Leptin plays a key role in appetite regulation and fat metabolism, and its relationship with body fat compartments and lipid markers under different diet strategies remains unclear. This study aimed to evaluate how changes in leptin levels are associated with body composition and lipid profiles in overweight individuals engaged in resistance training (RT), across time-restricted eating (TRE) and high-protein consumption intervention groups. A total of thirty-two overweight women, aged 18 to 30 years, were randomly divided into four intervention groups: time-restricted eating with high-protein intake (THP), time-restricted eating with regular-protein intake (TRP), high protein without time restriction (HP) and regular protein without time restriction (RP). All participants engaged in RT and followed a diet with a 25 % caloric deficit for 8 weeks. Participants in the high-protein groups consumed 1·6 g/kg/d of protein, whereas those in the standard-protein groups consumed 0·8 g/kg/d. Significant positive associations between changes in leptin and fat mass (FM) were observed in the THP (R2 = 0·69, P = 0·01) and TRP (R2 = 0·53, P = 0·03) groups. In contrast, no significant associations were identified between leptin and visceral adipose tissue, or subcutaneous adipose tissue in any group. Associations between leptin and lipid markers varied across intervention groups, with significant relationships observed for TG in the THP group (R2 = 0·59, P = 0·02) and for LDL-cholesterol (R2 = 0·51, P = 0·04) and HDL-cholesterol (R2 = 0·63, P = 0·01) in the HP group. These findings suggest that changes in leptin are more closely associated with changes in total FM than with regional adipose tissue depots. Associations between leptin and lipid markers were less consistent across intervention groups, indicating that the relationship between leptin and metabolic outcomes may be influenced by dietary context. Findings should be interpreted cautiously given the exploratory nature of the analyses and the relatively small sample size.

Delayed eating is associated with a higher risk of overweight and obesity in the general population, but its relationship with anthropometric measurements and body composition in individuals with prediabetes remains unclear. This study investigated the association between chrononutrition behaviours, anthropometric measurements and body composition in adults with prediabetes. This prospective longitudinal study enrolled 120 participants aged 54 ±15 years, who received standard care at healthcare clinics. Socio-demographic data were collected via an interviewer-administered questionnaire. Anthropometric measurements, body composition metrics and chrononutrition behaviours (assessed with the Malay-translated Chrononutrition Profile Questionnaire) were assessed at baseline and 6 months. Multiple linear regression analyses with adjustment for confounders were conducted. A later last meal was associated with higher body weight (β: 0·68 kg, 95 % CI: 0·31, 1·04) and larger waist circumference (β: 1·38 cm, 95 % CI: 0·57, 2·19). Each hour deviation from eating beyond the 07.00–19.00 time window corresponded to an increase in body weight of 1·41 kg (95 % CI: 0·05, 2·77). Increasing frequency of nighttime snacking was associated with higher BMI (β: 1·61 kg/m2, 95 % CI: 0·43, 2·79). Delaying last meal timing (β: 0·44 %, 95 % CI: 0·14, 0·74) and deviating from solar time were associated with higher body fat percentage (β: 1·36 %, 95 % CI: 0·30, 2·42), while increasing frequency of breakfast skipping was associated with lower muscle mass (β: −0·31 kg, 95 % CI: –0·56, 0·07). These findings highlight the importance of chrononutrition behaviours in influencing anthropometric and body composition outcomes, supporting targeted interventions on meal timing in prediabetes management.

Sarcopenia, the age-related decline in muscle mass and strength is a growing challenge for older adults. This study investigates whether meeting the WHO physical activity guidelines (150–300 min/week of moderate or 75 min/week of vigorous exercise) with higher protein intake, based on the RDA, is associated with appendicular lean soft tissue index (ALSTI) and handgrip strength (HGS) in adults living in the United States aged 40–59 years. Data from the National Health and Nutrition Examination Survey 2007–2020 included 2540 adults aged ≥40 years. Physical activity (moderate/vigorous) was self-reported, while higher protein intake was assessed via two 24-hour recalls (>0.8 g/kg/bodyweight). Linear regressions, adjusted for age, sex, BMI, race, education, comorbidities, and energy-adjusted protein intake were used to assess associations with ALSTI and HGS. In fully adjusted models, vigorous activity with higher protein intake (47.1 ± 5.6 years) was associated with ALSTI only after adjustments for age, sex, BMI, race, education (β = 0.37, SE 0.17, p = 0.047; mean baseline: 8.56 ± 1.67 kg/m2). No associations were found in the fully adjusted model for ALSTI (p = 0.31), and across all models for HGS (mean baseline: 43.6 ± 10.1 kg). Moderate activity with higher protein intake was not associated with HGS or ALSTI across adjusted models. Meeting vigorous or moderate-intensity activity guidelines with higher than the RDA protein intake was not associated with ALSTI or HGS in middle-aged US adults.

