Diverging associations of maternal age with low birthweight for black and white mothers

Janet W Rich-Edwards1 ,2 ,3 , Stephen L Buka1 ,3 ,4 , Robert T Brennan1 ,5 ,6 and Felton Earls1 ,3 ,5

1 Project on Human Development in Chicago Neighborhoods.
2 Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA, USA.
3 Department of Maternal and Child Health, Harvard School of Public Health, Boston, MA, USA.
4 Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.
5 Department of Administration, Planning, and Social Policy, Graduate School of Education, Harvard University, Cambridge, MA, USA.
6 Department of Social Medicine, Harvard Medical School, Boston, MA, USA.

Corrrespondence: Dr Rich-Edwards, Department of Ambulatory Care and Prevention, 133 Brookline Ave, 6th floor, Boston, MA, USA.


    Abstract
 Top
 Abstract
 Study population
 Statistical methods
 Results
 Discussion
 References
 
Background In the US, the risk of low birthweight appears to increase more quickly with maternal age for black women than it does for white women. Our aim was to investigate correlates and causes of the racial/ethnic divergence in low birthweight by maternal age.

Methods We analysed birth certificate data from 96 887 singleton births to black and white mothers in Chicago from 1994 to 1996 to determine if the association between maternal age and low birthweight differed by maternal ethnicity, marital status, and socioeconomic disadvantage. The association of maternal age with risk of low birthweight was examined, considering especially the interactions of maternal age with maternal race/ethnicity, marital status, education, and neighbourhood poverty.

Results In unadjusted data, the risk of low birthweight rose steeply with maternal age for black, but not white, mothers. Adjustment for the main effects of maternal education, marital status, adequacy of prenatal care, cigarette smoking, and neighbourhood poverty accounted for some of the age-related excess risk of black mothers. Further adjustment for interactions of maternal age with these risk factors eliminated the ethnic divergence in age slopes. The fully adjusted analysis indicated that the risk of low birthweight rises more quickly with maternal age for disadvantaged women, regardless of race/ethnicity.

Conclusion This analysis suggests that hardships act cumulatively to threaten reproductive health. The particularly steep increase in risk of low birthweight with increasing maternal age for black women is explained by the high prevalence of disadvantage in this population.


Keywords Maternal age, infant, low birthweight, pregnancy outcome, socioeconomic factors, ethnic groups, blacks, whites

Accepted 10 July 2002

In the US, black women bear more than twice the risk of delivering a low birthweight or very low birthweight infant compared with white women.1 Despite repeated epidemiological assaults, this enigmatic association remains largely impenetrable.2–6 Less widely appreciated, and less examined, is the possibility that this racial/ethnic gap in risk of low birthweight varies by maternal age.

Geronimus demonstrated an increasing risk of low birthweight with advancing maternal age among black, but not white, mothers, using 1989 birth certificate data from singleton first births to black and white mothers aged 15–34 in Michigan.7 The positive age slope was particularly steep among black women living in poor neighbourhoods. More recently, using New York City birth certificate data from 1987 to 1993, Rauh and colleagues also documented markedly increasing risk of delivering low birthweight infants with increasing age among African American women, compared with white women.8 The age-associated increase in risk of low birthweight was considerably greater for African American mothers receiving public insurance than for whites or for privately insured African Americans. Even after adjustment for multiple risk factors (including an interaction between maternal age and poverty), the risk of poor pregnancy outcome rose faster with age for African American women than for white women.

We sought to examine the associations between maternal race/ethnicity, age, socioeconomic risk factors, and the risk oflow birthweight in Chicago. We were particularly interested in examining whether the elevated risk of poor pregnancy outcome among older black women could be explained by higher risks of social or material disadvantage with increasing maternal age.


    Study population
 Top
 Abstract
 Study population
 Statistical methods
 Results
 Discussion
 References
 
Utilizing data from Illinois state birth certificates supplied by the Chicago Department of Public Health, we included all singleton births of black and non-Latina white mothers in Chicago from 1994 to 1996. Data on the birth certificate come from maternal interview and medical record abstraction by clinicians and clerks in the delivery hospitals. The birth certificate includes birthweight, self-reported maternal ethnicity, and maternal education, among other data. Births were excluded if they were from multiple gestations (n = 4564) r from mothers who were neither black nor non-Latina white (51 668 Latina, 3634 Asian American, and 2725 other or unknown maternal ethnicity). Hereafter, we use ‘ethnicity’ to refer to ‘race/ethnicity’.) We excluded birth records that were missing birthweight (n = 49), marital status (n = 26), maternal education (n = 931), or maternal cigarette smoking (n = 347). Mothers whose age was not recorded (n = 7) or who were <15 years old (n = 810) or >45 years old (n = 30) were also excluded. Finally, the 2991 births whose maternal residential address could not be mapped to a 1990 census tract were excluded.

