Rev Bras Enferm reben Revista Brasileira de Enfermagem Rev. Bras. Enferm. 0034-7167 1984-0446 Associação Brasileira de Enfermagem 6ssmqbFmc99fM36vSqvdDJw S0034-71672025001300167 10.1590/0034-7167-2025-0196 00167 ORIGINAL ARTICLE Maternal and neonatal factors associated with exclusive breastfeeding upon hospital discharge Fatores maternos e neonatais associados ao aleitamento materno exclusivo na alta hospitalar 0000-0003-2804-2504 Toapanta-Pinta Paola Cristina read approved the published version of the manuscript analyzed the data wrote the manuscript contributed to study design performed data acquisition coding and storage I 0009-0004-0920-9203 Cóndor Adriana Paola Sinchiguano read approved the published version of the manuscript analyzed the data wrote the manuscript II 0009-0009-9012-6419 Defaz Deicy Maribel Muso read approved the published version of the manuscript analyzed the data wrote the manuscript II 0009-0009-7612-4927 Landeta Angélica Oliva Gualavisí read approved the published version of the manuscript analyzed the data wrote the manuscript II 0009-0005-9750-8752 Cadena Blanca Llilman Parra read approved the published version of the manuscript analyzed the data wrote the manuscript II 0000-0002-1370-9700 Vasco-Morales Santiago read approved the published version of the manuscript analyzed the data wrote the manuscript contributed to study design performed data acquisition coding and storage I II Universidad Central del Ecuador Facultad de Ciencias Médicas Quito Pichincha Ecuador Universidad Central del Ecuador, Facultad de Ciencias Médicas. Quito, Pichincha, Ecuador Hospital Gineco-Obstétrico Isidro Ayora Quito Pichincha Ecuador Hospital Gineco-Obstétrico Isidro Ayora. Quito, Pichincha, Ecuador

Antonio José de Almeida Filho

Waldemar Brandão Neto

 Corresponding author: Paola Cristina Toapanta-Pinta , E-mail: ptoapanta@uce.edu.ec 12 12 2025 2025 78 suppl 4 e20250196 14 05 2025 24 08 2025 This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT Objective:

to identify maternal and neonatal factors associated with exclusive breastfeeding at hospital discharge from a tertiary care hospital.

 Methods:

a cross-sectional study using secondary data from 22,136 records of newborns hospitalized in a neonatal unit (2009-2022). Maternal and neonatal variables and feeding practices at discharge were analyzed. Bayesian logistic regression models were applied.

 Results:

exclusive breastfeeding at hospital discharge was 91.55%. Negatively associated factors were cesarean delivery (OR: 0.90), illicit substance use (OR: 0.30), low birth weight (OR: 0.84), and cleft lip and palate (OR: 0.15). Breastfeeding counseling and labor and delivery support promoted exclusive breastfeeding at hospital discharge.

 Conclusion:

despite the high prevalence of exclusive breastfeeding at hospital discharge, barriers persist that must be addressed through promotion strategies, staff training, and support for mothers at risk.

 RESUMO Objetivo:

identificar fatores maternos e neonatais associados ao aleitamento materno exclusivo na alta hospitalar de um hospital terciário.

 Métodos:

estudo transversal com dados secundários de 22.136 prontuários de recém-nascidos internados na unidade neonatal (2009-2022). Foram analisadas variáveis maternas e neonatais e práticas de alimentação na alta. Modelos de regressão logística bayesiana foram aplicados.

 Resultados:

o aleitamento materno exclusivo na alta hospitalar foi de 91,55%. Os fatores negativamente associados foram parto cesáreo (OR: 0,90), uso de substâncias ilícitas (OR: 0,30), baixo peso ao nascer (OR: 0,84) e fissura labiopalatina (OR: 0,15). O aconselhamento sobre amamentação e o apoio ao trabalho de parto e parto promoveram o aleitamento materno exclusivo na alta hospitalar.

 Conclusão:

apesar da alta prevalência de aleitamento materno exclusivo na alta hospitalar, persistem barreiras que devem ser superadas por meio de estratégias de promoção, treinamento da equipe e apoio às mães em risco.

 Descriptors: Breast Feeding Risk Factors Infant Newborn Maternal Behavior Maternal and Child Health. Descritores: Aleitamento Materno Fatores de Risco Recém-Nascido Comportamento Materno Saúde Materno-Infantil. INTRODUCTION

Exclusive breastfeeding (EBF) is recognized worldwide as the optimal method for ensuring adequate nutrition during the first months of life, promoting healthy growth and development. It also provides maternal health benefits, such as reducing the risk of postpartum hemorrhage and long-term metabolic diseases. In this context, the World Health Organization (WHO) recommends EBF during the first six months of life due to its multiple advantages, such as reducing respiratory and gastrointestinal infections, strengthening cognitive development, and promoting mother-child bonding(1,2).

Despite strong scientific evidence supporting these recommendations, exclusive breastfeeding at hospital discharge (EBHD) rates remain suboptimal in many regions. Factors such as limited access to health services, a lack of effective public policies, and the marketing of infant formulas hinder EBF(1,3,4).

The Hospital Gineco-Obstétrico Isidro Ayora (HGOIA) is a national reference institution in Ecuador. For several years, it has implemented the WHO’s Baby-Friendly Hospital Initiative (BFHI)(5) and complies with the national regulations for Mother and Child Friendly Health Establishments (In Spanish, Establecimientos de Salud Amigos de la Madre y del Niño - ESAMyN)(6). However, in Ecuador, there is a research gap on the factors that hinder the EBHD of newborns hospitalized in the neonatal area.

 OBJECTIVE

To identify maternal and neonatal factors associated with EBHD in a tertiary care hospital.

 METHODS Ethical considerations

The Universidad Central del Ecuador Research Ethics Committee approved the study. Informed consent was not required because anonymized secondary data were used.

 Study design and population

A cross-sectional study was conducted based on secondary data from the HGOIA’s Perinatal Information System, a tertiary care hospital and national referral center located in Quito, Ecuador. A total of 22,136 records of mothers and newborns hospitalized in the neonatal unit between January 2009 and December 2022 were analyzed. Variables included maternal and neonatal data as well as feeding practices upon discharge.

This study was reported according to the EQUATOR network guidelines, using the Strengthening the reporting of observational studies in epidemiology guideline(7).

 Inclusion and exclusion criteria

Records of newborns hospitalized in the HGOIA’s neonatal unit and associated information on their mothers were included. Cases with at least one of the following criteria were excluded: newborns transferred to another institution; neonatal death before hospital discharge; mothers with HIV infection; newborns with metabolic diseases that contraindicate breastfeeding (e.g., galactosemia, phenylketonuria); maternal death during hospitalization; incomplete data on key variables (10% missing values for feeding variables at hospital discharge, gestational age, type of delivery, or illicit substance use during pregnancy).

 Variables analyzed

The variable of interest was “diet at hospital discharge”. Maternal variables were analyzed, including sociodemographic characteristics (age, ethnicity, educational level, marital status), obstetric factors (previous pregnancies, pregnancy planning, prenatal visits, breastfeeding counseling, gestational hypertensive disorders, violence during pregnancy, and alcohol, tobacco, and illicit substance use during pregnancy), and childbith aspects (support, delivery route, and general anesthesia). Neonatal variables included sex, gestational age, weight-for-gestational age classification, Apgar scores, multiple pregnancy, and congenital defects (e.g., cleft lip and palate). For statistical analysis, variables were organized into dichotomous or polytomous categories, depending on their nature. Weight-for-gestational age was classified using the Fenton calculator(8).

 Statistical analysis

Absolute and relative frequencies were calculated for sociodemographic, obstetric, neonatal, and delivery variables. A Bayesian approach was used for bivariate and multivariate analyses. This method was selected for its ability to handle unbalanced data and small sample sizes, providing more robust and flexible estimates and minimizing the biases often present in frequentist approaches(9).

The “feeding at hospital discharge” variable was classified into three categories: a) EBF: for newborns fed exclusively with breast milk; b) Partial feeding: for those discharged with breast milk supplemented with formula; c) Artificial feeding: for newborns fed exclusively with formula at discharge. Bayesian analogues were applied to the contingency tables, as well as to the simple and multiple binary logistic regression models, using uninformative priors. For the posterior distribution, 1,000 iterations of the Markov Chain Monte Carlo algorithm were run. The Bayes Factor (BF) was used to assess the evidence between the null and alternative hypotheses (BF > 1 supported the alternative hypothesis; BF < 1 favored the null hypothesis). This probabilistic approach allowed for a more flexible interpretation of the associations between variables and EBF at hospital discharge.

