110 VOLUME 116 | NUMBER 1 | January 2008 • Environmental Health Perspectives

Research | Children’s Health

Several studies have found a relationship

between particulate matter (PM) air pollution

and infant mortality in countries with relatively high levels of PM air pollution as well

as in countries with lower pollution levels,

such as Canada and the United States (Bobak

and Leon 1999; Ha et al. 2003; Lipfert et al.

2000; Loomis et al. 1999; Ritz et al. 2006;

Woodruff et al. 1997, 2006) These studies

suggest that PM air pollution is more strongly

associated with postneonatal mortality

(deaths occurring after 28 days of life) than

with neonatal mortality (deaths occurring up

to 28 days of life) and that the association

with postneonatal mortality appears to be

specific to respiratory causes (Bobak and Leon

1999; Ha et al. 2003). However, a number of

questions remain about the infant mortality

and PM air pollution relationship and the

role of other air pollutants as either potential

confounders of the relationship or as independent predictors of infant mortality.

Until recently, most studies of air pollution and postneonatal infant mortality have

focused on larger particles, either measured as

total suspended particles or particles with an

aerodiameter of ≤ 10 μm (PM10) (Bobak and

Leon 1999; Ha et al. 2003; Lipfert et al.

2000; Ritz et al. 2006; Woodruff et al. 1997).

Although monitoring of smaller particles

measuring ≤ 2.5 μm (PM2.5) has become

more widespread, only one study in California

has evaluated PM2.5 in relation to respiratory

related infant mortality; results support a positive association (Woodruff et al. 2006).

Although many studies in adults suggest that

PM2.5 is more strongly associated with respiratory and cardiovascular morbidity and mortality than PM10, other studies have found larger

particles to be important for certain outcomes

(Brunekreef and Forsberg 2005; Pope and

Dockery 2006). 

In addition, few studies have evaluated

the contribution of other pollutants to infant

mortality, either on their own or as confounders of the association between particles

and infant mortality. A study in the Czech

Republic, examining nitrogen dioxide and

sulfur dioxide, did not find either pollutant

significantly associated with postneonatal respiratory deaths after including the other study

pollutants in the model (Bobak and Leon

1999). In a study of U.S. infants born in

1990, controlling for carbon monoxide in the

regression models did not affect the observed

relationship between PM and infant mortality

(Lipfert et al. 2000). Another study in

Southern California has found some suggestion of an independent effect of CO on respiratory postneonatal infant mortality and an

association between NO2 and sudden infant

death syndrome (SIDS) (Ritz et al. 2006). 

Finally, although relatively consistent

results have been found for PM and respiratory postneonatal infant mortality, varying

results have been found for the association

between PM and SIDS. PM10 had been found

in earlier studies to be associated with SIDS in

the United States (Lipfert et al. 2000;

Woodruff et al. 1997). However, a study in

Canada found that short-term increases in

NO2 and SO2, but not PM2.5, were associated

with SIDS between 1984 and 1999 (Dales

et al. 2004). Similarly, a recent analysis of

births in California during 1999–2000 did

not find a relationship between PM2.5 and

SIDS (Woodruff et al. 2006). 

Given the uncertainty in findings for different particle size (coarse vs. fine), the varied

findings for studies with multiple pollutants,

and the variability in the results for SIDS,

further evaluation is warranted. In this study,

we addressed these issues and evaluated the

role of chronic exposure to gaseous air pollutants (CO, SO2, and ozone) and different

particle size (both PM2.5 and PM10) in a

more contemporary national data set. We

used linked infant birth–death records for

infants born in the United States between

1999 and 2002 to examine the relationships

between these air pollutants and postneonatal

respiratory and SIDS infant mortality.

Methods

Study population. We obtained linked birth

and infant death files from the National

Center for Health Statistics, which consist of

birth certificate data linked to death certificates for those infants who die within the first

year of life, for all births during 1999–2002

(National Center for Health Statistics 2005).

Births in counties with < 250,000 residents

were not eligible for our study population

Address correspondence to T.J. Woodruff, Institute

for Health Policy Studies, 3333 California St., Suite

265, San Francisco, CA 94118 USA. Telephone:

(415) 476-1890. Fax: (415) 476-0705. E-mail:

woodrufft@obgyn.ucsf.edu

*This work was conducted primarily while at the

U.S. Environmental Protection Agency.

The findings and conclusions in this article are

those of the authors and do not necessarily represent

the views of the U.S. Environmental Protection

Agency or the National Center for Health Statistics,

Centers for Disease Control and Prevention; reference to commercial products or trade names does not

constitute endorsement or recommendation for use. 

