Neonatal Encephalopathy and Socioeconomic Status: Population-Based Case-Control Study

Objective  To investigate the association between maternal socioeconomic status and the risk of encephalopathy in full-term newborns.

Design  Population-based case-control study.

Setting  Washington State births from 1994 through 2002 recorded in the linked Washington State Birth Registry and Comprehensive Hospital Abstract Reporting System.

Participants  Cases (n = 1060) were singleton full-term newborns with Comprehensive Hospital Abstract Reporting System International Classification of Diseases, Ninth Revision diagnoses of seizures, birth asphyxia, central nervous system dysfunction, or cerebral irritability. Control cases (n = 5330) were singleton full-term newborns selected from the same database.

Main Exposures  Socioeconomic status was defined by median income of the census tract of the mother's residence, number of years of maternal educational achievement, or maternal insurance status.

Main Outcome Measures  Odds ratios estimating the risk of encephalopathy associated with disadvantaged socioeconomic status were calculated in 3 separate analyses using multivariate adjusted logistic regression.

Results  Newborns of mothers living in neighborhoods in which residents have a low median income were at increased risk of encephalopathy compared with newborns in neighborhoods in which residents have a median income more than 3 times the poverty level (adjusted odds ratio, 1.9; 95% confidence interval, 1.5-2.3). There was also a trend for increasing risk of encephalopathy associated with decreasing neighborhood income (P<.001). Newborns of mothers with less than 12 years of educational achievement had a higher risk of encephalopathy compared with newborns of mothers with more than 16 years of educational achievement (adjusted odds ratio, 1.7; 95% confidence interval, 1.3-2.3). Newborns of mothers receiving public insurance also had a higher risk of encephalopathy compared with newborns of mothers who have commercial insurance (adjusted odds ratio, 1.4; 95% confidence interval, 1.2-1.7).

Conclusion  Disadvantaged socioeconomic status was independently associated with an increased risk of encephalopathy in full-term newborns. These findings suggest that a mother's socioeconomic status may influence the risk of encephalopathy for her full-term newborn.

Disadvantaged socioeconomic status (SES) has been associated with many indicators of poor health in children including higher risks of infant mortality,^1-3 preterm birth,^4,5 and learning disabilities.⁶ Neonatal encephalopathy is “a clinically defined syndrome of disturbed neurological function in the earliest days of life in the term infant, manifested by difficulty initiating and maintaining respiration, depression of tone and reflexes, subnormal level of consciousness, and (often) seizures.”^7(p1325) One to 4 newborns per 1000 live births have symptoms consistent with neonatal encephalopathy,⁸ and most newborns with moderate to severe neonatal encephalopathy have profound developmental disabilities or die in the first year of life.⁹ Given the association of disadvantaged SES with neonatal morbidity and mortality and with other forms of neurological disease in adults and children,^1,3,10 it might be expected that full-term newborns of mothers with low SES could also be at higher risk of encephalopathy in the perinatal period. However, to our knowledge, there have been few studies in this area.

One Australian study found that full-term newborns of mothers with low SES had an approximately 3-fold increased risk of neonatal encephalopathy compared with newborns of mothers with high SES.¹¹ This study used maternal employment and health insurance status to determine SES. Given the limited range of these variables, it was difficult to determine whether there was a trend in the risk of neonatal encephalopathy associated with SES or if the association existed only for certain occupations. The authors also cautioned that the mechanism of action of their measures of SES on the risk of neonatal encephalopathy could vary in different populations and required further investigation.

The relationship between SES and cerebral palsy, one potential outcome of neonatal encephalopathy, has been studied more than the relationship between SES and neonatal encephalopathy. However, this relationship is complicated because preterm infants are at higher risk of cerebral palsy than full-term infants and low SES is associated with preterm birth. In addition, cerebral palsy is diagnosed in the postnatal period and, therefore, may be caused or exacerbated by postnatal factors. Studies of the association between cerebral palsy and SES have yielded conflicting results. Several investigators have found an association between SES and cerebral palsy,^12,13 but others have not found a significant association.^14,15 Recent studies of children with cerebral palsy suggest that the association between low SES and congenital cerebral palsy may be stronger in children of normal birth weight than in children of low birth weight.^12,13,15

Given that disadvantaged SES has been associated with premature birth and infant mortality¹⁶ and that factors associated with the risk of premature birth such as inflammatory states, maternal infection, or poor prenatal care have also been associated with neonatal encephalopathy,^17-19 we hypothesized that disadvantaged SES could also be associated with encephalopathy in full-term newborns. We examined the relationship between SES as measured by median neighborhood income of the mother's residence at the time of childbirth, maternal educational achievement, or insurance status, and the risk of encephalopathy in full-term newborns in Washington State from January 1994 through December 2002.

