Maternal smoking as a confounder in studies of air pollution and infant mortality.
Explore the source record for details and available documents.
Air Pollutants↗
Biomedical subjects
Jennifer D Parker
Publications and source records attributed to Jennifer D Parker.
Relationships between air pollution and preterm birth in California.
Air pollution from vehicular emissions and other combustion sources is related to cardiovascular and respiratory outcomes. However, few studies have investigated the relationship between air pollution and preterm birth, a primary cause of infant mortality and morbidity. This analysis examined the effect of fine particulate matter (PM(2.5)) and carbon monoxide (CO) on preterm birth in a matched case-control study. PM(2.5) and CO monitoring data from the California Air Resources Board were linked to California birth certificate data for singletons born in 1999-2000. Each birth was mapped to the closest PM monitor within 5 miles of the home address. County-level CO measures were utilised to increase sample size and maintain a representative population. After exclusion of implausible birthweight-gestation combinations, preterm birth was defined as birth occurring between 24 and 36 weeks' gestation. Each of the 10 673 preterm cases was matched to three controls of term (39-44 weeks) gestation with a similar date of last menstrual period. Based on the case's gestational age, CO and PM(2.5) exposures were calculated for total pregnancy, first month of pregnancy, and last 2 weeks of pregnancy. Exposures were divided into quartiles; the lowest quartile was the reference. Because of the matched design, conditional logistic regression was used to adjust for maternal race/ethnicity, age, parity, marital status and education. High total pregnancy PM(2.5) exposure was associated with a small effect on preterm birth, after adjustment for maternal factors (adjusted odds ratio [AOR] = 1.15, [95% CI 1.07, 1.24]). The odds ratio did not change after adjustment for CO. Results were similar for PM(2.5) exposure during the first month of pregnancy (AOR = 1.21, 95% CI [1.12, 1.30]) and the last 2 weeks of pregnancy (AOR = 1.17, 95% CI [1.09, 1.27]). Conversely, CO exposure at any time during pregnancy was not associated with preterm birth (AORs from 0.95 to 1.00). Maternal exposure to PM(2.5), but not CO, is associated with preterm birth. This analysis did not show differences by timing of exposure, although more detailed examination may be needed.
Adolescent↗
Fine particulate matter (PM2.5) air pollution and selected causes of postneonatal infant mortality in California.
Studies suggest that airborne particulate matter (PM) may be associated with postneonatal infant mortality, particularly with respiratory causes and sudden infant death syndrome (SIDS). To further explore this issue, we examined the relationship between long-term exposure to fine PM air pollution and postneonatal infant mortality in California. We linked monitoring data for PM<or=2.5 microm in aerodynamic diameter (PM2.5) to infants born in California in 1999 and 2000 using maternal addresses for mothers who lived within 5 miles of a PM2.5 monitor. We matched each postneonatal infant death to four infants surviving to 1 year of age, by birth weight category and date of birth (within 2 weeks). For each matched set, we calculated exposure as the average PM2.5 concentration over the period of life for the infant who died. We used conditional logistic regression to estimate the odds of postneonatal all-cause, respiratory-related, SIDS, and external-cause (a control category) mortality by exposure to PM2.5, controlling for the matched sets and maternal demographic factors. We matched 788 postneonatal infant deaths to 3,089 infant survivors, with 51 and 120 postneonatal deaths due to respiratory causes and SIDS, respectively. We found an adjusted odds ratio for a 10-microg/m3 increase in PM2.5 of 1.07 [95% confidence interval (CI), 0.93-1.24] for overall postneonatal mortality, 2.13 (95% CI, 1.12-4.05) for respiratory-related postneonatal mortality, 0.82 (95% CI, 0.55-1.23) for SIDS, and 0.83 (95% CI, 0.50-1.39) for external causes. The California findings add further evidence of a PM air pollution effect on respiratory-related postneonatal infant mortality.
Air Pollutants↗
Contextual effect of income inequality on birth outcomes.
