Lactation Consultant Access and Breastfeeding Outcomes in the United States: Cross-Sectional Analysis

Introduction

Background

Breastfeeding is a complex, symbiotic process between a mother and child and breast milk is the one source of infant nutrition that is perfectly, biologically suited for an infant in its unadulterated form. The value of breastfeeding goes well beyond meeting nutritional needs and it is a mother’s way to continue her uniquely profound role of nourishing and nurturing after childbirth. Although breastfeeding is the biological norm for humans, it is no longer the social norm. With the early 20th century commercialization of infant formula, which produces over US $55 billion in sales annually, mothers have been dissuaded from breastfeeding [1]. Infant formula marketing is partially to blame for the decrease in breastfeeding on a global scale—a drop from 90% in the 20th century to 42% in the 21st century [2]. Infant formula usage increasingly became the social norm while mothers increasingly lost their innate ability to breastfeed. Mothers have fewer supporters of breastfeeding as fewer people breastfeed, including their role models and peers. Although breastfeeding is innate, it can be incredibly challenging, especially considering most mothers today do not grow up seeing others breastfeed regularly. The potential problems that mothers can encounter are numerous and often lead to a mother discontinuing breastfeeding prematurely [3].

In the United States, approximately 83% of infants have ever breastfed [4]. This figure even includes babies who have latched just once in their life after birth, but were never breastfed again. By 3 months, the proportion of infants exclusively breastfed drops to approximately 45%, and then to 25% at 6 months. Nearly one-fifth of breastfed infants have already been given infant formula (artificial baby milk) before they are 2 days old. In a study by Perrine et al [5], approximately 68% of the participants did not meet their intended breastfeeding goal. The overarching message is that most women are breastfeeding for shorter durations than they intended.

Lactation consultants are clinical health care professionals that make it their mission to help mothers meet their breastfeeding goals and make breastfeeding the social norm again.

Lactation consultants are extensively educated and trained to understand the biological, anatomical, physiological, psychological, and social mechanisms of breastfeeding—on the part of both the mother and the infant. They are typically employed by hospitals or pediatric clinics or work in private practice. Lactation consultants are effective at improving breastfeeding outcomes, including exclusivity, duration, self-efficacy, and maternal mental health [6,7]. Although lactation consultants do indeed solve many breastfeeding problems, the problem of access to care remains. The lactation consultant profession is fairly small (approximately 19,000 in the United States and 35,000 worldwide) but growing, and it can be difficult for a mother to have geographical access to a lactation consultant [8].

Research Questions and Hypotheses

This study aims to evaluate the relationship between the population density of lactation consultants and breastfeeding outcomes across US states.

Research question: Is there a correlation between the population density of lactation consultants and breastfeeding outcomes?

The H₀ (null hypothesis) is that there is no correlation between the population density of lactation consultants and breastfeeding outcomes. The H₁ (alternative hypothesis) is that there is a correlation between the population density of lactation consultants and breastfeeding outcomes.

Study Rationale

Given that breastfeeding rates nationally and globally are low, especially for continuation of breastfeeding, the focus of this article examines access to lactation consultants, who are designated clinical breastfeeding professionals. Access to lactation consultants is a topic that has not been well researched. In the United States, postnatal support varies significantly depending on geographic location, health care provider networks, and insurance status. Unlike some countries with nationalized health care systems, the United States lacks a standardized postnatal care pathway, and support for breastfeeding often depends on fragmented services offered through hospitals, outpatient clinics, and community health programs. However, there is research indicating that the use of lactation consultants does contribute to better breastfeeding outcomes, including longer duration and fewer problems. The inclusion of key sociodemographic variables in this study—household income, education level, and health insurance coverage—reflects their importance as social determinants of health. These factors can significantly influence a mother’s ability to access lactation support services. For example, lower-income mothers or those without insurance may face barriers such as out-of-pocket costs or limited availability of lactation consultants in their communities. Similarly, differences in educational attainment may affect awareness of available resources and breastfeeding best practices. One gap in the current literature is an examination of the relationship between the access to lactation consultants and breastfeeding outcomes. Access to lactation consultants is a different problem entirely than the effectiveness of lactation consultants.

The objective of this study is to examine access to lactation consultants in the United States by measuring their population density at the state level and analyzing its association with key breastfeeding outcomes.

Subsequently, if the results indicate a higher population density of lactation consultants (International Board Certified Lactation Consultants [IBCLCs]) in an area results in better breastfeeding rates, a case can be made for public policy and funding to support improved access to lactation consultants.

