Human Milk Oligosaccharides, Gut Bifidobacterium, Vitamin D, and Infant Immunity (HMO-BIFIDI)

Subject recruitment was conducted during immunization activities at community health centers (Puskesmas) and integrated health posts (Posyandu). The subject collection technique used the quota sampling method, a non-probability subject selection technique carried out by determining the desired sample size (quota) from a population with predetermined criteria, and researchers collected sample units until the target quota was reached. Researchers provided an explanation of the research protocol and obtained informed consent from participants regarding their willingness to participate in the study. Participants who met the eligibility criteria (inclusion and exclusion criteria) were declared as research subjects. Next, a research questionnaire was completed, including recording the subject's identity (mother and baby), the mother's health and nutritional history, childbirth and breastfeeding history, observation of the baby's stool, history and risk factors for allergies, and a general physical examination.

Mature breast milk samples will be analyzed to determine maternal secretion status, HMO status, Bifidobacterium in breast milk, and the status of immune markers such as sCD14, TGF-beta, and IgA in breast milk. Stool samples will be analyzed to determine the infant's intestinal Bifidobacterium. Blood samples will also be analyzed to determine vitamin D levels. Statistical correlations between these parameters will be performed to determine the research objectives.

The collected data is grouped based on the purpose and type of data, then the appropriate statistical method is selected, namely:

1. Univariate analysis (Used to describe basic data characteristics, in the form of frequency, mean value, standard deviation, and range)

2. Bivariate analysis

   1. Comparison Test (To see differences between groups)

      • Chi-Square Test → If the variable is categorical (e.g., the relationship between maternal secretory status (Secretory vs. Non-Secretory) and delivery method (Vaginal vs. Cesarean section). An alternative test, the Fisher's Exact test, is performed if the basic assumptions of the Chi-Square are not met.
      • T-Test (Independent T-Test) → If you want to compare the means of two groups (e.g., the difference in vitamin D levels between male and female infants). An alternative test, the Mann-Whitney test, is used if the data is not normally distributed.
      • ANOVA Test → If you want to compare the means of more than two groups (e.g., the difference in vitamin D levels based on the timing of early breastfeeding initiation: <1 hour, 1-6 hours, >6 hours). An alternative test, the Kruskal-Wallis test, is used if the data is not normally distributed.

   2. Correlation Analysis (To see the relationship between two numeric variables)

      • Pearson Correlation → If the data is normally distributed.
      • Spearman Correlation → If the data is not normally distributed or is ordinal