While rapid four-compartment (4C) models have demonstrated cross-sectional validity in diverse populations, including athletes, their longitudinal validity remains unverified. This study aims to evaluate the longitudinal validity of utilising dual-energy X-ray absorptiometry (DXA)-derived estimates of body volume (BV) and bioelectrical impedance spectroscopy (BIS)-derived total body water (TBW) in rapid 4C models in athletes. Criterion 4C used DXA for bone mineral content, air displacement plethysmography for BV and 2H dilution for TBW. Analyses of longitudinal changes in fat mass (FM), in both kilograms and percentage, were performed in participants who experienced changes greater than 1 % (n 60) and in a subgroup exceeding the least significant change (1·97 kg, n 25). All alternative estimates underestimated changes relative to criterion 4C, with 4C TBWBIS providing the smaller mean difference (MD) (0·41 kg) and DXA the larger (0·94 kg). The MD for 4C BVSilvaTBWBIS and 4C BVHeymsfieldTBWBIS were 0·48 kg and 0·50 kg, respectively. Bland–Altman analyses showed wide limits of agreement (LOA) for all methods. Even the alternative with the smaller 95 % LOA had a wide LOA (4C TBWBIS: −2·9 %, 4·0 %, n 60). This investigation demonstrates that these rapid 4C models exhibit precision superior to or equivalent to DXA alone while offering reduced assessment times and broader accessibility than the criterion 4C. Regarding accuracy for evaluating changes over time, despite acceptable results at the group level, interpretation should be careful at the individual level.

Diet is key for a healthy lifestyle, yet evidence on how diet quality affects body composition and cardiometabolic health during pregnancy is insufficient. The aims of this study were to examine associations of diet quality (Swedish Healthy Eating Index (SHEI)) with body composition, cardiometabolic health in early and late pregnancy (gestational weeks 14 and 37) and gestational weight gain (GWG). This observational study used cross-sectional and prospective data from the HealthyMoms trial at two timepoints: early (n 302) and late pregnancy (n 134). Exposure was diet quality (SHEI) assessed through online 24 h recalls, and outcomes included body composition (body fatness, BMI, fat mass index (FMI)), cardiometabolic health (homeostatic model assessment for insulin resistance (HOMA-IR), metabolic syndrome (MetS) score, glycaemia) and GWG. Linear regression was used to investigate associations between SHEI and outcomes. In the cross-sectional analyses, higher SHEI was associated with lower body fatness, BMI, FMI and MetS score in early pregnancy (all B ≤ −0·14, all P ≤ 0·02). Similar results were seen in late pregnancy, with the addition of an association with HOMA-IR (all B ≤ −0·20, all P ≤ 0·008). Prospectively, higher SHEI in early pregnancy was associated with lower body fatness, BMI, FMI, glycaemia, HOMA-IR and MetS score in late pregnancy (all B ≤ −0·09, all P ≤ 0·01). There were no statistically significant associations of change in SHEI with GWG or other outcomes (P ≥ 0·09). In conclusion, a healthy diet, especially in early pregnancy, seems beneficial for body composition and cardiometabolic health. Focusing on key dietary advice, as captured by SHEI, may be advantageous and feasible within maternity care.

Body composition and fat distribution were found to display differential effects on the incidence and mortality of chronic disease. However, it remained unclear whether there is an interaction between lifestyle factors and genetic susceptibility on body composition and fat distribution. This study investigated the associations of lifestyle and genetic factors with body composition and fat distribution among 121 664 women from the UK Biobank cohort study. Women with a favourable lifestyle had lower BMI (BMI, –7·72 % (95 % CI: −7·93 %, −7·51 %)), fat mass index (FMI, −15·70 % (95 % CI: −16·09 %, −15·30 %)), fat-free mass index (FFMI, −2·86 % (95 % CI: −2·98 %, −2·74 %)), arm fat ratio (AFR, −5·19 %, (95 % CI: −5·38 %, −5·00 %)) and trunk fat ratio (TFR, −0·73 %, (95 % CI: −0·84 %, −0·62 %)) but higher leg fat ratio (LFR, 2·30 % (95 % CI: 2·16 %, 2·44 %)) than those with an unfavourable lifestyle. Significant interactions between lifestyle factors and genetic susceptibility on BMI, FMI and AFR were observed (Pinteraction < 0·05). Among women with a high genetic susceptibility to body composition or fat distribution, those with a healthy lifestyle still had a lower BMI, FMI, FFMI, AFR and TFR and higher LFR (Ptrend < 0·001). Women who adhere to a favourable lifestyle tend to have healthy body composition and fat distribution, and this association is consistent across all strata of genetic risk.

