María Elena Venegas Martinez, Nesly Lorena Velandia Forero, Tania Acosta Vergara, Rafael Tuesca Molina, Hernando Baquero Latorre, Carla Venegas

Abstract:

Importance: There is little knowledge about the influence of maternal socioeconomic vulnerability in developing COVID-19 infection in newborns. Described neonatal risk factors are mainly biological and do not include social factors. 

Objective: To evaluate the association between maternal socioeconomic vulnerability and the development of COVID-19 in newborns admitted to NICU.

Design: Original research, retrospective cohort study, in newborn-mother bond with one-year follow-up, admitted to NICU during the COVID-19 pandemic between March 2020 and December 2021. The primary endpoint was to evaluate maternal socioeconomic status through the Colombian national survey SISBEN-IV and the development of neonatal COVID-19. Data collectors were blinded about the patients’ COVID status.

Participants: 500 mother-child bond records were analyzed and followed for a year. The eligible population required documented SISBEN-IV classification and a newborn nasopharyngeal swab PCR for Sars-Cov-2. The exposed cohort were newborns from mothers with SISBEN-IV A classification (extreme poverty).

Results: 158 (31.8%) mothers were classified in SISBEN-IV group A (extreme poverty). Maternal COVID-19 was higher in the exposed group (8.8% vs 3.8% p=0.02). Exposed newborns had higher COVID-19 incidence compared to unexposed (10.1% vs. 4.7%, p=0.02). Newborns from vulnerable mothers were 2.2 more likely to develop the disease (adjusted OR: 2.24 95%CI 1.06 – 4.69 p-val=0.03).

Conclusion: Understanding the interaction between biological and social factors is essential to impacting infant morbidity and mortality outcomes. We suggest maternal socioeconomic vulnerability be considered a differentiating risk factor for prenatal care and weight control for neonatal disease.

Background:

The socioeconomic condition of a pregnant woman with a high social vulnerability index (SVI), independent of the used assessment scale, increases her mobility risk. The National Institute of Health (NIH) of the United States has considered health inequalities a risk factor for developing Coronavirus Disease 2019 (COVID-19), affecting mother and child (1-11). Consequently, newborns under one month of age are eight times more likely to be admitted to the Intensive Care Unit (NICU) due to COVID-19 (OR:5,1 IC:1,7-14,9) (1,12-14). Due to the low prevalence of COVID-19 in newborns (<10%) (15), there is little knowledge about the influence of maternal socioeconomic vulnerability in the development of newborn COVID-19 (12,16). Likewise, described neonatal risk factors are mainly biological and do not include social factors (2, 17-19).

The United States Center for Disease Control and Prevention (CDC) SET-NET 2020-2022 reports a prevalence of neonatal COVID-19 of 5.6%, an infection rate of 13.6% in the perinatal registry; and highlights that children under two months of age account for 25% of all hospitalization in children under four years of age (20). Since infant morbidity is an indicator of well-being and development of a country, a study of maternal vulnerability evaluating the socioeconomic risk factors for developing neonatal COVID-19 could provide data to address primary care, and under a salutogenic model guide, public health solutions oriented to reduce social inequality gaps (21-26).

Newborn vulnerability is understood as any biological, psychological, or socioeconomic threat from the maternal environment, the caregiver, or the health system, which can lead to developing newborn COVID-19 (27). Chile studied the pregnant women SVI using a governmental social protection file that records social stratification (4). They found vulnerable mothers with higher susceptibility to health damage when compared to non-vulnerable mothers (4). The CDC has declared “evident health inequalities” as a risk factor for developing infectious diseases. It uses the SVI to help local officials identify communities in need before, during, and after a disaster (2). The Pan-American Health Organization (PAHO) is requesting additional information to monitor health services and studying the relationship between the vulnerability of the Venezuelan migrant maternal population and their state of health (28) recognized maternal vulnerability as a risk factor for neonatal disease to achieve an effective, safe maternity program. 

As per the Colombian Infectious Disease Association, COVID-19 is classified as a Public Health hazard. Due to the nature of the COVID-19 pandemic as a health emergency, there is a knowledge gap about COVID-19 in the neonatal stage and its predisposing factors (1, 18). The present original study seeks to evaluate the association between maternal socioeconomic vulnerability and the development of COVID-19 in newborns admitted to a Newborn Intensive Care Unit (NICU) in Barranquilla, Colombia, during the COVID-19 pandemic. 

Materials and Methods: 

Study design and participants: 

Original research, retrospective cohort study, in newborn-mother bond with one-year follow-up, admitted to a high complexity Newborn Intensive Care Unit in Barranquilla – Colombia (MACSA-NICU), between March 2020 and December 2021. We built a cohort and examined the maternal socioeconomic status through the Colombian national survey SISBEN-IV and evaluated the presence of neonatal COVID-19 by PCR-RT. We reviewed the charts for all 1,100 newborns admitted during the study period. 

The primary endpoint was to determine the association between maternal socioeconomic vulnerability and the diagnosis of newborn COVID-19. Secondary endpoints are included to characterize the features of maternal socioeconomic vulnerability and describe the neonatal biological risk factors for developing COVID-19. 

Eligible populations included mothers of newborns admitted to the MACSA-NICU during the study period, with documented SISBEN-IV classification and a report of the newborn nasopharyngeal swab (real-time PCR for Sars-Cov-2). The exposed cohort was newborns from mothers with SISBEN-IV A classification, and the unexposed cohort was newborns from mothers with a classification other than A (it meant B, C, or D). Exclusion criteria included records from mothers without the SISBEN classification survey, newborns without a nasopharyngeal swab PCR-RT for Sars-Cov-2 result, or with dysmorphisms. Five hundred records of newborn-mother bonds met the study criteria and were defined as subjects of study (See Figure 1). 