To calculate the Bayesian logistic regression models, the variable of interest was recategorized as dichotomous (EBF (yes/no)). Simple and multiple logistic regression coefficients were estimated, which, when exponentiated, generated unadjusted and adjusted Odds Ratios (ORs) with 95% credibility intervals. The results were interpreted in terms of the posterior probability, which allowed a more precise assessment of the uncertainty associated with the estimates. The analysis was performed using the JASP v0.14.3(10) statistical software, and the trend graph was generated using the R programming language(11).

 RESULTS

During the study period, 26,236 newborns hospitalized in the HGOIA’s neonatal unit were registered. Four thousand one hundred records (15.62%) were excluded for not meeting inclusion criteria: 394 (1.50%) due to transfer to other health institutions; 1,744 (6.64%) due to death before hospital discharge; 118 (0.44%) due to maternal HIV infection; 43 (0.16%) due to maternal death; 11 (0.04%) due to metabolic diseases; and 1,700 (6.47%) due to incomplete data. The final analysis included 22,136 records.

The prevalence of EBHD was 91.55% (N=20,266). Moreover, 6.29% of newborns received partial feeding, while 2.16% received artificial feeding.

The trend analysis (Figure 1) shows a progressive increase in the proportion of newborns with EBHD, especially since 2016.

Exclusive breastfeeding trend at the <italic>Hospital Gineco-Obstétrico Isidro Ayora</italic>, Quito, Ecuador (2009-2022)

Characteristics of the study population and comparison of groups with and without exclusive breastfeeding at hospital discharge

Table 1 includes sociodemographic variables, obstetric factors, and birth factors. Most mothers were aged 20 to 29 years, had a secondary education, and were in a stable relationship. A higher frequency of EBHD was observed in mothers with a higher educational level and no history of substance use. Regarding birth characteristics, a higher proportion of EBHD was identified in mothers who delivered vaginally and received breastfeeding counseling during prenatal care.

Maternal and pregnancy course characteristics of the study population and comparison according to the type of feeding at hospital discharge. <italic>Hospital Gineco-Obstétrico Isidro Ayora</italic>, Quito, Ecuador
Variable Total population Comparison of groups
Exclusive breastfeeding Partial Artificial BF10
n (%) n (%) n (%) n (%)
Sociodemographic characteristics
Maternal age
Under 20 5,712 (25.80) 5,306 (26.18) 319 (22.92) 87 (18.20) 2.90 × 10-5
20 to 29 10,280 (46.44) 9,354 (46.16) 689 (49.50) 237 (49.58)
30 to 39 5,345 (24.15) 4,866 (24.01) 336 (24.14) 143 (29.92)
40 or older 799 (3.61) 740 (3.65) 48 (3.45) 11 (2.30)
Ethnicity
White 158 (0.71) 146 (0.72) 4 (0.29) 8 (1.67) 0.4
Indigenous 458 (2.07) 419 (2.07) 25 (1.80) 14 (2.93)
Mixed-race 2,0734 (93.67) 19,004 (93.77) 1,306 (93.82) 424 (88.70)
Black 439 (1.98) 368 (1.82) 46 (3.30) 25 (5.23)
Other 347 (1.57) 329 (1.62) 11 (0.79) 7 (1.46)
Educational level
None 303 (1.37) 261 (1.29) 32 (2.30) 10 (2.09) 925.42
Primary 4,944 (22.33) 4,410 (21.76) 381 (27.37) 153 (32.01)
Secondary 13,396 (60.52) 12,377 (61.07) 765 (54.96) 254 (53.14)
University 3,493 (15.78) 3,218 (15.88) 214 (15.37) 61 (12.76)
Marital status
Without a stable partner 5,792 (26.17) 5,363 (26.46) 321 (23.06) 108 (22.59) 0.03
With a stable partner 16,344 (73.83) 14,903 (73.54) 1,071 (76.94) 370 (77.41)
Obstetric factors
Previous gestations
Yes 13,388 (60.48) 12,160 (60.00) 876 (62.93) 352 (73.64) 99.127.88
No 8,748 (39.52) 8,106 (40.00) 516 (37.07) 126 (26.36)
Planned pregnancy
Yes 7,110 (32.12%) 6,466 (31.91%) 501 (35.99%) 143 (29.92%) 0.02
No 15,026 (67.88%) 13,800 (68.09%) 891 (64.01%) 335 (70.08%)
Prenatal care consultations
1 to 4 4,661 (21.06%) 98 (20.50%) 4,212 (20.78%) 351 (25.22%) 3.16x1013
5 to 7 9,238 (41.73%) 181 (37.87%) 8,485 (41.87%) 572 (41.09%)
8 and more 7,323 (33.08%) 153 (32.01%) 6,774 (33.43%) 396 (28.45%)
None 914 (4.13%) 46 (9.62%) 795 (3.92%) 73 (5.24%)
Breastfeeding counseling
Yes 10,091 (45.59%) 229 (47.91%) 9,366 (46.22%) 496 (35.63%) 36.14
No 12,045 (54.41%) 249 (52.09%) 10,900 (53.78%) 896 (64.37%)
Hypertensive disorders
Yes 1,028 (4.64%) 858 (4.23%) 135 (9.70%) 35 (7.32%) 10.19
No 21,108 (95.36%) 19,408 (95.77%) 1,257 (90.30%) 443 (92.68%)
Violence during pregnancy
Yes 359 (1.62%) 311 (1.53%) 29 (2.08%) 19 (3.97%) 1.33x109
No 21,777 (98.38%) 19,955 (98.47%) 1,363 (97.92%) 459 (96.03%)
Alcohol consumption
Yes 614 (2.77%) 540 (2.66%) 44 (3.16%) 30 (6.28%) 1.5
No 21,522 (97.23%) 19,726 (97.34%) 1,348 (96.84%) 448 (93.72%)
Illicit substance consumption
Yes 131 (0.59%) 93 (0.46%) 14 (1.01%) 24 (5.02%) 5.02x103
No 22,005 (99.41%) 20,173 (99.54%) 1,378 (98.99%) 454 (94.98%)
Tobacco smoke consumption/exposure
Si 1,328 (5.99%) 1,169 (5.77) 111 (7.97) 48 (10.04) 9.99x1022
No 20,808 (94.01%) 19,097 (94.23%) 1,281 (92.03%) 430 (89.96%)
Factors related to childbirth
Birth route
Caesarean section 11,925 (53.87%) 10,847 (53.52%) 704 (50.57%) 374 (78.24%) 9.99E+22
Vaginal 10,211 (46.13%) 9,419 (46.48%) 688 (49.43%) 104 (21.76%)
Birth companion
Yes 6,834 (30.87%) 6,369 (31.43%) 345 (24.78%) 120 (25.1%) 3.05
No 15,302 (69.13%) 13,897 (68.57%) 1,047 (75.22%) 358 (74.9%)
General anesthesia
Yes 723 (3.27%) 30 (6.28%) 636 (3.14%) 57 (4.09%) 3.03x1013
No 21,413 (96.73%) 448 (93.72%) 19,630 (96.86%) 1,335 (95.91%)
Legend: BF10: Bayes Factor.

Table 2 presents the distribution of neonatal characteristics in the study population, categorized according to the type of feeding at hospital discharge. Prematurity, low birth weight for gestational age, and the presence of congenital malformations were more common in infants who received partial or artificial feeding.

