Revista Brasileira de Ginecologia e Obstetrícia

Perinatal Outcomes and Factors Associated with Ethnic Group in cases of Preterm Birth: the Multicenter Study on Preterm Birth in Brazil

DOI: 10.1055/s-0041-1739492 - volume 43 - Janeiro 2022

Karayna Gil Fernandes, Renato Teixeira Souza, Renato Passini, Ricardo Porto Tedesco, José Guilherme Cecatti

Abstract

Objective
To investigate the characteristics of women who had preterm birth (PTB) and related outcomes according to ethnicity.

Methods
A secondary analysis of a multicenter cross-sectional study conducted in Brazil. Women who had PTB were classified by self-report as white and non-white. Clinical, pregnancy, and maternal data were collected through postpartum interviews and reviews of medical charts. The sociodemographic, obstetric and clinical characteristics of the women, as well as the mode of delivery and the neonatal outcomes among different ethnic groups were compared through a bivariate analysis.

Results
Of the 4,150 women who had PTB, 2,317 (55.8%) were non-white, who were more likely: to be younger than 19 years of age (prevalence ratio [PR]: 1.05; 95% confidence interval [95%CI]: 1.01-1.09); to be without a partner; to live on low income; to have lower levels of schooling; to have ≥ 2 children; to perform strenuous work; to be fromthe Northeastern region of Brazil rather than the from Southern region; to have a history of ≥ 3 deliveries; to have an interpregnancy interval<12 months; to have pregnancy complications such as abortion, PTB, preterm premature rupture of membranes (pPROM), and low birth weight; to initiate antenatal care (ANC) visits in the second or third trimesters; to have have an inadequate number of ANC visits; to be under continuous overexertion; to smoke in the first and second or third trimesters; and to have anemia and gestational hypertension. The maternal and neonatal outcomes did not differ between the groups, except for the higher rate of low birth weight (73.7% versus 69.0%) in infants born to non-white women, and the higher rate of seizures (4.05% versus 6.29%) in infants born to white women.

Conclusion
Unfavorable conditions weremore common in non-whites than inwhites. Proper policies are required to decrease inequalities, especially in the context of prematurity, when women and their neonates have specific needs.

Full Text

Introduction

Preterm birth (PTB) is a public health problem that may affect different strata of the population in an unequal manner. In general, PTBs affect 1 in every 8 infants born in Brazil, and is the main cause of neonatal morbidity and mortality.123 Preterm birth has a huge impact on all those involved (the individual, the family, or the community).3

It is widely known that maternal age, race/ethnicity, smoking, marital status, and socioeconomic level are factors related to a higher probability of having PTB.14 Racial/ethnic inequality is related to an increased risk of PTB in black women, although the determinants of ethnic disparity in PTBs are still unknown, particularly in extreme PTBs.5 Studies6 have shown higher PTB rates among black women, which may be justified by social disparities. Nevertheless, this association remains obscure. Some studies7 have shown that, even after adjusting for this potential bias (social disparity), PTB rates continue to be higher among black women. In 2018, a systematic review8 showed that PTB is 1.5 times more common among black women than among non black women. The study8 also concluded that there is a paucity of studies evaluating the ethnic aspects involved in this risk relation, and the assessment of the results from the literature search conducted by the authors suggested a publication bias.

Maternal stress before and during pregnancy and genital tract infection also increase the risk of PTB,910 in alignment with another study11 that showed that black infants are more likely to be born preterm in a metropolitan area with racial segregation than an infant born to a black woman living in a non-segregated metropolitan area, demonstrating that the environment where the woman lives exerts an influence on pregnancy outcomes.91011

Factors related to PTBs have not yet been completely elucidated. Furthermore, the distribution of these factors by race among the population is still incompletely explored. Advances in the identification of populations at risk of PTB and the recognition of the burden of consequences of PTB are of the utmost importance for the development of public policies intended to minimize the impact of this public health problem. The aim of the present study is to investigate the ethnic differentials in the characterization and determination of PTBs and their respective maternal and neonatal outcomes, according to a multicenter study conducted in Brazil.