The SISBEN-IV indicates social vulnerability in Colombia and was used to allocate resources to vulnerable populations. It was approved through document CONPES 3877 of 2016 and allows the calculation of the Multidimensional Poverty Index (MPI). This classification is comparable to international indicators such as the American SVI used by the CDC to investigate multilevel environmental and social influences and detect risk behaviors and health outcomes. The SISBEN-IV is carried out in the municipalities through a face-to-face survey by trained personnel, considering five items: housing and public services, education level, health status, and fertility, occupation, and household income. It determines the index of unsatisfied needs such as drinking water, sewage, garbage collection, electricity service, telephone line, literacy level, schooling level, health, and occupation. The classification goes from lowest to highest, where the lowest number has less capacity to generate income (See Figure 2). 

Maternal and neonatal variables and outcomes: 

Maternal vulnerability (Exposure) was analyzed as a dichotomous variable (yes/no), determined according to maternal classification in the SISBEN-IV as group A (extreme poverty). The vulnerability status was considered “Yes” if the mother belonged to SISBEN-IV category A or “No” if she belonged to any category other than A. 

The positive neonatal COVID-19 status (outcome) was determined as a dichotomous variable (yes/no) after confirmation of infection by positive PCR-RT for Sars-Cov-2 nasopharyngeal swab. All samples were carried out by authorized laboratories by the Colombian National Institute of Health. The Gold standard test was Real-time polymerase chain reaction (PCR-RT) for Sars- Cov-2. Laboratory results were generated through SemCovid and reported by SisMuestras Information System per resolution 1619 of 2015. Results were reported as “positive” or “negative.” 

Cohort follow-up: 

A PCR-RT for Sars-Cov-2 nasopharyngeal swab was obtained in all newborns admitted to the NICU during the study period. Due to a delay in getting laboratory results, the mother and relatives left accurate contact information. After the newborn-mother bond was discharged from the hospital, mothers were contacted to consent to the study and carry out their follow-up. Telephone surveys were carried out at one and six months from hospital discharge. 

Covariates: 

The following maternal covariates were considered: age, ethnicity, nationality, marital status, level of education, underlying diseases, vaccination status for COVID-19, and history of maternal COVID-19 to perform a comprehensive analysis. Environmental covariates included zip code, overcrowding, and type of health insurance. Newborn covariates were appropriate prenatal care (> six visits), type of delivery, gestational age, neonatal age, gender, weight, perinatal complications, nutritional status, type of diet, neonatal underlying diseases, and positive family contact for COVID-19. 

The Infectious Diseases Colombian Association criteria were followed to determine the risk factors for the severity of the disease. Mother’s vaccination status was considered complete or incomplete according to the type of vaccine received; however, most mothers were not vaccinated at the delivery time. 

Data collection: 

Data was collected using an Excel questionnaire directly fed from the MACSA software, which maintains a daily database of admitted patients. One thousand one hundred medical records were reviewed, and 500 which met inclusion criteria were analyzed. Five follow-up data collectors identified patients by telephone after hospital discharge and filled out the questionnaire. One hundred patients were assigned to each data collector blinded to the patients’ COVID status. 

The study followed national and international ethical considerations for human research. Research Ethical Committee (IRB) from Universidad del Norte approved and endorsed it as “less than minimal risk” (Registry No. 2067, May 26, 2022). 

Bias control: 

Potential sources of bias were controlled as follows: 

For data collection, the typing team was masked. Health personnel collected the information in a database without access to the research methodology to control observer bias. Telephone contact was maintained with the mother and relatives or via their health insurance, updating their information every three months to avoid losing follow-up,. The total dropout was 1,6%. Only patients registered in the SISBEN-IV government system were included To control selection bias. Each variable was analyzed independently for confusion bias, and the significant ones were included in a binomial logistic regression model. For misclassification bias, the database was double-checked by two different people before its final analysis. 

Statistical analysis: 

Qualitative variables (frequency and percentage) and quantitative variables (mean and standard deviation) were used to characterize the population. A univariate and bivariate descriptive analysis was carried out based on the effect variable (Positive Neonatal COVID-19). Contingency tables, Chi-square, p-value (significance <0.05), and simple logistic regression were used to establish the association between maternal socioeconomic vulnerability and diagnosis of neonatal COVID-19. Independent variables were analyzed, and then multi-variable analysis provided raw and adjusted ORs with their respective 95% CI. Significant variables were included in a binomial logistic regression model to establish the probabilities of newborns from socioeconomically vulnerable mothers presenting Neonatal COVID-19. A database was created in Excel (version 97-2004) and analyzed in the SPSS program version 2.9 0.0.0 (241). 

Results: 

Five hundred mother-child bond records were analyzed. Table 1 shows maternal (A), environmental (B), and neonatal (C) demographic characteristics. 

Maternal demographic characteristics: 

Mother’s average age was 24 years (SD 6.6 years); 281 (56,2%) were Colombians and 219 (43,8%) were Venezuelans. 465 (93%) mothers were “mestiza,” 12 (2,4%) “white,” 8 (1,6%) “Afro,” and 15 (3%) “other races” like native and gypsy. Most mothers were in free union with their partner (n=327 – 65,4%), 107 (21,4%) were single mothers, and 65 (13%) were married. Most mothers achieved an incomplete high school degree (324 – 64,8%) or an incomplete elementary degree (22 – 4,4%); 23 (4,7%) had no education; 31 (6,2%) completed high school and 54 (10,8%) a bachelor’s degree. One hundred fifteen mothers (23%) have at least one comorbidity: Preeclampsia (45 – 9%), Asthma (13 – 2,6%), Diabetes (8 – 1,6%), and Obesity (1 – 0,2%). Thirty-five mothers (7%) had no prenatal control, and 279 (55,8%) a poor-quality control with less than six visits at the time of delivery. 420 (84%) mothers were not vaccinated against COVID-19. At the delivery time, 27 moms (5.4%) had COVID-19. 

