketogenic diets (VLCKD) on VV and lipid-based atherogenic indices. A randomized clinical trial was performed to examine changes in adventitial VV density in 20 patients with moderate obesity who underwent a 6-month very low calorie ketogenic diet (VLCKD, 600–800 kcal/day), and 10 participants with hypocaloric diet based on the Mediterranean Diet (MedDiet, estimated reduction of 500 kcal on the usual intake). Contrast-enhanced carotid ultrasound was used to assess the VV. Body composition analysis was also used. The atherogenic index of plasma (log (triglycerides to high-density lipoprotein cholesterol ratio)) and the triglyceride-glucose index were calculated. Serum concentrations of soluble intercellular adhesion molecule 1 (sICAM-1), and soluble vascular cell adhesion molecule 1 (sVCAM-1) were measured. The impact of weight on quality of life-lite (IWQOL-Lite) questionnaire was administered. Participants of intervention groups displayed a similar VV values. Significant improvements of BMI (−5.3 [−6.9 to −3.6] kg/m², p < 0.001), total body fat (−7.0 [−10.7 to −3.3] %, p = 0.003), and IWQOL-Lite score (−41.4 [−75.2 to −7.6], p = 0.027) were observed in VLCKD group in comparison with MedDiet group. Although after a 6-months follow-up period VV density (mean, right and left sides) did not change significantly in any group, participants in the VLCKD exhibited a significantly decrease both in their atherogenic index of plasma and serum concentration of sICAM-1. A 6-month intervention with VLCKD do not impact in the density of the adventitial VV in subjects with moderate obesity, but induces significant changes in markers of endothelial dysfunction and CV risk.     

An Earlier First Meal Timing Associates with Weight Loss Effectiveness in A 12-Week Weight Loss Support Program

Recent studies have reported that meal timing may play an important role in weight regulation, however it is unknown whether the timing of meals is related to the amount of weight loss. This study aimed to examine the relationship between indices of meal timing and weight loss during weight loss intervention in adults. A 12-week weight loss support program was conducted for 97 adults (age: 47.6 ± 8.3 years, BMI: 25.4 ± 3.7 kg/m²). After the program, body weight decreased by −3.0 ± 2.7%. Only the start of the eating window was positively correlated with the weight change rate in both sexes (men: r = 0.321, p = 0.022; women: r = 0.360, p = 0.014). The participants were divided into two groups based on the start of the eating window as follows: the early group (6:48 ± 0:21 AM) and the late group (8:11 ± 1:05 AM). The weight loss rate in the early group was significantly higher (−3.8 ± 2.7%) than that in the late group (−2.2 ± 2.5%). The present results showed that the start of the early eating window was associated with weight loss and suggested paying attention to meal timing when doing weight loss.     

Trajectories of Food Choice Motives and Weight Status of Malaysian Youths during the COVID-19 Pandemic

Stay-at-home orders have abruptly altered food purchasing behaviour, dietary habits, and food choice motives. Therefore, this study aims to investigate the trajectory of food choice motives and their associations with the weight status of Malaysian youths in the time of COVID-19. Socio-demographic information and anthropometric measurements were self-reported by the respondents, while the food choice motives were assessed using a validated 38-item food choice questionnaire (FCQ). Of the 1013 Malaysian youths, 48.6% gained weight due to the confinement, with an average weight gain of 3.90 ± 2.92 kg. On the other hand, 47.0% to 73.0% of the youths changed their food choice motives in the time of COVID-19. Of the 10 motives, convenience (48.5%) had the largest percentage increase, followed by weight control (47.0%) and health (45.3%). Moreover, the mean scores of health (t = −3.324, p = 0.001), convenience (t = −5.869, p < 0.001), weight control (t = −7.532, p < 0.001), natural content (t = −5.957, p < 0.001), ethical concern (t = −4.419, p < 0.001) and price (t = −3.737, p < 0.001) were significantly higher during the pandemic compared to pre-pandemic. Findings from the multinomial regression model revealed that youths highly concerned for weight control were more likely to be in the weight loss category (Adjusted odds ratio (AOR) = 1.633, Confidence Interval (CI) = 1.230–2.168, p = 0.001). Conversely, those who gained weight due to the pandemic confinement highly valued natural content in foods (AOR = 0.653, CI = 0.481–0.886, p = 0.006) when making their food choices in this unprecedented pandemic. In conclusion, Malaysian youths made healthier food choices to mitigate the risk of COVID-19 infection.     