 

Methods

The present study is a secondary analysis of the Multicenter Study on Preterm Birth in Brazil (Estudo Multicêntrico de Investigação de Prematuridade no Brasil, EMIP, in Portuguese), a cross-sectional study in which the authors conducted a prospective surveillance of all PTBs occurring from April 2011 to July 2012 in 20 referral hospitals distributed throughout the 3 most populated regions of Brazil (Southern, Southeastern, and Northeastern).31213 The current analytical approach is to evaluate an association between ethnicity (defined by skin color) as an exposure factor and preterm deliveries. Two groups were considered: whites and non-whites. Maternal and perinatal outcomes were compared in both groups. In addition, an association between other maternal and pregnancy characteristics and PTB among non-white women was also investigated.

The methodological details of this study have already been described in other EMIP publications.31213 In brief, the participating centers conducted a prospective surveillance of 33.740 deliveries during the study period, including all pregnant women admitted due to PTB during the study period (less than 37 weeks of gestation), irrespective of the cause. The women were informed about the study. Data collection began after these women agreed to participate in the study and signed the consent form. Maternal and newborn data were collected in the postpartum period through a structured questionnaire applied by a duly trained research assistant. Information was collected through a review of the medical charts and in-person interviews with the woman prior to hospital discharge. Neonatal data were collected until hospital discharge or until 60 days postpartum.

For data standardization, in-person training was carried out to explain each step of data collection and data insertion into the specific platform of the study. For this procedure, an interviewer's manual was specially designed for the study, including all categories possible for each variable in the form, in addition to the procedures to which these women had been submitted.13 The data obtained were later typed into an electronic form (in the OpenClinica 3.0 platform) developed specifically for the study and available on the web page of the coordinating center of the study (Universidade Estadual de Campinas, UNICAMP, in Portuguese). The calculation of the sample size considered that the prevalence ratio (PR) of PTB in Brazil was of 6.5% in 2006. As a result, each subgroup required at least 1.054 women. The subgroup of spontaneous PTB contained patients with preterm premature rupture of membranes (pPROM) and those who started preterm labor spontaneously.3

For the current analysis, exposure variables were determined according to self-reported ethnicity. Women were then divided into a white and a non-white groups. To address whether maternal characteristics significantly vary according to ethnicity, maternal characteristics were divided into sociodemographic, obstetric history, and clinical care and antenatal care (ANC) characteristics. The sociodemographic variables included region of the country, maternal age, marital status, schooling, monthly income, number of children under 5 years of age, paid work during pregnancy, perceived strenuous work, and daily workload. Obstetric history (only for women with a previous pregnancy) included parity, and previous cesarian section, abortion, interpregnancy interval, PTB, pPROM and low birth weight. Finally, the clinical care and ANC characteristics were trimester when ANC visits began, adequate number of ANC visits, weight gain during pregnancy according to the first recorded weight before 20 weeks and the last recorded weight (the respective week of gestation was also recorded), perceived physical effort during pregnancy, smoking, urinary tract infection (including asymptomatic bacteriuria), vaginal bleeding, anemia (based on self-reports or medical records), chronic hypertension, diabetes (both preexisting or gestational diabetes), gestational hypertension, preeclampsia/eclampsia/hemolysis, elevated liver enzymes, and low platelet count (HELLP) syndrome, fetal malformation, fetal growth restriction, and multiple pregnancy.

A bivariate analysis was performed to determine the higher prevalence of different characteristics according to ethnicity using the PRs and the respective 95% confidence intervals (95%CIs). Maternal and neonatal outcomes were compared using proportions (expressed as percentages) and the Chi-squared test. The significance level adopted was of 5%. The Statistical Analysis System (SAS, SAS Institute, Cary, North Carolina, US) software for Windows, version 9.4, was used.

The study followed all international and national ethical guidelines for human research. All participants received information and instructions about the study. A consent form was read to dispel any doubts, which was signed after each woman agreed to participate in the study. The women were reassured that their identity would remain confidential, regardless of their participation in the study. The research was conducted in full compliance with the Declaration of Helsinki, and it was approved by the review board of the coordinating center and the Brazilian National Commission on Ethics in Research (Comissão Nacional de Ética em Pesquisa, Conep, in Portuguese) before the study began (Letter of approval 704/2009). Each participating center subsequently obtained approval from their local ethics committees before the study began.

 

Results

During the study period, surveillance of 33,740 deliveries was conducted, and 4,150 women who had PTB (12.3%) were identified and included in the EMIP study. Of the total number of women who had PTB, 1,833 (44.2%) were self-reported whites. and 2,317 (55.8%) were self-reported non-whites. Although the proportion of non-white women was statistically lower in the PTB group than in the term group,3 maternal outcomes such as the subtype of PTB, onset of labor and mode of delivery did not differ between the groups (Table 1).