The authors declare they have no competing

financial interests.

Received 17 April 2007; accepted 23 October 2007.

Air Pollution and Postneonatal Infant Mortality in the United States, 1999–2002

Tracey J. Woodruff,1* Lyndsey A. Darrow,2 and Jennifer D. Parker3

1Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, California, USA;

2Department of Epidemiology, Emory University, Atlanta, Georgia, USA; 3National Center for Health Statistics, Centers for Disease

Control and Prevention, Hyattsville, Maryland, USA 

OBJECTIVE: Our goal was to evaluate the relationship between cause-specific postneonatal infant

mortality and chronic early-life exposure to particulate matter and gaseous air pollutants across the

United States.

METHODS: We linked county-specific monitoring data for particles with aerodiameter of ≤ 2.5 μm

(PM2.5) and ≤ 10 μm (PM10), ozone, sulfur dioxide, and carbon monoxide to birth and death

records for infants born from 1999 to 2002 in U.S. counties with > 250,000 residents. For each

infant, we calculated the average concentration of each pollutant over the first 2 months of life. We

used logistic generalized estimating equations to estimate odds ratios of postneonatal mortality for

all causes, respiratory causes, sudden infant death syndrome (SIDS), and all other causes for each

pollutant, controlling for individual maternal factors (race, marital status, education, age, and primiparity), percentage of county population below poverty, region, birth month, birth year, and other

pollutants. This analysis includes about 3.5 million births, with 6,639 postneonatal infant deaths.

RESULTS: After adjustment for demographic and other factors and for other pollutants, we found

adjusted odds ratios of 1.16 [95% confidence interval (CI), 1.06–1.27] for a 10-μg/m3 increase in

PM10 for respiratory causes and 1.20 (95% CI, 1.09–1.32) for a 10-ppb increase in ozone and

deaths from SIDS. We did not find relationships with other pollutants and for other causes of

death (control category). 

CONCLUSIONS: This study supports particulate matter air pollution being a risk factor for

respiratory-related postneonatal mortality and suggests that ozone may be associated with SIDS in

the United States.

KEY WORDS: carbon monoxide, ozone, particulate matter air pollution, postneonatal infant mortality, respiratory-related deaths, sudden infant death syndrome, sulfur dioxide. Environ Health

Perspect 116:110–115 (2008). doi:10.1289/ehp.10370 available via http://dx.doi.org/ [Online

24 October 2007]
because these counties are not identified on

public-use files. We limited eligible births for

our study to singleton births with known birth

order, known maternal race, known maternal

education, known marital status, known

maternal age, known birth weight, and a

reported gestational age of up to 44 weeks.

Maternal race and Hispanic origin were collapsed into a single categorical variable with

three levels: non-Hispanic African American

(hereafter black), Hispanic, and non-Hispanic

white (hereafter white). Asian and American

Indian deaths were excluded from the analyses

because of small numbers of infant deaths. We

did not include infants who died in the neonatal period (before 28 days) as eligible births

because these deaths often happen before the

infant leaves the hospital and are often attributed to pregnancy complications or other factors intrinsically related to the infant. Finally,

we excluded postneonatal deaths if the residential county at birth did not match the residential county at death. These criteria gave an

eligible study population of 7,991,974 births

of 16,066,160 births during the study period.

The decrease was attributed primarily to the

exclusion of births in counties containing

< 250,000 residents.

Of the postneonatal deaths in our study

population, about 50% of the infants died

between 28 days and 3 months of age, about

30% died between 3 and 6 months, and the

remaining 20% of infants died between

6 months and 1 year of age; this distribution

of age of death was similar to that for all postneonatal deaths in the United States in 2002

(data not shown).

Exposure assessment. PM10, PM2.5, O3,

CO, and SO2 monitoring data for 1999–2002

were obtained from the U.S. Environmental

Protection Agency (2004). Both PM10 and

PM2.5 were typically measured continuously

for 24 hr once every 6 days. Gaseous pollutant

measurements were made daily. For O3, we

used the 24-hr daily average; long-term averages based on the 24-hr or maximum daily

8-hr average are highly correlated (data not

shown). To focus on pollution monitors most

likely to reflect population exposures, we

excluded monitors intended to capture

extreme downwind/upwind pollutant levels,

background levels, maximum levels, specific

source impacts, and economic impacts.