As the birth certificates lacked information on individual income, family income, or use of public health insurance (Medicaid), we used a proxy from the 1990 census data regarding income level of the mother’s residential neighbourhood. Maternal census tract indicators on the birth certificate were mapped to 343 ‘neighbourhood clusters’ defined by the Project on Human Development in Chicago Neighborhoods.9 The proportion of households in poverty in each neighbourhood cluster was determined from the 1990 census.


    Statistical methods
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 Abstract
 Study population
 Statistical methods
 Results
 Discussion
 References
 
Probabilities of low birthweight (<2500 g) and very low birthweight (<1500 g) were derived from frequency tables. To account for the clustering of births within neighbourhoods and the fact that our measure of neighbourhood poverty is a group-level characteristic, we used hierarchical non-linear models (estimated by the SAS procedure PROC NLMIXED) to estimate odds ratios (OR) of low birthweight for various exposures, adjusted for multiple covariates.10,11 These logistic regression analyses were confined to mothers aged 20–45 years. This age restriction facilitated a focus on the diverging risk of low birthweight after age 20 and enabled adjustment for maternal high school graduation and marital status.

The main focus of this analysis was the interaction of maternal age with maternal ethnicity, as well as the interactions of maternal age and ethnicity with other factors that are markers of social and economic disadvantage, specifically, maternal education, marital status, and neighbourhood poverty. Maternal age was represented as a continuous variable and multiplicative interactions were assessed by the statistical significance of cross-product terms between maternal age and other variables. In a multivariate model among mothers aged 20–45, the addition of a quadratic term for maternal age (the residual of age2 regressed on age), as well as interactions with this term made no material difference to the results (data not shown).

An interaction was retained in the model if it demonstrated a <=5% probability of occurring by chance alone. The exception to this was the retention in all models of the interaction term between ethnicity and age, as it was of primary interest. First, a ‘Main Effects Model’ was created as the foundation for analysis, which included the ethnicity*age term as well as established predictors of birthweight available from birth certificates: maternal age, ethnicity (black versus white), parity (in three categories), cigarette smoking during pregnancy (smoker versus non-smoker), adequacy of prenatal care (received first trimester care versus later care, no care, or unknown care), maternal education (high school graduate versus not), marital status (married versus not), and neighbourhood poverty. Then, to test whether the ethnic-specific age slopes varied by markers of socioeconomic disadvantage, we tested three-way interactions of maternal age and ethnicity with maternal education, marital status, and neighbourhood poverty (none were retained). Finally, to control for confounding of the maternal age*ethnicity interaction by interactions of other risk factors with age or ethnicity, we tested the effect on the age*ethnicity coefficient of including in the model two-way interactions of maternal education, marital status, parity, prenatal care, smoking, and neighbourhood poverty with maternal age and maternal ethnicity, respectively. The resulting model, which includes several two-way interaction terms, is called the ‘Interaction Model’.


    Results
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 Abstract
 Study population
 Statistical methods
 Results
 Discussion
 References
 
In all, 14% of the 66 495 singleton infants born to black and 5% of the 30 392 singleton infants born to white mothers weighed <2500 g at birth. The distribution of low birthweight (<2500 g) and very low birthweight (<1500 g) births by maternal age for all black and white mothers is shown in Figure 1aGo. This U-shaped distribution confirms the widespread perception that women at the extremes of the age distribution are at increased risk of delivering small infants. However, this composite picture conceals two markedly diverging trends in the risk of low birthweight by maternal age for black and white mothers (Figure 1bGo). Although black and white women under 18 years of age shared a similar risk of delivering a low birthweight child, that risk dropped with increasing age for white mothers and climbed for black mothers. A black mother over age 30 had a 20% chance of delivering a low birthweight child, as compared with the 5% chance of a white mother over age 30 delivering an infant <2500 g.



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Figure 1a  Proportion of low birthweight (<2500 g) and very low birthweight (<1500 g) births by maternal age, black and white mothers, Chicago, 1994–1996

 


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Figure 1b  Proportion of low birthweight (<2500 g) and very low birthweight (<1500 g) births by maternal age and ethnicity

 
Table 1Go presents the distribution of several risk factors for low birthweight, by maternal age and ethnicity. As expected, older women were more likely than younger women to be married, multiparous, and to receive prenatal care in the first trimester. While black mothers were less likely to be married than white mothers at any age, the relative gap in proportion married narrowed with age. Prevalence of cigarette smoking during pregnancy increased with age among black mothers, while it generally decreased with age among white mothers. Regardless of ethnicity, younger mothers lived in poorer neighbourhoods. Regardless of age, black mothers lived in neighbourhoods that had at least twice as many households in poverty compared with the neighbourhoods in which white mothers lived.


