Edad avanzada en la maternidad y factores asociados a la casi pérdida/near miss neonatal en mujeres nulíparas y multíparas

Cad Saude Publica csp Cadernos de Saúde Pública Cad. Saúde Pública 0102-311X 1678-4464 Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz El periodo neonatal temprano cuenta con aproximadamente la mitad de muertes de niños pequeños con una edad inferior a un año, y la near miss neonatal puede identificar factores que causan este número elevado de muertes. Por ello, el objetivo de este estudio es determinar si una edad avanzada maternal incrementa la oportunidad de near miss neonatal, además de identificar qué factores están asociados con la near miss neonatal, estratificada por paridad. Los datos son del 2011-2012, procedentes del estudio Nacer en Brasil, que utilizó una muestra nacional basada en población, compuesta por 15.092 recién nacidos de mujeres entre 20-29 y 35 años de edad o más (edad avanzada maternal). Se realizó una regresión múltiple logística para probar la asociación entre near miss neonatal y las variables prenatales, y de nacimiento de niños, enfermedades pregestacionales, historial obstétrico y características socioeconómicas, estratificada por paridad. La edad avanzada maternal estuvo estadísticamente asociada con near miss neonatal en nulíparas (OR = 1,62; 95%CI: 1,05-2,50) y multíparas (OR = 1,51; 95%CI: 1,20-1,91), cuando se compara con mujeres de 20-29 años de edad. Para las mujeres nulíparas, las principales variables estadísticamente asociadas con near miss neonatal fueron múltiple gestación (OR = 8,91) y enfermedad hipertensiva (OR = 2,57), mientras que el parto vaginal con apoyo de fórceps (OR = 7,19) y la gestación múltiple (OR = 4,47) fueron las variables asociadas para mujeres multíparas. Near miss neonatal ha demostrado estar relacionada con el acceso a servicios de salud para el parto, complicaciones gestacionales y características maternas, principalmente edad avanzada maternal. Por consiguiente, debería ser una estrategia prioritaria en los servicios de salud supervisar adecuadamente y clasificar el riesgo maternal gestacional, así como las complicaciones en el control gestacional durante el cuidado prenatal, al igual que dirigir correctamente a estas mujeres a cuidados para el parto. Background There is a worldwide trend of women in the contemporary world delaying pregnancy, and such a change may impact both maternal and perinatal outcomes 1. The etiology of adverse effects at birth is multifactorial and some outcomes, such as low birthweight (< 2,500g) 2,3, perinatal mortality 4 and abnormalities 5,6, show a connection with advanced maternal age. Also, maternal age and parity were shown to interact, whereby the impact of age at delivery differed between nulliparous and multiparous mothers 7,8. Some studies have focused only on nulliparous women as a distinct population 2,4, however not only the mother’s age at first childbirth is important to be analyzed as the risk factor of interest 8,9,10, and are well documented in the literature relating to the subject. However, other outcomes still require clarification, since existing studies either do not show the well-monitored confounding variables 8, or they address new outcomes, such as neonatal near miss. Neonatal near miss is a term used to describe a newborn which suffered potentially fatal complications during the pregnancy period, childbirth, or in the first seven days after the termination of pregnancy 11. Repeated efforts attempted to establish the criteria for the neonatal near miss indicator 11,12,13,14,15,16,17,18,19, however, there is not a standard global criteria. One of the criteria combines use of pragmatic and management markers of severity as predictors of early neonatal deaths using two World Health Organization (WHO) surveys. The aim was to guide leaders and policymakers regarding the distribution of often scarce resources, in order to improve the quality of healthcare and reduce neonatal mortality, especially in developing