To calculate chronic exposures for our

study population, we matched eligible births

with the pollutant data by mother’s county of

residence. For each infant, we calculated the

average concentration of each pollutant over

the first 2 months of life as a measure of

chronic exposure. Monthly averages were

calculated only if there were at least three

available measures for PM and at least 15 available measures for the gaseous pollutants over

the course of the month. Infants without air

pollution measures for all pollutants for both

of the first 2 months of life were excluded.

After considering the use of other exposures,

the 2-month exposure window was considered

appropriate because a) a large number of postneonatal infant deaths occur within 2 months;

b) we were able to assign comparable exposures

to the deaths and the surviving infants; c) larger

windows of exposure time would have reduced

the number of births in the study due to missing data, and a shorter window may not have

adequately represented exposure; d) a 2-month

average for the pollutants is highly correlated

with the annual average, suggesting that different metrics of chronic exposure would not produce significantly different results (data not

shown); and e) previous analyses have found

that using longer windows with declining levels

of particulate matter can bias the results

(Woodruff et al. 1997).

These exclusions led to a final study population of 3,583,495 births, including 6,639

postneonatal deaths occurring in 96 counties

throughout the United States. All of these 96

counties were classified by the Office of

Management and Budget as metropolitan

counties, which are defined as a) central counties with one or more urbanized areas, and

b) outlying counties that are economically tied

to the core counties as measured by work

commuting (U.S. Department of Agriculture

Economic Research Service 2003).

Infant outcomes. We obtained International

Classification of Diseases, 10th Revision (ICD-10)

(World Health Organization 1993) codes for

the underlying cause of death from the death

certificate information included in the linked

birth and death records. Respiratory mortality

primarily included underlying cause of death

codes from Chapter 10, “Diseases of the

Respiratory System” (J000-99), plus deaths

coded P27.1 [bronchopulmonary dysplasia

(BPD)]. SIDS was defined as R95, and

“Other ill-defined and unspecified causes of

mortality” (referred to in this analysis as “illdefined”) were defined as R99. In addition, we

evaluated all other deaths (any death not classified as respiratory, cardiovascular, SIDS, or

ill-defined) as a control category. Finally, we

further examined the SIDS and other illdefined cause of death by evaluating them

together. We combined the category of SIDS

and ill-defined deaths based on a recent analysis by Malloy and MacDorman (2005), which

suggested that during our study period, many

SIDS deaths may have been classified as R99. 

Analysis. Because the independence

assumption needed for ordinary logistic

regression may be violated by inclusion of

county-level variables (both pollution exposures and census-level covariates) that can lead

to within-county correlation among births,

we used logistic regression that incorporated

generalized estimating equations (GEE) to

estimate the odds ratios (ORs) for all-cause

and cause-specific postneonatal mortality by

exposure to air pollution (SAS Institute Inc.,

Cary, NC) (Zeger and Liang 1986). An

exchangeable correlation structure was

assumed for the GEE models, which is appropriate when there is no time dependence

among the births within county and any

ordering of the births within county is valid

within the data (Hardin and Hilbe 2003). 

All air pollution exposures were modeled

using a continuous, linear form. We evaluated

the appropriateness of a linear form from analysis based on quartiles of exposure, and determined the linear form as a reasonable

assumption (data not shown). Several covariates

were included in the regression models to

obtain adjusted estimates. Maternal characteristics from the birth certificate were maternal

race/ethnicity (black, white, Hispanic), marital

status, age (< 20 years, 20–34 years, ≥ 35 years),

education (< 12 years, 12 years, 13–15 years,

and > 15 years), and primiparity (first born).

Perinatal research has shown that neighborhood-level socioeconomic status (SES) variables in addition to individual-level covariates

from the birth certificate can influence perinatal outcomes (Pearl et al. 2001). To control

for potential additional confounding that may

not be captured by individual-level variables

on the birth certificate, we included countylevel poverty and per capita income levels

from the U.S. Census in the model (U.S.

Census Bureau 2000). We included year and

month of birth dummy variables to account

for time trend and seasonal effects. Finally, we

controlled for region of the country, to

account for potential confounding by population and PM composition variation, by classifying infants into one of six U.S. regions

(Southern California, Northwest, Southeast,

Southwest, Northeast, and Midwest) based on

the regions defined in the National Morbidity,

Mortality, and Air Pollution Study (Samet

et al. 2000).