Environmental characteristics: 

271 (54.2%) of the population resides in the urban area of Barranquilla, 179 (35.8%) in the suburbs, and 50 (10%) in the rural areas. 130 (26%) mothers reported living in overcrowding conditions (four or more people sleeping per room at home). 309 (61.8%) mothers had health insurance at hospital admission. 158 (31.8%) mothers were classified as SISBEN-IV group A, considered in extreme poverty and a marker of socioeconomic vulnerability for this cohort. 195 (39%) mothers were classified B, 127 (25.2%) C, and 20 (4%) D or population at not risk of poverty. 

Newborn demographic characteristics: 

Newborn average age seven days (SD 10.7 days); 278 (55.6%) were male and 222 (44,4%) females; gestational age 37.5 weeks (SD 2.7 weeks); weight 2,889 gms (SD 665 gms); 160 (32%) were preterm. 302 (60.4%) babies were born via cesarean section and 198 (39.6%) had vaginal delivery. 440 (88%) had adequate weight for their gestational age, 14 (2,8%) were small, and 46 (9,2%) were big. 219 (43.8%) newborns were exclusively breastfed. 106 (21.2%) present perinatal complications like neonatal asphyxia, premature membrane rupture, amniotic infection, or requiring reanimation. 32 (6.4%) newborns tested positive for COVID-19: 13 (2.6%) were diagnosed with mild disease, 11(2.2%) with severe, and 8(1.6%) with critical disease. There were no mortalities among the newborns COVID-19 positive. 

Follow-up Data and Cross-Analysis: 

479 (95.8%) newborns were discharged home, 17 (3.4%) were transferred to a higher level of care, and 4 (0.8%) died. No mortalities in COVID-19 patients. There were no deaths at six months and 8 (1.6%) dropouts (See Table 1). 

Table 2 shows maternal sociodemographic characteristics and clinical factors according to maternal vulnerability status (exposure/SISBEN-IV A). Homogeneous distribution for the populations was observed, with p-values > 0.05 for all variables. The presence of positive maternal COVID-19 at the time of delivery was higher for the exposed group (8.8% vs 3.8% p=0.02). Likewise, neonatal demographic characteristics had no statistical difference based on the maternal vulnerability status. Neonatal COVID-19 in the exposed group was higher when compared with the unexposed population (10.1% vs. 4.7%, p=0.02), and the infection was more critical (3.1% vs 0.9%, p=0.04). 

In a bivariate analysis, after adjusting for confounding variables, newborns from vulnerable mothers (Exposure/SISBEN-IV A) were 2.2 times more likely to develop COVID-19 when compared to not vulnerable mothers (adjusted OR: 2.24 95%CI 1.06 – 4.69 p-val=0.03). Model 2: b:2,68; DE=0,183; p val<0,001 (See Table 3). 

Discussion: 

After overcoming the first stage of the COVID-19 pandemic, the risk behavior for vulnerable populations is more frequently associated with adverse health outcomes. The scarce social and psychological resources that overwhelmed the healthcare systems during the spread of the Sars-CoV-2 virus have been an example of this (20). There is a systematic neglect of the need for equality by gender, social class, or race, which makes people lose trust in institutions, education, and health systems (29). In our study, according to the SISBEN-IV Colombian socioeconomic status, maternal vulnerability was a significant risk factor for developing neonatal COVID-19. 

The SISBEN-IV classification serves as an indicator of social vulnerability in Colombia and helps in the allocation of economic resources and benefit plans. This classification is comparable to international indicators like the USA SVI. Our study found that vulnerable mothers who correspond to extreme poverty presented higher incidences of COVID-19 infection at the time of delivery and a statistically significant relationship with the development of newborn COVID-19. Newborns from vulnerable mothers were up to 2.2 times more likely to develop the disease. 

Other studies have used SVIs in search of answers to health problems. In 2019, Yee et al. used the SVI as a predictor for adolescent pregnancy (30); the same year in Brazil, Oliveira et al. carried out a case-control study proposing a model to predict preterm birth considering socioeconomic vulnerability, family vulnerability, and non-acceptance of pregnancy (31). As in Oliveira’s study, we observed a high proportion of mothers without health insurance and unable to receive appropriate prenatal care. 

In our study, the risk of presenting neonatal COVID-19 in the exposed population attributable to maternal socioeconomic vulnerability was 55 per 1,000 newborns. Supporting these vulnerable mothers and identifying their risk in a differentiated prenatal control could reduce the development of neonatal COVID-19 by up to 50% and, indeed, other adverse obstetric events. This intervention would impact the figures for maternal and child morbidity and mortality and likely NICU expenses. 

One element amenable to improvement in prenatal care is the doctor-patient relationship. A Danish study published in 2022 revealed that even primary care physicians knew that socioeconomic vulnerability has increased in women of childbearing age, were familiar with indicators of vulnerability in pregnancy, and did not identify them during clinical practice. Not detecting vulnerability in pregnancy is a significant risk factor that contributes to maternal-perinatal inequity and generates adverse events (32). During the follow-up for our patients, mothers expressed feelings about their perception of the health team that led them to make appropriate or inappropriate decisions. This was also documented in a case-control study by Songco et al. (33). 

