Nutrition and weight gain during pregnancy can influence the life-course health of offspring. Clinical practice guidelines play an important role in ensuring appropriate nutrition and weight gain among pregnant women. This study aims to identify clinical practice guidelines on gestational weight gain and/or maternal nutrition across the Asia-Pacific region and to determine the quality of the guidelines and variability in the recommendations. Through a systematic search of grey literature from 38 Asia-Pacific countries, 23 published guidelines were obtained. Of these, 10 eligible clinical practice guidelines reporting nutrition- or/and weight-related recommendations for pregnant women were selected and reviewed. Guideline quality was determined using the Assessment of Guidelines for Research Evaluation II (AGREE II) instrument. Of the 10 guidelines, 90% were classified as low-quality in the AGREE II appraisal. Several variations were found with respect to recommendations on gestational weight gain, including those specific to Asian populations. The recommendations on dietary advice, additional energy intake, and nutritional supplementation during pregnancy were varied. Clinical practice guidelines on weight gain and nutrition in pregnancy across the Asia-Pacific region are generally of poor quality, reflecting significant variation, and need to be improved to ensure pregnant women receive appropriate advice. (PROSPERO registration no. CRD42021291395).

Herein, an algorithm that can be used in wearable health monitoring devices to estimate metabolic equivalents (METs) based on physical activity intensity data, particularly for certain activities in daily life that make MET estimation difficult. Energy expenditure data were obtained from 42 volunteers using indirect calorimetry, triaxial accelerations and heart rates. The proposed algorithm used the percentage of heart rate reserve (%HRR) and the acceleration signal from the wearable device to divide the data into a middle-intensity group and a high-intensity group (HIG). The two groups were defined in terms of estimated METs. Evaluation results revealed that the classification accuracy for both groups was higher than 91%. To further facilitate MET estimation, five multiple-regression models using different features were evaluated via leave-one-out cross-validation. Using this approach, all models showed significant improvements in mean absolute percentage error (MAPE) of METs in the HIG, which included stair ascent, and the maximum reduction in MAPE for HIG was 24% compared to the previous model (HJA-750), which demonstrated a 70.7% improvement ratio. The most suitable model for our purpose that utilized heart rate and filtered synthetic acceleration was selected and its estimation error trend was confirmed. For HIG, the MAPE recalculated by the most suitable model was 10.5%. The improvement ratio was 71.6% as compared to the previous model (HJA-750C). This result was almost identical to that obtained from leave-one-out cross-validation. This proposed algorithm revealed an improvement in estimation accuracy for activities in daily life; in particular, the results included estimated values associated with stair ascent, which has been a difficult activity to evaluate so far.

Even when meeting guidelines for physical activity (PA), considerable sedentary time may be included. This study in primary school children investigated the relationships between objectively evaluated sedentary and PA times at different intensities using triaxial accelerometry that discriminated between ambulatory and non-ambulatory PA. The relationships between subjectively evaluated screen time (i.e. time spent viewing television and videos, playing electronic games, and using personal computers) and objectively evaluated sedentary and PA times were examined. Objectively evaluated sedentary and PA times were assessed for 7 consecutive days using a triaxial accelerometer (Active style Pro: HJA-350IT) in 426 first to sixth grade girls and boys. Metabolic equivalents [METs] were used to categorize the minutes of sedentary time (≤1.5 METs), light PA (LPA, 1.6–2.9 METs), moderate-to-vigorous PA (MVPA, ≥3.0 METs) and vigorous PA (VPA, ≥6.0 METs). The physical activity level (PAL) was calculated using the mean MET value. Subjectively evaluated screen time behaviors were self-reported by participants and parents acting together. The associations between PA and sedentary and screen time variables were examined using partial correlation analyses. After adjustment for age, body weight and wearing time, objectively evaluated sedentary time correlated strongly with non-ambulatory and total LPA and PAL, moderately with ambulatory LPA, non-ambulatory or total MVPA, and weakly with ambulatory MVPA, ambulatory, non-ambulatory or total VPA. Subjectively evaluated screen time was not associated significantly with objectively evaluated sedentary and PA times or PAL. On average, each reduction of 30 min in daily sedentary time was associated with 6 or 23 min more of MVPA or LPA, respectively. These findings show that higher daily sedentary time may be compensated mainly by lower LPA, while the association between sedentary time and MVPA was moderate. Therefore, improving MVPA and reducing sedentary time are important in primary school children.

