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  • Systematic Review
  • Open Access

12 December 2025

Effects of Supplementation with Milk Proteins on Body Composition and Anthropometric Parameters: A Systematic Review and Dose–Response Meta-Analysis

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Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
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Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran
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San Dimas Community Hospital, San Dimas, CA 91773, USA
4
Department of Pediatrics, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran
Nutrients2025, 17(24), 3877;https://doi.org/10.3390/nu17243877 
(registering DOI)
This article belongs to the Section Proteins and Amino Acids
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Abstract

Background/Objectives: There is no consensus regarding the impacts of supplementation with milk proteins (MPs) on body composition (BC). This systematic review and dose–response meta-analysis of randomized controlled trials (RCTs) assessed the effects of MP, casein protein (CP), and whey protein (WP) supplementation on BC and anthropometric parameters. Methods: A comprehensive search was performed in several databases to identify eligible RCTs published until October 2025. Random-effects models were applied to estimate the pooled effects of MP supplementation on anthropometric parameters. Results: A total of 150 RCTs were included. MP supplementation substantially increased lean body mass (LBM) (weighted mean difference (WMD): 0.41 kg; 95% CI: 0.19, 0.62; p < 0.001) and fat-free mass (FFM) (WMD: 0.67 kg; 95% CI: 0.40, 0.94; p < 0.001). It also significantly reduced body fat percentage (BFP) (WMD: −0.66%; 95% CI: −1.03, −0.28; p = 0.001), fat mass (FM) (WMD: −0.66 kg; 95% CI: −0.91, −0.41; p < 0.001), and waist circumference (WC) (WMD: −0.69 cm; 95% CI: −1.16, −0.22; p = 0.004). No considerable effects were observed for muscle mass (MM), body mass index (BMI), and body weight (BW). Dose–response analysis revealed that MP dosage was associated with significant changes in BFP, LBM, and MM. Conclusions: MP supplementation was associated with favorable modifications in body composition, including increases in LBM and FFM, as well as reductions in FM, BFP, and WC. These findings provide coherent and consistent evidence supporting the potential role of MP supplementation in targeted body composition management.

1. Introduction

Supplementation with milk proteins (MPs) has been widely investigated for its potential effects on body composition (BC), particularly in individuals with specific nutritional needs or those engaged in high levels of physical activity [1,2]. Dairy-derived proteins enhance satiety, improve glycemic regulation, and support weight management [3,4]. Whey protein (WP) and milk protein concentrate (MPC) notably affect lean body mass (LBM) and body fat, positioning them as effective strategies for improving BC [1]. Incorporating milk products into the diet improves skeletal muscle mass (MM) and reduces body fat in young women with insufficient protein intake [5]. Among individuals participating in resistance training (RT), MPC supplementation has been associated with reductions in fat mass (FM) and body fat percentage (BFP), along with increases in LBM [6]. It has been indicated that MP supplementation, with or without RT, may improve MM and strength in older adults [7,8].
Cow’s milk provides essential macro- and micronutrients, along with high-quality proteins, making it an important component of a balanced diet [9,10]. Dairy proteins are primarily composed of whey and casein, which account for approximately 20% and 80% of the total amino acids (AAs), respectively [11]. These proteins differ markedly in their digestion and absorption kinetics [12]. WP is rapidly digested, in contrast to casein protein (CP), which is absorbed at a slower rate [13]. CP supplies all essential AAs except cysteine [14], whereas WP is particularly rich in branched-chain amino acids (BCAAs) (isoleucine, valine, and leucine) at higher concentrations than CP [15,16]. Leucine serves as a key regulator that stimulates muscle protein synthesis [17]. Conversely, CP contains higher amounts of non-essential AAs than WP [15]. Both WP and CP have received increasing attention from researchers and consumers because of their potential health benefits [18,19,20,21,22]. WP, one of the most commonly used supplements among athletes [23], provides BCAAs that promote muscle protein synthesis [24] and is safe for improving BC and reducing cardiovascular risk factors [14,20,21,25].
Several reviews and meta-analyses have examined the impacts of MP and WP supplementation, with or without RT, on BC [1,2,26,27,28,29,30]. However, the existing evidence is fragmented. Prior reviews have largely focused on either WP or CP in isolation, emphasized resistance-trained or athletic populations, or have not evaluated dose–response relationships. Furthermore, the effects of MP supplementation across diverse consumer groups on a broader range of anthropometric outcomes remain insufficiently characterized. These limitations have led to inconsistent or contradictory findings, preventing the development of clear, evidence-based recommendations for the use of MP supplementation to improve BC. Therefore, this systematic review and dose–response meta-analysis of randomized controlled trials (RCTs) aimed to comprehensively assess the effects of MP supplementation on BC and anthropometric parameters in adults and provide robust and clinically relevant evidence.