We calculated adjusted and unadjusted

ORs for each pollutant in single-pollutant

models for overall postneonatal mortality and

for each cause of death. We compared these

estimates to ORs for each pollutant calculated

from multipollutant models to assess potential confounding of copollutants. However,

we did not include both PM2.5 and PM10 in

the same model because PM2.5 is a component of PM10. All ORs are reported after

adjustment for the maternal characteristics

and spatial and temporal factors described

above. In general, adjusting for all the potential confounders in the model slightly

decreased the ORs (≤ 1% decrease; unadjusted data not shown). ORs are also reported

for an interquartile range (IQR) increase in

the pollutant to help standardize comparisons

across pollutants. 

Air pollution and infant mortality

Environmental Health Perspectives • VOLUME 116 | NUMBER 1 | January 2008 111
Results

Of the 6,639 infant deaths in our data set,

there were 576 deaths from respiratory causes,

1,379 deaths from SIDS, 755 deaths from illdefined causes, and 3,622 deaths due to other

causes. Our study cohort was demographically similar to the eligible births in the

United States, though we had a slightly

higher percentage of mothers with < 12 years

of education and a slightly higher percentage

of Hispanic and black mothers (with a complementary decrease in white mothers)

(Table 1). 

The median pollutant concentrations for

survivors and deaths are given in Table 2. The

exposure measurements were not highly correlated with each other (Table 3), the

strongest being a negative correlation between

CO and O3 (–0.46), reducing the potential

for colinearity in multipollutant models.

We found a statistically significant relationship between PM10 and respiratory-related

causes of death in the single-pollutant models

(Table 4). For a 10-μg/m3 increase in PM10,

rather than the IQR increase shown in Table

4, the odds of respiratory-related death

increased 16% [OR = 1.16; 95% confidence

interval (CI), 1.06–1.27]. There were elevated,

but not statistically significant, relationships

between respiratory-related postneonatal mortality and both PM2.5 and CO in single-pollutant models (Table 4); there were no

associations between respiratory deaths and

either O3 or SO2. The relationship between

PM10 and respiratory-related postneonatal

mortality remained elevated and significant in

the multipollutant model (Table 5). No other

relationships in the multipollutant model were

highly elevated or significant for respiratoryrelated postneonatal mortality (Table 5). 

For SIDS, only O3 was associated with a

significant increased risk in the single-pollutant models (Table 4). For a 10-ppb increase

in average O3 levels in the first 2 months of

life, the odds of SIDS mortality increased 20%

(OR = 1.20; 95% CI, 1.09–1.32). In the multipollutant model, the OR for SIDS and O3

was not substantially lower than that found in

the single-pollutant model (Table 5). We

found elevated ORs between ill-defined cause

of death and both PM2.5 (OR = 1.15; 95%

CI, 0.95–1.38) and PM10 (OR = 1.13; 95%

CI, 0.99–1.30) (for a 10-μg/m3 increase). 

In single-pollutant models, there were no

relationships between any of the pollutants

and other causes of death (the control category) (Table 4). However, there were slightly

elevated ORs for PM10, PM2.5, O3 and all

causes of death, likely driven by the observed

cause-specific relationships between PM and

respiratory causes and O3 and SIDS (Table 4). 

To assess the robustness of the reported

findings, we conducted further analyses of the

PM10 and respiratory postneonatal deaths and

O3 and SIDS. The relationship between O3

and SIDS could be influenced by residual

confounding by season, despite controlling

for month of birth in the models. SIDS

deaths follow a temporal pattern, with the

lowest percent of annual SIDS deaths occurring in the spring (19%) and the highest percent occurring in the fall (30%) and winter

(25%); O3 concentrations are highest in the

summer. Therefore, we examined the relationship between SIDS deaths and O3 by season of birth (Table 6) and found that the

ORs were generally consistent among the seasons, with a slight increase for those babies

born in the summer. 

We then evaluated the relationship

between PM10 and BPD (ICD-10 code

P2.71). Previous studies in California had

identified a higher association between BPD

and particulate matter, suggesting that infants

with BPD may have particular susceptibility

to PM (Ritz et al. 2006; Woodruff et al.

2006) because they are most often born premature and have underlying pulmonary

pathology. We found a similar but nonsignificant OR for the 158 deaths coded as BPD

(OR = 1.19; 95% CI 0.85–1.65; IQR, multipollutant model) compared with all postneonatal respiratory deaths. 

Next, we stratified by birth weight to

assess potential increased susceptibility for

low-birth-weight babies. For respiratory postneonatal deaths and PM10, we found an OR

for normal-birth-weight babies of 1.19 (95%

CI, 1.05–1.36; IQR, 241 deaths) and for

Woodruff et al.