Characteristics Non-white women White women Total p-value
n (%) n (%)
Preterm birth
 Spontaneous 839 (36.2) 652 (35.6) 1,491 0.6932
 Therapeutic or elective 793 (34.2) 675 (36.8) 1,468 0.0826
 Preterm premature rupture of membranes 685 (29.6) 506 (27.6) 1,191 0.1767
Onset of labor
 Spontaneous 1,265 (54.6) 952 (51.9) 2,217 0.1080
 Elective cesarian 752 (32.5) 607 (33.1) 1,359
 Induced labor 300 (12.9) 274 (14.9) 574
Mode of deliverya
 Vaginal 1,078 (47.0) 803 (44.6) 1,881 0.3011
 Cesarean 1,188 (51.8) 976 (54.2) 2,164
 Forceps/Vacuum 28 (1.2) 23 (1.3) 51
Total 2,317 (55.8) 1833 (44.2%) 4,150  

Table 1
Maternal outcomes of women who had preterm birth according to ethnic group

It was more likely that non-white women were: aged ≤ 19 years (PR: 1.05; 95%CI: 1.01–1.09); did not have a partner (PR: 1.09; 95%CI: 1.02–1.16); had a low monthly income (PR: 1.31; 95%CI: 1.24–1.39); had a low level of schooling (< 8 years; PR: 1.35; 95%CI: 1.19–1.53); had ≥ 2 children (PR: 1.19; 95%CI: 1.07–1.33); and performed strenuous work (PR: 1.16; 95%CI: 1.05–1.27) compared to white women (Table 2). Non-white women were more likely to be from the Northeasteran region and less likely to be from the Southern region of Brazil (2.7-fold and 0.54-fold respectively) (Table 2).

Sociodemographics Non-white women White women Prevalence ratio (95% confidence interval)
n (%) n (%)
Region of Brazil
 Southeastern 1,162 (50.2) 1,127 (61.5) 1
 Northeastern 1,011 (43.6) 330 (18.0) 2.72 (2.36–3.14)
 Southern 144 (6.2) 376 (20.5) 0.54 (0.47–0.63)
Maternal age (years)a
 ≤ 19 506 (21.9) 358 (19.5) 1.05 (1.01–1.09)
 20-34 1,502 (64.9) 1,178 (64.3) 1
 ≥ 35 308 (13.3) 297 (16.2) 1.04 (0.99–1.09)
Marital status
 Without partner 570 (24.6) 385 (21.0) 1.09 (1.02–1.16)
 With partner 1,747 (75.4) 1,448 (79.0) 1
Schooling (years)b
 < 8 1,005 (44.1) 636 (35.2) 1.35 (1.19–1.53)
 8-12 1,118 (49.1) 987 (54.6) 1.17 (1.04–1.33)
 > 12 154 (6.8) 186 (10.3) 1
Monthly incomec
 > US$ 500 1,612 (76.2) 1,454 (86.6) 1
 ≤ US$ 500 504 (23.8) 225 (13.4) 1.31 (1.24–1.39)
Children under the age of 5 d
 No 1,649 (71.2) 1,388 (75.8) 1
 1 546 (23.6) 377 (20.6) 1.09 (1.01–1.16)
 ≥ 2 121 (5.3) 66 (3.6) 1.19 (1.07–1.33)
*Paid work during pregnancy
 No 809 (87.2) 726 (88.6) 1
 Yes 119 (12.8) 93 (11.4) 1.06 (0.94–1.21)
*Strenuous worke
 No 425 (53.0) 440 (60.7) 1
 Yes 377 (47.0) 285 (39.3) 1.16 (1.05–1.27)
*Daily workloadf
 ≤ 8 hours 557 (69.9) 517 (71.9) 1
 > 8 hours 240 (30.1) 202 (28.1) 1.05 (0.94–1.16)
Total women 2,317   1,833    

Table 2
Maternal sociodemographics

Some maternal characteristics of the obstetric history of women who had PTB varied according to ethnicity. Non-white women were more likely to have a history of ≥ 3 deliveries (PR: 1.13; 95%CI: 1.05–1.23); interpregnancy interval < 12 months (PR 1.13; 95%CI: 1.02–1.25); and pregnancy complications such as abortion (PR: 1.09; 95%CI: 1.02–1.16), PTB (PR: 1.09; 95%CI: 1.02–1.16), pPROM (PR: 1.13; 95%CI: 1.03–1.24), and low birth weight (PR: 1.08; 95%CI: 1.01–1.16) (Table 3).

