Methods: : We utilized data among 1020 infants from a mother-offspring cohort, who were Singapore citizens or permanent residents of Chinese, Malay or Indian ethnicity with homogeneous parental ethnic backgrounds, and did not receive chemotherapy, psychotropic drugs or have diabetes mellitus. Ethnicity was self-reported at recruitment and later confirmed using genotype analysis. Subject-specific BMI curves were fitted to infant BMI data using natural cubic splines with random coefficients to account for repeated measures in each child. We estimated characteristics of the child's BMI peak [age and magnitude at peak, average pre-peak velocity (aPPV)]. Systolic (SBP) and diastolic blood pressure (DBP), BMI, sum of skinfolds (SSF) and fat-mass index (FMI) were measured during a follow-up visit at age 48 months. Weighted multivariable linear regression was used to assess the predictors (maternal BMI, gestational weight gain, ethnicity, infant sex, gestational age, birthweight-for-gestational age and breastfeeding duration) of infant BMI peak and its associations with outcomes at 48 months. Comparisons between ethnicities were tested using Bonferroni post-hoc correction.
Results: : Of 1020 infants, 80.5% were followed up at the 48-month visit. Mean (SD) BMI, SSF and FMI at 48 months were 15.6 (1.8) kg/m 2 , 16.5 (5.3) mm and 3.8 (1.3) kg/m 2 , respectively. Mean (SD) age at peak BMI was 6.0 (1.6) months, with a magnitude of 17.2 (1.4) kg/m 2 and pre-peak velocity of 0.7 (0.3) kg/m 2 /month. Compared with Chinese infants, the peak occurred later in Malay {B [95% confidence interval (CI): 0.64 mo (0.36, 0.92)]} and Indian infants [1.11 mo (0.76, 1.46)] and was lower in magnitude in Indian infants [-0.45 kg/m 2 (-0.69, -0.20)]. Adjusting for maternal education, BMI, gestational weight gain, ethnicity, infant sex, gestational age, birthweight-for-gestational-age and breastfeeding duration, higher peak and aPPV were associated with greater BMI, SSF and FMI at 48 months. Age at peak was positively associated with BMI at 48 months [0.15 units (0.09, 0.22)], whereas peak magnitude was associated with SBP [0.17 units (0.05, 0.30)] and DBP at 48 months [0.10 units (0.01, 0.22)]. Older age and higher magnitude at peak were associated with increased risk of overweight at 48 months [Relative Risk (95% CI): 1.35 (1.12-1.62) for age; 1.89 (1.60-2.24) for magnitude]. The associations of BMI peak with BMI and SSF at 48 months were stronger in Malay and Indian children than in Chinese children.
Conclusions: : Ethnic-specific differences in BMI peak characteristics, and associations of BMI peak with early childhood cardio-metabolic markers, suggest an important impact of early BMI development on later metabolic outcomes in Asian populations.
METHODS: Cross-sectional analysis of the Malaysian Elders Longitudinal Research (MELoR) study involving community-dwelling individuals aged >55 years was conducted. Information on sociodemographic factors, medical history, and lifestyle were obtained by computer-assisted interviews in participants' homes. Cognitive performance was assessed with the Montreal Cognitive Assessment (MoCA) tool during subsequent hospital-based health checks. Hierarchical multiple linear regression analyses were conducted with continuous MoCA scores as the dependent variable.
RESULTS: Data were available for 1,140 participants, mean (standard deviation [SD]) = 68.48 (7.23) years, comprising 377 (33.1%) ethnic Malays, 414 (36.3%) Chinese, and 349 (30.6%) Indians. Mean (SD) MoCA scores were 20.44 (4.92), 23.97 (4.03), and 22.04 (4.83) for Malays, Chinese, and Indians, respectively (p = 0.01). Age >75 years, <12 years of education, and low functional ability were common risk factors for low cognitive performance across all three ethnic groups. Cognitive performance was positively associated with social engagement among the ethnic Chinese (β [95% CI] = 0.06 [0.01, 0.11]) and Indians (β [95% CI] = 0.16 [0.09, 0.23]) and with lower depression scores (β [(95% CI] = -0.08 [-0.15, -0.01]) among the ethnic Indians.
CONCLUSION: Common factors associated with cognitive performance include age, education, and functional ability, and ethnic-specific factors were social engagement and depression. Interethnic comparisons of risk factors may form the basis for identification of ethnic-specific modifiable risk factors for cognitive decline and provision of culturally acceptable prevention measures.