Background: Traditional health management requires many human and material resources and cannot meet the growing needs. Remote medical technology provides an opportunity for health management; however, the research on it is insufficient. Objective: The objective of this study was to assess the effects of remote interventions on weight management. Methods: In this randomized controlled study, 750 participants were randomly assigned to a remote dietary and physical activity intervention group (group DPI), remote physical activity intervention group (group PI), or control group (group C). At baseline (time 1), day 45 (time 2), and day 90 (time 3), data were collected, including data on dietary intake, physical activity, indexes related to weight control, and health benefits. Results: A total of 85.6% (642/750) of participants completed the follow-up. Compared with group C, group DPI showed a significant decrease in energy intake (−581 vs −82 kcal; P<.05), protein intake (−17 vs −3 g; P<.05), fat intake (−8 vs 3 g; P<.05), and carbohydrate intake (−106.5 vs −4.7 g; P<.05) at time 3. Compared with time 1, groups DPI and PI showed a significant decrease in cereal and potato intake (P<.05). Compared with time 1, the physical activity levels related to transportation (group PI: 693 vs 597 metabolic equivalent [MET]–min/week, group C: 693 vs 594 MET-min/week; P<.05) and housework and gardening (group PI: 11 vs 0 MET-min/week, group C: 11 vs 4 MET-min/week; P<.05) in groups PI and C were improved at time 3. Compared with groups PI and C, group DPI showed a significant decrease in weight (−1.56 vs −0.86 kg and −1.56 vs −0.66 kg, respectively; P<.05) and BMI (−0.61 vs −0.33 kg/m2 and −0.61 vs −0.27 kg/m2, respectively; P<.05) at time 2. Compared with groups PI and C, group DPI showed a significant decrease in body weight (−4.11 vs −1.01 kg and −4.11 vs −0.83 kg, respectively; P<.05) and BMI (−1.61 vs −0.40 kg/m2 and −1.61 vs −0.33 kg/m2, respectively; P<.05) at time 3. Compared with group C, group DPI showed a significant decrease in triglyceride (−0.06 vs 0.32 mmol/L; P<.05) at time 2. Compared with groups PI and C, group DPI showed a significant decrease in systolic blood pressure (−8.15 vs −3.04 mmHg and −8.15 vs −3.80 mmHg, respectively; P<.05), triglyceride (−0.48 vs 0.11 mmol/L and −0.48 vs 0.18 mmol/L, respectively; P<.05), and fasting blood glucose (−0.77 vs 0.43 mmol/L and −0.77 vs 0.14 mmol/L, respectively; P<.05). There were significant differences in high-density lipoprotein cholesterol (−0.00 vs −0.07 mmol/L; P<.05) and hemoglobin A1c (−0.19% vs −0.07%; P<.05) between groups DPI and C. Conclusions: Remote dietary and physical activity interventions can improve dietary intake among participants with overweight and obesity, are beneficial for weight control, and have potential health benefits. Trial Registration: Chinese Clinical Trial Registry ChiCTR1900023355; https://www.chictr.org.cn/showproj.html?proj=38976

Background and Objective: Overweight or obesity, as an independent risk factor for chronic diseases, has been on the rise globally. Adopting a healthy lifestyle is positive to weight control. Mobile-based lifestyle interventions have shown potential benefits in weight loss, but most studies were carried out among non-elderly population, so it is necessary to perform well-designed randomized controlled trials among the elderly with overweight or obesity. The purpose of this study is to assess the effect of mobile-based lifestyle intervention on weight loss among the overweight and obese elderly population in China. Methods: This is a prospective, open-labeled, three-month, multicenter, randomized controlled trial involving 750 participants from five cities who were randomly assigned to dietary and physical activity interventions group (DPG; mobile phone with the App and bracelet), physical activity interventions group (PG; mobile phone with the App and bracelet) and control group (CG; no interventions and kept their lifestyle as before). The outcomes evaluated were changes in weight, body mass index (BMI), waist circumference (WC), and hip circumference (HC). Results: In total, 642 (85.6%) participants completed the study, 237 (94.8%), 203 (81.2%), and 202 (80.8%) for DPG, PG, and CG respectively. Comparing with PG and CG, the DPG showed a significant decrease in all outcomes after three months, including body weight (−4.1 kg vs. −1.0 kg; −4.1 kg vs. −0.8 kg; p < 0.05), BMI (−1.6 kg/m² vs. −0.4 kg/m²; −1.6 kg/m² vs. −0.3 kg/m²; p < 0.05), WC (−2.8 cm vs. −0.1 cm; −2.8 cm vs. −0.5 cm; p < 0.05), and HC (−3.8 cm vs. −1.3 cm; −3.8 cm vs. −1.3 cm; p < 0.05). Similar effects were seen across sex and BMI subgroups. Conclusions: Mobile-based lifestyle intervention obtained beneficial effect in weight loss among the elderly with overweight or obesity. Nevertheless, further studies are needed to confirm the effectiveness and its sustainability.

