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As the country has loosened its family planning policy and living standards have improved, postnatal obesity has become a social problem seriously threatening public health in China, which has attracted widespread attention from all walks of life. Therefore, a method for improving postpartum obesity urgently needs to be explored. Intestinal microecology is critical to the health of mothers and children, and plays an important role in the occurrence and development of obesity. Improving intestinal microecology as an effective way to improve obesity has attracted more and more attention. This article focuses on the relationship between postnatal obesity and intestinal microecology and summarizes the mechanisms of action of probiotics and prebiotics in regulating intestinal microecology to suppress postpartum obesity. The purpose of this article is to provide a theoretical basis for probiotic-prebiotic intervention based on intestinal microecology to suppress postpartum obesity.

Excessive postpartum weight retention puts women at risk for health problems. This study aimed to investigate the effects of dairy foods on weight retention and risk of obesity in postpartum women in the Nurses' Health Study II. Weight was reported every 2 years. We identified the pre-pregnancy and postpartum exams that were approximately 2 years before and after the birth year. Dairy consumption was averaged during these 4 years. Linear models were used to assess postpartum weight retention. Multivariable models were used to estimate risk of obesity. Women with higher yogurt (≥2 servings/week vs. <1 serving/month) intakes had 0.61 pounds less postpartum weight retention. Consuming ≥ 5 cheese servings/week was associated with 0.63 pounds less weight retention than the lowest intake. Among sedentary women, only yogurt intake was associated with lower risk of postpartum obesity (RR: 0.84; 95% CI: 0.71–1.00), though of borderline statistical significance. Among women with less healthy diets, yogurt consumption was also associated with lower postpartum obesity risk (RR: 0.70; 95% CI: 0.57–0.85). In sum, higher yogurt and cheese intakes were associated with less postpartum weight retention and among higher risk women (sedentary or lower diet quality) greater yogurt intake was associated with lower risks of postpartum obesity. [ABSTRACT FROM AUTHOR]

Excessive postpartum weight retention puts women at risk for health problems. This study aimed to investigate the effects of dairy foods on weight retention and risk of obesity in postpartum women in the Nurses’ Health Study II. Weight was reported every 2 years. We identified the pre-pregnancy and postpartum exams that were approximately 2 years before and after the birth year. Dairy consumption was averaged during these 4 years. Linear models were used to assess postpartum weight retention. Multivariable models were used to estimate risk of obesity. Women with higher yogurt (≥2 servings/week vs.

This study aims to prevent maternal social isolation by analyzing the causes of postpartum obesity and postpartum depression and stress in Korea. Gneral characteristics of mothers as a result of the study: 91.1% (102 people) answered that they had social experience, and only 8% (9 people) answered that they had no social experience. In the question of whether to return to society, 17.9% responded that they have already returned, 54.5% did not, and 18.8% were on maternity leave. As a result of examining the level of BMI increase among mothers through chi-square test of BMI changes before and after childbirth and general characteristics, 55% experienced below-average BMI increase; 45% experienced above-average BMI increase. Those in their 30s accounted for 40.2%, and those in their 40s accounted for 57.1%. Postpartum obesity and maternal psychological status (t-test): Mothers with postpartum obesity were more hypersensitive (t = -1.997, p = 0.048) and more prone to suffer from hard breathing (t = -1.930, p = 0.056), emptiness (t = -2.673, p = 0.010), and body numbness (t = -2.315, p = 0.024) than mothers who are not suffering from not postpartum obesity. Per the results of postpartum BMI increase and maternal psychological state (t-test) analysis, mothers with an average increase in postpartum BMI were more depressed than mothers who did not. Research Results - Postpartum obesity due to pregnancy and childbirth has been identified as an important individual cause affecting mental and physical problems after childbirth. In conclusion, I also think that the government should support the management of maternal obesity and the elimination of depression through the results of this study. [ABSTRACT FROM AUTHOR]