According to the World Health Organization (WHO), up to 95% of newborns will present a health problem in vulnerable populations such as ethnic minorities, displaced populations, or without satisfied minimum basic needs. Recognizing maternal vulnerability as a risk factor for neonatal disease may be the first step to achieving childhood social justice. 

Limitations and strengths: 

One limitation of our study was the inability to verify other COVID-19-positive contacts due to the scarcity of samples during the overwhelming health emergency, and some relatives refused to be tested. The PAHO states that fear, worries, and stress when facing a situation of high uncertainty, such as the COVID-19 pandemic, can be the explanation for these behaviors that affect mental health in general. 

This study occurred during the beginning of the COVID-19 pandemic when most mothers were not vaccinated against the disease. We suggest comparative vulnerability research in the maternal population with a complete vaccination scheme to analyze whether the association with neonatal COVID-19 persists or if it would be identified as a protective measure. 

The main strengths of our study were the availability of performing all tests by governmental institutions and the national standardized classification for maternal vulnerability through the SISBEN-IV classification. In addition, the MACSA software and database allow a reliable post-discharge follow-up for maternal-newborn bonds and maintain permanent contact with family members. 

Our study had no demographic differences in the exposed and unexposed populations. Although the reference hospital belongs to the governmental service, the reorganization of the health system during the COVID-19 health emergency allowed the care of newborns from all SISBEN-IV classifications. The risk of having COVID-19 in the population studied was 6.2%. This is slightly higher than what has been reported in the literature, as it is a captive population from a departmental reference site (32-34). 

Conclusions and Recommendations: 

This is the first study to determine the association between maternal socioeconomic vulnerability and neonatal COVID-19. We found a higher risk of having COVID-19 in newborns from socioeconomically vulnerable mothers up to 2.2 times (OR a: 2.24 CI 1.06-4.69 p= 0.03). We suggest maternal socioeconomic vulnerability should be considered as a differentiating risk factor for prenatal care and weight control for neonatal disease; and health professionals to be effectively trained in their active detection. 

Restructuring and regulating the process of active detection of socioeconomic vulnerability in pregnant women must become a priority goal, guaranteeing time for its management and allowing the creation of a strong doctor-patient relationship in prenatal care. 

TABLE 1: Mothers and Newborns Sociodemographic and Clinical Characteristics 

Maternal Sociodemographic Characteristics	N (500)	% (100)
Age (years)	24 (6,6 DE)
Nationality:  Colombian Venezuelan	281  219	56,2  43,8
Zipcode:  Rural   Suburbs   Rural	217  161  122	43,4  32,2  24,4
Marital status:   Married   Single   Divorced or separated   Free union (common law marriage)	65  107  1 327	13  21,4  0,2  65,4
SISBEN-IV Classification   A (Maternal Vulnerability marker) B   C   D	158  95  127  20	31,6  39  25,2  4
Education   Incomplete Elementary   Elementary   Incomplete High School   High School   Bachelor’s degree   Technician   Professional	22  44  324  31  54  2 23	4,4  8,8  64,8  6,2  10,8  0,4  4,7
Health Assurance   Yes   No	309  191	61,8  38,2
Overcrowding  Yes  No	130  370	26  74
Maternal Clinical Characteristics	N (500)	% (100)
Covid 19 vaccination   None   One dose   Two doses or more (Complete scheme)	420  51  29	84  10,2  5,8
Control Prenatal   None   Less than 6 controls   6 or more 6 controls	35  279  186	7 55,8  37,2
Maternal Covid-19 (during delivery)   Yes   No	27  473	5,4 94,6
Comorbidity   None   Preeclampsia   Diabetes   Obesity   Asma   Other	385  45  8 1 13  24	77  9 1,6  0,2  2,6  9,6
Neonatal Sociodemographic Characteristics	N(500)	%(100)
Age (Days)	7 (10,7 DE)
Gestational age (weeks)	37,5 SEM (2,7 DE)
Gender   Female   Male	222  278	44,4  55,6
Gestational age   Pre- term   Full Term   Post-term	160  337  3	32  67,4  0,6
Weight (in grams at admission)	2,889 (665 DE)
Neonatal Clinical Features	N (500)	% (100)
Birth Route   Vaginal   Cesárea	198  302	39,6  60,4
Nutritional status (weight)   Appropriate birth weight   Low birth weight (IUGR)   Large birth weight	440  14  46	88  2,8  9,2
Feeding  Exclusive breast milk   Formula   Mixed	219  147  1.34	43,8  29,4  26,8
Risk Factors for Severity   Prematurity   Low birth weight (IUGR)   Low weight after birth   Bronchopulmonary dysplasia   Major malformation   More Than One Factor   None	25  13  18  1  3  60  380	5  2,6  3,6  0,2  0,6  12  76
Perinatal complications   Asphyxia   Premature Membranes Rupture (PMR)   Intra-amniotic infection   Reanimation  2 or more complications   None	19  27  22  17  21  394	3,8  5,4  4,4  3,4  4,2  78,8
Covid -19 neonatal   Yes   No	32  468	6,4  93,6
Covid 19 Classification   Negative   Mild   Severe   Critical	468  13  11  8	93,6  2,6  2,2  1,6
Status at hospital discharge   Home   Transferred to higher level of care   Deceased	479  17  4	95,8  3,4  0,8
Status 6 months after discharge (496)   Alive   Deceased   No data	488  0  8	98,3  0  1,6

TABLE 2: Characteristics of Population According To Maternal Vulnerability Exposure