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Table 1 Distribution of births and risk factors for delivery of a low birthweight child, by maternal age and ethnicity. Singleton births to black and white mothers, Chicago, 1994–1996
 
Table 2Go presents the results of several models fit to explain the association between maternal age and risk of low birthweight for black and white mothers aged 20–45 years. The ‘Unadjusted’ model demonstrates that the interaction between black ethnicity and age is positive and highly unlikely to have occurred by chance alone (< 0.0001). This indicates that the risk of low birthweight rose more quickly with age among black mothers than it did among white mothers. In this unadjusted model, the odds of delivering a low birthweight infant did not increase with age for white mothers (OR per year of age = 1.00; 95% CI: 0.99–1.01), while the OR per year of maternal age for black women was 1.05 (95% CI: 1.04–1.05). Other models in Table 2Go show the effect of adjustment for the main effects of established predictors of low birthweight. Note that addition of these covariates does little to change the interaction between black ethnicity and age. Even after adjusting for the main effects of all these predictors in the ‘Main Effects Model’, there remains a significant interaction between black ethnicity and age. In this ‘Main Effects Model’, the OR of delivering a low birthweight infant was 1.04 (95% CI: 1.04–1.05) per year of maternal age among black women, compared to 1.02 (95% CI: 1.01–1.03) among white women. This ethnic divergence did not depend on maternal parity (= 0.99 for the interaction of the ethnicity*age slope with primiparity). The risk of low birthweight rose with age among white women in the ‘Main Effects Model’ because it sets levels of maternal education, parity, smoking status, prenatal care, marital status, and neighbourhood poverty equal to those more typical of black mothers. The fact that the age slopes diverge even after adjustment for these variables indicates that their main effects do not fully explain the steeper trajectory of risk with age for black women.


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Table 2 Odds ratios and 95% CI from hierarchical non-linear regression models fit to predict low birthweight and to explain the interaction between maternal ethnicity and maternal age
 
However, interactions between other risk factors and maternal age might explain the steeper age slope among blacks. The ‘Interaction Model’ adds to the ‘Main Effects Model’ terms to represent interactions of maternal age with education, marital status, parity, level of neighbourhood poverty, and cigarette smoking, as well as an interaction between maternal ethnicity and marital status. The results of this ‘Interaction Model’ are contrasted to those of the ‘Main Effects Model’ in Table 2Go. Statistically significant interactions were observed of maternal age with marital status (< 0.0001), neighbourhood poverty level (= 0.01), adequacy of prenatal care (= 0.002), and cigarette smoking (= 0.02). The interaction between maternal education and age approached conventional statistical significance (= 0.08). Marital status also appeared to interact with ethnicity (< 0.0001). In this ‘Interaction’ model, the interaction between ethnicity and age was no longer statistically significant (= 0.61). In this model, the OR of delivering a low birthweight infant was 1.05 (95% CI: 1.04–1.07) per year of age for blacks, and 1.05 (95% CI: 1.04–1.06) per year of age for whites.

Maternal age appeared to interact with marital status, neighbourhood poverty, adequacy of prenatal care, and cigarette smoking (Table 2Go; the following OR are derived from the combination of relevant terms from the Interaction Model). At age 20, compared to unmarried women of the same ethnicity, married black women enjoyed an OR of 0.90 (95% CI: 0.79–1.02), and married white women had an OR of 0.67 (95% CI: 0.58–0.79). By age 40, the protective association with marriage was even stronger for both black and white women (OR = 0.55 [95% CI: 0.48–0.64] for 40 year old black women and OR = 0.41 [95% CI: 0.35–0.49] for 40 year old white women). At either age, marriage had a stronger protective association for white women than for black women. The relative risk of low birthweight associated with neighbourhood poverty also grew with maternal age: the OR for living in a neighbourhood where 50% of households were in poverty, compared with 1% of households, was 1.00 (95% CI: 0.91–1.10) at age 20, and grew to 1.34 (95% CI: 1.13–1.56) by age 40. Similarly, relative risks of smoking appeared to accelerate with age. At age 20, the OR of low birthweight associated with cigarette smoking during pregnancy was 1.94 (95% CI: 1.76–2.15). At age 40, the OR for smoking was 2.47 (95% CI: 2.18–2.79). Compared with women who received no prenatal care, late prenatal care, or whose prenatal care status was unknown, women who received first trimester care had OR for low birthweight of 0.84 (95% CI: 0.77–0.91) at age 20 and 0.63 (95% CI: 0.56–0.71) at age 40. Although the interaction between maternal education and age did not attain conventional statistical significance (= 0.08), it was in a direction consistent with other markers of social and economic disadvantage: the relative risk of having a high school degree was 0.90 (95% CI: 0.82–0.99) at age 20 and 0.75 (95% CI: 0.65–0.86) at age 40.