Background: Pregnancy has become the main constituent for women to become overweight or obese during the postpartum phase. This could lead women to suffer from postpartum depression as well. Information technology (IT) has become more prevalent in the healthcare industry. It offers patients the opportunity to manage their health conditions via the use of several applications, one being the mHealth applications. Objective: The main purpose of this study is to experiment and understand the effects the mHealth applications (i.e., fitness and nutrition applications) have on the body mass index (BMI) and depression levels amongst postpartum women. Methods: Online questionnaires were sent to postpartum women within one year after their pregnancy, of which 819 completed questionnaires were returned. The frequency of the mHealth applications usage was categorized into daily, weekly, rarely and never streams. Therefore, the frequency of use of the mHealth applications for BMI and depression levels was analyzed based on the available statistical data. Descriptive statistics, ANOVA, and Dunnet tests were applied to analyze the experimental data. Results: Out of 819 respondents, 37.9% and 42.1% of them were overweight and obese, respectively. Almost 32.9% of the respondents were likely depressed, and 45.6% were at an increased risk. This study reports that only 23.4% and 28.6% of respondents never used the fitness and nutrition applications. The impact of the frequency of using the fitness applications on BMI and depression levels was obvious. This means that with the increased use of the fitness applications, there was also a significant effect in maintaining and decreasing the BMI and depression levels amongst Malaysians postpartum women. However, from the data of weekly and daily use of fitness applications, we found that the contribution toward the BMI and depression levels was high (p = 0.000). However, nutrition applications amongst the users were not significant within the main variables (p > 0.05). From the Dunnet test, the significance of using the fitness applications within the depression levels started from daily usage, whereas for BMI, it started from weekly usage. Conclusion: The efficiency of the fitness applications toward the BMI and depression levels has been proven in this research work. While nutrition applications did not affect the BMI and depression levels, some of the respondents were still categorized as weekly and daily users. Thus, the improvements in BMI and depression levels are associated with the types of mHealth app that had been used.

Objective: Postpartum obesity leads to long-term maternal obesity and promotes drastic health complications. Low glycemic index diet is suggested to have a beneficial impact on blood lipid levels. Therefore, we conducted a study to explore the effect of low glycemic diet on blood lipid profile in obese postpartum women. Methods: In a randomised controlled trial, 38 obese postpartum women in intervention and 36 obese postpartum women in control group were analysed. Subjects in the intervention group were assigned low glycemic index diet and to follow this protocol for 12 weeks and the control group was advised to continue their routine diet. Results: Low glycemic diet had a positive impact on low density lipoprotein (LDL), triglyceride and high density lipoprotein (HDL) concentration (p < 0.05). A strong positive correlation was observed between the glycemic index and LDL (mg/dl), (r = 0.57; p = 0.02) and between glycemic index and triglyceride (mg/dl), (r = 0.51; p = 0.01) in control and intervention group. A negative correlation was identified between glycemic index and HDL (mg/dl), (r = -0.45; p = 0.01). Conclusion: Study concluded that low glycemic index diet reduced low density lipoprotein and triglyceride level and increased HDL level in blood; further more a significant association was found between glycemic index and blood lipids profile. [ABSTRACT FROM AUTHOR]

Vitamin consumption prior to and during pregnancy has increased as a result of proactive recommendations by health professionals, wide availability of vitamin supplements, and liberal food-fortification policies. Folic acid, alone or in combination with other B vitamins, is the most recommended vitamin consumed during pregnancy because deficiency of this vitamin leads to birth defects in the infant. Folic acid and other B vitamins are also integral components of biochemical processes that are essential to the development of regulatory systems that control the ability of the offspring to adapt to the external environment. Although few human studies have investigated the lasting effects of high vitamin intakes during pregnancy, animal models have shown that excess vitamin supplementation during gestation is associated with negative metabolic effects in both the mothers and their offspring. This research from animal models, combined with the recognition that epigenetic regulation of gene expression is plastic, provides evidence for further examination of these relationships in the later life of pregnant women and their children. [ABSTRACT FROM AUTHOR]