2. Methods

This systematic review and meta-analysis were implemented following the recommendations outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement [31] and the Cochrane Handbook for Systematic Reviews of Interventions. In addition, the systematic review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (No. CRD42025634923).

2.1. Search Strategy

Two investigators searched some databases (Scopus, PubMed/MEDLINE, and Web of Science) for potential RCTs published until October 2025. A grey literature search was performed using Google Scholar and trial registries to detect additional studies. The reference lists of relevant systematic reviews and included trials were also screened to find any further RCTs. When full texts were not accessible, the corresponding authors were contacted to request the necessary information and full texts.
The search strategy was structured around the PICOS framework (Population, Intervention, Comparator, Outcomes, and Study design) [32] to guide the identification of eligible studies. Search strategies were customized for each database. Both Medical Subject Headings (MeSH) and non-MeSH keywords were used. Boolean operators (OR, AND) were applied to combine search terms and enhance the overall sensitivity of the search. Body composition and anthropometric parameters were MM, LBM, FM, BFP, fat-free mass (FFM), body mass index (BMI), waist circumference (WC), and body weight (BW).
The search strategy included the following terms: (“milk protein” OR “milk” OR “milk protein supplementation” OR “milk protein supplement” OR “casein” OR “whey” OR “whey supplementation” OR “whey supplement” OR “casein supplementation” OR “casein supplement” OR “MPC” OR “milk protein concentrate” OR “whey protein hydrolysates” OR “WPH”) AND (“body weight” OR “body mass index” OR “BMI” OR “WC” OR “waist circumference” OR “BFP” OR “body fat percentage” OR “FFM” OR “fat-free mass” OR “FM” OR “fat mass” OR “LBM” OR “lean body mass” OR “muscle mass” OR “MM”) AND (“randomized controlled trial” OR “RCT” OR “clinical trial”). The search strategy in PubMed is provided in Table S1.

2.2. Selection Criteria

All citations retrieved for this meta-analysis were transferred into EndNote for reference management. Study selection was performed independently by two researchers, and any differences in assessment were addressed in consultation with a third investigator. Eligible RCTs evaluated the effects of supplementation with MP on BC and anthropometric measurements in adults and compared the intervention with a placebo or standard control. Both crossover and parallel RCTs were included. Studies were required to have an intervention duration of at least 2 weeks, enroll participants aged ≥ 18 years, and report at least one outcome of interest (FFM, BMI, WC, MM, LBM, FM, BFP, or BW) at both baseline and post-intervention. Early anabolic and atrophic responses in muscle protein metabolism can occur within days, and previous meta-analyses have documented measurable lean-mass changes within 14 days [33]. Therefore, a ≥2-week minimum intervention duration was selected to ensure inclusion of trials capable of producing early physiological adaptations while excluding very short exposure periods unlikely to yield meaningful changes. Trials were excluded if MP was provided as part of a multicomponent supplement in the intervention or control group. Additional exclusion criteria were the absence of a control or placebo arm, enrollment of pregnant women or participants < 18 years, the use of observational or other non-randomized designs, failure to meet the ≥2-week minimum intervention duration, or a lack of adequate baseline or post-intervention data for at least one outcome of interest.

2.3. Data Extraction

Data extraction was conducted independently by two investigators, and any discrepancies were settled through consultation with another researcher. The extracted information included study characteristics such as trial design, duration, setting, sample size, first author name, publication year, and MP dose. Participant demographics, including BMI, sex, and age, were also collected. The outcomes of interest (WC, FFM, BMI, FM, BW, LBM, MM, and BFP) were recorded at baseline and at the post-intervention time point.

