Maternal health behaviors at conception and during pregnancy are important determinants of fetal growth and child development. Maternal smoking is one of the most commonly studied behavioral risk factors that affect fetal/child development and is often considered the single most important, modifiable factor affecting birth outcomes (Kramer 1987
). Prenatal and postnatal exposures to cigarette smoking are leading causes of child mortality and morbidity (DiFranza and Lew 1996
; Ebrahim, Floyd, Merritt, et al. 2000
). Prenatal smoking has also been linked to low fetal growth, low birth weight, premature births, and sudden infant death syndrome (Schoendorf and Kiely 1992
), and has been shown to increase the risk of admission to neonatal intensive care, increasing healthcare costs of the birth by $700 (Adams et al. 2002
Several observational studies have found that prenatal maternal smoking decreased birth weight by about 250 grams (Evans and Ringel 1999
; Rosenzweig 1983
). Low birth weight is an important predictor of child neurodevelopment and future health and socioeconomic status (Anderson and Doyle 2003
; Boardman et al. 2002
; Mervis et al. 1995
; Saigal et al. 2001
; Victora et al. 2008
; Wolf, Smit, and de Groot 2001
), suggesting that fetal exposure to smoking may reduce long term health and human capital through the impact of smoking on birth outcomes. Indeed, researchers have found that maternal smoking during pregnancy is associated with greater child’s behavioral risks including developing behavioral problems later in childhood (Weitzman, Gortmaker, and Sobol 1992
), participating in criminal behavior, and lifetime nicotine dependence (Buka, Shenassa, and Niaura 2003
). Maternal smoking during pregnancy has also been associated with increased risks of language problems, hyperactivity, fearfulness, and not getting along with peers (Faden and Graubard 2000
The prevalence of prenatal smoking has fallen over time but is still high with a substantial number of children exposed to tobacco pre and postnatally worldwide. For example, 13.8% of women smoked during pregnancy in 2005 in the US(Tong et al. 2009
). In Norway, the rate of smoking during pregnancy was 11 % in 2004, compared to about 21% in 1994–1995 (Eriksson et al. 1998
; Kvalvik, Skjaerven, and Haug 2008
Discovering which behavioral factors have the greatest negative effect on fetal and child development will aid policymakers in the development of interventions to reduce these negative effects (Heckman 2000
; Heckman 2008
). Given that maternal health behaviors during the prenatal period are likely to influence multiple child physical and neurological outcomes (such as birth weight and neurological development), developing interventions that address these health behaviors is likely to have large returns in child and future health and to be more cost-effective in enhancing child health than specific interventions that target child developmental problems post occurrence.
The commonly reported harmful effects of prenatal smoking on fetal growth and child health may occur via various biological pathways, including cell damage and changes to the placenta and a reduction in oxygen availability (hypoxia) to the fetus (Walsh 1994
). However, endogenous maternal selection into smoking and biased reporting of smoking behaviors complicate the estimation of the causal effects of smoking on birth outcomes(Brachet 2005
). Specifically, mothers who smoke during pregnancy are also likely to self-select into smoking based on their preferences for health and risk taking and their perceptions of fetal health endowments. These factors, typically unobserved in available data samples, are related to fetal health through other pathways besides smoking. For example, women who smoke during pregnancy may adopt other unhealthy behaviors that may also have adverse effects on the fetus (e.g. poorer nutrition or reduced prenatal care), but may also be less likely to have a family history of poor birth outcomes. Therefore, the actual contribution of smoking to child health, independently of the confounding pathways that correlate with both smoking and child health, and the direction of the potential net bias in estimating the effects of smoking on birth outcomes without accounting for non-random self-selection into smoking, is theoretically ambiguous and an open question.
Several papers have previously evaluated the effects of smoking on birth weight using a myriad of statistical and econometric methods. Most commonly, researchers employ statistical models that attempt to adjust directly for a variety of observable characteristics that may proxy for the relevant unobservable factors. These factors include other maternal behaviors besides smoking, measures of pregnancy wantedness and maternal health (Reichman et al. 2006
). Others have used propensity score matching strategies that are also limited to observable characteristics and found similar results as more traditional specifications (Almond, Chay, and Lee 2005
Several authors have used experimental or quasi-experimental designs to attempt to estimate causal effects of prenatal smoking on birth outcomes. Permutt and Hebel (1989)
use a smoking cessation intervention to introduce random variation in smoking status and find large effects of smoking cessation on birth weight (15 grams per cigarette vs. 2 grams using OLS and an overall effect of 400 grams)(Permutt and Hebel 1989
). Evans and Ringel (1999)
use state level cigarette taxes in an instrumental variable (IV) strategy and find no statistically discernable difference between 2SLS and baseline estimates(Evans and Ringel 1999
). However, the 2SLS effect estimate is 350–600 gram decrease in birth weight across several 2SLS models versus 230–250g across OLS models. Interestingly, the 2SLS estimates in both Permutt and Hebel and Evans and Ringel are larger than their OLS estimates. This is consistent with other studies that use IV estimation of smoking effects on birth weight, which also find generally larger
adverse smoking effects using IV than those found with classical single-equation models (see also (Grossman and Joyce 1990
; Lien 2005
; Rosenzweig 1983
In this paper, we employ an IV model with genetic risk factors for smoking as instruments to shed more light on the causal link between maternal smoking during pregnancy and infant birth weight.1
The goal is to identify the effects of smoking using a previously unexplored source of variation in smoking that is due to individual-level differences in genetic risk factors that predispose for smoking, in order to account for unobserved factors that are related to the choice of smoking and to birth outcomes. One strength of utilizing genetic variants as instruments is that these variants are inherited at conception and, therefore, cannot be reversely affected by smoking or other behaviors. Another advantage is that confounding factors for smoking and birth weight, such as state-level health measures, are unlikely to be correlated with genetic variants compared to other instruments, such as tax rates or smoking policies (Lawlor et al. 2008
; Smith et al. 2007
). Similar to other instruments, there are also challenges in using genetic instruments, which we describe in detail in the instrument validity section below.
Previous IV estimations of the effects of smoking have mainly utilized taxes or changes in smoking policies between states as instruments. One limitation in these analyses is that these are aggregate level measures that only utilize area-level variation in smoking and ignore within area variation due to individual-level factors. Our primary contribution is that variation in genetic markers occurs within the individual at the molecular level. Thus, the study uses a different source of variation to identify impacts. It is of interest to use different instrument sets in order to potentially estimate different local average treatment effects (LATE). We describe below how we select the genetic instruments for this analysis.
We focus our attention on birth weight as the measure of infant health, similar to most of the previous studies. Low birth weight is generally considered to be an important predictor of other health and human capital outcomes later in life. From a policy perspective, the study findings are important for developing health policies that target pharmacotherapy or raise awareness for smoking cessation and public taxation policies that aim at reducing the negative externalities of smoking, given that accurate estimation of the effects of smoking on child health is needed in order to assess the cost-effectiveness of such policies.
The remaining sections are designed as follows: Section II describes the data sources and the model used to identify the impact of prenatal smoking on birth weight, as well as a description of the study measures. Section III presents our empirical results. Section IV discusses the study findings and implications for public policy and future research studies.