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Exclusive Breast Milk Feeding Specificiations Manual for Joint Commission National Quality Measures

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  • Matern Child Nutr
  • v.14(3); 2018 Jul
  • PMC6866094

Matern Child Nutr. 2018 Jul; 14(3): e12589.

The effect of Baby‐friendly status on exclusive breastfeeding in U.S. hospitals

Julie A. Patterson

1 College of Agricultural and Life Sciences, Department of Nutritional Sciences, University of Wisconsin–Madison, Madison Wisconsin, USA

Nicholas S. Keuler

2 College of Letters and Science, Department of Statistics, University of Wisconsin–Madison, Madison Wisconsin, USA

Beth H. Olson

1 College of Agricultural and Life Sciences, Department of Nutritional Sciences, University of Wisconsin–Madison, Madison Wisconsin, USA

Received 2017 Aug 3; Revised 2017 Nov 21; Accepted 2017 Dec 11.

Abstract

In 2014, a leading hospital accreditation agency, mandated hospitals publicly report their exclusive breastfeeding (EBF) rates. This new regulation provided an opportunity to explore differences in EBF outcomes using a standardized definition across a large hospital sample in the United States. The purpose of this study was to examine the relationships between population demographics and the Baby‐friendly (BF) hospital designation on EBF rates in hospitals throughout the United States. We obtained EBF rates from 121 BF hospitals and 1,608 hospitals without the BF designation. Demographic variables were computed using census tract data for the population surrounding each hospital. Relationships were explored using linear regression. We found that EBF rates were positively correlated with a bachelor's degree, log income, and those who identified as White or Asian and negatively correlated with those without college attendance, individuals living below the poverty line, and those who identified as African American or Hispanic. For all models, the BF designation of a hospital was associated with higher EBF rates (p < 0.01; effect sizes, 0.11–0.49) with the exception of the model containing log income. Using a multiple linear regression model that was allowed to contain more than one independent variable, we were able to explain 22% of the variability in EBF rates. The BF hospital designation was associated with significantly higher EBF rates independent of demographic variables. Support for hospitals to attain the BF hospital designation is a meaningful public health goal.

Keywords: Baby‐friendly hospital initiative, breastfeeding, breastfeeding disparities, breastfeeding promotion, exclusive breastfeeding rates, joint commission

Key messages

  • All infants and mothers should have access to a hospital environment of care that is associated with better breastfeeding outcomes.

  • Many factors contribute to the complex nature of breastfeeding decisions, however, maternity practices experienced in the hospital are associated with differences in EBF rates.

  • Disparities exist with EBF rates; however, EBF rates were higher across all population demographics studied in hospitals that were BF.

  • While population demographics and the BF hospital designation are important predictors of EBF rates, inclusion of other maternity practices not represented by these variables may improve our ability to positively influence EBF outcomes in the hospital.

1. INTRODUCTION

Suboptimal breastfeeding is associated with significant morbidity and mortality for both mothers and infants, making it a serious public health issue (Bartick et al., 2016; Chowdhury et al., 2015; Ip et al., 2007; Vennemann et al., 2009). While breastfeeding overall is beneficial, exclusive breastfeeding (EBF) has been associated with a greater level of protection (Chantry, Howard, & Auinger, 2006; Ip et al., 2007; Kramer et al., 2001; Quigley, Kelly, & Sacker, 2007; Vennemann et al., 2009). EBF is associated with increased duration of any breastfeeding, (Brownell et al., 2015) and studies have shown a dose–response relationship between the duration of breastfeeding and a reduction in risk for infant morbidity and mortality (Chantry et al., 2006; Merten, Dratva, & Ackermann‐Liebrich, 2005; Sankar et al., 2015; Victora et al., 2016). Therefore, EBF is a valuable public health indicator (American Academy of Pediatrics, 2012; Brownell et al., 2015). EBF rates in the United States (US) continue to fall below Healthy People 2020 goals, with a disparity in EBF rates between groups that varies by factors such as race/ethnicity, age of mother, educational attainment, and family income (Office of Disease Prevention and Health Promotion, 2017). To protect, promote, and support breastfeeding, the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) launched the Baby‐friendly (BF) hospital initiative in 1991 (WHO & UNICEF, 2009). The BF hospital initiative is a set of 10 maternity practices that when used together improve breastfeeding outcomes (Declercq, Labbok, Sakala, & O'Hara, 2009; DiGirolamo, Grummer‐Strawn, & Fein, 2008; Perrine, Scanlon, Li, Odom, & Grummer‐Strawn, 2012; Rosenberg, Stull, Adler, Kasehagen, & Crivelli‐Kovach, 2008). Studies have shown that the proportion of EBF infants (Merten et al., 2005) and the duration of EBF are higher when mothers are exposed to BF hospital practices (Braun et al., 2003; DiGirolamo et al., 2008; Kramer et al., 2001; Merten et al., 2005; Perez‐Escamilla, Martinez, & Segura‐Perez, 2016).

