Abstract
Background:
Preterm birth (PTB) disproportionately affects African-American compared to Caucasian women, although reasons for this disparity remain unclear. Some suggest that a differential effect of maternal age by race/ethnicity, especially at older maternal ages, may explain disparities.
Objective:
To determine whether the relationship between maternal age and preterm birth varies by race/ethnicity among primiparae non-Hispanic blacks (NHB) and non-Hispanic whites (NHW).
Methods:
A cross-sectional study of 367,081 singleton live-born first births to NHB and NHW women in California from 2008–2012 was conducted. Rate ratios (RR) were estimated for PTB and its subtypes – spontaneous and clinician-initiated – after adjusting for confounders through Poisson regression. Universal age/race reference groups (NHW, 25–29 years) and race-specific reference groups (NHW or NHB, 25–29 years) were used for comparisons.
Results:
Among all women, RR of PTB was highest at the extremes of age (<15 and ≥40 years). Among NHBs, the risk of PTB was higher than among NHWs at all maternal ages (adjusted RR of PTB 1.38 to 2.93 versus 0.98 to 2.38). However, using race-specific reference groups, the risk of PTB for NHB women (RR 0.91 to 1.88) versus NHW women (RR 0.98 to 2.39) was nearly identical at all maternal ages, with overlapping confidence intervals. Analyses did not demonstrate substantial divergence of risk with advancing maternal age. PTB, spontaneous PTB and clinician-initiated PTB demonstrated similar risk patterns at younger but not older maternal ages, where risk of clinician-initiated PTB increased sharply for all women.
Conclusions:
Primiparae NHBs demonstrated increased risk of PTB, spontaneous and clinician-initiated PTB compared to NHWs at all maternal ages. However, RRs using race-specific reference groups converged across maternal ages, indicating a similar independent effect of maternal age on PTB by race/ethnicity. A differential effect of maternal age does not appear to explain disparities in preterm birth by race/ethnicity.
Keywords: Black, disparities, maternal age, preterm birth, weathering
Background
In the United States, non-Hispanic black women experience higher rates of infant mortality, preterm birth (<37 weeks) and small for gestational age births compared to non-Hispanic white women, even after adjustment for socioeconomic, health and behavioral factors.1,2 Though exact mechanisms remain unclear, one proposed hypothesis, known as “weathering”, attributes poorer birth outcomes among black women to earlier and more rapid deterioration of health with advancing age.3 This earlier and steeper health decline is conceptualised as a direct consequence of lifelong exposure to social and environmental disadvantage, which ultimately leads to widening health disparities between blacks and whites as they age. While initially presented as an explanation for excess rates of infant mortality among black women,3,4 it is now applied to explain broader disparities in health outcomes among disadvantaged populations.5–8
Additional hypotheses, including normative differences in childbearing patterns by age,9 allostatic load,6,10–12 the developmental origins of health and disease,13 and the life-course framework 11,14–16 have been developed to advance our understanding of disparities in birth outcomes.16–24 The extent to which the various hypotheses apply to all minority women at all points in their reproductive lives is not clear. For weathering specifically, researchers often use white women in their twenties as the universal reference group, an approach that does not sufficiently account for the increased baseline risk of poor outcomes among black women at all ages, nor for the increasing risk of poor birth outcomes with advancing maternal age for all women.25–28 Furthermore, age is frequently grouped into broad, uneven categories and fails to include women at the tails of the distribution (below 20 years or over 35 years), a particular shortcoming as childbearing patterns have shifted toward later initiation of births among US women.29,30 In addition, many early studies included only limited adjustment for multiple confounders, especially maternal health conditions and measures of socioeconomic status, which have demonstrated associations with poor birth outcomes.4,19,31–33
We sought to evaluate whether maternal age modifies the relationship between race and preterm birth (PTB) and its subtypes (spontaneous and clinician-initiated) by conducting analyses that incorporated universal and race-specific reference groups. We hypothesised that given population-wide changes in fertility timing, enhanced social opportunities for women, changes in obstetrical practice and heightened attention to chronic disease management, the independent effect of maternal age on PTB would not vary by race, and the risk of PTB would not diverge by race with advancing maternal age.
Methods
We conducted a population-based, cross-sectional study using the California Office of Statewide Health Planning and Development linked birth cohort data for the years 2008–2012. Using vital statistics and hospital discharge records, this linked database provides information about the maternal delivery hospitalization and maternal and infant data from birth certificates. Mother-infant pairs were linked using probabilistic linkage methods; detailed descriptions of the dataset and linkage techniques have been published previously.34 Approval for the study was obtained from Yale University Institutional Review Board, the Office of Statewide Health, Planning and Development of the State of California, the California Department of Public Health and the Committee for the Protection of Human Subjects of the State of California.
Cohort selection
There were 2,615,033 birth records in California between 2008–2012. Of these, we sequentially excluded the following: twins or higher-order births (n=83,225), stillbirths (n=4,375), and parity 2 or higher (n=1,517,044). After these exclusions, 1,007,675 singleton, live-born first births remained. We additionally excluded births with implausible maternal age and gestational age data (n=9,456), births to women of Hispanic ethnicity (n=452,356), and births to women of self-identified race other than “White” or “Black” (n=157,960), leaving the analytic cohort to 367,081 births. First births were selected to adjust for parity by design and the increasing age at first birth for women of all races in recent years.29 The cohort selection is detailed in Figure 1.
Figure 1.

Selection of birth cohort for analysis, California, 2008–2012
Exposure
Maternal age was recorded at the time of delivery and categorised as <15, 15–19, 20–24, 25–29, 30–34, 35–39 and ≥40 years (range 11–71 years). Five-year age categories were chosen to reduce heterogeneity within categories and to more precisely model the shape of the relationship between exposure and outcome relative to other studies,4,19 which often used broader age categories. Maternal race/ethnicity was self-reported, abstracted from the birth certificate, and classified as non-Hispanic white (NHW) or non-Hispanic black (NHB). The sample was restricted to non-Hispanic black and white women since much of the disparities literature addresses comparisons between these two groups.35
Outcome
Gestational age was based on the last menstrual period and restricted to 22–44 weeks. Preterm birth was defined as <37 completed weeks of gestation. We approached the categorisation of this variable from a clinically-minded stand-point, and thus did not include stillbirths or those born below the limit of viability. Using a validated algorithm developed for use with US vital records, we stratified preterm births by type, categorising them as spontaneous (preceded by spontaneous membrane rupture and/or uterine contractions) or clinician-initiated (labor or delivery occurred secondary to medical intervention).36 The kappa statistic for the algorithm is 0.83 (0.70, 0.95), indicating excellent agreement between algorithm-assigned and manually-assigned preterm birth type.37
Covariate selection
Covariates were selected based on review of the literature for factors known to be associated with PTB.38–42 Sociodemographic factors included nativity (US vs foreign-born), insurance status (none, private, public), smoking status (ever/never) and age-appropriate education. An age-appropriate measure of highest level of education was used to minimise the potential effects of misclassification bias for the youngest women. Mother’s level of education was grouped as: none/not age appropriate; age appropriate (for women who were not old enough to have completed high school), high school degree or some college; associates degree; or bachelor’s degree or more. Prior to final categorization, linear contrasts were performed to ensure the homogeneity of women within each group with respect to the outcome.
