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Contains fulltext : 225413.pdf (Publisher’s version ) (Closed access) Despite development of new technologies for caries control, tooth decay in primary teeth remains a major global health problem. Caries risk assessment (CRA) models for toddlers and preschoolers are rare. Among them, almost all models use dental factors (e.g., past caries experience) to predict future caries risk, with limited clinical/community applicability owing to relatively uncommon dental visits compared to frequent medical visits during the first year of life. The objective of this study was to construct and evaluate risk prediction models using information easily accessible to medical practitioners to forecast caries at 2 and 3 y of age. Data were obtained from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) mother-offspring cohort. Caries was diagnosed using modified International Caries Detection and Assessment System criteria. Risk prediction models were constructed using multivariable logistic regression coupled with receiver operating characteristic analyses. Imputation was performed using multiple imputation by chained equations to assess effect of missing data. Caries rates at ages 2 y (n = 535) and 3 y (n = 721) were 17.8% and 42.9%, respectively. Risk prediction models predicting overall caries risk at 2 and 3 y demonstrated area under the curve (AUC) (95% confidence interval) of 0.81 (0.75-0.87) and 0.79 (0.74-0.84), respectively, while those predicting moderate to extensive lesions showed 0.91 (0.85-0.97) and 0.79 (0.73-0.85), respectively. Postimputation results showed reduced AUC of 0.75 (0.74-0.81) and 0.71 (0.67-0.75) at years 2 and 3, respectively, for overall caries risk, while AUC was 0.84 (0.76-0.92) and 0.75 (0.70-0.80), respectively, for moderate to extensive caries. Addition of anterior caries significantly increased AUC in all year 3 models with or without imputation (all P < 0.05). Significant predictors/protectors were identified, including ethnicity, prenatal tobacco smoke exposure, history of allergies before 12 mo, history of chronic maternal illness, maternal brushing frequency, childbearing age, and so on. Integrating oral-general health care using medical CRA models may be promising in screening caries-susceptible infants/toddlers, especially when medical professionals are trained to "lift the lip" to identify anterior caries lesions.

The amygdala and hippocampus undergo rapid development in early life. The relative contribution of genetic and environmental factors to the establishment of their developmental trajectories has yet to be examined. We performed imaging on neonates and examined how the observed variation in volume and microstructure of the amygdala and hippocampus varied by genotype, and compared with prenatal maternal mental health and socioeconomic status. Gene × Environment models outcompeted models containing genotype or environment only to best explain the majority of measures but some, especially of the amygdaloid microstructure, were best explained by genotype only. Models including DNA methylation measured in the neonate umbilical cords outcompeted the Gene and Gene × Environment models for the majority of amygdaloid measures and minority of hippocampal measures. This study identified brain region-specific gene networks associated with individual differences in fetal brain development. In particular, genetic and epigenetic variation within CUX1 was highlighted. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) National Medical Research Council (NMRC) National Medical Research Council, Grant/Award Numbers: NMRC/TCR/004-NUS/2008,NMRC/TCR/012-NUHS/2014; NUS Instituteof Data Science, Singapore; Singapore Ministryof Education; Agency for Science Technologyand Research (ASTAR); Singapore Institute forClinical Sciences; Singapore National ResearchFoundation

In Singapore, the obesity prevalence is disproportionately higher in the Asian-Indians and Malays than the Chinese. Lower resting energy expenditure (REE) may be a contributory factor.We explored the association between ethnicity and REE in Chinese, Asian-Indian and Malay men living in Singapore and determined the influence of body composition, mass/volume of high metabolic rate organs, represented by brain volume and trunk fat-free mass (FFM), and physical activity on ethnic differences.Two hundred and forty-four men from Singapore (n=100 Chinese, 70 Asian-Indians and 74 Malays), aged 21-40 years and body mass index of 18.5-30.0 kg m(-2), were recruited in this cross-sectional study. REE was assessed by indirect calorimetry and body composition by dual-energy X-ray absorptiometry. Brain volume was measured by magnetic resonance imaging. Physical activity was assessed by the Singapore Prospective Study Program Physical Activity Questionnaire.REE was significantly lower in Asian-Indians compared with that in Chinese after adjusting for body weight. FFM (total, trunk and limb) and total fat mass were important predictors of REE across all ethnic groups. Brain volume was positively associated with REE only in Malays. Moderate and vigorous physical activity was positively associated with REE only in Asian-Indians and Malays. The difference in REE between Asian-Indians and Chinese was attenuated but remained statistically significant after adjustment for total FFM (59±20 kcal per day), fat mass (67±20 kcal per day) and brain volume (54±22 kcal per day). The association between REE and ethnicity was no longer statistically significant after total FFM was replaced by trunk FFM (which includes heart, liver, kidney and spleen) but not when it was replaced by limb FFM (skeletal muscle).We have demonstrated a lower REE in Asian-Indians compared with Chinese who may contribute to the higher rates of obesity in the former. This difference could be accounted for by differences in metabolically active organs.