Comparison of neonatal characteristics between exclusively breastfed and non-exclusively breastfed newborns at hospital discharge. <italic>Hospital Gineco-Obstétrico Isidro Ayora</italic>, Quito, Ecuador
Variable Total population Comparison of groups
Exclusive breastfeeding Partial Artificial BF10
n (%) n (%) n (%) n (%)
Condition at birth
Sex
Female 10,111 (45.68) 9,279 (45.79) 613 (44.04) 219 (45.82) 3.6 × 10-5
Male 12,023 (54.31) 10,985 (54.2) 779 (55.96) 259 (54.18)
Not defined 2 (0.01) 2 (0.01) 0 (0.0) 0 (0.0)
Gestational age
Premature 8,043 (36.33) 7,254 (35.79) 606 (43.53) 183 (38.28) 151,25
Break up 13,964 (63.08) 12,900 (63.65) 775 (55.68) 289 (60.46)
Post-break up 129 (0.58) 112 (0.55) 11 (0.79) 6 (1.26)
Weight for gestational age
Low 6,717 (30.34) 6,058 (29.89) 471 (33.84) 188 (39.33) 1.873,99
Adequate 14,013 (63.30) 12,918 (63.74) 814 (58.48) 281 (58.79)
High 1,406 (6.35) 1,290 (6.37) 107 (7.69) 9 (1.88)
1-minute Apgar
>7 18,576 (83.92) 17,033 (84.05) 1,120 (80.46) 423 (88.49) 3,1
<7 3,560 (16.08) 3,233 (15.95) 272 (19.54) 55 (11.51)
5-minute Apgar
>7 21,575 (97.47) 19,777 (97.59) 1,331 (95.62) 467 (97.70) 5,34
<7 561 (2.53) 489 (2.41) 61 (4.38) 11 (2.30)
Multiple pregnancy product
Yes 1,720 (3.89) 1,510 (3.73) 174 (6.25) 36 (3.77) 1.76x10-5
No 20,416 (46.11) 18,756 (46.27) 1,218 (43.75) 442 (46.23)
Congenital anomalies
Type of defect
Major 1,379 (6.23) 1,257 (6.20) 85 (6.11) 37 (7.74) 1.3 × 10-4
Minor 938 (4.24) 838 (4.14) 84 (6.03) 16 (3.35)
None 19,819 (89.53) 18,171 (89.66) 1,223 (87.86) 425 (88.91)
Cleft lip and palate
Yes 184 (0.83) 116 (0.57) 45 (3.23) 23 (4.81) 4,22x1023
No 2,1952 (99.17) 20,150 (99.43) 1,347 (96.77) 455 (95.19)
Cardiopulmonary malformations
Yes 480 (2.17) 446 (2.20) 23 (1.65) 11 (2.30) 2.39 × 10-3
No 21,656 (97.83) 19,820 (97.80) 1,369 (98.35) 467 (97.70)
Musculoskeletal malformations
Yes 326 (1.47) 302 (1.49) 19 (1.36) 5 (1.05) 1.72 × 10-3
No 21,810 (98.53) 19,964 (98.51) 1,373 (98.64) 473 (98.95)
Gastrointestinal malformations
No 22,029 (99.52) 20,172 (99.54) 1,383 (99.35) 474 (99.16) 0,02
Yes 107 (0.48) 94 (0.46) 9 (0.65) 4 (0.84)
Nervous system malformations
Yes 615 (2.78) 566 (2.79) 40 (2.87) 9 (1.88) 1.44 × 10-3
No 21,521 (97.22) 19,700 (97.21) 1,352 (97.13) 469 (98.12)
Urogenital malformations
Yes 239 (1.08) 217 (1.07) 19 (1.36) 3 (0.63) 4.6 × 10-3
No 21,897 (98.92) 20,049 (98.93) 1,373 (98.64) 475 (99.37)
Integumentary malformations
Yes 117 (0.53) 108 (0.53) 8 (0.57) 1 (0.21) 5.05 × 10-3
No 22,019 (99.47) 20,158 (99.47) 1,384 (99.43) 477 (99.79)
Legend: >7: less than; ≥: equal to or greater than; BF10: Bayes Factor. Factors associated with exclusive breastfeeding upon hospital discharge

Table 3 shows the results of the logistic regression analysis assessing maternal and neonatal factors associated with BDHD. For this analysis, the “feeding at hospital discharge” variable was recoded as dichotomous (yes/no). Bayesian models estimated odds ratios (crude and adjusted ORs) with their respective 95% Credible Intervals.

Maternal and neonatal factors associated with exclusive breastfeeding at hospital discharge. <italic>Hospital Gineco-Obstétrico Isidro Ayora</italic>, Quito, Ecuador
Variable Unadjusted OR Adjusted OR
Maternal factors
Low educational level 0.68 (0.61 - 0.74) 0.74 (0.66 - 0.82)
Previous pregnancies 0.79 (0.72 - 0.87) 0.97 (0.81 - 1.05)
Alcohol use 0.73 (0.58 - 1.00) 0.94 (0.72 - 1.25)
Illegal substance use 0.23 (0.16 - 0.34) 0.30 (0.20 - 0.46)
Tobacco use/exposure 0.68 (0.57 - 0.80) 0.76 (0.63 - 0.92)
Exposure to violence 0.66 (0.50 - 1.00) 0.83 (0.59 - 1.14)
Prenatal visits ≥5 1.31 (1.17 - 1.43) 1.16 (1.04 - 1.30)
Breastfeeding counseling 1.34 (1.22 - 1.48) 1.28 (1.16 - 1.42)
Hypertensive disorders during pregnancy 0.45 (0.38 - 0.53) 0.39 (0.33 - 0.47)
Partner during labor 1.36 (1.22 - 1.52) 1.38 (1.23 - 1.54)
Cesarean delivery 0.87 (0.78 - 0.95) 0.9 (0.81 - 0.99)
Use of general anesthesia 0.71 (0.59 - 1.00) 0.76 (0.60 - 0.96)
Neonatal factors
Multiple pregnancy 0.65 (0.55 - 0.74) 0.70 (0.60 - 0.84)
1-minute Apgar score <7 0.97 (0.86 - 1.02) 1.01 (0.88 - 1.15)
5-minute Apgar score <7 0.66 (0.51 - 0.87) 0.66 (0.50 - 0.87)
Prematurity 0.77 (0.70 - 0.85) 0.90 (0.82 - 1.01)
Low weight 0.79 (0.73 - 0.88) 0.84 (0.76 - 0.94)
Cleft lip and palate 0.16 (0.12 - 0.21) 0.15 (0.11 - 0.21)
Legend: <: less than; >: greater than; OR: Odds Ratio. DISCUSSION

The frequency of EBHD in the present study was 91.55%, similar to that reported by Zimmerman et al. in the United States, where 91.8% of mothers initiated EBF during their hospital stay(12). However, this proportion differs from that observed in other regions such as Japan, where Yasuda et al.(13) documented a prevalence of 66.4%, attributing these results to the lack of support from doulas or midwives. In Turkey, Çelik et al.(14) reported 87.6% of newborns discharged with EBF.

Furthermore, 8.45% of newborns did not receive EBHD. Multivariate analysis identified several factors negatively associated with EBHD, such as low maternal educational level, illicit substance or tobacco use during pregnancy, hypertensive disorders, cesarean section, general anesthesia, being a multiple pregnancy, 5-minute Apgar score <7, low birth weight for gestational age, and cleft lip and palate. In contrast, a higher number of prenatal checkups, breastfeeding counseling, and labor and delivery assistance were positively associated with EBHD.

In this study, an increase in EBHD rates was observed, going from 89.71% in 2009 to 93.32% in 2016 and 92.96% in 2022. As a maternal and child hospital, HGOIA follows international regulations, such as the BFHI(5), and national regulations, such as ESAMyN(6), promoting EBF through early initiation, proper use of breast milk substitutes and comprehensive training of health personnel.

Low education showed a negative association with EBHD, coinciding with a study conducted in Cape Verde, where mothers with secondary education or higher were 1.55 times more likely to breastfeed than those with basic education(15).

In this study, illicit substance and tobacco use during pregnancy was negatively associated with EBHD. Local regulations advise against breastfeeding in abstinent mothers while they receive multidisciplinary care, prioritizing their recovery and neonatal well-being(16). Bremer and Knippen reported that opioid exposure before or during pregnancy reduces the likelihood of initiating EBF during hospitalization(17). In the United States, Chang et al. identified that 16 of 110 hospitals restrict breastfeeding in mothers with positive cannabinoid results(18).

Beyond hospital policies, substance-using mothers also show lower intentions to breastfeed. Jawale et al. observed this trend in women who use marijuana(19). Similarly, smoking during pregnancy and the postpartum period decreases the likelihood of continuing EBF by 51%, according to a study in Sydney, Australia(20). An analysis of the CDC’s Pregnancy Risk Assessment Monitoring System (2016-2018) revealed that combined use of tobacco and illicit substances significantly reduces the likelihood of initiating EBF (aOR: 0.58; 95% CI: 0.39-0.87)(21).