The maternal diet can potentially influence the life-course health of the child. A poor-quality maternal diet creates nutrient deficiencies and affects immune–metabolic regulation during pregnancy. The nutrient-based overall dietary quality can be assessed using the Nutrient-Rich Food Index 9.3 (NRF9.3), which measures adherence to the national reference daily values of nutrient intake. Pro- and anti-inflammatory nutrient intake can be assessed using the energy-adjusted dietary inflammatory index (E-DII), a comprehensive index of diet-derived inflammatory capacity. Using these indices, we assessed the overall dietary quality and inflammatory potential of pregnant women during mid-gestation in an urban area of Japan (n = 108) and found that there was a strong inverse correlation between the NRF9.3 and E-DII scores. Comparison of the scores among the tertiles of NRF9.3 or E-DII indicated that dietary fiber, vitamin C, vitamin A, and magnesium mainly contributed to the variability of both indices. Intake of vegetables and fruits was positively associated with high NRF9.3 scores and negatively associated with high E-DII scores, after adjustment for maternal age, pre-pregnancy body mass index, and educational level. Consistent with the previous studies that used dietary pattern analysis, this study also demonstrated that vegetables and fruits were the food groups chiefly associated with high dietary quality and low inflammatory potential among pregnant Japanese women.

Background: Heart rate (HR) during physical activity is strongly affected by the level of physical fitness. Therefore, to assess the effects of fitness, we developed predictive equations to estimate the metabolic equivalent (MET) of daily activities, which includes low intensity activities, by % HR reserve (%HRR), resting HR, and multiple physical characteristics. Methods: Forty volunteers between the ages of 21 and 55 performed 20 types of daily activities while recording HR and sampling expired gas to evaluate METs values. Multiple regression analysis was performed to develop prediction models of METs with seven potential predictors, such as %HRR, resting HR, and sex. The contributing parameters were selected based on the brute force method. Additionally, leave-one-out method was performed to validate the prediction models. Results: %HRR, resting HR, sex, and height were selected as the independent variables. %HRR showed the highest contribution in the model, while the other variables exhibited small variances. METs were estimated within a 17.3% difference for each activity, with large differences in document arrangement while sitting (+17%), ascending stairs (−8%), and descending stairs (+8%). Conclusions: The results showed that %HRR is a strong predictor for estimating the METs of daily activities. Resting HR and other variables were mild contributors. (201 words)

Mid-to-late gestation is a unique period in which women experience dynamic changes in lipid metabolism. Although the recent intensive epigenome-wide association studies (EWAS) using peripheral leukocytes have revealed that lipid-related traits alter DNA methylation, the influence of pregnancy-induced metabolic changes on the methylation levels of these differentially methylated sites is not well known. In this study, we performed a prospective cohort study of pregnant women (n = 52) using the MassARRAY EpiTYPER assay and analyzed the methylation levels of variably methylated sites, including CPT1A intron 1 and SREBF1 intron 1 CpGs, which were previously verified to be robustly associated with adiposity traits. Although methylation of SREBF1 was associated with body mass index (BMI) and low-density lipoprotein cholesterol at mid-gestation, this association was attenuated at late gestation, which was consistent with the metabolic switch from an anabolic to a catabolic state. However, the BMI association with CPT1A intron 1 methylation appeared to strengthen at late gestation; this association was mediated by pre-pregnancy BMI-dependent change in the leukocyte proportion during mid-to-late gestation. Thus, the methylation of adiposity-related differentially methylated regions was sensitive to metabolic and immunological changes during mid-to-late gestation.