Factors associated with neonatal near miss in the Southeastern region of Brazil: results from Birth in Brazil II

Abstract

This article aims to analyze the factors associated with neonatal near miss (NMN) in public and private hospitals in the Southeast region of Brazil. A prospective cohort study with 7,552 live births from singleton pregnancies from the “Born in Brazil II” study (2021-2023). NMN was defined according to the criteria of Pileggi-Castro et al. (2014), and the independent variables were organized in a hierarchical model: distal level (sociodemographic characteristics), intermediate level (maternal conditions and prenatal care), and proximal level (obstetric complications, type of delivery, and sex of the newborn). Neonatal mortality (NMN) occurred in 12.5% of live births. After adjustment, the following were associated with the outcome: urban residence (OR=1.75), absence of a partner (OR=1.36), hypertensive syndromes of pregnancy, pre-gestational diabetes (OR=2.76), syphilis (OR=5.44), less than 50% of prenatal visits (OR=2.14), alcoholism (OR=1.50), severe maternal morbidity (OR=1.96), forceps/vacuum delivery (OR=2.39), and male sex (OR=1.23). NMN was associated with clinical, sociodemographic, and care determinants, highlighting persistent inequalities in prenatal and intrapartum care and the need to strengthen integrated maternal and neonatal care policies.

Key words:
Near miss; Pregnancy Complications; Risk Factors; Socioeconomic Factors; Maternal and Child Health Services

Resumo

O objetivo deste artigo é analisar os fatores associados ao near miss neonatal (NMN) em hospitais públicos e privados da região Sudeste do Brasil. Estudo de coorte prospectiva com 7.552 nascidos vivos de gestações únicas do estudo Nascer no Brasil II (2021-2025). O NMN foi definido pelos critérios de Pileggi-Castro et al. (2014) e as variáveis independentes foram organizadas em modelo hierárquico: nível distal (características sociodemográficas), intermediário (condições maternas e assistência pré-natal) e proximal (complicações obstétricas, tipo de parto e sexo do recém-nascido). O NMN ocorreu em 12,5% dos nascidos vivos. Após ajuste, associaram-se ao desfecho: residência urbana (OR=1,75), ausência de companheiro (OR=1,36), síndromes hipertensivas da gestação, diabetes pré-gestacional (OR=2,76), sífilis (OR=5,44), realização de menos de 50% das consultas pré-natais (OR=2,14), etilismo (OR=1,50), morbidade materna grave (OR=1,96), parto por fórceps/vácuo (OR=2,39) e sexo masculino (OR=1,23). O NMN associou-se a determinantes clínicos, sociodemográficos e assistenciais, evidenciando desigualdades persistentes na atenção pré-natal e intraparto e a necessidade de fortalecer políticas integradas de cuidado materno e neonatal.

Palavras-chave:
Near miss; Complicações na Gravidez; Fatores de Risco; Fatores Socioeconômicos; Serviços de Saúde Maternoinfantil

Resumen

El objetivo de este artículo es analizar los factores asociados a la morbilidad neonatal grave (MNG) en hospitales públicos y privados de la región Sudeste de Brasil. Estudio de cohorte prospectivo con 7552 nacidos vivos de embarazos únicos del estudio “Nacidos en Brasil II” (2021-2025). La MNG se definió según los criterios de Pileggi-Castro et al. (2014), y las variables independientes se organizaron en un modelo jerárquico: nivel distal (características sociodemográficas), nivel intermedio (condiciones maternas y atención prenatal) y nivel proximal (complicaciones obstétricas, tipo de parto y sexo del recién nacido). La mortalidad neonatal (MN) se presentó en el 12,5 % de los nacidos vivos. Tras el ajuste, los siguientes factores se asociaron con el desenlace: residencia urbana (OR=1,75), ausencia de pareja (OR=1,36), síndromes hipertensivos del embarazo, diabetes pregestacional (OR=2,76), sífilis (OR=5,44), menos del 50 % de las visitas prenatales (OR=2,14), alcoholismo (OR=1,50), morbilidad materna grave (OR=1,96), parto con fórceps o ventosa (OR=2,39) y sexo masculino (OR=1,23). La MN se asoció con determinantes clínicos, sociodemográficos y asistenciales, lo que pone de manifiesto las persistentes desigualdades en la atención prenatal e intraparto y la necesidad de fortalecer las políticas integradas de atención materna y neonatal.

Palabras clave:
Morbilidad neonatal grave; Complicaciones del embarazo; Factores de riesgo; Factores socioeconómicos; Servicios de salud maternoinfantil

Introduction

Infant mortality is an important indicator of health conditions and inequalities in access to and quality of maternal and child care¹. Despite advances in reducing this indicator in Brazil, especially in the post-neonatal and late infant components, neonatal mortality still accounts for about 70% of deaths among children under five years of age², highlighting persistent challenges in prenatal care, delivery, and immediate newborn care^3,4.

Neonatal near miss (NNM) has been used as a complementary indicator to neonatal mortality because it identifies newborns who face an imminent risk of death but survive⁵. Its analysis contributes to evaluating the quality of care and recognizing failures and avoidable factors not captured by deaths alone⁶. Despite the broad acceptance of the concept, there is heterogeneity in the criteria for its definition and measurement, which generates wide variation in estimates, with NNM rates ranging from two to as much as ten times higher than neonatal mortality rates, depending on the criteria and the context^7,8.

The occurrence of NNM is associated with multiple sociodemographic, maternal, neonatal, and care-related factors^6-9. Despite this, in Southeastern Brazil, the region that accounts for a substantial proportion of births because it has the largest hospital network in the country, investigations into factors associated with NNM remain scarce and, in general, are restricted to local studies using diverse criteria for defining this outcome^8,10. In addition, there is a lack of population-based analytical studies that coordinate sociodemographic, clinical, and care-related determinants, which is a relevant scientific and health-management gap.

Therefore, this study aimed to analyze the association between sociodemographic factors, maternal characteristics/habits, organizational aspects of health services, obstetric complications, delivery type, and the occurrence of NNM in public and private hospitals in Southeastern Brazil.

Methods

This prospective cohort study of live births in Southeastern Brazil was based on questionnaires administered to postpartum women and medical-record data from the Birth in Brazil II study (2021-2025). Details of the design and methodology are described in Theme Filha et al. ¹¹ and Leal et al. ¹².