Hypertensive disorders during pregnancy were negatively associated with EBHD. A Canadian study found that these conditions affect the initiation and continuation of breastfeeding(22).

Cesarean section and the use of general anesthesia were negatively associated with EBHD. A cross-sectional study by Pohol et al.(23) in Israel found that, in Jewish women of Ethiopian origin, cesarean section reduced EBHD (OR: 0.481; 95% CI: 0.232-0.998). Similarly, Alchalel et al.(24) determined that cesarean section reduced the likelihood of EBHD (OR: 0.64; 95% CI: 0.44-0.94; p = 0.023) in hospitals in Haifa and Netanya.

Furthermore, general anesthesia delays skin-to-skin contact, affecting maternal receptivity immediately after surgery. Initiating breastfeeding within the first hour is crucial for the success of EBHD(25).

In this study, being a product of multiple pregnancies was negatively associated with EBHD, likely due to difficulties in timing, organization, and breastfeeding technique. A study in Japan compared EBF among singletons, twins, and triplets, finding a lower prevalence in multiple births. Only 4.1% of twins and triplets received EBF compared to 44.7% of singletons. Furthermore, mothers of twins or triplets were 2.44 times more likely to opt for exclusive formula feeding(26).

A low 5-minute Apgar score was negatively associated with HDB. Herrera Gómez et al.(27) found that newborns with a 5-minute Apgar score >7 were 13.4 times more likely to initiate breastfeeding early. This may be due to increased complications and the need for admission to Neonatal Intensive Care Units, which makes it difficult to initiate and maintain HDB.

This study identified a negative association between low birth weight and EBHD. In Ghana, Agyekum et al. found that normal birth weight (OR = 7.53; 95% CI: 2.17-26.13) and high birth weight (OR = 6.65; 95% CI: 1.48-29.98) infants were more likely to receive EBF than low birth weight infants(28). Vesel et al. identified, in India, Malawi and Tanzania, that maternal perception of insufficient milk supply and latching difficulties were the main barriers to EBF in low birth weight infants(29). In Germany, Scholten et al. reported that only 7.8% of mothers initiated breastfeeding immediately, 38.2% within the first six hours, and 60.9% used formula during hospitalization(30).

This study identified a negative association between cleft lip and/or palate and EBHD. Becker de Oliveira et al. reported that this condition increases the absence of breastfeeding (OR = 18.08; 95% CI: 7.09-46.09), reduces its frequency (OR = 5.93; 95% CI: 4.30-8.16), and generates greater difficulties in breastfeeding (OR = 13.55; 95% CI: 4.91-37.43)(31). A qualitative study highlighted that hospitalization and the use of tubes, bottles, and syringes hampered the first contact between mother and child, affecting the initiation of breastfeeding(32). Boztepe et al. reported that these mothers experienced greater stress due to the inability to breastfeed(33). In Uganda, Nabatanzi et al. found that only 72% of children with cleft lip and palate were breastfed, with lack of latch and suction as the main barriers(34). Similarly, Adekunle et al. in Nigeria observed that although 83% of mothers initiated breastfeeding, 46% cited inability to suck as the main barrier(35).

Attendance at five or more prenatal checkups and breastfeeding counseling were positively associated with EBHD. Sabilla et al. reported that mothers with prenatal care were 1.43 times more likely to achieve EBF compared to those without follow-up (95% CI: 1.416-1.444)(36). Within prenatal care, breastfeeding counseling plays a key role. Lanyo et al. found that women who received group prenatal care were more likely to meet the WHO recommendation of EBF for six months (OR: 3.6, 95% CI: 2.1-6.3)(37). Likewise, Lynn & Tener reported that promoting breastfeeding intention was significantly associated with higher breastfeeding self-efficacy (aOR 2.7; 95% CI: 1.3 to 5.8)(38).

In the present study, accompaniment during birth was positively associated with EBHD. García-Bautista(39) found that paternal presence at birth generated positive emotions in women during labor and postpartum, favoring EBF.

No association was identified between previous pregnancies and EBHD. A previous study reported that multiparity is associated with greater use of formula during hospitalization (OR: 1.29; 95% CI: 1.29-1.30)(40), while another found that it favors EBF(41). Similarly, alcohol consumption during pregnancy showed no relationship with EBHD in this study, as did Edwards et al., who found no association between prenatal alcohol consumption and EBF(42). No association was identified between violence and EBHD. However, Khalid et al. reported that physical and emotional intimate partner violence reduced the likelihood of EBF by 32% (aOR = 0.68; 95% CI: 0.49-0.98; P < 0.05) and 31% (aOR = 0.69; 95% CI: 0.47-0.92; P < 0.05), respectively(43).

Although prematurity was not associated with EBHD in this study, previous research highlights its challenges. Paes et al. reported lower breastfeeding rates in late preterm infants compared to full-term infants(44). Crippa et al. observed that only 16.8% of late preterm infants in primary care received EBHD(45), while Gianni et al. documented a prevalence of 43%(46). Furthermore, Yang et al. pointed out that prolonged separation in the Intensive Care Unit makes breastfeeding difficult, being perceived as exhausting despite its importance(47).

Study strengths

The study has a large sample size and a long analysis period, which strengthens the validity of the findings. Furthermore, its implementation in a national referral hospital provides relevant information for the public health context in Ecuador.

 Study weaknesses

The cross-sectional design prevents establishing causality, limiting it to associations. Retrospective data collection may have compromised data quality. Social desirability bias may have underestimated self-reported variables, such as illicit substance use.

 Contributions to nursing, health, or public policy

The findings guide strategies to improve EBHD rates. Identifying risk factors allows for staff training in complex cases and effective promotion of EBF. Furthermore, they support hospital policies that prioritize monitoring of vulnerable mothers, promote skin-to-skin contact, prenatal education, and breastfeeding-friendly environments. This study contributes to improving maternal and child health indicators and strengthens the evidence base for clinical practice and health policies.

 CONCLUSION

This study highlights the appropriate frequency of EBHD, but also underscores the need to address risk factors that prevent some newborns from benefiting from it. Prospective, preferably multicenter, studies are needed to confirm and investigate new associations that promote or constitute a barrier to EBHD.

In summary, this study provides key evidence to strengthen strategies for promoting, protecting, and fostering EBF.

 DATA AND MATERIAL AVAILABILITY

The data used in this study are available in Mendeley data: https://data.mendeley.com/datasets/c4wpbkwwx4/1

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Breastfeeding experiences and perspectives on support among Chinese mothers separated from their hospitalized preterm infants: a qualitative study Int Breastfeed J 2019 14 1 45 https://doi.org/10.1186/s13006-019-0242-9 10.1590/0034-7167-2025-0196es ARTICULO ORIGINAL Factores maternos y neonatales asociados a la lactancia materna exclusiva al egreso hospitalario 0000-0003-2804-2504 Toapanta-Pinta Paola Cristina analizaron los datos redactaron el manuscrito han leído aprobado la versión publicada del manuscrito contribuyeron al diseño del estudio realizaron la adquisición codificación almacenamiento de los datos I 0009-0004-0920-9203 Cóndor Adriana Paola Sinchiguano analizaron los datos redactaron el manuscrito han leído aprobado la versión publicada del manuscrito II 0009-0009-9012-6419 Defaz Deicy Maribel Muso analizaron los datos redactaron el manuscrito han leído aprobado la versión publicada del manuscrito II 0009-0009-7612-4927 Landeta Angélica Oliva Gualavisí analizaron los datos redactaron el manuscrito han leído aprobado la versión publicada del manuscrito II 0009-0005-9750-8752 Cadena Blanca Llilman Parra analizaron los datos redactaron el manuscrito han leído aprobado la versión publicada del manuscrito II 0000-0002-1370-9700 Vasco-Morales Santiago analizaron los datos redactaron el manuscrito han leído aprobado la versión publicada del manuscrito contribuyeron al diseño del estudio realizaron la adquisición codificación almacenamiento de los datos I II Universidad Central del Ecuador, Facultad de Ciencias Médicas. Quito, Pichincha, Ecuador Hospital Gineco-Obstétrico Isidro Ayora. Quito, Pichincha, Ecuador Autor Correspondente: Paola Cristina Toapanta-Pinta , E-mail: ptoapanta@uce.edu.ec

Antonio José de Almeida Filho

Waldemar Brandão Neto

 RESUMEN Objetivo:

identificar los factores maternos y neonatales asociados con la lactancia materna exclusiva al egreso hospitalario en un hospital de tercer nivel.