112 VOLUME 116 | NUMBER 1 | January 2008 • Environmental Health Perspectives

Table 1. Characteristics of births in U.S. population, eligible births, and study sample for singleton infants:

United States, 1999–2002.

Birthsa Eligible birthsb Study cohortc Deaths

Maternal factors (n = 16,066,160) (n = 7,991,974) (n = 3,590,134) (n = 6,639)

Age (mean years) 27.2 27.6 27.3 25.3

Married (%) 66.6 64.5 61.8 39.7

Parity (%)

First birth 39.8 40.4 39.8 35.1

Missing 0.4 0 0 0

Education [years (%)]

< 12 21.3 23.5 27.6 38.7

12 31.2 29.7 29.9 34.1

13–15 21.4 20.8 19.9 16.9

> 15 24.6 26.1 22.7 10.3

Missing (%) 1.5 0 0 0

Race/ethnicity (%) 

Black 14.8 18.5 18.8 39.8

Hispanic 20.6 29.9 37.3 29.4

White 58.8 51.6 43.8 30.9

Asian/Pacific Islander 4.8 0 0 0

American Indian 1.0 0 0 0

aSingleton births in United States 1999–2002 excluding those in U.S. territories. bEligible infants were born and resided in a

county with > 250,000 people; were singletons; had complete information on birth weight, gestational age (≤ 44 weeks),

race, maternal education, maternal age, marital status, and parity; and lived for at least 28 days. cEligible births that could

be linked to PM2.5, PM10, O3, SO2, and CO monitoring data were included in this study cohort.

Table 2. Median and IQR (25th–75th percentiles) of PM10, PM2.5, SO2, O3, and CO concentrations for survivors and specific causes of postneonatal infant death in

the study population for 1999–2002.

Population subset No. PM10 (μg/m3) PM2.5 (μg/m3) CO (ppm) SO2 (ppb) O3 (ppb)

Survivors 3,583,495 28.9 (23.3–34.4) 14.8 (11.7–18.7) 0.67 (0.48–0.87) 2.81 (1.64–4.35) 26.6 (19.6–32.2)

All causes of death 6,639 29.1 (23.9–34.5) 14.9 (12.0–18.6) 0.70 (0.48–0.87) 3.14 (1.79–4.83) 26.4 (19.8–32.0)

Respiratorya 576 29.8 (24.3–36.5) 14.8 (11.5–18.5) 0.72 (0.52–0.93) 3.01 (1.85–4.63) 25.8 (19.7–31.6)

SIDSb 1,379 28.6 (23.5–33.8) 14.5 (12.0–17.5) 0.63 (0.46–0.83) 3.42 (1.92–5.10) 27.4 (20.7–32.7)

SIDS + ill-definedc 2,134 28.8 (23.9–33.9) 14.8 (12.1–18.5) 0.64 (0.47–0.85) 3.13 (1.80–4.90) 26.7 (20.0–32.1)

Other causesd 3,622 29.2 (23.9–34.5) 14.9 (12.0–18.6) 0.67 (0.49–0.88) 3.17 (1.78–4.79) 26.2 (19.6–32.0)

aICD-10 codes J000-J984, P271. bICD-10 code R95. cICD-10 codes R95 and R99. dICD-10 code not in respiratory, SIDS, ill-defined or cardiac-related (codes I219-I999) (ICD-10, World

Health Organization 1993).

Table 3. Spearman correlation coefficients between

PM10, PM2.5, SO2, O3, and CO concentrations of average first 2 months of exposure for infants born

1999–2002 in the United States. 

PM10 PM2.5 CO SO2 O3

PM10 1

PM2.5 0.34 1

CO 0.18 0.35 1

SO2 0.00 0.21 0.27 1

O3 0.20 –0.10 –0.46 –0.22 1
low-birth-weight babies 1.12 (95% CI,

0.95–1.31; IQR, 335 deaths). We found for

O3 and SIDS an OR for low-birth-weight

babies of 1.33 (95% CI, 0.94–1.88; IQR,

245 deaths) and an OR for normal-birthweight babies of 1.19 (95% CI, 1.01–1.39;

IQR, 1,134 deaths). 

We also examined the subset of birth

records with complete information on maternal cigarette smoking to assess potential confounding by maternal smoking. As we have

reported elsewhere, controlling for maternal

smoking in the model had no effect on the

parameter estimates for any of the pollutants

(Darrow et al. 2006). We also evaluated the

effect of removing the variable for region in

the model for postneonatal respiratory deaths,

under the possibility that region is not a confounding factor. This produced an increased

OR for PM10 of 1.30 (95% CI, 1.04–1.61)

for a 10-μg/m3 increase. There were no significant relationships for the other pollutants.