Obstetric history Non-white women White women Prevalence ratio (95% confidence interval)
N (%) N (%)
Parity
 Nulliparous 1,076 (46.4) 900 (49.1) 1.0
 1-2 deliveries 952 (41.1) 756 (41.2) 1.02 (0.96–1.08)
 ≥ 3 deliveries 289 (12.5) 177 (9.7) 1.13 (1.05–1.23)
Previous cesarian sectiona
 No 1,825 (78.8) 1,422 (77.6) 1.03 (0.96–1.10)
 Yes 491 (21.2) 411 (22.4) 1.0
Previous abortion
 No 1,735 (74.9) 1,437 (78.4) 1.0
 Yes 582 (25.1) 396 (21.6) 1.09 (1.02–1.16)
*Interpregnancy interval
 < 12 months 144 (10.3) 81 (7.8) 1.13 (1.02–1.25)
 ≥ 12 months 1,255 (89.7) 959 (92.2) 1.0
Previous preterm birthb
 No 1,829 (79.2) 1,497 (81.9) 1.0
 Yes 491 (20.8) 331 (18.1) 1.09 (1.02–1.16)
Previous preterm premature rupture of membranesc
 No 2,107 (91.4) 1,706 (93.5) 1.0
 Yes 198 (8.6) 119 (6.5) 1.13 (1.03–1.24)
Previous low birth weightd
 No 1,879 (82.0) 1,545 (84.7) 1.0
 Yes 412 (18.0) 280 (15.3) 1.08 (1.01–1.16)
Total women 2,317   1,833    

Table 3
Maternal obstetric history

Regarding the clinical care and ANC characteristics, some unfavorable conditions were more frequent among non-white women, who were more likely to initiate ANC visits in the second or third trimesters (PR: 1.06; 95%CI: 1.09–1.23); have an inadequate number of ANC visits (PR: 1.09; 95%CI: 1.07–1.19); experience frequent physical exertion (PR: 1.15; 95%CI: 1.08–1.22); smoke in the first and second (PR: 1.16; 95%CI: 1.03–1.31) or third trimesters (PR: 1.09; 95%CI: 1.01–1.19); have anemia (PR: 1.14; 95%CI: 1.08–1.20); and gestational hypertension (PR: 1.09; 95%CI: 1.02–1.23) (Table 4).

linical and antenatal care characteristics Non-white women White women Prevalence ratio (95% confidence interval)
n (%) n (%)
Antenatal care
 No 89 (3.8) 63 (3.4) 1.05 (0.92–1.20)
 Yes 2,229 (96.2) 1,770 (96.6) 1.0
Onset of antenatal carea
 First trimester 1,141 (61.1) 1,046 (68.9) 1.0
 Second/third trimester 726 (38.9) 472 (31.1) 1.06 (1.09–1.23)
Adequate number of antenatal care visitsb
 Adequate (≥ 6) 1,386 (63.0) 1,205 (69.3) 1.0
 Inadequate (< 6) 813 (37.0) 533 (30.7) 1.13 (1.07–1.19)
Weight gain during pregnancyc
 ≤ 7 kg 694 (35.9) 505 (30.9) 1.12 (1.04–1.21)
 8-12 kg 643 (33.3) 569 (34.8) 1.03 (0.95–1.11)
 > 12 kg 596 (30.8) 559 (34.2) 1.0
Physical effortd
 No or rarely 1,810 (78.7) 1,523 (83.8) 1.0
 Yes (often) 489 (21.3) 294 (16.2) 1.15 (108–1.22)
Smoking
 Never/not during pregnancy 1,955 (84.4) 1,604 (87.5) 1.0
 Until the first and second trimesters 108 (4.7) 61 (3.3) 1.16 (1.03–1.31)
 Until the third trimester 254 (10.9) 168 (9.2) 1.09 (1.01–1.19)
Urinary tract infectione
 No 1,395 (60.9) 1,115 (61.3) 1.0
 Yes 896 (39.1) 705 (38.7) 1.01 (0.95–1.06)
Vaginal bleedingf
 No 1,706 (73.7) 1,361 (74.4) 1.0
 Yes 608 (26.3) 467 (25.6) 1.02 (0.96–1.08)
Anemiag
 No 1,271 (55.2) 1,135 (62.4) 1.0
 Yes 1,030 (44.8) 685 (37.6) 1.14 (1.08–1.20)
*Chronic hypertensionh
 No 1,256 (89.5) 1,005 (89.9) 1.0
 Yes 143 (10.5) 113 (10.1) 1.01 (0.89–1.13)
*Diabetesi
 No 1,256 (91.2) 1,005 (89.4) 1.0
 Yes 121 (8.8) 119 (10.6) 0.91 (0.79–1.03)
*Gestational hypertensionj
 No 1,256 (86.3) 1,005 (89.4) 1.0
 Yes 199 (13.7) 119 (10.6) 1.13 (1.02–1.23)
*Preeclampsia/Eclampsia/Hemolysis, elevated liver enzymes, and low platelet count (HELLP) syndrome
 No 1,256 (75.2) 1,005 (76.0) 1.0
 Yes 414 (24.8) 317 (24.0) 1.02 (0.95–1.09)
*Fetal growth restrictionk
 No 1,573 (87.4) 1350 (87.0) 1.0
 Yes 227 (12.6) 202 (13.0) 0.98 (0.89–1.08)
Multiple pregnancy
 No 2,091 (90.3) 1622 (88.5) 1.0
 Yes 226 (9.7) 211 (11.5) 0.92 (0.83–1.01)
Total 2,317   1833    

