2.1 Participants and procedure
In this prospective cohort study, two members of the research team recruited 320 pregnant women with singleton pregnancies at 35–37 weeks of gestation during their scheduled prenatal visits between September 2022 and March 2023 at Nanjing Maternity and Child Health Care Hospital. This hospital, designated as "baby-friendly" since 1993, delivers approximately 24,800 newborns annually. The inclusion criteria were as follows: women with a BMI of ≥18.5 kg/m² who expressed an intention to breastfeed, primiparas aged 20–35 years, and those who delivered healthy full-term newborns (≥ 37 weeks gestation). The exclusion criteria encompassed severe psychiatric illnesses, cardiovascular or pulmonary diseases, a history of breast surgery or injury, or a diagnosis of mammary dysplasia that could hinder the establishment of effective breastfeeding. All participants were followed for at least six months postpartum.
2.2 Measures
2.2.1 Independent variable
Pre-pregnancy BMI was directly obtained from the obstetric clinic’s system, and self-reported by the participants at their initial prenatal visit. Pre-pregnancy BMI was calculated as weight in kilograms divided by the square of height in meters (kg/m²) and classified according to Chinese standards into four categories: underweight (BMI < 18.5 kg/m²), normal BMI (BMI 18.5–23.9 kg/m²), overweight (BMI 24.0–27.9 kg/m²), and obese (BMI ≥ 28.0 kg/m²) [28]. For this study, participants were divided into two groups: normal BMI (BMI 18.5–23.9 kg/m²) and overweight/obese (BMI ≥ 24.0 kg/m²).
2.2.2 Dependent variables
The outcome analyzed in this study was exclusive breastfeeding up to 6 months postpartum. Exclusive breastfeeding status at this time point was assessed using a 7-day dietary recall method for infants, based on mothers’ self-reports concerning the frequency and amount of breastfeeding and formula milk supplementation. Infants solely receiving breast milk, with no intake of other solids or liquids over the previous 7 days, were classified as “exclusive breastfeeding.” Those who ingested any breast milk during the same timeframe were classified as “any breastfeeding.”
2.2.3 Potential mediating variables
2.2.3.1 IWS
IWS was assessed with the Weight Bias Internalization Scale (WBIS). WBIS offers a precise measure for assessing weight-bias internalization, clearly distinguishing this construct from anti-fat attitudes, self-esteem, and body image. This scale includes 11 items, each rated on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Reverse coding of two specific items (items 1 and 9) is required before summing the scores, which total up to a maximum of 55. The WBIS exhibits satisfactory internal consistency, with a Cronbach’s alpha of 0.9. Higher aggregate scores indicate a more pronounced internalization of weight stigma [12]. The Chinese version of the WBIS modifies the term “overweight” to “weight” to better suit individuals across various weight statuses. For example, the item “I hate myself for being overweight” is adapted to “I hate myself because of my weight.” The Chinese version of the WBIS demonstrates robust internal consistency in research conducted with Chinese children, adolescents, and postpartum populations [29, 30].
2.2.3.2 Breastfeeding difficulties
Drawing from the Breastfeeding Problems Inventory utilized in the research by O'Sullivan et al. [11], this study evaluated the extent of maternal breastfeeding difficulties at 6 months postpartum. If the mother discontinued breastfeeding within the first 6 months postpartum, difficulties encountered during the final period of breastfeeding should be reported. The questionnaire, having undergone expert validation and preliminary surveys, has been adapted to reflect the clinical realities of breastfeeding in China. It comprises 17 questions across four dimensions: insufficient milk production, breast dysfunction, infant feeding difficulties, and excessive lactation. During the survey, mothers were asked, “In the past week, have you experienced any of the following problems while breastfeeding your infant?” They were directed to identify applicable issues from a list of 17 potential breastfeeding problems, scoring each on a binary scale: 1 for “yes” and 0 for “no.” The total possible score ranges from 0 to 17, with higher scores indicating greater breastfeeding challenges faced by the mother.