We examined the ORs for increasing

quartiles of exposures, and found that infants

in the highest quartile of exposure had elevated odds of respiratory mortality, compared

with infants in the lowest quartile of exposure

both for PM2.5, of 1.39 (95% CI, 1.04–1.85),

and for PM10, 1.31 (95% CI, 1.00–1.71),

with weaker responses at the lower exposure

levels (data not shown for other quartiles).

There was a monotonic increase in odds of

SIDS for each quartile of O3 exposure compared with the lowest quartile (highest quartile

OR = 1.51; 95% CI, 1.17–1.96). No other

pollutants had elevated ORs in the highest to

lowest quartile comparisons.

Finally, we examined only those deaths

that occurred within the first 90 days, which

most closely matched our exposure metric of

the average over the first 2 months of life. We

found for PM10 and respiratory-related deaths

an adjusted OR of 1.25 (95% CI, 1.06–1.47

for an IQR, 249 deaths). For O3 and SIDS

the adjusted OR was 1.33 (95% CI,

1.13–1.57 for an IQR, 731 deaths). 

Discussion

A recent review of air pollution and children’s

health in Europe by the World Health

Organization concluded that “the evidence is

sufficient to infer a causal relationship

between particulate air pollution and respiratory deaths in the post-neonatal period”

(World Health Organization 2005). This

study, in conjunction with previous U.S.

studies, suggests this statement remains true

at PM levels found in the United States. 

Our study builds on previous large infant

cohort studies by adding additional features to

the analysis. We have assessed both sizes of particulates and other air pollutants in a national

study. We examined the role of air pollution in

SIDS, both over the whole study period and by

season; this contemporary analysis is important

in light of the changing patterns of SIDS in the

last 15 years. We have controlled for additional

variables—both individual maternal characteristics and contextual SES variables—although

these factors had little effect on the reported

associations. The observed relationships

between PM10 and respiratory postneonatal

mortality and O3 and SIDS remain relatively

robust to model alternatives.

Several analytic decisions could have

influenced our study population and results.

We evaluated those infants that could be

linked to multiple pollutants, rather than

focusing on the larger group of infants living

in counties with just PM monitors, thus

reducing our study sample. Studies comparing populations covered by multiple monitors

versus those covered by just PM monitors

have found that the relationship between PM

and general health and birth weight varies

only slightly depending on which population

is evaluated (Parker and Woodruff, in press;

Parker et al., in press). However, the smaller

study size does limit our ability to fully evaluate regional difference, such as from variation

in populations or PM composition, and to

completely characterize the relationship in

other parts of the country. This should be

explored in future studies. 

In addition, the maternal demographics

of our study population, though similar to

those for all births, does have a slightly higher

proportion of women who are at greater risk

of adverse birth outcomes (more women are

Air pollution and infant mortality

Environmental Health Perspectives • VOLUME 116 | NUMBER 1 | January 2008 113

Table 4. Adjusteda ORs for single-pollutant models and selected causes of postneonatal infant mortality in the United States, 1999–2002.

OR for an IQR increase (95% CI)

PM10 (μg/m3

) PM2.5 (μg/m3) CO SO2 O3

Cause of death (IQR 11 μg/m3) (IQR 7 μg/m3) (IQR 0.39 ppm) (IQR 2.7 ppb) (IQR 12.6 ppb)

All causes 1.04 (0.99–1.10) 1.04 (0.98–1.11) 1.01 (0.95–1.07) 0.96 (0.91–1.02) 1.05 (0.98–1.13)

Respiratoryb 1.18 (1.06–1.31) 1.11 (0.96–1.29) 1.14 (0.93–1.40) 1.05 (0.94–1.18) 0.92 (0.76–1.10)

SIDSc 1.02 (0.89–1.16) 1.01 (0.86–1.20) 0.88 (0.76–1.03) 0.95 (0.86–1.04) 1.28 (1.13–1.46)

Ill-defined + SIDSd 1.06 (0.97–1.16) 1.06 (0.97–1.17) 0.93 (0.84–1.02) 0.95 (0.88–1.04) 1.14 (1.04–1.26)

Other causese 1.02 (0.96–1.07) 1.03 (0.96–1.12) 1.02 (0.97–1.07) 0.98 (0.92–1.04) 1.00 (0.92–1.09)

aAdjusted for individual maternal factors [race/ethnicity (black, white, Hispanic), marital status, maternal education (< 12, 12, 13–15, > 15 years), maternal age (< 20, 20–34, > 35 years),

primiparity], percentage population below poverty, region, birth month, and birth year. bICD-10 codes J000-J984, P271. cICD code R95. dICD-10 code R99 or R95. eICD-10 code not in respiratory, SIDS, ill-defined or cardiac-related (codes I219-I999) (ICD-10, World Health Organization 1993).