Negative emotions and gut microbiota during pregnancy both bear significant public health implications. However, the relationship between them has not been fully elucidated. This study, utilizing data from a pregnancy cohort, employed metagenomic sequencing to elucidate the relationship between anxiety, depression, and gut microbiota’s diversity, composition, species, and functional pathways. Data from 87 subjects, spanning 225 time points across early, mid, and late pregnancy, were analyzed. The results revealed that anxiety and depression significantly corresponded to lower alpha diversity (including the Shannon entropy and the Simpson index). Anxiety and depression scores, along with categorical distinctions of anxiety/non-anxiety and depression/non-depression, were found to account for 0.723%, 0.731%, 0.651%, and 0.810% of the variance in gut-microbiota composition (p = 0.001), respectively. Increased anxiety was significantly positively associated with the abundance of Oscillibacter sp. KLE 1745, Oscillibacter sp. PEA192, Oscillibacter sp. KLE 1728, Oscillospiraceae bacterium VE202 24, and Treponema socranskii. A similar association was significantly noted for Oscillibacter sp. KLE 1745 with elevated depression scores. While EC.3.5.3.1: arginase appeared to be higher in the anxious group than in the non-anxious group, vitamin B12-related enzymes appeared to be lower in the depression group than in the non-depression group. The changes were found to be not statistically significant after post-multiple comparison adjustment.

Objective: To investigate the association between the neighborhood food environment and body mass index (BMI) among Chinese older adults. Methods: A multi-stage stratified random sampling method was used to recruit participants from 12 communities in Beijing, China, in 2019. Participants (n = 1764, 1034 women) in this study were older adults aged 65 to 80. We collected the participants’ basic information, measured their height and weight, and calculated their BMI. Neighborhood food environments were measured by the density of and proximity to different food outlets using the Baidu Map Application Programming Interface. Adjusted multiple linear regression was performed to estimate the association between the food environment and BMI. Results: Participants had a mean age of 69.7 ± 4.32 years old and an average BMI of 26.3 ± 3.50 kg/m². Among the three types of stores, convenience stores had the easiest access, followed by greengrocers and supermarkets. Sit-down restaurants had the best access among different restaurants, followed by Chinese fast-food restaurants, and western fast-food restaurants had the worst access. Easier access to greengrocers (β = 0.281, p < 0.001) and sit-down restaurants (β = 0.304, p < 0.001) was associated with higher BMI in the 250 m buffer zone. More supermarkets were associated with higher BMI in the 500 m buffer zone (β = 0.593, p < 0.001). Access to convenience stores was positively associated with BMI in the 800 m buffer zone (β = 0.057, p < 0.001). Better access to Chinese fast-food restaurants was associated with higher BMI (β = 0.071, p = 0.001), and better access to western fast- food restaurants was associated with lower BMI (β = −0.400, p < 0.001) in the 1000 m buffer zone. There was a negative association between the nearest distance to greengrocers and BMI (β = −0.004, p < 0.001). Conclusion: Although we found some significant associations between the neighborhood food environment and obesity, the current results are not strong enough to draw specific conclusions. Policymakers will need to rely on more evidence to derive concrete policy recommendations.