The national sample included 20,276 newborns (20,051 live births, 225 stillbirths, and 73 neonatal deaths). The Southeast recorded 7,827 newborns (7,737 live births, 90 stillbirths, and 24 neonatal deaths). For this analysis, 7,552 live births from singleton pregnancies were used.

Women admitted for delivery (live birth or stillbirth) or abortion in hospitals with ≥100 live births per year (SINASC) were included. Postpartum women with communication difficulties, multiple births, and cases admitted for abortion who were discharged while still pregnant were excluded. This study considered only live births from singleton pregnancies in Southeastern Brazil, excluding multiple pregnancies, stillbirths, and abortions.

The NNM outcome was defined according to Pileggi-Castro et al. ⁷ and encompassed pragmatic criteria (birth weight <1,750 g, gestational age <33 weeks, Apgar score <7 at the 5^th minute) and management criteria (mechanical ventilation, resuscitation, intubation, antibiotics, among others). Newborns who survived the neonatal period and had ≥1 of these criteria were classified as NNM.

The hierarchical NNM model was structured on the basis of risk factors for neonatal death¹³ and organized into distal, intermediate, and proximal levels, according to their proximity to the outcome and the theoretical-conceptual model (Chart 1).

Chart 1
Theoretical-conceptual model of predictive factors for neonatal near miss in the Brazilian Southeast.

Distal level	Intermediate level	Proximal level
Sociodemographic variables: • Hospital size • Payment method • Home location • Maternal age • Skin color • Marital status • Education level • Work during pregnancy • Household income	Variables related to maternal characteristics/habits and the organization of health services: • Parity • Pre-gestational body mass index (BMI) • Pregnancy hypertensive syndromes • Pre-gestational diabetes mellitus • Syphilis • Gestational age at the start of prenatal care • Adequacy of the number of prenatal care visits • Tobacco use • Alcohol use	Obstetric complication and delivery type: • Severe maternal morbidity (SMM) • Delivery type

• Source: Authors.

At the distal level, the following sociodemographic variables were included: hospital size (<1,000/≥1,000 live births/year), payment type (public/private), place of residence (urban/rural), maternal age (10-19, 20-34, 35-39, ≥40 years), skin color (White, Black, Brown/Asian/Indigenous), marital status (with/without partner), schooling (incomplete elementary/no information; complete elementary; complete high school; complete higher education), paid work during pregnancy (yes/no), and household income (no information; 1^st-5^th quintiles).

At the intermediate level, variables related to maternal characteristics/habits and service organization were included: parity (primiparous, 1-2, ≥3 births); pregestational BMI (underweight, normal weight, overweight/obesity); gestational hypertensive syndromes (GHS) (no/yes); diabetes (none, pregestational, gestational); syphilis (no/yes); prenatal care start (≤12, 13-20, 21-27, >28 weeks/no prenatal care); appropriate number of prenatal care appointments (<50%/none, 50-74%, 75-99%, 100%); tobacco use and alcohol use during pregnancy (no/yes).

At the proximal level, severe maternal morbidity before delivery (no/yes) and delivery type (vaginal, forceps/vacuum, cesarean section) were included. Newborn sex (male/female) was not part of the hierarchical levels but was incorporated into the final model because it is an important predictor of neonatal mortality⁸.

Pregestational nutritional status was classified by BMI according to the Institute of Medicine¹⁴. Gestational hypertensive syndromes (GHS) followed the classification of the American College of Obstetricians and Gynecologists¹⁵. Severe maternal morbidity (SMM) was defined according to WHO criteria¹⁶, including events such as placental abruption, uterine rupture, eclampsia, HELLP syndrome, severe hypertension, pulmonary edema, respiratory failure, seizures, shock, thrombocytopenia, and thyrotoxic crisis.

Initially, absolute and relative frequencies of the predictor variables were estimated. In the bivariate analysis, Pearson’s chi-square test, the odds ratio (OR), and 95% confidence intervals (95%CI) were applied. The multivariate analysis used logistic regression, adopting the OR as the measure of association between maternal characteristics, sociodemographic factors, care-related variables, and NNM. Variables with p<0.25 in the bivariate analysis were included in the model, and those with p<0.05 remained.

The Research Ethics Committee of ENSP-Fiocruz approved the main study under Opinion No. 4.104.073, CAAE: 21633519.5.0000.5240, in accordance with CNS Resolution No. 466/2012^17,18, and all participants signed an informed consent form.

Results

A total of 7,552 live births were analyzed; 940 (12.45%) met the criteria for NNM. Among the pragmatic criteria, gestational age <33 weeks (10.85%), birth weight <1,750 g (10.11%), and Apgar score <7 (6.06%) stood out, totaling 17.87%. Regarding management criteria, 97.81% underwent some intervention (12.17% of the total), especially phototherapy within the first 24 hours (70.75%), antibiotics (37.34%), and CPAP (31.70%) (Table 1).

Table 1
Incidence of total neonatal near miss according to pragmatic and management criteria. Southeast Region, 2021-2025.

	n	% among NNM	% among LB
Live births from single pregnancies	7,552	-	100.00
NNM (Pragmatic or managed)	940	100.00	12.45
Pragmatic (GA, weight, or Apgar)	168	17.87	2.22
GA <33 weeks	102	10.85	1.35
Weight <1,750 g	95	10.11	1.26
Apgar <7 at 5 minutes	57	6.06	0.75
Management	919	97.81	12.17
Phototherapy in the first 24 hours of life	665	70.75	8.81
Antibiotic use	351	37.34	4.65
Continuous positive airway pressure (CPAP) in the delivery room	298	31.70	3.95
Orotracheal intubation	106	11.28	1.40
Use of surfactant	103	10.96	1.36
Use of vasoactive drugs	95	10.11	1.26
Use of anticonvulsants	66	7.02	0.87
Blood transfusion	65	6.92	0.86
Neonatal resuscitation maneuvers	56	5.96	0.74
Underwent any surgery during hospitalization	53	5.64	0.70
Cardiac massage	50	5.32	0.66
Use of corticosteroids for treatment of refractory hypoglycemia	23	2.45	0.30

• Source: Authors.