countries 16. The neonatal death rate in Brazil has significantly decreased from 25 deaths/1,000 live births in 1990 to 9 deaths/1,000 live births in 2017, but is still far from the high income countries whose rates are approximately 3 deaths/1,000 live births 20. To reach this level, factors that contribute to the death or near death of newborns must be identified. Following the identification of factors, it will be possible to control or improve treatment for these factors in healthcare for the mother and the newborn. Advanced maternal age stands out as a significant factor warranting investigation. Consequently, the aim of this study is to determine whether advanced maternal age increases the chance of neonatal near miss, and to pinpoint which factors are associated with neonatal near miss, according to parity. Methods Data for this study were obtained from a national hospital-based survey of postpartum women and their newborns, Birth in Brazil, carried out from February 2011 to October 2012. The sample was selected in three stages. The first included hospitals with more than 500 births/year, which were stratified according to macro-regions of the country (North, South, Northeast, Southeast and Central), location (capital or non-capital), and type of hospital (public, private, or both). In the second stage, the number of days required to interview 90 postnatal women in each of the 266 previously selected hospitals (minimum of 7 days) was defined using the inverse sampling method. In the third stage, the postpartum women and their newborns were selected. Further information on sample design can be found in the study by Vasconcellos et al. 21. We applied the complex sampling design for all statistical analysis. Each stratum of selection was attributed a calibration procedure based on basic sample weights to ensure that the distribution of postpartum women was similar to that observed in births of the population sampled in 2011, deriving weighted percentages. In this analysis, we considered all newborns of postpartum women between 20-29 years of age and 35 years of age or more. We chose these age ranges based on the Brazilian neonatal death rate that exceeds the level of 7/1,000 live births, which begins to increase at a faster rate for women aged 35 years or more (Departamento de Informática do SUS. Sistema de Informações sobre Nascidos Vivos. http://tabnet.datasus.gov.br/cgi/tabcgi.exe?sinasc/cnv/nvuf.def, accessed on 28/Feb/2016). The age group of 20 to 29 is considered the most adequate period for reproduction and delivery, since women have the lowest rates of chronic medical complications and pregnancy-induced complications 22,23. We did not include stillbirths and early neonatal deaths and their mothers, as to be a near miss the baby must have survived the first seven days of life. We collected information via interview with the postpartum women during their hospital stay by way of an electronic questionnaire. We recorded data from the prenatal card (via photographs), and maternal and newborn records, which we collected after the woman’s discharge or on the 42nd day of hospital admission and/or after discharge from hospital or the 28th day of the newborn's hospitalization. Further details on data collection methods are described by Carmo Leal et al. 24. We established the neonatal near miss variable using recommendations from Pileggi-Castro et al. 16, which looked at two surveys carried out by the WHO. The existence of any of the following characteristics was used to indicate a neonatal near miss: pragmatic criteria: Apgar score < 7 at 5th minutes, birthweight < 1,750g and gestational age < 33 weeks; management criteria: use of antibiotics, continuous positive airway pressure (CPAP), phototherapy in the first 72 hours, vasoactive drug, anticonvulsants, surfactant, cardiac massage, hypoglycemia and orotracheal intubation. We considered the following sociodemographic variables: maternal age (20-29 years, ≥35 years), mother’s years of schooling (< 7 years, 