Causes and consequences of child growth faltering in low-resource settings.

Growth faltering in children (low length for age or low weight for length) during the first 1,000 days of life (from conception to 2 years of age) influences short-term and long-term health and survival1,2. Interventions such as nutritional supplementation during pregnancy and the postnatal period could help prevent growth faltering, but programmatic action has been insufficient to eliminate the high burden of stunting and wasting in low- and middle-income countries. Identification of age windows and population subgroups on which to focus will benefit future preventive efforts. Here we use a population intervention effects analysis of 33 longitudinal cohorts (83,671 children, 662,763 measurements) and 30 separate exposures to show that improving maternal anthropometry and child condition at birth accounted for population increases in length-for-age z-scores of up to 0.40 and weight-for-length z-scores of up to 0.15 by 24 months of age. Boys had consistently higher risk of all forms of growth faltering than girls. Early postnatal growth faltering predisposed children to subsequent and persistent growth faltering. Children with multiple growth deficits exhibited higher mortality rates from birth to 2 years of age than children without growth deficits (hazard ratios 1.9 to 8.7). The importance of prenatal causes and severe consequences for children who experienced early growth faltering support a focus on pre-conception and pregnancy as a key opportunity for new preventive interventions.

Nonlinearity in demographic and behavioral determinants of morbidity.

OBJECTIVE: To examine nonlinearity of determinants of morbidity in the United States DATA SOURCES: A secondary analysis of data on individuals with dietary data from the Cancer Epidemiology Supplement and National Health Interview Survey (NHIS) 1987, a cross-sectional, stratified random sample of the U.S. population (n = 22,080). STUDY DESIGN: A statistical exploration using additive multiple regression models. METHODS: A Morbidity Index (0-30 points), derived from 1987 National Health Interview Survey data, combines number of conditions, hospitalizations, sick days, doctor visits, and degree of disability. Behavioral (health habits) variables were added to multivariate models containing demographic terms, with Morbidity Index and Self-assessed Health outcomes (n = 17,612). Tables and graphs compare models of morbidity with self-assessed health models, with and without behavioral terms. Graphs illustrate curvilinear relationships. PRINCIPAL FINDINGS: Morbidity and health are associated nonlinearly with age, race, education, and income, as well as alcohol, diet change, vitamin supplement use, body mass index (BMI), marital status/living arrangement, and smoking. Diet change and supplement use, education, income, race/ethnicity, and age relate differently to self-assessed health status than to morbidity. Morbidity is strongly associated with income up to about dollars 15,000 above poverty. Additional income predicts no further reduction in morbidity. Better health is strongly related to both higher income and education. After controlling for income, black race does not predict morbidity, but remains associated with lower self-assessed health. CONCLUSIONS: Good health habits, as captured in these models, are associated with a 10-20-year delay in onset and progression of morbidity.