In Southeastern Brazil, 67.9% of births occurred in the public sector and 32.1% in the private sector. In the public sector, the predominant characteristics were complete high school education (53.1%), elementary education (25.1%), lower income (18.5%), multiparity (47.6%), and vaginal delivery (50.4%). In the private sector, complete higher education (54.4%), high income (52.3%), primiparity (55.8%), and cesarean sections (81.3%) predominated. Chronic hypertension (7.4%), preeclampsia (4.2%), and syphilis (8.1%) were more common in the public sector. Prenatal care was more adequate in the private sector (85.8%), and SMM was higher in the public sector (13.0%) (Table 2).

Table 2
Sociodemographic, obstetric, and health service organization characteristics according to type of childbirth payment. Southeast Region, 2021-2025.

	Public-Southeast		Private-Southeast		P-value	Total-Southeast
	n	%	n	%		n	%
Live births from single pregnancies	5,128	100.0	2,424	100.0		7,552	100.0
Delivery payment type
Public	5,128	100.0	0	0.0	-	5,128	67.9
Private	0	0.0	2,424	100.0		2,424	32.1
Residence location
Urban	4,578	89.3	2,236	92.3	0,556	6,814	90.2
Rural	550	10.7	188	7.7		737	9.8
Age
10-19	647	12.6	41	1.7	<0,001	688	9.1
20-34	3,696	72.1	1,608	66.3		5,304	70.2
35-39	577	11.3	588	24.2		1,165	15.4
≥40	207	4.0	188	7.7		395	5.2
Skin color
White	1,514	29.5	1,348	55.6	<0,001	2,863	37.9
Black	788	15.4	264	10.9		1,052	13.9
Brown	2,825	55.1	812	33.5		3,637	48.2
Marital status
Not living with partner	1,045	20.4	138	5.7	<0,001	1,183	15.7
Living with partner	4,081	79.6	2,286	94.3		6,367	84.3
Schooling (study years)
≤8 (EL incomplete)/no information	760	14.8	41	1.7	<0,001	801	10.6
9-11 (EL complete)	1,286	25.1	106	4.4		1,391	18.4
12-15 (HS complete)	2,725	53.1	958	39.5		3,683	48.8
≥16 (HE complete)	357	7.0	1,320	54.4		1,676	22.2
Working during pregnancy
No	2,806	54.7	560	23.1	<0,001	3,365	44.6
Yes	2,322	45.3	1,864	76.9		4,186	55.4
Household Income Quintile
1 quintile (<1300)	946	18.5	36	1.5	<0,001	982	13.0
2 quintile (1300-1899)	1,042	20.3	69	2.9		1,112	14.7
3 quintile (1900-2599)	1,187	23.1	199	8.2		1,386	18.4
4 quintile (2600-4699)	399	7.8	520	21.5		920	12.2
5 quintile (≥4700)	307	6.0	1,269	52.3		1,575	20.9
No information	712	13.9	331	13.6		1,043	13.8
Parity
Primiparous	2,049	40.0	1352	55.8	<0,001	3400	45.0
1-2	2,443	47.6	1020	42.1		3463	45.9
≥3	636	12.4	52	2.1		688	9.1
Pregestational BMI
<18.5	288	5.6	48	2.0	<0,001	336	4.4
18.5-24.9	2,066	40.3	1,022	42.1		3,087	40.9
25-29.9	1,462	28.5	810	33.4		2,272	30.1
≥30	1,312	25.6	545	22.5		1,857	24.6
Hypertensive syndromes (HS)
No	3,923	76.5	1,988	82.0	0,002	5,911	78.3
Chronic AH	377	7.4	131	5.4		508	6.7
Gestational AH	345	6.7	140	5.8		485	6.4
Preeclampsia	215	4.2	79	3.2		294	3.9
Preeclampsia superimposed on chronic preeclampsia	114	2.2	43	1.8		157	2.1
Unspecified HS	154	3.0	43	1.8		197	2.6
Diabetes
Pregestational diabetes	114	2.2	37	1.5	0,127	151	2.0
Gestational diabetes (≥92 mg/dl)	853	16.6	441	18.2	0,291	1,293	17.1
Maternal syphilis diagnosis*	414	8.1	43	1.8	<0,001	457	6.1
Prenatal care start
≤12	3,955	77.1	2,079	85.8	<0,001	6,035	79.9
13-20	773	15.1	286	11.8		1,058	14.0
21-27	237	4.6	33	1.3		269	3.6
28+ (or did not do it)	163	3.2	27	1.1		189	2.5
Appropriate prenatal care appointments
<50% (or did not do it)	226	4.4	52	2.1	<0,001	278	3.7
50-74%	472	9.2	104	4.3		576	7.6
75-99%	546	10.6	184	7.6		730	9.7
≥100%	3,883	75.7	2,084	86.0		5,967	79.0
Severe Maternal Morbidity before delivery**	667	13.0	200	8.2	<0,001	867	11.5
Delivery type
Vaginal	2,584	50.4	408	16.8	<0,001	2,992	39.6
Forceps/vacuum	63	1.2	45	1.9		108	1.4
Cesarean	2,481	48.4	1,971	81.3		4,451	58.9

• *Laboratory or clinical diagnosis during prenatal care or upon admission for delivery. **Premature placental abruption, uterine rupture, eclampsia, HELLP syndrome, severe preeclampsia, severe hypertension, pulmonary edema, acute respiratory failure, seizures, shock, thrombocytopenia, and thyrotoxic crisis.
• Source: Authors.

Table 3 presents the results of the bivariate analysis. At the distal level, the following variables were associated with NNM: residing in an urban area (OR=1.74; 95%CI: 1.15-2.61), maternal age ≥40 years (OR=1.34; 95%CI: 1.01-1.78), and not living with a partner (OR=1.43; 95%CI: 1.16-1.77).

Table 3
Bivariate analysis of sociodemographic factors, maternal characteristics/habits, organizational aspects of health services, obstetric complications, delivery type, and the occurrence of neonatal near misses. Southeast Region, 2021-2025.

