Dataset Information

Predicting risk of early discontinuation of exclusive breastfeeding at a Brazilian referral hospital for high-risk neonates and infants: a decision-tree analysis.

ABSTRACT:

Background

Determinants at several levels may affect breastfeeding practices. Besides the known historical, socio-economic, cultural, and individual factors, other components also pose major challenges to breastfeeding. Predicting existing patterns and identifying modifiable components are important for achieving optimal results as early as possible, especially in the most vulnerable population. The goal of this study was building a tree-based analysis to determine the variables that can predict the pattern of breastfeeding at hospital discharge and at 3 and 6 months of age in a referral center for high-risk infants.

Methods

This prospective, longitudinal study included 1003 infants and was conducted at a high-risk public hospital in the following three phases: hospital admission, first visit after discharge, and monthly telephone interview until the sixth month of the infant's life. Independent variables were sorted into four groups: factors related to the newborn infant, mother, health service, and breastfeeding. The outcome was breastfeeding as per the categories established by the World Health Organization (WHO). For this study, we performed an exploratory analysis at hospital discharge and at 3 and at 6 months of age in two stages, as follows: (i) determining the frequencies of baseline characteristics stratified by breastfeeding indicators in the three mentioned periods and (ii) decision-tree analysis.

Results

The prevalence of exclusive breastfeeding (EBF) was 65.2% at hospital discharge, 51% at 3?months, and 20.6% at 6 months. At hospital discharge and the sixth month, the length of hospital stay was the most important predictor of feeding practices, also relevant at the third month. Besides the mother's and child's characteristics (multiple births, maternal age, and parity), the social context, work, feeding practice during hospitalization, and hospital practices and policies on breastfeeding influenced the breastfeeding rates.

Conclusions

The combination algorithm of decision trees (a machine learning technique) provides a better understanding of the risk predictors of breastfeeding cessation in a setting with a large variability in expositions. Decision trees may provide a basis for recommendations aimed at this high-risk population, within the Brazilian context, in light of the hospital stay at a neonatal unit and period of continuous feeding practice.

SUBMITTER: Silva MDB

PROVIDER: S-EPMC7783998 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Predicting risk of early discontinuation of exclusive breastfeeding at a Brazilian referral hospital for high-risk neonates and infants: a decision-tree analysis.

Silva Maíra Domingues Bernardes MDB de Oliveira Raquel de Vasconcellos Carvalhaes RVC da Silveira Barroso Alves Davi D Melo Enirtes Caetano Prates ECP

International breastfeeding journal 20210104 1

<h4>Background</h4>Determinants at several levels may affect breastfeeding practices. Besides the known historical, socio-economic, cultural, and individual factors, other components also pose major challenges to breastfeeding. Predicting existing patterns and identifying modifiable components are important for achieving optimal results as early as possible, especially in the most vulnerable population. The goal of this study was building a tree-based analysis to determine the variables that can ...[more]

PMID: 33397423

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Project description:Introduction:Practicing exclusive breastfeeding (EBF) in an infant's first six months of life is recommended by the World Health Organization because of its proven effectiveness as a method to support the infant's short- and long-term physical and cognitive development. However, many countries, including Cambodia, face contextually driven challenges in meeting this optimum standard of breastfeeding. The recent declining EBF rate in Cambodia is a concerning indicator of the impact of these challenges. Methods:We used existing data from the 2014 Cambodian Demographic and Health Survey (CDHS) to analyze 717 Cambodian mother-infant pairs. CDHS 2014 used a two-stage stratified cluster sampling approach to select samples. A multivariable logistic regression analysis was used to assess determinants of EBF, taking into account the sampling weight in the analysis. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated, and significance level was considered at p value < 0.05. Results:Our findings indicate that among mothers with infants under six months, EBF was more likely if they resided rurally (AOR = 2.28; 95% CI 1.23-4.23) and if they delivered at a public hospital (AOR = 2.64; 95% CI 1.28-5.47). On the other hand, mothers of middle wealth index practiced EBF less than mothers of low wealth index (AOR = 0.58; 95% CI 0.34-0.99). And as expected, our analysis confirmed that the older the infants grew, the less likely they were to be exclusively breastfed than those younger than one month old (2-3 months: AOR = 0.49; 95% CI 0.26-0.92; 4-5 months: AOR = 0.25; 95% CI 0.15-0.43). Conclusion:The findings emphasize the need to address these determinants adequately by appropriate interventions to halt the declining trend of EBF practice. We recommend a multifaceted approach to improve EBF rates in Cambodia. Advocacy around EBF at public hospitals should continue, and private hospital staff should receive training to provide EBF counselling and support to mothers.