2.4. Risk of Bias Assessment

The risk of bias in each included study was independently evaluated by two reviewers using the Cochrane Risk of Bias 2 (RoB 2) tool. Any differences in their assessments were addressed through consultation with a third researcher. The RoB 2 framework evaluated study quality through structured signaling questions across five key areas: how well participants were randomized, whether any departures from assigned interventions may have influenced outcomes, the extent and impact of missing outcome data, the appropriateness and consistency of outcome measurement, and whether the reported findings align with pre-specified analyses. Based on these evaluations, each domain was rated as “low risk,” “some concerns,” or “high risk” of bias [34].

2.5. Certainty Assessment

The certainty of evidence for each outcome was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. This framework evaluated five key areas (indirectness, RoB, imprecision, inconsistency, and potential publication bias). GRADE classified the certainty of evidence as high, moderate, very low, or low [35]. Two reviewers conducted the assessments independently, and any differences were resolved through discussion.

2.6. Statistical Analysis

All statistical analyses were conducted using STATA software (version 17). Outcomes were summarized as mean values with their corresponding standard deviations (SD), and effect sizes were expressed as mean differences. To compare changes from baseline to post-intervention between the MP and placebo groups, weighted mean differences (WMDs) with 95% confidence intervals (CIs) were calculated [36]. Pooled WMDs were estimated using a random-effects model [36]. Between-trial heterogeneity was assessed using the I2 statistic and Cochran’s Q test [36]. I2 values were classified as low (0–25%), moderate (26–50%), substantial (51–75%), or considerable (>75%) heterogeneity [37].
Subgroup analyses were implemented to detect possible factors contributing to heterogeneity, such as participant sex (both sexes, male, female), health status (unhealthy vs. healthy), protein type (MP, WP, CP), baseline BMI (overweight, obesity, and normal), age (>60 vs. ≤60 years), trial duration (>8 vs. ≤8 weeks), and MP dosage (>30 vs. ≤30 g/day). Sensitivity analyses were applied to evaluate the effect of each trial on overall results.
Publication bias was evaluated by inspecting funnel plot symmetry, as well as Begg’s [38] and Egger’s [39] tests. Statistical significance was p < 0.05. Dose–response relationships were examined using the fractional polynomial method [40]. It was applied to explore potential non-linear associations between MP dosage (g/day) or intervention duration (weeks) and changes in the outcomes. Meta-regression analyses were carried out to examine linear dose–response associations between MP dosage or trial duration and the corresponding changes in outcomes [41].

3. Results

3.1. Study Selection

A comprehensive search among several databases retrieved 6574 records, and 1418 duplicate entries were subsequently excluded. Screening of abstracts and titles for the remaining 5156 records led to the exclusion of 4944. The full-text assessment of 212 articles resulted in the inclusion of 150 studies in the current meta-analysis. Figure 1 displays the flow diagram outlining the stages of screening and selecting studies.
Figure 1. Flow diagram of study selection.

