Breast milk dominant phyla and probiotic bacteria population in obese lactating women: a case-control study

Breast milk dominant phyla and probiotic bacteria population in obese lactating women: a case-control study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Article Breast milk dominant phyla and probiotic bacteria population in obese lactating women: a case-control study Shahla Karami, Seyedeh Neda Mousavi, Reza Shapouri, Hasti Naderloo, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4333651/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Background The main purpose was to determine amount of dominant phyla, Bifidobacteria and Lactobacillus in breast milk of obese mothers versus normal at 3rd of lactation in Iranian population. Methods Eighty health women at the third month of lactation, without any chronic, and gastrointestinal disorders were included and categorized base on body mass index (BMI) to two groups as obese (BMI ≥ 30 kg/m2) and normal (18.5 < BMI < 24.9). Bacterial DNA was extracted and qPCR of the 16S region was performed after human milk donation in sterile conditions. A linear regressions model was used to determine the baseline parameters on the population. Results Bifidobacteria population was significantly higher in normal group than obese mothers. Current BMI showed a significant effect on the Actinobacteria population in milk. Bacteroidetes and Firmicutes population were significantly lower in mother’s milk with cesarean delivery (p = 0.04). Pre-pregnancy obesity was associated with lower Firmicutes and Lactobacillus population in maternal milk (p = 0.04 and p = 0.01). A significant association was observed between the infant height with Actinobacteria and Bifidobacteria population of milk (p = 0.008 and p = 0.04). Conclusions Current and pre-pregnancy obesity are associated with lower beneficial phylum and probiotic bacteria in breast milk. Both of them are associated with infant’s height. Biological sciences/Microbiology Health sciences/Gastroenterology Health sciences/Health care Milk Bacterial phyla Probiotic bacteria obese Introduction Human breast milk is considered the best feeding for newborns up to the first six month due to its ability to provide complete needs of infant to growth. Despite the initial notions of being sterile, today breast milk is considered as a bio-fluid, which is a source of beneficial bacteria. Maternal, environmental and neonatal factors affect the composition of milk microbiota, and the transfer of these microorganisms during breastfeeding from mother to infant is an important factor determining the current health and in the future at adulthood ( 1 – 3 ). Bacterioidetes , Firmicutes , Actinobacteria , and the Proteobacteria are introduced as the main milk phylum ( 4 ). Moreover, Lactobacillus and Bifidobacteria genus, as the probiotic microflora, exert health-promoting effects for children ( 5 ). Despite the microbial variation during the lactation, a few cross-sectional studies assessed the effects of maternal body mass index and route of delivery on milk microbiota composition which samples have been collected various times after delivery ( 6 , 7 ). However, the results of these few studies are contradictory due to the difference in the sample collection method and the studied population. Recently, one study reported no significant association between maternal pre-pregnancy body mass index and mode of labor with milk microbial α-diversity however; it is associated with β-diversity. Bacterioidetes population was significantly increased, but the proteobacteria habitat decreased in milk of obese women than the overweight-one ( 8 ). Another study reported that maternal milk microbial composition in obese lactating mothers was differed depending the infant’s gender ( 9 ). Generally, gestational age, infant gender, route of delivery, mode of feeding, lactation stage, geographical location, maternal diet, social network density and maternal health status are important determinants of the microbial composition of human milk ( 10 ). Based on the literature review, no study was founded on the composition of human milk phyla in obese Iranian population, up to now. Considering the impact of maternal milk composition up to 100-days after birth on health status at adulthood, amount of maternal milk dominant phyla and probiotic bacteria was measured in lactating mothers at third month. The most predictors of this composition were determined. Materials and methods Study participants and sample collection The present study has been ethically approved by the ethics committee of Zanjan Azad University under the code of IR.IAU.Z.REC.1401.068. All methods were performed in accordance with the Helsinki guidelines and regulations. In the present case-control study, eighty mother-infant pairs were enrolled. Mothers aged 18–40 years, exclusively breast feeding, who had single birth and were attending to the health centers for the growth assessment living in Zanjan city with Iranian ethnicity were participated. Participants, who were not smoker, addict, or alcohol/drugs consumers were included. Participants were randomly assigned based on the current body mass index (BMI) status to normal (18.5 < BMI 30 kg/m 2 ) groups by dividing weight (kg) to height square (m) 2 ratio ( 11 ). Cluster sampling was used based on the geographical distribution and with the aim to cover all areas of the city. Participants were included in the study after obtaining oral, written informed consent and based on the inclusion criteria. Participants who consumed probiotic, prebiotic, symbiotic or antibiotics at least during the past two month were excluded. Participants with any type of chronic diseases including type 1 or 2 diabetes, renal, kidney, heart, immune, psychiatrics and thyroid disorders not included in the study. Any gastro-intestinal disorder including nausea, vomiting, diarrhea, constipation, celiac or any mal-absorptive and inflammatory situation were excluded. Women who had preterm labour did not include. Lactating women with a history of diabetes or hypertension during gestation were not included. Mothers with small and large newborns for gestational age were excluded. The maternal milk samples were collected in the morning at the health center after washing and sterilizing the hands, cleaning the nipples and the surrounding areas with chlorhexidine 2% solution prior to collecting 3–5 mL of milk in sterile falcons. All samples were collected from both breasts, manually. Before the DNA extraction, all samples were centrifuged at 5000 rpm for 20 min for fat separation and were stored at − 75°C. Demographic, dietary and anthropometric assessment The demographic and anthropometric measures of the participants including maternal age, education, mode of delivery, birth anthropometric indices including the weight, height and head circumference, and gender were recorded. Weight and height of mothers were measured using a calibrated scale, with minimal clothing and without shoes and an inflexible meter, without shoes in a standing state, look forward, respectively. A food frequency questionnaire (FFQ) was completed for all participants, validated by a three days food diary (two regular days and one holiday). To measure weight and length of infants without clothes and nappy, a calibrated seca baby scale (Harlow Healthcare, London, UK) and standard issue neonatometer (Harlow Health Care, London, UK) were used to the last 0.1 kg and 0.5 cm, respectively. Head circumference was measured by a flexible metal tape measure from the most prominent part of the forehead (1–2 fingers above the eyebrow) around to the widest part of the back of the head. ( 12 ). DNA extraction and polymerase chain reaction 200 µl milk sample, 200 µl binding buffer and 40 µl proteinase K were added to a 1.5 ml micro centrifuge tube, mixed immediately and incubated at 70°C for 10 min. Then, 100 µl isopropanol was added and mixed well. Samples were centrifuged at 8000 rpm for 1 min, after purification through filter inserted to collection tubes. Filter tubes were combined in a new collection tube, and 500 µl inhibitor removal buffers was added to the upper reservoir and centrifuged at 8000 rpm for 1 min. The last step was repeated two times by adding 500 µl washing buffer. After discarding the flow through, the entire high pure assembly was centrifuged for 10 seconds at full speed. To exclude the DNA, filter tube was inserted to a sterile 1.5 ml micro centrifuge tube, 200 µl pre-warmed elution buffer was added and centrifuged at 8000 rpm for 1 min. The DNA quality was examined by running a small amount on the agarose gel and concentration of the extracted DNA was determined by a Nano drop spectrophotometer. The extracted DNA was kept in -20°C refrigerator to final analysis. DNA Amplification of 16S rRNA gene was done by qPCR method using universal bacterial primers (5՜ to 3՜) as follows: the Firmicutes phylum; F: GGAGYATGTGGTTTAATTCGAAGCA, R: AGCTGACGACAACCATGCAC. The Bacterioidetes phylum; F: GGARCATGTGGTTTAATTCGATGAT, R: AGCTGACGACAACCATGCAG. The Actinobacteria phylum; F: TACGGCCGCAAGGCTA, R: TARTCCCCACCTTCCTCCG. Proteobacteria ; F: CATGACGTTACCCGCAGAAGAA, R: CTCTACGAGACTCAAGCTTGC. Bifidobacteria ; F: TCGCGTCYGGTGTGAAAG, R: CCACATCCAGCRTCCAC. Lactobacillus; F: AGCAGTAGGGAATCTTCCA, R:CACCGCTACACATGGAG These primers were verified in the primer-BLAST database of the National Center for Biotechnology Information (NCBI). ABI StepOne sequence detection system (Applied Biosystems, California, USA) was used for the real-time polymerase chain reaction (RT-PCR). 20 µL micro tubes were used, with 10 µL of SYBR Green Master Mix (Amplicon, Denmark), 4 µL of DNA template, and 0.5 µL of each forward and reverse primer. 5 µL purified water free of DNA and RNA was added. 16SrRNA was used as the positive control in each run and a blank (purified water free of DNA and RNA) was added for each bacterial phylum. The cycle threshold (CT) values were normalized against 16SrRNA as a negative control. The initial denaturation included one cycle: 95°C for 10 min. The amplification profile included 40 three-step cycles, including denaturation, annealing, and extension steps: 95°C for 30 s, 60°C for 30 s and 72°C for 30s. The final extension was provided in one cycle: 72°C for 30 s. The results were generated and analyzed using the 2 ^−∆∆Ct method in which ∆∆CT was computed as follows: ∆∆CT = (CT each bacterial phylum - CT 16SrRNA ) times X – (CT each bacterial phylum - CT 16SrRNA ) time0 Sample size and statistical analysis Considering the power of 80% and type 1 error, based on the previous study ( 13 ) on bacterial profile of human milk, forty participants were considered in each group. Dietary information was inserted into the N4 software (Nutritionist 4, USA). All dietary intakes converted to grams per day and data transferred to SPSS software, version 18. The Kolmogorov Smirnoff test was used to assess the distribution form of data. In normal distributed data, an independent sample t-test was used to determine differences between the two groups. However, non-parametric tests were used for non-normal distributed data. Qualitative variables were compared by the chi 2 square test. A linear regression model was used to determine the effect of each assessed parameter on the bacterial population, adjusting for others. Results Demographic and baseline data of participants have been shown in Table 1 . As shown, weight, BMI, and pre-pregnancy weight showed a significant difference between the two studied groups (p < 0.001 in all