Effects of early-life poverty on health and human capital in children and adolescents: analyses of national surveys and birth cohort studies in LMICs.

The survival and nutrition of children and, to a lesser extent, adolescents have improved substantially in the past two decades. Improvements have been linked to the delivery of effective biomedical, behavioural, and environmental interventions; however, large disparities exist between and within countries. Using data from 95 national surveys in low-income and middle-income countries (LMICs), we analyse how strongly the health, nutrition, and cognitive development of children and adolescents are related to early-life poverty. Additionally, using data from six large, long-running birth cohorts in LMICs, we show how early-life poverty can have a lasting effect on health and human capital throughout the life course. We emphasise the importance of implementing multisectoral anti-poverty policies and programmes to complement specific health and nutrition interventions delivered at an individual level, particularly at a time when COVID-19 continues to disrupt economic, health, and educational gains achieved in the recent past.

Health and development from preconception to 20 years of age and human capital.

Optimal health and development from preconception to adulthood are crucial for human flourishing and the formation of human capital. The Nurturing Care Framework, as adapted to age 20 years, conceptualises the major influences during periods of development from preconception, through pregnancy, childhood, and adolescence that affect human capital. In addition to mortality in children younger than 5 years, stillbirths and deaths in 5-19-year-olds are important to consider. The global rate of mortality in individuals younger than 20 years has declined substantially since 2000, yet in 2019 an estimated 8·6 million deaths occurred between 28 weeks of gestation and 20 years of age, with more than half of deaths, including stillbirths, occurring before 28 days of age. The 1000 days from conception to 2 years of age are especially influential for human capital. The prevalence of low birthweight is high in sub-Saharan Africa and even higher in south Asia. Growth faltering, especially from birth to 2 years, occurs in most world regions, whereas overweight increases in many regions from the preprimary school period through adolescence. Analyses of cohort data show that growth trajectories in early years of life are strong determinants of nutritional outcomes in adulthood. The accrual of knowledge and skills is affected by health, nutrition, and home resources in early childhood and by educational opportunities in older children and adolescents. Linear growth in the first 2 years of life better predicts intelligence quotients in adults than increases in height in older children and adolescents. Learning-adjusted years of schooling range from about 4 years in sub-Saharan Africa to about 11 years in high-income countries. Human capital depends on children and adolescents surviving, thriving, and learning until adulthood.

Growth in Infancy and Childhood and Age at Menarche in Five Low- or Middle-Income Countries: Consortium of Health Orientated Research in Transitional Societies (COHORTS).

BACKGROUND: Earlier age at menarche is associated with behavioral and noncommunicable disease risks. The influence of birth weight (BW) (intrauterine) and postnatal growth on age at menarche is not well studied in low- and middle-income countries (LMICs). OBJECTIVE: Therefore, we investigated these associations in 5 LMIC birth cohorts. METHODS: We analyzed data from Brazil, Guatemala, India, the Philippines, and South Africa (n = 3983). We derived stunting (< -2 SD scores) at 24 mo using the WHO child growth standards. We generated interaction terms with categorized BW and conditional weight (lighter < 0 or heavier ≥ 0), and height (shorter < 0 or taller ≥ 0) z-scores. We categorized early-, modal-, and late-onset menarche and used multilevel ordinal regression. We used multilevel linear regression on continuous age at menarche. RESULTS: Mean age at menarche was 12.8 y (95% CI: 12.7 12.9). BW was not associated with age at menarche. Conditional height at 24 mo and mid-childhood (OR: 1.35; 95% CI: 1.27, 1.44 and 1.32; 1.25, 1.41, respectively) and conditional weight at 24 mo and mid-childhood (OR: 1.15; 1.08, 1.22 and 1.18; 1.11, 1.25, respectively) were associated with increased likelihood of early-onset menarche. Being heavier at birth and taller at 24 mo was associated with a 4-mo (95% CI: 0.8, 7.6) earlier age at menarche than being lighter at birth and shorter at 24 mo. Being heavier at birth but lighter in mid-childhood was associated with a 3-mo (95% CI: 0.8, 4.8) later age at menarche than being lighter at birth and mid-childhood. Age at menarche was 7 mo later in stunted than nonstunted girls. CONCLUSION: Age at menarche is inversely related to relative weight gain but also to rapid linear growth among those born shorter but remained stunted, and those born taller and grew excessively. These findings do not deter the global health goal to reduce growth faltering but emphasize the potential adverse effects of an obesogenic environment on adolescent development.