In 2014, the Joint Commission, a leading hospital accreditation agency in the US, required hospitals with ≥1,100 births to publically report their EBF rates (The Joint Commission, 2013). This new regulation, which generated data on EBF rates using a standardized definition, provided an opportunity to explore differences in EBF outcomes in a large nationwide sample of hospitals accredited by the Joint Commission. The Joint Commission defined EBF as "a newborn receiving only breast milk and no other liquids or solids except for drops or syrups consisting of vitamins, minerals, or medicines" (The Joint Commission, 2014, 2015b). To validate hospitals EBF rates, the Joint Commission requires documentation that newborns were exclusively fed breast milk during the entire hospitalization (The Joint Commission, 2014, 2015b).

A policy update in California used this new data source to highlight higher EBF rates in BF hospitals regardless of the population they served (California WIC Association & UC Davis Human Lactation Center, 2008). What is not known is whether this finding would be replicated with hospitals nationwide. California is a state with many legal and public health protections including legislation that requires all birthing hospitals to adopt the BF hospital initiative by 2025 (National Conference of State Legislatures, 2017). The purpose of this study was to examine the relationships between several variables including population demographics, such as poverty and race, and the BF hospital designation and EBF outcomes in hospitals in the US. We were also interested in exploring how well we could predict EBF rates with the use of a model containing a collection of demographic variables.

2. METHODS

The data for this study were obtained from three sources: (a) the Joint Commission (2016); (b) the U.S. Census Bureau (2014); and (c) Baby Friendly USA (2015), an accrediting body for the BF hospital initiative. In 2014, the Joint Commission began requiring hospitals they certify, which have 1,100 births or more per year, to report their EBF rates. These publically available data are reported as an aggregated "Exclusive Breast Milk Feeding" rate from a sample of eligible infants within the hospital population and expressed as a percentage. This sample excluded infants admitted to the neonatal intensive care unit, diagnosed with galatosemia, on parenteral nutrition, infants who had died, with a hospital stay of ≥120 days, enrolled in clinical trials, transferred to another hospital, or had a documented reason for not exclusively breastfeeding (The Joint Commission, 2014, 2015a). Data extracted from the Joint Commission data set included EBF for 1,729 hospitals located in all 50 states and the District of Columbia, for the time period of April 1, 2014, to March 31, 2015, (The Joint Commission, 2016). California had the largest representation of BF designated hospitals, 39.6%. To account for this, a subset analysis was conducted that excluded data from California.

Census data were applied using census tract data from the American Community Survey conducted by the U.S. Census Bureau (US Census Bureau, 2014). A census tract is a cluster of areas designed to have a population size of 1,200–8,000 people. This information represents the demographic information for the community surrounding the hospital and provides a proxy for the patients served by the hospital. While many factors influence patients' hospital utilization, studies have shown travel distance is a significant determinant of hospital utilization (Friedman et al., 2015) and the majority of women deliver at their local hospital (Kozhimannil, Casey, Hung, Prasad, & Moscovice, 2016). Demographic variables were calculated and expressed as a proportion of the population of interest. Variables representing race/ethnicity comprised of non‐Hispanic White (White), non‐Hispanic African American (African American), non‐Hispanic Asian (Asian), and Hispanic. The population in poverty is defined as the proportion of the population that is below 200% of the poverty line. The education variables only refer to persons 25 years old and older with at least a bachelor's degree (proportion with bachelors) and those who never attended college (proportion without college attendance). The log income was calculated as log10 of the median household income.

Hospitals that were designated a BF hospital as of April 1, 2014, were identified through Baby Friendly USA (2015). There were 172 BF hospitals on April 1, 2014; of these, 121 hospitals were matched by address to the Joint Commission data set. All variables were continuous with the exception of the BF hospital designation, which was dichotomous. Within the data set, there were two hospitals with some missing data. The first hospital was a military hospital situated in an area that excludes housing, so there was no demographic information. The second hospital did not have poverty or income information, which is consistent with the fact that it is located in a large academic community. These hospitals were omitted from any analyses that included variables for which they had no data. This study was certified as not human subjects research and therefore did not require oversight by the Institutional Review Board.

2.1. Statistical Analysis

Data analysis was performed with the R statistical package (version 3.1.1), using RStudio software (version 0.99.902) as an interface (R Core Team, 2013). Separate multiple linear regression models were fit. EBF was the dependent variable for all models. Each model contained one of the demographic independent variables (race/ethnicity, education, and income) together with BF designation, as well as the interaction between the two. This was done to determine whether BF hospital designation affected relationships between the independent and dependent variables. Subsequently, an exhaustive approach was used to create a multiple linear regression model that was allowed to contain more than one independent variable, with the model selected using adjusted R 2 as the criterion. Variance inflation factors indicated possible multicollinearity between some of the independent variables. Therefore, a model was chosen that had the highest adjusted R 2 while maintaining low variance inflation factors. All models were checked graphically for adherence to the assumptions of linear regression. Normality of the residuals was checked using normal Q–Q plots, and constant variance and model fit using residuals versus fitted values plots.