BACKGROUND: Though associations between income inequality and birth outcome have been suggested, mechanisms underlying this relationship are not known. In this analysis, we examined the relationship between income inequality and preterm birth (PTB) and post-neonatal mortality (PNM) to explore two potential mechanisms-the proposed psychosocial stress and neo-material pathways. METHODS: Data on singleton births from 1998 to 2000 were obtained from the CDC's National Center for Health Statistics' Linked Birth and Infant Death files. The Gini Index was utilized to measure income inequality and was divided into tertiles representing high, medium, and low county-level inequality. To determine the association between the birth outcomes and county income inequality and to account for clustering within counties, we employed generalized estimating equation (GEE) modelling. RESULTS: PTB increased from 8.3% in counties with low income inequality to 10.0% in counties with high inequality. The Gini Index remained modestly associated with PTB after adjusting for individual level variables and mean county-level per capita income within the total population (AOR: 1.06; 95% CI 1.03-1.09) as well as within most of the racial/ethnic groups. PNM increased from 1.15 deaths per 1000 live births in low inequality counties to 1.32 in high-inequality counties. However, after adjustment, income inequality was only associated with PNM within the non-Hispanic black population (AOR: 1.20; 95% CI 1.03-1.39). CONCLUSIONS: These findings may provide some support for the association between income inequality and PTB. Further research is required to elucidate the biological mechanisms of income inequality.
Adult↗
Air pollution and birth weight among term infants in California.
OBJECTIVE: To examine associations between birth weight and air pollution among full-term infants in California. METHODS: We matched exposure data collected from air pollution monitors for small particles (PM(2.5)) and carbon monoxide (CO) to California birth records for singleton births delivered at 40 weeks' gestation in 2000 using the locations of the monitors and mother's residence. Pollution measurements collected within 5 miles of the mother's residence, averaged for the time period corresponding to the duration of pregnancy and each trimester, were used as exposure variables. Logistic and linear regression models were used to estimate the associations between the pollution measures and 2 pregnancy outcomes: small for gestational age (SGA) and birth weight. Variations of the models were used to examine the robustness of the findings. RESULTS: The adjusted odds ratio for SGA for exposure in the highest compared with lowest quartile of PM(2.5) was 1.26 (95% confidence interval [CI]: 1.03-1.50). We found no association between CO and birth weight or SGA after controlling for maternal factors and PM(2.5) (mean birth weight difference: 2.6 g; 95% CI: -20.6 to 25.8). The difference in mean birth weight for infants with a 9-month exposure in the highest quartile of PM(2.5) compared with that of infants who were exposed in the lowest quartile was -36.1 g (95% CI: -16.5 g to -55.8 g); this difference was similar after controlling for CO. We did not find PM(2.5) exposure during a particular trimester most important for assessing birth weight; trimester-level associations were similar to those found using the 9-month exposure variable. CONCLUSIONS: We found an increased odds of SGA and a small difference in mean birth weight between infants with the highest and lowest exposures to PM(2.5) but not CO. These findings have important implications for infant health because of the ubiquitous exposure to fine particulate air pollution across the United States.
Air Pollutants↗
Comparing exposure metrics in the relationship between PM2.5 and birth weight in California.
Although studies suggest that air pollution is linked to perinatal outcomes, the geographic characterization of exposure to pollution differs between the studies. We compared neighborhood- and county-level measures of air pollution exposure, while examining the association between particulate matter less than 2.5 microm in aerodynamic diameter (PM(2.5)) and birth weight among full-term births in California in 2000. To reduce the effects of demographic variability, our analysis was limited to two populations of 8579 non-Hispanic white and 8114 Hispanic mothers who were married, between 20 and 30 years of age, completed at least a high school education, and gave birth for the first time. Measurements from the nearest monitor, and average and distance-weighted average of monitors within a 5-mile radius from each mother's residence (constituting neighborhood metrics) and the mean of monitors within each mother's county of residence were considered. PM(2.5) measurements, provided by the California Air Resources Board, were calculated to correspond to each mother's 9-month gestation period. Although metrics within the 5-mile radii and the county were highly correlated (r(2)=0.78), the county-level metric provided a stronger association between PM(2.5) and birth weight (beta=-4.04, 95% confidence interval =-6.71, -1.37) than the metric for the average of all monitors within 5-miles (beta=-1.38, 95% confidence interval =-3.36, 0.60) among non-Hispanic white mothers; similar results were observed among the Hispanic sample of mothers. Consequently, inferences from studies using different definitions of air pollution exposure may not be comparable.