3.2. Study Characteristics

This systematic review and dose–response meta-analysis included 150 RCTs [12,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190]. Their characteristics are summarized in Table 1. Across 150 studies, 7998 participants were enrolled (MP group: n = 3979; control group: n = 4019), with sample sizes ranging from 10 to 208. The mean age of participants ranged from 18 to 86 years, with a mean BMI ranging from 18.5 to 46.5 kg/m2. In addition, 73 trials recruited mixed-sex samples [42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,176,177,178,180,181,183,185,186,187,188,189,190], 28 were performed exclusively among female participants [12,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,174,179], and 49 included only men [128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,175,182,184].
Table 1. Characteristics of included RCTs in the meta-analysis.
The trials were conducted across diverse participants, including dialysis patients [57,61,81,82,86]; older adults [52,66,68,71,75,77,83,84,85,87,89,90,93,94,95,96,98,99,103,108,110,111,114,119,121,124,159,164,184,185,186,187,188,189,190] with sarcopenic obesity [106,169]; individuals with overweight or obesity [42,43,48,49,50,53,54,55,56,59,67,70,78,80,105,107,112,115,116,117,128,129,130,137,174], abdominal obesity [76,91] hypertension (HTN) and pre-HTN [44,58,132], or increased visceral fat [45]; individuals who underwent laparoscopic sleeve gastrectomy [180]; patients with type 2 diabetes mellitus (T2DM) [64,101,109,126,158,175], human immunodeficiency virus (HIV) infection [69,104], metabolic syndrome (MetS) [47], cystic fibrosis (CF) [51], amyotrophic lateral sclerosis (ALS) [60], cancer [63,88], chronic obstructive pulmonary disease (COPD) [65,72,100], sarcopenia [123,139], chronic liver disease [97], or hyperlipidemia [145]; pre-menopausal women [179]; postmenopausal women [118,154] who underwent bariatric surgery [125]; patients who underwent one anastomosis gastric bypass (OAGB) [181]; patients with chronic heart disease (CHD) [102]; and women with polycystic ovary syndrome (PCOS) [127]. Trials were also performed among healthy individuals [62,79,92,113,133,134,138,140,141,143,144,146,150,151,157,161,163,165,166,167,168,170,171,177], nursing home residents [73], midlife adults [46], sedentary individuals [183], basketball players [120,135], futsal players [136], trained men [74,131,147,148,153,155,156], male bodybuilders [142], physically active men [149,182], recreationally active men [172], well-trained endurance athletes [173], master triathletes [152], untrained individuals [176,178], collegiate female athletes [12], collegiate female dancers [122], and army soldiers [160,162].
The articles were published between 2000 and 2025. The RCTs were carried out in multiple countries, including Finland [73,138,150], the Netherlands [42,83,89,172,182,190], Australia [43,67,103,119,142], Japan [45,72,93,94,121,123,132], Iran [61,65,109,115,117,126,128,129,130,135,144,174,181], France [66,149], Tunisia [173], Brazil [60,97,99,101,102,106,110,111,116,118,124,125,175], Germany [47,169,177,178], Denmark [49,54,56,91,98], Canada [51,76,78,80,113,133,139,141,161,164,186], and the United States of America (USA) [12,44,46,48,50,52,53,55,57,59,62,69,70,74,75,77,79,85,92,95,104,105,107,112,114,120,122,127,131,134,140,143,145,147,148,151,154,155,156,157,160,162,165,170,176,183,188]. Trials were also conducted in China [58,90,96,100,108], Thailand [63], Italy [64,88], Portugal [136], Sweden [137,146], the Czech Republic [68], Norway [71,84], the United Kingdom (UK) [152,153,184,187,189], Israel [81,82], New Zealand [158,159,179], Malaysia [86], South Korea [168,171], Spain [87], Turkey [180], Iceland [185], Serbia [163], Chile [166], and Saudi Arabia [167]. Trial durations varied from 2 to 96 weeks, and the daily doses of CP, MP, and WP ranged between 3.14 and 137 g.

3.3. Effect of Supplementation with MP on BW

The meta-analysis of 114 RCTs [42,43,44,45,46,47,48,49,50,51,52,53,55,56,58,59,60,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,83,85,86,87,88,89,91,92,94,95,96,98,99,100,101,103,104,105,107,108,112,113,114,115,116,117,118,119,120,121,123,124,125,126,127,130,131,132,133,134,135,136,137,138,139,141,142,143,144,145,146,148,149,152,153,154,156,157,159,160,161,162,165,166,167,168,170,171,173,174,176,177,178,179,182,183,184,186,187] found no statistically significant impact of MP consumption on BW in the MP-treated group compared to the control group (WMD: −0.22 kg, 95% CI: −0.52, 0.09; p = 0.160). Moderate heterogeneity was observed among the included RCTs (I2 = 38.3%, p < 0.001) (Figure 2A). Subgroup analyses showed significant reductions in BW with MP supplementation among women, participants aged ≤60 years, and individuals with obesity. However, it significantly increased BW in participants older than 60 years (Table 2).
Figure 2. The forest plots illustrate the WMDs and 95% CIs regarding the impact of MP supplementation on (A) BW (Kg), (B) BMI (kg/m2), (C) WC (cm), (D) FM (kg), (E) BFP (%), (F) FFM (Kg), (G) LBM (kg), and (H) MM (kg) [12,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190].
Table 2. Subgroup analyses of the effects of MP supplementation on BC and anthropometric parameters.

