A structured electronic literature search was conducted under the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (16). The search included six electronic databases (Web of Science, PubMed, ProQuest, Scopus, EBSCO, and CNKI). The retrieval was “[Title/Abstract] = (‘Fundamental Movement Skills' OR ‘Motor skill') AND [Title/Abstract] = (‘health related fitness' OR ‘health benefits' OR ‘body composition' OR ‘body mass index' OR ‘weight' OR ‘fat percentage' OR ‘cardiorespiratory fitness' OR ‘cardiopulmonary function' OR ‘musculoskeletal fitness' OR ‘muscle strength' OR ‘muscle endurance' OR ‘flexibility'). The search was conducted from January 1, 2000, to November 23, 2022, and only literature in English and Chinese published in peer-reviewed journals was considered.

Two researchers independently screened and reviewed the literature and jointly determined the final article list. If inconsistent screening results occurred, a third researcher was asked to decide.

A PECO (population, exposure, comparison and outcome) approach (17) was used as inclusion criteria: (a) Population: participants were 3–16 years old and were in preschool education or school; (b) Exposure: fundamental movement skills, including comprehensive fundamental movement skills or subitems (locomotor, object manipulation, and balance skills); (c) Comparison: health-related fitness elements (cardiopulmonary function, muscle strength and endurance, flexibility, and body composition); (d) Outcome: report or data that makes it possible to estimate associations.

The exclusion criteria were as follows: (a) research articles on special groups, such as cardiovascular disease, developmental coordination disorders, mental disorders, etc.; (b) intervention study (literature on fundamental movement skills and health-related fitness association with an experimental intervention); (c) study sample of fewer than 50 people; (d) no cross-sectional data of fundamental movement skills and health-related fitness; (e) non-English or non-Chinese literature.

The data extraction form retrieved the following information: first author and publication time, test method, health-related fitness elements, study design type, participant, and statistical method. Two researchers independently completed the data extraction, followed by discussion and cross-checking to ensure consistency and accuracy.

The literature quality was assessed using the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement (18) and the Consolidated Standards of Reporting Trials (CONSORT) statement (19), based on Lubans et al. (8) and Cattuzzoa et al. (9). The quality score for each study was based on six questions: (1) Did the study describe the participant eligibility criteria? (2) Were the participants randomly selected (or for the experimental studies, was the randomization process clearly described and adequately carried out)? (3) Did the study report the sources and details of the FMS assessment, and did the instruments have acceptable reliability for the specific age group? (4) Did the study report the sources and details of the assessment of potential benefits, and did all the methods have acceptable reliability? (5) Did the study report a power calculation, and was the study adequately powered to detect the hypothesized relationships? (6) Did the study report the numbers of individuals who completed each of the different measures, and did participants complete at least 80% of the FMS and benefit measures? The above questions were scored as 0 (missing or underdescribed) or 1 (clear description and presence), and the scores for all questions were combined. Studies scoring 0–2 were considered low-quality studies, studies scoring 3–4 were classified as medium-quality, and 5–6 were classified as high-quality.

Figure 1 shows the study selection flow chart. A total of 49 articles met the eligibility criteria. These articles all had cross-sectional data, including 44 cross-sectional studies, four longitudinal studies, and one long-term trend study. These articles were published from January 2002 to November 2022. There were 42 English studies and 7 Chinese studies. Eight of the studies were conducted in the UK, eight in China, six in the US, five in Australia, five in Iran, four in Finland, four in Ireland, two in Croatia, and one each in Canada, Slovenia, Brazil, Italy, the Czech Republic, South Korea and South Africa. The study participants ranged from 50 (20) to 6,917 (21). Details are given in Table 1.

The authors had a 94% consensus on the study assessment criteria and reached a complete consensus after discussion. Twenty-eight studies were identified as high-quality, 21 were rated as moderate-quality, and none were classified as low-quality. Most studies used valid and reliable measures of fundamental movement skills assessment. All studies reported reliable data on their potential benefits, methods for valid calculations, and whether the study had sufficient evidence to support the hypothesis relationship.

The literature included 13 fundamental movement skill assessment tools, as shown in Table 2. Because the research topics were limited to fundamental movement skills, the literature using Koperkoordination-Test fur Kinder (KTK) (81) and Bruininks-Oseretsky Test of Motor Proficiency (BOTMP & BOT-2) (82), mainly used to test motor coordination and fine motor skills, was omitted.