Maternal vulnerability (SISBEN A/extreme poverty)	Yes (158)	%	No (342)	%	P-val
Maternal Nationality Colombian Venezuelan	94 64	59,1 40,9	187 155	54,8 45,2	0,313
Marital status Married Single Separate Free union (Common-law marriage)	12 38 0 108	7,6 24 0 68,4	53 69 1 219	15,5 20,1 0,3 64,1	0,081
Education Complete Elementary Incomplete Elementary Completed High School Incomplete High School Technician Professional None	15 7 11 96 18 1 10	9,5 4,4 7 60,7 11,3 0,6 6,5	29 15 20 228 36 1 13	8,5 4,4 5,8 66,6 10,5 0,3 3,9	0,832
Overcrowding   Yes No	44 114	27,9 72,1	86 256	25,1 74,9	0,522
Ethnicity Mongrel Afro White Other	152 2 4 0	96,2 1,3 2,5 0	313 6 8 15	91,5 1,7 2,3 4,5	0,061
Health Assurance Yes No	99 59	62,6 37,4	210 132	61,4 38,6	0,788
Mother vaccinated for Covid 19 None One dose Two doses or more (Complete scheme)	134 14 10	84,8 8,8 6,4	286 37 19	83,6 10,8 5,6	0,459
Maternal Comorbidity None   Preeclampsia Diabetes   Obesity   Asthma   Other   Two or more	113 16 1 0 7 10 11	71,5 3,8 0,6 0 4,4 6,3 13,4	272 29 7 1 6 12 15	79,5 0,2 2 0,3 1,7 3,5 12,8	0,155
Mother Covid 19 (during Delivery) Yes No	14 144	8,8 91,2	13 329	3,8 96,2	0,020
Control prenatal None Less than 6 controls More than 6 controls	6 89 63	3,7 56,3 40	29 190 123	8,5 26,3 65,2	0,147
Newborn	n(158)	%	n(342)	%	P-val
Gender Female Male	67 91	42,4 57,6	155 187	45,3 54,7	0,542
Neonatal perinatal complications Asphyxia   Premature rupture of membranes Intraamniotic infection Post-resuscitation 2 or more None	9 8 10 7 5 119	5,7 5 6,3 4,4 3,1 75,5	10 19 12 10 16 275	3 2,6 3,5 3 4,7 83,2	0,321
Newborn Nutritional Status Appropriate birth weight  Low birth weight (IUGR) Large birth weight	138 4 16	87,3 2,5 10,2	302 10 30	88,3 3 8,7	0,867
Risk for severe neonatal Covid-19   Prematurity   Growth restriction   Low weight   Bronchopulmonary dysplasia   Major malformation   More than 1 risk factor   No risk factors	10 4 4 0 2 20 118	6,3 2,5 2,5 0 1,2 12,6 74,9	15 9 14 1 1 40 269	4,4 2,6 4 0,3 0,3 11,7 76,7	0,660
Neonatal Covid-19 positive Yes No	16 142	10,1 89,9	16 326	4,7 95,3	0,021
Classification of neonatal Covid-19 Mild   Severe Critical No Covid	6 5 5 142	3,8 3,2 3,2 89,9	7  6 3 3260	2 1,8 0,9 95,3	0,106

TABLE 3: Relationship between crude and adjusted ORs from significant variables

** Covid 19 neonatal positive	OR	IC 95%	Adjusted OR	IC95%	P-val
Maternal Vulnerability (SISBÉN A)	1,6	1,13 – 2,39	2,24	1,06 – 4,69	0,033
Colombian Nationality	2,3	1,07 – 5,10	2,22	0,96– 5,11	0,61
Newborn small weight	1,3	0,48 – 3,60	1,45	0,47- 4,50	0,51
Newborn big weight	0,65	0,32 – 1,34	0,22	0,04 – 1,14	0,072
Covid -19 Family Contact	2,83	1,08 – 7,43	2,91	0,86- 9,80	0,83

References: 