Background: Promotion of a healthy lifestyle is considered a good strategy for dealing with chronic diseases. Mobile-based lifestyle interventions have shown beneficial effects in the control and treatment of chronic diseases such as diabetes, obesity and metabolic syndrome. Current clinical trials for mobile-based lifestyle intervention were mainly conducted among non-elderly populations, thus well-designed trials performed among the elderly who are more susceptible to chronic diseases are needed. The study aims to assess the effect of the mobile-based lifestyle intervention on the improvement of body weight, glucose and lipid metabolism among overweight and obese elderly adults in China. Materials and Methods: Participants aged 60–80 years who are overweight or obese will be randomly assigned to receive mobile-based nutrition and exercise intervention, mobile-based exercise intervention and no intervention for 3 months. Before the intervention, participants will receive the training of the mobile application and sports bracelet. The primary outcome will be the between-group (three groups) difference in body mass index at the end of intervention. The secondary outcomes will include body composition, parameters of glucose and lipid metabolism, blood pressure, dietary data and physical activity data. All these outcomes will be assessed at baseline, day 45 and day 90. Ethics and dissemination: The trial has been approved by the Ethics Committee of Peking University Health Science Center (IRB00001052-18039).

BACKGROUND Traditional health management requires many human and material resources and cannot meet the growing needs. Remote medical technology provides an opportunity for health management; however, the research on it is insufficient. OBJECTIVE The objective of this study was to assess the effects of remote interventions on weight management. METHODS In this randomized controlled study, 750 participants were randomly assigned to a remote dietary and physical activity intervention group (group DPI), remote physical activity intervention group (group PI), or control group (group C). At baseline (time 1), day 45 (time 2), and day 90 (time 3), data were collected, including data on dietary intake, physical activity, indexes related to weight control, and health benefits. RESULTS A total of 85.6% (642/750) of participants completed the follow-up. Compared with group C, group DPI showed a significant decrease in energy intake (−581 vs −82 kcal; P<.05), protein intake (−17 vs −3 g; P<.05), fat intake (−8 vs 3 g; P<.05), and carbohydrate intake (−106.5 vs −4.7 g; P<.05) at time 3. Compared with time 1, groups DPI and PI showed a significant decrease in cereal and potato intake (P<.05). Compared with time 1, the physical activity levels related to transportation (group PI: 693 vs 597 metabolic equivalent [MET]–min/week, group C: 693 vs 594 MET-min/week; P<.05) and housework and gardening (group PI: 11 vs 0 MET-min/week, group C: 11 vs 4 MET-min/week; P<.05) in groups PI and C were improved at time 3. Compared with groups PI and C, group DPI showed a significant decrease in weight (−1.56 vs −0.86 kg and −1.56 vs −0.66 kg, respectively; P<.05) and BMI (−0.61 vs −0.33 kg/m2 and −0.61 vs −0.27 kg/m2, respectively; P<.05) at time 2. Compared with groups PI and C, group DPI showed a significant decrease in body weight (−4.11 vs −1.01 kg and −4.11 vs −0.83 kg, respectively; P<.05) and BMI (−1.61 vs −0.40 kg/m2 and −1.61 vs −0.33 kg/m2, respectively; P<.05) at time 3. Compared with group C, group DPI showed a significant decrease in triglyceride (−0.06 vs 0.32 mmol/L; P<.05) at time 2. Compared with groups PI and C, group DPI showed a significant decrease in systolic blood pressure (−8.15 vs −3.04 mmHg and −8.15 vs −3.80 mmHg, respectively; P<.05), triglyceride (−0.48 vs 0.11 mmol/L and −0.48 vs 0.18 mmol/L, respectively; P<.05), and fasting blood glucose (−0.77 vs 0.43 mmol/L and −0.77 vs 0.14 mmol/L, respectively; P<.05). There were significant differences in high-density lipoprotein cholesterol (−0.00 vs −0.07 mmol/L; P<.05) and hemoglobin A1c (−0.19% vs −0.07%; P<.05) between groups DPI and C. CONCLUSIONS Remote dietary and physical activity interventions can improve dietary intake among participants with overweight and obesity, are beneficial for weight control, and have potential health benefits. CLINICALTRIAL Chinese Clinical Trial Registry ChiCTR1900023355; https://www.chictr.org.cn/showproj.html?proj=38976