All medical/obstetrical variables were categorical, and included prenatal care (none, 1st, 2nd or 3rd trimester), pre-pregnancy body mass index (BMI; underweight, normal weight, overweight, obese),43 rate of net gestational weight gain (inadequate, appropriate, excessive),44 diabetes (none, pre-pregnancy or gestational), hypertensive disorders (none, chronic/pre-pregnancy or pregnancy-associated) and asthma (yes/no). As previous studies have documented under-reporting of maternal medical conditions on the birth certificate,45 ICD-9 codes abstracted from the hospital billing records were used in conjunction with birth certificate data to define the hypertension, diabetes and asthma variables. Report of these conditions in either source was coded as presence of the condition; cross-tabulations for these variables are provided in eTable 1.
Statistical analysis
Maternal sociodemographic and health characteristics and incidence of PTB were compared by race. Multivariable Poisson regression models were used to estimate relative risk (RR) and 95% confidence intervals (95% CI) for associations with PTB, spontaneous PTB and clinician-initiated PTB, using both a universal reference group (joint effects model) and race-specific reference groups (stratified model). Statistical analysis was performed using SAS version 9.4 (SAS Institute, Cary, NC, USA).
Missing Data
Among the 2,615,033 birth records, we excluded 15 records with missing data for plurality (singleton or higher-order multiples) and 2,699 records (1%) with missing data for parity. Due to the low proportion of missingness for each key variable, records with missing or biologically implausible values for gestational age (<22 or ≥47 completed weeks, n=25,761; 2.5% missing), maternal age (n=69; <0.01% missing), race (n=20,068; 2.0% missing) or ethnicity (n=19,633; 2.0% missing) were excluded.
Although the percentage of women with missing data for any single covariate did not exceed 2.5%, we performed simple imputation by race for the nativity, insurance status, smoking status, age-appropriate education, BMI and rate of net gestational weight gain variables due to the cumulative degree of missing covariate information. Sensitivity analyses for the imputed variables demonstrated minimal change in point estimates. Imputed covariates were therefore used in all Poisson regression models. Results of the sensitivity analyses are presented in eTable 2.
Results
The final analytic sample included 367,081 singleton, live-born first births to NHW and NHB women. NHW women were more likely to be foreign-born, have an advanced degree, initiate prenatal care during the first trimester, and have a history of smoking (Table 1). NHB women were more likely to initiate prenatal care during the second trimester, be overweight or obese prior to pregnancy, exhibit a slow rate of gestational weight gain, and have hypertensive disorders of pregnancy or asthma. Women in both groups were equally likely to have health insurance, though NHW women were more likely to be privately insured and NHB women more likely to be publicly insured. Rates of pre-pregnancy diabetes, gestational diabetes and chronic hypertension were similar for both groups. The incidence of PTB was 7.7% overall; NHB women had a higher incidence than NHW women (11.1% versus 7.0%). Differences in maternal age at first birth between the two groups were evident, as more than half of NHW women gave birth to their first child between the ages of 25–34 years (55.1%), while the majority of NHB women did so between 15–24 years (63.5%).
Table 1.
Characteristics of Women in Sample Population by Race and Preterm Birth Status
| Non-Hispanic Whites | Non-Hispanic Blacks | Total | |||||||
|---|---|---|---|---|---|---|---|---|---|
| (n=308,584, 7.0% PTB) | (n=58,497, 11.1% PTB) | (n=367,081, 7.7% PTB) | |||||||
| Number | %a | PTB (%)b |
Number | %a | PTB (%)b |
Number | %a | PTB (%)b |
|
| <15 | 140 | 0.05 | 15.7 | 201 | 0.4 | 21.9 | 341 | 0.1 | 19.4 |
| 15–19 | 23,903 | 7.75 | 8.5 | 14,797 | 25.3 | 11.5 | 38,700 | 10.5 | 9.7 |
| 20–24 | 66,964 | 21.7 | 6.8 | 22,366 | 38.2 | 10.3 | 89,330 | 24.4 | 7.7 |
| 25–29 | 89,203 | 28.9 | 6.2 | 11,084 | 18.9 | 10.7 | 100,287 | 27.3 | 6.7 |