Table 4
Clinical and antenatal care characteristics

The neonatal outcomes did not vary significantly between infants born to white and non-white women, except for the higher frequency of low birth weight (73.75% versus 69.02%; p = 0.0008) in infants born to non-white women, and the higher rate of seizures (4.05% versus 6.29%; p = 0.0085) in infants born to white women (Table 5).

Neonatal outcomes Non-white women White women p-value
n (%) n (%)
Gestational age at birth (weeks)
 < 28 178 (7.68) 130 (7.09) 0.7684
 28 -34 1,023 (44.15) 812 (44.30)
 35-36 1,116 (48.17) 891 (48.61)
Birth weighta
 < 2,500 g 1,700 (73.75) 1,259 (69.02) 0.0008
 ≥ 2,500 g 605 (26.25) 565 (30.98)
Fetal death 98 (4.23) 66 (3.60) 0.3017
Fetal malformationsb 233 (10.81) 191 (11.09) 0.7826
Orotracheal intubationc 352 (16.15) 294 (16.92) 0.5192
*Respiratory distress 1,201 (75.77) 865 (75.81) 0.9819
*Neonatal sepsisd 452 (29.50) 324 (29.37) 0.9427
*Pneumothoraxe 52 (3.47) 47 (4.34) 0.2569
*Seizuresf 63 (4.05) 71 (6.29) 0.0085
*Pneumoniag 100 (6.45) 61 (5.42) 0.2691
Total 2,317 1,833  

Table 5
Neonatal outcomes of preterm births according to ethnic group

 

Discussion

Non-white women comprised around 56% of women who had PTB (2,317/4,150), and they had a higher proportion of unfavorable conditions related to maternal and perinatal health, such as not having a partner, age < 19 years, low level of schooling, low family income, ≥ 2 children under 5 years of age, performance of strenuous work during pregnancy, ANC visits initiated after the first trimester, inadequate number of ANC visits, smoking, anemia, and gestational hypertension. Some factors, including smoking, anemia, previous PTB, PROM or low birth weight have been recognized as remarkable risk factors for spontaneous PTB. One of the risk factors for provider-initiated PTB is gestational hypertension.141516 Despite the lack of differences between the subtype of PTB and mode of delivery, infants born to non-white women were more likely to have low birth weight, while seizures were more frequent in infants born to white women.