1. Needleman JS, Hanson AE. COVID-19-associated apnea and circumoral cyanosis in a 3-week-old. BMC Pediatr. 2020 Aug 12;20(1). 
2. Torres-Torres J, Martinez-Portilla RJ, Espino-y-Sosa S, Estrada-Gutierrez G, Solis- Paredes JM, Villafan-Bernal JR, et al. Comorbidity, poverty and social vulnerability as risk factors for mortality in pregnant women with confirmed SARS-CoV-2 infection: analysis of 13 062 positive pregnancies including 176 maternal deaths in Mexico. Ultrasound in Obstetrics and Gynecology. 2022 Jan 1;59(1):76–82. 
3. Brembilla A, Bernard N, Pujol S, Parmentier AL, Eckman A, Mariet AS, et al. Pregnancy vulnerability in urban areas: a pragmatic approach combining behavioral, medico-obstetrical, socioeconomic, and environmental factors. Sci Rep. 2019 Dec 1;9(1). 
4. Arcos E, Angélica Muñoz L, Sánchez X, Vollrath A, Latorre C, Bonatti C, et al. Vulnerabilidad social en mujeres embarazadas de una comuna de la Región Metropolitana Vulnerability of pregnant women living in a community of Metropolitan Santiago. Vol. 139, Rev Med Chile. 2011. 
5. Lisboa Riquinho D, Gomes Correia S. Mortalidade materna: perfil sócio-demográfico e causal. Vol. 59, Rev Bras Enferm. 2006. 
6. Kaye DK, Kakaire O, Nakimuli A, Mbalinda SN, Osinde MO, Kakande N. Survivors’ understanding of vulnerability and resilience to maternal near-miss obstetric events in Uganda. International Journal of Gynecology and Obstetrics. 2014 Dec 1;127(3):265–8. 
7. Dintrans PV, Maddaleno M, Román YG, Delpiano PV, Castro A, Vance C, et al. Disruption of health services for pregnant women, newborns, children, adolescents, and women during the COVID-19 pandemic: ISLAC 2020 Project. Revista Panamericana de Salud Publica/Pan American Journal of Public Health. 2021;45. 
8. García Hernández GE. Teen pregnancy and poverty, a complex relationship. 2014 DOI: https://doi.org/10.28928/ri/772014/atc1/garciahernandeze 
9. Mirahmadizadeh A, Borazjani R, Ebrahimi M, Haghighi LH, Kamali K, Hamzavi SS, et al. COVID-19 presented with gastrointestinal manifestations in an 11-days-old newborn: A case report and review of the literature. Arc 
10. Livingston E, Bucher K. Coronavirus Disease 2019 (COVID-19) in Italy. JAMA. 2020 Apr 14;323(14):1335. 
11. Fathi M, Vakili K, Deravi N, Yaghoobpoor S, Ahsan E, Mokhtari M, et al. Coronavirus diseases and pregnancy: COVID- 19,SARS, and MERS. Przegl Epidemiol. 2020;74(2):276–89. 
12. Miembros del Grupo de Trabajo de Pediatría Basada en la Evidencia (GT-PBE) que trabajan en el informe de la COVID-19. Marzo2021. Covid-19 en pediatria valoración critica de la evidencia rev ext-5. COVID-19 en Pediatría: valoración crítica de la evidencia. 2021;32–97. 
13. Brini Khalifa I, Hannachi N, Guerrero A, Orth-Höller D, Bhiri S, Bougila J, et al. Demographic and seasonal characteristics of respiratory pathogens in newborns and infants aged 0 to 12 months in the Central-East region of Tunisia. J Med Virol. 2019 Apr 1;91(4):570–81. 
14. Yan K, Xiao FF, Jiang YW, Xiao TT, Zhang DJ, Yuan WH, et al. Effects of SARS-CoV-2 infection on neuroimaging and neurobehavior in newborns. World Journal of Pediatrics. 2021 Apr 1;17(2):171–9. 
15. Vélez M, Acosta-Reyes J, investigador P, Patiño D, Andrea Rami P. Factores clínicos pronósticos de enffermedad grave y mortalidad en pacientes con covid 19. https://es.cochrane.org/sites/es.cochrane.org/files/uploads/COVID-19/udea-uned_sintesisrapida_covid-19_pronostico_22abril2020.pdf 
16. Boly TJ, Reyes-Hernandez ME, Daniels EC, Kibbi N, Bermick JR, Elgin TG. Hyperglycemia and Cytopenias as Signs of SARS-CoV-2 Delta Variant Infection in Preterm Infants. Pediatrics [Internet]. 2022 Mar 3; Available from: https://publications.aap.org/pediatrics/article/doi/10.1542/peds.2021-055331/185249/Hyperglycemia-and-Cytopenias-as-Signs-of-SARS-CoV
17. Portugués-de la Red M del M, Fernández-Pinilla I, Cabrera- Alvargonzález JJ, et al. Differential clinic in children infected by SARS-CoV-2, traceability of contacts and cost-effectiveness of diagnostic tests: Cross-sectional observational study. An Pediatr (Engl Ed). 2021 May 1;94(5):318–26. 
18. 18. Auriti C, de Rose D, Mondì V, Stolfi I, Tzialla C. Neonatal SARS-CoV-2 Infection: Practical Tips. Pathogens [Internet]. 2021 May 17;10(5):611. Available from: https://www.mdpi. com/2076-0817/10/5/611 
19. 19. Pierce-Williams RAM, Burd J, Felder L, Khoury R, Bernstein PS, Avila K, et al. Clinical course of severe and critical coronavirus disease 2019 in hospitalized pregnancies: a United States cohort study. Am J Obstet Gynecol MFM. 2020 Aug 1;2(3):100134. 
20. Godleski SA, Harris CT, Fitzpatrick KM, Kothari A. Social and behavioral vulnerability, pregnancy, and negative mental health outcomes in the U.S. during the COVID-19 pandemic. AIMS Public Health. 2022;9(2):331–41. 
21. Ozores A, González-Durán ML, Novoa-Carballal R, Portugués-de la Red M del M, Fernández-Pinilla I, Cabrera- Alvargonzález JJ, et al. Differential clinic in children infected by SARS-CoV-2, traceability of contacts and cost-effectiveness of diagnostic tests: Cross-sectional observational study. An Pediatr (Engl Ed). 2021 May 1;94(5):318–26. 