| 30–34 | 80,815 | 26.2 | 6.6 | 6,313 | 10.8 | 11.6 | 87,128 | 23.7 | 7.0 |
| 35–39 | 37,046 | 12.0 | 8.1 | 2,857 | 4.9 | 13.9 | 39,903 | 10.9 | 8.6 |
| ≥40 | 10513 | 3.4 | 10.2 | 879 | 1.5 | 16.0 | 11,392 | 3.1 | 10.7 |
| Nativity | |||||||||
| US born | 270,445 | 87.6 | 7.1 | 53,309 | 91.1 | 11.3 | 323,754 | 88.2 | 7.8 |
| Foreign born | 38,139 | 12.4 | 6.5 | 5,188 | 8.9 | 9.3 | 43,327 | 11.8 | 6.8 |
| Education | |||||||||
| None/not age appropriate | 7,121 | 2.3 | 9.7 | 3,059 | 5.3 | 12.7 | 10,180 | 2.8 | 10.6 |
| High school degree, some college or age appropriate | 131,478 | 42.6 | 7.6 | 43,719 | 74.7 | 11.3 | 175,197 | 47.7 | 8.5 |
| Associates degree | 21,590 | 7.0 | 6.9 | 2,901 | 5.0 | 11.1 | 24,491 | 6.7 | 7.4 |
| Bachelor’s degree or more | 148,395 | 48.1 | 6.4 | 8,818 | 15.1 | 9.8 | 157,213 | 42.8 | 6.6 |
| Ever Smoker | |||||||||
| No | 286,120 | 92.7 | 6.9 | 56,097 | 95.9 | 11.0 | 342,217 | 93.2 | 7.6 |
| Yes | 22,464 | 7.3 | 8.0 | 2,400 | 4.1 | 13.4 | 24,864 | 6.8 | 8.5 |
| Initiation of Prenatal care | |||||||||
| 1st trimester | 272,184 | 88.2 | 7.0 | 46,944 | 0.5 | 11.2 | 319,128 | 86.9 | 7.6 |
| 2nd trimester | 30,540 | 9.9 | 6.7 | 9,334 | 0.2 | 10.9 | 39,874 | 10.9 | 7.7 |
| 3rd trimester | 5,335 | 1.7 | 6.0 | 1,952 | 16.0 | 8.9 | 7,287 | 2.0 | 6.8 |
| None | 525 | 0.2 | 25.9 | 267 | 3.3 | 28.1 | 792 | 0.2 | 26.6 |
| Insurance status | |||||||||
| None | 3,420 | 1.1 | 8.7 | 977 | 1.7 | 15.7 | 4,397 | 1.2 | 10.3 |
| Public | 73,989 | 24.0 | 7.9 | 35,440 | 60.6 | 11.3 | 109,429 | 29.8 | 9.0 |
| Private | 231,175 | 74.9 | 6.7 | 22,080 | 37.7 | 10.6 | 253,255 | 69.0 | 7.0 |
| Pre-pregnancy BMI | |||||||||
| Underweight | 14,037 | 4.6 | 8.1 | 2,685 | 4.6 | 13.2 | 16,722 | 4.6 | 8.9 |
| Normal weight | 192,003 | 62.2 | 6.7 | 30,090 | 51.4 | 11.0 | 222,093 | 60.5 | 7.3 |
| Overweight | 61,445 | 19.9 | 6.9 | 13,404 | 22.9 | 10.6 | 74,849 | 20.4 | 7.6 |
| Obese | 41,099 | 13.3 | 8.3 | 12,318 | 21.1 | 11.6 | 53,417 | 14.5 | 9.1 |
| Rate of net gestational weight gain | |||||||||
| Slow | 70,333 | 22.8 | 7.3 | 16,487 | 28.2 | 11.8 | 86,820 | 23.6 | 8.1 |
| Appropriate | 166,127 | 53.8 | 6.5 | 27,314 | 46.7 | 10.4 | 193,441 | 52.7 | 7.1 |
| Excessive | 72,124 | 23.4 | 7.9 | 14,696 | 25.1 | 11.8 | 86,820 | 23.7 | 8.5 |
| Pre-pregnancy diabetes | |||||||||
| No | 306,542 | 99.3 | 6.9 | 57,917 | 99.0 | 11.0 | 364,459 | 99.3 | 7.6 |
| Yes | 2,042 | 0.7 | 21.6 | 580 | 1.0 | 25.5 | 2,622 | 0.7 | 22.5 |
| Gestational diabetes | |||||||||
| No | 291,824 | 94.6 | 6.8 | 53,944 | 95.4 | 11.3 | 347,646 | 94.7 | 7.5 |
| Yes | 16,760 | 5.4 | 9.9 | 4,553 | 4.6 | 8.9 | 19,435 | 5.3 | 10.6 |
| Pre-pregnancy hypertension | |||||||||
| No | 303,458 | 98.3 | 6.8 | 56,928 | 97.3 | 10.8 | 360,386 | 98.2 | 7.5 |
| Yes | 5,126 | 1.7 | 16.8 | 1,569 | 2.7 | 24.8 | 6,695 | 1.8 | 18.7 |
| Hypertensive disorders of pregnancy | |||||||||
| No | 281,934 | 91.4 | 6.2 | 51,285 | 87.7 | 9.5 | 333,219 | 93.5 | 6.7 |
| Yes | 26,650 | 8.6 | 15.9 | 7,212 | 12.3 | 22.9 | 33,862 | 9.2 | 17.4 |
| Asthma | |||||||||
| No | 293,352 | 95.1 | 6.9 | 53,661 | 91.7 | 11.1 | 347,013 | 94.5 | 7.6 |
| Yes | 15,232 | 4.9 | 8.4 | 4,836 | 8.3 | 12.0 | 20,068 | 5.5 | 9.2 |
Abbreviation: NHW, non-Hispanic white; NHB, non-Hispanic black; PTB, preterm birth
column percent
row percent
Table 2 presents results from the joint effects and stratified Poisson multivariable regression models estimating the RR of PTB, spontaneous and clinician-initiated PTB by maternal age. The joint effects model, which allows between-race comparisons using a universal reference group (NHW women aged 25–29 years), produced two parallel J-shaped curves, with a subtle widening of the difference in the risk estimates at the tails of the age distribution and narrowing at ages 20–24 years (Figure 2, panel A). Among spontaneous PTBs, the risk estimates decrease with advancing maternal age, and the difference between the estimates by race narrows (Figure 2, panel C). Conversely, the risk of clinician-initiated PTB increased dramatically for both NHB and NHW women with advancing maternal age, with risk differences initially increasing, then remaining relatively constant from age 30 onwards (Figure 2, panel E).
Table 2.
