In this study involving 3.5 million live births, we observed different risk factors between incident and recurrent PTB for household overcrowding, maternal race/ethnicity, marital status, number of prenatal visits, maternal age, and delivery mode; association estimates were stronger in magnitude for incident PTB than recurrent PTB. On the other hand, the magnitudes of association for interbirth interval and maternal age were higher for recurrent PTB. The chances of incident and recurrent PTB increased in live births from mothers with fewer than four prenatal visits in the second or in both pregnancies. Four prenatal visits or more in the second pregnancy minimizes the chance of incident PTB.
To our knowledge, risk factors for incident versus recurrent PTB have been reported in a single study [11]. Our findings that a wide range of risk factors was observed for the incident PTB compared to recurrent PTB are consistent with the results reported by Grantz et al. (2014) [11]. Nonetheless, in our study, many risk factors persisted for recurrent PTB after accounting for the excess risk associated with prior PTB history, unlike those reported by the authors above. The mechanisms that explain these results are not fully understood but can be attributed to higher baseline risk among women who have had a previous preterm birth [11]. Another explanation may be related to “index event bias,” which is possible when studying recurrent events. An analysis conditioned to a previous event can induce inverse associations between risk factors (known and unknown). This type of bias can lead to misleading findings and potentially harmful conclusions [27]. We adjusted our analyses for multiple risk factors in an attempt to minimize the index event bias. However, the ability to adjust analyses for all risk factors is a limitation in epidemiological studies in general, and not just in this particular case.
Our results found an increased chance of incident PTB with household overcrowding, Black/mixed and indigenous race/ethnicity, younger ages at birth, and cesarean delivery but not for recurrent PTB. Overcrowding is a marker of poverty and social deprivation [28] and may be associated with PTB since the number of people in a family can influence per capita income, family expenditure, access to food, and other essential services. Crowding can also trigger stress factors on health and well-being, increasing exposure to risk factors for preterm birth [29]. For Black/mixed women, exposure to psychosocial stressors (poverty, homelessness, living in dangerous neighborhoods, domestic violence, experience of discrimination or racism) and risk behaviors associated with stress can favor an increased risk of preterm birth [30]. The association between indigenous race/ethnicity and PTB can be related to worse social and health outcomes of this population when compared to the general population [31]. Concerning the increased risk of PTB among adolescent mothers, some of the explanations proposed are biological immaturity and competition for nutrients between the fetus and the pregnant adolescent [32]. Also, the association between cesarean delivery and preterm birth can be related to the expansion of obstetric interventions aimed at reducing maternal and fetal complications [33].
We observed that a lower number of prenatal visits more than doubled the risk of incident and recurrent PTB. This was notably the strongest factor observed to be associated with PTB incidence. These results corroborate those of several other studies that have reported an increased risk of recurrent PTB among women who make fewer prenatal visits [24, 34]. These findings reinforce the importance of prenatal care for the identification of women at high risk for preterm birth [10]. In our study, we also found lower chances of incident and recurrent PTB among live births from single women (single, widowed, or divorced), with higher protective effect for incident PTB. It is possible that bias in filling out this variable occurred, resulting in the underreporting of women in a stable relationship [35].
We also identified increased chances of incident and recurrent PTB among live births among mothers with short inter-birth intervals and in births from mothers of advanced maternal age, however, unlike the other factors, the estimates were higher for recurrent PTB. Other studies have also identified an increased risk of PTB incident [11] and recurrent [22,23,24,25] among women with a short pregnancy interval. This association may be related to maternal nutritional depletion, folate depletion, cervical insufficiency, and infections [36]. Short birth intervals are more common in women from LMICs, where lower socioeconomic status, less education, high fertility rates, and the mother’s age are often associated with short birth intervals [37]. Richer and better-educated women are better off and have access to health services, as well as to information on the use of contraceptive methods and supplies of them, expanding their intervals between deliveries [37]. Preterm birth among women of advanced age may be associated with the increase in clinical complications as age increases, such as arterial hypertension and diabetes mellitus [38].