Study question Are higher overall and central adiposity associated with reduced fecundability, measured by time-to-pregnancy (TTP), in Asian women? Summary answer Higher overall adiposity, but not central adiposity, was associated with longer TTP in Asian women. What is known already High body mass index (BMI) has been associated with a longer TTP, although the associations of body composition and distribution with TTP are less clear. There are no previous studies of TTP in Asian women, who have a relatively higher percentage of body fat and abdominal fat at relatively lower BMI. Study design, size, duration Prospective preconception cohort using data from 477 Asian (Chinese, Malay and Indian) women who were planning to conceive and enrolled in the Singapore PREconception Study of long-Term maternal and child Outcomes (S-PRESTO) study, 2015-2017. Participants/materials, setting, methods Women's mean age was 30.7 years. Overall adiposity was assessed by BMI, sum of 4-site skinfold thicknesses (SFT) and total body fat percentage (TBF%, measured using air displacement plethysmography); central adiposity was assessed by waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and A body Shape Index (ABSI). Pregnancy occurring within one year from recruitment was ascertained by ultrasonography. Those who did not conceive within one year of recruitment, were lost to follow-up, or initiated fertility treatment were censored. TTP was measured in cycles. Discrete-time proportional hazards models were used to estimate the fecundability ratio (FR) and 95% confidence interval (CI) for each anthropometric measure in association with fecundability, adjusting for confounders. Main results and the role of chance Compared to women with a normal BMI of 18.5-22.9 kg/m2, women with higher BMI of 23-27.4 and ≥27.5 kg/m2 showed lower FR of 0.66 (95% CI 0.45, 0.97) and 0.53 (0.31, 0.89), respectively. Compared to women in the lowest quartile of SFT (25-52.9 mm), those in the highest quartile of ≥90.1 mm showed lower FR of 0.58 (95% CI 0.36, 0.95). Compared to women in the lowest quartile of TBF% (13.6-27.2%), those in the upper two quartiles of 33.0-39.7% and ≥39.8% showed lower FR of 0.56 (95% CI 0.32, 0.98) and 0.43 (0.24, 0.80), respectively. Association of high BMI with reduced fecundability was particularly evident among nulliparous women. Measures of central adiposity (WC, WHR, WHtR, ABSI) were not associated with fecundability. Limitations reasons for caution Small sample size could restrict power of analysis.The analysis was confined to planned pregnancies, which could limit generalizability of findings to non-planned pregnancies, estimated at around 44% in Singapore. Information on the date of last menstrual period for each month was not available, hence the accuracy of self-reported menstrual cycle length could not be validated, potentially introducing error into TTP estimation. Measures of exposures and covariates such as cycle length were not performed repeatedly over time; cycle length might have changed during the period before getting pregnant. Wider implications of the findings Other than using BMI as the surrogate measure of body fat, we provide additional evidence showing that higher amounts of subcutaneous fat that based on the measure of SFT at the sites of biceps, triceps, suprailiac and subscapular, and TBF% are associated with longer TTP. Achieving optimal weight and reducing total percentage body fat may be a potential intervention target to improve female fertility. The null results observed between central adiposity and TTP requires confirmation in further studies. Study funding/competing interest(s) This research is supported by Singapore National Research Foundation under its Translational and Clinical Research Flagship Programme and administered by the Singapore Ministry of Health's National Medical Research Council, (NMRC/TCR/004-NUS/2008; NMRC/TCR/012-NUHS/2014). Additional funding is provided by the Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore. Y.S.C., K.M.G., F.Y. and Y.S.L. have received reimbursement to speak at conferences sponsored by companies selling nutritional products. Y.S.C., K.M.G. and S.Y.C. are part of an academic consortium that has received research funding from Abbott, Nutrition, Nestle and Danone. Other authors declared no conflicts of interest. Trial registration number N/A.