Adult↗
From single-race reporting to multiple-race reporting: using imputation methods to bridge the transition.
In 1997, the Office of Management and Budget issued revised standards for the collection of race information within the Federal statistical system. One revision allows individuals to choose more than one race group when responding to Federal surveys and other Federal data collections. This paper explores methods that impute single-race categories for those who have given multiple-race responses. Such imputations would be useful when it is desired to conduct analyses involving only single-race categories, such as when trends over time are being examined by race group so that data collected under the old and new standards are being combined. The National Health Interview Survey has allowed multiple-race responses for several years, while also asking respondents to specify one race as their primary race. Exploratory analyses of data from the survey suggest that imputation methods that use demographic and contextual covariate information to predict primary race can have advantages with respect to lower bias and improved variance estimation compared to simpler methods discussed by the Office of Management and Budget. It also appears, however, that the relationships between primary race and covariates might be changing over time. Thus, caution should be exercised if an imputation model fitted to data from one time period is to be applied to data from another time period. Published in 2003 by John Wiley & Sons, Ltd.
Adolescent↗
Excessive maternal weight gain patterns in adolescents.
The objective of this study was to examine the correlates of excessive maternal weight gain among adolescent mothers in the United States. Data from the Centers for Disease Control & Prevention 2000 natality file were analyzed to examine weight gain among adolescents (< or=19 years) compared with their older counterparts (> or=20 years). Using the Institute of Medicine guidelines, we defined excessive weight gain as more than 40 pounds. Our study population was restricted to singleton births, delivered after 36 weeks of gestation, who did not live in California. Maternal weight gain distributions were tabulated by maternal age and other maternal characteristics. Demographic characteristics potentially associated with maternal weight gain were compared for adolescents and older mothers. We further evaluated the role of parity and maternal race on the relationship between excessive weight gain and maternal age. Odds ratios and 95% confidence intervals were estimated using logistic regression. Over 27% of adolescent mothers gained excessive weight during pregnancy, although approximately 18% of their older counterparts gained more than 40 pounds. The association between young maternal age and weight gain was stronger for primiparous women than multiparous women and stronger among non-Hispanic white and non-Hispanic black mothers than Hispanic mothers. Adolescents were more likely to gain excessive weight than their older counterparts in nearly all demographic categories, regardless of parity or race. Adolescents are at high risk of gaining an excessive amount of weight during pregnancy and should be monitored during pregnancy by dietetics professionals.
Adolescent↗
Mind the gap: bridge methods to allocate multiple-race mothers in trend analyses of birth certificate data.
OBJECTIVES: To examine the effects of proposed methods of redistributing multiple-race mothers to single-race categories when computing trend data from birth certificates. METHODS: Low birthweight and multiple (twin and higher-order) birth rates for California were calculated for non-Hispanic mothers from birth certificate data for 2000. Births to the 1.9% of mothers identified as multiple-race were reassigned to single-race groups according to 12 "bridging" methods. Bridge methods utilized population-based whole allocation, fractional allocation, and other methods, primarily depending on first race listed. RESULTS: For large race groups, there was little difference in low birthweight and multiple birth rates regardless of the bridge method employed. For smaller groups such as Native Hawaiians and other Pacific Islanders and American Indians/Alaska Natives, there was substantial variation by bridge method in observed rates. CONCLUSIONS: Tracking trends in birth outcomes across the change in data collection will challenge public health researchers. This paper outlines advantages and disadvantages of various bridge methods.
Adolescent↗
Disparities in exposure to air pollution during pregnancy.