We also explored changes in the number of prenatal visits between pregnancies and we found that live births from mothers who had a low number of prenatal visits in the first pregnancy and who made four or more prenatal visits in the second pregnancy had less chance of incident PTB, but not recurrent PTB. This finding can be partly explained by the index event bias already discussed in our work and also by Smits et al. [27]. Furthermore, the adoption of ≥4 antenatal visits in the second pregnancy may be affected by the status of the first delivery. The fact is that the first birth status can influence both the follow-up of ≥ 4 prenatal visits during the second pregnancy and the situation of the second birth.
We also observed that the chances of incident and recurrent PTB increased when mothers had fewer than four prenatal visits in the second and both pregnancies. It is known that adequate prenatal care can lead to the adoption of and timely access to preventive measures and effective interventions to reduce biological, social, and behavioral risk factors associated with prematurity [10] in current and subsequent pregnancies. The prevention of premature births occurs through reducing risk behaviors, the identification and treatment of sexually transmitted diseases and other infections, and malnutrition identification and nutritional advice, including supplementation with multiple nutrients [10]. Besides, other health services, such as family planning, favor adequate spacing between pregnancies and reduce the risk of prematurity in subsequent pregnancies [39]. We highlight that, despite the expansion of prenatal care coverage in Brazil in recent decades, there are still regional and social inequalities in access to adequate prenatal care which impact the high level of PTB in our country [40]. Our results reinforce the importance of expanding the access and quality of primary care, especially primary care and access to prenatal care to women in the reproductive phase in order to achieve a reduction in premature births, especially in a current pregnancy.
Strengths and limitations
This is the first study to assess the factors associated with the incidence and recurrence of PTB in a poor population in a middle-income country with great social and health inequalities. The linkage with the national live birth information system allowed us to track women individually through successive pregnancies. Also, the large number of cases allowed us to simultaneously investigate the factors associated with the incidence and recurrence of PTB, and to carry out our analysis considering the changes in the number of prenatal consultations between pregnancies.
However, this study has some limitations. The use of secondary data, which was not designed primarily for research purposes, may be subject to some limitations related to missing, underestimation, and potential misclassification. The proportion of preterm births recorded in SINASC may be subject to underreporting related to errors in the gestational age [41]. Until 2010, the gestational age at birth was collected over wide intervals of gestational weeks. As of 2011, SINASC started to collect gestational age as a continuous variable; however, the estimation method changed to be mainly based on the LMP [26]. The LMP is the method recommended by WHO, due to its wide accessibility and low cost [42]. Nonetheless, this method can be sometimes not much accurate due to circumstances such as individual variations in the length of the menstrual cycle, especially memory biases [43]. However, these are probably non-differential errors and are unlikely to introduce bias in the measure of association, although the absolute measures of risk may be underestimated. In addition, the proportion of missing data in the cohort could be a limitation for the generalization of our findings. Residual confounding is also possible because important variables for determining PTB, such as maternal comorbidities (e.g., obesity, diabetes, and hypertension), risk behaviors (e.g., smoking, alcohol, or drug use during pregnancy), and access and quality of health services were not available. Also, we were not able to classify the preterm birth subtypes (spontaneous or with medical indication) because of the lack of information in our dataset. The lack of genetic information is another limiting factor; it is known that genetic variants are associated with the duration of pregnancy and the risk of PTB [44]. These limitations may be affecting the differences observed between incident vs. recurrent PTB in this study. In addition, the association between changes in the number of prenatal care visits and PTB according to previous PTB history may present confounding bias. Our findings must be interpreted with caution because the absence of an association between a risk factor and PTB recurrence should not be a reason to dismiss the factor as a potential focus for preventive action. Finally, this study was conducted among the poorest population of a middle-income country with a history of great social and health inequalities which might limit the generalizability of these findings.