22. DeBiasi RL, Song X, Delaney M, Bell M, Smith K, Pershad J, et al. Severe Coronavirus Disease-2019 in Children and Young Adults in the Washington, DC, Metropolitan Region. Journal of Pediatrics. 2020 Aug 1;223:199-203.e1. 
23. Cen Y, Chen X, Shen Y, Zhang XH, Lei Y, Xu C, et al. Risk factors for disease progression in patients with mild to moderate coronavirus disease 2019—a multi-centre observational study. Clinical Microbiology and Infection. 2020 Sep 1;26(9):1242–7. 
24. 24. Jang JG, Hur J, Choi EY, Hong KS, Lee W, Ahn JH. Prognostic factors for severe coronavirus disease 2019 in daegu, Korea. J Korean Med Sci. 2020 Jun 1;35(23). 
25. Torres JP, Izquierdo G, Acuña M, Pavez D, Reyes F, Fritis A, et al. Multisystem inflammatory syndrome in children (MIS-C): Report of the clinical and epidemiological characteristics of cases in Santiago de Chile during the SARS-CoV-2 pandemic. International Journal of Infectious Diseases. 2020 Nov 1;100:75–81. 
26. KC A, Gurung R, Kinney M v., Sunny AK, Moinuddin M, Basnet O, et al. Effect of the COVID-19 pandemic response on intrapartum care, stillbirth, and neonatal mortality outcomes in Nepal: a prospective observational study. Lancet Glob Health. 2020 Oct 1;8(10):e1273–81. 
27. Dintrans PV, Maddaleno M, Román YG, Delpiano PV, Castro A, Vance C, et al. Disruption of health services for pregnant women, newborns, children, adolescents, and women during the COVID-19 pandemic: ISLAC 2020 Project. Revista Panamericana de Salud Publica/Pan American Journal of Public Health. 2021;45. 
28. Fernandez-Niño Julian Alfredo. Recommendations for the response against COVID- 19 in migratory contexts under a closed border: The case of Colombia. Biomédica 2020;40(Supl2):68-72. https://doi.org/107705/biomedica5512. 
29. Basile Ibrahim B, Interrante JD, Fritz AH, Tuttle MS, Kozhimannil KB. Inequities in Availability of Evidence-Based Birth Supports to Improve Perinatal Health for Socially Vulnerable Rural Residents. Children. 2022 Jul 1;9(7). 
30. Yee CW, Cunningham SD, Ickovics JR. Application of the Social Vulnerability Index for Identifying Teen Pregnancy Intervention Need in the United States. Matern Child Health J. 2019 Nov 1;23(11):1516–24. 
31. Oliveira AA de, Almeida MF de, Silva ZP da, Assunção PL de, Silva AMR, Santos HG dos, et al. Fatores associados ao nascimento pré-termo: da regressão logística à modelagem com equações estruturais. Cad Saude Publica. 2019;35(1). 
32. Brygger Venø L, Pedersen LB, Søndergaard J, Ertmann RK, Jarbøl DE. Assessing and addressing vulnerability in pregnancy: General practitioners perceived barriers and facilitators – a qualitative interview study. BMC Primary Care. 2022;23(1). 
33. Songco A, Minihan S, Fox E, Ladouceur C, Mewton L, Moulds M, et al. Social and cognitive vulnerability to COVID-19-related stress in pregnancy: A case-matched-control study of antenatal mental health. J Affect Disord. 2023;325. 
34. Mark EG, Golden WC, Gilmore MM, Sick-Samuels A, Curless MS, Nogee LM, et al. Community-Onset Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Young Infants: A Systematic Review. Journal of Pediatrics. 2021 Jan 1;228:94-100.e3. 
35. Xiao T, Xia S, Zeng L, Lin G, Wei Q, Zhou W, et al. A multicentre observational study on newborns exposed to SARS-CoV-2 in China: The Neo-SARS-CoV-2 Study protocol. BMJ Open. 2020 Jul 22;10(7). 
36. Gagneur A, Vallet S, Talbot PJ, Legrand-Quillien MC, Picard B, Payan C, et al. Outbreaks of human coronavirus in a paediatric and neonatal intensive care unit. Eur J Pediatr. 2008 Dec;167(12):1427–34. 
37. Singh T, Heston SM, Langel SN, Blasi M, Hurst JH, Fouda GG, Kelly MS, Permar SR. Lessons From COVID-19 in Children: Key Hypotheses to Guide Preventative and Therapeutic Strategies. Clin Infect Dis. 2020 Nov 5;71(8):2006- 2013. doi: 10.1093/cid/ciaa547. PMID: 32382748; PMCID: PMC7239258. 
38. King JA, Whitten TA, Bakal JA, McAlister FA. Symptoms associated with a positive result for a swab for SARS-CoV-2 infection among children in Alberta. CMAJ. 2021 Jan 4;193(1):E1–9. 
39. Xiao T, Xia S, Zeng L, Lin G, Wei Q, Zhou W, et al. A multicentre observational study on newborns exposed to SARS-CoV-2 in China: The Neo-SARS-CoV-2 Study protocol. BMJ Open. 2020 Jul 22;10(7). 
40. Needleman Karabay M, Çınar N, Karakaya Suzan Ö, Yalnızoğlu Çaka S, Karabay O. Clinical characteristics of confirmed COVID-19 in newborns: a systematic review. Journal of Maternal-Fetal and Neonatal Medicine. Taylor and Francis Ltd.; 2020. 
41. Kamali Aghdam M, Jafari N, Eftekhari K. Novel coronavirus in a 15-day-old newborn with clinical signs of sepsis, a case report. Infect Dis. 2020 Jun 2;52(6):427–9. 
42. Jin W, Dan W, Guo-Ce C, Xu-Wei T, Ling-Kong Z. SARS-CoV-2 infection with gastrointestinal symptoms as the first manifestation in a newborn. Vol. 22, Chinese Journal of Contemporary Pediatrics. Xiangya Hospital of CSU; 2020. p. 211–4. 
43. Baquero H, Venegas ME, Velandia L, Neira F, Navarro E. Neonatal late-onset infection with SARS CoV-2. Biomedica. 2020;40:44–9. 