comparisons). Participants were matched by age and route of delivery. Obese mothers had more delivery than the normal group (p = 0.002). No significant difference was shown in the sex of newborns and maternal education. Not only birth weight, height and waist circumference was not significantly different between the two groups, but also they showed no difference three months after birth. Table 1 Demographic and baseline characteristics of mothers and infants in the two studied groups Variables groups Normal (n = 30) Means ± SE Obese (n = 30) Means ± SE p value † Mothers Age, yrs. 30.01 ± 1.02 32.03 ± 1.2 0.2 Current weight, kg 63.7 ± 1.4 79.1 ± 1.9 < 0.001 Pre-pregnancy weight, kg 61.4 ± 1.4 73.1 ± 2.05 < 0.001 Weight gain, kg 9.76 ± 0.45 11 ± 0.71 0.15 BMI, kg/m 2 24.1 ± 0.43 31.01 ± 0.7 < 0.001 Education Under diploma, n (%) 4 (13.3%) 11 (36.7%) 0.07 Diploma, n (%) 12 (40%) 9 (30%) University, n (%) 14 (46.7%) 10 (33.3%) Number of delivery 1st, n (%) 12 (40%) 13 (43.3%) 0.002 2nd, n (%) 16 (53.3%) 12 (40%) 3rd, n (%) 2 (6.7%) 5 (16.7%) Route of delivery Vaginal 14 (46.7%) 16 (53.3%) 0.6 Cesarean 16 (53.3%) 14 (46.7%) Infants Sex Boy, n (%) Girl, n (%) 20 (66.7%) 10 (33.3%) 13 (43.3%) 17 (56.7%) 0.43 Birth weight, kg 4 ± 0.8 4.4 ± 0.11 0.78 Birth height, cm 49.1 ± 0.3 49.3 ± 0.45 0.75 Birth head circumference, cm 34.9 ± 0.25 34.9 ± 0.26 0.8 Weight at 3 month, kg 6.8 ± 0.12 6.7 ± 0.19 0.91 Height at 3 month, cm 63.7 ± 0.38 63.7 ± 0.56 0.92 Head circumference at 3 month, cm 42.3 ± 0.75 41.4 ± .28 0.25 † assessed by independent sample t−test for quantitative and chi−square test for qualitative parameters Dietary intake of participants was compared and is shown in Table 2 . Normal group consumed more energy (p = 0.02), carbohydrate (p = 0.01), fiber (p = 0.01), and MUFAs (p = 0.009) in daily diet compared to the obese mothers. Other macronutrients showed no significant difference between the two groups. Table 2 Dietary intake of pregnant mothers in the two studied groups Variables groups Normal (n = 30) Means ± SE Obese (n = 30) Means ± SE p value Energy, kcal/day 2890.8 ± 98.4 2463.2 ± 142.1 0.02 Carbohydrates, g/day 368.8 ± 11.05 305.9 ± 20.6 0.01 Protein, g/day 106.3 ± 4.6 130.7 ± 9.9 0.2 Fiber, g/day 57.3 ± 2.6 44.2 ± 4.2 0.01 Fat, g/day 116.1 ± 6.1 112.5 ± 13.4 0.8 SFAs, g/day 37.7 ± 2.3 43.1 ± 9.8 0.59 MUFAs, g/day 35.8 ± 1.8 28.8 ± 1.8 0.009 PUFAs, g/day 18.4 ± 1.5 16.4 ± 1.1 0.27 Cholesterol, mg/day 341.04 ± 23.3 323.5 ± 25.7 0.61 † assessed by independent sample t−test The milk dominant phyla were compared between the two groups. As shown in Table 3 , no significant difference was shown on the milk phylum population including Bacteroidetes , Firmicutes, Actinobacteria and Proteobacteria population between the two groups. But, the Bifidobacteria population was significantly higher in the milk of normal mothers than the obese-one (p = 0.04). Table 3 Profile of gut bacterial phyla and some species in the two studied groups Variables groups Normal (n = 30) Means ± SE Obese (n = 30) Means ± SE P value Bacteroidetes 2.4 ± 0.45 1.9 ± 0.45 0.46 Firmicutes 3.1 ± 1.1 2.88 ± 0.56 0.87 Actinobacteria 1.9 ± 0.35 3.4 ± 0.94 0.13 Proteobacteria 2.78 ± 0.71 1.98 ± 0.55 0.38 Bifidobacteria 4.6 ± 1.4 2.05 ± 0.42 0.04 Lactobacillus 2.4 ± 0.53 2.04 ± 0.32 0.55 † assessed by Mann−Whitney test To determine the effect of the baseline assessed parameters and dietary components on the milk phyla and some species, a linear regression model was used. Route of delivery showed a significant effect on Bacteroidetes (OR=-0.35, 95% CI:-3.4, -0.01; p = 0.04), and Firmicutes (OR=-0.29, 95% CI:-6.2,-0.43; p = 0.04) population in maternal milk. Maternal pre-pregnancy weight showed a significant negative effect on Firmicutes population (OR=-0.62, 95%CI: -0.5, -0.01, p = 0.04) (Tables 4 & 5 ). Milk Actinobacteria population was significantly higher in normal mothers than obese by 39% (95%CI: 0.06, 9.6; p = 0.03). In addition, milk Actinobacteria population was significantly higher in mothers with girl than the boys by 59% (95%CI: 0.35, 6.3; p = 0.03). A significant association was observed between the infant height and Actinobacteria population in milk (OR=-0.67, 95%CI: -1.7, -0.29; p = 0.008). Higher dietary intake of SFAs decreased Actinobacteria population by 68% (95%CI: 0.07, 0.003; p = 0.04) (Table 6 ). The birth height of infants showed a negative association with Proteobacteria population in maternal milk (OR=-0.4, 95%CI: -1.36, -0.03; p = 0.03) (Table 7 ). At the species level, higher number of delivery decreased Bifidobacteria population in the milk of mothers by 50% (95%CI: -8.2, -0.32; p = 0.03). Bifidobacteria population was significantly lower in the milk of mothers with boy infants than the girls (OR= -0.52, 95%CI: -10.3, -2.002; p = 0.005). Infant height showed a significant association with the population of Bifidobacteria in maternal milk (OR = 0.47, 95%CI: 0.02, 2.06; p = 0.04). Moreover, maternal pre-pregnancy weight showed a significant effect on Lactobacillus population in maternal milk (OR = 0.75, 95%CI: 0.04, 0.028; p = 0.01). Table 4 Effect of the assessed parameters on the milk Bacterioidetes population Variables B ± SE OR ‡ p value † 95% CI Group -2 ± 1.5 -0.4 0.21 -5.2, 1.24 Route of delivery -1.7 ± 0.8 -0.35 0.04 -3.4, -0.01 BMI, kg/m 2 0.3 ± 0.23 0.57 0.2 -0.16, 0.77 Age, yrs 0.09 ± 0.1 0.23 0.4 -0.12, 0.31 Pre-pregnancy weight, kg -0.02 ± 0.07 -0.08 0.8 -0.15, 0.12 Current weight, kg -0.08 ± 0.09 -0.38 0.39 -0.26, 0.1 sxzWeight gain, kg 0.03 ± 0.11 0.04 0.8 -0.2, 0.27 Education -0.05 ± 0.69 -0.02 0.94 -1.5, 1.3 Number of delivery -0.14 ± 0.92 -0.04 0.88 -2.02, 1.7 Sex 0.5 ± 0.98 0.09 0.62 -1.5, 2.4 Birth weight, kg 3.67 ± 0.01 0.078 0.62 0.00, 0.00 Infant weight, kg 0.1 ± 0.04 4.55 0.24 0.003, 0.2 Birth height, cm 0.11 ± 0.23 0.09 0.63 -0.36, 0.58 Infant height, cm -0.28 ± 0.24 -0.3 0.24 -0.78, 0.2 Energy, kcal/d 0.001 ± 0.003 0.07 0.9 -0.005, 0.006 Protein, g/d -0.001 ± 0.003 -0.2 0.62 -0.006, 0.004 Carbohydrate, g/d 0.005 ± 0.01 0.21 0.71 -0.02, 0.03 Fat, g/day -0.001 ± 0.02 -0.03 0.96 -0.055, 0.05 Fiber, g/d -0.05 ± 0.03 -0.43 0.16 -0.13, 0.02 SFAs, g/d 0.005 ± 0.01 0.08 0.65 -0.02, 0.03 MUFAs, g/d -0.06 ± 0.06 -0.27 0.32 -0.19, 0.06 PUFAs, g/d 0.005 ± 0.07 0.01 0.95 -0.15, 0.16 Cholesterol, mg/d 0.005 ± 0.004 0.28 0.22 -0.003, 0.014 † assessed by a linear regression model; ‡ OR: odds ratio; SFAs: saturated fatty acids; MUFA: mono−unsaturated fatty acids; PUFA: poly−unsaturated fatty acids Table 5 Effect of the assessed parameters on the milk Firmicutes population Variables B ± SE OR ‡ p value † 95% CI Group -1.3 ± 3.1 -0.13 0.68 -7.5, 5.02 Route of delivery -2.9 ± 1.6 -0.29 0.04 -6.2, -0.43 BMI, kg/m 2 0.72 ± 0.44 0.67 0.12 -0.18, 1.6 Age, yrs 0.29 ± 0.21 0.35 0.17 -0.13, 0.71 Pre-pregnancy weight, kg -0.3 ± 0.13 -0.62 0.04 -0.5, -0.01 Current weight, kg -0.006 ± 0.17 -0.01 0.97 -0.36, 0.35 Weight gain, kg -0.14 ± 0.23 -0.09 0.53 -0.6, 0.32 Education 0.05 ± 1.3 0.008 0.97 -2.7, 2.8 Number of delivery -1.2 ± 1.8 -0.17 0.49 -4.9, 2.4 Sex 2.3 ± 1.9 0.22 0.24 -1.6, 6.1 Birth weight, kg 8.44 ± 0.0001 0.09 0.56 0.00, 0.00 Infant weight, kg 0.001 ± 0.001 0.26 0.2 0.00, 0.004 Birth height, cm -0.17 ± 0.45 -0.07 0.71 -1.1, 0.75 Infant height, cm -0.52 ± 0.47 -0.28 0.27 -1.5, 0.43 Energy, kcal/d 0.001 ± 0.005 -0.08 0.9 -0.01, 0.1 Protein, g/d -0.008 ± 0.005 -0.61 0.62 -0.006, 0.004 Carbohydrate, g/d 0.005 ± 0.01 0.21 0.11 -0.02, 0.002 Fat, g/day 0.05 ± 0.05 0.6 0.31 -0.05, 0.15 Fiber, g/d -0.07 ± 0.07 -0.28 0.34 -0.21, 0.07 SFAs, g/d -0.007 ± 0.02 -0.05 0.75 -0.05, 0.04 MUFAs, g/d 0.08 ± 0.12 0.17 0.52 -0.17, 0.33 PUFAs, g/d -0.04 ± 0.14 -0.06 0.7 -0.33, 0.25 Cholesterol, mg/d -0.006 ± 0.008 -0.15 0.48 -0.02, 0.01 † assessed by a linear regression model; ‡ OR: odds ratio; SFAs: saturated fatty acids; MUFA: mono−unsaturated fatty acids; PUFA: poly−unsaturated fatty acids Table 6 Effect of the assessed parameters on the milk Actinobacteria population Variables B ± SE OR ‡ p value † 95% CI Group 4.8 ± 2.4 0.61 0.03 0.06, 9.6 Route of delivery -2.02 ± 1.2 -0.26 0.11 -4.6, 0.53 BMI, kg/m 2 -0.5 ± 0.34 -0.6 0.15 -1.2, 0.2 Age, yrs 0.03 ± 0.16 0.04 0.85 -0.29, 0.35 Pre-pregnancy weight, kg -0.07 ± 0.1 -0.2 0.5 -0.3, 0.13 Current weight, kg 0.15 ± 0.13 0.45 0.28 -0.12, 0.42 Weight gain, kg -0.11 ± 0.17 -0.09 0.53 -0.46, 0.24 Education -0.44 ± 1.03 -0.08 0.67 -2.5, 1.7 Number of delivery 1.5 ± 1.4 0.26 0.27 -1.3, 4.3 Sex 3.3 ± 1.4 0.41 0.03 0.35, 6.3 Birth weight, kg 15.2 ± 0.0001 0.02 0.89 0.00, 0.00 Infant weight, kg 0.001 ± 0.001 0.12 0.53 -0.001, 0.002 Birth height, cm 0.26 ± 0.35 0.14 0.45 -0.44, 0.97 Infant height, cm -1.02 ± 0.36 -0.67 0.008 -1.7, -0.29 Energy, kcal/d -0.004 ± 0.004 -0.68 0.33 -0.01, 0.004 Protein, g/d -0.005 ± 0.004 -0.5 0.18 -0.01, 0.003 Carbohydrate, g/d 0.02 ± 0.02 0.55 0.3 -0.02, 0.07 Fat, g/day 0.03 ± 0.04 0.5 0.38 -0.04, 0.11 Fiber, g/d -0.04 ± 0.05 -0.22 0.44 -0.15, 0.07 SFAs, g/d -0.03 ± 0.02 -0.32 0.04 0.07, 0.003 MUFAs, g/d 0.08 ± 0.12 0.17 0.52 -0.17, 0.33 PUFAs, g/d 0.07 ± 0.11 0.12 0.55 -0.16, 0.29 Cholesterol, mg/d -0.009 ± 0.006 -0.32 0.14 -0.02, 0.003 † assessed by a linear regression model; ‡ OR: odds ratio; SFAs: saturated fatty acids; MUFA: mono−unsaturated fatty acids; PUFA: poly−unsaturated fatty acids Table 7 Effect of the assessed parameters on the milk Proteobacteria population Variables B ± SE OR ‡ p value † 95% CI Group -1.6 ± 2.2 -0.23 0.47 -6.1, 2.9 Route of delivery -0.83 ± 1.1 -0.12 0.48 -3.2, 1.6 BMI, kg/m 2 0.47 ± 0.32 0.62 0.15 -0.18, 1.1 Age, yrs 0.15 ± 0.15 0.26 0.32 -0.15, 0.45 Pre-pregnancy weight, kg -0.008 ± 0.09 -0.02 0.9 -0.2, 0.18 Current weight, kg -0.15 ± 0.12 -0.53 0.23 -0.41, 0.1 Weight gain, kg -0.21 ± 0.16 -0.2 0.2 -0.55, 0.12 Education 0.3 ± 0.97 0.07 0.75 -1.7, 2.3 Number of delivery -0.66 ± 1.3 -0.13 0.61 -3.3, 1.96 Sex 1.5 ± 1.4 0.2 0.28 -1.3, 4.25 Birth weight, kg 15.2 ± 0.0001 0.02 0.89 0.00, 0.00 Infant weight, kg 0.001 ± 0.001 0.2 0.19 -0.001, 0.002 Birth height, cm -0.7 ± 0.32 -0.4 0.03 -1.36, -0.03 Infant height, cm 0.16 ± 0.33 0.12 0.65 -0.5, 0.84 Energy, kcal/d 0.001 ± 0.004 0.07 0.9 -0.007, 0.008 Protein, g/d -0.005 ± 0.004 -0.5 0.18 -0.01, 0.003 Carbohydrate, g/d 0.001 ± 0.02 -0.01 0.98 -0.02, 0.07 Fat, g/day -0.01 ± 0.04 -0.15 0.79 -0.08, 0.06 Fiber, g/d -0.02 ± 0.05 -0.15 0.6 -0.13, 0.08 SFAs, g/d 0.002 ± 0.02 0.02 0.9 -0.03, 0.03 MUFAs, g/d 0.01 ± 0.08 0.04 0.9 -0.16, 0.19 PUFAs, g/d -0.02 ± 0.1 -0.03 0.87 -0.23, 0.2 Cholesterol, mg/d -0.002 ± 0.006 -0.09 0.68 -0.01, 0.009 † assessed by a linear regression model; ‡ OR: odds ratio; SFAs: saturated fatty acids; MUFA: mono−unsaturated fatty acids; PUFA: poly−unsaturated fatty acids Discussion Despite the Bifidobacteria genus, other breast milk phyla and lactobacillus showed no significant difference between obese and normal mothers. Adjusting for all parameters, current and pre-pregnancy obesity associated with lower Actinobacteria and Bifidobacteria , as the beneficial phyla and genus on health that both of them showed a significant association with infant’s height. Pre-pregnancy obesity associated with lower Lactobacillus in milk of mothers. Moreover, mothers with girls had higher the Actinobacteria and Bifidobacteria population in their milk than mothers with boys. Bacteroidetes and Firmicutes population were lower in milk of mothers with cesarean section. Higher dietary intake of SFAs decreased the Actinobacteria population in breast milk. Early-life gut microbiota affects health and risk of chronic diseases in future life. Its colonization and composition are determined by the milk