Project description:BackgroundBangladesh is a South Asian developing country trying to achieve the Sustainable Development Goals (SDG)-3 and the objective of the Rural Electrification Board (REB) regarding child mortality. Infectious diseases are leading causes of child mortality, and lack of exclusive breastfeeding (EBF) among infants aged 0-6 months increases child morbidity and mortality from various infectious diseases in developing countries. However, as per existing literature, no study has been conducted yet to determine the lack of EBF practice effect on child mortality in Bangladesh. With this backdrop, the authors intend to measure the likelihood of infectious diseases due to the lack of EBF of infants aged 0-6 months in Bangladesh.Materials and methodsThis study used Bangladesh Demographic and Health Survey (BDHS) data over 1996-97 to 2017-18. The mothers of infants aged 0-6 months who were willingly participated in the BDHSs were considered to include in our analysis. Initially, there were 9,133 cases in the combined dataset. After filtering, there were 5,724 cases in the final dataset. We have considered diarrhea (D), acute respiratory infection (ARI) separately as well as the presence of either D or ARI or both and named as CoDARI as outcome variables. This study used both graphical and statistical techniques (Chi-square test, Wald test, and logistic regression) to analyze the data. The odds ratio (OR) and 95% confidence interval (CI) were used to quantify the likelihood of infectious diseases due to lack of EBF practice and its elasticity, respectively.ResultsThe EBF practice got a conspicuous increasing trend, but the prevalence of infectious diseases was declined from 0 to 3 months of age of infants, whereas an inverse scenario is observed between 4-6 months. The significance of that inverse relationship was confirmed by p-value corresponding to the chi-square test and the Wald test of the adjusted regression coefficients after adjusting the associated factor's effect on infectious diseases. The adjusted ORs also concluded that the lack of EBF practice up to six months of age could enhance the risk of D, ARI, and CoDARI by 2.11 [95% CI: 1.56-2.85], 1.43 [95% CI: 1.28-1.60], and 1.48 [95% CI: 1.32-1.66] times higher, respectively.ConclusionFindings of this study emphasize the importance of EBF up to six months of age of infants against diarrhea and ARI specific morbidity and mortality. Our results also agreed to the recommendation of the World Health Organization (WHO), United Nations International Children's Emergency Fund (UNICEF), American Academy of Pediatrics (AAP), American Academy of Family Physicians (AAFP), and National Nutrition Programme of Ethiopia (NNPE) that the EBF practice for the first six months of age could be a best, cost-effective, long-lasting natural preventive way to reduce the child morbidity and mortality due to infectious diseases in developing countries. Therefore, findings would help policymakers ensuring the achievement target of REB and SDG-3 associated with the health sector in Bangladesh.

Project description:BackgroundEarly breast milk expression, prolonged skin-to-skin contact, rooming-in, use of test-weighing and minimizing use of pacifiers are positively associated with exclusive breastfeeding of preterm infants, whereas use of nipple shields is negatively associated.AimTo test whether a training program for neonatal nurses with a focus on these six breastfeeding-supportive clinical practices affects the rate of preterm infants exclusively breastfed at discharge to home, the postmenstrual age at establishment of exclusive breastfeeding, and maternal self-reported use of the practice in the neonatal intensive care unit, the.MethodsA quasi-experimental multi-centre intervention study from 2016-2019 including a control group of 420 preterm mother-infant dyads, an intervention with a training program for neonatal nurses and implementation of weekly breastfeeding meetings for neonatal nurses, and an intervention group of 494 preterm mother-infant dyads.ResultsSignificantly more preterm infants in the intervention group were exclusively breastfed at discharge to home (66.6%) than in the control group (58.1%) p = 0.008. There was no significant difference in postmenstrual age at establishment of exclusive breastfeeding between control and intervention group (37.5 vs.37.8 weeks, p = 0.073). Compared to the control group the number of infants continuing daily skin-to-skin contact after incubator care increased (83.2% vs. 88.3%, p = 0.035), infants using a nipple shield decreased (61.8% vs. 54.2%, p = 0.029), and the number of mothers initiating breast milk expression before six hours post-partum increased (32.6% vs. 42.4%, p = 0.007). There was a significant correlation between percentage of neonatal nurses participating in the breastfeeding training program and changes in exclusive breastfeeding rates (Pearson Correlation 0.638, p = 0.047).ConclusionExclusive breastfeeding rates in preterm infants and maternal self-reported use of breastfeeding-supportive practices increased by training neonatal nurses in the six clinical practices. It is important to include all nurses in the breastfeeding training program to ensure positive effect on exclusive breastfeeding rates.