8-10 years, > 10 years), classification of income level according to the Brazilian Association of Market Research Institutes (classes A/B - high income, C/D/E - lower income), race/color (white, black, brown, yellow and indigenous) and the region of residence (North, Northeast, Southeast, South and Central) and pre-gestational body mass index (BMI - kg/m²) (< 18.5 = underweight, 18.5-24.9 = normal weight, 25.0-29.9 = overweight, 30.0 or more = obese) with imputation of about 17.5% of the missing data on weight and height using the chained equations method (MICE). The obstetric history involved: previous miscarriage, history of prematurity, history of low birthweight and previous C-section procedure, all of them classified as existing or non-existing. The variable related to prenatal healthcare was the minimum overall adequacy of prenatal care (minimally adequate, inadequate). The minimum overall prenatal adequacy recommended by the Ministry of Health was adopted and adapted by Domingues et al. 25. Prenatal care was considered minimally adequate when: the onset of the care occurred up until the 12th week of pregnancy; the number of consultations was adequate for gestational age at the time of delivery; at least one of the following routine exams was performed: syphilis serology, fasting blood sugar level, urine test, HIV serology and ultrasonography test; a maternal report regarding guidance to the reference hospital was performed. We applied the following variables in this study: source of payment for childbirth (public or private), being turned away from hospital at the moment of childbirth - failure to be admitted to the first maternity ward sought for childbirth (yes or no), type of childbirth (vaginal, C-section with labor, C-section without labor, or vaginal forceps delivery) and maternal near miss (yes or no). Pre-gestational diseases included: pre-gestational diabetes, heart disease and chronic kidney disease. Complications of pregnancy included: hypertensive disease (chronic hypertension, pre-eclampsia, eclampsia or HELLP syndrome), prepartum and intrapartum hemorrhage, gestational diabetes and urinary infection, all classified either as existing or non-existing. Multiple gestations were also considered (no - one fetus or yes - more than one fetus), if any. We classified the maternal near miss according to clinical, laboratorial and management criteria defined by the WHO 26. We performed all the analyses stratified by parity, because the literature shows that there is difference for some complications between the groups. We considered women who had not previously given birth as nulliparous and those who had given birth on one or more occasions as multiparous. Initially, we verified each of the items that make up the near miss neonatal and the final indicator associated with age ≥ 35 years. We also verified the socioeconomic characteristics of prenatal care, childbirth, pre-gestational diseases and obstetric history associated with neonatal near miss. For both analyses, the chi-square test was used to determine differences between proportions, considering a 95% confidence interval (95%CI). We subsequently applied univariate and multiple logistic regression models to determine the characteristics of the neonatal near miss. The multivariable analysis was based on the hierarchical model, composed of distal (sociodemographic characteristics), intermediate (obstetrics pre-conditions and characteristics of health system) and proximal factors (pre-gestational diseases and pregnancy complications). Initially, each block of variables from a given level was included in the hierarchical analysis model, keeping all variables with p-value ≤ 0.10. In this model, the variables, located at a hierarchically higher level than that of the variable in question were considered as potential confounding in relation to the outcome, while variables located at lower levels were considered as potential mediators. Only the variables with p < 0.05 remained in the final model (adjusted OR). We also calculated the near miss neonatal rate per 1,000 births according to maternal age. The rate for each maternal age is represented by the running average of the neonatal near miss divided by the total number of newborns. The mean is calculated using data from age analysis plus the age given before and afterwards. We used this feature to reduce random fluctuations, since the number of cases was small. For newborns with mothers over 42 years of age, the number of infants was considerably lower. For this reason, we grouped newborns of women aged ≥ 43 years. This research was approved by the Research Ethics Committee of the National School of Public Health of the Oswaldo Cruz Foundation, under n. 92/2010 and 2.041.963/2017 (CAAE: 63785517.2.0000.5240). We obtained consent from the directors of the hospitals, and from each postpartum woman who read and signed the informed consent form before the interview. Results A total of 15,092 newborns were included in this study; 6,219 (41.2%) children of nulliparous women - 5,703 (37.8%) of mothers between 20-29 years of age, 516 (3.4%) of mothers aged 35 years and over - and 8,873 (58.8%) children of multiparous women - 6,868 (45.5%) were of mothers between 20-29 years of age and 2,005 (13.3%) of mothers of 35 years and over. Among the factors that make up the neonatal near miss indicator, we found a higher frequency of use of nasal CPAP, antibiotics, surfactant, phototherapy and hypoglycemia in newborns of women of advanced maternal age, regardless of parity. We also found higher frequency of weight < 1,750g among nulliparous women, and gestational age < 33 weeks in multiparous women (Table 1). Table 1 Factors of neonatal near miss according to maternal age and parity. Brazil, 2011-2012. Variables Nulliparous Multiparous 20-29 years old [n = 5,703] n (%) ≥ 35 years old [n = 516] n (%) p-value 20-29 years old [n = 6,868] n (%) ≥ 35 years old [n = 2,005] n (%) p-value Neonatal near miss Apgar < 7 in the 5th minute 33 (0.6) 08 (1.5) 0.998 48 (0.7) 16 (0.8) 0.742 Weight < 1,750g 99 (1.7) 20 (3.9) 0.014 81 (1.2) 37 (1.8) 0.109 Gestational age < 33 weeks 135 (2.4) 20 (3.9) 0.109 123 (1.8) 70 (3.5) 0.002 Vasoactive drugs 39 (0.7) 05 (1.0) 0.594 46 (0.7) 15 (0.7) 0.743 CPAP nasal 173 (3.0) 21 (4.1) 0.001 128 (1.9) 61 (3.1) 0.008 Antibiotics 261 (4.5) 47 (9.0) 0.003 245 (3.6) 88 (4.4) 0.005 Intubation 80 (1.4) 08 (1.6) 0.783 74 (1.1) 32 (1.6) 0.104 Phototherapy 268 (4.7) 62 (12.1) < 0.001 206 (3.0) 115 (5.8) < 0.001 Cardiac massage 22 (0.4) 02 (0.4) 0.782 37 (0.5) 09 (0.4) 0.681 Anticonvulsant 17 (0.3) 0 (0) - 23 (0.3) 08 (0.4) 0.004 Surfactant 78 (1.4) 18 (3.5) 0.002 75 (1.1) 45 (2.3) 0.006 Hypoglycemia 74 (1.3) 10 (2.0) 0.003 44 (0.6) 42 (2.1) < 0.001 Neonatal near miss indicator No 5,137 (90.1) 429 (83.1) 0.007 6,372 (92.8) 1,769 (88.2) < 0.001 Yes 566 (9.9) 87 (16.9) 496 (7.2) 236 (11.8) The average neonatal near miss rate was 91.7/1,000 births. In addition, the weighted arithmetic mean of neonatal near miss per 1,000 births according to the maternal age of patients aged 20-29 and older than 35 or more is illustrated in Figure 1. The trend showed an increase in the mean of neonatal near misses as mothers got older; whilst the mean for younger women fluctuated around 80.0/1,000, in women of advanced maternal age it varied from 93.8/1,000 to 157.8/1,000. Figure 1 Neonatal near miss rate per 1,000 live births according to maternal age at childbirth for women 20-29 years old and 35 years old or older. The percentages of neonatal near miss and their associated factors are shown in Tables 2 and 3. Regardless of parity, we found the highest percentages of neonatal near miss with statistically significant differences in: maternal age ≥ 35, existence of maternal near miss, presence of hypertensive disease, urine infection, and chronic kidney disease, and in cases of multiple gestation (p-value < 5%). For nulliparous women, in addition to these factors, we observed higher percentages in women with pre-gestational