Along party Lines: Examining the gubernatorial party difference in COVID-19 mortality rates in U.S. Counties.

Drawing upon the literatures on risk factors for COVID-19 and the roles of political party and political partisanship in COVID-19 policies and outcomes, this study quantifies the extent to which differences in Republican- and Democrat-governed counties' observable characteristics explain the Republican - Democrat gap in COVID-19 mortality rate in the United States. We analyze the county COVID-19 mortality rate between February 1 and December 31, 2020 and employ the Blinder-Oaxaca decomposition method. We estimate the extent to which differences in county characteristics - demographic, socioeconomic, employment, health status, healthcare access, area geography, and Republican vote share, explain the difference in COVID-19 mortality rates in counties governed by Republican vs Democrat governors. Among 3,114 counties, Republican-governed counties had significantly higher COVID-19 mortality than did Democrat-governed counties (127 ± 86 vs 97 ± 80 per 100,000 population, p < 0.001). Results are sensitive to which weights are used: of the total gap of 30.3 deaths per 100,000 population, 12.8 to 20.5 deaths, or 42.2-67.7 %, are explained by differences in observable characteristics of Republican- and Democratic-governed counties. Difference in support for President Trump between Republican- and Democrat-governed counties explains 25 % of the additional deaths in Republican counties. Policies aimed at improving population health and lowering racial disparity in COVID-19 outcomes may also be correlated with reducing the partisan gap in COVID-19 mortality.

Decomposing racial differences in adolescent smoking in the U.S.

Despite declining smoking rates in the U.S., a substantial fraction of adolescents still smoke. In addition, there are notable racial differences in adolescent smoking. We use Add Health data and apply a nonlinear decomposition method to determine the extent to which racial differences in observable characteristics account for (i) the racial smoking gaps in adolescent smoking (ages 12-18) and (ii) racial gaps in the probability of becoming a smoker in young adulthood (ages 18-24), conditional on being a non-smoker in adolescence. The model includes a host of explanatory factors, including individual, family socioeconomics, smoke exposure, school characteristics, and county crime rate. Of the 19 (9) percentage-point gap in white-black (white-Hispanic) smoking in adolescence, these factors together account for 22-28% (39-77%) of the smoking gap; and of the 18 (13) percentage-point gap in white-black (white-Hispanic) smoking up-take in young adulthood, these factors together account for 26-50% (48-100%) of the gap, depending on which set of coefficients are used for the decomposition. The biggest drivers of racial smoking gaps in adolescence are differences in friends' smoking and school peer smoking, while only school peer smoking contributes to the explained portion of racial gaps in smoking up-take in young adulthood.

What is driving the black-white difference in low birthweight in the US?

This is a first effort to quantify the contribution of different factors in explaining racial difference in low birthweight rate (LBW). Mother's health, child characteristics, prenatal care, socioeconomic status (SES), and the socioeconomic and healthcare environment of mother's community are important inputs into the birthweight production function, and a vast literature has delved into obtaining causal estimates of their effect on infant health. What is unknown is how much of the racial gap in LBW is explained by all these inputs together. We apply a nonlinear extension of the Oaxaca-Blinder method proposed by Fairlie to decompose this gap into the portion explained by differences in observed characteristics and the portion that remains unexplained. Data are obtained from several sources in order to capture as many observables as possible, although the primary data source is the Natality Detail Files. Results show that of the 6.8 percentage point racial gap in LBW, only 0.9-1.9 points are explained by white-black differences in endowments across those measures, and of those endowments, most of the gap in LBW is explained by the differences in SES. The unexplained difference is attributed to racial differences in the returns to or the marginal product of investments in infant health.

Does access to fast food lead to super-sized pregnant women and whopper babies?

Rise in the availability of fast-food restaurants has been blamed, at least partly, for the increasing obesity in the U.S. The existing studies of obesity have focused primarily on children, adolescents, and adults, and this paper extends the literature by raising a little-studied question and using nationally representative data to answer it. It examines the relationship between the supply of fast-food restaurants and weight gain of pregnant women and their newborns. I study prenatal weight gain because excessive weight gain has been linked to postpartum overweight/obesity and I study both tails of the birthweight distribution because the origin of obesity may be traced to the prenatal period and both tail outcomes have been associated with obesity later in life. I merge the 1998 and 2004 Natality Detail Files with the Area Resource File, and County Business Patterns, which provide data on the number of fast-food restaurants in the metropolitan area where the mother resides. The empirical model includes an extensive list of MSA characteristics and MSA fixed effects to control for factors that may be correlated with both health outcomes and restaurants' location decision. Results reveal that the fast-food and weight gain relationship is robust to the inclusion of these controls but these controls greatly mitigate the fast food-infant health relationship. Greater access to fast-food restaurants is positively related to mothers' probability of excessive weight gain but it does not share a statistically significant relationship with birthweight. These relationships hold in all the socioeconomic and demographic subgroups studied.

Relative deprivation and child health in the USA.

Some recent papers have suggested that relative deprivation could be negatively related to health through psychosocial stress and related behaviors. While there is a large literature on the association between absolute deprivation, i.e., income, and child health, little is known about the association between relative deprivation and child health. This paper asks: controlling for a measure of absolute deprivation, is a mother's relative deprivation related to infant health and maternal health behavior? There are many limitations regarding our measures and methods, and we interpret our results only as associations. Using US 2001 Natality Detail data, we find that pregnant women of lower socioeconomic status relative to other expectant mothers in their Metropolitan Statistical Area give birth to very slightly lighter babies and are more likely to smoke. A back-of-the envelope calculation shows the magnitude of the association we observe between relative deprivation and birthweight is close to what medical studies would predict if the probability of prenatal tobacco use were to increase by the amount we estimate.

Does government provision of healthcare explain the relationship between income inequality and low birthweight?

This paper estimates the relationship between state and county income inequality and low birthweight (LBW) in the U.S. It examines whether more unequal societies are also less healthy because such societies have lower investment in population health. The model includes an extensive list of community and individual controls and community fixed-effects. Results show that unequal states in fact have greater social investments, and absent these investments children born in such states would be more likely to be LBW. Using alternate measures of inequality reveals that income inequality in the upper tail of the income distribution is not related to LBW; but inequality in the lower tail of the income distribution is associated with increased LBW where the supply of healthcare mitigates the effect of income inequality. Consistent with prior findings, county income inequality is not significantly related to LBW.

Prenatal health investment decisions: does the child's sex matter?

Individuals invest in their own health, but children rely on parents to act on their behalf especially in the case of prenatal health. In this article, we ask, Do parents in the United States who choose to give birth allocate resources differently in the prenatal health of their sons and daughters when the sex of the child is known in advance? We pay special attention to prenatal health behaviors, which can be viewed as investment decisions, of first-generation immigrant parents from India and China, two countries with demonstrated son preference. Ultrasound receipt proxies for knowing fetal gender, enabling us to separate child sex-related biological differences from investment differences in sons' and daughters' health. There is evidence consistent with sex-selective abortions among Indian and Chinese populations, but among parents who choose to carry the pregnancy to term, our findings do not suggest that knowledge of child sex drives prenatal health investments in the United States, neither in the population as a whole nor among Indian and Chinese immigrants.