Table 5. Adjusteda ORs for multipollutant models for selected causes of postneonatal infant mortality in the United States, 1999–2002.

OR for an IQR increase (95% CI)

Cause of PM10 (μg/m3) PM2.5 (μg/m3) CO SO2 O3

postneonatal death (IQR 11 μg/m3) (IQR 7 μg/m3) (IQR 0.39 ppm) (IQR 2.7 ppb) (IQR 12.6 ppb)

Respiratoryb

PM10, CO, O3, SO2 1.16 (1.04–1.30) 1.02 (0.89–1.15) 1.07 (0.88–1.29) 0.92 (0.77–1.10)

PM2.5, CO, O3, SO2 1.05 (0.89, 1.24) 1.02 (0.90–1.16) 1.11 (0.88–1.39) 0.95 (0.79–1.14)

SIDSc

PM10, CO, O3, SO2 1.02 (0.90–1.16) 0.96 (0.87–1.06) 0.91 (0.78–1.05) 1.24 (1.08–1.44)

PM2.5, CO, O3, SO2 1.04 (0.87, 1.23) 0.96 (0.87–1.06) 0.90 (0.77–1.06) 1.24 (1.07–1.43)

aAdjusted for individual maternal factors [race/ethnicity (black, white, Hispanic), marital status, maternal education (< 12, 12, 13–15, > 15 years), maternal age (< 20, 20–34, > 35 years),

primiparity], percentage population below poverty, region, birth month, and birth year. bICD-10 codes J000-J984, P271. cICD-10 code R95 (ICD-10, World Health Organization 1993). 

Table 6. Adjusteda ORs for an IQR increase in O3 and postneontal infant mortality due to SIDS in the United

States by season of birth. 

Dec–Feb Mar–May June–Aug Sept–Nov

OR for 12.6-ppb increase in O3 (95% CI) 1.24 (0.73–2.10) 1.21 (0.85–1.70) 1.43 (1.19–1.73) 1.21 (0.84–1.74)

No. of deaths 246 358 449 326

aAdjusted for individual maternal factors [race (black, white, Hispanic), marital status, maternal education (< 12, 12, 13–15,

> 15 years), maternal age (< 20, 20–34, > 35 years), primiparity], percentage of population below poverty, region, birth

month, and birth year.
unmarried, of lower education, and black),

and are at higher risk of living in an area of

poor air quality (Woodruff et al. 2003). Some

residual confounding could be influencing

our observed results after we controlled for

individual-level and contextual-level SES factors, though accounting for these factors did

not significantly alter effect estimates. 

A recent study of infant deaths in

Southern California found a relationship

between CO concentrations in the last 2

weeks of life and respiratory postneonatal

mortality (Ritz et al. 2006). However, in our

study, we did not observe a relationship

between postneonatal respiratory mortality

and early-life exposure to CO. This discrepancy may be explained partly by differences in

exposure metrics. We use a measure that is

larger spatially (county averages vs. the closest

monitor in Ritz et al.) and temporally different (we used a more chronic measure, average

first 2 months of exposure, and Ritz et al.

used a more acute measure, average of the last

weeks before death). CO may have a more

acute effect, or a more refined geographic

scale may be needed to better analyze the

potential role of this pollutant. 

We examined whether a particular respiratory condition, BPD, might have increased

susceptibility to exposure to PM, as suggested

by two recent analyses in California (Ritz

et al. 2006; Woodruff et al. 2006). The OR

for this outcome suggested an increased but

nonsignificant risk of mortality for exposure

to PM10 (data not shown). However, the

increased OR for BPD found in this study

was not as great as in the studies in California.

This could be attributed to regional differences in coding for cause of death or regional

variation in PM composition. 