BMI > 25.0 (overweight or obese), pre-existing conditions of heart disease, and pre-gestational diabetes. As for multiparous women, the highest percentages were for those who had ≤ 7 years of schooling, who had a history of low birth weight and prematurity, who tried and failed to be admitted to the first hospital for the childbirth, who had a cesarean section or forceps delivery, and who suffered a prepartum and/or intrapartum haemorrhage. Table 2 Neonatal near miss according to sociodemographic characteristics ande obstetrics pre-conditions per parity. Brazil, 2011-2012. Variables Neonatal near miss Nulliparous Multiparous Total (n) Yes [n (%)] χ2 p-value Total (n) Yes [n (%)] χ2 p-value Maternal age (years) 0.014 < 0.001 20-29 5,703 566 (9.9) 6,868 496 (7.2) ≥ 35 516 87 (16.9) 2,005 236 (11.8) Mother’s years of schooling (years) 0.669 0.027 ≤ 7 578 64 (11.1) 2,950 289 (9.8) 8-10 1,014 109 (10.7) 2,460 174 (7.1) ≥ 11 4,598 475 (10.3) 3,422 267 (7.8) Socioeconomic class 0.995 0.231 Class D/E 959 101 (10.5) 2,398 235 (9.8) Class C 3,319 338 (10.2) 4,541 334 (7.4) Class A/B 1,893 203 (10.7) 1,853 154 (8.3) Skin color 0.774 0.874 White 2,381 245 (10.3) 2,761 244 (8.8) Black 482 51 (10.6) 816 73 (8.9) Brown 3,260 350 (10.7) 5,171 407 (7.9) Yellow 75 5 (6.7) 85 7 (8.2) Indigenous 19 1 (5.3) 39 2 (5.1) Region 0.581 0.666 North 420 41 (9.8) 926 85 (9.2) Northeast 1,909 229 (12.0) 2,423 179 (7.4) Southeast 2,726 283 (10.4) 3,761 336 (8.9) South 788 68 (8.6) 1,141 90 (7.9) Central 375 32 (8.5) 622 43 (6.9) BMI pre-gestational (kg/m²) 0.020 0.669 Below weight 546 36 (6.6) 569 48 (8.4) Normal 3,956 400 (10.1) 4,950 395 (8.0) Overweight 1,229 152 (12.4) 2,392 200 (8.4) Obesity 488 65 (13.3) 963 89 (9.2) Previous abortion 0.177 0.067 No 5,470 546 (10.0) 6,739 529 (7.8) Yes 748 106 (14.2) 2,133 203 (9.3) Low weight history < 0.001 No - - - 7,791 588 (7.5) Yes - - - 923 126 (13.7) Prematurity history < 0.001 No - - - 7,795 556 (7.1) Yes - - - 1,017 173 (17.0) Previous C-section 0.056 No - - - 5,332 398 (7.5) Yes - - - 3,485 329 (9.4) BMI: body mass index; C-section: cesarean section. Table 3 Near miss neonatal according to characteristics of prenatal care, childbirth and pre-gestational diseases and pregnancy complications per parity. Brazil, 2011-2012. Variables Neonatal near miss Nulliparous Multiparous Total (n) Yes [n (%)] p-value Total (n) Yes [n (%)] p-value Adequacy prenatal 0.543 0.547 Inadequate 4,982 534 (10.7) 7,716 643 (8.3) Adequate 1,235 118 (9.6) 1,156 89 (7.7) Source of payment for childbirth 0.863 0.935 Public 4,440 462 (10.4) 7,526 622 (8.3) Private 1,778 190 (10.7) 1,347 110 (8.2) Failing to be admitted at the first maternity ward sought for childbirth 0.075 0.007 No 5,003 503 (10.1) 7,185 534 (7.4) Yes 1,211 147 (12.1) 1,686 198 (11.7) Mode of birth 0.085 < 0.001 Vaginal-induced 2,243 194 (8.6) 4,541 290 (6.4) Cesarean with labor 600 60 (10.0) 644 67 (10.4) Cesarean with no labor 3,266 385 (11.8) 3,586 343 (9.6) Forceps-induced 109 14 (12.8) 102 32 (31.4) Multiple gestation < 0.001 < 0.001 No 6,045 571 (9.4) 8,677 673 (7.8) Yes 172 81 (47.1) 195 59 (30.3) Maternal near miss 0.002 0.001 No 6,148 631 (10.3) 8,795 717 (8.2) Yes 69 21 (30.4) 78 15 (19.2) Hypertensive disease * < 0.001 < 0.001 No 5,369 478 (8.9) 7,833 586 (7.5) Yes 849 174 (20.5) 1,040 146 (14.0) Diabetes during pregnancy 0.083 0.091 No 5,746 593 (10.3) 8,063 649 (8.0) Yes 473 60 (12.7) 810 83 (10.2) Hemorrhage 0.909 < 0.001 No 5,843 609 (10.4) 8,373 636 (7.6) Yes 374 43 (11.5) 500 96 (19.2) Urinary infection 0.004 0.041 No 5,407 538 (10.0) 7,610 600 (7.9) Yes 810 114 (14.1) 1,263 132 (10.5) Pre-gestational diabetes 0.028 0.062 No 6,174 643 (10.4) 8,743 714 (8.2) Yes 43 9 (20.9) 130 18 (13.8) Cardiac disease 0.011 0.383 No 6,182 639 (10.3) 8,808 725 (8.2) Yes 36 13 (36.1) 65 7 (10.8) Chronic kidney disease 0.015 0.001 No 6,208 648 (10.4) 8,848 726 (8.2) Yes 10 4 (40.0) 25 6 (24.0) * Chronic hypertension, pre-eclampsia, eclampsia or HELLP syndrome. Regardless of the parity, after adjustment