Normal reference values for body composition and physical performance measures are needed in order to determine cut-off values for suboptimal health such as obesity and related cardiometabolic diseases, and/or sarcopenia. Few studies have provided comparative normative reference ranges across different populations. We compare several body composition and physical performance measures between older Hong Kong Chinese and Canadians to derive and contrast their respective reference values. 17 451 older adults from the Canadian Longitudinal Study on Aging (CLSA) and 4000 from the Hong Kong Mr. and Ms. Osteoporosis (Os) cohort aged 65 years and over were included to derive reference values for walking speed, grip strength, 5-times chair stand test (CST), percentage body fat (PBF), weight, BMI, waist:hip ratio (WHR) and Conicity Index (C-index), stratified by age and sex. Overall normal reference values for Hong Kong males were higher compared with Canadians, particularly in younger age groups. The observations were reversed for females. Not surprisingly, Canadians have higher body weight and BMI compared with Hong Kong older adults. Older Canadian males also have a higher PBF and WHR, compared with Hong Kong older males. When fat distribution was compared, Hong Kong Chinese females have higher C-index, indicating greater central fat distribution compared with Canadian females. Normative reference values are best derived in the context of ethnicity and geographic regions, when used in relation to health assessments requiring physical performance measures and body composition.

Disordered eating (DE) significantly affects both physical and mental health, contributing to morbidity, mortality, and considerable global healthcare costs. This cross-sectional study assessed the prevalence of high-risk DE and examined its associations with body composition, behavioural factors, diet quality, and perceived stress among university students in the United Arab Emirates. A total of 911 students were recruited using non-probability quota sampling (50.49% female). Body composition was measured using a TANITA BC-420MA body composition monitor. Usual dietary intake was assessed via a validated 65-item food frequency questionnaire. DE risk was assessed using the Eating Attitudes Test (EAT-26) and perceived stress using the PSS-10. Analysis included linear regression and independent-samples t-test (p < 0.05). High-risk DE (EAT-26 ≥ 20) prevalence was 30.3%. High-risk DE was significantly associated with higher body fat percentage (β = 0.121, p < 0.001), fat mass (β = 0.148, p < 0.001), fat-free mass (β = 0.079, p = 0.017), lean mass (β = 0.08, p = 0.016), total body water (β = 0.084, p = 0.011), and lower total body water percentage (β = −0.131, p < 0.001). High-risk students also reported higher intakes of fibre (β = 0.12, p = 0.018), beta-carotene (β = 0.14, p = 0.025), vitamin A (β = 0.13, p = 0.034), B12 (β = 0.15, p = 0.043), folate (β = 0.16, p = 0.006), and vitamin D (β = 0.16, p = 0.036). Compared with the low-risk group, high-risk DE was associated with higher adiposity markers and slightly higher perceived stress, and differed in selected nutrient intakes; sociodemographic characteristics were largely similar between groups except for smoking status. These findings support the implementation of targeted prevention strategies, including nutrition education, routine screening, and culturally tailored programmes, for young adults in the UAE.

The objectives of the present study were (a) to determine the effects of a 12-week intervention using wearables promoted through physical education classes on physical activity, body composition, physical fitness and psychological well-being of overweight or obese adolescents; and (b) to analyze the differences in outcomes based on gender and baseline physical activity. Seventy-three overweight and obese adolescents (mean age: 13.44 ± 1.12 years) were randomly assigned to an experimental group (EG) or control group (CG). The EG used a physical activity wearable for 12 weeks. Both groups were assessed before and after the intervention. Regarding primary outcomes, the EG showed an increase in physical activity (p = 0.048) and reductions in body mass index (p = 0.007), fat mass (p < 0.001), and sum of 3 skinfolds (p = 0.002), with moderate-to-large effect sizes (η2 > 0.09). According to the secondary outcomes, improvements in physical fitness were limited, with increases observed only in abdominal muscular endurance, and these changes were also present in the CG. Subgroup analyses showed that females and adolescents with low baseline physical activity experienced greater benefits, particularly in fat-related variables (p < 0.001–0.037), with large effect sizes (η2 > 0.14). Additionally, adolescents with greater exposure to the wearable-based intervention showed more consistent improvements in fat-related outcomes (p < 0.001–0.032), with large effect sizes (η2 > 0.25). In conclusion, a wearable-based intervention promoted through physical education classes may contribute to meaningful improvements in body composition, particularly among females and previously inactive adolescents who are overweight or obese. However, effects on physical fitness and psychological well-being were limited, highlighting the importance of intervention design, adherence, and complementary motivational strategies.