Excessive postpartum weight retention puts women at risk for health problems. This study aimed to investigate the effects of dairy foods on weight retention and risk of obesity in postpartum women in the Nurses’ Health Study II. Weight was reported every 2 years. We identified the pre-pregnancy and postpartum exams that were approximately 2 years before and after the birth year. Dairy consumption was averaged during these 4 years. Linear models were used to assess postpartum weight retention. Multivariable models were used to estimate risk of obesity. Women with higher yogurt (≥2 servings/week vs. <1 serving/month) intakes had 0.61 pounds less postpartum weight retention. Consuming ≥ 5 cheese servings/week was associated with 0.63 pounds less weight retention than the lowest intake. Among sedentary women, only yogurt intake was associated with lower risk of postpartum obesity (RR: 0.84; 95% CI: 0.71−1.00), though of borderline statistical significance. Among women with less healthy diets, yogurt consumption was also associated with lower postpartum obesity risk (RR: 0.70; 95% CI: 0.57−0.85). In sum, higher yogurt and cheese intakes were associated with less postpartum weight retention and among higher risk women (sedentary or lower diet quality) greater yogurt intake was associated with lower risks of postpartum obesity.

To evaluate: change in Body Mass Index (BMI) of adolescent mothers (14–19 years of age) from pre-pregnancy to 36 months postpartum; BMI of their children age 2 or older; relationship between maternal BMI and children’s BMI. Retrospective medical record abstraction of adolescent mothers attending a medical program in Massachusetts between 2001 and 2005 who had self-reported pre-pregnancy BMI data at first prenatal visit, at least one BMI measure 12 or more months postpartum, and who did not experience a repeat pregnancy ( n = 52). Children of adolescent mothers were included if they had received their 2 ( n = 41) and/or 3 ( n = 28) year physical. Adolescent mothers: overweight increased from 25% pre-pregnancy to 33% at 24–36 months postpartum; obesity more than doubled in the same time period, from 15% to 36%. Those with BMI data available pre-pregnancy and postpartum had an increase in mean BMI from 25 pre-pregnancy to 29 at 24–36 months postpartum ( P < 0.001). Two-year-old children: About 5% were at risk for overweight and 12% were overweight. Three-year-old children: About 18% were at risk for overweight and 18% were overweight. When BMI categories of children were compared to BMI categories of their mothers, there was a trend for adolescent mothers with overweight/obesity at 24–36 months postpartum to have 3-year-old children at risk for overweight or overweight ( P = 0.092). There was a significant increase in overweight/obesity in this cohort of adolescent mothers and their children followed 36 months postpartum. The long-term sequelae of overweight/obesity indicates a need for effective interventions. [ABSTRACT FROM AUTHOR]

This narrative review is intended to present an evidence and opinion-based weight management module for Indian postpartum women to be used by clinicians. Electronic databases such as PubMed and Google Scholar were accessed to extract relevant studies to derive evidence-based information. The reference list of the extracted studies was also checked to obtain further relevant articles. The opinion-based information was achieved from the consensus among the gynaecologists, nutritionists and doctors from Medicine according to their practical experiences in real time. In this review, we have used the term "postpartum" to represent the time period of two years after delivery. A postpartum weight management module consisting of information about diet, physical activity, sleep and breastfeeding was devised to be used in regular clinical practice, particularly in the Indian settings. Postpartum women deal with various unique challenges as compared to other population groups. Individualised weight management strategies should be adopted to facilitate sustainable postpartum weight management. • Postpartum obesity is a significant public health challenge worldwide and in India. • Socio-demographic, obstetric and behavioural predictors are related to postpartum weight changes. • Successful management strategies addressing postpartum obesity are needed to target healthy weight loss. [ABSTRACT FROM AUTHOR]

This study selected Google and Naver, the most recognizable Internet portals in Korea, as subjects for analysis. "Postpartum obesity" and "postpartum depression" were used as keywords for data collection. This study aimed to provide basic data for solving maternal problems using big data. Keywords related to postpartum obesity were collected from the portal site Google from 1 January 2019 to 31 December 2019. The collected data were analyzed through simple frequency analysis, N-gram analysis, and keyword network. This study can be used as basic data for postpartum obesity-related programs or academic research. It is also expected to be used for research on the development of a mobile-based customized healthcare system focused on maternal health. Previous papers and data are still insufficient at solving the physical and mental problems related to postpartum obesity and depression. It is necessary to find ways to continuously integrate and collect data from mothers across the country.