Figure 2Go depicts the OR and 95% CI for black ethnicity at various maternal ages, as predicted by the ‘Unadjusted’, ‘Main Effects’, and ‘Interaction’ models in Table 2Go. The OR for black ethnicity grew dramatically with maternal age in unadjusted data. Adjustment for the main effects of established risk factors diminished the age-related gap (‘Main Effects Model’). However, it was only after adjustment for the interactions of these risk factors with maternal age that the ethnic divergence in risk of low birthweight with maternal age was explained (‘Interaction Model’).



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Figure 2  Odds ratios of delivering low birthweight for black mothers compared with white mothers by maternal age, derived from three models. Chicago, 1994–1996

 

    Discussion
 Top
 Abstract
 Study population
 Statistical methods
 Results
 Discussion
 References
 
These data from Chicago showed markedly divergent trends in the association between maternal age and low birthweight for black and white mothers, confirming Geronimus’ original observations in Michigan that the ethnic birthweight gap was amplified with age.7 Our findings also agree with those of Rauh and colleagues, who documented ethnic age-divergence in the risk of low birthweight in New York City.8 In all three studies, adjustment for markers of maternal social and economic disadvantage diminished the ethnic age divergence.

Although these studies agree in their broad strokes, there are some important differences in their findings. Rauh and colleagues tested all possible interactions between maternal age and risk factors for low birthweight in New York. Only maternal ethnicity and Medicaid status interacted significantly with age. In New York, even after adjustment for main effects of established risk factors and the interaction of maternal age with Medicaid status, there remained a significant interaction between maternal age and ethnicity, such that the OR of having a moderately low birthweight infant for African American women (compared with white) rose from 1.8 at age 20 to 2.6 at age 40, while the OR of having a very low birthweight infant rose from 2.5 to 4.2

In contrast, in Chicago we found that most markers of socioeconomic status interacted with maternal age. The Chicago birth certificates did not include Medicaid status, so we were unable to test for the interaction between age and Medicaid status detected in New York. Although it is possible that the interactions of maternal age with neighbourhood poverty, marital status, and education might have been explained by Medicaid status, it seems more likely that all these factors capture overlapping, but not identical, facets of socioeconomic position. In Chicago, the age trajectories in risk of low birthweight were significantly steeper for women who were unmarried, smoked, lived in a poor neighbourhood, or who received inadequate prenatal care. Adjustment for these interactions with age eliminated the interaction between maternal ethnicity and age in Chicago. In other words, the risk of delivering a low birthweight child rose with maternal age for both white and black women who were unmarried, lived in poor neighbourhoods, smoked cigarettes, or received inadequate prenatal care.

Although this analysis in Chicago revealed increasing risk of low birthweight with advancing age among disadvantaged white and black mothers, social disadvantage was disproportionately borne by black women. This explains why the unadjusted data show a steep rise in risk of low birthweight with maternal age particular to black women. It should also be noted that, even after adjustment for multiple risk factors, there remained a twofold OR of low birthweight for black women compared with white women at any age. The failure to explain the overall ethnic birthweight gap with standard measures of current socioeconomic status is consistent with many previous studies.2–6

Several competing hypotheses can be marshalled to explain the apparent amplification of social and economic risk factors with age. First, the interactions could simply reflect a greater impact of recent exposures among older pregnant women. For example, the interaction between smoking and maternal age (which was also reported by Cnattingius et al. in Sweden)12 could indicate that smoking during pregnancy has a more detrimental impact on perinatal outcomes among older mothers. Along the same lines, prenatal care might yield more benefit to older mothers, who carry more risks of complications.