 Métodos:

estudio transversal con datos secundarios de 22.136 registros de recién nacidos hospitalizados en la unidad de neonatología (2009-2022). Se analizaron variables maternas, neonatales y prácticas de alimentación al alta. Se aplicaron modelos de regresión logística bayesiana.

 Resultados:

la lactancia materna exclusiva al egreso hospitalario fue del 91,55%. Factores asociados negativamente fueron parto por cesárea (OR: 0,90), consumo de sustancias ilícitas (OR: 0,30), bajo peso al nacer (OR: 0,84), y labio y paladar hendido (OR: 0,15). La consejería en lactancia y el acompañamiento en el parto favorecieron la lactancia materna exclusiva al egreso hospitalario.

 Conclusión:

a pesar de la alta prevalencia de lactancia materna exclusiva al egreso hospitalario, persisten barreras que deben abordarse mediante estrategias de promoción, capacitación del personal y apoyo a madres en situación de riesgo.

 Descriptores: Lactancia Materna Factores de Riesgo Recién Nacido Conducta Materna Salud Materno-Infantil. INTRODUCCIÓN

La lactancia materna exclusiva (LME) es reconocida a nivel mundial como el método óptimo para garantizar una nutrición adecuada durante los primeros meses de vida, favoreciendo un crecimiento y desarrollo saludables. Además, proporciona beneficios a la salud materna, como la reducción del riesgo de hemorragia posparto y enfermedades metabólicas a largo plazo. En este contexto, la Organización Mundial de la Salud (OMS) recomienda la LME durante los primeros seis meses de vida, por sus múltiples ventajas, como la disminución de infecciones respiratorias y gastrointestinales, el fortalecimiento del desarrollo cognitivo, y la promoción del vínculo madre-hijo(1,2).

A pesar de la sólida evidencia científica que respalda estas recomendaciones, las tasas de lactancia materna exclusiva al egreso hospitalario (LMEEH) siguen siendo subóptimas en muchas regiones. Factores como el acceso limitado a servicios de salud, la falta de políticas públicas efectivas y la comercialización de fórmulas infantiles obstaculizan la LME(1,3,4).

El Hospital Gineco-Obstétrico Isidro Ayora (HGOIA) es una institución de referencia nacional en Ecuador. Desde hace varios años, ha implementado la Iniciativa Hospital Amigo de la Madre y del Niño (IHAN) de la OMS(5) y cumple la normativa nacional para los Establecimientos de Salud Amigos de la Madre y del Niño (ESAMyN)(6). Sin embargo, en el Ecuador, existe una brecha en la investigación sobre los factores que dificultan la LMEEH de los recién nacidos hospitalizados en el área de neonatología.

 OBJETIVO

Identificar factores maternos y neonatales asociados con la LMEEH en un hospital de tercer nivel.

 MÉTODOS Consideraciones éticas

El Comité de Ética en Investigación en Seres Humanos de la Universidad Central del Ecuador aprobó el estudio. Al utilizar datos secundarios anonimizados, no se requirió consentimiento informado.

 Diseño y población del estudio

Se realizó un estudio transversal basado en datos secundarios del Sistema de Información Perinatal del HGOIA, hospital de tercer nivel y referencia nacional ubicado en Quito, Ecuador. Se analizaron 22.136 registros de madres y recién nacidos hospitalizados en neonatología entre enero 2009 y diciembre 2022. Las variables incluyeron datos maternos, neonatales y prácticas de alimentación al alta.

Este estudio fue reportado conforme a las directrices de la red EQUATOR, utilizando la guía Strengthening the reporting of observational studies in epidemiology para estudios observacionales en epidemiología(7).

 Criterios de inclusión y exclusión

Se incluyeron los registros de recién nacidos hospitalizados en neonatología del HGOIA y la información asociada de sus respectivas madres. Se excluyeron casos con al menos uno de los siguientes criterios: recién nacidos trasladados a otra institución; fallecimiento neonatal antes del alta hospitalaria; madre con infección por VIH; neonatos con enfermedades metabólicas que contraindican la lactancia materna (ejemplo: galactosemia, fenilcetonuria); muerte materna durante la hospitalización; datos incompletos en variables clave (10% de valores faltantes en las variables de alimentación al alta hospitalaria, edad gestacional, tipo de parto o consumo de sustancias ilícitas durante la gestación).

 Variables analizadas

La variable de interés fue “alimentación al alta hospitalaria”. Se analizaron variables maternas, incluyendo características sociodemográficas (edad, etnia, nivel educativo, estado civil), factores obstétricos (gestas previas, planificación del embarazo, consultas prenatales, consejería sobre lactancia, trastornos hipertensivos gestacionales, violencia durante el embarazo, y consumo de alcohol, tabaco y sustancias ilícitas durante el embarazo) y aspectos del parto (acompañamiento, vía de parto y anestesia general). Las variables neonatales incluyeron sexo, edad gestacional, clasificación del peso para la edad gestacional, puntajes de Apgar, producto de embarazo múltiple y defectos congénitos (ejemplo: labio y paladar hendido). Para el análisis estadístico, las variables fueron organizadas en categorías dicotómicas o politómicas, según su naturaleza. El peso para la edad gestacional se clasificó utilizando la calculadora de Fenton(8).

 Análisis estadístico

Se calcularon las frecuencias absolutas y relativas de las variables sociodemográficas, obstétricas, neonatales y del parto. Para los análisis bivariados y multivariados, se utilizó un enfoque bayesiano. Este método fue seleccionado por su capacidad para manejar datos desbalanceados y tamaños de muestra pequeños, proporcionando estimaciones más robustas y flexibles, y minimizando los sesgos que suelen presentarse en enfoques frecuentista(9).

La variable “alimentación al alta hospitalaria” se clasificó en tres categorías: a) LME: para los recién nacidos alimentados únicamente con leche materna; b) Alimentación parcial: para aquellos que egresaron con lactancia materna complementada con fórmula; c) Alimentación artificial: para los recién nacidos que fueron alimentados exclusivamente con fórmula al alta. Los análogos bayesianos se aplicaron en las tablas de contingencia, así como para los modelos de regresión logística binaria simple y múltiple, empleando priors no informativos. Para la distribución posterior, se ejecutaron 1.000 iteraciones del algoritmo Markov Chain Monte Carlo. El Factor de Bayes (BF) se utilizó para evaluar la evidencia entre las hipótesis nula y alternativa (BF > 1 respaldó la hipótesis alternativa; BF < 1 favoreció la hipótesis nula). Este enfoque probabilístico permitió una interpretación más flexible de las asociaciones entre las variables y la LME al alta hospitalaria.

Para el cálculo de los modelos de regresión logística bayesiana, la variable de interés fue recategorizada como dicotómica (lactancia exclusiva (sí/no)). Se estimaron los coeficientes de regresión logística simple y múltiple, los cuales, al exponenciarse, generaron razones de probabilidades (Odds Ratios, OR) crudas y ajustadas, con Intervalos de Credibilidad del 95%. Los resultados se interpretaron en términos de la probabilidad posterior, lo que permitió una evaluación más precisa de la incertidumbre asociada a las estimaciones. El análisis se realizó utilizando el software estadístico JASP v0.14.3(10), y el gráfico de tendencia fue generado mediante el lenguaje de programación R(11).

 RESULTADOS

Durante el periodo de estudio, se registraron 26.236 recién nacidos hospitalizados en la unidad de neonatología del HGOIA. Se excluyeron 4.100 registros (15,62%) por no cumplir criterios de inclusión: 394 (1,50%) por traslado a otras instituciones de salud; 1.744 (6,64%) por fallecimiento antes del alta hospitalaria; 118 (0,44%) por infección materna por VIH; 43 (0,16%) por muerte materna; 11 (0.04%) por enfermedades metabólicas; y 1.700 (6,47%) por datos incompletos. El análisis final incluyó 22.136 registros.