Conditional wealth to estimate association of wealth mobility with health and human capital in low- and middle-income country cohorts.

Temporally harmonized asset indices allow the study of changes in relative wealth (mean, variance, social mobility) over time and its association with adult health and human capital in cohort studies. Conditional measures are the unexplained residuals of an indicator regressed on its past values. Using such measures, previously used to study the relative importance of key life stages for anthropometric growth, we can identify specific life stages during which changes in relative wealth are important for adult health in longitudinal studies. We discuss the assumptions, strengths and limitations of this methodology as applied to relative wealth. We provide an illustrative example using a publicly-available longitudinal dataset and show how relative wealth changes at different life stages are differentially associated with body mass index in adulthood.

Early Life Influences on Hearing in Adulthood: a Systematic Review and Two-Step Individual Patient Data Meta-Analysis.

OBJECTIVES: Adverse prenatal and early childhood development may increase susceptibility of hearing loss in adulthood. The objective was to assess whether indices of early development are associated with adult-onset hearing loss in adults ≥18 years. DESIGN: In a systematic review and meta-analysis, four electronic databases were searched for studies reporting associations between indices of early development (birth weight and adult height) and adult-onset hearing loss in adults ≥18 years. We screened studies, extracted data, and assessed risk of bias. Authors were contacted to provide adjusted odds ratios from a logistic regression model for relationships between birth weight/adult height and normal/impaired hearing enabling a two-step individual patient data random-effects meta-analysis to be carried out. The study is registered with PROSPERO, CRD42020152214. RESULTS: Four studies of birth weight and seven of adult height were identified. Three studies reported smaller birth weight associated with poorer adult hearing. Six studies reported shorter height associated with poorer hearing. Risk of bias was low to moderate. Four studies provided data for two-step individual patient data random-effects meta-analysis. Odds of hearing impairment were 13.5% lower for every 1 kg increase in birth weight [OR: 0.865 (95% confidence interval: 0.824 to 0.909)] in adulthood over two studies (N=81,289). Every 1 cm increase in height was associated with a 3% reduction in the odds of hearing impairment [OR: 0.970 (95% confidence interval: 0.968 to 0.971)] over four studies (N=156,740). CONCLUSIONS: Emerging evidence suggests that adverse early development increases the likelihood of hearing impairment in adulthood. Research and public health attention should focus on the potential for prevention of hearing impairment by optimizing development in early life.

Peri-conceptional diet patterns and the risk of Gestational diabetes mellitus in South Indian women.

OBJECTIVE: To identify peri-conceptional diet patterns among women in Bangalore, and examine their associations with risk of gestational diabetes mellitus. DESIGN: BANGLES, started in June 2016, was a prospective observational study, in which women were recruited at 5-16 weeks' gestation. Peri-conceptional diet was recalled at recruitment, using a validated 224-item food frequency questionnaire. GDM was assessed by a 75-gram oral glucose tolerance test at 24-28 weeks' gestation, applying WHO 2013 criteria. Diet patterns were identified using principal component analysis and diet pattern-GDM associations were examined using multivariate logistic regression, adjusting for 'a priori' confounders. SETTING: Antenatal clinics of two hospitals, Bangalore, South India. PARTICIPANTS: 785 pregnant women of varied socio-economic status. RESULTS: GDM prevalence was 22%. Three diet patterns were identified: a) High-diversity, urban (HDU) characterised by diverse, home-cooked and processed foods was associated with older, more affluent, better-educated and urban women; b) Rice-fried snacks-chicken-sweets (RFCS), characterised by low diet-diversity, was associated with younger, less-educated, and lower income, rural and joint families; c) Healthy, traditional vegetarian (HTV), characterised by home-cooked-vegetarian and non-processed foods was associated with less-educated, more affluent, and rural and joint families. The HDU pattern was associated with a lower GDM risk (aOR: 0.80 per SD, 95% CI: 0.64, 0.99, p=0.04) after adjusting for confounders. BMI was strongly related to GDM risk and possibly mediated diet-GDM associations. CONCLUSIONS: The findings support global recommendations to encourage women to attain a healthy pre-pregnancy BMI and increase diet-diversity. Both healthy and unhealthy foods in the patterns indicate low-awareness about healthy foods and a need for public-education.