3.4. Effect of Supplementation with MP on BMI

The meta-analysis of 59 trials [43,44,45,49,50,52,53,56,57,58,60,61,63,64,65,66,68,77,80,81,82,86,87,90,95,100,101,105,107,108,112,114,115,116,117,125,126,127,128,129,130,131,135,139,145,146,154,159,164,167,174,177,178,179,181,182,184,186,187] revealed no statistically substantial differences in BMI between the MP and placebo groups (WMD: −0.03 kg/m2, 95% CI: −0.14, 0.09; p = 0.626) (Figure 2B). Subgroup analyses indicated substantial reductions in BMI among female participants and those who consumed MP supplements (Table 2).

3.5. Effect of Supplementation with MP on WC

The meta-analysis of 36 studies [42,43,44,45,47,48,49,52,53,54,56,58,64,70,79,80,102,105,106,107,110,111,112,115,116,117,124,125,126,130,158,169,174,177,178,184] revealed that MP supplementation significantly reduced WC in the MP group compared to the placebo group (WMD: −0.69 cm, 95% CI: −1.16, −0.22; p = 0.004) (Figure 2C). Moderate heterogeneity was identified among the included studies (I2 = 47.9%, p < 0.001). Subgroup analyses displayed that long-term supplementation (>8 weeks) with high doses (>30 g/day) of WP markedly decreased WC in healthy participants and individuals with obesity (regardless of sex or age) (Table 2).

3.6. Effect of Supplementation with MP on FM

The meta-analysis, which included 93 trials [12,42,43,46,48,53,54,55,56,62,67,69,70,71,72,74,75,76,77,78,80,83,84,85,89,92,94,95,97,99,102,104,106,107,108,111,113,115,116,117,118,120,122,124,125,127,129,131,133,134,135,136,137,138,139,141,142,143,145,147,151,152,153,154,155,156,157,159,160,162,163,164,165,166,168,169,170,172,173,174,175,176,177,178,179,180,181,182,183,184,186,189,190] demonstrated that supplementation with MP substantially decreased FM in the MP group compared with the placebo group (WMD: −0.66 kg, 95% CI: −0.91, −0.41; p < 0.001) (Figure 2D). Moderate heterogeneity was detected among the trials (I2 = 42.1%, p < 0.001). Subgroup analyses further revealed that supplementation with MP or WP significantly decreased FM, particularly in healthy participants aged ≤ 60 years (irrespective of dose, duration, sex, or BMI) (Table 2).

3.7. Effect of Supplementation with MP on BFP

The meta-analysis of 68 RCTs [12,42,44,45,48,49,50,51,52,53,54,56,57,58,60,63,66,67,71,74,76,80,87,89,92,95,98,101,102,106,107,108,110,116,122,124,125,129,130,131,133,134,136,137,142,143,145,147,148,149,150,151,152,153,159,163,164,166,167,168,171,174,177,178,179,182,183,184] displayed substantial reductions in BFP following MP supplementation compared to the placebo group (WMD: −0.66%, 95% CI: −1.03, −0.28; p = 0.001) (Figure 2E). The analysis also revealed a very high level of heterogeneity among the included RCTs (I2 = 71.2%, p < 0.001). Subgroup analyses indicated that BFP significantly reduced during supplementation with WP or MP among participants aged ≤ 60 years and those with normal BMI (independent of dose, duration, sex, and health status) (Table 2).

3.8. Effect of Supplementation with MP on FFM

The effect of MP supplementation on FFM was assessed through the analysis of 34 RCTs [42,49,60,65,66,72,73,77,92,97,104,108,117,118,125,131,143,145,149,152,153,154,155,160,162,163,165,166,167,171,180,181,184,188]. The meta-analysis indicated that MP supplementation substantially increased FFM in the MP group compared with that in the placebo group (WMD: 0.67 kg, 95% CI: 0.40, 0.94; p < 0.001) (Figure 2F). Subgroup analyses further revealed that long-term supplementation with low WP doses significantly increased FFM among healthy participants and those with obesity (regardless of age or sex) (Table 2).

3.9. Effect of Supplementation with MP on LBM

The meta-analysis of 56 RCTs [43,44,46,50,53,54,55,56,57,62,65,67,69,71,74,75,78,83,84,85,87,89,93,94,95,96,99,107,113,116,120,127,130,131,132,133,135,136,137,139,140,142,147,148,151,156,159,164,172,175,176,179,182,183,185,186] revealed that MP supplementation significantly increased LBM in the MP group compared with the placebo group (WMD: 0.41 kg, 95% CI: 0.19, 0.62; p < 0.001) (Figure 2G). The analysis also revealed low heterogeneity among the included RCTs (I2 = 25.5%, p = 0.036). Subgroup analyses further indicated that LBM significantly increased after supplementation with WP or MP among participants with normal BMI (irrespective of dose, duration, sex, age, or health status) (Table 2).