Project description:BackgroundTo investigate the prevalence and patterns of breastfeeding at discharge and in the first six months of life in a high-risk fetal, neonatal and child referral center.MethodsProspective, longitudinal study that included the following three steps: hospital admission, first visit after hospital discharge and monthly telephone interview until the sixth month of life. The total number of losses was 75 mothers (7.5%). Exposure variables were sorted into four groups: factors related to the newborn, the mother, the health service and breastfeeding. The dependent variable is breastfeeding as per categories established by the WHO. All 1200 children born or transferred to the high-risk fetal, neonatal and child referral center, within a seven-day postpartum period, from March 2017 to April 2018, were considered eligible for the study, and only 1003 were included. The follow-up period ended in October 2018. For this paper, we performed an exploratory analysis at hospital discharge in three stages, as follows: (i) frequencies of baseline characteristics, stratified by risk for newborn; (ii) a multiple correspondence analysis (MCA); and (iii) clusters for variables related to hospital practice and exclusive breastfeeding (EBF).ResultsThe prevalence of EBF at hospital discharge was 65.2% (62.1-68.2) and 20.6% (16.5-25.0) in the six months of life. Out of all at-risk newborns, 45.7% were in EBF at discharge. The total inertia corresponding to the two dimensions in the MCA explained for 75.4% of the total data variability, with the identification of four groups, confirmed by the cluster analysis.DiscussionOur results suggest that robust breastfeeding hospital policies and practices influence the establishment and maintenance of breastfeeding in both healthy and at-risk infants. It is advisable to plan and implement additional strategies to ensure that vulnerable and healthy newborns receive optimal feeding. It is necessary to devote extra effort particularly to at-risk infants who are more vulnerable to negative outcomes.ConclusionAt-risk newborns did not exclusively breastfeed to the same extent as healthy newborns at hospital discharge. A different approach is required for at-risk neonates, who are more physically challenged and more vulnerable to problems associated with initiation and maintenance of breastfeeding.

Project description:IntroductionExclusive breastfeeding (EBF) is the safest and healthiest option of feeding among infants in the first 6 months throughout the world. Thus, the promotion of EBF is essential to prevent complex infant health problems even at the adulthood level. But the majority of previous studies focused on individual- level determinants of EBF by using basic regression models in localized areas. This study aimed to identify the determinants of EBF at the individual and community level which would be helpful to design appropriate strategies for improving the practice of EBF.MethodsIt is a secondary data analysis using the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total of 1185 infants under 6 months of age were included in the analysis. A Multilevel logistic regression model was employed to investigate factors significantly associated with EBF among under-six infants in Ethiopia. Adjusted odds ratio (AOR) with 95% confidence interval (CI) was used to measure the association of variables whereas Intracluster correlation (ICC), median odds ratio (MOR), and proportional change in variance (PCV) were used to measure random effects (variation).ResultIn multilevel logistic regression; 4-5 months age infant (AOR = 0.04, 95%CI:0.02-0.07), female infants (AOR = 2.51, 95%CI:1.61-3.91), infant comorbidities (AOR = 0.35, 95%CI: 0.21-0.57), richest household wealth index (AOR = 10.34, 95%CI: 3.14-34.03) and antenatal care (AOR = 2.25, 95%CI:1.32-3.82) were individual- level determinants significantly associated with exclusive breastfeeding. Whereas, contextual region (AOR = 0.30, 95%CI: 0.10-0.87), community- level of postnatal visit (AOR = 2.77, 95%CI: 1.26-6.58) and community -level of maternal employment (AOR = 2.8, 95%CI: 1.21-6.47) were community level determinants significantly associated with EBF. The full model showed that46.8% of the variation of exclusive breastfeeding was explained by the combined factors at the individual and community levels. Similarly, it showed that the variation in exclusive breastfeeding across communities remained statistically significant (ICC = 8.77% and variance = 0.32 with P<0.001).Conclusion and recommendationOur study showed that both individual and community level determinants were significantly associated with EBF practice among under 6 infants. Based on our findings, it is recommended to promote and enhance antenatal and postnatal care services utilization of mothers to improve exclusive breastfeeding practice and more emphasis should be given to infants with comorbid conditions and those who were living in the pastoralist regions.

Dataset Information

Predicting risk of early discontinuation of exclusive breastfeeding at a Brazilian referral hospital for high-risk neonates and infants: a decision-tree analysis.

Background

Methods

Results

Conclusions

Publications

Predicting risk of early discontinuation of exclusive breastfeeding at a Brazilian referral hospital for high-risk neonates and infants: a decision-tree analysis.

Similar Datasets

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