Global Incidence	NNM-total (%)	Crude regression
	12.5	OR	95%CI
Hospital size
≥1000 LB/year	13.2	1.51	0.99-2.30
<1000 LB/year	9.2	1	-
Payment type
Public	13.3	1.29	0.99-1.66
Private	10.7	1	-
Residence location
Urban	12.9	1.74	1.15-2.61
Rural	7.9	1	-
Age
10-19	15.1	1.27	0.99-1.63
20-34	12.3	1	-
35-39	10.6	0.85	0.70-1.03
≥40	15.8	1.34	1.01-1.78
Skin color
White	12.4	1	-
Black	14.2	1.18	0.92-1.51
Brown	12.0	0.97	0.81-1.15
Marital status
Not living with partner	16.1	1.43	1.16-1.77
Living with partner	11.8	1	-
Schooling (study years)
≤8 (EL incomplete)/no information	12.2	1.05	0.76-1.45
9-11 (EL complete)	14.5	1.28	0.99-1.66
12-15 (HS complete)	12.1	1.04	0.84-1.28
≥16 (HE complete)	11.7	1	-
Working during pregnancy
No	12.0	0.93	0.78-1.11
Yes	12.8	1	-
Household Income Quintile
1 quintile (<1300)	14.3	1.17	0.87-1.57
2 quintile (1300-1899)	12.5	1.00	0.73-1.38
3 quintile (1900-2599)	13.0	1.04	0.81-1.35
4 quintile (2600-4699)	11.1	0.87	0.69-1.12
5 quintile (≥4700)	12.5	1	-
No information on income	11.7	0.93	0.67-1.29
Parity
Primiparous	13.0	1.14	0.96-1.35
1-2	11.6	1	-
≥3	14.3	1.27	0.97-1.67
Pregestational BMI
<18.5	13.4	1.08	0.70-1.66
18.5-24.9	12.6	1	-
25-29.9	11.6	0.92	0.75-1.12
≥30	13.0	1.04	0.84-1.30
Hypertensive syndromes
No	11.2	1	-
Chronic AH	15.2	1.43	1.06-1.93
Gestational AH	12.3	1.12	0.80-1.56
Preeclampsia	22.4	2.29	1.55-3.38
Preeclampsia superimposed on chronic preeclampsia	24.4	2.57	1.68-3.92
Unspecified HS	19.2	1.89	1.06-3.38
Diabetes
No	11.2	1	-
Pregestational diabetes	27.6	2.76	1.83-4.16
Gestational diabetes (≥92 mg/dl)	13.5	1.12	0.90-1.39
Maternal syphilis diagnosis*
No	10.7	1	-
Yes	39.6	5.48	4.07-7.38
Prenatal care start
≤12	12.0	1	-
13-20	13.0	1.09	0.88-1.36
21-27	16.2	1.42	1.01-2.00
28+ (or did not do it)	21.2	1.97	1.26-3.07
Appropriate prenatal care appointments
<50% (or did not do it)	24.4	2.40	1.60-3.61
50-74%	12.9	1.10	0.82-1.46
75-99%	12.2	1.03	0.79-1.36
≥100%	11.9	1	-
Smoking during pregnancy
No	11.7	1	-
Yes	21.3	2.04	1.55-2.69
Alcohol use during pregnancy
No	11.6	1	-
Yes	15.7	1.43	1.13-1.80
Severe Maternal Morbidity before delivery**
No	11.2	1	-
Yes	22.0	2.24	1.81-2.77
Delivery type
Vaginal	11.8	1	-
Forceps/vacuum	25.2	2.51	1.47-4.28
Cesarean	12.6	1.07	0.87-1.31
NB sex
Male	13.6	1.23	1.04-1.46
Female	11.3	1	-

• *Laboratory or clinical diagnosis during prenatal care or upon admission for delivery. **Premature placental abruption, uterine rupture, eclampsia, HELLP syndrome, severe preeclampsia, severe hypertension, pulmonary edema, acute respiratory failure, seizures, shock, thrombocytopenia, and thyrotoxic crisis.
• Source: Authors.

At the intermediate level, NNM was associated with hypertensive syndromes (chronic hypertension, OR=1.43; preeclampsia, OR=2.29; superimposed preeclampsia, OR=2.57; unspecified hypertension, OR=1.89), pregestational diabetes (OR=2.76; 95%CI: 1.83-4.16), maternal syphilis (OR=5.48; 95%CI: 4.07-7.38), late onset or lack of prenatal care (OR=1.97; 95%CI: 1.26-3.07), inadequate number of prenatal care appointments (OR=2.40; 95%CI: 1.60-3.61), tobacco use (OR=2.04; 95%CI: 1.55-2.69), and alcohol use during pregnancy (OR=1.43; 95%CI: 1.13-1.80). At the proximal level, the following variables were associated with NNM: SMM (OR=2.24; 95%CI: 1.81-2.77), forceps/vacuum delivery (OR=2.51; 95%CI: 1.47-4.28), and male sex of the newborn (OR=1.23; 95%CI: 1.04-1.46) (Table 3).

In the multivariate model, NNM remained associated with residing in an urban area (OR_adj=1.75; 95%CI: 1.15-2.65), not living with a partner (OR_adj=1.36; 95%CI: 1.11-1.67), hypertensive syndromes (chronic hypertension: OR_adj=1.39; preeclampsia: OR_adj=2.35; superimposed preeclampsia: OR_adj=2.59; unspecified hypertension: OR_adj=2.06), pregestational diabetes (OR_adj=2.76; 95%CI: 1.78-4.28), maternal syphilis (OR_adj=5.44; 95%CI: 3.96-7.48), inadequate prenatal care (<50% of recommended appointments: OR_adj=2.14; 95%CI: 1.44-3.18), alcohol consumption (OR_adj=1.50; 95%CI: 1.11-2.02), SMM before delivery (OR_adj=1.96; 95%CI: 1.43-2.69), forceps/vacuum delivery (OR_adj=2.39; 95%CI: 1.39-4.13), and male sex (OR_adj=1.23; 95%CI: 1.03-1.47) (Table 4).

Table 4
Multivariate regression of sociodemographic factors, maternal characteristics/habits, organizational aspects of health services, obstetric complications, delivery type, and the occurrence of neonatal near misses. Southeast Region, 2021-2025.

