Longitudinal associations of modifiable risk factors in the first 1000 days with weight status and metabolic risk in early adolescence. Issue 1 (12th November 2020)

• Record Type: Journal Article
• Authors: Hu, Jiajin; Aris, Izzuddin M; Lin, Pi-I D; Rifas-Shiman, Sheryl L; Perng, Wei; Woo Baidal, Jennifer A; Wen, Deliang; Oken, Emily
• Is Part Of: American journal of clinical nutrition. Volume 113:Issue 1(2021)
• Page Start: 113
• Page End: 122
• Publication Date: 2020-11-12
• Subjects: metabolic risk -- obesity -- body composition -- early-life risk factors -- adolescence; Diet therapy -- Periodicals; Nutrition -- Periodicals; Dietetics -- Periodicals; 613.205
• DOI: 10.1093/ajcn/nqaa297
• Languages: English
• ISSNs: 0002-9165

Abstract

ABSTRACT: Background: Many studies have identified early-life risk factors for childhood overweight/obesity (OwOb), but few have evaluated how they combine to influence later cardiometabolic health. Objectives: We aimed to examine the association of risk factors in the first 1000 d with adiposity and cardiometabolic risk in early adolescence. Methods: We studied 1038 mother–child pairs in Project Viva. We chose 6 modifiable early-life risk factors previously associated with child adiposity or metabolic health in the cohort: smoking during pregnancy (yes compared with no); gestational weight gain (excessive compared with nonexcessive); sugar-sweetened beverage consumption during pregnancy (≥0.5 compared with <0.5 servings/d); breastfeeding duration (<12 compared with ≥12 mo); timing of complementary food introduction (<4 compared with ≥4 mo); and infant sleep duration (<12 compared with ≥12 h/d). We computed risk factor scores by calculating the cumulative number of risk factors for each child. In early adolescence (median: 13.1 y) we measured indicators of adiposity [BMI, fat mass index (FMI), trunk fat mass index (TFMI)]. We also calculated OwOb prevalence and metabolic syndrome (MetS) risk z score of adolescents. Results: Among 1038 adolescents, 71% had >1 early-life risk factor. In covariate-adjusted models, we observed positive monotonic increases in BMI, FMI, TFMI, and MetS z scores with increasing risk factor score. Children with 5‒6 risk factors (compared with 0–1 risk factors) had the highest risk of OwOb [risk ratio (RR): 2.53; 95% CI: 1.63, 3.91] and being in the highest MetS quartile (RR: 2.46; 95% CI: 1.43, 4.21). The predicted probability of OwOb in adolescence varied from 9.4% (favorable levels for all factors) to 63.6% (adverse levels for all factors), and for being in the highest MetS quartile from 9.6% to 56.6%. Conclusions: Early-life risk factors in the first 1000 d cumulatively predicted higher adiposity and cardiometabolic risk in early adolescence. Intervention strategies to prevent later obesity and cardiometabolic risk may be more effective if they concurrently target multiple modifiable factors.