Previous research shows poorer birth outcomes for racial and ethnic minorities and for persons with low socioeconomic status (SES). We evaluated whether mothers in groups at higher risk for poor birth outcomes live in areas of higher air pollution and whether higher exposure to air pollution contributes to poor birth outcomes. An index representing long-term exposure to criteria air pollutants was matched with birth certificate data at the county level for the United States in 1998-1999. We used linear regression to estimate associations between the air pollution index and maternal race and educational attainment, a marker for SES of the mother, controlling for age, parity, marital status, and region of the country. Then we used logistic regression models both to estimate likelihood of living in counties with the highest levels of air pollution for different racial groups and by educational attainment, adjusting for other maternal risk factors, and to estimate the effect of living in counties with higher levels of air pollution on preterm delivery and births small for gestational age (SGA). Hispanic, African-American, and Asian/Pacific Islander mothers experienced higher mean levels of air pollution and were more than twice as likely to live in the most polluted counties compared with white mothers after controlling for maternal risk factors, region, and educational status [Hispanic mothers: adjusted odds ratio (AOR) = 4.66; 95% confidence interval (95% CI), 1.92-11.32; African-American mothers: AOR = 2.58; 95% CI, 1.00-6.62; Asian/Pacific Islander mothers: AOR = 2.82; 95% CI, 1.07-7.39]. Educational attainment was not associated with living in counties with highest levels of the air pollution index (AOR = 0.95; 95% CI, 0.40-2.26) after adjusting for maternal risk factors, region of the country, and race/ethnicity. There was a small increase in the odds of preterm delivery (AOR = 1.05; 95% CI, 0.99-1.12) but not SGA (AOR = 0.96; 95% CI, 0.86-1.07) in a county with high air pollution. Additional risk of residing in areas with poor air quality may exacerbate health problems of infants and children already at increased risk for poor health.
Air Pollutants↗
Contribution of excess weight gain during pregnancy and macrosomia to the cesarean delivery rate, 1990-2000.
OBJECTIVE: After declining for many years, cesarean delivery rates recently increased. To explore whether this increase is associated with excess weight gain during pregnancy, resulting in macrosomic infants who require cesarean delivery, we examined trends in excess weight gain, macrosomia, and cesarean delivery. METHODS: Analysis of 1990-2000 US Natality Files of birth certificate data were restricted to first birth, singleton infants of 37 to 42 weeks' gestation to avoid confounding by repeat cesarean delivery, complications of multigestational pregnancy, and preterm and postterm birth. Excess weight gain was defined according to current guidelines (41+ lb) and macrosomia as birth weight >4000 g. RESULTS: From 1990-2000, excess weight gain rose steadily from 18.6% to 24.2%. There was a 19.3% decline in macrosomic infants among women who gained excess weight compared with an 11.9% decline among women who gained 15-40 lb, although the absolute risk remained substantially greater among women who gained excess weight (eg, 14.2% vs 7.2%, in 2000). From 1990-1997, cesarean delivery declined by 20.2% among women who gained excess weight compared with 15.7% among women who gained 15 to 40 lb. After 1997, cesarean delivery increased in all weight gain categories, and absolute risks in 2000 were 25.8% for women who gained excess weight compared with 21.6% for women who gained 15-40 lb. Overall, women who gained excess weight accounted for 24.1% of cesarean deliveries in 1990 and 28.1% in 2000. CONCLUSIONS: Excess weight gain and macrosomia do not seem to be the primary factors that contribute to the recent increase in cesarean delivery because cesarean delivery rates have increased in all weight gain categories and macrosomia rates have decreased steadily from 1990-2000. Nonetheless, women who gain excess weight account for a growing proportion of cesarean deliveries because their relative numbers have grown.
Birth Certificates↗
United States Census 2000 population with bridged race categories.
OBJECTIVES: The objectives of this report are to document the methods developed at the National Center for Health Statistics (NCHS) to bridge the Census 2000 multiple-race resident population to single-race categories and to describe the resulting bridged race resident population estimates. METHOD: Data from the pooled 1997-2000 National Health Interview Surveys (NHIS) were used to develop models for bridging the Census 2000 multiple-race population to single-race categories. The bridging models included demographic and contextual covariates, some at the person-level and some at the county-level. Allocation probabilities were obtained from the regression models and applied to the Census Bureau's April 1, 2000, Modified Race Data Summary File population counts to assign multiple-race persons to single-race categories. RESULTS: Bridging has the most impact on the American Indian and Alaska Native (AIAN) and Asian or Pacific Islander (API) populations, a small impact on the Black population and a negligible impact on the White population. For the United States as a whole, the AIAN, API, Black, and White bridged population counts are 12.0, 5.0, 2.5, and 0.5 percent higher than the corresponding Census 2000 single-race counts. At the sub-national level, there is considerably more variation than observed at the national level. The bridged single-race population counts have been used to calculate birth and death rates produced by NCHS for 2000 and 2001 and to revise previously published rates for the 1990s, 2000, and 2001. The bridging methodology will be used to bridge postcensal population estimates for later years. The bridged population counts presented here and in subsequent years may be updated as additional data become available for use in the bridging process.