microbiome. Exclusive breast-feeding are encouraged due to bioactive, hormonal and nutritional components in human milk, which contribute to infant’s health ( 14 , 15 ). The development of gut microbiota begins at birth and continues to be shaped until 2–3 years old. After this period, reach a relatively stable level that makeup the adult taxonomic microbiome ( 16 ). Previous study reported that the fecal Bacteroidetes population was correlated with the pre-pregnancy BMI, current BMI, waist circumference, and percentage of body fat ( 17 – 21 ). Moreover, a higher Bacteroides genus belonging to the Bacteroidetes phyla was found in the feces of pregnant women with normal pre-pregnancy weight compared to overweight ( 22 ). Our results showed no difference in the Bacterioidetes population because we analyzed the milk samples, not feces. Moreover, current weight was considered to categorize participants in each group. In our study, maternal pre-pregnancy weight affected the Actinobacteria and Bifidobacteria population in milk that is similar to the mentioned studies regarding the Actinobacteria . Three different hypotheses including entero-mammary, the retrograde inoculation pathways and resident mammary microbiota have been proposed to explain the microbe’s residence in milk. The entero-mammary pathway points the translocation of maternal gut bacteria to the mammary glands through openings in tight junctions of epithelial cells created by the dendritic cells and possibly macrophages. Hormonal changes during the last month of pregnancy provide this condition that help travelling of dendritic cells through the lymphatic and blood circulation to the mammary ducts where they release the bacteria in the milk ( 23 ). However, maternal skin, infant oral cavity and environment are other sources of bacteria presenting in breast milk including Staphylococcus and Corynebacterium belonging to the Firmicutes a nd Actinobacteria , respectively that explain the retrograde backflow during breastfeeding ( 24 , 25 ). It is noted that presence of anaerobes such as Bifidobacteria and Faecalibacterium genera in breast milk cannot fully explained by the retrograde inoculation pathway. This means that both pathways may be potential sources of the breast milk microbiota ( 26 ). One study reported that maternal diet shapes the composition of breast milk microbiota. Carbohydrate intake was associated with Staphylococcus and Bifidobacteria genera in the milk, but the Streptococcus genus was correlated to omega-3 fatty acids in diet. The effect of diet on milk microbiota was founded in mothers with cesarean section, not vaginal delivery. Lactobacillus, Bacteroides , and Sediminibacterium genera were decreased in milk of mothers consuming higher animal and fat sources that delivered their baby by cesarean section ( 27 ). Our results showed that higher SFA intake negatively affected Actinobacteria abundance in maternal milk. Breast milk sampling was performed during 7–15 days after birth in the mentioned study; however, we collected samples at third months of lactation. Differences in the lactation period effect on milk microbiota, because bacterial population differ during the various stages. Moreover, dietary pattern and intake of food groups are different among various countries that make inconsistencies. Bifidobacerium belong to Actinobacteria phylum were significantly lower in milk of obese mothers than normal. Increase in the gut’s Bifidobacteria genera has been associated with a lower risk of childhood disorders including infections, atopic disorders, and obesity ( 28 , 29 ). Bifidobacteria in the gut makes the presence of other microbes correlated to health ( 30 ). Previous studies have been reported the protective effects of Bifidobacteria in infants from prevalence of obesity, diabetes, metabolic disorder, and all-cause mortality later in life ( 31 – 33 ). This means that maternal obesity during lactation predisposes infants to all chronic diseases in future. Substantial evidence indicates that total fat, saturated-, omega-3 and omega-6 fatty acids, and microbiome diversity are associated with maternal weight status ( 34 , 35 ). This was the first analytical observational study on the microbial composition of milk in lactating women living in Iran with a special diet, geographical location and ethnicity. There are some limitations like all studies. The case-control design makes us unable to determine the causal-relationship. Moreover, infant’s fecal microbiota must be assessing to determine the association of infant gut microbiota with maternal milk. Intervention studies with special diets are encouraged to manipulate maternal milk bacterial composition and abundance to make this bio-fluid healthier for infants. Moreover, studies on the associations between the breast-milk Bifidobacteria with neurodevelopmental complications are encouraged. In summary, the main milk phylum and probiotic bacteria population were assessed in milk of obese versus normal lactating mothers. Bifidobacteria , as beneficial probiotic bacteria, was lower in milk of obese mothers. Current and pre-pregnancy obesity showed an inverse association with population of beneficial phylum and probiotic bacteria in breast milk. Both of them showed a significant association with infant’s height. Infant’s height is a main determinant of health and diseases in future. Further dipper investigations are needed to understand the main pathways and effective factors on milk phylum considering dietary habits and environmental exposures. Declarations Conflict of interest There is no conflict of interest to declare. Author Contribution SN. M conceptualized and supervised the project, data analysis, and interpretation, and revise of the manuscript. Sh. K did the human intervention study, quantitative and qualitative analysis andwrote the first draft of manuscript. R. Sh. conceptualized and supervised the project andcontributed to data interpretation. H.N. did the human intervention study and the manuscript. S.H advised the project and contributed to data interpretation and the manuscript. D. A. advised theproject and contributed to data interpretation and the manuscript. Acknowledgements All authors are very thankful from lactating women who were participated in the present study. Data Availability The data that support the findings of this study are available from the corresponding author uponreasonable request. References Lyons KE, Ryan CA, Dempsey EM, Ross RP, Stanton C. Breast Milk, a Source of Beneficial Microbes and Associated Benefits for Infant Health. Nutrients . 2020; 12(4):1039. Hermansson H, Kumar H, Collado M.C, Salminen S, Isolauri E, Rautava S. Breast milk microbiota is shaped by mode of delivery and intrapartum antibiotic exposure. Front. Nutr. 2019; 6:4. Papachatzi E, Dimitriou G, Dimitropoulos K, Vantarakis A. Pre-pregnancy obesity: Maternal, neonatal and childhood outcomes. J. Neonatal-Perinat. Med. 2013;6:203–216. Agha-Jaffar R, Oliver N, Johnston D, Robinson S. Gestational diabetes mellitus: does an effective prevention strategy exist? Endocrinology . 2016;12:533–546. Łubiech K, Twarużek M. Lactobacillus Bacteria in Breast Milk. Nutrients . 2020; 12(12):3783. Eyupoglu ND, Caliskan Guzelce E, Acikgoz A, Uyanik E, Bjørndal B, Berge RK, et al. Circulating gut microbiota metabolite trimethylamine N-oxide and oral contraceptive use in polycystic ovary syndrome. Clin Endocrinol (Oxford). 2019;91:810–815. Zhou L , Xiao X , Zhang Q , Zheng J , Li M , Wang X , et al. Gut microbiota might be a crucial factor in deciphering the metabolic benefits of perinatal genistein consumption in dams and adult female offspring. Food Funct . 2019;10:4505. Simpson SSL, Bowe J. Placental peptides regulating islet adaptation to pregnancy: clinical potential in gestational diabetes mellitus. Curr Opin Pharmacol . 2018;43:59–65. C Urbaniak, M Angelini, GB Gloor, G. Reid. Human milk microbiota profiles in relation to birthing method, gestation and infant gender. Microbiome . 2016; 4: 1. Anastasia Mantziari, Samuli Rautava. Factors influencing the microbial composition of human milk. Seminars in Perinatology . 2021; 45 (8):151507. Diario Oficial de la Federación NORMA Oficial Mexicana NOM-043-SSA2-2012, Servicios Básicos de Salud. Promoción y Educación Para la Salud en Materia Alimentaria. Criterios Para Brindar Orientación. [(accessed on 8 February 2022)];2013 Available online: https://www.dof.gob.mx/nota_detalle.php?codigo=5285372&fecha=22/01/2013#gsc.tab=0 Bryant M, Santorelli G, Fairley L, Petherick ES, Bhopal R, Lawlor DA, Tilling K, Howe LD, Farrar D, Cameron N, Mohammed M, Wright J; Born in Bradford Childhood Obesity Scientific Group. Agreement between routine and research measurement of infant height and weight. Arch Dis Child . 2015;100(1):24-9. Cheema AS, Gridneva Z, Furst AJ, Roman AS, Trevenen ML, Turlach BA, Lai CT, Stinson LF, Bode L, Payne MS, Geddes DT. Human Milk Oligosaccharides and Bacterial Profile Modulate Infant Body Composition during Exclusive Breastfeeding. Int J Mol Sci . 2022; 23(5):2865. Chong H.Y, Tan L, Law J, Hong K, Ratnasingam V, Ab Mutalib N, Lee L, Letchumanan V. Exploring the potential of human milk and formula milk on infant’s gut and health. Nutrients . 2022; 14 (7): 3554. World Health Organization. Exclusive Breastfeeding for Six Months Best for Babies Everywhere. Available online: https://www.who.int/news/item/15-01-2011-exclusive -breastfeeding-for-six-months-best-for-babies-everywhere (accessed on 18 April 2022). Koo H, Crossman D.K, Morrow C.D. Strain tracking to identify individualized patterns of microbial strain stability in the developing infant gut ecosystem. Fron. Pediatrics . 2020; 8: 549844. Chavoya-Guardado MA, Vasquez-Garibay EM, Ruiz-Quezada SL, Ramírez-Cordero MI, Larrosa-Haro A, Castro-Albarran J. Firmicutes , Bacteroidetes and Actinobacteria in Human Milk and Maternal Adiposity. Nutrients. 2022;14(14):2887. Koliada A, Syzenko G, Moseiko V, Budovska L, Puchkov K, Perederiy V, et al. Association between body mass index and Firmicutes/Bacteroidetes ratio in an adult Ukrainian population. BMC Microbiol. 2017;1:120. Kumar H, du Toit E, Kulkarni A, Aakko J, Linderborg K.M, Zhang Y, et al. Distinct Patterns in Human Milk Microbiota and Fatty Acid Profiles across Specific Geographic Locations. Front. Microbiol. 2016;7:1619. Eckburg P.B, Bik E.M, Bernstein C.N, Purdom E, Dethlesfsen L, Sargent M, et al. Diversity of the Human Intestinal Microbial Flora. Science. 2005;308:1635–1638. Riva A, Borgo F, Lassandro C, Verduci E, Morace G, Borghi E, et al. Pediatric obesity is associated with an altered gut microbiota and discordant shifts in Firmicutes populations. Environ. Microbiol. 2017;19:95–105. Collado M.C, Isolauri E, Laitinen K, Salminen S. Distinct Composition of Gut Microbiota during Pregnancy in Overweight and Normal-Weight Women. Am. J. Clin. Nutr. 2008;88:894–899. Rodríguez JM. The origin of human milk bacteria: is there a bacterial entero-mammary pathway during late pregnancy and lactation? Adv Nutr . 2014;5(6):779-84. Lee JE, Kim GB. Human Milk Microbiota: A Review. J Dairy Sci Biotechnol . 2019;37(1):15-26. Togo A, Dufour JC, Lagier JC, Dubourg G, Raoult D, Million M. Repertoire of human breast and milk microbiota: a systematic review. Future Microbiol . 2019;14:623-641. Gueimonde M, Laitinen K, Salminen S, Isolauri E. Breast milk: a source of bifidobacteria for infant gut development and maturation? Neonatology . 