This study aimed to evaluate the agreement between three body composition devices and dual-energy X-ray absorptiometry (DXA) in assessing segmental body composition among healthy Iranian adults. This comparative study recruited 62 healthy adults (33 men and 29 women) from Tehran, Iran, using a convenience sampling approach. Socio-demographic data were collected, and segmental body composition was assessed using several devices, including the InBody 770, Anea bioelectrical impedance analysis (BIA), Tanita BC-418 and DXA. Agreement between DXA and the BIA devices was evaluated using Lin’s concordance correlation coefficient (CCC). Additionally, Bland–Altman plots and mean percentage error were applied to assess the consistency between the two methods. The Anea, InBody 770 and Tanita BC-418 devices showed strong correlation with DXA for all segmental measurements (r ≥ 0·74, P < 0·05). Moderate agreement (CCC: 0·90 ≤ CCC < 0·95) with the DXA method was found for some segments using the Anea (trunk fat mass, arms fat-free mass, legs fat-free mass and trunk fat-free mass) and the InBody 770 (trunk lean body mass and trunk fat mass) devices. The estimation of legs fat mass was the least accurate across all BIA devices. Furthermore, subgroup analyses showed that the BIA devices provided more precise results in men and in individuals with a BMI < 25·00 kg/m2. The Anea BIA and InBody 770 devices show relatively acceptable validity for segmental body composition assessment. More research is needed to confirm these findings.

Surface anthropometric measures are commonly used to assess body composition in trained individuals. Standardised pre-test guidelines (morning, fasted) present logistical concerns. The impact of daily activities on skinfold (SKF) assessment has been established in males; however, there is a lack of research examining females. The aim of this study was to assess the within-day agreement between standardised and non-standardised surface anthropometric measures in trained females. Measures including body mass, eight SKF and six circumferences were collected by an International Society for the Advancement of Kinanthropometry level 1 anthropometrist on forty trained females (twenty naturally menstruating and twenty using a contraceptive) under standardised conditions (morning, fasted, rested and hydrated) and non-standardised conditions (9–10 h later after free-living) on the same day. The menstrual or contraceptive pill phase was not controlled for. The intra-class correlation coefficient and typical error were calculated to assess reliability. Overall group means were compared to assess if a significant change occurred. The sum of eight SKF sites (∑8 SKF) displayed excellent reliability, and no significant difference was noted between conditions. Greater levels of disagreement were represented by those with ∑8 SKF > 136 mm. Significant differences in group means were recorded for body mass and waist circumference. All other five circumference sites remained unchanged throughout the day. Findings suggest that if accuracy is required, body mass and waist circumference should be collected in a standardised state. SKF and all five other circumferences can be collected in trained females at any time of day without considering pre-test standard guidelines.

Body composition (BC) offers essential insights into the physical condition and performance capacity of athletes. Several factors can influence athletes’ BC, such as nutrition, which can improve lean mass (LM) and body fat percentage (%BF). This longitudinal observational study aimed to investigate the factors influencing BC in professional female football players, including hormones, dietary habits and physical activity, as these are relevant to their sport performance and health. Data related to dietary habits, dual-energy X-ray absorptiometry measurements, serum hormones, menstruation and global position system metrics were collected in November 2023 and late March 2024 from thirty-eight female football players from the Real Sociedad team. Of the thirty-eight players enrolled, thirty-five completed all assessments and were included in the final analyses. Spearman correlations and linear regression analyses were performed. Statistically significant models were executed for %BF and LM (adjusted R2 = 0·55 and 0·47, respectively). For %BF, total testosterone had a positive influence, while high-speed running per minute, follicle-stimulating hormone, distance covered per minute, prolactin and fat intake influenced negatively. In the LM model, positive associations were total testosterone, progesterone, age, adrenocorticotropic hormone and carbohydrate intake, while insulin, distance covered per minute and sex hormone binding globulin had negative associations. These results emphasise the complexity of the factors influencing BC in female football players. Personalising and periodising carbohydrate intake and monitoring training loads are crucial to prevent adverse effects such as higher %BF and muscle catabolism. Establishing healthy nutritional practices is essential for long-term health and performance.