There remains uncertainty as to which

particles are related to respiratory postneonatal infant mortality. We found that PM10, but

not PM2.5, was associated with respiratory

infant mortality, though we found a relationship for the highest quartile of PM2.5 exposure. A similar source of pollution may be

contributing to both PM10 and PM2.5 in this

study, such as combustion-related sources,

because the study area includes only urban

counties. Several studies suggest the coarse

fraction of PM10 (PM 2.5–10 μm in diameter) may be responsible for some of the

observed associations between PM10 and

other health outcomes. Using time-series and

case–crossover analyses, Lin et. al. (2002)

observed a relationship between asthma hospitalization and coarse PM; no relationship

was observed with either PM10 or PM2.5. A

recent review of the health effects of coarse

PM concluded that compared with fine PM,

coarse particles show as strong or stronger

acute effects on asthma, chronic obstructive

pulmonary disease, and respiratory hospital

admissions (Brunekreef and Forsberg 2005).

Furthermore, although short-term mortality

appears to be more strongly related to fine

PM, coarse PM has been associated with cardiovascular morbidity, such as heart rate variability and various types of cardiovascular

disease hospital admissions (Brunekreef and

Forsberg 2005; Lipsett et al. 2006). A recent

study also reports an association between prenatal exposure to coarse particles and decrease

birth weight, with little effect from fine particles (Parker and Woodruff, in press).

The relationship between air pollution

and SIDS continues to warrant further study.

Given our findings of a relationship between

O3 and SIDS, we might also expect O3 to be

related to respiratory postneonatal mortality,

because O3 is a well-established respiratory

irritant (Bell et al. 2004; Hubbell et al. 2005).

In addition, a recent study by Triche and colleagues (2006) found ambient measures of O3

to be associated with respiratory symptoms in

infants, such as wheeze and difficulty breathing. However, neither our study nor a recent

Southern California study found O3 associated with respiratory postneonatal mortality

(Ritz et al. 2006). In addition, studies in

Southern California and Canada did not find

O3 associated with SIDS (Dales et al. 2004;

Ritz et al. 2006). Differences in exposure

metrics, study design, and study populations

could contribute to observed differences. We

used the O3 averaged over the county for the

first 2 months of the infant’s life. Ritz et al.

(2006) used a more acute exposure metric

based on O3 from the nearest monitor averaged over the last 2 months or 2 weeks of the

infant’s life. Dales et al. (2004) used a timeseries approach to assess acute (daily) exposures to O3. Our O3 exposure metric could be

a proxy for some other air pollutant, though

we might expect similar findings for other

pollutants and SIDS if this were the case. It is

also possible that early life is a more susceptible time period for O3 exposure. 

Shifts in the diagnostic coding from SIDS

to primarily ICD-10 R99—“ill-defined and

unspecified causes of mortality”—as found by

Malloy and MacDorman (2005) may also

influence observed results. We found a

stronger relationship between PM10 and

SIDS + ill-defined causes of death, but the

association between O3 and SIDS + illdefined causes of death was lower than for

SIDS alone. Finally, the back-to-sleep campaign may also be playing some role in differences between associations between PM and

SIDS in the 1990s versus little association

with SIDS around the year 2000. 

As with most other air pollution epidemiology studies, we rely on outdoor monitors as a

proxy for exposures. PM ambient monitors

have been found to be a reasonable proxy for

personal exposures (Sarnat et al. 2001, 2006).

In addition, measurements from ambient monitors for gaseous pollutants have been found to

be better surrogates for personal particulate

exposures than personal gaseous pollutant exposure (Sarnat et al. 2001, 2006). These findings

support using ambient monitors to assess exposures from particulate matter. They also suggest

that findings of associations between health

outcomes and gaseous pollutants may be

attributed partially to ambient concentrations

of specific PM components. 

The exposures in this study focus on a

metric of chronic exposure after the infant’s

birth. Exposures that occur prenatally may

further enhance susceptibility and increase

risk to infant death. Studies suggest that air

pollution can increase the risk of adverse perinatal outcomes, including growth restriction

and preterm delivery, both of which increase

risk of infant mortality (Glinianaia et al.

2004; Huynh et al. 2006; Parker and

Woodruff, in press; Salam et al. 2005).

Future analysis to evaluate the role of prenatal

exposures is warranted to evaluate any potential prenatal contribution 

This study builds on previous large infant

cohort studies by adding additional features to

the analysis. We have controlled for additional

variables, both individual maternal characteristics and contextual SES variables, and assessed

multiple pollutants, using both linear and categorical forms of exposure. The observed relationships between PM10 and respiratory

postneonatal mortality and O3 and SIDS

remain relatively robust to model alternatives. 

This study provides further support for

PM air pollution as a risk factor for respiratory-related postneonatal infant mortality and

suggests that O3 may play a role in SIDS. 

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