2007;92(1):64-6. Cortes-Macías E, Selma-Royo M, García-Mantrana I, Calatayud M, González S, Martínez-Costa C, Collado MC. Maternal Diet Shapes the Breast Milk Microbiota Composition and Diversity: Impact of Mode of Delivery and Antibiotic Exposure. J Nutr . 2021;151(2):330-340. Akay H.K, Bahar Tokman H, Hatipoglu N, Hatipoglu H, Siraneci R, Demirci M, et al. The relationship between bifidobacteria and allergic asthma and/or allergic dermatitis: A prospective study of 0–3 years-old children in Turkey. Anaerobe . 2014; 28: 98–103. Dogra S, Sakwinska O, Soh S-E, Ngom-Bru C, Brück W.M, Berger B, et al. Dynamics of infant gut microbiota are influenced by delivery mode and gestational duration and are associated with subsequent adiposity. MBio . 2015; 6: e02419-14. Stanford J, Charlton K, Stefoska-Needham A, Ibrahim R, Lambert K. The gut microbiota profile of adults with kidney disease and kidney stones: A systematic review of the literature. BMC Nephrol . 2020; 21:215. Milani C, Duranti S, Bottacini F, Casey E, Turroni F, Mahony J, et al. The first microbial colonizers of the human gut: Composition, activities, and health implications of the infant gut microbiota. Microbiol. Mol. Biol. Rev . 2017; 81:e00036-17. Sutharsan R, Mannan M, Doi S.A, Al Mamun A. Caesarean delivery and the risk of offspring overweight and obesity over the life course: A systematic review and bias-adjusted meta-analysis. Clin. Obes . 2015;5:293–301. Korpela K, Zijlmans M.A.C, Kuitunen M, Kukkonen K, Savilahti E, Salonen A, et al. Childhood BMI in relation to microbiota in infancy and lifetime antibiotic use. Microbiome . 2017;5:26. Makela J, Linderborg K, Niinikoski H, Yang B, Lagstrom H. Breast milk fatty acid composition differs between overweight and normal weight women: The STEPS Study. Eur J Nutr 2013;52(2):727–35. Cabrera-Rubio R, Collado MC, Laitinen K, Salminen S, Isolauri E, Mira A. The human milk microbiome changes over lactation and is shaped by maternal weight and mode of delivery. Am J Clin Nutr . 2012;96(3):544– 51. Additional Declarations No competing interests reported. Supplementary Files Graphicalabstract.png Graphical abstract Cite Share Download PDF Status: Published Journal Publication published 19 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 29 Jul, 2024 Reviews received at journal 22 Jul, 2024 Reviewers agreed at journal 11 Jul, 2024 Reviews received at journal 01 Jul, 2024 Reviewers agreed at journal 06 Jun, 2024 Reviewers agreed at journal 23 May, 2024 Reviewers invited by journal 10 May, 2024 Editor assigned by journal 10 May, 2024 Editor invited by journal 02 May, 2024 Submission checks completed at journal 02 May, 2024 First submitted to journal 27 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4333651","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":299428339,"identity":"311bb74d-8198-4717-a1e2-3e2194e72535","order_by":0,"name":"Shahla Karami","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shahla","middleName":"","lastName":"Karami","suffix":""},{"id":299428341,"identity":"612bccb8-0291-4eec-bec0-84a11d1ab4a0","order_by":1,"name":"Seyedeh Neda Mousavi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYHACAzjrwAcsgvi1HJxBshZmHmJcZc7evPEDY45N4vz2M4aHbf4cjpZvYH74gaHgHk4tlj3HiiUYt6UlbjiTY3A4h+dw7oYDbMYSDAbFuF11I8cAqOVw4gaGtITDORJALQwMZkDxBNxa7r8x/gHSMr//WcJhC4PDufMb2L/h13KDxwxsS8ON5AOHGRIO5zYc4CFgy5m0MovEbWnGG248PnCw50B67obDPMUSCfi0HD+8+cbHbTay8/sTmz/8+GOdO7+9feOHD39wawEDVGlmDJFRMApGwSgYBaQCAC2FWIbX82saAAAAAElFTkSuQmCC","orcid":"","institution":"Zanjan University of Medical Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Seyedeh","middleName":"Neda","lastName":"Mousavi","suffix":""},{"id":299428342,"identity":"d94db288-f7ec-488a-98cd-bdbd0137bb64","order_by":2,"name":"Reza Shapouri","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Reza","middleName":"","lastName":"Shapouri","suffix":""},{"id":299428344,"identity":"db26560f-ce34-4348-9f6b-0c735dca4fc5","order_by":3,"name":"Hasti Naderloo","email":"","orcid":"","institution":"Zanjan University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hasti","middleName":"","lastName":"Naderloo","suffix":""},{"id":299428346,"identity":"6e9f321c-9d7d-4e97-b17a-5766ee47b8a6","order_by":4,"name":"Siamak Heidarzadeh","email":"","orcid":"","institution":"Zanjan University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Siamak","middleName":"","lastName":"Heidarzadeh","suffix":""},{"id":299428348,"identity":"5df46ba2-a23f-45e8-8564-1ba32b52446e","order_by":5,"name":"Davoud Afshar","email":"","orcid":"","institution":"Zanjan University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Davoud","middleName":"","lastName":"Afshar","suffix":""}],"badges":[],"createdAt":"2024-04-27 10:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4333651/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4333651/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-70070-w","type":"published","date":"2024-08-19T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63300692,"identity":"94e397a5-686e-43c4-8b6f-e08a6dbd8a4f","added_by":"auto","created_at":"2024-08-26 16:16:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":944721,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4333651/v1/051d6237-4e1b-42ff-b813-08feede608fc.pdf"},{"id":56087097,"identity":"4e739082-a794-4c90-9327-25f32eed50f9","added_by":"auto","created_at":"2024-05-08 11:20:10","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":121206,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical abstract\u003c/p\u003e","description":"","filename":"Graphicalabstract.png","url":"https://assets-eu.researchsquare.com/files/rs-4333651/v1/8cfe68835a33698f1fb16424.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Breast milk dominant phyla and probiotic bacteria population in obese lactating women: a case-control study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman breast milk is considered the best feeding for newborns up to the first six month due to its ability to provide complete needs of infant to growth. Despite the initial notions of being sterile, today breast milk is considered as a bio-fluid, which is a source of beneficial bacteria. Maternal, environmental and neonatal factors affect the composition of milk microbiota, and the transfer of these microorganisms during breastfeeding from mother to infant is an important factor determining the current health and in the future at adulthood (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). \u003cem\u003eBacterioidetes\u003c/em\u003e, \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eActinobacteria\u003c/em\u003e, and the \u003cem\u003eProteobacteria\u003c/em\u003e are introduced as the main milk phylum (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Moreover, \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003eBifidobacteria\u003c/em\u003e genus, as the probiotic microflora, exert health-promoting effects for children (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Despite the microbial variation during the lactation, a few cross-sectional studies assessed the effects of maternal body mass index and route of delivery on milk microbiota composition which samples have been collected various times after delivery (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, the results of these few studies are contradictory due to the difference in the sample collection method and the studied population. Recently, one study reported no significant association between maternal pre-pregnancy body mass index and mode of labor with milk microbial α-diversity however; it is associated with β-diversity. \u003cem\u003eBacterioidetes\u003c/em\u003e population was significantly increased, but the \u003cem\u003eproteobacteria\u003c/em\u003e habitat decreased in milk of obese women than the overweight-one (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Another study reported that maternal milk microbial composition in obese lactating mothers was differed depending the infant\u0026rsquo;s gender (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Generally, gestational age, infant gender, route of delivery, mode of feeding, lactation stage, geographical location, maternal diet, social network density and maternal health status are important determinants of the microbial composition of human milk (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Based on the literature review, no study was founded on the composition of human milk phyla in obese Iranian population, up to now. Considering the impact of maternal milk composition up to 100-days after birth on health status at adulthood, amount of maternal milk dominant phyla and probiotic bacteria was measured in lactating mothers at third month. The most predictors of this composition were determined.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants and sample collection\u003c/h2\u003e \u003cp\u003e The present study has been ethically approved by the ethics committee of Zanjan Azad University under the code of IR.IAU.Z.REC.1401.068. All methods were performed in accordance with the Helsinki guidelines and regulations. In the present case-control study, eighty mother-infant pairs were enrolled. Mothers aged 18\u0026ndash;40 years, exclusively breast feeding, who had single birth and were attending to the health centers for the growth assessment living in Zanjan city with Iranian ethnicity were participated. Participants, who were not smoker, addict, or alcohol/drugs consumers were included. Participants were randomly assigned based on the current body mass index (BMI) status to normal (18.5\u0026thinsp;\u0026lt;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e) or high (BMI\u0026thinsp;\u0026gt;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e) groups by dividing weight (kg) to height square (m)\u003csup\u003e2\u003c/sup\u003e ratio (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Cluster sampling was used based on the geographical distribution and with the aim to cover all areas of the city. Participants were included in the study after obtaining oral, written informed consent and based on the inclusion criteria. Participants who consumed probiotic, prebiotic, symbiotic or antibiotics at least during the past two month were excluded. Participants with any type of chronic diseases including type 1 or 2 diabetes, renal, kidney, heart, immune, psychiatrics and thyroid disorders not included in the study. Any gastro-intestinal disorder including nausea, vomiting, diarrhea, constipation, celiac or any mal-absorptive and inflammatory situation were excluded. Women who had preterm labour did not include. Lactating women with a history of diabetes or hypertension during gestation were not included. Mothers with small and large newborns for gestational age were excluded. The maternal milk samples were collected in the morning at the health center after washing and sterilizing the hands, cleaning the nipples and the surrounding areas with chlorhexidine 2% solution prior to collecting 3\u0026ndash;5 mL of milk in sterile falcons. All samples were collected from both breasts, manually. Before the DNA extraction, all samples were centrifuged at 5000 rpm for 20 min for fat separation and were stored at \u0026minus;\u0026thinsp;75\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDemographic, dietary and anthropometric assessment\u003c/h2\u003e \u003cp\u003eThe demographic and anthropometric measures of the participants including maternal age, education, mode of delivery, birth anthropometric indices including the weight, height and head circumference, and gender were recorded. Weight and height of mothers were measured using a calibrated scale, with minimal clothing and without shoes and an inflexible meter, without shoes in a standing state, look forward, respectively. A food frequency questionnaire (FFQ) was completed for all participants, validated by a three days food diary (two regular days and one holiday). To measure weight and length of infants without clothes and nappy, a calibrated seca baby scale (Harlow Healthcare, London, UK) and standard issue neonatometer (Harlow Health Care, London, UK) were used to the last 0.1 kg and 0.5 cm, respectively. Head circumference was measured by a flexible metal tape measure from the most prominent part of the forehead (1\u0026ndash;2 fingers above the eyebrow) around to the widest part of the back of the head. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction and polymerase chain reaction\u003c/h2\u003e \u003cp\u003e200 \u0026micro;l milk sample, 200 \u0026micro;l binding buffer and 40 \u0026micro;l proteinase K were added to a 1.5 ml micro centrifuge tube, mixed immediately and incubated at 70\u0026deg;C for 10 min. Then, 100 \u0026micro;l isopropanol was added and mixed well. Samples were centrifuged at 8000 rpm for 1 min, after purification through filter inserted to collection tubes. Filter tubes were combined in a new collection tube, and 500 \u0026micro;l inhibitor removal buffers was added to the upper reservoir and centrifuged at 8000 rpm for 1 min. The last step was repeated two times by adding 500 \u0026micro;l washing buffer. After discarding the flow through, the entire high pure assembly was centrifuged for 10 seconds at full speed. To exclude the DNA, filter tube was inserted to a sterile 1.5 ml micro centrifuge tube, 200 \u0026micro;l pre-warmed elution buffer was added and centrifuged at 8000 rpm for 1 min. The DNA quality was examined by running a small amount on the agarose gel and concentration of the extracted DNA was determined by a Nano drop spectrophotometer. The extracted DNA was kept in -20\u0026deg;C refrigerator to final analysis. DNA Amplification of 16S rRNA gene was done by qPCR method using universal bacterial primers (5՜ to 3՜) as follows: the \u003cem\u003eFirmicutes\u003c/em\u003e phylum; F: GGAGYATGTGGTTTAATTCGAAGCA, R: AGCTGACGACAACCATGCAC. The \u003cem\u003eBacterioidetes\u003c/em\u003e phylum; F: GGARCATGTGGTTTAATTCGATGAT, R: AGCTGACGACAACCATGCAG. The \u003cem\u003eActinobacteria\u003c/em\u003e phylum; F: TACGGCCGCAAGGCTA, R: TARTCCCCACCTTCCTCCG. \u003cem\u003eProteobacteria\u003c/em\u003e; F: CATGACGTTACCCGCAGAAGAA, R: CTCTACGAGACTCAAGCTTGC. \u003cem\u003eBifidobacteria\u003c/em\u003e; F: TCGCGTCYGGTGTGAAAG, R: CCACATCCAGCRTCCAC. \u003cem\u003eLactobacillus;\u003c/em\u003e F: AGCAGTAGGGAATCTTCCA, R:CACCGCTACACATGGAG\u003c/p\u003e \u003cp\u003eThese primers were verified in the primer-BLAST database of the National Center for Biotechnology Information (NCBI). ABI StepOne sequence detection system (Applied Biosystems, California, USA) was used for the real-time polymerase chain reaction (RT-PCR).\u003c/p\u003e \u003cp\u003e20 \u0026micro;L micro tubes were used, with 10 \u0026micro;L of SYBR Green Master Mix (Amplicon, Denmark), 4 \u0026micro;L of DNA template, and 0.5 \u0026micro;L of each forward and reverse primer. 5 \u0026micro;L purified water free of DNA and RNA was added. 16SrRNA was used as the positive control in each run and a blank (purified water free of DNA and RNA) was added for each bacterial phylum.\u003c/p\u003e \u003cp\u003eThe cycle threshold (CT) values were normalized against 16SrRNA as a negative control. The initial denaturation included one cycle: 95\u0026deg;C for 10 min. The amplification profile included 40 three-step cycles, including denaturation, annealing, and extension steps: 95\u0026deg;C for 30 s, 60\u0026deg;C for 30 s and 72\u0026deg;C for 30s. The final extension was provided in one cycle: 72\u0026deg;C for 30 s. The results were generated and analyzed using the 2\u003csup\u003e^\u0026minus;∆∆Ct\u003c/sup\u003e method in which ∆∆CT was computed as follows:\u003c/p\u003e \u003cp\u003e∆∆CT = (CT \u003csub\u003eeach bacterial phylum\u003c/sub\u003e- CT \u003csub\u003e16SrRNA\u003c/sub\u003e) \u003csub\u003etimes X\u003c/sub\u003e \u0026ndash; (CT \u003csub\u003eeach bacterial phylum\u003c/sub\u003e- CT \u003csub\u003e16SrRNA\u003c/sub\u003e) \u003csub\u003etime0\u003c/sub\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSample size and statistical analysis\u003c/h2\u003e \u003cp\u003eConsidering the power of 80% and type 1 error, based on the previous study (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) on bacterial profile of human milk, forty participants were considered in each group. Dietary information was inserted into the N4 software (Nutritionist 4, USA). All dietary intakes converted to grams per day and data transferred to SPSS software, version 18. The Kolmogorov Smirnoff test was used to assess the distribution form of data. In normal distributed data, an independent sample t-test was used to determine differences between the two groups. However, non-parametric tests were used for non-normal distributed data. Qualitative variables were compared by the chi\u003csup\u003e2\u003c/sup\u003e square test. A linear regression model was used to determine the effect of each assessed parameter on the bacterial population, adjusting for others.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDemographic and baseline data of participants have been shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. As shown, weight, BMI, and pre-pregnancy weight showed a significant difference between the two studied groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 in all comparisons). Participants were matched by age and route of delivery. Obese mothers had more delivery than the normal group (p\u0026thinsp;=\u0026thinsp;0.002). No significant difference was shown in the sex of newborns and maternal education. Not only birth weight, height and waist circumference was not significantly different between the two groups, but also they showed no difference three months after birth.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and baseline characteristics of mothers and infants in the two studied groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables groups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003cp\u003eMeans\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObese (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003cp\u003eMeans\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMothers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-pregnancy weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder diploma, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiploma, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNumber of delivery\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1st, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (40%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eRoute of delivery\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (46.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfants\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003cp\u003eBoy, n (%)\u003c/p\u003e \u003cp\u003eGirl, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (66.7%)\u003c/p\u003e \u003cp\u003e10 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (43.3%)\u003c/p\u003e \u003cp\u003e17 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth head circumference, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight at 3 month, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight at 3 month, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead circumference at 3 month, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.4\u0026thinsp;\u0026plusmn;\u0026thinsp;.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csub\u003eassessed by independent sample t\u0026minus;test for quantitative and chi\u0026minus;square test for qualitative parameters\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDietary intake of participants was compared and is shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Normal group consumed more energy (p\u0026thinsp;=\u0026thinsp;0.02), carbohydrate (p\u0026thinsp;=\u0026thinsp;0.01), fiber (p\u0026thinsp;=\u0026thinsp;0.01), and MUFAs (p\u0026thinsp;=\u0026thinsp;0.009) in daily diet compared to the obese mothers. Other macronutrients showed no significant difference between the two groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDietary intake of pregnant mothers in the two studied groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables groups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003cp\u003eMeans\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObese (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003cp\u003eMeans\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy, kcal/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2890.8\u0026thinsp;\u0026plusmn;\u0026thinsp;98.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2463.2\u0026thinsp;\u0026plusmn;\u0026thinsp;142.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrates, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e368.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e305.9\u0026thinsp;\u0026plusmn;\u0026thinsp;20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e106.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e130.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e57.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e44.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e116.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e112.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFAs, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e37.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e43.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFAs, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFAs, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e18.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e16.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol, mg/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e341.04\u0026thinsp;\u0026plusmn;\u0026thinsp;23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e323.5\u0026thinsp;\u0026plusmn;\u0026thinsp;25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csub\u003eassessed by independent sample t\u0026minus;test\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe milk dominant phyla were compared between the two groups. As shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, no significant difference was shown on the milk phylum population including \u003cem\u003eBacteroidetes\u003c/em\u003e, \u003cem\u003eFirmicutes, Actinobacteria and Proteobacteria\u003c/em\u003e population between the two groups. But, the \u003cem\u003eBifidobacteria\u003c/em\u003e population was significantly higher in the milk of normal mothers than the obese-one (p\u0026thinsp;=\u0026thinsp;0.04).