We conducted a population-based case-control study linking information from the Washington State Birth Registry to the Comprehensive Hospital Abstract Reporting System (CHARS) for births that occurred in Washington State from January 1994 through December 2002. The Birth Registry contains information recorded on the birth certificate for every birth in Washington State. CHARS is a database created by the Washington State Department of Health that includes ICD-9International Classification of Diseases, Ninth Revision (ICD-9) discharge diagnosis codes and other administrative information for all hospitalizations in nonfederal hospitals in Washington State, including those for both mothers and their newborns. The CHARS records of mothers and newborns are linked to each infant's Washington State birth certificate data using unique identifiers. During the study period, 89% of all singleton births in Washington State were linked to CHARS records (n = 586 118). The information was deidentified before receipt by the authors. Institutional review board approval from the Washington State Department of Health and the University of Washington, Seattle, for use of these data was received before the conduct of the study.

Case infants (n = 1060) were singleton full-term (≥37 weeks' gestational age) newborns maintained in the birth hospital or admitted to the hospital within 2 days of birth whose ICD-9 discharge diagnose codes included severe birth asphyxia; birth asphyxia with neurological involvement (768.5), unspecified birth asphyxia in live born infant (768.9), newborn convulsions (779.0), convulsions (780.3), other and unspecified cerebral irritability in the newborn (779.1), or cerebral depression, coma, and other abnormal cerebral signs; and central nervous system dysfunction in newborn, not otherwise specified (779.2) in the CHARS database. We believed that most infants with these diagnoses would have evidence of neurological dysfunction in the perinatal period given the definitions of these diagnosis codes. Control infants (n = 5330) were singleton full-term (≥37 weeks' gestational age) newborns selected from the same database. Five control infants were randomly selected for each infant with encephalopathy and were matched only by birth year. All subjects included in the final analyses had maternal information recorded in the CHARS database. All infants with congenital anomalies (225 cases and 373 controls) or drug withdrawal syndrome (20 cases and 8 controls) were excluded from the analysis. All infants whose gestational age was unknown or recorded as more than 45 weeks were also excluded (24 cases and 73 controls).

We used 3 variables to measure SES, including median income of the neighborhood of the mother's residence at the time of the infant's birth, number of years of maternal educational achievement, and maternal health insurance status. We used the median income of the census tract of the mother's residence as listed on the birth certificate to define neighborhood income. We then categorized the median neighborhood income based on the US poverty level for a family of 4 (2 adults and 2 children) for each year from 1994 through 2002. The US poverty level for a family of 4 ranged from an annual income of $15 029 in 1994 to $18 244 in 2002.²⁰ Subjects without a maternal residence listed or those whose residence could not be linked to a census tract were excluded from the final neighborhood income analysis (96 cases and 355 controls were excluded).

Maternal educational achievement was defined as the number of years of schooling as reported on the birth certificate and was categorized based on the number of years completed, as follows: less than 12 years, 12 years, 13 to 15 years, or greater than or equal to 16 years. Subjects who did not have maternal educational achievement listed on the birth certificate were excluded from analysis of maternal educational achievement (103 cases and 475 controls were excluded).

Maternal insurance status was defined as the primary payer listed in the CHARS database. Maternal insurance was divided into 2 groups: public insurance (primary payer listed as Medicaid or Medicare) and private insurance (primary payer listed as commercial insurance, health maintenance organization, or health care services contractor). Two small groups of mothers with self-pay (14 cases and 92 controls) or other insurance (16 cases and 73 controls) were excluded from the final analyses by insurance status.

Odds ratios were calculated using univariate and multivariate logistic regression. We performed separate analyses to determine the relationship between the 3 measures of SES and the risk of encephalopathy. Confounders were selected before analysis based on the likelihood of confounding given results of our univariate analyses and previous studies^11,17,21 that indicated that these variables may have an effect on the risk of encephalopathy and mother's SES. The confounders in our models included maternal age, parity, maternal race/ethnicity, marital status, presence of preeclampsia, and birth year. Maternal race/ethnicity was recorded on the birth certificate and was usually reported by the mother, although hospital staff may also record this information. The original adjusted odds ratios (AORs) were compared with the results obtained when the intermediate variables of timing of prenatal care, exposure to intrapartum fever or chorioamnionitis, smoking, and urban vs rural residence were individually added to the model to determine the effect these intermediate variables might have on the relationship between encephalopathy and low SES. A change of more than 10% was predetermined to indicate a significant alteration of the odds ratio.