3. RESULTS

Figure1 summarizes the BF hospital effect on EBF rates across the entire sample of hospitals. EBF rates were significantly higher for hospitals with the BF designation (62%) as compared with those without the BF hospital designation (48%) Welch's t test: T146 = −9.1, p < 0.001.

An external file that holds a picture, illustration, etc. Object name is MCN-14-e12589-g001.jpg

Difference in exclusive breastfeeding rates between hospitals without the baby‐friendly (BF) hospital designation compared with hospitals with the BF designation (p < 0.001)

In Table1, Models 1 through 8 summarize information about the variables that were examined using separate linear regression models for each demographic variable. Education, income, and proportion of the population of White or Asian were all positively correlated with EBF rates. All were significant (p < 0.001) with the exception of the proportion of the population that identifies as Asian (p = 0.60). The proportion of the population that identified as African American or Hispanic, the proportion without college attendance, and the proportion of the population living below the poverty line were negatively associated with EBF rates (all p < 0.001). For all models, the BF hospital designation was associated with higher EBF rates (p < 0.01; effect sizes 0.11–0.49) with the exception of the model containing log income. Subset analysis excluding data from California hospitals showed approximately the same results (results not shown), so the full data set was used for all modelling.

Table 1

Regressions determining association between exclusive breastfeeding rates and demographic variables

95% CI
Predictor (demographics) Adj R 2, a B b SE c p valued Lower Upper
Model 1 0.14
BFe 0.13 0.04 0.003 0.05 0.21
Proportion without college attendancef −0.55 0.04 <0.001 −0.63 −0.47
BF × without college attendance 0.04 0.16 0.81 −0.27 0.35
Model 2 0.07
BF 0.18 0.03 <0.001 0.12 0.24
Proportion with bachelorsg 0.29 0.04 <0.001 0.21 0.37
BF × bachelors −0.16 0.13 0.22 −0.41 0.09
Model 3 0.07
BF 0.50 0.35 0.16 −0.19 1.19
Log income 0.18 0.02 <0.001 0.14 0.22
BF × log income −0.08 0.08 0.32 −0.24 0.08
Model 4 0.07
BF 0.11 0.04 0.004 0.03 0.19
Proportion below the poverty line −0.21 0.03 <0.001 −0.27 −0.15
BF × proportion below the poverty line 0.08 0.09 0.37 −0.10 0.26
Model 5 0.14
BF 0.15 0.02 <0.001 0.11 0.19
Proportion African American −0.34 0.02 <0.001 −0.38 −0.30
BF × proportion African American −0.16 0.12 0.20 −0.40 0.08
Model 6 0.12
BF 0.18 0.04 <0.001 0.10 0.26
Proportion White 0.23 0.02 <0.001 0.19 0.27
BF × proportion White −0.04 0.06 0.56 −0.16 0.08
Model 7 0.06
BF 0.15 0.03 <0.001 0.09 0.21
Proportion Hispanic −0.16 0.03 <0.001 −0.22 −0.10
BF × proportion Hispanic 0.01 0.08 0.85 −0.15 0.17
Model 8 0.03
BF 0.12 0.02 <0.001 0.08 0.16
Proportion Asian 0.03 0.06 0.61 −0.09 0.15
BF × proportion Asian 0.29 0.21 0.17 −0.12 0.70
Model 9 0.22
BF 0.14 0.02 <0.001 0.10 0.18
Proportion African American −0.31 0.02 <0.001 −0.35 −0.27
Proportion Hispanic −0.13 0.02 <0.001 −0.17 −0.09
Proportion without college attendance −0.39 0.04 <0.001 −0.47 −0.31
Proportion Asian −0.13 0.05 0.01 −0.23 −0.03

Model 9 summarizes the variables in the multiple linear regression model that had the best adjusted R 2, which were BF hospital, proportion without college attendance, the proportion Hispanic, proportion African American, and proportion Asian. In this model, EBF rates were higher for hospitals with BF designation (p < 0.001). The proportion of the population without college attendance, the proportion of Hispanic, the proportion of African American, and the proportion of Asian were all negatively associated with EBF rates (all p < 0.001 except proportion of Asian p < 0.01). The model was able to explain 22% of the variability in EBF rates.

