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Changes in asset-based wealth across the life course in birth cohorts from five low- and middle-income countries.

ABSTRACT: Background:Temporally-harmonized asset-based measures of wealth can be used to study the association of life-course wealth exposures in the same scale with health outcomes in low- and middle-income countries (LMICs). The within-individual longitudinal stability of asset-based indices of wealth in LMICs is poorly understood. Methods:Using data from five birth cohorts from three continents, we developed temporally-harmonized asset indices over the life course through polychoric principal component analysis of a common set of assets collected consistently over time (18 years in Brazil to 50 years in Guatemala). For each cohort, we compared the harmonized index to cross-sectional indices created using more comprehensive asset measures using rank correlations. We evaluated the rank correlation of the harmonized index in early life and adulthood with maternal schooling and own attained schooling, respectively. Results:Temporally-harmonized asset indices developed from a consistently-collected set of assets (range: 10 in South Africa to 30 in Philippines) suggested that mean wealth improved over time for all birth cohorts. Cross-sectional indices created separately for each study wave were correlated with the harmonized index for all cohorts (Brazil: r = 0.78 to 0.96; Guatemala: r = 0.81 to 0.95; India: 0.75 to 0.93; Philippines: r = 0.92 to 0.99; South Africa: r = 0.84 to 0.96). Maternal schooling (r = 0.15 to 0.56) and attained schooling (r = 0.23 to 0.53) were positively correlated with the harmonized asset index in childhood and adulthood respectively. Conclusions:Temporally-harmonized asset indices displayed coherence with cross-sectional indices as well as construct validity with schooling.

SUBMITTER: Varghese JS

PROVIDER: S-EPMC8637637 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundInfant-feeding patterns may influence lifelong health. This study tested the hypothesis that longer duration of breastfeeding and later introduction of complementary foods in infancy are associated with reduced adult cardiovascular risk.MethodsData were pooled from 10?912 subjects in the age range of 15-41?years from five prospective birth-cohort studies in low-/middle-income countries (Brazil, Guatemala, India, Philippines and South Africa). Associations were examined between infant feeding (duration of breastfeeding and age at introduction of complementary foods) and adult blood pressure (BP), plasma glucose concentration and adiposity (skinfolds, waist circumference, percentage body fat and overweight/obesity). Analyses were adjusted for maternal socio-economic status, education, age, smoking, race and urban/rural residence and infant birth weight.ResultsThere were no differences in outcomes between adults who were ever breastfed compared with those who were never breastfed. Duration of breastfeeding was not associated with adult diabetes prevalence or adiposity. There were U-shaped associations between duration of breastfeeding and systolic BP and hypertension; however, these were weak and inconsistent among the cohorts. Later introduction of complementary foods was associated with lower adult adiposity. Body mass index changed by -0.19?kg/m(2) [95% confidence interval (CI) -0.37 to -0.01] and waist circumference by -0.45?cm (95% CI -0.88 to -0.02) per 3-month increase in age at introduction of complementary foods.ConclusionsThere was no evidence that longer duration of breastfeeding is protective against adult hypertension, diabetes or overweight/adiposity in these low-/middle-income populations. Further research is required to determine whether 'exclusive' breastfeeding may be protective. Delaying complementary foods until 6 months, as recommended by the World Health Organization, may reduce the risk of adult overweight/adiposity, but the effect is likely to be small.

Project description:ImportanceWorldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies.ObjectiveTo investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB.Design, setting, and participantsThis diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019.ExposuresBlood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites.Main outcomes and measuresThe PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation.ResultsOf the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways.Conclusions and relevanceThis study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB.

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Changes in asset-based wealth across the life course in birth cohorts from five low- and middle-income countries.

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