3.10. Effect of Supplementation with MP on MM

The meta-analysis of 11 RCTs [63,71,157,170,177,178,180,181,184,189,190] did not demonstrate statistically significant impacts of MP supplementation on MM in the MP group compared with the placebo group (WMD: −0.07 kg, 95% CI: −0.33, 0.19; p = 0.588) (Figure 2H). Subgroup analyses also did not reveal any significant effects of supplementation with MP on MM (Table 2).

3.11. Publication Bias

Visual inspection of the funnel plots displayed asymmetry for all outcomes (Figure S1). However, Egger’s and Begg’s tests did not detect any evidence of publication bias for BMI, WC, FFM, BW, FM, LBM, BFP, and MM.

3.12. Risk of Bias Evaluation

The overall RoB of 150 included RCTs is summarized in Table S2. Among these studies, 99 RCTs were rated low RoB, while 51 were rated high RoB.

3.13. GRADE

Table S3 shows the certainty of evidence for the outcomes evaluated after MP supplementation. The evidence for BW, FM, FFM, BMI, WC, MM, and LBM was rated as high certainty, whereas the evidence for BFP was rated as moderate certainty.

3.14. Linear and Non-Linear Dose–Response Relations

Dose–response analyses revealed significant linear (−4.48, p = 0.011; Figure S4E) and non-linear (−0.04, p < 0.001; Figure S2E) associations between MP dose and changes in BFP. A significant linear relationship was also detected between MP dose and changes in LBM (5.66, p = 0.030; Figure S4G). In addition, a substantial non-linear association was identified between MP supplementation dose and change in MM (22.97, p = 0.003; Figure S2H).

3.15. Sensitivity Analysis

The leave-one-out sensitivity analysis revealed no changes in any of the evaluated outcomes.

4. Discussion

This systematic review and dose–response meta-analysis included 150 RCTs. It revealed that MP supplementation may beneficially influence specific BC and anthropometric parameters, as evidenced by increases in LBM and FFM and reductions in FM, BFP, and WC. However, it had no substantial effects on BW, MM, and BMI.
Subgroup analyses revealed that MP substantially reduced BW in women, participants aged ≤60 years, and individuals with obesity. However, it significantly increased BW in participants aged 60 years or older. In addition, significant reductions in BMI were observed among female participants. Long-term supplementation (>8 weeks) with high WP doses (>30 g/day) markedly decreased WC in healthy participants and those with obesity (regardless of sex or age). Supplementation with MP or WP significantly reduced FM in healthy participants aged ≤ 60 years (independent of dose, duration, sex, and BMI). Furthermore, BFP significantly declined during supplementation with WP or MP among participants aged ≤ 60 years and those with normal BMI (irrespective of dose, duration, sex, or health status). Long-term supplementation with low WP doses significantly increased FFM among healthy participants and those with obesity (independent of age or sex). Moreover, LBM significantly increased after supplementation with WP or MP among participants with normal BMI (independent of dose, duration, sex, age, and health status).
Dose–response analyses demonstrated significant linear and non-linear associations between MP dosage and changes in BFP. A substantial linear relationship was also observed between MP dose and changes in LBM, whereas a significant non-linear association was found between MP dose and changes in MM.
A meta-analysis of 35 RCTs demonstrated that WP supplementation improved several BC indicators, including FM, BMI, LBM, and WC [27]. The beneficial effects of WP on BC appeared to be most pronounced when combined with RT and an overall calorie restriction [27]. Another meta-analysis of 10 trials reported that concurrent MP supplementation and RT yielded favorable effects on FFM in older adults, although no significant changes were observed in FM or BW [28]. Moreover, a meta-analysis of nine studies indicated that WP supplementation may increase BW and total FM in individuals with obesity or overweight [1]. These divergent findings likely reflect differences in participant characteristics, baseline adiposity, energy intake, and concurrent RT across trials. A meta-analysis of 17 RCTs suggested that MP is more effective than WP in improving RT-induced LBM or FFM gains in older adults [26]. A recent meta-analysis reported that WP supplementation did not significantly improve anthropometric indicators, including FM, BFP, LBM, or WC, in older adults [30]. It has been revealed that WP is more effective than CP in stimulating protein synthesis in older adults [191]. In addition, milk proteins, particularly WP, may play a critical role in mitigating sarcopenia, a condition characterized by a progressive decline in MM [192,193,194].