Unadjusted and adjusted relative risk estimates of preterm birth and subtypes by maternal age
| Maternal age (years) |
Non-Hispanic White | Non-Hispanic Black (Universal reference) |
Non-Hispanic Black (Race-specific reference) |
All Women | ||||
|---|---|---|---|---|---|---|---|---|
| Rate ratio (95% confidence interval) | Rate ratio (95% confidence interval) | Rate ratio (95% confidence interval) | Rate ratio (95% confidence interval) | |||||
| Unadjusted | Adjusted | Unadjusted | Adjusted | Unadjusted | Adjusted | Unadjusted | Adjusted | |
| Preterm Birth | ||||||||
| <15 | 2.53 (1.66, 3.84) | 2.38 (1.56, 3.62) | 3.52 (2.62, 4.74) | 2.93 (2.17, 3.95) | 2.04 (1.51, 2.76) | 1.88 (1.39, 2.55) | 2.88 (2.26, 3.67) | 2.15 (1.68, 2.74) |
| 15–19 | 1.37 (1.30, 1.44) | 1.18 (1.12, 1.25) | 1.86 (1.76, 1.96) | 1.55 (1.46, 1.65) | 1.08 (1.00, 1.16) | 1.01 (0.93, 1.09) | 1.44 (1.39, 1.50) | 1.13 (1.08, 1.18) |
| 20–24 | 1.09 (1.05, 1.13) | 0.98 (0.94,1.02) | 1.66 (1.58, 1.74) | 1.38 (1.31, 1.45) | 0.96 (0.90, 1.03) | 0.91 (0.84, 0.98) | 1.14 (1.10, 1.18) | 0.97 (0.93, 1.00) |
| 25–29 | 1.00 (reference) | 1.00 (reference) | 1.72 (1.62, 1.84) | 1.49 (1.40, 1.59) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 30–34 | 1.07 (1.03, 1.11) | 1.14 (1.10, 1.19) | 1.87 (1.73, 2.02) | 1.65 (1.53, 1.78) | 1.08 (0.99, 1.19) | 1.12 (1.02, 1.24) | 1.04 (1.00, 1.08) | 1.13 (1.09, 1.17) |
| 35–39 | 1.31 (1.25, 1.37) | 1.37 (1.31, 1.43) | 2.24 (2.02, 2.48) | 1.91 (1.73, 2.12) | 1.30 (1.16, 1.46) | 1.31 (1.17, 1.48) | 1.27 (1.22, 1.33) | 1.35 (1.30, 1.41) |
| ≥40 | 1.65 (1.54, 1.76) | 1.63 (1.52, 1.74) | 2.58 (2.18, 3.05) | 2.15 (1.82, 2.54) | 1.50 (1.26, 1.78) | 1.46 (1.23, 1.75) | 1.59 (1.50, 1.69) | 1.60 (1.50, 1.70) |
| Spontaneous Preterm Birth | ||||||||
| <15 | 2.68 (1.58, 4.53) | 2.35 (1.39, 3.98) | 4.60 (3.30, 6.42) | 3.60 (2.57, 5.04) | 2.81 (2.00, 3.95) | 2.30 (1.63, 3.25) | 3.57 (2.69, 4.73) | 2.44 (1.84, 3.25) |
| 15–19 | 1.51 (1.42, 1.61) | 1.25 (1.17, 1.34) | 2.12 (1.98, 2.26) | 1.77 (1.64, 1.90) | 1.29 (1.18, 1.42) | 1.11 (1.00, 1.23) | 1.63 (1.55, 1.71) | 1.23 (1.16, 1.30) |
| 20–24 | 1.14 (1.08, 1.20) | 1.00 (0.95, 1.06) | 1.70 (1.60, 1.81) | 1.44 (1.35, 1.54) | 1.04 (0.95, 1.14) | 0.92 (0.84, 1.02) | 1.19 (1.15, 1.25) | 0.99 (0.95, 1.04) |
| 25–29 | 1.00 (reference) | 1.00 (reference) | 1.64 (1.51, 1.78) | 1.51 (1.39, 1.65) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 30–34 | 1.06 (1.00, 1.11) | 1.13 (1.08, 1.19) | 1.64 (1.48, 1.82) | 1.61 (1.45, 1.79) | 1.00 (0.88, 1.13) | 1.10 (0.97, 1.25) | 1.03 (0.98, 1.07) | 1.12 (1.07, 1.17) |
| 35–39 | 1.21 (1.15, 1.29) | 1.30 (1.22, 1.38) | 1.64 (1.41, 1.91) | 1.61 (1.38, 1.88) | 1.00 (0.84, 1.18) | 1.12 (0.94, 1.33) | 1.16 (1.10, 1.23) | 1.27 (1.20, 1.34) |
| ≥40 | 1.19 (1.08, 1.32) | 1.24 (1.12, 1.34) | 1.54 (1.16, 2.05) | 1.50 (1.13, 2.00) | 0.94 (0.70, 1.26) | 1.03 (0.76, 1.38) | 1.14 (1.04, 1.25) | 1.20 (1.10, 1.32) |
| Clinician-initiated Preterm Birth | ||||||||
| <15 | 2.60 (1.30, 5.21) | 2.66 (1.33, 5.33) | 2.22 (1.15, 4.28) | 1.96 (1.02, 3.78) | 1.12 (0.58, 2.17) | 1.19 (0.61, 2.14) | 2.16 (1.34, 3.48) | 1.74 (1.08, 2.81) |
| 15–19 | 1.17 (1.07, 1.28) | 1.05 (0.96, 1.16) | 1.54 (1.40, 1.70) | 1.26 (1.14, 1.40) | 0.78 (0.69, 0.88) | 0.80 (0.70, 0.91) | 1.19 (1.11, 1.27) | 0.95 (0.88, 1.03) |
| 20–24 | 1.02 (0.96, 1.09) | 0.94 (0.87, 1.01) | 1.67 (1.54, 1.81) | 1.33 (1.22, 1.45) | 0.85 (0.76, 0.94) | 0.86 (0.77, 0.97) | 1.07 (1.01, 1.13) | 0.92 (0.86, 0.97) |
| 25–29 | 1.00 (reference) | 1.00 (reference) | 1.98 (1.79, 2.18) | 1.54 (1.40, 1.71) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 30–34 | 1.09 (1.03, 1.16) | 1.17 (1.10, 1.25) | 2.39 (2.13, 2.67) | 1.82 (1.62, 2.04) | 1.21 (1.05, 1.38) | 1.17 (1.02, 1.35) | 1.07 (1.01, 1.13) | 1.17 (1.10, 1.24) |
| 35–39 | 1.50 91.40, 1.61) | 1.52 (1.42, 1.64) | 3.46 (3.02, 3.97) | 2.44 (2.12, 2.80) | 1.75 (1.50, 2.05) | 1.58 (1.34, 1.86) | 1.48 (1.39, 1.58) | 1.53 (1.43, 1.63) |
| ≥40 | 2.48 (2.26, 2.71) | 2.25 (2.05, 2.47) | 4.59 (3.73, 5.65) | 3.09 (2.51, 3.81) | 2.32 (1.86, 2.89) | 1.98 (1.58, 2.48) | 2.39 (2.19, 2.59) | 2.21 (2.03, 2.41) |
Universal, universal reference group (white women ages 25–29)
Race-specific, race-specific reference groups (black or white women ages 25–29, respectively)
Rate ratios were adjusted for maternal nativity, insurance status, smoking status, level of education, prenatal care, pre-pregnancy BMI, rate of net gestational weight gain, diabetes, hypertensive disorders and asthma
Figure 2.

Adjusted relative risk of PTB by maternal age for NHW and NHB primiparae in California, 2008–2012. Joint effects models of (A) preterm birth, (C) spontaneous preterm birth, and (E) clinician initiated preterm birth use a universal reference group for comparisons. Stratified models of (B) preterm birth, (D) spontaneous preterm birth, and (F) clinician initiated preterm birth use race-specific reference groups for comparisons.