Various aspects of health, population and environment related to sociocultural aspects require consideration in order to understand the role of ethnicity in the complex relationship between PTB and its related outcomes. Although recent publications have not shown an association between ethnicity and spontaneous or provider-initiated PTB in the Brazilian population,31217 ethnicity has been recognized as an important factor in the prevention, diagnosis and provision of appropriate obstetric care.1819

A recent systematic review19 suggested that income and the level of schooling may not be sufficient to explain why vulnerable conditions are associated with adverse maternal and perinatal outcomes such as PTB or low birth weight; however, ethnicity was strongly associated with both in that review. A study20 comparing data from 4 population-based cohorts studies including all hospital births in 1982, 1993, 2004 and 2015 in the city of Pelotas, Southern Brazil, showed that, despite the economic advances and improvement in some reproductive health indicators in the last decades, ethnic inequalities remained stable. Poorer health indicators and conditions of vulnerability are higher among non-white women than among white women. The present study supports the evidence that ethnic inequality remains a challenge to be overcome.

In Brazil, recent maternal health programs have been launched to improve the access, coverage and quality of ANC and intrapartum care services, and some improvement in the quality of healthcare has been achieved.21 However, ethnic inequalities in healthcare remain challenging. Historically, non-white women in Brazil have had limited access to ANC and intrapartum care services, and they have received lower quality of care.222324 According to the Birth in Brazil study, a recent national hospital-based study representative of the Brazilian population, access barriers and pilgrimage in search of delivery care were significantly more common among non-white women than among whites. In addition, blacks are at greater risk of receiving substandard care or delayed access to obstetric care during pregnancy complications.25

Some risk factors for PTB were more frequently found in the non-white group. The distribution of risk factors may also vary between groups depending on biological and environmental characteristics.2627 The burden of risk factors, including cervical length, obesity, and smoking varies according to ethnic aspects.28 On the other hand, smoking cessation programs appear to be more effective for white women.29 Adverse cervical characteristics, such as short length and dilation, seem to occur more frequently in black than in white women.28 In the United States, for example, preterm-related infant mortality is 54% higher among non-Hispanic blacks than among non-Hispanic whites.30 However, we did not find any significant differences in short-term neonatal outcomes regarding ethnic groups, except for low birth weight and seizures. The EMIP study was conducted in 20 referral obstetric maternity hospitals that are part of the Brazilian Unified Health System. Universal coverage offered by the system may explain the reduced neonatal impact of unequal access to aANC in non-white women.

The current study has some limitations. Cervical length was not evaluated due to its observational nature. A multivariate analysis was not conducted, since our aim was to investigate whether the maternal characteristics of women who had PTB and its related outcomes differed according to ethnicity and not by independent risk factors for PTB per ethnic group. A strength of the study is that it is a prospective, observational, cross-sectional analysis with a large sample of women from the more populated regions in the country, with systematic and standardized data collection.

 

Conclusion

No significant differences in maternal and perinatal outcomes were found between white and non-white women who had PTB in Brazil. However, several characteristics related to lower socioeconomic status and poor health were more frequently found among non-white women, showing their higher vulnerability.


References

1 Morken NH. Preterm birth new data on a global health priority. Lancet. 2012;379(9832):2128-2130


2 Blencowe H, Cousens S, Oestergaard MZ, Chou D, Moller AB, Narwal R. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries a systematic analysis and implications. Lancet. 2012;379(9832):2162-2172


3 . Brazilian multicentre study on preterm birth (EMIP) prevalence and factors associated with spontaneous pretermbirth. PLoS One. 2014;9(10):-


4 Rolett A, Kiely JL. Maternal sociodemographic characteristics as risk factors for preterm birth in twins versus singletons. Paediatr Perinat Epidemiol. 2000;14(03):211-218


5 Schempf AH, Branum AM, Lukacs SL, Schoendorf KC. The contribution of preterm birth to the Black-White infant mortality gap, 1990 and 2000. AmJ Public Health. 2007;97(07):1255-1260


6 Carmichael SL, Kan P, Padula AM, Rehkopf DH, Oehlert JW, Mayo JA. Social disadvantage and the black-white disparity in spontaneous pretermdelivery among California births. PLoS One. 2017;12(08):-


7 Kramer MR, Cooper HL, Drews-Botsch CD, Waller LA, Hogue CR. Metropolitan isolation segregation and Black-White disparities in very preterm birth a test of mediating pathways and variance explained. Soc Sci Med. 2010;71(12):2108-2116


8 Oliveira KA, Araújo EM, Oliveira KA, Casotti CA, Silva CALD, Santos DBD. Association between race/skin color and premature birth a systematic review with meta-analysis. Rev Saude Publica. 2018;52:26-26