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProfile of gut bacterial phyla and some species in the two studied groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables groups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003cp\u003eMeans\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObese (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003cp\u003eMeans\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacteroidetes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFirmicutes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eActinobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProteobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBifidobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLactobacillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csub\u003eassessed by Mann\u0026minus;Whitney test\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo determine the effect of the baseline assessed parameters and dietary components on the milk phyla and some species, a linear regression model was used. Route of delivery showed a significant effect on \u003cem\u003eBacteroidetes\u003c/em\u003e (OR=-0.35, 95% CI:-3.4, -0.01; p\u0026thinsp;=\u0026thinsp;0.04), and \u003cem\u003eFirmicutes\u003c/em\u003e (OR=-0.29, 95% CI:-6.2,-0.43; p\u0026thinsp;=\u0026thinsp;0.04) population in maternal milk. Maternal pre-pregnancy weight showed a significant negative effect on \u003cem\u003eFirmicutes\u003c/em\u003e population (OR=-0.62, 95%CI: -0.5, -0.01, p\u0026thinsp;=\u0026thinsp;0.04) (Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u0026amp; \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Milk \u003cem\u003eActinobacteria\u003c/em\u003e population was significantly higher in normal mothers than obese by 39% (95%CI: 0.06, 9.6; p\u0026thinsp;=\u0026thinsp;0.03). In addition, milk \u003cem\u003eActinobacteria\u003c/em\u003e population was significantly higher in mothers with girl than the boys by 59% (95%CI: 0.35, 6.3; p\u0026thinsp;=\u0026thinsp;0.03). A significant association was observed between the infant height and \u003cem\u003eActinobacteria\u003c/em\u003e population in milk (OR=-0.67, 95%CI: -1.7, -0.29; p\u0026thinsp;=\u0026thinsp;0.008). Higher dietary intake of SFAs decreased \u003cem\u003eActinobacteria\u003c/em\u003e population by 68% (95%CI: 0.07, 0.003; p\u0026thinsp;=\u0026thinsp;0.04) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The birth height of infants showed a negative association with \u003cem\u003eProteobacteria\u003c/em\u003e population in maternal milk (OR=-0.4, 95%CI: -1.36, -0.03; p\u0026thinsp;=\u0026thinsp;0.03) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). At the species level, higher number of delivery decreased \u003cem\u003eBifidobacteria\u003c/em\u003e population in the milk of mothers by 50% (95%CI: -8.2, -0.32; p\u0026thinsp;=\u0026thinsp;0.03). \u003cem\u003eBifidobacteria\u003c/em\u003e population was significantly lower in the milk of mothers with boy infants than the girls (OR= -0.52, 95%CI: -10.3, -2.002; p\u0026thinsp;=\u0026thinsp;0.005). Infant height showed a significant association with the population of \u003cem\u003eBifidobacteria\u003c/em\u003e in maternal milk (OR\u0026thinsp;=\u0026thinsp;0.47, 95%CI: 0.02, 2.06; p\u0026thinsp;=\u0026thinsp;0.04). Moreover, maternal pre-pregnancy weight showed a significant effect on \u003cem\u003eLactobacillus\u003c/em\u003e population in maternal milk (OR\u0026thinsp;=\u0026thinsp;0.75, 95%CI: 0.04, 0.028; p\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of the assessed parameters on the milk \u003cem\u003eBacterioidetes\u003c/em\u003e population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-5.2, 1.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoute of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.4, -0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.16, 0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.12, 0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-pregnancy weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.15, 0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.26, 0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esxzWeight gain, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.2, 0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.5, 1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.02, 1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.5, 2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00, 0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003, 0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.36, 0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.78, 0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy, kcal/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.005, 0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.006, 0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02, 0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.055, 0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.13, 0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02, 0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.19, 0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.15, 0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol, mg/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.003, 0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csub\u003eassessed by a linear regression model;\u003c/sub\u003e \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003csub\u003eOR: odds ratio; SFAs: saturated fatty acids; MUFA: mono\u0026minus;unsaturated fatty acids; PUFA: poly\u0026minus;unsaturated fatty acids\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of the assessed parameters on the milk \u003cem\u003eFirmicutes\u003c/em\u003e population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-7.5, 5.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoute of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-6.2, -0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.18, 1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.13, 0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-pregnancy weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.5, -0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.006\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.36, 0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.6, 0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.7, 2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.9, 2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.6, 6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00, 0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00, 0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.1, 0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.5, 0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy, kcal/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.01, 0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.008\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.006, 0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02, 0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.05, 0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.21, 0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.007\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.05, 0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.17, 0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.33, 0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol, mg/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.006\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02, 0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csub\u003eassessed by a linear regression model;\u003c/sub\u003e \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003csub\u003eOR: odds ratio; SFAs: saturated fatty acids; MUFA: mono\u0026minus;unsaturated fatty acids; PUFA: poly\u0026minus;unsaturated fatty acids\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of the assessed parameters on the milk \u003cem\u003eActinobacteria\u003c/em\u003e population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06, 9.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoute of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-2.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.6, 0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.2, 0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.29, 0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-pregnancy weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.3, 0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.12, 0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.46, 0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.5, 1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.3, 4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.35, 6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00, 0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.001, 0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.44, 0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.7, -0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy, kcal/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.01, 0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.01, 0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02, 0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.04, 0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.15, 0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.07, 0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.17, 0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.16, 0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol, mg/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.009\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02, 0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csub\u003eassessed by a linear regression model;\u003c/sub\u003e \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003csub\u003eOR: odds ratio; SFAs: saturated fatty acids; MUFA: mono\u0026minus;unsaturated fatty acids; PUFA: poly\u0026minus;unsaturated fatty acids\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of the assessed parameters on the milk \u003cem\u003eProteobacteria\u003c/em\u003e population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-6.1, 2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoute of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.2, 1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.18, 1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.15, 0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-pregnancy weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.008\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.2, 0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.41, 0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.55, 0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.7, 2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.3, 1.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.3, 4.