An alternative hypothesis posits that the high risk of poor pregnancy outcome among disadvantaged older mothers is the result of selective social mobility: less healthy women may ‘drift downwards’ into poverty as they age. Thus, it has been argued that poor health causes poverty, rather than poverty causing poor health.13,14 If ill health or other unmeasured risk factors for poor pregnancy outcome caused widespread downward mobility between ages 20 and 45 years, health risk might cluster among older disadvantaged women. Although this could theoretically produce the divergent age gradients observed in this study, selective mobility would have to be quite strong to account for such large social class differentials.15 It seems unlikely that most women bearing children in poor neighbourhoods are trapped there by ill health. In fact, there is evidence that childhood poverty precedes poor pregnancy outcome: low birthweight is better predicted by socioeconomic conditions in childhood than during the pregnancy.16–18

Finally, interactions between maternal age and risk factors could reflect a ‘weathering’ effect of cumulative disadvantage as women age. The ‘weathering hypothesis’ was coined by Geronimus, who proposed that health ‘may begin to deteriorate in early adulthood as a physical consequence of cumulative socioeconomic disadvantage’.19 A similar view is promoted by the ‘life course approach’, which emphasizes the cumulative health impact of social, biological, and psychological processes from conception to death.20 Both the ‘life course approach’ and the ‘weathering hypothesis’ suggest that social inequalities cause premature ageing. According to these approaches, the accumulating burdens of poverty and discrimination compromise a woman’s health and chances of delivering a healthy infant, even before she conceives the pregnancy. Our observation of steep age gradients among the most disadvantaged black and white women is consistent with these approaches. Seen through a ‘weathering’ lens, for disadvantaged populations, maternal age becomes a marker of duration of exposure to hardship. For example, an interaction between poverty and maternal age may capture a degrading impact of long-lasting poverty on health. Likewise, the interaction between prenatal care and maternal age could indicate a deterioration in health resulting from lack of health care throughout childhood and the reproductive years. With similar logic, the interaction between smoking and age could reflect cumulative damage from long-term smoking.

Cross-sectional data such as these collected in Michigan, New York, and Chicago cannot reveal which of these three hypotheses—true interactions with advanced maternal age; downward social mobility among the unhealthy; or ‘weathering’—are responsible for the significant interactions of maternal age with social and economic risk factors. These hypotheses are not mutually exclusive; all three mechanisms may contribute to the very high risk of poor pregnancy outcome among older disadvantaged women. Definitive evidence distinguishing these alternatives will come only from a longitudinal study with multiple observations of the same woman over time, linking changing exposures to sequential pregnancy outcomes. Although vital statistics datasets may be large enough to test such interactions, they typically lack longitudinal exposure information. There are other limitations to data collected for vital statistics purposes, including limited scope and varying degrees of accuracy.21,22

Although it cannot provide proof, this analysis provides supporting evidence that the lifelong tolls of social and economic disadvantage constitute powerful ‘weathering’ forces that age women prematurely by wreaking cumulative physiological damage. If so, efforts to improve birth outcomes must safeguard and enhance the health of disadvantaged women long before they become pregnant. Future longitudinal studies are needed to establish definitively whether, and how, women are ‘weathered’ by socioeconomic disadvantage.


KEY MESSAGES

• In the urban US, the risk of delivering a low birthweight infant generally rises with maternal age for black mothers, while it drops with age for white mothers.

Some, but not all, of the ethnic divergence in maternal age trends is explained by the main effects of social and economic risk factors for low birthweight. In this analysis, further adjustment for the interaction of maternal age with these risk factors completely explained the ethnic divergence in the risk of low birthweight associated with increasing maternal age.

Thus, older mothers at social and material disadvantage were at especially high risk of poor pregnancy outcome, regardless of ethnicity. Future longitudinal studies are needed to determine whether this high risk among older disadvantaged mothers indicates a cumulative, ‘weathering’ exposure to hardship.

 


    Acknowledgments
 
Funding for this project came from the March of Dimes Foundation, the John D and Catherine R MacArthur Foundation, the National Institute of Justice, and the National Institute of Mental Health. We are grateful for the statistical advice of Dr Ken Kleinman and the programming assistance of Ms Kathy McGaffigan.


    References
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 Abstract
 Study population
 Statistical methods
 Results
 Discussion
 References
 
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20 Kuh D, Ben-Shlomo Y. A Life Course Approach to Chronic Disease Epidemiology. Oxford: Oxford University Press, 1997.

21 Piper JM, Mitchell EF Jr, Snowden M, Hall C, Adams M, Taylor P. Validation of 1989 Tennessee birth certificates using maternal and newborn hospital records. Am J Epidemiol 1993;137:758–68.[Abstract]

22 Parrish KM, Holt VL, Connell FA, Williams B, LoGerfo JP. Variations in the accuracy of obstetric procedures and diagnoses on birth records in Washington state, 1989. Am J Epidemiol 1993;138:119–27.[Abstract]