4. DISCUSSION

To our knowledge, this is the first study to evaluate EBF rates using a standardized definition across hospitals nationwide. This study found most demographic variables included in our analysis were correlated with EBF rates, and EBF rates were significantly higher in hospitals that have the BF designation. The findings are consistent with studies showing that BF hospitals have better EBF outcomes (Braun et al., 2003; Merewood, Mehta, Chamberlain, Philipp, & Bauchner, 2005; Merten et al., 2005). Using this large nationwide hospital data set, we also see a consistent theme with the scientific literature on disparities in breastfeeding rates related to race/ethnicity, education, income, and poverty status (California WIC Association & UC Davis Human Lactation Center, 2008; Forste, Weiss, & Lippincott, 2001; Murray, Ricketts, & Dellaport, 2007). In our study, as the proportion of African American individuals, Hispanic individuals, those without college attendance, and poverty increased, there was a negative linear trend for EBF rates. The opposite was true for populations that had a high proportion of White individuals and those with a bachelor's degree. In multiple linear regression models that looked at these variables individually, we observed higher EBF rates in hospitals with the BF hospital designation. Increases in breastfeeding initiation rates across all ethnic and socio‐economic groups were found in a study that evaluated breastfeeding outcomes after the implementation of the BF hospital designation in a large teaching institution serving primarily minority, poor, and immigrant families (Philipp et al., 2001). Considering EBF rates specifically, California presented a similar increase in EBF rates across all demographic variables when comparing hospitals with and without the BF hospital designation (California WIC Association & UC Davis Human Lactation Center, 2008). Our study is significant because it supports that hospitals with the BF designation have higher EBF rates across all demographic variables studied. Although significant strides have been made in the number of BF hospitals, there is room for improvement in access to these hospitals. Approximately 21% of infants were born in BF hospitals as of June 2017 (Baby Friendly USA, 2015). Public health initiatives aimed at increasing BF hospitals should remain a high priority. The Centers for Disease Control and Prevention (CDC) quality improvement project was successful at helping 72 out of 90 (80%) hospitals attain the BF hospital designation (Feldman‐Winter et al., 2017). This collaborative approach nearly doubled the BF hospitals in the US (Feldman‐Winter et al., 2017).

With the use of census data as a proxy for the population served by the hospital, we were still able to explain 22% of the variability in EBF in the multiple linear regression model. The multiple regression model that was allowed to contain more than one demographic variable did a better job of explaining the variability in EBF rates than any model containing a single demographic variable plus BF hospital designation. This showed that variables were explaining different aspects of the EBF rates and underscores that many factors are involved in the complex nature of breastfeeding decisions. For the purposes of this study, we were only able to include selected demographic variables and the BF hospital initiative on EBF rates. Strengths of the study include that is was a national hospital sample and utilized a standardized definition of EBF. Limitations of this study include that U.S. census data for the community surrounding the hospital was used as a proxy for the demographics actually served by the hospital. In order to strengthen the model's ability to predict EBF rates, other maternity practices, such as those measured by the CDC Maternity Practices in Infant Nutrition and Care survey could be evaluated (CDC, 2017). In addition, hospitals that were marked as non‐BF hospitals may have been in various stages of obtaining designation, and therefore, a dichotomous variable may not have fully represented true impact of the BF hospital designation. Finally, research has found a dose–response relationship between BF hospital practices that mothers experience and their achievement of EBF goals (Perrine et al., 2012). Research that expands upon this dose–response relationship, using other maternity practices outside of the 10 steps to BF, may be informative for hospitals that are looking for additional ways to positively influence EBF rates.

5. CONCLUSION

We observed a mean difference in EBF rates between hospitals with the BF designation versus without the BF designation. Those with the BF hospital designation had higher EBF rates. Higher EBF rates shown across the demographic variables of race/ethnicity, income, and education offer a broad public health benefit. This study supports the use of hospitals achieving the BF designation to help move EBF rates towards goals set by Healthy People 2020. Legislative efforts such as those in California and public health initiatives like the CDC, both of which promote obtaining BF hospital status, have been effective. Such efforts, if carried across the US, would have a significant impact on maternal and child health.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

CONTRIBUTIONS

JAP led the design of the study, statistical analysis, writing, revising, and final approval of the manuscript. NSK guided the statistical analysis and contributed to writing and revising as well as final approval of the manuscript. BHO supervised the overall study and contributed to the design, analysis, writing and revising, and final approval of the document.

ACKNOWLEDGMENTS

We thank W. R. Buckingham from the University of Wisconsin–Madison, Applied Population Laboratory, for his assistance. We would also like to thank the College of Agricultural and Life Sciences and the Wisconsin Alumni Research Foundation for their financial support.

Notes

Patterson JA, Keuler NS, Olson BH. The effect of Baby‐friendly status on exclusive breastfeeding in U.S. hospitals. Matern Child Nutr. 2018;14:e12589 10.1111/mcn.12589 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6866094/

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