44. Gale C, Quigley MA, Placzek A, Knight M, Ladhani S, Draper ES, et al. Characteristics and outcomes of neonatal SARS-CoV-2 infection in the UK: a prospective national cohort study using active surveillance. Lancet Child Adolesc Health. 2021 Feb 1;5(2):113–21. 
45. Metz TD, Clifton RG, Hughes BL, Sandoval GJ, Grobman WA, Saade GR, et al. Association of SARS-CoV-2 Infection with Serious Maternal Morbidity and Mortality from Obstetric Complications. JAMA – Journal of the American Medical Association. 2022; 
46. Sola A, Rodríguez S, Cardetti M, Dávila C. Perinatal COVID-19 in Latin America. Revista Panamericana de Salud Publica/Pan American Journal of Public Health. 2020;44(1). 
47. Duran P, Berman S, Niermeyer S, Jaenisch T, Forster T, Ponce de Leon RG, et al. COVID-19 and newborn health: Systematic review. Vol. 44, Revista Panamericana de Salud Publica/Pan American Journal of Public Health. Pan American Health Organization; 2020. 
48. Antúnez-Montes OY, Escamilla MI, Figueroa-Uribe AF, Arteaga-Menchaca E, Lavariega-Saráchaga M, Salcedo- Lozada P, et al. COVID-19 and Multisystem Inflammatory Syndrome in Latin American Children: A Multinational Study. Pediatric Infectious Disease Journal. 2020; 
49. García-Salido A, Leoz-Gordillo I, Martínez De Azagra-Garde A, Nieto-Moro M, Iglesias- Bouzas MI, García-Teresa MÁ, et al. Children in Critical Care Due to Severe Acute Respiratory Syndrome Coronavirus 2 Infection: Experience in a Spanish Hospital. Pediatric Critical Care Medicine. 2020 Aug 1;21(8):E576–80. 
50. Charki S, Skalyanshettar S. Case Report Open Access Arterial Thrombosis and Gangrene in a Newborn with COVID-19: A Case Report. Iranian Journal of Neonatology. 2021 Apr: 12(2). DOI: 10.22038/ijn.2021.52842.1948. 
51. Kaushik S, Aydin SI, Derespina KR, Bansal PB, Kowalsky S, Trachtman R, et al. Multisystem Inflammatory Syndrome in Children Associated with Severe Acute Respiratory Syndrome Coronavirus 2 Infection (MIS-C): A Multi-institutional Study from New York City. Journal of Pediatrics. 2020 Sep 1;224:24–9. 
52. de Rose DU, Auriti C, Landolfo F, Capolupo I, Salvatori G, Ranno S, et al. Reshaping neonatal intensive care units (NICUs) to avoid the spread of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) to high-risk infants. Vol. 42, Infection Control and Hospital Epidemiology. Cambridge University Press; 2021. p. 632–3. 
53. Mullins E, Hudak ML, Banerjee J, Getzlaff T, Townson J, Barnette K, et al. Pregnancy and neonatal outcomes of COVID-19: coreporting of common outcomes from PAN- COVID and AAP-SONPM registries. Ultrasound in Obstetrics and Gynecology. 2021 Apr 1;57(4):573–81. 
54. de Farias ECF, Piva JP, de Mello MLFMF, do Nascimento LMPP, Costa CC, Machado MMM, et al. Multisystem inflammatory syndrome associated with coronavirus disease in children: A multi-centered study in Belém, Pará, Brazil. Pediatric Infectious Disease Journal. 2020;E374–6. 
55. Mithal LB, Machut KZ, Muller WJ, Kociolek LK. SARS-CoV-2 Infection in Infants Less than 90 Days Old. Journal of Pediatrics. 2020 Sep 1;224:150–2. 
56. Farghaly MAA, Kupferman F, Castillo F, Kim RM. Characteristics of Newborns Born to SARS-CoV-2-Positive Mothers: A Retrospective Cohort Study. Am J Perinatol. 2020 Nov 1;37(13):1310–6. 
57. Solís-García G, Gutiérrez-Vélez A, Pescador Chamorro I, Zamora-Flores E, Vigil- Vázquez S, Rodríguez-Corrales E, et al. Epidemiology, management, and risk of SARS- CoV-2 transmission in a cohort of newborns born to mothers diagnosed with COVID-19 infection. An Pediatr (Engl Ed). 2021 Mar 1;94(3):173–8. 
58. 58. Salvatore CM, Han JY, Acker KP, Tiwari P, Jin J, Brandler M, et al. Neonatal management, and outcomes during the COVID-19 pandemic: an observation cohort study. Lancet Child Adolesc Health. 2020 Oct 1;4(10):721–7. 
59. Consenso colombiano de atención, diagnóstico y manejo de la infección por SARS-COV- 2/COVID-19 en establecimientos de atención de la salud: recomendaciones basadas en consenso de expertos e informadas en la evidencia acin-iets. https://revistainfectio.org/P_OJS/index.php/infectio/issue/view/101 
60. https://www.aap.org/en/pages/2019-novel-coronavirus-COVID-19-infections/clinical-guidance/faqs-management-of-infants-born-to-COVID-19-mothers/ 
61. Ludvigsson JF. Systematic review of COVID-19 in children shows milder cases and a better prognosis than adults. Vol. 109, Acta Paediatrica, International Journal of Paediatrics. Blackwell Publishing Ltd; 2020. p. 1088–95. 
62. Reinders S, Alva A, Huicho L, Blas MM. Indigenous communities’ responses to the COVID-19 pandemic and consequences for maternal and neonatal health in remote Peruvian Amazon: A qualitative study based on routine programme supervision. BMJ Open. 2020 Dec 29;10(12). 
63. Stern C. Vulnerabilidad social y embarazo adolescente en México. https://www.redalyc.org/articulo.oa?id=11203906 
64. Ferreira RA, Ferriani M das GC, de Mello DF, de Carvalho IP, Cano MA, de Oliveira LA. Análise espacial da vulnerabilidade social da gravidez na adolescência. Cad Saude Publica. 2012;28(2). 

Disclosure: The authors have no conflicts of interests to disclose.