Cardiovascular disease in people born to unmarried mothers in two historical periods: The Helsinki Birth Cohort Study 1934-1944.

Aims:Socio-economic conditions in early life are important contributors to cardiovascular disease - the leading cause of mortality globally - in later life. We studied coronary heart disease (CHD) and stroke in adulthood among people born out of wedlock in two historical periods: before and during World War II in Finland. Methods: We compared offspring born out of wedlock before (1934-1939) and during (1940-1944) World War II with the offspring of married mothers in the Helsinki Birth Cohort Study. The war affected the position of unmarried mothers in society. We followed the study subjects from 1971 to 2014 and identified deaths and hospital admissions from CHD and stroke. Data were analysed using a Cox regression, adjusting for other childhood and adulthood socio-economic circumstances. Results: The rate of out-of-wedlock births was 240/4052 (5.9%) before World War II and 397/9197 (4.3%) during World War II. Among those born before World War II, out-of-wedlock birth was associated with an increased risk of stroke (hazard ratio (HR)=1.44; 95% confidence interval (CI) 1.00-2.07) and CHD (HR=1.37; 95% CI 1.02-1.86). Among those born out of wedlock during World War II, the risks of stroke (HR=0.89; 95% CI 0.58-1.36) and CHD (HR=0.70; 95% CI 0.48=1.03) were similar to those observed for the offspring of married mothers. The p-values for interaction of unmarried×World War II were (p=0.015) for stroke and (p=0.003) for CHD. Conclusions: In a society in which marriage is normative, being born out of wedlock is an important predictor of lifelong health disadvantage. However, this may change rapidly when societal circumstances change, such as during a war.

Distinct opposing associations of upper and lower body fat depots with metabolic and cardiovascular disease risk markers.

BACKGROUND: To examine the associations of total and regional adiposity with metabolic and cardiovascular disease (CVD) risk markers. METHODS: This cross-sectional study included 1080 (53.8% men, aged 39-44 years) individuals from South India. Anthropometry (height, weight, waist and hip circumference), body composition assessment using dual-energy X-ray absorptiometry (DXA), blood pressure (BP), and plasma glucose, insulin and lipids were measured. Regression analysis was used to examine associations of standardized fat measurements with type 2 diabetes (T2D), insulin resistance (IR), hypertension and hypertriglyceridemia and continuous measurements of BP, glucose, insulin, HOMA-IR and lipids. Contour plots were constructed to visualize the differential effect of upper and lower fat depots. RESULTS: DXA-measured fat depots were positively associated with metabolic and CVD risk markers. After adjusting for fat mass index, upper body fat remained positively, while lower body fat was negatively associated with risk markers. A one standard deviation (SD) increase in android fat showed higher odds ratios (ORs) for T2D (6.59; 95% CI 3.17, 13.70), IR (4.68; 95% CI 2.31, 9.50), hypertension (2.57; 95% CI 1.56, 4.25) and hypertriglyceridemia (6.39; 95% CI 3.46, 11.90) in men. A 1 SD increase in leg fat showed a protective effect with ORs for T2D (0.42; 95% CI 0.24, 0.74), IR (0.31; 95% CI 0.17, 0.57) and hypertriglyceridemia (0.61; 95% CI 0.38, 0.98). The magnitude of the effect was greater with DXA-measured fat compared with anthropometry. CONCLUSION: At any level of total body fat, upper and lower body fat depots demonstrate opposite risk associations with metabolic and CVD risk markers in Asian Indians.