Studying the determinants and the long-term consequences of fetal adipose accretion requires accurate assessment of neonatal body composition. In large epidemiological studies, in-depth body composition measurement methods are usually not feasible for cost and logistical reasons, and there is a need to identify anthropometric measures that adequately reflect neonatal adiposity. Methods In a multiethnic Asian mother-offspring cohort in Singapore, anthropometric measures (weight, length, abdominal circumference, skinfold thicknesses) were measured using standardized protocols in newborn infants, and anthropometric indices [weight/length, weight/length2 (body mass index, BMI), weight/length3 (ponderal index, PI)] derived. Neonatal total adiposity was measured using air displacement plethysmography (ADP) and abdominal adiposity using magnetic resonance imaging (MRI). Correlations of the anthropometric measures with ADP- and MRI-based adiposity were assessed using Pearson’s correlation coefficients (rp), including in subsamples stratified by sex and ethnicity. Results Study neonates (n =251) had a mean (SD) age of 10.2 (2.5) days. Correlations between ADP-based fat mass (ADPFM) and anthropometric measures were moderate (rp range: 0.44-0.67), with the strongest being with weight/length, weight, BMI and sum of skinfolds (rp =0.67, 0.66, 0.62, 0.62, respectively, all P

Many studies have identified early-life risk factors for subsequent childhood overweight/obesity, but few have evaluated how they combine to influence risk of childhood overweight/obesity. We examined associations, individually and in combination, of potentially modifiable risk factors in the first 1000 days after conception with childhood adiposity and risk of overweight/obesity in an Asian cohort. Six risk factors were examined: maternal pre-pregnancy overweight/obesity (body mass index (BMI) ⩾25 kg m−2), paternal overweight/obesity at 24 months post delivery, maternal excessive gestational weight gain, raised maternal fasting glucose during pregnancy (⩾5.1 mmol l−1), breastfeeding duration

There have been hypotheses that early life adiposity gain may influence blood pressure (BP) later in life. We examined associations between timing of height, body mass index (BMI) and adiposity gains in early life with BP at 48 months in an Asian pregnancy-birth cohort.In 719 children, velocities for height, BMI and abdominal circumference (AC) were calculated at five intervals [0-3, 3-12, 12-24, 24-36 and 36-48 months]. Triceps (TS) and subscapular skinfold (SS) velocities were calculated between 0-18, 18-36 and 36-48 months. Systolic (SBP) and diastolic blood pressure (DBP) was measured at 48 months. Growth velocities at later periods were adjusted for growth velocities in preceding intervals, as well as measurements at birth.After adjusting for confounders and child height at BP measurement, each unit z-score gain in BMI, AC, TS and SS velocities at 36-48 months were associated with 2.3 (95% CI:1.6, 3.1), 2.1 (1.3, 2.8), 1.4 (0.6, 2.2) and 1.8 (1, 2.6) mmHg higher SBP respectively, and 0.9 (0.4, 1.4), 0.9 (0.4, 1.3), 0.6 (0.1, 1.1) and 0.8 (0.3, 1.3) mmHg higher DBP respectively. BMI and adiposity velocities (AC, TS or SS) at various intervals in the first 36 months however, were not associated with BP. Faster BMI, AC, TS and SS velocities, but not height, at 36-48 months were associated with 0.22 (0.15, 0.29), 0.17 (0.10, 0.24), 0.11 (0.04, 0.19) and 0.15 (0.08, 0.23) units higher SBP z-score respectively, and OR=1.46 (95% CI: 1.13-1.90), 1.49 (1.17-1.92), 1.45 (1.09-1.92) and 1.43 (1.09, 1.88) times higher risk of prehypertension/hypertension respectively at 48 months.Our results indicated that faster BMI and adiposity (AC, TS or SS) velocities only at the preceding interval before 48 months (36-48 months), but not at earlier intervals in the first 36 months, are predictive of BP and prehypertension/hypertension at 48 months.