La prevalencia de LMEEH fue del 91,55% (N=20.266). El 6,29% de los neonatos recibió alimentación parcial, mientras que el 2,16%, recibió alimentación artificial.

El análisis de tendencias (Figura 1) muestra un incremento progresivo en la proporción de recién nacidos con LMEEH, especialmente a partir de 2016.

Tendencia de lactancia materna exclusiva en el Hospital Gineco-Obstétrico Isidro Ayora, Quito,Ecuador (2009-2022)

Características de la población estudiada y comparación de grupos con y sin lactancia materna exclusiva al egreso hospitalario

En la Tabla 1, se incluyeron variables sociodemográficas, factores obstétricos y del parto. La mayoría de las madres tenían entre 20 a 29 años, con educación secundaria y una pareja estable. Se observó una mayor frecuencia de LMEEH en madres con mayor nivel educativo y sin antecedentes de consumo de sustancias. En cuanto a las características del parto, se identificó una mayor proporción de LMEEH en madres que tuvieron parto vaginal y que recibieron consejería sobre lactancia materna en los controles prenatales.

Características maternas y del curso del embarazo de la población estudiada y comparación según el tipo de alimentación al alta hospitalaria. Hospital Gineco-Obstétrico Isidro Ayora, Quito, Ecuador
Variable Población total Comparación de grupos
Lactancia exclusiva Parcial Artificial BF10
n (%) n (%) n (%) n (%)
Características sociodemográficas
Edad materna
Menor de 20 5.712 (25,80) 5.306 (26,18) 319 (22,92) 87 (18,20) 2.90 × 10-5
20 a 29 10.280 (46,44) 9.354 (46,16) 689 (49,50) 237 (49,58)
30 a 39 5.345 (24,15) 4.866 (24,01) 336 (24,14) 143 (29,92)
40 o más 799 (3,61) 740 (3,65) 48 (3,45) 11 (2,30)
Etnia
Blanca 158 (0,71) 146 (0,72) 4 (0,29) 8 (1,67) 0,4
Indígena 458 (2,07) 419 (2,07) 25 (1,80) 14 (2,93)
Mestiza 2.0734 (93,67) 19.004 (93,77) 1.306 (93,82) 424 (88,70)
Negra 439 (1,98) 368 (1,82) 46 (3,30) 25 (5,23)
Otra 347 (1,57) 329 (1,62) 11 (0,79) 7 (1,46)
Nivel educativo
Ninguno 303 (1,37) 261 (1,29) 32 (2,30) 10 (2,09) 925,42
Primaria 4.944 (22,33) 4.410 (21,76) 381 (27,37) 153 (32,01)
Secundaria 13.396 (60,52) 12.377 (61,07) 765 (54,96) 254 (53,14)
Universidad 3.493 (15,78) 3.218 (15,88) 214 (15,37) 61 (12,76)
Estado civil
Sin pareja estable 5.792 (26,17) 5.363 (26,46) 321 (23,06) 108 (22,59) 0,03
Con pareja estable 16.344 (73,83) 14.903 (73,54) 1071 (76,94) 370 (77,41)
Factores obstétricos
Gestas previas
Sí 13.388 (60,48) 12.160 (60,00) 876 (62,93) 352 (73,64) 99.127,88
No 8.748 (39,52) 8.106 (40,00) 516 (37,07) 126 (26,36)
Embarazo planeado
Sí 7.110 (32,12%) 6.466 (31,91%) 501 (35,99%) 143 (29,92%) 0,02
No 15.026 (67,88%) 13.800 (68,09%) 891 (64,01%) 335 (70,08%)
Consultas prenatales
1 a 4 4.661 (21,06%) 98 (20,50%) 4.212 (20,78%) 351 (25,22%) 3.16x1013
5 a 7 9.238 (41,73%) 181 (37,87%) 8.485 (41,87%) 572 (41,09%)
8 o más 7.323 (33,08%) 153 (32,01%) 6.774 (33,43%) 396 (28,45%)
Ninguno 914 (4,13%) 46 (9,62%) 795 (3,92%) 73 (5,24%)
Consejería sobre lactancia
Sí 10.091 (45,59%) 229 (47,91%) 9.366 (46,22%) 496 (35,63%) 36,14
No 12.045 (54,41%) 249 (52,09%) 10.900 (53,78%) 896 (64,37%)
Trastornos hipertensivos
Sí 1.028 (4,64%) 858 (4,23%) 135 (9,70%) 35 (7,32%) 10,19
No 21.108 (95,36%) 19.408 (95,77%) 1.257 (90,30%) 443 (92,68%)
Violencia durante el embarazo
Sí 359 (1,62%) 311 (1,53%) 29 (2,08%) 19 (3,97%) 1.33x109
No 21.777 (98,38%) 19.955 (98,47%) 1.363 (97,92%) 459 (96,03%)
Consumo de alcohol
Sí 614 (2,77%) 540 (2,66%) 44 (3,16%) 30 (6,28%) 1.5
No 21.522 (97,23%) 19.726 (97,34%) 1.348 (96,84%) 448 (93,72%)
Consumo de sustancias ilícitas
Sí 131 (0,59%) 93 (0,46%) 14 (1,01%) 24 (5,02%) 5.02x103
No 22.005 (99,41%) 20.173 (99,54%) 1.378 (98,99%) 454 (94,98%)
Consumo/exposición al humo de tabaco
Sí 1.328 (5,99%) 1.169 (5,77) 111 (7,97) 48 (10,04) 9,99x1022
No 20.808 (94,01%) 19.097 (94,23%) 1.281 (92,03%) 430 (89,96%)
Factores relacionados con el parto
Vía del parto
Cesárea 11.925 (53,87%) 10.847 (53,52%) 704 (50,57%) 374 (78,24%) 9,99E+22
Vaginal 10.211 (46,13%) 9.419 (46,48%) 688 (49,43%) 104 (21,76%)
Acompañante de parto
Sí 6.834 (30,87%) 6.369 (31,43%) 345 (24,78%) 120 (25,1%) 3,05
No 15.302 (69,13%) 13.897 (68,57%) 1.047 (75,22%) 358 (74,9%)
Anestesia general
Sí 723 (3,27%) 30 (6,28%) 636 (3,14%) 57 (4,09%) 3.03x1013
No 21.413 (96,73%) 448 (93,72%) 19.630 (96,86%) 1.335 (95,91%)
Leyenda: BF10: Factor de Bayes.

La Tabla 2 presenta la distribución de las características neonatales en la población estudiada, categorizadas según el tipo de alimentación al alta hospitalaria. Se observó que la prematuridad, el bajo peso para la edad gestacional y la presencia de malformaciones congénitas estuvieron más representadas en los neonatos que recibieron alimentación parcial o artificial.