To evaluate trends in our exposures of interest, we used logistic regression to estimate the change in the risk of encephalopathy associated with 1 unit of change in neighborhood income or educational achievement levels. For neighborhood income, we defined the unit of change as 1 poverty level, the dollar figure assigned to each year to define poverty level (eg, $15 029 for 1994 or $17 960 for 2001) to ensure that each unit was roughly equivalent from year to year. For educational achievement, the unit of change was 1 year of maternal educational achievement.

The distribution of maternal age, race/ethnicity, marital status, rural residence, and reported smoking were similar between the encephalopathy and control groups. Mothers of case infants were more likely to be nulliparous, to have had later entry into prenatal care, and to have preeclampsia than mothers of controls. Infants with encephalopathy were more likely to be male or have low birth weight than control infants. Infants exposed to intrapartum fever or chorioamnionitis also had a higher risk of encephalopathy than unexposed infants (Table 1).

Residence in a low-income neighborhood, with median income less than 2 times the poverty level, was associated with a 1.9-fold (95% confidence interval [CI], 1.5-2.3) increased risk of encephalopathy when compared with residence in neighborhoods with a median income more than 3 times the poverty level (Table 2). Using a continuous variable for neighborhood income, we identified a linear trend in the risk of encephalopathy associated with neighborhood income. For each poverty-level unit increase in median neighborhood income, the risk of encephalopathy decreased by 24% (AOR, 0.76; 95% CI, 0.69-0.84; P for trend <.001).

The association between neighborhood income and encephalopathy persisted in the subgroups of infants diagnosed with seizures or birth asphyxia and was strongest in the group of infants diagnosed with severe birth asphyxia (Table 2). Addition of timing of prenatal care, smoking, or exposure to intrapartum fever or chorioamnionitis to the model or removal of preeclampsia from the model altered the original AORs by less than 5%, indicating that these intermediate variables were likely not responsible for the association between neighborhood income and risk of encephalopathy.

Fewer years of maternal educational achievement were also associated with an increased risk of encephalopathy. Compared with infants of mothers with 16 years of educational achievement or more, risk of encephalopathy was increased 1.3-fold (95% CI, 1.0-1.6) in infants of mothers with 13 to 15 years of educational achievement, 1.6-fold (95% CI, 1.1-1.6) in infants of mothers with 12 years of educational achievement, and 1.7-fold (95% CI, 1.3-2.3) in infants of mothers with less than 12 years of educational achievement (Table 2). We also identified a linear trend, such that higher maternal educational achievement was associated with a decreased risk of encephalopathy. For each additional year of educational achievement, the risk of encephalopathy decreased by 6% (AOR, 0.94; 95% CI, 0.92-0.97; P<.001). This relationship seemed to persist in the groups of infants diagnosed as having seizures or asphyxia but was only significant in infants with seizures whose mothers had 12 years of educational achievement or infants with any asphyxia and mothers with 12 years of educational achievement or less (Table 2).

Maternal public health insurance, compared with private insurance, was also associated with an increased risk of encephalopathy (AOR, 1.4; 95% CI, 1.2-1.7), seizures (AOR, 1.3; 95% CI, 1.0-1.6), and asphyxia (AOR, 1.3; 95% CI, 1.0-1.6) (Table 2). There was less than a 5% change in the AORs when the intermediate variables (timing of prenatal care, exposure to intrapartum fever or chorioamnionitis, smoking, or urban vs rural residence) were individually added to the final models for educational achievement and insurance status, indicating that these intermediate variables are likely not responsible for the association between maternal educational achievement or insurance and risk of encephalopathy. In addition to this finding, we did not find evidence of effect modification of the relationship between SES and encephalopathy by parity or maternal age.

In a full model including all 3 indicators of SES (neighborhood income, maternal educational achievement, and maternal health insurance) and the preselected confounders, we found that the risk of encephalopathy associated with neighborhood income and maternal insurance decreased by less than 10% (range, 1%-7.5%) with the addition of 1 or both of the other SES factors. This indicates that neighborhood income and maternal insurance status were equally predictive of disease and were relatively independent of each other. However, the odds ratios associated with maternal educational achievement decreased by 23% when both income and maternal insurance were added to the model. Adding educational achievement to the income or maternal insurance models changed these odds ratios by less than 3.5% (range, 0.4%-3.4%). This indicates that the relationship between educational achievement and encephalopathy may be influenced by other factors associated with neighborhood income or insurance status.

Disadvantaged SES was associated with an increased risk of encephalopathy in full-term newborns in Washington State. This association was significant whether neighborhood income, maternal educational achievement, or insurance status was used as a measure of SES. Of these 3 measures, low median neighborhood income was most robustly associated with the risk of encephalopathy. However, we found that all of these components of SES are important and that each measure of SES evaluated seemed to have an effect on the risk of encephalopathy in full-term newborns.