The stratified model used race-specific reference groups, accounting for the effect of higher baseline rates of PTB among NHB women and isolating the independent effect of maternal age by race. This model produced two similar J-shaped curves with convergence of RR from age 20 years onward (Figure 2, panel B). The confidence intervals for the RR estimates of PTB overlap at almost all maternal ages. For maternal ages 15–19 years, there was a lower relative risk of PTB for NHB (RR 1.01, 95% CI 0.93, 1.09) compared to NHW women (RR 1.18, 95% CI 1.12, 1.25).
Among NHB women, the adjusted relative risk of PTB by age was similar with overlapping confidence intervals for women aged 15–19 years (RR 1.01, 95% CI 0.93, 1.09), 20–24 years (RR 0.91, 95% CI 0.84, 0.98) and 25–29 years (reference). Among NHW women, the adjusted RR of PTB was similar for ages 20–24 years (RR 0.98, 95% CI 0.94, 1.02) and 25–29 years (RR 1.00, reference), but did not overlap and was modestly increased among women aged 15–19 years (RR 1.18, 95% CI 1.12, 1.25).
For PTB subtypes, the stratified models demonstrated decreasing risk estimates with advancing maternal age for spontaneous PTB (Figure 2, panel D), and a U-shaped curve with increasing risk estimates from age 20 years onwards for clinician-initiated PTB (Figure 2, panel F). Interestingly, there was convergence of the NHB and NHW curves across all maternal ages for spontaneous PTB, while this convergence occurs only from age 20 years and older for clinician-initiated PTB.
Table 3 presents the adjusted associations between each covariate and PTB. The highest risk of PTB (RR >2) was found among women with pre-pregnancy diabetes, hypertensive disorders of pregnancy (including pregnancy-induced hypertension, preeclampsia, eclampsia and HELLP syndrome [Hemolysis, Elevated Liver enzymes, Low Platelets]), or with no prenatal care. Women with higher levels of education (associates degree, bachelor’s degree or higher), earlier initiation of prenatal care, and who were not born in the United States had slightly decreased risk of PTB.
Table 3.
Adjusted Rate Ratios (95% confidence interval) of Preterm Birth
| Race-specific |
All women | ||
|---|---|---|---|
| Non-Hispanic White | Non-Hispanic Black | ||
| Adjusted rate ratio (95% CI) | Adjusted rate ratio (95% CI) | Adjusted rate ratio (95% CI) | |
| Maternal Nativity: US born (vs foreign born) | 1.05 (1.01, 1.10) | 1.26 (1.14, 1.39) | 1.08 (1.04, 1.13) |
| Maternal Education | |||
| None/not age appropriate | 1.23 (1.13, 1.33) | 1.12 (1.01, 1.24) | 1.19 (1.11, 1.27) |
| High school degree, some college or age appropriate | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) |
| Associates degree | 0.93 (0.88, 0.98) | 0.96 (0.86, 1.08) | 0.93 (0.88, 0.98) |
| Bachelor’s degree or more | 0.85 (0.82, 0.89) | 0.83 (0.76, 0.90) | 0.84 (0.82, 0.87) |
| Insurance status | |||
| None | 1.28 (1.14, 1.43) | 1.48 (1.26, 1.75) | 1.35 (1.23, 1.48) |
| Public | 1.14 (1.10, 1.18) | 1.07 (1.01, 1.13) | 1.12 (1.09, 1.15) |
| Private | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) |
| Initiation of Prenatal care | |||
| 1st trimester | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) |
| 2nd trimester | 0.91 (0.86, 0.95) | 0.96 (0.90, 1.03) | 0.93 (0.89, 0.96) |
| 3rd trimester | 0.80 (0.71, 0.90) | 0.77 (0.67, 0.90) | 0.79 (0.72, 0.87) |
| None | 3.01 (2.51, 3.61) | 2.25 (1.79, 2.83) | 2.66 (2.31, 3.07) |
| Ever Smoker | 1.05 (0.99, 1.10) | 1.16 (1.03, 1.29) | 1.07 (1.02, 1.12) |
| Pre-pregnancy BMI | |||
| Underweight | 1.22 (1.15, 1.30) | 1.25 (1.12, 1.39) | 1.23 (1.16, 1.300) |
| Normal weight | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) |
| Overweight | 0.94 (0.91, 0.98) | 0.91 (0.86, 0.97) | 0.94 (0.91, 0.97) |
| Obese | 0.95 (0.91, 0.99) | 0.84 (0.79, 0.90) | 0.92 (0.89, 0.95) |
| Rate of net gestational weight gain | |||
| Slow | 1.07 (1.04, 1.11) | 1.16 (1.09, 1.23) | 1.10 (1.06, 1.13) |
| Appropriate | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) |
| Excessive | 1.11 (1.08, 1.15) | 1.06 (1.00, 1.13) | 1.10 (1.07, 1.13) |
| Pre-pregnancy diabetes | 2.14 (1.94, 2.36) | 1.56 (1.32, 1.85) | 1.96 (1.81, 2.13) |
| Gestational diabetes | 1.20 (1.14, 1.27) | 1.15 (1.04, 1.28) | 1.19 (1.14, 1.25) |
| Pre-pregnancy hypertension | 1.61 (1.49, 1.72) | 1.58 (1.41, 1.76) | 1.60 (1.50, 1.69) |
| Hypertensive disorders of pregnancy | 2.35 (2.27, 2.44) | 2.28 (2.15, 2.42) | 2.33 (2.26, 2.41) |
| Asthma | 1.10 (1.04, 1.17) | 1.04 (0.95, 1.13) | 1.08 (1.03, 1.14) |
CI, confidence interval
Rate ratios were adjusted for maternal nativity, insurance status, smoking status, level of education, prenatal care, pre-pregnancy BMI, rate of net gestational weight gain, diabetes, hypertensive disorders and asthma
Comment
Principal findings
This study shows a J-shaped relation between maternal age and the risk of PTB among singleton, live-born first births, with the highest risk of PTB among women under 15 years of age and the lowest risk among women aged 20–24 years. Stratifying age by race/ethnicity and using a universal reference group, the joint effects model demonstrated uniformly higher risk of PTB among primiparae NHB compared to primiparae NHW women, except among those younger than 15 years with clinician-initiated PTB, where the risk was higher among NHW compared to NHB women. The race-stratified model estimates, which used race-specific reference groups and adjusted for multiple covariates as in the joint effects model, produced superimposed curves which converged with advancing maternal age. The shape of the curves for PTB, spontaneous PTB and clinician-initiated PTB were distinct and maintained their respective shapes across the joint effects and stratified models (Figure 1). There is no evidence of effect modification by maternal age on the risk of preterm birth by race.