Methods

Study Design and Setting

This study used a cross-sectional ecological design to investigate associations between state-level availability of lactation consultants and breastfeeding outcomes across the 50 US states. Data were compiled from publicly available national sources representing the year 2022. No human participants were recruited, as the analysis was based on aggregated secondary data. The setting spanned all 50 US states, and data collection periods correspond to annual releases from the US Census Bureau, the Centers for Disease Control and Prevention (CDC), and the International Board of Lactation Consultant Examiners (IBLCE).

Participants and Eligibility

The unit of analysis was each individual US state. All 50 states were eligible and included in the study based on the availability of complete data across key variables. The District of Columbia and US territories were excluded to ensure consistency in health care infrastructure, population metrics, and reporting standards. As an ecological study, eligibility criteria were based on data completeness at the state level rather than individual characteristics.

Data Sources and Assessments

Workforce statistics for IBCLCs were obtained from IBLCE’s published reports, which detail the number of actively certified professionals per state. IBCLC density, the primary exposure variable, was calculated as the number of IBCLCs per 100,000 women aged 15-49 years using 2022 US Census Bureau data [9,10]. Breastfeeding outcomes were obtained from the CDC’s 2022 Breastfeeding Report Card, which draws on data from the National Immunization Survey. The 3 key outcomes assessed were breastfeeding initiation (defined as ever having breastfed), exclusive breastfeeding at 3 months, and exclusive breastfeeding at 6 months. These outcomes represent population-level estimates based on parent-reported data and are considered valid for surveillance purposes.

The Breastfeeding Report Card data are derived from the National Immunization Survey, a telephone-based survey of parents with children aged 19-35 months. The CDC uses standardized weighting methods to ensure national representativeness. Although this is a well-established source of breastfeeding surveillance data, it is important to acknowledge that self-reported data can be subject to recall and social desirability bias.

Additionally, the study used the World Health Organization’s definition of women of reproductive age—15 to 49 years old—to calculate IBCLC density [11]. This aligns with global demographic standards and ensures comparability across public health data sources.

The study also included 3 covariates identified as potential confounders based on existing literature about social determinants of health: average household income, the percentage of the population without health insurance, and the percentage of women aged 25 years and older with a bachelor’s degree or higher. These variables were extracted from the US Census Bureau’s 2022 state-level data. Together, these measures were used to assess sociodemographic context and its potential influence on breastfeeding behaviors.

Study Size

The final study population included all 50 US states. This sample size was determined by the availability of complete and consistent state-level data for all variables of interest. As a fixed and exhaustive sample of all states, a formal power analysis or sample size calculation was not necessary or applicable to this ecological analysis.

Data Analysis

Descriptive statistics were used to summarize the distribution of IBCLC density and breastfeeding outcomes across states. Simple linear regression models were conducted to assess the unadjusted associations between IBCLC density and each of the 3 breastfeeding outcomes. Subsequently, multiple linear regression models were developed to control for the influence of income, insurance coverage, and educational attainment. The primary independent variable in all models was IBCLC density, while the dependent variables were breastfeeding initiation, exclusive breastfeeding at 3 months, and exclusive breastfeeding at 6 months.

Pearson correlation analyses were conducted to examine the strength and direction of linear relationships between IBCLC density and each of the 3 breastfeeding outcomes: initiation, exclusive breastfeeding at 3 months, and exclusive breastfeeding at 6 months. These analyses provided initial insight into bivariate associations and guided the selection of variables for subsequent regression modeling. Correlation coefficients (r) and P values were reported to assess statistical significance.

Regression results were reported as standardized beta coefficients (β) along with 95% CIs, P values, and adjusted R² values to assess statistical significance and explanatory power. All analyses were conducted using Python programming tools (version 3.11; Python Software Foundation).

Ethical Considerations

This research involved the secondary analysis of publicly available, deidentified datasets and did not include any interaction with human subjects or use of private, identifiable information. Accordingly, ethics board review was not sought, in accordance with US Department of Health and Human Services regulations (45 CFR 46.102), which state that such studies do not constitute human subjects research. Institutional policy at Rockhurst University confirms that publicly available and anonymized data analyses are exempt from institutional review board review. All data used in this study were obtained from official public sources, including the CDC, US Census Bureau, and IBLCE. The study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for transparent reporting of observational cross-sectional research.

Statistical Testing

To enable consistent cross-state comparisons, the researchers first calculated the density of IBCLCs per 100,000 females of childbearing age (15‐49 years) using Microsoft Excel 2021 (Microsoft Corp).