4.1. Possible Underlying Mechanisms

The impact of MP on BC appears to be mediated through multiple physiological pathways involving satiety regulation, energy metabolism, and hormonal responses [3,195]. WP and CP exert distinct metabolic effects that influence weight management and BC [195]. Dairy proteins have been shown to enhance satiety more effectively than carbohydrates or fats, thereby reducing overall energy intake [3]. WP is primarily associated with short-term satiety, whereas CP contributes to prolonged feelings of fullness [195]. Additionally, dairy proteins may modulate energy expenditure and lipid metabolism via calcium- and vitamin D-dependent mechanisms that regulate lipolysis and fatty acid oxidation [196]. MP also improves postprandial glycemic control by attenuating blood glucose responses when co-ingested with carbohydrates [3], an effect linked to enhanced insulin sensitivity and more favorable long-term regulation of BW and BC [197,198].
The rapid digestion and absorption of WP lead to elevated circulating AAs [199]. This stimulates muscle protein synthesis and modestly inhibits muscle protein degradation after RT [200]. Therefore, the influence of WP on BC is closely associated with metabolic regulation and MM preservation [1]. WP also stimulates the release of appetite-regulating hormones, including dipeptidyl peptidase 4 (DPP-4), cholecystokinin (CCK), and glucagon-like peptide-1 (GLP-1) [201], contributing to appetite regulation [195]. Owing to its high biological value and rich BCAA profile, WP effectively supports muscle protein synthesis, which is a key determinant of BC maintenance during weight loss [125]. Furthermore, WP may promote the browning of white adipose tissue (WAT) and activate brown adipose tissue (BAT), thereby increasing energy expenditure and facilitating fat loss [202]. It has been suggested that uncoupling proteins and reduced lipogenesis may act as mechanisms contributing to improved weight management [202]. WP also enhances fat oxidation while preserving LBM, providing additional benefits for BC optimization [4,203].
In contrast, CP undergoes slower digestion, leading to the gradual release of AAs and prolonged satiety [195]. This sustained absorption may help maintain energy levels and reduce hunger, thereby supporting effective weight management [195]. CP intake has also been associated with the modulation of gastrointestinal hormones involved in appetite regulation, although evidence regarding its superiority over other protein sources is inconclusive [195]. Moreover, CP may influence metabolic hormones, potentially improving glucose metabolism and attenuating fat accumulation [204]. Overall, WP, CP, and MP exhibited distinct but complementary effects on BC, and their outcomes may vary according to individual metabolic profiles, physiological status, and dietary context.

4.2. Strengths and Limitations

This systematic review is the first dose–response meta-analysis that thoroughly assessed the effect of MP supplementation on BC. It included a large number of RCTs (n = 150) with sufficient sample sizes to identify statistically significant relationships between variables. The systematic literature search was unrestricted by publication date or language, reducing potential selection bias. Including recent studies from various regions improves the external validity and applicability of the results. The included RCTs enrolled adults with diverse health conditions, which enhances the generalizability of the findings and captures a wide range of potential responses across different populations. Additionally, the majority of studies demonstrated low RoB, and the GRADE assessment was high for all variables except BFP, which was rated as moderate.
However, this study had several limitations. Considerable heterogeneity was observed across the trials in terms of characteristics of participants, intervention duration, and supplement dosage. Further sources of heterogeneity included the use of different body composition assessment methods (e.g., dual-energy x-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), or skinfolds). Only short- to moderate-term trials were available, limiting the ability to assess long-term effects of WP, CP, or MP supplementation. Differences between the non-intervention and placebo groups also contributed to variability in outcomes. Additionally, variations in macronutrient composition, particularly total protein intake, between the intervention and control groups could have influenced BC outcomes independent of supplementation with MPs. Energy intake, a major determinant of BC, also differed among the studies and may have confounded their results. Moreover, most included trials focused on WP supplementation, whereas fewer studies investigated whole MP or CP supplementation. Therefore, additional RCTs are required to clarify the distinct and combined effects of CP and MP on BC and related anthropometric parameters. However, this meta-analysis provides a comprehensive and valuable insight for future studies.