Strengths of the study
This study adds to the literature by presenting associations between maternal age and PTB, adjusted for multiple confounders and stratified by maternal race/ethnicity, using both universal and race-specific reference groups. The large sample size and ability to distinguish spontaneous from clinician-initiated preterm births facilitates a more granular examination of associations with maternal age, highlighting similarities and differences in patterns by race/ethnicity, parity, and etiology.
Limitations of the data
This study restricted the sample population to singleton first births, which was imposed to control for the potential cumulative effect of multiple previous pregnancies, prior PTB, short inter-pregnancy interval and multiple gestations, all of which are known risk factors for PTB.46,47 While this constraint permits controlling for confounding by design, it may limit the generalisability of results to women across all parity groups. The scope of the study was limited to non-Hispanic white and black women; we excluded a large percentage of births due to Hispanic ethnicity and Asian background. Because of this intentional restriction, it is unclear the extent to which these findings may be generalisable to all first births in the US.
We recognize that determination of gestational age based on last menstrual period (LMP) has some limitations, and tends to over-estimate preterm births and post-term births compared to best obstetrical estimate (OE).53 However, the percent of preterm infants within our sample closely approximated the state-specific birth data for 2013 based on OE, with the maximum discrepancy noted among infants 34–36 weeks gestational age (LMP 5.5% versus OE 6.1%). The LMP-based gestational age data was quite complete, with only 2.5% of the data missing or out of the range of biologic plausibility and demonstrated a unimodal distribution peaking at 39–40 weeks. We also note that the data was robust to multiple sensitivity analyses; together these factors lead us to believe that the likelihood of misclassification bias causing error in our point estimates is low.
Our covariates allowed us to adjust for multiple indicators of the maternal environment; however, we recognise that maternal level of education and maternal insurance status, though widely-accepted proxies for socioeconomic status, do not fully capture the intricacies of a woman’s social context and remain imperfect measures of the social environment. Moving forward, analyses incorporating neighbourhood or area-level exposures present an exciting avenue for exploration.8,54
Interpretation
This study indicates that at all maternal ages, primiparous NHB women have higher risks of PTB compared to primiparous NHW women, even after adjusting for sociodemographic and health characteristics. However, our results also suggest that the within-group risk of PTB by maternal age for NHB women is similar to the within-group risk among NHW women across all maternal age groups, and does not diverge with advancing maternal age as previously suggested.4,8,10,18,19,55 This finding suggests that the association between maternal age and the risk of PTB does not vary by race in this group of primiparous women, and the effect of maternal age does not appear to explain persistent race-disparity in PTB. However, this interpretation does not imply that maternal age and race/ethnicity are not associated with PTB. Numerous studies have demonstrated that women at the extremes of age (compared to those in their 20s) and black women (compared to white women) experience increased risk of PTB,56 which our results confirm. Rather, the findings presented here suggest that the effect of maternal age on PTB and its subtypes among primiparous women does not vary by race.
Additionally, the age-related increasing risk of PTB demonstrated in this study appears to be driven by clinician-initiated preterm births more than spontaneous preterm births and is independent of race/ethnicity. This finding speaks to differences in PTB etiology and pathophysiology by maternal age and may help identify opportunities for creating more targeted screening, intervention and prevention strategies by maternal age, regardless of maternal race/ethnicity.
Though the field of disparities research is expanding rapidly, identification of causal factors directly influencing reproductive outcomes remains elusive. Though recent studies have implicated racism and stress as etiologic factors driving disparities,35,57–60 how these concepts translate into causative biological mechanisms and pathways remains complex and poorly understood. Promising research investigating concepts of allostatic load, biological age and the role of the stress response and resiliency in relation to poor health outcomes is ongoing, but the mechanisms by which these factors affect birth timing have yet to be delineated. Contributory mechanisms are unlikely to be straight-forward, as mounting evidence implicates a complicated interplay between individual biology, environment, and social forces.
Conclusions
Moving forward, it will be important to critically evaluate the relationship between maternal age and race/ethnicity within other groups, including women of Hispanic ethnicity and Asian origin, to enrich our understanding of age-related trends in PTB and expand generalizability of these findings. Similarly, broadening analyses to include stillbirths and higher parity births will also add to the understanding of relationships between maternal age and birth outcomes. Future studies should distinguish between spontaneous and clinician-initiated preterm births, as age-based associations may not be consistent across subtypes. It will also be important to independently evaluate whether maternal age modifies the effect between race/ethnicity and other perinatal outcomes to determine whether and how etiologies, mechanisms and interventions overlap with or differ from those implicated in PTB.
Supplementary Material
Social media quote
Maternal age at delivery does not appear to drive racial disparities in preterm birth among first-time non-Hispanic white and black mothers
Synopsis
Study question:
Is there a differential effect of maternal age on the risk of preterm birth for non-Hispanic black compared to non-Hispanic white women?
What’s already known:
The risk of preterm birth increases with advancing maternal age, but it is unclear whether the age of highest risk and the rate at which the risk increases is the same for non-Hispanic white and non-Hispanic black women.
What this study adds:
This study suggests that among first-time mothers, the effect of maternal age on the risk of preterm birth is the same for non-Hispanic black and non-Hispanic white women, and maternal age is not the driving force behind disparities in rates of preterm birth.
Acknowledgements
The authors wish to thank Leah Horton for her assistance with data analysis, and the anonymous peer reviewers and the Editor for their valuable suggestions in revising the final manuscript. This work was partially supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH (grant T32 HD007094, AMK); and by the Sutland-Pakula Endowed Fellowship for Neonatal Research (AMK). The funding sources had no involvement in the study design; collection, analysis or interpretation of data; writing of the report, or in the decision to submit the manuscript for publication.