	NNM-total (%)	Adjusted regression
Global Incidence	12.5	ORadj	95%CI
Payment type
Public	13.3	1.22	0.94-1.58
Private	10.7	-	-
Residence location
Urban	12.9	1.75	1.15-2.65
Rural	7.9	-	-
Age
10-19	15.1	1.11	0.86-1.42
20-34	12.3	-	-
35-39	10.6	0.88	0.73-1.07
≥40	15.8	1.37	1.01-1.84
Marital status
Not living with partner	16.1	1.36	1.11-1.67
Living with partner	11.8	-	-
Parity
Primiparous	13.0	1.22	1.02-1.47
1-2	11.6	-	-
≥3	14.3	1.05	0.78-1.41
Hypertensive syndromes
No	11.2	-	-
Chronic AH	15.2	1.39	1.03-1.88
Gestational AH	12.3	1.11	0.78-1.57
Preeclampsia	22.4	2.35	1.61-3.43
Preeclampsia superimposed on chronic preeclampsia	24.4	2.59	1.66-4.06
Unspecified HS	19.2	2.06	1.08-3.92
Diabetes
No	11.2	-	-
Pregestational diabetes	27.6	2.76	1.78-4.28
Gestational diabetes (≥92 mg/dl)	13.5	-	-
Maternal syphilis diagnosis*
No	10.7	-	-
Yes	39.6	5.44	3.96-7.48
Appropriate prenatal care appointments
<50% (or did not do it)	24.4	2.14	1.44-3.18
50-74%	12.9	0.97	0.72-1.30
75-99%	12.2	0.98	0.73-1.30
≥100%	11.9	-	-
Smoking during pregnancy
No	11.7	-	-
Yes	21.3	1.50	1.11-2.02
Severe Maternal Morbidity before delivery**
No	11.2	-	-
Yes	22.0	1.96	1.43-2.69
Delivery type
Vaginal	11.8	-	-
Forceps/vacuum	25.2	2.39	1.39-4.13
Cesarean	12.6	1.12	0.90-1.39
NB sex
Male	13.6	1.23	1.03-1.47
Female	11.3	-	-

• *Laboratory or clinical diagnosis during prenatal care or upon admission for delivery. **Premature placental abruption, uterine rupture, eclampsia, HELLP syndrome, severe preeclampsia, severe hypertension, pulmonary edema, acute respiratory failure, seizures, shock, thrombocytopenia, and thyrotoxic crisis.
• Source: Authors.

Discussion

Using the criterion proposed by Pileggi-Castro et al. ⁷, NNM incidence was 12.45%, similar to that reported in national studies^19-21. Among the pragmatic criteria, prematurity (10.85%) and low birth weight (10.11%) predominated. A study in high-risk hospitals in Recife found 8.59% of births occurring at <33 weeks²². The frequency of low birth weight, however, differed from that reported in other investigations^23,24.

Regarding management criteria, 97.81% of the NNM cases underwent some intervention, indicating greater severity²². In a study with 4,571 postpartum women, Assis et al. ²⁵ found lower frequencies of phototherapy (4%), antibiotics (3.8%), and CPAP (2.1%), whereas Carvalho et al. ²⁶ observed mechanical ventilation in 66.8% of the cases²⁷. These discrepancies reflect population differences, diagnostic criteria, and care complexity, reinforcing the need for standardization and contextualization of practices^7,23,27.

Among the socioeconomic variables in the hierarchical model, residing in an urban area increased the odds of NNM by 75% (OR_adj=1.75; 95%CI: 1.15-2.65). Studies reinforce the role of sociodemographic factors in neonatal morbidity and mortality^28,29. In a national cohort, hospitals located in state capitals also increased the risk of NNM (RR_adj=1.89; 95%CI: 1.40-2.55)²¹. Thus, even with greater infrastructure, urban overload and inequalities may compromise neonatal outcomes^21,30,31.

Not living with a partner increased the odds of NNM by 36% (OR_adj=1.36; 95% CI: 1.11-1.67), reinforcing the role of social support during pregnancy. Consistently, Pereira et al. ²¹ observed a higher occurrence of severe outcomes among women without a marital bond, attributed to poorer adherence to prenatal care and greater barriers to access.

The literature points to maternal morbidity as a strong predictor of severe neonatal outcomes^32-34. In this study, syphilis was the condition most strongly associated with NNM (OR_adj=5.44). In a prospective cohort, Kate et al. ³⁵ likewise identified a more than threefold increased risk, especially with late prenatal care or inadequate treatment. Recognized as a marker of vulnerability and of failures in surveillance^36,37, congenital syphilis remains an indicator of inequalities in prenatal care³⁷.

Maternal hyperglycemia is widely recognized as a determinant of perinatal morbidity^38-40. In this study, pregestational diabetes nearly tripled the risk of NNM (OR_adj=2.76), a finding consistent with Pereira et al. ²¹ (RR_adj=2.63). Hypertensive syndromes also increased the risk of NNM (OR_adj=2.35 and 2.59). National and international evidence shows higher prematurity rates and poorer neonatal outcomes among pregnant women with hypertension^41,42, reinforcing that blood pressure decompensation impairs placental perfusion and increases the risk of fetal hypoxia^43,44.

Women who attended fewer than 50% of the recommended prenatal care appointments had a twofold higher risk of NNM (OR_adj=2.14), a finding consistent with the literature^45,46. In Brasília, Modes et al. ⁴⁷ also observed a higher risk with fewer than six appointments (OR=2.20). These results reinforce the importance of adequate prenatal care for early identification of maternal risk conditions and for reducing NNM^21,48-52.

Alcohol use during pregnancy increased the odds of NNM by 50% (OR_adj=1.50). The literature confirms that maternal alcohol use compromises fetal growth and increases neonatal complications^53-55, pointing to the need for screening and counseling during prenatal care⁵⁶.

Regarding SMM, recognized as a risk factor for adverse neonatal outcomes, this study identified a 1.96-fold increase in the odds of NNM, consistent with the literature^57,58. Similarly, a prospective cohort study in Uganda involving 220 women showed that SMM quadrupled the risk of adverse perinatal outcomes (RR_adj=4.02; 95%CI: 2.32-6.98), such as prematurity, low birth weight, and the need for neonatal intensive care⁵⁹.

Instrumental delivery by forceps or vacuum increased the odds of NNM by 2.39 times, indicating that emergency obstetric interventions reflect greater clinical severity^60,61.

Male sex was also associated with the risk of NNM (OR_adj=1.23), due to greater biological vulnerability, such as pulmonary immaturity and a greater propensity for respiratory distress and prematurity⁶². Thus, sex should be included in adjustment models and neonatal surveillance analyses, also considering social and care-related influences⁶³.

Although this study is regional, its findings are in dialogue with those of Pereira et al. ²¹ by confirming the central role of hypertensive syndromes and pregestational diabetes in NNM.

However, unlike the aforementioned study, in which no variable at the distal level (sociodemographic) showed a significant association with the outcome, this investigation found strong associations with sociodemographic factors, indicating a shift in the profile of vulnerability among pregnant women. Whereas clinical and care-related factors previously predominated, in this study, the social determinants began to exert a relevant influence on the occurrence of NNM.