Censuses↗
Implications of cleaning gestational age data.
Gestational age is an important birth characteristic examined in epidemiological studies. Though there are well-documented problems with the reporting of gestational age on birth certificates, schemes for addressing this issue have not been systematically evaluated. With singleton births from the 1995-97 US linked birth/infant death files, we compared a handful of perinatal outcome estimates derived from the resulting analytical files using two published methods often used to manage inconsistent gestational age data. The first method (Alexander et al., 1996), provides cut-points for implausible birthweight-gestational age combinations and excludes infants with birthweights outside a plausible range. The second (Zhang and Bowes, 1995), provides different cut-points for implausible birthweight-gestational age combinations and then substitutes the clinical gestational age estimate for the original value, if available, reducing the number of births at the affected gestational age, but excluding fewer births from the resulting analytical files. The Alexander method excluded 0.4 of our study population and the Zhang method reassigned and excluded 1.0 and 0.2, respectively; however, over 20 of birth records with gestational age 28-30 weeks were modified by either method. Using either method, more high-risk than low-risk and more black than white births were excluded. These differential exclusions affected corresponding perinatal outcome estimates and relative risks between maternal risk groups for preterm delivery, gestation-specific infant mortality and birthweight; overall infant mortality rates were not affected. Systematic comparisons between results of different studies will need to consider the data modifications used, the populations affected, and the outcomes assessed when drawing conclusions.
Black or African American↗
The correspondence between interracial births and multiple-race reporting.
OBJECTIVES: Race-specific health statistics are routinely reported in scientific publications; most describe health disparities across groups. Census 2000 showed that 2.4% of the US population identifies with more than 1 race group. We examined the hypothesis that multiple-race reporting is associated with interracial births by comparing parental race reported on birth certificates with reported race in a national health survey. METHODS: US natality data from 1968 through 1998 and National Health Interview Survey data from 1990 through 1998 were compared, by year of birth. RESULTS: Overall multiple-race survey responses correspond to expectations from interracial births. However, there are discrepancies for specific multiple-race combinations. CONCLUSIONS: Projected estimates of the multiple-race population can be only partially informed by vital records.
Birth Certificates↗
Family structure, socioeconomic status, and access to health care for children.
OBJECTIVE: To test the hypothesis that among children of lower socioeconomic status (SES), children of single mothers would have relatively worse access to care than children in two-parent families, but there would be no access difference by family structure among children in higher SES families. DATA SOURCES: The National Health Interview Surveys of 1993-95, including 63,054 children. STUDY DESIGN: Logistic regression was used to examine the relationship between the child's family structure (single-mother or two-parent family) and three measures of health care access and utilization: having no physician visits in the past year, having no usual source of health care, and having unmet health care needs. To examine how these relationships varied at different levels of SES, the models were stratified on maternal education level as the SES variable. The stratified models adjusted for maternal employment, child's health status, race and ethnicity, and child's age. Models were fit to examine the additional effects of health insurance coverage on the relationships between family structure, access to care, and SES. PRINCIPAL FINDINGS: Children of single mothers, compared with children living with two parents, were as likely to have had no physician visit in the past year; were slightly more likely to have no usual source of health care; and were more likely to have an unmet health care need. These relationships differed by mother's education. As expected, children of single mothers had similar access to care as children in two-parent families at high levels of maternal education, for the access measures of no physician visits in the past year and no usual source of care. However, at low levels of maternal education, children of single mothers appeared to have better access to care than children in two-parent families. Once health insurance was added to adjusted models, there was no significant socioeconomic variation in the relationships between family structure and physician visits or usual source of care, and there were no significant disparities by family structure at the highest levels of maternal education. There were no family structure differences in unmet needs at low maternal education, whereas children of single mothers had more unmet needs at high levels of maternal education, even after adjustment for insurance coverage. CONCLUSIONS: At high levels of maternal education, family structure did not influence physician visits or having a usual source of care, as expected. However, at low levels of maternal education, single mothers appeared to be better at accessing care for their children. Health insurance coverage explained some of the access differences by family structure. Medicaid is important for children of single mothers, but children in two-parent families whose mothers are less educated do not always have access to that resource. Public health insurance coverage is critical to ensure adequate health care access and utilization among children of less educated mothers, regardless of family structure.