Comparación de características neonatales entre recién nacidos con y sin lactancia materna exclusiva al alta hospitalaria. Hospital Gineco-Obstétrico Isidro Ayora, Quito, Ecuador
Variable Población total Comparación de grupos
Lactancia exclusiva Parcial Artificial BF10
n (%) n (%) n (%) n (%)
Condición al nacimiento
Sexo
Femenino 10.111 (45,68) 9.279 (45,79) 613 (44,04) 219 (45,82) 3.6 × 10-5
Masculino 12.023 (54,31) 10.985 (54,2) 779 (55,96) 259 (54,18)
No definido 2 (0,01) 2 (0,01) 0 (0,0) 0 (0,0)
Edad gestacional
Prematuro 8.043 (36,33) 7.254 (35,79) 606 (43,53) 183 (38,28) 151,25
Término 13.964 (63,08) 12.900 (63,65) 775 (55,68) 289 (60,46)
Post-término 129 (0,58) 112 (0,55) 11 (0,79) 6 (1,26)
Peso para edad gestacional
Bajo 6.717 (30,34) 6.058 (29,89) 471 (33,84) 188 (39,33) 1.873,99
Adecuado 14.013 (63,30) 12.918 (63,74) 814 (58,48) 281 (58,79)
Grande 1.406 (6,35) 1.290 (6,37) 107 (7,69) 9 (1,88)
Apgar 1 minuto
>7 18.576 (83,92) 17.033 (84,05) 1.120 (80,46) 423 (88,49) 3,1
<7 3.560 (16,08) 3.233 (15,95) 272 (19,54) 55 (11,51)
Apgar 5 minutos
>7 21.575 (97,47) 19.777 (97,59) 1.331 (95,62) 467 (97,70) 5,34
<7 561 (2,53) 489 (2,41) 61 (4,38) 11 (2,30)
Producto de embarazo múltiple
Sí 1.720 (3,89) 1.510 (3,73) 174 (6,25) 36 (3,77) 1.76x10-5
No 20.416 (46,11) 18.756 (46,27) 1.218 (43,75) 442 (46,23)
Anomalías congénitas
Tipo de defecto
Mayor 1.379 (6,23) 1.257 (6,20) 85 (6,11) 37 (7,74) 1.3 × 10-4
Menor 938 (4,24) 838 (4,14) 84 (6,03) 16 (3,35)
Ninguno 19.819 (89,53) 18.171 (89,66) 1.223 (87,86) 425 (88,91)
Labio y paladar hendido
Sí 184 (0,83) 116 (0,57) 45 (3,23) 23 (4,81) 4,22x1023
No 2.1952 (99,17) 20.150 (99,43) 1.347 (96,77) 455 (95,19)
Malformación cardiopulmonar
Sí 480 (2,17) 446 (2,20) 23 (1,65) 11 (2,30) 2.39 × 10-3
No 21.656 (97,83) 19.820 (97,80) 1.369 (98,35) 467 (97,70)
Malformaciones musculoesqueléticas
Sí 326 (1,47) 302 (1,49) 19 (1,36) 5 (1,05) 1.72 × 10-3
No 21.810 (98,53) 19.964 (98,51) 1.373 (98,64) 473 (98,95)
Malformación gastrointestinal
No 22.029 (99,52) 20.172 (99,54) 1.383 (99,35) 474 (99,16) 0,02
Sí 107 (0,48) 94 (0,46) 9 (0,65) 4 (0,84)
Malformación de sistema nervioso
Sí 615 (2,78) 566 (2,79) 40 (2,87) 9 (1,88) 1.44 × 10-3
No 21.521 (97,22) 19.700 (97,21) 1.352 (97,13) 469 (98,12)
Malformación urogenital
Sí 239 (1,08) 217 (1,07) 19 (1,36) 3 (0,63) 4.6 × 10-3
No 21.897 (98,92) 20.049 (98,93) 1.373 (98,64) 475 (99,37)
Malformaciones tegumentarias
Sí 117 (0,53) 108 (0,53) 8 (0,57) 1 (0,21) 5.05 × 10-3
No 22.019 (99,47) 20.158 (99,47) 1.384 (99,43) 477 (99,79)
Leyenda: >7: menor que; ≥: igual o mayor que; BF10: Factor de Bayes. Factores asociados a lactancia materna exclusiva al egreso hospitalario

La Tabla 3 muestra los resultados del análisis de regresión logística, evaluando factores maternos y neonatales asociados a la LMEEH. Para este análisis, la variable “alimentación al alta hospitalaria” fue recodificada como dicotómica (sí/no). Los modelos bayesianos estimaron las razones de probabilidades (OR crudas y ajustadas) con sus respectivos Intervalos de Credibilidad al 95%.

Factores maternos y neonatales asociados a la lactancia materna exclusiva al alta hospitalaria. Hospital Gineco-Obstétrico Isidro Ayora, Quito, Ecuador
Variable OR crudo OR ajustado
Factores maternos
Nivel educativo bajo 0,68 (0,61 - 0,74) 0,74 (0,66 - 0,82)
Con gestas previas 0,79 (0,72 - 0,87) 0,97 (0,81 - 1,05)
Consumo de alcohol 0,73 (0,58 - 1,00) 0,94 (0,72 - 1,25)
Consumo de sustancias ilícitas 0,23 (0,16 - 0,34) 0,30 (0,20 - 0,46)
Consumo/exposición a tabaco 0,68 (0,57 - 0,80) 0,76 (0,63 - 0,92)
Exposición a violencia 0,66 (0,50 - 1,00) 0,83 (0,59 - 1,14)
Consultas prenatales ≥5 1,31 (1,17 - 1,43) 1,16 (1,04 - 1,30)
Con consejería lactancia 1,34 (1,22 - 1,48) 1,28 (1,16 - 1,42)
Con trastornos hipertensivos durante la gestación 0,45 (0,38 - 0,53) 0,39 (0,33 - 0,47)
Con acompañante durante el parto 1,36 (1,22 - 1,52) 1,38 (1,23 - 1,54)
Parto por cesárea 0,87 (0,78 - 0,95) 0,9 (0,81 - 0,99)
Uso de anestesia general 0,71 (0,59 - 1,00) 0,76 (0,60 - 0,96)
Factores neonatales
Producto de embarazo múltiple 0,65 (0,55 - 0,74) 0,70 (0,60 - 0,84)
Apgar <7 al primer minuto 0,97 (0,86 - 1,02) 1,01 (0,88 - 1,15)
Apgar <7 al quinto minuto 0,66 (0,51 - 0,87) 0,66 (0,50 - 0,87)
Prematurez 0,77 (0,70 - 0,85) 0,90 (0,82 - 1,01)
Peso bajo 0,79 (0,73 - 0,88) 0,84 (0,76 - 0,94)
Labio y paladar hendido 0,16 (0,12 - 0,21) 0,15 (0,11 - 0,21)
Leyenda: <: menor que; >: mayor que; OR: Odds Ratio. DISCUSIÓN

La frecuencia de LMEEH en el presente estudio fue del 91,55%, similar a lo reportado por Zimmerman et al. en Estados Unidos, donde el 91,8% de las madres iniciaron la LME durante la estancia hospitalaria(12). Sin embargo, esta proporción difiere de la observada en otras regiones como Japón, donde Yasuda et al.(13) documentaron una prevalencia del 66,4%, atribuyendo estos resultados a la ausencia de apoyo por parte de doulas o parteras. En Turquía, Çelik et al.(14) informaron de un 87,6% de neonatos dados de alta con LME.

El 8,45% de los neonatos no recibió LMEEH. El análisis multivariado identificó varios factores asociados negativamente con la LMEEH, como el bajo nivel educativo materno, el consumo de sustancias ilícitas o tabaco en la gestación, trastornos hipertensivos, cesárea, anestesia general, ser producto de embarazo múltiple, Apgar <7 al minuto cinco, el bajo peso para la edad gestacional, y labio y paladar hendido. En contraste, un mayor número de controles prenatales, consejería en lactancia y el acompañamiento en el parto se asociaron positivamente con la LMEEH.

En este estudio, se observó un aumento en las tasas de LMEEH, pasando del 89,71%, en 2009, al 93,32%, en 2016, y al 92,96%, en 2022. Como hospital materno-infantil, el HGOIA sigue normativas internacionales, como la IHAN(5), y nacionales, como el ESAMyN(6), promoviendo la LME a través del inicio temprano, el uso adecuado de sustitutos de leche materna y la capacitación integral del personal de salud.

La baja escolaridad mostró una asociación negativa con LMEEH, coincidiendo con un estudio realizado en Cabo Verde, donde las madres con educación secundaria o superior tenían 1,55 veces más probabilidades de amamantar que aquellas con educación básica(15).

En este estudio, el consumo de sustancias ilícitas y de tabaco durante el embarazo se asoció negativamente con la LMEEH. Las normativas locales desaconsejan la lactancia materna en madres en abstinencia mientras reciben atención multidisciplinaria, priorizando su recuperación y el bienestar neonatal(16). Bremer y Knippen reportaron que la exposición a opioides antes o durante la gestación reduce la probabilidad de iniciar LME en la hospitalización(17). En Estados Unidos, Chang et al. identificaron que 16 de 110 hospitales restringen la lactancia en madres con resultados positivos de cannabinoides(18).

Mas allá de las políticas hospitalarias, las madres consumidoras de sustancias también muestran menor intención de amamantar. Jawale et al. observaron esta tendencia en mujeres que consumen marihuana(19). Asimismo, fumar en la gestación y el posparto disminuye en 51% la probabilidad de continuar la LME, según un estudio en Sídney, Australia(20). Un análisis del Sistema de Monitoreo de Evaluación y Riesgos en el Embarazo de los CDC (2016-2018) reveló que el uso combinado de tabaco y sustancia ilícitas reduce significativamente la probabilidad de iniciar la LME (ORa: 0,58; IC 95: 0,39-0,87)(21).

