Search

ObjectiveWe sought to determine the impact of changes in breastfeeding rates on population health.Materials and methodsWe used a Monte Carlo simulation model to estimate the population-level changes in disease burden associated with marginal changes in rates of any breastfeeding at each month from birth to 12 months of life, and in rates of exclusive breastfeeding from birth to 6 months of life. We used these marginal estimates to construct an interactive online calculator (available at www.usbreastfeeding.org/saving-calc ). The Institutional Review Board of the Cambridge Health Alliance exempted the study.ResultsUsing our interactive online calculator, we found that a 5% point increase in breastfeeding rates was associated with statistically significant differences in child infectious morbidity for the U.S. population, including otitis media (101,952 cases, 95% confidence interval [CI] 77,929-131,894 cases) and gastrointestinal infection (236,073 cases, 95% CI 190,643-290,278 cases). Associated medical cost differences were $31,784,763 (95% CI $24,295,235-$41,119,548) for otitis media and $12,588,848 ($10,166,203-$15,479,352) for gastrointestinal infection. The state-level impact of attaining Healthy People 2020 goals varied by population size and current breastfeeding rates.ConclusionModest increases in breastfeeding rates substantially impact healthcare costs in the first year of life.

ObjectiveTo estimate the disease burden and associated costs attributable to suboptimal breastfeeding rates among non-Hispanic blacks (NHBs), Hispanics, and non-Hispanic whites (NHWs).Study designUsing current literature on associations between breastfeeding and health outcomes for 8 pediatric and 5 maternal diseases, we used Monte Carlo simulations to evaluate 2 hypothetical cohorts of US women followed from age 15 to 70 years and their infants followed from birth to age 20 years. Accounting for differences in parity, maternal age, and birth weights by race/ethnicity, we examined disease outcomes and costs using 2012 breastfeeding rates by race/ethnicity and outcomes that would be expected if 90% of infants were breastfed according to recommendations for exclusive and continued breastfeeding duration.ResultsSuboptimal breastfeeding is associated with a greater burden of disease among NHB and Hispanic populations. Compared with a NHW population, a NHB population had 1.7 times the number of excess cases of acute otitis media attributable to suboptimal breastfeeding (95% CI 1.7-1.7), 3.3 times the number of excess cases of necrotizing enterocolitis (95% CI 2.9-3.7), and 2.2 times the number of excess child deaths (95% CI 1.6-2.8). Compared with a NHW population, a Hispanic population had 1.4 times the number of excess cases of gastrointestinal infection (95% CI 1.4-1.4) and 1.5 times the number of excess child deaths (95% CI 1.2-1.9).ConclusionsRacial/ethnic disparities in breastfeeding have important social, economic, and health implications, assuming a causal relationship between breastfeeding and health outcomes.

The aim of this study was to quantify the excess cases of pediatric and maternal disease, death, and costs attributable to suboptimal breastfeeding rates in the United States. Using the current literature on the associations between breastfeeding and health outcomes for nine pediatric and five maternal diseases, we created Monte Carlo simulations modeling a hypothetical cohort of U.S. women followed from age 15 to age 70 years and their children from birth to age 20 years. We examined disease outcomes using (a) 2012 breastfeeding rates and (b) assuming that 90% of infants were breastfed according to medical recommendations. We measured annual excess cases, deaths, and associated costs, in 2014 dollars, using a 2% discount rate. Annual excess deaths attributable to suboptimal breastfeeding total 3,340 (95% confidence interval [1,886 to 4,785]), 78% of which are maternal due to myocardial infarction (n = 986), breast cancer (n = 838), and diabetes (n = 473). Excess pediatric deaths total 721, mostly due to Sudden Infant Death Syndrome (n = 492) and necrotizing enterocolitis (n = 190). Medical costs total $3.0 billion, 79% of which are maternal. Costs of premature death total $14.2 billion. The number of women needed to breastfeed as medically recommended to prevent an infant gastrointestinal infection is 0.8; acute otitis media, 3; hospitalization for lower respiratory tract infection, 95; maternal hypertension, 55; diabetes, 162; and myocardial infarction, 235. For every 597 women who optimally breastfeed, one maternal or child death is prevented. Policies to increase optimal breastfeeding could result in substantial public health gains. Breastfeeding has a larger impact on women's health than previously appreciated.