Association between Single Nucleotide Polymorphisms and Weight Reduction in Behavioural Interventions—A Pooled Analysis

Knowledge of the association between single nucleotide polymorphisms (SNPs) and weight loss is limited. The aim was to analyse whether selected obesity-associated SNPs within the fat mass and obesity-associated (FTO), transmembrane protein 18 (TMEM18), melanocortin-4 receptor (MC4R), SEC16 homolog B (SEC16B), and brain-derived neurotrophic factor (BDNF) gene are associated with anthropometric changes during behavioural intervention for weight loss. genetic and anthropometric data from 576 individuals with overweight and obesity from four lifestyle interventions were obtained. A genetic predisposition score (GPS) was calculated. Our results show that study participants had a mean age of 48.2 ± 12.6 years and a mean baseline body mass index of 33.9 ± 6.4 kg/m². Mean weight reduction after 12 months was −7.7 ± 10.9 kg. After 12 months of intervention, the MC4R SNPs rs571312 and rs17782313 were significantly associated with a greater decrease in body weight and BMI (p = 0.012, p = 0.011, respectively). The investigated SNPs within the other four genetic loci showed no statistically significant association with changes in anthropometric parameters. The GPS showed no statistically significant association with weight reduction. In conclusion there was no consistent evidence for statistically significant associations of SNPs with anthropometric changes during a behavioural intervention. It seems that other factors play a more significant in weight management than the investigated SNPs.     

Impact of COVID-19 Pandemic on Weight and BMI among UK Adults: A Longitudinal Analysis of Data from the HEBECO Study

COVID-19-related restrictions impacted weight and weight-related factors during the initial months of the pandemic. However, longitudinal analyses are scarce. An online, longitudinal study was conducted among self-selected UK adults (n = 1818), involving three surveys (May–June, August–September, November–December 2020), covering anthropometric, sociodemographic, COVID-19-related and behavioural measures. Data were analysed using generalised estimating equations. Self-reported average weight/body mass index (BMI) significantly increased between the May–June period and the August–September period (74.95 to 75.33 kg/26.22 kg/m² to 26.36kg/m², p < 0.001, respectively), and then significantly decreased to November–December (to 75.06 kg/26.27 kg/m², p < 0.01), comparable to May–June levels (p = 0.274/0.204). However, there was great interindividual variation, 37.0%/26.7% increased (average 3.64 kg (95% confidence interval: 3.32, 3.97)/1.64 kg/m² (1.49, 1.79)), and 34.5%/26.3% decreased (average 3.59 kg (3.34, 3.85)/1.53 kg/m² (1.42, 1.63)) weight/BMI between May–June and November–December. Weight/BMI increase was significantly negatively associated with initial BMI, and positively associated with monthly high fat, salt and sugar (HFSS) snacks intake and alcohol consumption, and for BMI only, older age. Associations were time-varying; lower initial BMI, higher HFSS snacks intake and high-risk alcohol consumption were associated with maintaining weight/BMI increases between August–September and November–December. The average weight/BMI of UK adults fluctuated between May–June and November–December 2020. However, the substantial interindividual variation in weight/BMI trajectories indicates long-term health impacts from the pandemic, associated with food and alcohol consumption.     

The Effect of Obesity Class on the Energetics and Mechanics of Walking

Higher mass-normalized net energy cost of walking (NetC_w/kg) and mechanical pendular recovery are observed in obese compared to lean adults. This study aimed to investigate the effect of different classes of obesity on the energetics and mechanics of walking and to explore the relationships between body mass, NetC_w/kg and gait mechanics by using principal component analysis (PCA). NetC_w/kg and gait mechanics were computed in severely obese (SOG; n = 18, BMI = 40.1 ± 4.4 kg·m⁻²), moderately obese (MOG; n = 17, BMI = 32.2 ± 1.5 kg·m⁻²) and normal-weight (NWG; n = 13, BMI = 22.0 ± 1.5 kg·m⁻²) adults during five walking trials (0.56, 0.83, 1.11, 1.39, 1.67 m·s⁻¹) on an instrumented treadmill. NetC_w/kg was significantly higher in SOG compared to NWG (p = 0.019), with no significant difference between SOG and MOG (p = 0.14), nor between MOG and NWG (p = 0.27). Recovery was significantly higher in SOG than in NWG (p = 0.028), with no significant difference between SOG and MOG (p = 0.13), nor between MOG and NWG (p = 0.35). PCA models explained between 17.0% and 44.2% of the data variance. This study showed that: (1) obesity class influences the gait energetics and mechanics; (2) PCA was able to identify two components, showing that the obesity class is associated with lower walking efficiency and better pendulum-like characteristics.