9 Rich-Edwards JW, Grizzard TA. Psychosocial stress and neuroendocrine mechanisms in preterm delivery. Am J Obstet Gynecol. 2005;192(5, Suppl):S30-S35


10 Wadhwa PD. Psychoneuroendocrine processes in human pregnancy influence fetal development and health. Psychoneuroendocrinology. 2005;30(08):724-743


11 Osypuk TL, Acevedo-Garcia D. Are racial disparities in preterm birth larger in hypersegregated areas. Am J Epidemiol. 2008;167(11):1295-1304


12 . The burden of provider-initiated preterm birth and associated factors evidence fromthe BrazilianMulticenter Study on Preterm Birth (EMIP). PLoS One. 2016;11(02):-


13 . Methodological issues on planning and running the Brazilian Multicenter Study on Preterm Birth. ScientificWorldJournal. 2015;2015:719104-719104


14 Baer RJ, Yang J, Berghella V, Chambers CD, Coker TR, Kuppermann M. Risk of preterm birth by maternal age at first and second pregnancy and race/ethnicity. J Perinat Med. 2018;46(05):539-546


15 Koullali B, Oudijk MA, Nijman TAJ, Mol BW, Pajkrt E. Risk assessment and management to prevent preterm birth. Semin Fetal Neonatal Med. 2016;21(02):80-88


16 . Born too soon the global epidemiology of 15 million preterm births. Reprod Health. 2013;10(Suppl 1):S2-S2


17 Leal MD, Esteves-Pereira AP, Nakamura-Pereira M, Torres JA, Theme-Filha M, Domingues RM. Prevalence and risk factors related to preterm birth in Brazil. Reprod Health. 2016;13(Suppl 3):127-127


18 A Nyarko K, López-Camelo J, E Castilla E, L Wehby G. [Explaining racial disparities in infant health in Brazil]. Rev Panam Salud Publica. 2014;35(04):305-316


19 de Sadovsky ADI, Mascarello KC, Miranda AE, Silveira MF. The associations that income, education, and ethnicity have with birthweight and prematurity how close are they?. Rev Panam Salud Publica. 2018;42:-


20 . Maternal reproductive history trends and inequalities in four population-based birth cohorts in Pelotas, Brazil, 1982-2015. Int J Epidemiol. 2019;48(Suppl 1):i16-i25


21 Leal MDC, Bittencourt SA, Esteves-Pereira AP, Ayres BV, Silva LB, Thomaz EB. Progress in childbirth care in Brazil preliminary results of two evaluation studies. Cad Saude Publica. 2019;35(07):-


22 Leal MDC, Gama SGND, Pereira APE, Pacheco VE, Carmo CND, Santos RV. The color of pain: racial iniquities in prenatal care and childbirth in Brazil. Cad Saude Publica. 2017;33(33, Suppl 1):-


23 Viellas EF, Domingues RM, Dias MA, Gama SG, Theme Filha MM, Costa JV. Prenatal care in Brazil. Cad Saude Publica. 2014;30(Suppl 1):S1-S15


24 Domingues RM, Viellas EF, Dias MA, Torres JA, Theme-Filha MM, Gama SG. [Adequacy of prenatal care according to maternal characteristics in Brazil]. Rev Panam Salud Publica. 2015;37(03):140-147


25 . Delays in receiving obstetric care and poor maternal outcomes results from a national multicentre cross-sectional study. BMC Pregnancy Childbirth. 2014;14:159-159


26 Manuck TA. Racial and ethnic differences in preterm birth A complex, multifactorial problem. Semin Perinatol. 2017;41(08):511-518


27 Culhane JF, Goldenberg RL. Racial disparities in preterm birth. Semin Perinatol. 2011;35(04):234-239


28 Harville EW, Knoepp LR, Wallace ME, Miller KS. Cervical pathways for racial disparities in preterm births the Preterm Prediction Study. J Matern Fetal Neonatal Med. 2019;32(23):4022-4028


29 Kale PL, Fonseca SC, da Silva KS, Rocha PM, Silva RG, Pires AC. Smoking prevalence, reduction, and cessation during pregnancy and associated factors a cross-sectional study in public maternities, Rio de Janeiro, Brazil. BMC Public Health. 2015;15:406-406


30 MacDorman MF. Race and ethnic disparities in fetal mortality, preterm birth, and infant mortality in the United States an overview. Semin Perinatol. 2011;35(04):200-208