2.2.3.3 Breastfeeding self-efficacy
To assess breastfeeding self-efficacy, we utilized the Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF), as developed by Dennis [31], which demonstrated excellent reliability with a Cronbach’s alpha of 0.927. This scale comprises 14 items, each scores on a 5-point Likert scale ranging from 1 (“completely lack confidence”) to 5 (“extremely confident”). Higher scores reflect greater self-efficacy in breastfeeding. The BSES-SF, which has undergone international validation, has been translated into multiple languages, such as Polish and Spanish [32, 33], with Cronbach’s alpha coefficients ranging from 0.85 to 0.95. The Chinese version of BSES-SF had good reliability and validity, with a Cronbach’s alpha coefficient of 0.927 [34].
2.2.4 Covariates
We utilized a multimodal data collection strategy encompassing structured interviews, self-administered questionnaires, and comprehensive review of medical records to assess confounders and precision variables. Sociodemographic variables were systematically recorded, including maternal age, educational attainment, employment status before pregnancy, household income, and gestational weight gain (GWG). We classified GWG as “inadequate”, “adequate”, or “excessive” according to the Institute of Medicine 2009 GWG guideline[35]. Postpartum data collection involved a detailed examination of medical records for each mother-infant dyad, documenting the mode of delivery, any complications arising during delivery, gestational age at birth, infant birth weight, and incidences of each mother-infant separation or neonatal complications.
2.3 Sample size estimation
We utilized Power Analysis & Sample Size (PASS) software version 15.0 (NCSS Statistical Software, LLC, Kaysville, UT, USA) to determine the required sample size, drawing on data from our previous study. In our previous study, the exclusive breastfeeding rate at 6 months postpartum was 14.0% among the overweight/obese group and 34.0% in the normal-BMI group. To ensure robust statistical power, we recruited women with pre-pregnancy overweight/obesity and normal BMI in a 1:1 ratio, targeting 90% power at a 5% significance level, and accounting for a potential 20% attrition rate. Consequently, a minimum of 89 participants per group was deemed necessary. Additionally, Kline suggested an acceptable sample size for studies using structural equation modeling (SEM), which is about 200 cases [36]. The sample for this study included 296 participants, exceeding both the previously determined sample size of 178 and the recommended threshold for SEM analysis.
2.4 Statistical analysis
We conducted primary analyses using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Preliminary analyses explored bivariate associations between pre-pregnancy overweight/obesity and other model variables. Our hypotheses were theoretically grounded and based on literature, and they were specified before data treatment. To test these hypotheses, we conducted SEM analyses using Mplus version 8.3.
This study aimed to clarify the mechanisms by which pre-pregnancy overweight/obesity, compared to women with normal BMI, influenced the rate of exclusive breastfeeding at 6 months postpartum. Pre-pregnancy BMI was considered as the independent variable (assigned as normal-BMI = 0, pre-pregnancy overweight/obesity = 1). IWS, breastfeeding difficulties, and breastfeeding self-efficacy were set as mediating variables. The binary outcome of exclusive breastfeeding at 6 months postpartum (non-exclusive = 0, exclusive = 1) served as the dependent variable. Using a multiple mediation model, we were able to uncover complex interaction pathways among variables, enhance the explanatory power of our analysis, and detect indirect effects through the interconnected influence of multiple mediators. We utilized SEM with maximum likelihood estimation, along with bias-corrected bootstrap testing provided by the Mplus 8.3 software package, to estimate and assess the mediation effects. Total effects (X on Y), direct effects (X on Y, adjusted for mediating effects), and specific indirect effects (X on Y through a specific mediator) were estimated with the use of a cumulative logistic regression-based, path-analytic framework. Mediation analyses incorporated a bias-corrected bootstrap method with 95% confidence intervals (CIs, 1,000 resamples) to estimate the magnitude of the total, direct, and indirect effects. The bootstrap method is the most extensively employed approach for directly testing the product of coefficients, ab, in mediation analysis. This method involves repeatedly drawing bootstrap samples and computing estimates of a and b, to derive the bootstrap 95% confidence interval for the product ab. If this confidence interval does not include zero, the mediating effect is deemed statistically significant; conversely, if the interval includes zero, the mediating effect is considered not significant. Furthermore, we controlled for the influence of potential confounders, such as gestational weight gain, mode of childbirth, comorbidity, and infant birth weight, in all mediation analyses. It should be noted, however, that the term “effect” referred to a statistical and not a causal effect in our mediation analysis.