by applying the variables of the final model, we found neonatal near miss increase in relation to the following factors: maternal age ≥ 35 years, failure to be admitted at the maternity ward sought for childbirth, hypertensive disease, urine infection and multiple gestation. As for newborns from multiparous women, we also found that mother’s years of schooling of ≤ 7 years, type of delivery (cesarean birth without labor and forceps-assisted vaginal delivery), prepartum and/or intrapartum hemorrhage, pre-gestational chronic kidney disease, and a history of prematurity in previous pregnancies were variables related to the outcome (Table 4). The chance of neonatal near miss for nulliparous women aged ≥ 35 was 62% higher when compared to women aged 20-29, and for multiparous women this chance was 51% higher. In addition, the highest degree of association for neonatal near miss occurred in multiple gestations among nulliparous women, and forceps-assisted vaginal delivery among multiparous women, with probabilities eight and seven times higher, respectively, when compared to single pregnancies and vaginal delivery (Table 4). Table 4 Factors related to neonatal near miss of nulliparous ande multiparous. Brazil, 2011-2012. Variables Nulliparous Multiparous OR * (95%CI) Adjusted OR ** (95%CI) OR * (95%CI) Adjusted OR ** (95%CI) Age (years) 20-29 1.00 1.00 1.00 1.00 ≥ 35 1.83 (1.18-2.85) 1.62 (1.05-2.50) 1.71 (1.35-2.17) 1.51 (1.20-1.91) BMI pre-gestational (kg/m²) Below weight 0.63 (0.39-0.99) - - - Normal 1.00 - - - Overweight 1.25 (0.95-1.64) - - - Obesity 1.36 (0.98-1.88) - - - Mother’s years of schooling (years) ≤ 7 - - 1.43 (1.09-1.87) 1.34 (1.04-1.74) 8-10 - - 1.00 1.00 ≥ 11 - - 1.11 (0.88-1.40) 1.05 (0.83-1.34) Failing to be admitted at the first maternity ward sought for childbirth No 1.00 1.00 1.00 1.00 Yes 1.24 (0.90-1.70) 1.43 (1.08-1.89) 1.66 (1.17-2.34) 1.58 (1.19-2.11) Mode of birth Vaginal-induced 1.00 1.00 1.00 Cesarean with labor 1.16 (0.82-1.65) - 1.71 (1.23-2.38) 1.41 (0.99-2.00) Cesarean with no labor 1.41 (1.06-1.86) 1.55 (1.27-1.90) 1.51 (1.19-1.91) Forceps-induced 1.53 (0.84-2.78) - 6.70 (1.88-23.90) 7.19 (1.96-26.28) Hypertensive disease *** No 1.00 1.00 1.00 1.00 Yes 2.64 (2.08-3.34) 2.57 (2.04-3.24) 2.02 (1.63-2.50) 1.49 (1.19-1.86) Hemorrhage No - - 1.00 1.00 Yes - - 2.89 (2.02-4.13) 2.77 (1.98-3.87) Urinary infection No 1.00 1.00 1.00 1.00 Yes 1.48 (1.10-2.00) 1.66 (1.25-2.22) 1.37 (0.99-1.88) 1.42 (1.06-1.92) Multiple gestation No 1.00 1.00 1.00 1.00 Yes 8.53 (3.00-24.20) 8.91 (3.10-25.62) 5.18 (3.18-8.46) 4.47 (2.70-7.39) Pre-gestational diabetes No 1.00 - 1.00 - Yes 2.32 (1.01-5.37) - 1.81 (0.98-3.32) - Chronic kidney disease No 1.00 - 1.00 1.00 Yes 6.10 (1.07-35.00) - 3.48 (1.51-8.06) 3.28 (1.53-7.04) Prematurity history No - - 1.00 1.00 Yes - - 2.62 (1.95-3.52) 2.53 (1.91-3.34) Previous C-section No - - 1.00 - Yes - - 1.29 (1.04-1.61) - 95%CI: 95% confidence interval; BMI: body mass index; C-section: cesarean section; OR: odds ratio. * All variables were tested with p-value < 0.10. However, only ones considered in the table where the ones tested according to the final model. ** OR adjusted by the variables that continued in the final model. *** Hypertensive disease = chronic hypertension+pre-eclampsia+eclampsia or HELLP syndrome. Discussion Advanced maternal age was shown to be a risk factor for neonatal near miss in nulliparous and multiparous women. Even after other confounding variables were controlled, the risk proved to be significantly higher in women aged 35 years and older. Factors related to access to healthcare services for childbirth, maternal characteristics and gestational complications also played an important role in the explanation of the neonatal near miss, although the determination of these factors was different among nulliparous and multiparous women. The neonatal near miss rate for this study was higher than the figures found by Pillegi-Castro et al. 16 for Brazil, namely 71.8/1,000 births. However, the authors