References
- 1.Giurgescu C, McFarlin BL, Lomax J, Craddock C, Albrecht A. Racial discrimination and the black-white gap in adverse birth outcomes: a review. J Midwifery Womens Health. 2011;56(4):362–370. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Vahratian A, Buekens P, Alexander GR. State-specific trends in preterm delivery: are rates really declining among non-Hispanic African Americans across the United States? Matern Child Health J. 2006;10(1):27–32. [DOI] [PubMed] [Google Scholar]
- 3.Geronimus AT. The weathering hypothesis and the health of African-American women and infants: evidence and speculations. Ethn Dis. 1992;2:207–221. [PubMed] [Google Scholar]
- 4.Buescher PA, Mittal M. Racial disparities in birth outcomes increase with maternal age: recent data from North Carolina. N C Med J. 2006;67:16–20. [PubMed] [Google Scholar]
- 5.Thorpe RJ, Fesahazion RG, Parker L, et al. Accelerated Health Declines among African Americans in the USA. J Urban Health. 2016;93(5):808–819. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Patchen L, Rebok G, Astone NM. Differences in Obesity Rates Among Minority and White Women: The Latent Role of Maternal Stress. J Midwifery Womens Health. 2016;61(4):489–496. [DOI] [PubMed] [Google Scholar]
- 7.Schmeer KK, Tarrence J. Racial-ethnic Disparities in Inflammation: Evidence of Weathering in Childhood? J Health Soc Behav. 2018;59(3):411–428. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Love C, David RJ, Rankin KM, Collins JW Jr., Exploring weathering: effects of lifelong economic environment and maternal age on low birth weight, small for gestational age, and preterm birth in African-American and white women. Am J Epidemiol. 2010;172:127–134. [DOI] [PubMed] [Google Scholar]
- 9.Stevens-Simon C The weathering hypothesis. Am J Public Health. 2002;92:507–508; author reply 508. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Geronimus AT, Hicken M, Keene D, Bound J. “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States. Am J Public Health. 2006;96(5):826–833. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Lu MC, Kotelchuck M, Hogan V, Jones L, Wright K, Halfon N. Closing the Black-White gap in birth outcomes: a life-course approach. Ethn Dis. 2010;20(1 Suppl 2):S2–62-76. [PMC free article] [PubMed] [Google Scholar]
- 12.Lu MC, Halfon N. Racial and ethnic disparities in birth outcomes: a life-course perspective. Matern Child Health J. 2003;7:13–30. [DOI] [PubMed] [Google Scholar]
- 13.Gluckman PD, Hanson MA, Buklijas T. A conceptual framework for the developmental origins of health and disease. J Dev Orig Health Dis. 2010;1(1):6–18. [DOI] [PubMed] [Google Scholar]
- 14.Diez Roux AV. Complex systems thinking and current impasses in health disparities research. Am J Public Health. 2011;101(9):1627–1634. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Pearl M, Ahern J, Hubbard A, et al. Life-course neighbourhood opportunity and racial-ethnic disparities in risk of preterm birth. Paediatr Perinat Epidemiol. 2018;32(5):412–419. [DOI] [PubMed] [Google Scholar]
- 16.Alwin DF, Wray LA. A life-span developmental perspective on social status and health. J Gerontol B Psychol Sci Soc Sci. 2005;60 Spec No 2:7–14. [DOI] [PubMed] [Google Scholar]
- 17.Dennis JA, Mollborn S. Young maternal age and low birth weight risk: An exploration of racial/ethnic disparities in the birth outcomes of mothers in the United States. Soc Sci J. 2013;50(4):625–634. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Rich-Edwards JW, Buka SL, Brennan RT, Earls F. Diverging associations of maternal age with low birthweight for black and white mothers. Int J Epidemiol. 2003;32(1):83–90. [DOI] [PubMed] [Google Scholar]
- 19.Reichman NE, Pagnini DL. Maternal age and birth outcomes: data from New Jersey. Fam Plann Perspect. 1997;29:268–272, 295. [PubMed] [Google Scholar]
- 20.Holzman C, Eyster J, Kleyn M, et al. Maternal weathering and risk of preterm delivery. Am J Public Health. 2009;99:1864–1871. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Blumenshine P, Egerter S, Barclay CJ, Cubbin C, Braveman PA. Socioeconomic disparities in adverse birth outcomes: a systematic review. Am J Prev Med. 2010;39(3):263–272. [DOI] [PubMed] [Google Scholar]
- 22.Braveman PA, Heck K, Egerter S, et al. The role of socioeconomic factors in Black-White disparities in preterm birth. Am J Public Health. 2015;105(4):694–702. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Dunlop AL, Kramer MR, Hogue CJ, Menon R, Ramakrishan U. Racial disparities in preterm birth: an overview of the potential role of nutrient deficiencies. Acta Obstet Gynecol Scand. 2011;90(12):1332–1341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Giscombé CL, Lobel M. Explaining disproportionately high rates of adverse birth outcomes among African Americans: the impact of stress, racism, and related factors in pregnancy. Psychol Bull. 2005;131(5):662–683. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.DuPlessis HM, Bell R, Richards T. Adolescent pregnancy: understanding the impact of age and race on outcomes. J Adolesc Health. 1997;20:187–197. [DOI] [PubMed] [Google Scholar]
- 26.Srinivasjois RM, Shah S, Shah PS, Knowledge Synthesis Group on Determinants Of Preterm LBWB. Biracial couples and adverse birth outcomes: a systematic review and meta-analyses. Acta Obstet Gynecol Scand. 2012;91:1134–1146. [DOI] [PubMed] [Google Scholar]
- 27.Howell EA, Janevic T, Hebert PL, Egorova NN, Balbierz A, Zeitlin J. Differences in Morbidity and Mortality Rates in Black, White, and Hispanic Very Preterm Infants Among New York City Hospitals. JAMA Pediatr. 2018;172(3):269–277. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Anderson JG, Rogers EE, Baer RJ, et al. Racial and Ethnic Disparities in Preterm Infant Mortality and Severe Morbidity: A Population-Based Study. Neonatology. 2018;113(1):44–54. [DOI] [PubMed] [Google Scholar]
- 29.Martin JA, Hamilton BE, Osterman MJ, Driscoll AK, Mathews TJ. Births: Final Data for 2015. Natl Vital Stat Rep. 2017;66(1):1. [PubMed] [Google Scholar]
- 30.Liu K, Case A, COMMITTEE REAI. Advanced reproductive age and fertility. J Obstet Gynaecol Can. 2011;33(11):1165–1175. [DOI] [PubMed] [Google Scholar]
- 31.Graham J, Zhang L, Schwalberg R. Association of maternal chronic disease and negative birth outcomes in a non-Hispanic Black-White Mississippi birth cohort. Public Health Nurs. 2007;24:311–317. [DOI] [PubMed] [Google Scholar]