Background: Pregnancy has become the main constituent for women to become overweight or obese during the postpartum phase. This could lead women to suffer from postpartum depression as well. Information technology (IT) has become more prevalent in the healthcare industry. It offers patients the opportunity to manage their health conditions via the use of several applications, one being the mHealth applications. Objective: The main purpose of this study is to experiment and understand the effects the mHealth applications (i.e., fitness and nutrition applications) have on the body mass index (BMI) and depression levels amongst postpartum women. Methods: Online questionnaires were sent to postpartum women within one year after their pregnancy, of which 819 completed questionnaires were returned. The frequency of the mHealth applications usage was categorized into daily, weekly, rarely and never streams. Therefore, the frequency of use of the mHealth applications for BMI and depression levels was analyzed based on the available statistical data. Descriptive statistics, ANOVA, and Dunnet tests were applied to analyze the experimental data. Results: Out of 819 respondents, 37.9% and 42.1% of them were overweight and obese, respectively. Almost 32.9% of the respondents were likely depressed, and 45.6% were at an increased risk. This study reports that only 23.4% and 28.6% of respondents never used the fitness and nutrition applications. The impact of the frequency of using the fitness applications on BMI and depression levels was obvious. This means that with the increased use of the fitness applications, there was also a significant effect in maintaining and decreasing the BMI and depression levels amongst Malaysians postpartum women. However, from the data of weekly and daily use of fitness applications, we found that the contribution toward the BMI and depression levels was high (p = 0.000). However, nutrition applications amongst the users were not significant within the main variables (p > 0.05). From the Dunnet test, the significance of using the fitness applications within the depression levels started from daily usage, whereas for BMI, it started from weekly usage. Conclusion: The efficiency of the fitness applications toward the BMI and depression levels has been proven in this research work. While nutrition applications did not affect the BMI and depression levels, some of the respondents were still categorized as weekly and daily users. Thus, the improvements in BMI and depression levels are associated with the types of mHealth app that had been used. [ABSTRACT FROM AUTHOR]

As postpartum obesity is becoming a global public health challenge, there is a need to apply postpartum obesity modeling to determine the indicators of postpartum obesity using an appropriate statistical technique. This research comprised two phases, namely: (i) development of a previously created postpartum obesity modeling; (ii) construction of a statistical comparison model and introduction of a better estimator for the research framework. The research model displayed the associations and interactions between the variables that were analyzed using the Structural Equation Modeling (SEM) method to determine the body mass index (BMI) levels related to postpartum obesity. The most significant correlations obtained were between BMI and other substantial variables in the SEM analysis. The research framework included two categories of data related to postpartum women: living in urban and rural areas in Iran. The SEM output with the Bayesian estimator was 81.1%, with variations in the postpartum women's BMI, which is related to their demographics, lifestyle, food intake, and mental health. Meanwhile, the variation based on SEM with partial least squares estimator was equal to 70.2%, and SEM with a maximum likelihood estimator was equal to 76.8%. On the other hand, the output of the root mean square error (RMSE), mean absolute error (MSE) and mean absolute percentage error (MPE) for the Bayesian estimator is lower than the maximum likelihood and partial least square estimators. Thus, the predicted values of the SEM with Bayesian estimator are closer to the observed value compared to maximum likelihood and partial least square. In conclusion, the higher values of R-square and lower values of MPE, RMSE, and MSE will produce better goodness of fit for SEM with Bayesian estimators.