There was also a greater influence of severe maternal conditions and aspects related to intrapartum care. The differences between the studies suggest advances in the recognition and management of clinical conditions traditionally associated with NNM, yet they also highlight the persistent and more profound territorial, social, and care-related inequities. In the present study, the higher odds of NNM among women living in urban areas and among those not living with a partner, as well as the association with inadequate prenatal care, maternal syphilis, and alcohol use during pregnancy, indicate that the outcome remains socially determined and unequally distributed.

These findings reveal avoidable inequalities related to living conditions, social support, and the opportunity and quality of prenatal and intrapartum care, which fall disproportionately on groups in greater social vulnerability. We reinforce the need for intersectoral actions in order to expand access to and improve the quality of prenatal care, qualify delivery care, and manage comorbidities early, thereby reducing NNM and avoidable morbidity and mortality.

References

• ¹ Chafik K, Barich F, Aslaou F, Laamiri FZ, Barkat A. The evolution of the criteria for identifying neonatal near miss: a systematic review. Turk J Pediatr 2023; 65(2):181-193.
• ² Lopes ASA, Cariry EL, Leite DF, Santana LB, Silva JRS, Santos VS, Gurgel RQ. Early-life mortality rates in Brazil and progress toward meeting related sustainable development goals: a nationwide population study. Lancet Reg Health 2025; 47:101133.
• ³ United Nations Children's Fund (UNICEF). Child Mortality Estimates: Brazil Neonatal Mortality Rate, 2023-2024. New York: UNICEF; 2024.
• ⁴ World Health Organization (WHO). Neonatal mortality rate (per 1000 live births). Geneva: WHO; 2024.
• ⁵ Medeiros PB, Bailey C, Andrews C, Liley H, Gordon A, Flenady V. Neonatal near miss: A review of current definitions and the need for standardisation. Aust N Z J Obstet Gynaecol 2022; 62(3):358-363.
• ⁶ Medeiros PB, Bailey C, Pollock D, Liley H, Gordon A, Andrews C, Flenady V. Neonatal near-miss audits: a systematic review and a call to action. BMC Pediatr 2023; 23(1):573.
• ⁷ Pileggi-Castro C, Camelo JS Jr, Perdoná GC, Mussi-Pinhata MM, Cecatti JG, Mori R, Morisaki N, Yunis K, Vogel JP, Tunçalp Ö, Souza JP, on behalf of the WHO Multicountry Survey on Maternal and Newborn Health Research Network. Development of criteria for identifying neonatal near-miss cases: analysis of two WHO multicountry cross-sectional studies. BJOG 2014; 121(Supl. 1):110-118.
• ⁸ Kale PL, Mello-Jorge MHP, Silva KS, Fonseca SC. Neonatal near miss and mortality: factors associated with life-threatening conditions in newborns at six public maternity hospitals in Southeast Brazil. Cad Saude Publica 2017; 33(4):e00179115.
• ⁹ Rocha NM, Kale PL, Fonseca SC, Brito ADS. Neonatal near miss and mortality and associated factors: a cohort study of births in the city of Rio de Janeiro, RJ, Brazil. Rev Paul Pediatr 2022; 41:e2021302.
• ¹⁰ Silva JMP, Kale PL, Fonseca SC, Nantes T, Alt NN. Factors associated with severe maternal, fetuses and neonates' outcomes in a university hospital in Rio de Janeiro State. Rev Bras Saude Mater Infant 2023; 23:e20220135.
• ¹¹ Theme Filha MM, Baldisserotto ML, Leite TH, Mesenburg MA, Fraga ACSA, Bastos MP, Domingues RMSM, Gama SGN, Bittencourt SA, Nakamura-Pereira M, Estevs-Pereira AP, Leal MC. Nascer no Brasil II: protocolo de investigação da saúde materna, paterna e da criança no pós-parto. Cad Saude Publica 2024; 40(4):e00249622.
• ¹² Leal MC, Esteves-Pereira AP, Bittencourt SA, Domingues RMSM, Theme Filha MM, Leite TH, Ayres BVS, Baldisserotto ML, Nakamura-Pereira M, Moreira MEL, Gomes MASM, Dias MAB, Takemoto MLS, Pacagnella RC, Gama SGN. Protocolo do Nascer no Brasil II: Pesquisa Nacional sobre Aborto, Parto e Nascimento. Cad Saude Publica 2024; 40(4):e00036223.
• ¹³ Lima S, Carvalho ML, Vasconcelos AGG. Proposta de modelo hierarquizado aplicado à investigação de fatores de risco de óbito infantil neonatal. Cad Saude Publica 2008; 24(8):1910-6.
• ¹⁴ Institute of Medicine; National Research Council. Weight Gain During Pregnancy: Reexamining the Guidelines. Washington, D.C.: National Academies Press; 2009.
• ¹⁵ American College of Obstetricians and Gynecologists. Gestational hypertension and preeclampsia: ACOG Practice Bulletin, Number 222. Obstet Gynecol 2020; 135(6):e237-e260.
• ¹⁶ Say L, Souza JP, Pattinson RC. Maternal near miss: towards a standard tool for monitoring quality of maternal health care. Best Pract Res Clin Obstet Gynaecol 2009; 23:287-296.
• ¹⁷ Brasil. Ministério da Saúde (MS). Conselho Nacional de Saúde (CNS). Resolução nº 466, de 12 de dezembro de 2012. Diário Oficial da União 2013; 13 jun.
• ¹⁸ Fundação Oswaldo Cruz (Fiocruz). Nascer no Brasil II: inquérito nacional sobre perdas fetais, partos e nascimentos. Rio de Janeiro: Fiocruz; 2020.
• ¹⁹ Silva GA, Rosa KA, Saguier ESF, Henning E, Mucha F, Franco SC. Estudo de base populacional sobre a prevalência de near miss neonatal em município do Sul do Brasil. Rev Bras Saude Mater Infant 2017; 17(1):169-177.