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00, 0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant weight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.001, 0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.36, -0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant height, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.5, 0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy, kcal/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.007, 0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.005\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.01, 0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02, 0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat, g/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.08, 0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.13, 0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.002\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.03, 0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.16, 0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFAs, g/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.23, 0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol, mg/d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.002\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.01, 0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003csub\u003eassessed by a linear regression model;\u003c/sub\u003e \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003csub\u003eOR: odds ratio; SFAs: saturated fatty acids; MUFA: mono\u0026minus;unsaturated fatty acids; PUFA: poly\u0026minus;unsaturated fatty acids\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDespite the \u003cem\u003eBifidobacteria\u003c/em\u003e genus, other breast milk phyla and \u003cem\u003elactobacillus\u003c/em\u003e showed no significant difference between obese and normal mothers. Adjusting for all parameters, current and pre-pregnancy obesity associated with lower \u003cem\u003eActinobacteria\u003c/em\u003e and \u003cem\u003eBifidobacteria\u003c/em\u003e, as the beneficial phyla and genus on health that both of them showed a significant association with infant\u0026rsquo;s height. Pre-pregnancy obesity associated with lower \u003cem\u003eLactobacillus\u003c/em\u003e in milk of mothers. Moreover, mothers with girls had higher the \u003cem\u003eActinobacteria\u003c/em\u003e and \u003cem\u003eBifidobacteria\u003c/em\u003e population in their milk than mothers with boys. \u003cem\u003eBacteroidetes\u003c/em\u003e and \u003cem\u003eFirmicutes\u003c/em\u003e population were lower in milk of mothers with cesarean section. Higher dietary intake of SFAs decreased the \u003cem\u003eActinobacteria\u003c/em\u003e population in breast milk. Early-life gut microbiota affects health and risk of chronic diseases in future life. Its colonization and composition are determined by the milk microbiome. Exclusive breast-feeding are encouraged due to bioactive, hormonal and nutritional components in human milk, which contribute to infant\u0026rsquo;s health (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The development of gut microbiota begins at birth and continues to be shaped until 2\u0026ndash;3 years old. After this period, reach a relatively stable level that makeup the adult taxonomic microbiome (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Previous study reported that the fecal \u003cem\u003eBacteroidetes\u003c/em\u003e population was correlated with the pre-pregnancy BMI, current BMI, waist circumference, and percentage of body fat (\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Moreover, a higher \u003cem\u003eBacteroides\u003c/em\u003e genus belonging to the \u003cem\u003eBacteroidetes\u003c/em\u003e phyla was found in the feces of pregnant women with normal pre-pregnancy weight compared to overweight (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Our results showed no difference in the \u003cem\u003eBacterioidetes\u003c/em\u003e population because we analyzed the milk samples, not feces. Moreover, current weight was considered to categorize participants in each group. In our study, maternal pre-pregnancy weight affected the \u003cem\u003eActinobacteria\u003c/em\u003e and \u003cem\u003eBifidobacteria\u003c/em\u003e population in milk that is similar to the mentioned studies regarding the \u003cem\u003eActinobacteria\u003c/em\u003e. Three different hypotheses including entero-mammary, the retrograde inoculation pathways and resident mammary microbiota have been proposed to explain the microbe\u0026rsquo;s residence in milk. The entero-mammary pathway points the translocation of maternal gut bacteria to the mammary glands through openings in tight junctions of epithelial cells created by the dendritic cells and possibly macrophages. Hormonal changes during the last month of pregnancy provide this condition that help travelling of dendritic cells through the lymphatic and blood circulation to the mammary ducts where they release the bacteria in the milk (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). However, maternal skin, infant oral cavity and environment are other sources of bacteria presenting in breast milk including \u003cem\u003eStaphylococcus\u003c/em\u003e and \u003cem\u003eCorynebacterium\u003c/em\u003e belonging to the \u003cem\u003eFirmicutes a\u003c/em\u003end \u003cem\u003eActinobacteria\u003c/em\u003e, respectively that explain the retrograde backflow during breastfeeding (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). It is noted that presence of anaerobes such as \u003cem\u003eBifidobacteria\u003c/em\u003e and \u003cem\u003eFaecalibacterium\u003c/em\u003e genera in breast milk cannot fully explained by the retrograde inoculation pathway. This means that both pathways may be potential sources of the breast milk microbiota (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). One study reported that maternal diet shapes the composition of breast milk microbiota. Carbohydrate intake was associated with \u003cem\u003eStaphylococcus\u003c/em\u003e and \u003cem\u003eBifidobacteria\u003c/em\u003e genera in the milk, but the \u003cem\u003eStreptococcus\u003c/em\u003e genus was correlated to omega-3 fatty acids in diet. The effect of diet on milk microbiota was founded in mothers with cesarean section, not vaginal delivery. \u003cem\u003eLactobacillus, Bacteroides\u003c/em\u003e, and \u003cem\u003eSediminibacterium\u003c/em\u003e genera were decreased in milk of mothers consuming higher animal and fat sources that delivered their baby by cesarean section (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Our results showed that higher SFA intake negatively affected \u003cem\u003eActinobacteria\u003c/em\u003e abundance in maternal milk. Breast milk sampling was performed during 7\u0026ndash;15 days after birth in the mentioned study; however, we collected samples at third months of lactation. Differences in the lactation period effect on milk microbiota, because bacterial population differ during the various stages. Moreover, dietary pattern and intake of food groups are different among various countries that make inconsistencies. \u003cem\u003eBifidobacerium\u003c/em\u003e belong to \u003cem\u003eActinobacteria\u003c/em\u003e phylum were significantly lower in milk of obese mothers than normal. Increase in the gut\u0026rsquo;s \u003cem\u003eBifidobacteria\u003c/em\u003e genera has been associated with a lower risk of childhood disorders including infections, atopic disorders, and obesity (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). \u003cem\u003eBifidobacteria\u003c/em\u003e in the gut makes the presence of other microbes correlated to health (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Previous studies have been reported the protective effects of \u003cem\u003eBifidobacteria\u003c/em\u003e in infants from prevalence of obesity, diabetes, metabolic disorder, and all-cause mortality later in life (\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). This means that maternal obesity during lactation predisposes infants to all chronic diseases in future. Substantial evidence indicates that total fat, saturated-, omega-3 and omega-6 fatty acids, and microbiome diversity are associated with maternal weight status (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis was the first analytical observational study on the microbial composition of milk in lactating women living in Iran with a special diet, geographical location and ethnicity. There are some limitations like all studies. The case-control design makes us unable to determine the causal-relationship. Moreover, infant\u0026rsquo;s fecal microbiota must be assessing to determine the association of infant gut microbiota with maternal milk. Intervention studies with special diets are encouraged to manipulate maternal milk bacterial composition and abundance to make this bio-fluid healthier for infants. Moreover, studies on the associations between the breast-milk \u003cem\u003eBifidobacteria\u003c/em\u003e with neurodevelopmental complications are encouraged. In summary, the main milk phylum and probiotic bacteria population were assessed in milk of obese \u003cem\u003eversus\u003c/em\u003e normal lactating mothers. \u003cem\u003eBifidobacteria\u003c/em\u003e, as beneficial probiotic bacteria, was lower in milk of obese mothers. Current and pre-pregnancy obesity showed an inverse association with population of beneficial phylum and probiotic bacteria in breast milk. Both of them showed a significant association with infant\u0026rsquo;s height. Infant\u0026rsquo;s height is a main determinant of health and diseases in future. Further dipper investigations are needed to understand the main pathways and effective factors on milk phylum considering dietary habits and environmental exposures.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThere is no conflict of interest to declare.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSN. M conceptualized and supervised the project, data analysis, and interpretation, and revise of the manuscript. Sh. K did the human intervention study, quantitative and qualitative analysis andwrote the first draft of manuscript. R. Sh. conceptualized and supervised the project andcontributed to data interpretation. H.N. did the human intervention study and the manuscript. S.H advised the project and contributed to data interpretation and the manuscript. D. A. advised theproject and contributed to data interpretation and the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eAll authors are very thankful from lactating women who were participated in the present study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author uponreasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLyons KE, Ryan CA, Dempsey EM, Ross RP, Stanton C. Breast Milk, a Source of Beneficial Microbes and Associated Benefits for Infant Health. \u003cem\u003eNutrients\u003c/em\u003e. 2020; 12(4):1039.\u003c/li\u003e\n\u003cli\u003eHermansson H, Kumar H, Collado M.C, Salminen S, Isolauri E, Rautava S. Breast milk microbiota is shaped by mode of delivery and intrapartum antibiotic exposure. \u003cem\u003eFront. Nutr. \u003c/em\u003e2019; 6:4. \u003c/li\u003e\n\u003cli\u003ePapachatzi E, Dimitriou G, Dimitropoulos K, Vantarakis A. Pre-pregnancy obesity: Maternal, neonatal and childhood outcomes. \u003cem\u003eJ. Neonatal-Perinat. Med. \u003c/em\u003e2013;6:203\u0026ndash;216.\u003c/li\u003e\n\u003cli\u003eAgha-Jaffar R, Oliver N, Johnston D, Robinson S. Gestational diabetes mellitus: does an effective prevention strategy exist? \u003cem\u003eEndocrinology\u003c/em\u003e. 2016;12:533\u0026ndash;546.\u003c/li\u003e\n\u003cli\u003eŁubiech K, Twarużek M. \u003cem\u003eLactobacillus\u003c/em\u003e Bacteria in Breast Milk. \u003cem\u003eNutrients\u003c/em\u003e. 2020; 12(12):3783.\u003c/li\u003e\n\u003cli\u003eEyupoglu ND, Caliskan Guzelce E, Acikgoz A, Uyanik E, Bj\u0026oslash;rndal B, Berge RK, et al. Circulating gut microbiota metabolite trimethylamine N-oxide and oral contraceptive use in polycystic ovary syndrome. \u003cem\u003eClin Endocrinol\u003c/em\u003e (Oxford). 2019;91:810\u0026ndash;815.\u003c/li\u003e\n\u003cli\u003eZhou L , Xiao X , Zhang Q , Zheng J , Li M , Wang X , et al. Gut microbiota might be a crucial factor in deciphering the metabolic benefits of perinatal genistein consumption in dams and adult female offspring. \u003cem\u003eFood Funct\u003c/em\u003e. 2019;10:4505.\u003c/li\u003e\n\u003cli\u003eSimpson SSL, Bowe J. Placental peptides regulating islet adaptation to pregnancy: clinical potential in gestational diabetes mellitus. \u003cem\u003eCurr Opin Pharmacol\u003c/em\u003e. 2018;43:59\u0026ndash;65.