5. Conclusions

This dose–response meta-analysis revealed that MP supplementation improved LBM, FFM, FM, BFP, and WC, supporting its potential as a feasible dietary approach to enhance BC. However, MP supplementation had no significant effect on BW, BMI, or MM. These findings should be interpreted cautiously due to heterogeneity across trials and the presence of several studies with high RoB. Well-designed, large-scale RCTs with longer follow-up periods are required to confirm these findings and determine the specific contributions of whole milk or CP supplementation to BC outcomes.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/nu17243877/s1. Figure S1: funnel plots; Figure S2: non-linear dose–response association between MP dose and mean differences in anthropometric parameters; Figure S3: non-linear dose–response association between duration of MP supplementation and mean differences in anthropometric parameters; Figure S4: linear dose–response association between MP dose and mean differences in anthropometric parameters; Figure S5: linear dose–response association between duration of MP supplementation and mean differences in anthropometric parameters; Table S1: Search strategy in MEDLINE (PubMed); Table S2: RoB assessment for included RCTs; Table S3: GRADE assessment.

Author Contributions

Conceptualization: S.M., D.A.-L. and O.A.; Methodology: S.M., D.A.-L. and O.A.; Formal Analysis: S.M. and O.A.; Investigation: S.M., D.A.-L., O.A., N.A., A.F.A., S.S., A.B., M.M., D.G.C., S.C.F., J.A. and K.S.; Writing—Original Draft Preparation: S.M.; Writing—Review and editing: S.M., D.G.C., S.C.F., J.A. and K.S.; Project Administration: S.M. and K.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

S.C.F. is a scientific advisor for Bear Balanced®, has received creatine donations from Creapure® for research purposes, and is a sports nutrition advisor for the International Society of Sports Nutrition (ISSN). J.A. is the CEO and co-founder of the ISSN, an academic non-profit organization that has received sponsorship from companies involved in dietary supplement manufacturing and marketing. He also serves as a scientific advisor to several brands, including Forbes®, Bear Balanced®, Create®, Liquid Youth®, Algae to Omega™, and ENHANCED Games®. D.A.-L. is professionally involved in the health and nutrition industry, including work related to dietary products and supplements; however, no commercial interests influenced the design, analysis, or interpretation of this study. The other authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
MPMilk protein
BCBody composition
MPCMilk protein concentrate
WMDWeighted mean difference
LBMLean body mass
WPWhey protein
FFMFat-free mass
CIConfidence interval
RTResistance training
WCWaist circumference
FMFat mass
RCTRandomized controlled trial
PROSPEROProspective Register of Systematic Reviews
BMIBody mass index
PRISMAPreferred Reporting Items for Systematic Reviews and Meta-Analyses
SDStandard deviation
RoBRisk of Bias
GRADEGrading of Recommendations, Assessment, Development, and Evaluation
BFPBody fat percentage
CPCasein protein
BWBody weight
AAsAmino acids
BCAAsBranched-chain amino acids
ALSAmyotrophic lateral sclerosis
CFCystic fibrosis
CHDChronic heart disease
COPDChronic obstructive pulmonary disease
HIVHuman immunodeficiency virus
HTNHypertension
MetSMetabolic syndrome
MMMuscle mass
OAGBOne anastomosis gastric bypass
PCOSPolycystic ovary syndrome
PICOSPopulation, intervention, comparator, outcomes, study design
T2DMType 2 diabetes mellitus
WPHWhey protein hydrolysates
GLP-1Glucagon-like peptide-1
CCKCholecystokinin
BATBrown adipose tissue
WATWhite adipose tissue
OWOverweight
OBObesity
AOAbdominal obesity
BPBlood pressure
WPIWhey protein isolate
WPCWhey protein concentrate
PLPlacebo
WPC-LHigh-lactoferrin-containing WPC
ERDEnergy-restricted diet
CHOCarbohydrate
MDMaltodextrin
PREProgressive resistance exercise
ITFInulin-type fructans
SGSleeve gastrectomy
UKUnited Kingdom
USAUnited States of America
DPP-4Dipeptidyl peptidase 4

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