• ²⁰ Lopes FNB, Gouveia APM, Carvalho OMC, Viana Júnior AB, Leite ÁJM, Araujo Júnior E. Associated factors with neonatal near miss in twin pregnancies in a public referral maternity unit in Brazil. J Turk Ger Gynecol Assoc 2021; 22(1):12-21.
• ²¹ Pereira TG, Rocha DM, Fonseca VM, Moreira MEL, Gama SGN. Fatores associados ao near miss neonatal no Brasil. Rev Saude Publica 2020; 54:123.
• ²² França KEX, Vilela MBR, Frias PG, Chaves MA, Sarinho SW. Near miss neonatal em hospitais de referência para gestação e parto de alto risco: estudo transversal. Cad Saude Publica 2021; 37(6):e00196220.
• ²³ Santos P, Cecatti JG, Serruya SJ, Almeida PV, Duran P, Mucio Bd, Pileggi-Castro C; PAHO Neonatal Near Miss Working Group. Neonatal near miss: the need for a standard definition and appropriate criteria and the rationale for a prospective surveillance system. Clinics 2015; 70(12):820-826.
• ²⁴ Brasil DRPA, Vilela MBR, França KEX, Sarinho SW. Neonatal morbidity near miss in tertiary hospitals in a capital of Northeast Brazil. Rev Paul Pediatr 2019; 37(3):275-282.
• ²⁵ Assis TSC, Martinelli KG, Gama SGN, Santos Neto ET. Associated factors of neonatal near miss among newborns of adolescent mothers in Brazil. Rev Esc Enferm USP 2022; 56:e20210359.
• ²⁶ Carvalho OMC, Junior ABV, Augusto MCC, Xavier ATO, Gouveia APM, Lopes FNB, Carvalho FHC. Factors associated with neonatal near miss and death in public referral maternity hospitals. Rev Bras Saude Mater Infant 2020; 20(3):839-850.
• ²⁷ Silva AAM, Leite AJM, Lamy ZC, Moreira MEL, Gurgel RQ, Cunha AJLA, Leal MC. Neonatal near miss in the Birth in Brazil survey. Cad Saude Publica 2014; 30(Supl. 1):S182-S191.
• ²⁸ Faruk MO, Zahangir MS, Akhter S, Prome JF, Akter N, Tasnim J. A review of the impact of socio-economic, demographic and cultural factors on child mortality. Discov Public Health 2025; 22:141.
• ²⁹ Kale PL, Fonseca SC. Age-specific neonatal mortality and associated factors in the 2021 state of Rio de Janeiro (Brazil) birth cohort. Rev Bras Epidemiol 2022; 25:e220038.
• ³⁰ Silva MLM, Oliveira NN, Ferdin A, Galdino MJQ, Melo EC, Oliveira RR. Análise espacial do near miss neonatal e fatores contextuais no Paraná, Brasil (2020-2022). Rev Bras Saude Mater Infant 2025; 28(2):317-329.
• ³¹ Rocha PRH, Bettiol H, Confortin SC, Bazo G, Aristizábal LYG, Simões VMF, Matijasevich A, Santos IS, Silveira MF, Cavalli RC, Silva AAM, Barbieri MA. Fatores associados ao near miss neonatal: coortes de nascimentos de três cidades brasileiras. Cien Saude Colet 2022; 27(7):4663-4674.
• ³² Goyomsa GG, Deriba BS, Wadejo MM, Debela SA, Amhare AF. Magnitude of neonatal near miss and associated factors among newborns delivered at North Shewa zone public hospitals, Ethiopia. Front Public Health 2022; 10:979636.
• ³³ Colomar M, Mucio B, Sosa C, Gomez R, Mainero L, Souza RT, Costa ML, Luz AG, Sousa MH, Cruz CM, Chevez LM, Lopez R, Carrillo G, Rizo U, Saint Hillaire EE, Arriaga WE, Guadalupe RM, Ochoa C, Gonzalez F, Castro R, Stefan A, Moreno A, Serruya SJ, Cecatti JG. Neonatal outcomes according to different degrees of maternal morbidity: evidence from the CLAP network. Glob Health Action 2023; 16(1):2269736.
• ³⁴ Mengistu TS, Turner JM, Flatley C, Fox J, Kumar S. The impact of severe maternal morbidity on perinatal outcomes in high income countries: systematic review and meta-analysis. J Clin Med 2020; 9(7):2035.
• ³⁵ Kale PL, Mello-Jorge MHP, Silva KS, Fonseca SC. Neonatal near miss and mortality: factors associated with life-threatening conditions in newborns at six public maternity hospitals in Southeast Brazil. Cad Saude Publica 2017; 33(4):e00179115.
• ³⁶ Silva KAG, Oliveira KCPN, Almeida DM, Sobrinha ES, Santos EA, Melo GC, Santos RSP. Desfechos em fetos e RN expostos a infecções na gravidez. Rev Bras Enferm 2021; 74(3):e20200236.
• ³⁷ Esméria Neta M, Silva CSO, Silva Junior RF, Eleutério TP, Holzmann APF, Ruas EFG, Marques LO. Prevalence and associated factors with syphilis in pregnant women attended in primary health care in a city in the Southeast, Brazil. Rev. Bras Saude Mater Infant 2024; 24:e20230188.
• ³⁸ Yang F, Liu H, Ding C. Gestational diabetes mellitus and risk of neonatal respiratory distress syndrome: a systematic review and meta-analysis. Diabetol Metab Syndr 2024; 16(1):294.
• ³⁹ Costa LMO, Rocha Neta RDO, Silva ZP, Souza MVC, Piovezan AP, Andrade ILXC, Lins JVM, Soares BNP. Complicações obstétricas e neonatais relacionadas ao diabetes mellitus gestacional: revisão integrativa. LEV 2024; 15(43):9266-9283.
• ⁴⁰ Battarbee AN, Venkatesh KK, Aliaga S, Boggess KA. The association of pregestational and gestational diabetes with severe neonatal morbidity and mortality. J Perinatol 2020; 40(2):232-239.
• ⁴¹ Pereira JC, Pereira Junior AC, Martins EF, Couto BRGM, Souza KV, Rezende EM. Desfechos neonatais desfavoráveis: um estudo de base hospitalar. Rev Med Minas Gerais 2024; 34:e-34101.
• ⁴² Bromfield SG, Ma Q, DeVries A, Inglis T, Gordon AS. The association between hypertensive disorders during pregnancy and maternal and neonatal outcomes: a retrospective claims analysis. BMC Pregnancy Childbirth 2023; 23(1):514.