Consequences of ignoring clustering in linear regression.

BACKGROUND: Clustering of observations is a common phenomenon in epidemiological and clinical research. Previous studies have highlighted the importance of using multilevel analysis to account for such clustering, but in practice, methods ignoring clustering are often employed. We used simulated data to explore the circumstances in which failure to account for clustering in linear regression could lead to importantly erroneous conclusions. METHODS: We simulated data following the random-intercept model specification under different scenarios of clustering of a continuous outcome and a single continuous or binary explanatory variable. We fitted random-intercept (RI) and ordinary least squares (OLS) models and compared effect estimates with the "true" value that had been used in simulation. We also assessed the relative precision of effect estimates, and explored the extent to which coverage by 95% confidence intervals and Type I error rates were appropriate. RESULTS: We found that effect estimates from both types of regression model were on average unbiased. However, deviations from the "true" value were greater when the outcome variable was more clustered. For a continuous explanatory variable, they tended also to be greater for the OLS than the RI model, and when the explanatory variable was less clustered. The precision of effect estimates from the OLS model was overestimated when the explanatory variable varied more between than within clusters, and was somewhat underestimated when the explanatory variable was less clustered. The cluster-unadjusted model gave poor coverage rates by 95% confidence intervals and high Type I error rates when the explanatory variable was continuous. With a binary explanatory variable, coverage rates by 95% confidence intervals and Type I error rates deviated from nominal values when the outcome variable was more clustered, but the direction of the deviation varied according to the overall prevalence of the explanatory variable, and the extent to which it was clustered. CONCLUSIONS: In this study we identified circumstances in which application of an OLS regression model to clustered data is more likely to mislead statistical inference. The potential for error is greatest when the explanatory variable is continuous, and the outcome variable more clustered (intraclass correlation coefficient is ≥ 0.01).

Size at birth, lifecourse factors, and cognitive function in late life: findings from the MYsore study of Natal effects on Ageing and Health (MYNAH) cohort in South India.

OBJECTIVE: To examine if smaller size at birth, an indicator of growth restriction in utero, is associated with lower cognition in late life, and whether this may be mediated by impaired early life brain development and/or adverse cardiometabolic programming. DESIGN: Longitudinal follow-up of a birth cohort. SETTING: CSI Holdsworth Memorial Hospital (HMH), Mysore South India. PARTICIPANTS: 721 men and women (55-80 years) whose size at birth was recorded at HMH. Approximately 20 years earlier, a subset (n = 522) of them had assessments for cardiometabolic disorders in mid-life. MEASUREMENTS: Standardized measurement of cognitive function, depression, sociodemographic, and lifestyle factors; blood tests and assessments for cardiometabolic disorders. RESULTS: Participants who were heavier at birth had higher composite cognitive scores (0.12 SD per SD birth weight [95% CI 0.05, 0.19] p = 0.001) in late life. Other lifecourse factors independently positively related to cognition were maternal educational level and participants' own educational level, adult leg length, body mass index, and socioeconomic position, and negatively were diabetes in mid-life and current depression and stroke. The association of birth weight with cognition was independent cardiometabolic risk factors and was attenuated after adjustment for all lifecourse factors (0.08 SD per SD birth weight [95% CI -0.01, 0.18] p = 0.07). CONCLUSIONS: The findings are consistent with positive effects of early life environmental factors (better fetal growth, education, and childhood socioeconomic status) on brain development resulting in greater long-term cognitive function. The results do not support a pathway linking poorer fetal development with reduced late life cognitive function through cardiometabolic programming.