- 32.Blackmore CA, Savitz DA, Edwards LJ, Harlow SD, Bowes WA Jr, Racial differences in the patterns of preterm delivery in central North Carolina, USA. Paediatr Perinat Epidemiol. 1995;9:281–295. [DOI] [PubMed] [Google Scholar]
- 33.Geronimus AT, Bound J. Black/white differences in women’s reproductive-related health status: evidence from vital statistics. Demography. 1990;27:457–466. [PubMed] [Google Scholar]
- 34.Snowden JM, Mission JF, Marshall NE, et al. The Impact of maternal obesity and race/ethnicity on perinatal outcomes: Independent and joint effects. Obesity (Silver Spring). 2016;24(7):1590–1598. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Alhusen JL, Bower KM, Epstein E, Sharps P. Racial Discrimination and Adverse Birth Outcomes: An Integrative Review. J Midwifery Womens Health. 2016;61(6):707–720. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Klebanoff MA, Yossef-Salameh L, Latimer C, et al. Development and Validation of an Algorithm to Determine Spontaneous versus Provider-Initiated Preterm Birth in US Vital Records. Paediatr Perinat Epidemiol. 2016;30(2):134–140. [DOI] [PubMed] [Google Scholar]
- 37.Viera AJ, Garrett JM. Understanding interobserver agreement: the kappa statistic. Fam Med. 2005;37(5):360–363. [PubMed] [Google Scholar]
- 38.Kleinman JC, Pierre MB, Madans JH, Land GH, Schramm WF. The effects of maternal smoking on fetal and infant mortality. Am J Epidemiol. 1988;127(2):274–282. [DOI] [PubMed] [Google Scholar]
- 39.Lau TK, Pang MW, Sahota DS, Leung TN. Impact of hypertensive disorders of pregnancy at term on infant birth weight. Acta Obstet Gynecol Scand. 2005;84(9):875–877. [DOI] [PubMed] [Google Scholar]
- 40.Rosenberg TJ, Garbers S, Lipkind H, Chiasson MA. Maternal obesity and diabetes as risk factors for adverse pregnancy outcomes: differences among 4 racial/ethnic groups. Am J Public Health. 2005;95(9):1545–1551. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Dewyea VA, Nelson MR, Martin BL. Asthma in pregnancy. Allergy Asthma Proc. 2005;26(4):323–325. [PubMed] [Google Scholar]
- 42.Metcalfe A, Wick J, Ronksley P. Racial disparities in comorbidity and severe maternal morbidity/mortality in the United States: an analysis of temporal trends. Acta Obstet Gynecol Scand. 2018;97(1):89–96. [DOI] [PubMed] [Google Scholar]
- 43.Power ML, Lott ML, Mackeen AD, DiBari J, Schulkin J. A retrospective study of gestational weight gain in relation to the Institute of Medicine’s recommendations by maternal body mass index in rural Pennsylvania from 2006 to 2015. BMC Pregnancy Childbirth. 2018;18(1):239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Kramer MS, McLean FH, Eason EL, Usher RH. Maternal nutrition and spontaneous preterm birth. Am J Epidemiol. 1992;136(5):574–583. [DOI] [PubMed] [Google Scholar]
- 45.Robledo CA, Yeung EH, Mendola P, et al. Examining the Prevalence Rates of Preexisting Maternal Medical Conditions and Pregnancy Complications by Source: Evidence to Inform Maternal and Child Research. Matern Child Health J. 2017;21(4):852–862. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Ahrens KA, Hutcheon JA, Ananth CV, et al. Report of the Office of Population Affairs’ expert work group meeting on short birth spacing and adverse pregnancy outcomes: Methodological quality of existing studies and future directions for research. Paediatr Perinat Epidemiol. 2019;33(1):O5–O14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Ahrens KA, Nelson H, Stidd RL, Moskosky S, Hutcheon JA. Short interpregnancy intervals and adverse perinatal outcomes in high-resource settings: An updated systematic review. Paediatr Perinat Epidemiol. 2019;33(1):O25–O47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Martin JA, Hamilton BE, Sutton PD, Ventura SJ, Mathews TJ, Osterman MJ. Births: final data for 2008. Natl Vital Stat Rep. 2010;59(1):1, 3–71. [PubMed] [Google Scholar]
- 49.Martin JA, Hamilton BE, Ventura SJ, et al. Births: final data for 2009. Natl Vital Stat Rep. 2011;60(1):1–70. [PubMed] [Google Scholar]
- 50.Martin JA, Hamilton BE, Ventura SJ, Osterman MJ, Wilson EC, Mathews TJ. Births: final data for 2010. Natl Vital Stat Rep. 2012;61(1):1–72. [PubMed] [Google Scholar]
- 51.Martin JA, Hamilton BE, Ventura SJ, Osterman MJ, Mathews TJ. Births: final data for 2011. Natl Vital Stat Rep. 2013;62(1):1–69, 72. [PubMed] [Google Scholar]
- 52.Martin JA, Hamilton BE, Osterman MJ, Curtin SC, Matthews TJ. Births: final data for 2012. Natl Vital Stat Rep. 2013;62(9):1–68. [PubMed] [Google Scholar]
- 53.Martin JA, Osterman MJ, Kirmeyer SE, Gregory EC. Measuring Gestational Age in Vital Statistics Data: Transitioning to the Obstetric Estimate. Natl Vital Stat Rep. 2015;64(5):1–20. [PubMed] [Google Scholar]
- 54.Collins JW Jr., David RJ, Simon DM, Prachand NG. Preterm birth among African American and white women with a lifelong residence in high-income Chicago neighborhoods: an exploratory study. Ethn Dis. 2007;17:113–117. [PubMed] [Google Scholar]
- 55.Geronimus AT. Black/white differences in the relationship of maternal age to birthweight: a population-based test of the weathering hypothesis. Soc Sci Med. 1996;42(4):589–597. [DOI] [PubMed] [Google Scholar]
- 56.Fuchs F, Monet B, Ducruet T, Chaillet N, Audibert F. Effect of maternal age on the risk of preterm birth: A large cohort study. PLoS One. 2018;13(1):e0191002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Staneva A, Bogossian F, Pritchard M, Wittkowski A. The effects of maternal depression, anxiety, and perceived stress during pregnancy on preterm birth: A systematic review. Women Birth. 2015;28(3):179–193. [DOI] [PubMed] [Google Scholar]
- 58.Shapiro GD, Fraser WD, Frasch MG, Séguin JR. Psychosocial stress in pregnancy and preterm birth: associations and mechanisms. J Perinat Med. 2013;41(6):631–645. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Dominguez TP. Race, racism, and racial disparities in adverse birth outcomes. Clin Obstet Gynecol. 2008;51(2):360–370. [DOI] [PubMed] [Google Scholar]
- 60.Dominguez TP, Dunkel-Schetter C, Glynn LM, Hobel C, Sandman CA. Racial differences in birth outcomes: the role of general, pregnancy, and racism stress. Health Psychol. 2008;27(2):194–203. [DOI] [PMC free article] [PubMed] [Google Scholar]
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