Adolescent↗
Methodologic implications of allocating multiple-race data to single-race categories.
OBJECTIVE: To illustrate methods for comparing race data collected under the 1977 Federal Office of Management and Budget (OMB) directive, known as OMB-15, with race data collected under the revised 1997 OMB standard. DATA SOURCES/STUDY SETTING: Secondary data from the 1993-95 National Health Interview Surveys. Multiple-race responses, available on in-house files, were analyzed. STUDY DESIGN: Race-specific estimates of employer-sponsored health insurance were calculated using proposed allocation methods from the OMB. Estimates were calculated overall and for three population subgroups: children, those in households below poverty, and Hispanics. PRINCIPAL FINDINGS: Although race distributions varied between the different methods, estimates of employer-sponsored health insurance were similar. Health insurance estimates for the American Indian/Alaska Native group varied the most. CONCLUSIONS: Employer-sponsored health insurance estimates for American Indian/Alaska Natives from data collected under the 1977 OMB directive will not be comparable with estimates from data collected under the 1997 standard. The selection of a method to distribute to the race categories used prior to the 1997 revision will likely have little impact on estimates of employer-sponsored health insurance for other groups. Additional research is needed to determine the effects of these methods for other health service measures.
Child↗
Multiple-race mortality data for California, 2000-2001.
OBJECTIVES: To examine mortality rates and quality of race reporting for multiple-race individuals in California using the new multiple-race data available on the death certificate. METHODS: Death date were drawn from California vital statistics for 2000 and 2001. Denominator data were drawn from the 2000 census Modified Race Data Summary File. The authors calculated mortality rates and relative standard errors for multiple-race individuals as a whole and by county, and for the three largest reported multiple-race groups (African American and white, American Indian/Alaska Native and white, and Asian and white). RESULTS: Decedents reported to be of more than one race were disproportionately young, Hispanic, male, and never-married. Age-adjusted mortality rates for multiple-race groups were approximately one-sixth as high as rates for single-race individuals. There was substantial variability in rates for multiple-race decedents according to county of residence. CONCLUSIONS: Mortality rates for multiple-race people were implausibly low, and death certificates for multiple-race individuals were geographically clustered. Race reporting on death certificates will need to be improved before accurate death rates can be calculated for those of multiple races.
Adolescent↗
Bridging between two standards for collecting information on race and ethnicity: an application to Census 2000 and vital rates.
OBJECTIVES: The 2000 Census, which provides denominators used in calculating vital statistics and other rates, allowed multiple-race responses. Many other data systems that provide numerators used in calculating rates collect only single-race data. Bridging is needed to make the numerators and denominators comparable. This report describes and evaluates the method used by the National Center for Health Statistics to bridge multiple-race responses obtained from Census 2000 to single-race categories, creating single-race population estimates that are available to the public. METHODS: The authors fitted logistic regression models to multiple-race data from the National Health Interview Survey (NHIS) for 1997-2000. These fitted models, and two bridging methods previously suggested by the Office of Management and Budget, were applied to the public-use Census Modified Race Data Summary file to create single-race population estimates for the U.S. The authors also compared death rates for single-race groups calculated using these three approaches. RESULTS: Parameter estimates differed between the NHIS models for the multiple-race groups. For example, as the percentage of multiple-race respondents in a county increased, the likelihood of stating black as a primary race increased among black/white respondents but decreased among American Indian or Alaska Native/black respondents. The inclusion of county-level contextual variables in the regression models as well as the underlying demographic differences across states led to variation in allocation percentages; for example, the allocation of black/white respondents to single-race white ranged from nearly zero to more than 50% across states. Death rates calculated using bridging via the NHIS models were similar to those calculated using other methods, except for the American Indian/Alaska Native group, which included a large proportion of multiple-race reporters. CONCLUSION: Many data systems do not currently allow multiple-race reporting. When such data systems are used with Census counts to produce race-specific rates, bridging methods that incorporate geographic and demographic factors may lead to better rates than methods that do not consider such factors.
Adolescent↗