\u003c/li\u003e\n\u003cli\u003eC Urbaniak, M Angelini, GB Gloor, G. Reid. Human milk microbiota profiles in relation to birthing method, gestation and infant gender. \u003cem\u003eMicrobiome\u003c/em\u003e. 2016; 4: 1.\u003c/li\u003e\n\u003cli\u003eAnastasia Mantziari, Samuli Rautava. Factors influencing the microbial composition of human milk. \u003cem\u003eSeminars in Perinatology\u003c/em\u003e. 2021; 45 (8):151507.\u003c/li\u003e\n\u003cli\u003eDiario Oficial de la Federaci\u0026oacute;n NORMA Oficial Mexicana NOM-043-SSA2-2012, Servicios B\u0026aacute;sicos de Salud. Promoci\u0026oacute;n y Educaci\u0026oacute;n Para la Salud en Materia Alimentaria. Criterios Para Brindar Orientaci\u0026oacute;n. [(accessed on 8 February 2022)];2013 Available online: https://www.dof.gob.mx/nota_detalle.php?codigo=5285372\u0026amp;fecha=22/01/2013#gsc.tab=0\u003c/li\u003e\n\u003cli\u003eBryant M, Santorelli G, Fairley L, Petherick ES, Bhopal R, Lawlor DA, Tilling K, Howe LD, Farrar D, Cameron N, Mohammed M, Wright J; Born in Bradford Childhood Obesity Scientific Group. Agreement between routine and research measurement of infant height and weight. \u003cem\u003eArch Dis Child\u003c/em\u003e. 2015;100(1):24-9.\u003c/li\u003e\n\u003cli\u003eCheema AS, Gridneva Z, Furst AJ, Roman AS, Trevenen ML, Turlach BA, Lai CT, Stinson LF, Bode L, Payne MS, Geddes DT. Human Milk Oligosaccharides and Bacterial Profile Modulate Infant Body Composition during Exclusive Breastfeeding. \u003cem\u003eInt J Mol Sci\u003c/em\u003e. 2022; 23(5):2865.\u003c/li\u003e\n\u003cli\u003eChong H.Y, Tan L, Law J, Hong K, Ratnasingam V, Ab Mutalib N, Lee L, Letchumanan V. Exploring the potential of human milk and formula milk on infant\u0026rsquo;s gut and health. \u003cem\u003eNutrients\u003c/em\u003e. 2022; 14 (7): 3554.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Exclusive Breastfeeding for Six Months Best for Babies Everywhere. Available online: https://www.who.int/news/item/15-01-2011-exclusive -breastfeeding-for-six-months-best-for-babies-everywhere (accessed on 18 April 2022). \u003c/li\u003e\n\u003cli\u003eKoo H, Crossman D.K, Morrow C.D. Strain tracking to identify individualized patterns of microbial strain stability in the developing infant gut ecosystem. \u003cem\u003eFron. Pediatrics\u003c/em\u003e. 2020; 8: 549844. \u003c/li\u003e\n\u003cli\u003eChavoya-Guardado MA, Vasquez-Garibay EM, Ruiz-Quezada SL, Ram\u0026iacute;rez-Cordero MI, Larrosa-Haro A, Castro-Albarran J. \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eBacteroidetes\u003c/em\u003e and \u003cem\u003eActinobacteria\u003c/em\u003e in Human Milk and Maternal Adiposity. Nutrients. 2022;14(14):2887. \u003c/li\u003e\n\u003cli\u003eKoliada A, Syzenko G, Moseiko V, Budovska L, Puchkov K, Perederiy V, et al. Association between body mass index and \u003cem\u003eFirmicutes/Bacteroidetes\u003c/em\u003e ratio in an adult Ukrainian population. \u003cem\u003eBMC Microbiol. \u003c/em\u003e2017;1:120. \u003c/li\u003e\n\u003cli\u003eKumar H, du Toit E, Kulkarni A, Aakko J, Linderborg K.M, Zhang Y, et al. Distinct Patterns in Human Milk Microbiota and Fatty Acid Profiles across Specific Geographic Locations. \u003cem\u003eFront. Microbiol. \u003c/em\u003e2016;7:1619.\u003c/li\u003e\n\u003cli\u003eEckburg P.B, Bik E.M, Bernstein C.N, Purdom E, Dethlesfsen L, Sargent M, et al. Diversity of the Human Intestinal Microbial Flora. \u003cem\u003eScience. \u003c/em\u003e2005;308:1635\u0026ndash;1638.\u003c/li\u003e\n\u003cli\u003eRiva A, Borgo F, Lassandro C, Verduci E, Morace G, Borghi E, et al. Pediatric obesity is associated with an altered gut microbiota and discordant shifts in \u003cem\u003eFirmicutes\u003c/em\u003e populations. \u003cem\u003eEnviron. Microbiol. \u003c/em\u003e2017;19:95\u0026ndash;105.\u003c/li\u003e\n\u003cli\u003eCollado M.C, Isolauri E, Laitinen K, Salminen S. Distinct Composition of Gut Microbiota during Pregnancy in Overweight and Normal-Weight Women. \u003cem\u003eAm. J. Clin. Nutr. \u003c/em\u003e2008;88:894\u0026ndash;899.\u003c/li\u003e\n\u003cli\u003eRodr\u0026iacute;guez JM. The origin of human milk bacteria: is there a bacterial entero-mammary pathway during late pregnancy and lactation? \u003cem\u003eAdv Nutr\u003c/em\u003e. 2014;5(6):779-84.\u003c/li\u003e\n\u003cli\u003eLee JE, Kim GB. Human Milk Microbiota: A Review. \u003cem\u003eJ Dairy Sci Biotechnol\u003c/em\u003e. 2019;37(1):15-26.\u003c/li\u003e\n\u003cli\u003eTogo A, Dufour JC, Lagier JC, Dubourg G, Raoult D, Million M. Repertoire of human breast and milk microbiota: a systematic review. \u003cem\u003eFuture Microbiol\u003c/em\u003e. 2019;14:623-641.\u003c/li\u003e\n\u003cli\u003eGueimonde M, Laitinen K, Salminen S, Isolauri E. Breast milk: a source of bifidobacteria for infant gut development and maturation? \u003cem\u003eNeonatology\u003c/em\u003e. 2007;92(1):64-6. \u003c/li\u003e\n\u003cli\u003eCortes-Mac\u0026iacute;as E, Selma-Royo M, Garc\u0026iacute;a-Mantrana I, Calatayud M, Gonz\u0026aacute;lez S, Mart\u0026iacute;nez-Costa C, Collado MC. Maternal Diet Shapes the Breast Milk Microbiota Composition and Diversity: Impact of Mode of Delivery and Antibiotic Exposure. \u003cem\u003eJ Nutr\u003c/em\u003e. 2021;151(2):330-340.\u003c/li\u003e\n\u003cli\u003eAkay H.K, Bahar Tokman H, Hatipoglu N, Hatipoglu H, Siraneci R, Demirci M, et al. The relationship between bifidobacteria and allergic asthma and/or allergic dermatitis: A prospective study of 0\u0026ndash;3 years-old children in Turkey. \u003cem\u003eAnaerobe\u003c/em\u003e. 2014; 28: 98\u0026ndash;103.\u003c/li\u003e\n\u003cli\u003eDogra S, Sakwinska O, Soh S-E, Ngom-Bru C, Br\u0026uuml;ck W.M, Berger B, et al. Dynamics of infant gut microbiota are influenced by delivery mode and gestational duration and are associated with subsequent adiposity. \u003cem\u003eMBio\u003c/em\u003e. 2015; 6: e02419-14.\u003c/li\u003e\n\u003cli\u003eStanford J, Charlton K, Stefoska-Needham A, Ibrahim R, Lambert K. The gut microbiota profile of adults with kidney disease and kidney stones: A systematic review of the literature. \u003cem\u003eBMC Nephrol\u003c/em\u003e. 2020; 21:215.\u003c/li\u003e\n\u003cli\u003eMilani C, Duranti S, Bottacini F, Casey E, Turroni F, Mahony J, et al. The first microbial colonizers of the human gut: Composition, activities, and health implications of the infant gut microbiota. \u003cem\u003eMicrobiol. Mol. Biol. Rev\u003c/em\u003e. 2017; 81:e00036-17. \u003c/li\u003e\n\u003cli\u003eSutharsan R, Mannan M, Doi S.A, Al Mamun A. Caesarean delivery and the risk of offspring overweight and obesity over the life course: A systematic review and bias-adjusted meta-analysis. \u003cem\u003eClin. Obes\u003c/em\u003e. 2015;5:293\u0026ndash;301.\u003c/li\u003e\n\u003cli\u003eKorpela K, Zijlmans M.A.C, Kuitunen M, Kukkonen K, Savilahti E, Salonen A, et al. Childhood BMI in relation to microbiota in infancy and lifetime antibiotic use. \u003cem\u003eMicrobiome\u003c/em\u003e. 2017;5:26. \u003c/li\u003e\n\u003cli\u003eMakela J, Linderborg K, Niinikoski H, Yang B, Lagstrom H. Breast milk fatty acid composition differs between overweight and normal weight women: The STEPS Study. \u003cem\u003eEur J Nutr\u003c/em\u003e 2013;52(2):727\u0026ndash;35.\u003c/li\u003e\n\u003cli\u003eCabrera-Rubio R, Collado MC, Laitinen K, Salminen S, Isolauri E, Mira A. The human milk microbiome changes over lactation and is shaped by maternal weight and mode of delivery. \u003cem\u003eAm J Clin Nutr\u003c/em\u003e. 2012;96(3):544\u0026ndash; 51.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Milk, Bacterial phyla, Probiotic bacteria, obese","lastPublishedDoi":"10.21203/rs.3.rs-4333651/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4333651/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main purpose was to determine amount of dominant phyla, \u003cem\u003eBifidobacteria\u003c/em\u003e and \u003cem\u003eLactobacillus\u003c/em\u003e in breast milk of obese mothers versus normal at 3rd of lactation in Iranian population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEighty health women at the third month of lactation, without any chronic, and gastrointestinal disorders were included and categorized base on body mass index (BMI) to two groups as obese (BMI ≥ 30 kg/m2) and normal (18.5 \u0026lt; BMI \u0026lt; 24.9). Bacterial DNA was extracted and qPCR of the 16S region was performed after human milk donation in sterile conditions. A linear regressions model was used to determine the baseline parameters on the population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBifidobacteria\u003c/em\u003e population was significantly higher in normal group than obese mothers. Current BMI showed a significant effect on the \u003cem\u003eActinobacteria\u003c/em\u003e population in milk. \u003cem\u003eBacteroidetes\u003c/em\u003e and \u003cem\u003eFirmicutes\u003c/em\u003e population were significantly lower in mother’s milk with cesarean delivery (p = 0.04). Pre-pregnancy obesity was associated with lower \u003cem\u003eFirmicutes\u003c/em\u003e and \u003cem\u003eLactobacillus\u003c/em\u003e population in maternal milk (p = 0.04 and p = 0.01). A significant association was observed between the infant height with \u003cem\u003eActinobacteria\u003c/em\u003e and \u003cem\u003eBifidobacteria\u003c/em\u003e population of milk (p = 0.008 and p = 0.04).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrent and pre-pregnancy obesity are associated with lower beneficial phylum and probiotic bacteria in breast milk. Both of them are associated with infant’s height.\u003c/p\u003e","manuscriptTitle":"Breast milk dominant phyla and probiotic bacteria population in obese lactating women: a case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-08 11:20:05","doi":"10.21203/rs.3.rs-4333651/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-29T06:01:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-22T14:25:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226046705562713947780222503103776534815","date":"2024-07-11T15:26:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-01T09:24:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72989909866033035436606410038231544583","date":"2024-06-06T14:12:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198499000722881210436847476464597975122","date":"2024-05-23T13:16:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-10T14:49:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-10T14:44:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-02T09:48:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-02T09:43:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-04-27T10:50:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"780b6a4e-a0de-450c-9dd5-d379265127ac","owner":[],"postedDate":"May 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":31588959,"name":"Biological sciences/Microbiology"},{"id":31588960,"name":"Health sciences/Gastroenterology"},{"id":31588961,"name":"Health sciences/Health care"}],"tags":[],"updatedAt":"2024-08-26T16:09:22+00:00","versionOfRecord":{"articleIdentity":"rs-4333651","link":"https://doi.org/10.1038/s41598-024-70070-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-08-19 15:57:46","publishedOnDateReadable":"August 19th, 2024"},"versionCreatedAt":"2024-05-08 11:20:05","video":"","vorDoi":"10.1038/s41598-024-70070-w","vorDoiUrl":"https://doi.org/10.1038/s41598-024-70070-w","workflowStages":[]},"version":"v1","identity":"rs-4333651","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4333651","identity":"rs-4333651","version":["v1"]},"buildId":"CiT4i_kKBbxQbnFL0ufpk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}