Jagim, Andrew

Weight loss and thermogenic dietary supplements often claim to promote weight loss by increasing metabolic activity. This study characterized the identity and quantity of common supplement ingredients. Commercially available products (n=98) whose name, label, or packaging referenced promotion of thermogenesis or weight loss were identified at retail outlets or web search. Product ingredients were divided into 6 possible categories of ingredient quantity based on packaging. Extracts included raw plant ingredients, plant extracts, etc. Small molecule isolates included caffeine, melatonin, etc. The remaining 4 ingredient categories were lipids, minerals, vitamins, and amino acids. Product suggested serving size was 13±16 grams (40±71 Cal). Green tea (521±1334 mg), cayenne (57±46 mg) and black pepper (5±2 mg) extracts were the most common, with 22 ingredients of 137 extracts being quantified 3 or more times. Caffeine (181±59 mg), acetyl-L-carnitine (595±368 mg) and L-carnitine (510±345 mg) were the most common small molecule isolates, with 11 of 49 total ingredients quantified in at least 3 products. There were 18 different lipid or fatty acid ingredients with only linoleic (740±718 mg) and lipoic (250±235 mg) acids being quantified in at least 3 products. Chromium (268±282 µg), calcium (156±110 mg), and iodine (145±85 mg) were the most common minerals, with 10 of 14 minerals quantified in at least 3 products. Cobalamin (49±78 µg), pyridoxine (8±9 mg) and folate (391±252 mcg) were the 3 most common vitamins, with 5 of 13 vitamins quantified in at least 3 products. Alanine (2133±924 mg), tryptophan (60±40 mg) and tyrosine (250±229 mg) were the most common amino acids, with 3 of 9 amino acids quantified in at least 3 products. Ingredients were indicated as “present” but not quantified 541 times across the 98 products. Proprietary formulas and vaguely worded ingredients were listed in 44 of the 98 products. The 98 thermogenic and weight loss products contained a tremendous variety of ingredients, although only 53 of the 240 different ingredients were present in 3 or more products. Variable ingredient content and quantity, complicate blanket claims about function, efficacy, or safety. Future evaluations of ingredient contents should determine if specific amounts confer discernable benefits. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Objective We examined the weight management practices of successful high school wrestlers to contribute meaningful data to the conversations that weight-certifying clinicians and athletic trainers have with athletes at the start of the wrestling season. Understanding how elite athletes navigate weight management can inform safer and more individualized guidance during preseason assessments. Specifically, we sought to determine the proportion of state-qualifying wrestlers who competed at or above their certified minimum weight class. We also quantified the magnitude of weight change from certification to state competition and analyzed seasonal trends in both body weight and body fat percentage over a 20-year period. Design Longitudinal retrospective review. Setting Four Minnesota high schools. Patients or Other Participants State-qualifying wrestlers from 2003 to 2023. Independent Variable State-qualifying weight class. Main Outcome Measure(s) Dependent variables are certification weight, measured body fat percent, and calculated minimum weight class. Results Only 48 wrestlers (52.7%; CI = 42.5%, 63.0%) competed at state in their minimum weight class, while the other 43 competed 1 to 2 weight classes above. Thirty-six wrestlers (39.6%) gained weight over the season. Conclusions Nearly half the successful wrestlers competed in weight classes above their minimum weight, while 5% lost 9% to 18% of their body mass over the wrestling season. This suggests factors other than maximizing individual athletic potential, such as team needs to fill a weight class, influence weight management decisions. Over the 20-year span of the study, trends toward lower measured body fat percentage and lower weight fluctuations suggest influences from sports specialization and year-round training and less emphasis on extreme leanness for competitive advantage. Athletes, in consultation with their coaches and clinicians, should select a competition weight class where they can adequately fuel, train, and recover. This may not be their minimum certified weight class.

Abstract Magee, MK, Fields, JB, Jagim, A, Lockard, B, Miller, A, Stroiney, D, and Jones, MT. Estimation of whole-body bone mineral density through air displacement plethysmography in a large sample of elite athletes. J Strength Cond Res 39(4): 427–432, 2025—Dual-energy x-ray absorptiometry (DXA) is used to determine bone mineral density (BMD) and body composition. Regulations and cost may limit DXA's utility in some athletic settings. Air displacement plethysmography (ADP), while able to measure body composition, does not measure BMD. The purpose was to evaluate the influence of body composition parameters obtained from ADP on BMD. Collegiate athletes (males, n = 153; females, n = 208) underwent ADP and DXA assessments. For ADP testing, the Brozek equation was used to estimate body fat percent (BF%) and fat-free mass (FFM) from body density. Dual-energy x-ray absorptiometry tests were completed to obtain BMD using the whole-body scan mode. Stepwise regression was conducted using age, body mass, height, sex, race, FFM (ADP), BF% (ADP), and sport type as independent variables. Total BMD (DXA) was the dependent variable. Accuracy and precision of the final equation were evaluated through Bland–Altman and linear regression. The final regression equation yielded an R 2 of 0.691 with race, mass, BF%, age, and sport type as significant predictors ( p < 0.05) of BMD. Bland–Altman and linear regression showed systematic {95% confidence interval [CI] (−0.619 to −0.360)} and proportional bias (95% CI [0.173–0.374]). Although an ADP-derived regression equation may not provide a precise prediction of BMD, it may be useful to establish risk for low BMD if DXA is unavailable. Dual-energy x-ray absorptiometry may not be feasible for some athletic programs; therefore, an estimation equation for BMD derived from ADP values is advantageous for practitioners. This equation may assist in screening athletes for risk of low BMD.