Los trastornos hipertensivos en el embarazo mostraron asociación negativa con la LMEEH. Un estudio realizado en Canadá encontró que estas condiciones afectan el inicio y la continuidad de la lactancia materna(22).

La cesárea y el uso de anestesia general se asociaron negativamente con la LMEEH. Un estudio transversal realizado por Pohol et al.(23) en Israel encontró que, en mujeres judías de origen etíope, la cesárea redujo la LMEEH (OR: 0,481; IC 95: 0,232-0,998). De manera similar, Alchalel et al.(24) determinaron que la cesárea reduce la probabilidad de LME (OR: 0,64; IC 95%: 0,44-0,94; p = 0,023) en hospitales de Haifa y Netanya.

Además, la anestesia general retrasa el contacto piel con piel, afectando la receptividad materna inmediata tras la cirugía. El inicio de la lactancia en la primera hora es crucial para el éxito de la LMEEH(25).

En este estudio, ser producto de embarazo múltiple mostró asociación negativa con la LMEEH, probablemente debido a dificultades en tiempo, organización y técnica de amamantamiento. Un estudio en Japón comparó la LME entre neonatos únicos, gemelos y trillizos, encontrando menor prevalencia en nacimientos múltiples. Solo el 4,1% de gemelos y trillizos recibió LME frente al 44,7% de los nacimientos únicos. Además, las madres de gemelos o trillizos tenían 2.44 veces más probabilidades de optar por alimentación exclusiva con fórmula(26).

La baja puntuación de Apgar a los cinco minutos presentó asociación negativa con la LMEEH. Herrera Gómez et al.(27) encontraron que neonatos con Apgar >7 a los cinco minutos presentaban 13.4 veces más probabilidades de iniciar la lactancia materna precoz. Esto puede deberse a mayores complicaciones y necesidad de ingreso a Unidades de Cuidados Intensivos Neonatales, lo que dificulta el inicio y mantenimiento de la LMEEH.

Este estudio identificó una asociación negativa entre el bajo peso al nacer y la LMEEH. En Ghana, Agyekum et al. encontraron que neonatos con peso normal (OR = 7.53; IC 95: 2.17-26.13) y elevado (OR = 6.65; IC 95: 1.48-29.98) tenían una mayor probabilidad de recibir LME que aquellos de bajo peso(28). Vesel et al. identificaron, en India, Malawi y Tanzania, que la percepción materna de insuficiencia de leche y dificultades en el agarre eran las principales barreras para la LME en neonatos de bajo peso(29). En Alemania, Scholten et al. reportaron que solo el 7,8% de las madres inició la lactancia de inmediato, el 38,2%, en las primeras seis horas, y el 60,9% utilizó fórmula durante la hospitalización(30).

Este estudio identificó una asociación negativa entre labio y/o paladar hendido y la LMEEH. Becker de Oliveira et al. reportaron que esta condición incrementa la ausencia de lactancia materna (OR = 18,08; IC 95: 7,09-46,09), reduce su frecuencia (OR = 5,93; IC 95: 4,30-8,16), y genera mayores dificultades para amamantar (OR = 13,55; IC 95: 4,91-37,43)(31). Un estudio cualitativo destacó que la hospitalización y el uso de sondas, biberones y jeringas dificultaron el primer contacto entre madre e hijo, afectando el inicio de la lactancia materna(32). Boztepe et al. informaron que estas madres experimentaron mayor estrés por la imposibilidad de amamantar(33). En Uganda, Nabatanzi et al. encontraron que solo el 72% de los niños con fisura labiopalatina fueron amamantados, con la falta de agarre y succión como principales barreras(34). De manera similar, Adekunle et al., en Nigeria, observaron que, aunque el 83% de las madres inició la lactancia, el 46% mencionó la incapacidad de succión como el principal obstáculo(35).

La asistencia a cinco o más controles prenatales y la consejería sobre lactancia materna se asociaron positivamente con la LMEEH. Sabilla et al., reportaron que las madres con atención prenatal tenían 1,43 veces más probabilidades de lograr LME frente a aquellas sin seguimiento (IC del 95 %: 1,416-1,444)(36). Dentro del control prenatal, la consejería en lactancia desempeña un papel clave. Lanyo et al. encontraron que las mujeres con atención prenatal grupal tenían mayor probabilidad de cumplir la recomendación de la OMS de amamantar exclusivamente por seis meses (OR: 3,6, IC del 95%: 2,1-6,3)(37). Asimismo, Lynn & Tener (2024) reportaron que promover la intención de amamantar se asoció significativamente con una mayor autoeficacia en la lactancia materna (ORa 2,7; IC del 95 %: 1,3 a 5,8)(38).

En el presente estudio, el acompañamiento durante el parto se asoció de manera positiva con la LMEEH. García-Bautista(39) encontró que la presencia paterna en el nacimiento generó emociones positivas en las mujeres durante el parto y postparto, favoreciendo la LME.

No se identificó asociación entre gestas previas y LMEEH. Un estudio previo reportó que la multiparidad se asocia con mayor uso de fórmula durante la hospitalización (OR: 1,29; IC 95%: 1,29-1,30)(40), mientras que otro encontró que favorece la LME(41). De manera similar, el consumo de alcohol durante el embarazo no mostró relación con la LMEEH en este estudio, al igual que Edwards et al., quienes no encontraron asociación entre el consumo prenatal de alcohol y la LME(42). Tampoco se identificó asociación entre violencia y LMEEH. Sin embargo, Khalid et al. reportaron que la violencia física y emocional de pareja redujo la probabilidad de LME en un 32% (ORa = 0,68; IC 95%: 0,49-0,98; P < 0,05) y 31% (ORa = 0,69; IC 95%: 0,47-0,92; P < 0,05), respectivamente(43).

Aunque la prematurez no se asoció con la LMEEH en este estudio, investigaciones previas evidencian sus dificultades. Paes et al. reportaron menores tasas de lactancia en prematuros tardíos frente a recién nacidos a término(44). Crippa et al. observaron que solo el 16,8% de los prematuros tardíos en el primer nivel de atención recibían LMEEH(45), mientras que Gianni et al. documentaron una prevalencia del 43%(46). Además, Yang et al., señalaron que la separación prolongada en la Unidad de Cuidados Intensivos dificulta la lactancia, percibiéndose como agotadora pese a su importancia(47).

Fortalezas del estudio

El estudio cuenta con una muestra amplia y un período de análisis extenso, lo que fortalece la validez de los hallazgos. Además, su realización en un hospital de referencia nacional proporciona información relevante para el contexto de salud pública en Ecuador.

 Debilidades del estudio

El diseño transversal impide establecer causalidad, limitándose a asociaciones. La recolección retrospectiva de los datos pudo afectar la calidad de estos. El sesgo de deseabilidad social pudo subestimar las variables autoinformadas, como el consumo de sustancias ilícitas.

 Contribuciones a la enfermería, la salud o las políticas públicas

Los hallazgos orientan estrategias para mejorar las tasas de LMEEH. La identificación de factores de riesgo permite capacitar al personal en casos complejos y promover eficazmente la LME. Además, respaldan políticas hospitalarias que prioricen el seguimiento de madres vulnerables, fomenten el contacto piel a piel, la educación prenatal y entornos favorables para la lactancia. Este estudio contribuye a mejorar los indicadores de salud materno-infantil, y refuerza la evidencia en la práctica clínica y las políticas sanitarias.

 CONCLUSIÓN

Este estudio destaca que la frecuencia de LMEEH es adecuada, pero también subraya la necesidad de abordar los factores de riesgo que impiden que algunos neonatos se beneficien de ella. Se deben realizar estudios prospectivos y de preferencia multicéntricos para confirmar y buscar nuevas asociaciones que favorezcan o constituyan una barrera para LMEEH.

En síntesis, este estudio proporciona evidencia clave para fortalecer las estrategias de promoción, protección y fomento de la LME.

 DISPONIBILIDAD DE DATOS Y MATERIAL

Los datos utilizados en este estudio están disponibles en Mendeley data: https://data.mendeley.com/datasets/c4wpbkwwx4/1