of the aforementioned study did not use a representative sample from Brazil. Women aged 30-34 were not included, which is likely to have reduced the neonatal near miss rate, since younger women showed lower rates. This indicator is considered high when compared to countries with a very high Human Development Index (HDI), which showed a mean rate of 39.0/1,000 births 16, and is considered low when compared to two maternity hospital for high-risk pregnancy in Brazil (147.3/1,000 births and 220/1,000 births) 13,27. This showed that the healthcare system needs to improve prenatal care and peripartum care for pregnant women and their newborns in order to minimize the number of births with adverse perinatal outcomes. Negative perinatal outcomes such as prematurity, low birth weight and Apgar < 7 in the 5th minute are items that make up the neonatal near miss and also relate in the same way to maternal age, when it is presented continuously 8. As in this study, the chance of neonatal near miss increases by more than 50% for mothers age ≥ 35 years 7. A study carried out in China confirmed the relationship of prematurity with maternal age and cesarean section without labor. This study, even when adjusting the model for hypertensive disorders, diabetes mellitus and antepartum hemorrhage - factors also associated with prematurity - found a greater chance of premature birth in women of advanced maternal age 28. In addition, comparing preterm and spontaneous preterm delivery with regard to parity of younger women with those of advanced maternal age women, the study found a greater chance of preterm birth in multiparous women, but not in spontaneous preterm birth, indicating that older Chinese women have their deliveries induced by the provider 28. The main causes of non-spontaneous birth before 34 weeks are pre-eclampsia and small for gestational age infants 29, showing that the management and provision of antenatal care for advanced maternal age women show peculiar characteristics that should be closely observed 28. Cesarean section without labor and forceps-assisted delivery were also associated with neonatal near miss. This may reflect therapeutic interventions that attempt to provide better childbirth care in situations where vaginal delivery is not recommended 30. This idea is reinforced by another study carried out in the same population, which found no connection between the different types of childbirth and neonatal mortality 31. However, it is also possible that some cesarean sections were performed without medical indication in babies under 39 weeks, resulting clearly in more serious consequences, such as cardiorespiratory arrest, sepsis, phototherapy, admission into neonatal intensive care unit (ICU), hospitalization, and hypoglycemia 32. In addition, need for hospital care during childhood, mainly due to obstructive airway diseases and ophthalmological and motor problems 33. Gestational complications, such as hypertensive diseases (pre-eclampsia and eclampsia), urine infection and pre and intra-partum hemorrhage turned out to be related to neonatal near miss. These are complications that make up the gestational risk and must be correctly diagnosed and properly treated in the prenatal period, so as to avoid negative outcomes for the woman and the fetus 34,35. A study conducted by the WHO in 29 countries found that only 11.4% of early neonatal deaths were not associated with maternal complications 36, suggesting that deaths could be prevented through a comprehensive approach by pregnant women, starting from early identification of risk pregnancies, treatment of infections and gestational complications in a timely manner, and referral to a hospital equipped with facilities capable of providing the mother and the newborn with adequate healthcare 31,34. In addition to the characteristics described, in order to prevent neonatal deaths, it is essential to control intrauterine hypoxia, and to introduce good practices in labor and delivery, training multi-professional