• ⁴³ Herrera CL, Wang Y, Udayakumar D, Xi Y, Do QN, Lewis MA, Owen DM, Fei B, Spong CY, Twickler DM, Madhuranthakam AJ. Longitudinal assessment of placental perfusion in normal and hypertensive pregnancies using pseudo-continuous arterial spin-labeled MRI. Eur Radiol 2023; 33(12):9223-9232.
• ⁴⁴ Guida JPS, Dias TZ, Lajos GJ, Nomura ML, Pacagnella RC, Tedesco RP, Rehder PM, Haddad S, Sousa MH, Passini Junior R, Cecatti JG, Costa ML. Hypertensive disorders during pregnancy as a major cause of preterm birth and adverse perinatal outcomes. Einstein (Sao Paulo) 2024; 22:eAO0514.
• ⁴⁵ Ferreira FM, Venâncio KCMP, Narchi NZ. Network care: relationship between prenatal care adequacy and hospital obstetric care in a cross-sectional study. Rev Esc Enferm USP 2022; 56:e20220011.
• ⁴⁶ Vale CCR, Almeida NKO, Almeida RMVR. Association between prenatal care adequacy indexes and low birth weight outcome. Rev Bras Ginecol Obstet 2021; 43(4):256-263.
• ⁴⁷ Modes PSSA, Gaíva MAM, Andrade ACS, Fujimori E. Near miss neonatal em capital do Centro-Oeste brasileiro: estudo caso-controle. Cien Saude Colet 2024; 29(1):e17462022.
• ⁴⁸ Anggondowati T, El-Mohandes AAE, Qomariyah SN, Kiely M, Ryon JJ, Gipson RF, Zinner B, Achadi A, Wright LL. Maternal characteristics and obstetrical complications impact neonatal outcomes in Indonesia: a prospective study. BMC Pregnancy Childbirth 2017;17(1):100.
• ⁴⁹ Crequit S, Chatzistergiou K, Bierry G, Bouali S, La Tour AD, Sgihouar N, Renevier B. Association between social vulnerability profiles, prenatal care use and pregnancy outcomes. BMC Pregnancy Childbirth 2023; 23(1):465.
• ⁵⁰ Modes PSSA, Gaíva MAM, Andrade ACS, Guimarães LV. Factors associated with neonatal near miss in a Midwest capital in Brazil. Rev Bras Saude Mater Infant 2023; 23:e20210244.
• ⁵¹ Defilipo ÉC, Chagas PSC, Drumond CM, Ribeiro LC. Factors associated with premature birth: a case- control study. Rev Paul Pediatr 2022; 40:e2020486.
• ⁵² Silva AAD, Leite LOB, Azevedo WF. Assistência pré- natal e desfechos neonatais em RN pré-termos tardios. Braz J Health Rev 2025; 8(5):e82845.
• ⁵³ Popova S, Dozet D, Temple V, Riddell C, Yang C. A population-based study on women who used alcohol during pregnancy and their neonates in Ontario, Canada. Children (Basel) 2024; 11(8):993.
• ⁵⁴ Negrão MEA, Rocha PRH, Saraiva MCP, Barbieri MA, Simões VMF, Batista RFL, Ferraro AA, Bettiol H. Association between tobacco and/or alcohol consumption during pregnancy and infant development: BRISA Cohort. Braz J Med Biol Res 2021; 54(1):10252.
• ⁵⁵ Pielage M, El Marroun H, Odendaal HJ, Willemsen SP, Hillegers MHJ, Steegers EAP, Rousian M. Alcohol exposure before and during pregnancy is associated with reduced fetal growth: the Safe Passage Study. BMC Med 2023; 21(1):318.
• ⁵⁶ Muggli E, Halliday J, Elliott EJ, Anderson PJ, Penington A, Spittle A, Forster DA, Lewis S, Elliott EJ, Anderson PJ. Low to moderate prenatal alcohol exposure and neurodevelopment in early school-aged children. Sci Rep 2024; 14:7302.
• ⁵⁷ Domingues RMSM, Dias MAB, Nakamura-Pereira M, Pacagnella RC, Lansky S, Gama SGN, Esteves-Pereira AP, Bittencourt SA, Miranda Theme Filha M, Ayres BVDS, Baldisserotto ML, Leite TH, Leal MDC. Mortalidade perinatal, morbidade materna grave e near miss materno: protocolo da pesquisa Nascer no Brasil II. Cad Saude Publica 2024; 40(4):e00248222.
• ⁵⁸ Ferreira MES, Coutinho RZ, Queiroz BL. Morbimortalidade materna no Brasil e a urgência de um sistema nacional de vigilância do near miss materno. Cad Saude Publica 2023; 39(8):e00013923.
• ⁵⁹ Jjuuko M, Lugobe HM, Migisha R, Agaba DC, Tibaijuka L, Kayondo M, Ngonzi J, Kalyebara PK, Kanyesigye H. Maternal near miss as a predictor of adverse perinatal outcomes: findings from a prospective cohort study in Uganda. BMC Pregnancy Childbirth 2024; 24:42.
• ⁶⁰ Chawanpaiboon S, Titapant V, Pooliam J. Neonatal complications and risk factors associated with assisted vaginal delivery. Sci Rep 2024; 14:11960.
• ⁶¹ Muraca GM, Ralph LE, Christensen P, D'Souza R, Geoffrion R, Lisonkova S, Joseph KS. Maternal and neonatal trauma during forceps and vacuum-assisted vaginal delivery. BMJ 2023; 383:e073991.
• ⁶² Aliyi AA, Deyessa N, Dilnessie MY. Effect of maternal near miss on neonatal mortality in selected hospitals: prospective cohort study, Ethiopia. SAGE Open Med 2021; 9:20503121211042219.
• ⁶³ Aristizábal LYG, Rocha PRH, Confortin SC, Simões VMF, Bettiol H, Barbieri MA, Silva AAM. Associação entre quase-forte neonatal e desenvolvimento infantil: coortes de nascimento BRISA. BMC Pediatr 2023; 23(1):125.

• Data availability statement
  The research data are available upon request from the corresponding author.

• Chief editors:
  Maria Cecília de Souza Minayo, Romeu Gomes, Antônio Augusto Moura da Silva, Vania de Matos Fonseca

Data availability

The research data are available upon request from the corresponding author.

Publication Dates

• Publication in this collection
  17 Aug 2026
• Date of issue
  Aug 2026

History

• Received
  17 Apr 2026
• Accepted
  27 Apr 2026
• Published
  29 Apr 2026