This review aims to (1) provide an overview of research investigating the relationship between body composition, specifically fat-free mass (FFM) and fat mass (FM), appetite and energy intake (EI) and (2) to investigate potential mechanisms underlying these relationships, with a focus on ageing. Appetite and EI are influenced by complex, multifactorial pathways involving physiological, psychological, environmental, social and cultural factors. Early research investigating the association of body composition with appetite and EI focused on FM; however, the role of FFM in appetite control is gaining increasing attention. Studies have shown that FFM is positively associated with EI in younger populations, including infants, adolescents and adults. In contrast, FM appears to have no association or a weak inverse association with appetite/EI. However, research in older adults is limited, and the underlying mechanisms are not fully understood. It has been suggested that one way in which FFM may influence appetite and EI is by impacting resting metabolic rate (RMR). FFM, which includes metabolically active tissues including skeletal muscle and organs, represents the largest determinant of RMR and therefore may influence appetite and EI by ensuring the energetic requirements of crucial tissue-organs and metabolic processes are reached. Given that declines in FFM and RMR are common with ageing, they may be possible targets for interventions aimed at improving appetite and EI. While current evidence in older adults supports a positive association between FFM and appetite, further longitudinal studies are needed to explore this relationship in different contexts, along with the underlying mechanisms.

We aimed to investigate the association of chrono-nutrition components with anthropometric measures and body composition in adults living in Tehran. This cross-sectional study was conducted on 450 healthy adults. The exposures of the study were meal frequency, meal timing, meal irregularity, breakfast skipping, night fasting duration, time of the first and last eating occasion and the time interval from the last meal to bed. The outcomes were BMI, waist circumference, neck circumference (NC), waist:hip ratio, waist:height ratio (WHtR), body adiposity index (BAI), body roundness index (BRI), a body shape index, percentage of body fat (PBF), fat mass (FM), fat-free mass and muscle mass. Bonferroni correction was applied, and the significance level was less than 0·004. Using ANCOVA, after adjusting for confounders, late lunch eating was associated with a lower PBF. There was a positive trend across the tertiles of dinner time with greater WHtR (mean difference = 0·019; Ptrend = 0·025) and BRI (mean difference = 0·24; Ptrend = 0·022). Moreover, increased irregularity at dinner time was associated with higher levels of PBF (Ptrend = 0·026) and FM (Ptrend = 0·025). Also, longer overnight fasting was associated with lower NC (Ptrend = 0·049) and a greater BRI (Ptrend = 0·050). We found differences across the time interval from the last meal to bed with greater means of BAI (Ptrend = 0·026), PBF (Ptrend = 0·014) and FM (Ptrend = 0·020). However, after applying the Bonferroni correction, we found no significant association between chrono-nutrition components and anthropometric measures and body composition in adults living in Tehran. Further studies are necessary to confirm the results.

Neonatal growth assessment during the first 28 days of life is a critical determinant of infant health and survival. Anthropometric measurements provide a simple, inexpensive, and non-invasive means to evaluate neonatal size, nutritional status, and growth, as well as to predict long-term health outcomes. Alongside standard growth curves, methods for assessing neonatal body composition offer additional insights into fat and fat-free mass distribution, which are linked to later risks such as childhood obesity and metabolic complications. This review summarizes the commonly used anthropometric measures and advanced laboratory techniques for assessing neonatal growth and body composition, discusses their advantages and limitations, and highlights the importance of their combined use in clinical and research settings. Understanding these methods is essential for early identification of growth disturbances and for promoting optimal nutrition and health outcomes throughout the life course.

Skinfold callipers are used internationally in research, clinical and field settings to assess body composition and nutritional status. Notably, currently available instruments differ in important specificities that impact measurement. In this sense, this report proposes a methodological approach that organises skinfold callipers into three categories (Original, Generic and Hybrid) and three configurations (Type A, Type B and Type C) based on physical-mechanical properties and characteristics. Therefore, this concept provides technical support for choosing the most appropriate skinfold calliper in different contexts.