teams to follow protocols based on scientific evidence and to provide qualified healthcare through a regionalized and hierarchical network. Late prematurity and intrapartum asphyxia were the main causes of preventable neonatal deaths in Brazil, and are preventable by the implementation of recommended practices in childbirth and delivery, once services are available 31. Practices such as triage and proper referral of pregnant women at risk, whose newborns may present complications during childbirth and in the first hours of life, are key in the prevention of deaths 36,37, since many of them die due to lack of a neonatal ICU or transfer to a hospital with more complex resources 31. Thus, when analyzing the neonatal near miss in infants considered small for gestational age, in countries of low HDI, 49% of neonates < 32 gestational weeks experienced neonatal near miss, of which 70% died, while in countries with high HDI, where prenatal care is widely provided and delivery assistance is adequate, 80% of newborns with gestational age < 32 weeks experienced neonatal near miss, and perinatal mortality rate amounted to approximately 11% 36. Another problem of perinatal care is the failure to be admitted to the maternity hospital sought for childbirth by pregnant woman with intercurrences, which may be a result of the lack of a referral to a hospital better equipped for childbirth or due to the woman’s own difficulties 36. The delay caused by pregnant woman searching for an adequate service can constitute one of the factors for the worsening of her condition and of the situation of the fetus, since in regions far from the capital city, delivery care is mostly provided by mixed private units, associated to the Brazilian Unified National Health System (SUS), generally without the infrastructure necessary to serve both pregnant woman and infants at risk in the Brazilian context 38. Strengths and limitations This study is valuable in that it identifies factors related to neonatal near miss, regarding age and parity. Given the fact that little research has been conducted on the topic, most neonatal near miss studies focus on determining the criteria for this indicator, rather than on the factors associated with it. In addition, not only does this study use pragmatic criteria, it makes use of a representative sample in Brazil and stands out by applying the protocol proposed by WHO for the composition of the indicator. Some limitations should be mentioned, such as the absence of blood transfusion variables and surgery up to seven days of life, which make up the 14 criteria described by WHO. The frequency, however, was extremely low in the study of the protocol (0.26% and 0.07%, respectively) 16. Moreover, these are more serious characteristics, and infants showing them were probably already accounted for by other characteristics making up the neonatal near miss. Furthermore, this study does not include the variable conception by in vitro fertilization to analyze its relationship with neonatal near miss. Nonetheless, this is not very prevalent in Brazil, and since it is not part of the table of procedures covered by SUS, and is restricted to private clinics with very high costs, the chance of these women forming part of the study is low. Hence, the early neonatal death outcome was used as a proxy for the neonatal near miss during the discussion of this study, as studies have not yet analyzed the factors associated with this outcome. Conclusion Neonatal near miss has been shown to be connected with access to health services for childbirth, gestational complications and maternal characteristics, including advanced maternal age. Therefore, to properly monitor and classify maternal gestational risk, to control gestational complications during prenatal care, and to correctly refer these women to childbirth care should be priority strategies for healthcare services aiming to reduce neonatal near miss rates and mortality. 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