The Costs of Low Birth Weight

By D. Almond, Kenneth Y. Chay, David S. Lee. 2004

800 citations recorded by the source corpus.

Birth weight has emerged as the leading indicator of infant health and welfare and the central focus of infant health policy. This is because low birth weight (LBW) infants experience severe health and developmental difficulties that can impose enormous costs on society. But would the prevention of LBW generate equally sizable cost savings and health improvements? Estimates of the return to LBW-prevention from cross-sectional associations may be biased by omitted variables that cannot be influenced by policy, such as genetic factors. To address this, we compare the hospital costs, health at birth, and infant mortality rates between heavier and lighter infants from all twin pairs born in the United States. We also examine the effect of maternal smoking during pregnancy the leading risk factor for LBW in the United States on health among singleton births after controlling for detailed background characteristics. Both analyses imply substantially smaller effects of LBW than previously thought, suggesting two possibilities: 1) existing estimates overstate the true costs and consequences of LBW by at least a factor of four and by as much as a factor of 20; or 2) different LBW-preventing interventions have different health and cost consequences, implying that policy efforts that presume a single return to reducing LBW will necessarily be suboptimal.

Subfields: Pediatrics, Perinatology and Child Health

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Citations in the corpus

Causal Effect Inference with Deep Latent-Variable Models (2017, neutral): “We introduce a new benchmark task that utilizes data from twin births in the USA between 1989-1991 [3] 3.”
Nonparametric estimation of distributional policy effects (2010, positive): “…runs (dashed line), and the corresponding pointwise 5% and 95% quantiles (dash-dotted lines). of subsequent health problems and has even been linked to later educational attainment and labor market outcomes (see for example Almond, Chay, and Lee (2005) or Black, Devereux, and Salvanes (2007)).”
Quantity-Quality and the One Child Policy: The Only-Child Disadvantage in School Enrollment in Rural China. NBER Working Paper No. 14973. (2009, methodology): “The estimated coe¢ cients for the triple interaction terms from equation (11) are shown in Table 3, column (5).”
Weather shocks and health at birth in Colombia (2014, background): “Poor health at birth adversely affects health in childhood and adulthood (Almond et al., 2005; Black et al., 2007, Alderman et al., 2006; Almond, 2006) and educational outcomes (Behrman and Rosenzweig 2004; Glewwe et al., 2001).”
Estimating Conditional Average Treatment Effects (2014, background): “Almond, Chay, and Lee (2005), da Veiga and Wilder (2008), and Walker, Tekin, and Wallace (2009) also used variants of the unconfoundedness assumption to identify the average effect of smoking on birth weight.”
The long-run impact of a traumatic experience on risk aversion (2014, background): “There is a growing body of literature that shows that early childhood conditions are significant for subsequent life outcomes (Heckman et al., 2012; Black et al., 2007; Alderman et al., 2006; and Almond et al., 2005).”
Efficient semiparametric estimation of multi-valued treatment effects under ignorability (2010, positive): “In a recent paper, Almond et al. (2005) study the economic costs of low birth weight using different non-experimental techniques.”
Selection into Identification in Fixed Effects Models, with Application to Head Start (2019, neutral): “The main implication of SI is that under heterogeneous treatment effects, the FE estimate is no longer representative of the ATE for the sample.”
Inequality at Birth: Some Causes and Consequences (2011, neutral): “But there is reason to believe that it does not capture the full spectrum of fetal health effects (Almond, Chay, and Lee 2005).”
Doubly robust uniform confidence band for the conditional average treatment effect function (2016, methodology): “Note that the dataset was originally used in Almond et al. (2005). We restrict our sample to white and non-Hispanic mothers, and the sample size is 3754.”
GENERATIVE ADVERSARIAL NETS (2018, methodology): “Twins: This dataset is derived from all births in the USA between 1989-1991 (Almond et al. (2005)).”
The Long Term Consequences of Famine on Survivors: Evidence from a Unique Natural Experiment Using China's Great Famine (2009, background): “The estimates from equation (3) are shown in Table 4.”
Inside the War on Poverty: The Impact of Food Stamps on Birth Outcomes (2011, positive): “These estimates are roughly in line with the birth weight–neonatal mortality rate relationship estimated by Almond et al. (2005): for whites, we estimate a very similar birth weight-mortality relationship, although the relationship between birth weight and mortality we estimate for blacks is…”
Multiple Experiments for the Causal Link between the Quantity and Quality of Children (2010, neutral): “…usually have lower birth weight (LBW) than singletons, but the question of whether this matters for adult outcomes remains controversial (see, e.g Almond et al., 2005; Behrman and Rosenzweig, 2004; Conley, 2006; 28 C. Combining 2+, 3+, 4+, and 5+ Samples To further increase precision we also…”
Data Analysis Using Regression and Multilevel/Hierarchical Models: Understanding and summarizing the fitted models (2006, background): “For more on overdispersion, see Anderson (1988) and Liang and McCullagh (1993).”