We aimed to investigate the association between plasma advanced glycation end products (AGE) level and fat, skeletal muscle-related body composition parameters in middle-aged and elderly Chinese participants. A total of 1139 participants aged over 40 years were included in a cross-sectional study. Body composition including BMI, waist:hip ratio (WHR), fat mass index (FMI), percentage of body fat (PBF), the ratio of trunk fat to legs fat (trunk fat/legs fat), fat free mass (FFM), fat free mass index (FFMI) and skeletal muscle index (SMI) was measured using a bioelectrical impedance analyser. Plasma free and combined AGE were measured by ultra-high performance liquid chromatography-tandem MS. Multiple linear regression and weighted quantile sum regression models were used to examine the association between AGE and body composition parameters. Total exposure of plasma advanced glycation end products (AGE) was positively associated with BMI (β (95 % CI): 0·381 (0·037, 0·724), P = 0·030), FMI (β (95 % CI): 0·521 (0·241, 0·800), P = 0·001), PBF (β (95 % CI): 1·996 (1·160, 2·832), P < 0·0001), trunk fat/legs fat (β (95 % CI): 0·058 (0·036, 0·080), P < 0·001); while it was negatively associated with FFM (β (95 % CI): −1·075 (–2·028, –0·122), P = 0·027), FFMI (β (95 % CI): −0·687 (–1·076, –0·297), P = 0·001) and SMI (β (95 % CI): −1·264 (–1·767, –0·761), P < 0·001). The associations between plasma AGE and FFM and FFMI were more pronounced in those aged less than 61 years and female participants. This study provides evidence on the associations between plasma AGE and fat and skeletal muscle parameters, suggesting their potential role in the development of obesity and skeletal muscle loss.

Infants born at high altitudes, such as in the Puno region, typically exhibit higher birthweights than those born at low altitudes; however, the influence of ethnicity on childhood anthropometric patterns in high-altitude settings remains poorly understood. This study aimed to characterise the nutritional status, body composition and indices, and somatotype of Quechua and Aymara children aged 6–10 years. A cross-sectional, descriptive, and comparative design was employed, with a simple random sampling of children from six provinces representative of the Puno region, including 1,289 children of both sexes. Twenty-nine anthropometric measurements were taken, and fat, muscle, and bone components were assessed using bioelectrical impedance analysis. Standardised equations were applied to determine body indices. Among the findings, most children presented normal nutritional status according to BMI-for-age and height-for-age Z-scores. However, high rates of overweight and obesity were observed in Aymara (39%) and Quechua (28.4%) children, with differences in fat content between ethnic groups at the 5th, 10th, 50th, and 75th percentiles. Both groups were characterised by brachytypy and brachybrachial proportions; Quechua children were mesoskelic and Aymara brachyskelic, with macrocormic proportions, rectangular trunks, and broad backs. The predominant somatotype was mesomorphic, with a stronger endomorphic tendency among Aymara. It is concluded that both groups exhibit normal nutritional status; however, Aymara children show a greater tendency towards fat accumulation and notable morphological differences. Differences were also observed in limb proportions, particularly a relatively shorter lower limb.

Proper nutrition enhances athletes’ performance and recovery during sports activities. This review aims to investigate the effects of nutrition education interventions on dietary intake, nutrition knowledge, and body composition of female athletes. From a comprehensive search, we identified twenty single-arm and eight double-arm studies that met the inclusion criteria. The interventions in these studies ranged from personalised consultations to group workshops. The mode of delivery was mainly face-to-face. Most of these interventions consisted of group sessions with variable duration and frequency. From the studies finally included, nutrition education intervention significantly increased the nutrition knowledge of female athletes in 76% and improved their dietary intake in 67%. However, only 44% of the studies that measured changes in body composition reported significant changes. Moreover, only a minority of studies (14%) maintained follow-up assessments to measure the lasting impact of the interventions. Overall, 60% of interventions were delivered by professional nutritionists or dietitians, ensuring high-quality education. There is a need for standardised methodologies and more robust study designs to better assess the effectiveness of nutrition education interventions. Knowing athletes’ preferences when planning education may improve engagement and intervention efficacy. Also, longer-term follow-up of athletes would allow for a more accurate evaluation of the consolidation of acquired knowledge. Including coaches in nutrition education interventions would probably amplify the impact on athletes’ dietary behaviours. Nutrition education can positively influence the knowledge and eating habits of female athletes, but its effect on body composition represents an area where much remains to be explored.