ObjectiveTo estimate risk of necrotizing enterocolitis (NEC) for extremely low birth weight (ELBW) infants as a function of preterm formula (PF) and maternal milk intake and calculate the impact of suboptimal feeding on the incidence and costs of NEC.Study designWe used aORs derived from the Glutamine Trial to perform Monte Carlo simulation of a cohort of ELBW infants under current suboptimal feeding practices, compared with a theoretical cohort in which 90% of infants received at least 98% human milk.ResultsNEC incidence among infants receiving ≥98% human milk was 1.3%; 11.1% among infants fed only PF; and 8.2% among infants fed a mixed diet (P = .002). In adjusted models, compared with infants fed predominantly human milk, we found an increased risk of NEC associated with exclusive PF (aOR = 12.1, 95% CI 1.5, 94.2), or a mixed diet (aOR 8.7, 95% CI 1.2-65.2). In Monte Carlo simulation, current feeding of ELBW infants was associated with 928 excess NEC cases and 121 excess deaths annually, compared with a model in which 90% of infants received ≥98% human milk. These models estimated an annual cost of suboptimal feeding of ELBW infants of $27.1 million (CI $24 million, $30.4 million) in direct medical costs, $563 655 (CI $476 191, $599 069) in indirect nonmedical costs, and $1.5 billion (CI $1.3 billion, $1.6 billion) in cost attributable to premature death.ConclusionsAmong ELBW infants, not being fed predominantly human milk is associated with an increased risk of NEC. Efforts to support milk production by mothers of ELBW infants may prevent infant deaths and reduce costs.

Background Preterm infants are a group at high risk of having experienced placental insufficiency. It is unclear which growth charts perform best in identifying infants at increased risk of stillbirth and other adverse perinatal outcomes. We compared 2 birthweight charts (population centiles and INTERGROWTH-21st birthweight centiles) and 3 fetal growth charts (INTERGROWTH-21st fetal growth charts, World Health Organization fetal growth charts, and Gestation Related Optimal Weight [GROW] customised growth charts) to identify which chart performed best in identifying infants at increased risk of adverse perinatal outcome in a preterm population. Methods and findings We conducted a retrospective cohort study of all preterm infants born at 24.0 to 36.9 weeks gestation in Victoria, Australia, from 2005 to 2015 (28,968 records available for analysis). All above growth charts were applied to the population. Proportions classified as Conclusions In this study, fetal charts classified greater proportions of preterm and stillborn infants as SGA, which more accurately reflected true fetal growth restriction. Of the intrauterine charts, INTERGROWTH classified the smallest number of preterm infants as SGA, although it identified a particularly high-risk cohort, and GROW customised charts classified the greatest number at increased risk of perinatal mortality., Author(s): Natasha L. Pritchard 1,2, Richard J. Hiscock 1,2, Elizabeth Lockie 1, Michael Permezel 1,2, Monica F. G. McGauren 2, Amber L. Kennedy 1,2, Brittany Green 1, Susan P. Walker [...]

Despite major advances in research and treatment, identifying important genotype risk factors for high blood pressure remains challenging. Traditional genome-wide association studies (GWAS) focus on one single nucleotide polymorphism (SNP) at a time. We aim to select among over half a million SNPs along with time-varying phenotype variables via simultaneous modeling and variable selection, focusing on the most dangerous blood pressure levels at high quantiles. Taking advantage of rich data from a large-scale public health study, we develop and apply a novel quantile penalized generalized estimating equations (GEE) approach, incorporating several key aspects including ultra-high dimensional genetic SNPs, the longitudinal nature of blood pressure measurements, time-varying covariates, and conditional high quantiles of blood pressure. Importantly, we identify interesting new SNPs for high blood pressure. Besides, we find blood pressure levels are likely heterogeneous, where the important risk factors identified differ among quantiles. This comprehensive picture of conditional quantiles of blood pressure can allow more insights and targeted treatments. We provide an efficient computational algorithm and prove consistency, asymptotic normality, and the oracle property for the quantile penalized GEE estimators with ultra-high dimensional predictors. Moreover, we establish model-selection consistency for high-dimensional BIC. Simulation studies show the promise of the proposed approach. for this article are available online. [ABSTRACT FROM AUTHOR]