Simple linear regression analyses were conducted in Python to evaluate the unadjusted relationship between IBCLC density and each of the 3 key breastfeeding outcomes:

1. Breastfeeding initiation.
2. Exclusive breastfeeding at 3 months.
3. Exclusive breastfeeding at 6 months.

Multiple linear regression was then used to control for potential confounding variables. The dependent (outcome) variables remained the same: breastfeeding initiation, exclusive breastfeeding at 3 months, and exclusive breastfeeding at 6 months. The independent variables in the adjusted models included:

• IBCLC population density (primary exposure)
• Average household income
• Proportion of the population without health insurance
• Proportion of the population with a bachelor’s degree or higher

These covariates were selected based on their theoretical importance as social determinants of health, supported by prior research linking these factors to maternal and infant health disparities [12]. Variables were added to the regression models simultaneously; no stepwise (forward or backward) selection methods were applied.

For each model, we report regression coefficients, P values, and adjusted R² values to assess the strength, significance, and explanatory power of the observed relationships.

For reader clarity, we have included definitions of relevant terms in Multimedia Appendix 1.

Results

The relevant demographic makeup for each state is shown in Table 1, along with measures for the United States on average.

The breastfeeding initiation, exclusivity at 3 months, and exclusivity at 6 months rates for each state and the United States averages are shown in Table 2.

The initiation rates range from 59.8% in West Virginia to 94% in Colorado. Exclusivity rates at 3 months range from 28% in West Virginia to 62.8% in Colorado. Exclusivity rates at 6 months range from 13.8% in West Virginia to 36.5% in Minnesota. The number of IBCLCs and IBCLC density in each state are shown in Table 3.

The average IBCLC density for the entire United States female childbearing age population is 25.5, while the state with the highest density of IBCLCs was Alaska at 60.7 and the lowest density was in Wyoming at 14.4.

The simple linear regression for IBCLC density and breastfeeding initiation shown in Table 4 yielded a correlation coefficient of 0.38 with a P value of <.001 and an R² of 0.26.

The simple linear regression for IBCLC density and exclusive breastfeeding at 3 months shown in Table 5 yielded a correlation coefficient of 0.52 with a P value of <.001 and an R² of 0.41.

The simple linear regression for IBCLC density and exclusive breastfeeding at 6 months shown in Table 6 yielded a correlation coefficient of 0.32 with a P value of <.001 and an R² of 0.41.

The multiple linear regression analysis for breastfeeding initiation shown in Table 7 has an adjusted R² of 0.44, and it produced a coefficient of 0.26 for IBCLC density with a P value of .005. Income had an extremely low coefficient of 0.0003 with a P value of .005. Lack of health insurance coverage yielded a very high coefficient of 47.93, but a P value of .14. Having a bachelor’s degree or higher yielded a coefficient of −6.05 and P value of .82.

The results for exclusive breastfeeding at 3 months shown in Table 8 are as follows: adjusted R²=0.42, IBCLC density coefficient=0.43 with P<.001, income coefficient=0.0002 with P=.20, lack of health insurance coefficient=−8.17 with P=.82, and bachelor’s degree or higher coefficient=−0.62 with P=.98.

Exclusive breastfeeding at 6 months results shown in Table 9 are as follows: adjusted R²=0.44, IBCLC density coefficient=0.25 with P<.001, income coefficient=0.0000 with P=.74, lack of health insurance coefficient=−15.34 with P=.49, and bachelor’s degree or higher coefficient=15.9 with P=.37.

Discussion

Principal Findings

This study found a positive association between the population density of IBCLCs and key breastfeeding outcomes in the United States, including initiation, exclusive breastfeeding at 3 months, and exclusive breastfeeding at 6 months (Multimedia Appendix 2). The strongest relationship was observed for exclusive breastfeeding at 3 months. These findings align with previous research showing that IBCLCs are associated with improved breastfeeding duration and exclusivity. For example, Patel and Patel [7] reported significant increases in breastfeeding rates when lactation support was provided in both hospital and community settings, and our findings reinforce the importance of IBCLC access beyond the point of care delivery. Similarly, Chrzan-Dętkoś et al [6] found that lactation consultations not only improved exclusivity but also maternal mental health, suggesting multifaceted benefits that may partly explain the state-level effects observed in our analysis.

Importantly, our study adds to this body of work by analyzing IBCLC density as a structural factor at the population level. Although Perrine et al [5] showed that hospital practices aligned with the Baby-Friendly Hospital Initiative improve exclusive breastfeeding intentions, our data demonstrate that widespread IBCLC availability across an entire state is similarly associated with improved breastfeeding metrics. This macro-level perspective complements prior individual-level studies and offers a broader lens on access equity.