Socioeconomic status can be difficult to measure or to define consistently and accurately. Several studies of the relationship between SES and encephalopathy or cerebral palsy have used self-reported measures, which are prone to bias, or general measures such as insurance status or maternal employment. We used the report of mother's residence from the birth certificate combined with the median income of the census tract of the mother's residence from census data to generate our neighborhood income variable. These data were less susceptible to reporting bias than self-report of income or other measures. This measure also provides a representation of the neighborhood environment of each participant, which may be relevant in different ways than individual income alone. One limitation to this approach is that we were unable to identify a census tract for some control and case infants, so there may have been some nondifferential bias if the mothers of infants with encephalopathy and missing neighborhood income data were somehow different than the mothers of controls with missing neighborhood income data. Our data for maternal insurance status was also unbiased but provided only 2 broad categories. Maternal educational achievement was determined by self-report on the birth certificate and was, therefore, most prone to reporting bias of the 3 measures used in this study.

Another limitation of this study was the use of ICD-9 codes to identify newborns with encephalopathy and our inability to verify these diagnoses by medical record review. We were unable to conduct medical record reviews because all information was deidentified and the infants were hospitalized at many institutions throughout Washington State. Despite these limitations, to our knowledge, this is one of the largest studies to investigate the association between encephalopathy in the term newborn and maternal SES and to provide evidence that disadvantaged antenatal SES is a risk factor for neonatal encephalopathy.

The link between SES and infant mortality and between SES and prematurity has been firmly established in many earlier studies.^2,3,22 This study provides evidence that low SES is also associated with adverse neonatal neurological outcomes in full-term newborns. We found this association to hold true for 3 different classifications of SES and, in most cases, for diagnoses of any encephalopathy, neonatal seizures, or birth asphyxia. However, the underlying mechanisms that account for these associations remain unclear, although disparities in infant health have existed for many years and many theories have been advanced to explain the relationship between low SES and poor perinatal health. The disparities between neonatal outcomes for the rich and the poor continue despite medical advances in prenatal and perinatal care, and prenatal programs such as the Women, Infants and Children Program and others that were designed to improve maternal and child health by improving access to medical care, maternal nutrition, and support for vulnerable women and their children.²³

The association between disadvantaged SES and encephalopathy in full-term newborns in this study could not be attributed to differences in prenatal care, race/ethnicity, urban vs rural residence, exposure to intrapartum fever or chorioamnionitis, or rate of preeclampsia. Other factors such as social stress, perceived disparities, neighborhood violence, and social support systems may influence perinatal health²⁴; however, we were unable to measure the effect of these factors on the risk of encephalopathy. There is also growing evidence that chronic stress may lead to alterations in maternal physiology such as altered vascular responses and stress hormone production.²⁴ While there is little firm evidence that links these changes to premature birth or neonatal outcomes, it is possible that physiological changes induced by chronic stressors could influence neonatal outcomes and may influence the risk of neonatal encephalopathy.

Indicators of disadvantaged SES such as residence in a low-income neighborhood at the time of birth, lack of advanced maternal educational achievement, or maternal public insurance were associated with increased risk of encephalopathy in full-term newborns in Washington State. This association does not seem to be mediated by timing of prenatal care, race/ethnicity, smoking, exposure to intrapartum fever or chorioamnionitis, or preeclampsia.

While the mechanisms behind the relationship between SES and the risk of neonatal encephalopathy remain unclear, these findings suggest that maternal SES may influence the risk of encephalopathy in newborns. Further investigation is necessary to attempt to identify factors such as stress, perceived disparity, differential infection rates, toxic exposures, or other characteristics that may lead to higher risk of encephalopathy in populations with disadvantaged SES. Once identified, these factors may provide targets for interventions to improve neonatal outcomes and reduce the risk of neonatal encephalopathy in vulnerable populations.

Correspondence: Heidi K. Blume, MD, MPH, Division of Pediatric Neurology, Children's Hospital and Regional Medical Center, University of Washington, 4800 Sandpoint Way, Mailstop B-5552, Seattle, WA 98105 (heidi.blume@seattlechildrens.org).

Accepted for Publication: January 25, 2007.

Author Contributions:Study concept and design: Blume. Acquisition of data: Blume. Analysis and interpretation of data: Blume, Loch, and Li. Drafting of the manuscript: Blume. Critical revision of the manuscript for important intellectual content: Blume, Loch, and Li. Statistical analysis: Blume and Loch. Administrative, technical, and material support: Blume. Study supervision: Li.

Financial Disclosure: None reported.