These findings suggest that increased access to professional lactation support may play an important role in promoting breastfeeding continuation during the critical early months of infancy.

Comparison to Prior Work

The association between IBCLC density and breastfeeding outcomes identified in this study is consistent with literature emphasizing the clinical effectiveness of professional lactation support. Previous studies have documented improvements in breastfeeding duration and maternal confidence following targeted lactation interventions [6,7]. However, these studies were conducted in localized or clinical settings. Our analysis broadens this understanding by showing that even at the population level, the presence of IBCLCs is significantly associated with improved breastfeeding outcomes, indicating that workforce distribution matters as much as clinical quality.

Additionally, Rollins et al [1] emphasized how gaps in health system structures and commercial pressures undermine breastfeeding support globally. Our findings offer a US-specific parallel, suggesting that one way to counteract these systemic barriers is to increase the geographic accessibility of IBCLCs. Unlike initiatives limited to single institutions, the presence of IBCLCs across regions may mitigate inequities in maternal health resources.

Furthermore, while Perrine et al [5] focused on hospital practices, we extend their insights by suggesting that system-level workforce planning (ie, ensuring every region has adequate access to IBCLCs) could serve as a complementary public health strategy. By embedding our results in this broader context, we highlight how both institutional practices and population-based interventions may be needed to achieve national breastfeeding goals.

Strengths and Limitations

This study has several strengths. It draws from comprehensive, publicly available national datasets, applies both simple and multiple linear regression models, and includes key sociodemographic variables as potential confounders. This enhances the reliability of the observed associations and provides a foundation for future public health policy exploration.

However, several limitations must be acknowledged.

First, the study relies on secondary data sources, which limits the inclusion of other relevant variables such as cultural norms, maternity leave policies, or maternal health conditions. Attempts were made to address this through the inclusion of known confounders (income, education, and insurance status), but unmeasured variables likely remain.

Second, the focus on IBCLCs exclusively excludes other types of lactation support providers (eg, Certified Lactation Counselors; Women, Infants, and Children Peer Counselors), which may result in an underestimation of lactation support availability in some regions. This may particularly affect underserved areas where IBCLCs are sparse but alternative supports are present.

Third, the breastfeeding outcome data are based on parent-reported responses collected through telephone surveys, which may be susceptible to recall or social desirability bias. Although the CDC’s methods are well-established and designed to minimize such issues, this limitation is inherent in self-reported data.

Fourth, the analysis was conducted at the state level, which may obscure important regional disparities. Breastfeeding behaviors and IBCLC availability likely vary significantly within states, suggesting the need for future studies using data at the county or ZIP code level.

Future Directions

To build on these findings, future research should focus on more granular geographic data, such as IBCLC access by zip code or county, to better identify disparities masked by state-level averages. Linking provider registries with localized breastfeeding surveillance systems may also enhance understanding of the real-world accessibility of lactation support. Additionally, expanding the analysis to include other types of lactation professionals and examining awareness of services among postpartum individuals could provide valuable insights. Longitudinal research tracking changes in IBCLC workforce density and breastfeeding rates over time would further clarify the nature of these relationships.

Conclusions

Given that national breastfeeding rates remain subpar, widespread promotion of breastfeeding as the sociocultural norm is a paramount initiative. The statistical results of this research collectively indicate that IBCLC density plays a valuable role in promoting positive breastfeeding outcomes, even when considering potential confounding factors. The positive correlations between IBCLC density and breastfeeding rates at various time points are supported by the simple linear and multiple regression analyses, highlighting the significance of lactation consultants in achieving breastfeeding success. However, these findings should be interpreted in light of certain limitations, including the use of aggregated state-level data and exclusion of non-IBCLC lactation professionals. Future research would benefit from more granular geographic data, such as breastfeeding rates at the county or zip code level and IBCLC distribution. Such data would enable more precise correlation and may uncover regional disparities masked in state-level analysis. One approach to improve data granularity could involve integrating provider workforce registries with public health datasets at the substate level or collaborating with hospitals and health departments to collect real-time lactation support utilization data. Additionally, exploring longitudinal outcomes and incorporating combination feeding practices could enhance the ecological validity of future studies. Many mothers are not aware that they can receive comprehensive health care from a lactation consultant to prevent and solve breastfeeding complications. Even with a fair population density of IBCLCs in an area, not having an awareness of their services poses a barrier to that care. Improved public awareness and policy-level initiatives that fund and integrate IBCLCs into postnatal care structures may significantly boost breastfeeding continuation rates. Further research with more granular baseline data would be an excellent start for promoting the expansion of IBCLC care and improving breastfeeding rates.