The included studies have differences in the selection of fundamental movement skills evaluation tools. Thirty-five studies (71.5%) used process assessment, including 20 studies that used TGMD-2 as a single test, one used TGMD, 7 used POC, 3 used the Fundamental motor skills Assessment, two used OSU-SIGMA, 1 used PDMS-2, and one used Passport for Life and PLAYbasic. Eight (16.3%) studies used outcome assessments, 2 used the PE metric, 3 used the Move!, 1 study used POLYGON, and 2 used MABC-2. Six (12.2%) studies used a combination of process and outcome assessment, 5 of which used the TGMD-3 assessment tool, and 1 used the TGMD-2 and POLYGON.

Among the included literature, there were 4 tools for comprehensive evaluation of health-related fitness, including the health-related fitness test battery for children and adolescents (ALPHA), FitnessGram assessment (FitnessGram), Monitoring system for physical functional capacity (Move!) and National Physical Fitness Test Standards Manual-Preschool part (NPFTSM-Preschool).

ALPHA was published by Ruiz et al. (83) based on assessment methodology for physical activity levels in the European Member States. Testing included a 20-meter shuttle run, grip strength, standing long jump, body mass index, skinfold thickness and waist circumference.

FitnessGram is now the educational assessment of the Presidential Youth Fitness Program (84). The test items include pull-ups for boys/modified pull-ups for girls, straight leg sit-ups, shuttle run, standing broad (long) jump, 50-yd dash, and softball throw for distance, 600-yd run/walk, and three aquatic tests that are rarely used.

Move! is a national physical functional capacity monitoring and feedback system for Finnish 5th and 8th-grade pupils (80). Move! consists of eight sections of measurements that provide information about the state of physical functional capacity. The sections measure pupils' endurance, strength, speed, mobility, balance, and fundamental movement skills. The specific items are the 20-meter line run, five continuous jumps, upper body lift, push-up, body mobility, squat, lower back extension, right and left shoulders, and a throw-catch combination.

NPFTSM-Preschool (85) was promulgated by the Ministry of Education of the People's Republic of China in 2003. The test content included morphometric measures, a 10-meter return run, standing long jump, tennis throwing, continuous jump, sit and reach, and walking on the balance beam.

In addition to the above tools, some studies selected different evaluation tools for comprehensive utilization; for example, Behan et al. (23) adopted BMI and waist circumference, sit and reach, grip strength (86), plank (87), a 20 m sprint run (88) as health-related fitness assessment content.

Moreover, health-related fitness assessment can be an overall assessment of all elements, and it can also be an assessment of only one element. In evaluating sub-elements of health-related fitness, various tools have been used in the included studies.

The cardiopulmonary function was assessed by the PACER (Progressive Aerobic Cardiovascular Endurance Run), 550 m walking and running test (89) or long-distance running (68, 89, 90).

The musculoskeletal function was evaluated by two groups, muscle strength and endurance, and flexibility. Methods to assess muscle strength and endurance included grip strength, curl-ups, push-ups, plank, and standing long jump. Furthermore, methods to assess flexibility included sit and reach and trunk lifting.

Body composition assessment methods were body mass index (BMI), waist circumference (WC), skinfold thickness, body fat percentage (BF%), abdominal fat percentage (AF%), fat mass index (FMI), and fat-free mass index (FFMI).

A total of 10 articles (19, 23, 24, 28, 29, 34, 39, 40, 53, 68) have studied the correlation between fundamental movement skills and cardiopulmonary function, and all the findings showed a significant positive association between fundamental movement skills and cardiopulmonary function.

Among the subitems of fundamental movement skills, five studies (19, 23, 29, 34, 39) showed a significant correlation between locomotor skills and cardiopulmonary function, six studies (19, 23, 28, 29, 34, 39) showed a significant correlation between object manipulation skills and cardiopulmonary function, and three studies (19, 29, 39) showed a significant association between balance skills and cardiopulmonary function. Thus, there is strong evidence for a positive association between the total and subitems of fundamental movement skills and cardiopulmonary function.

A total of 12 studies (23, 28, 29, 34, 36, 39–41, 53, 64, 66, 68) were included that evaluated the correlation between fundamental movement skills and muscle strength and endurance. These studies found a significant positive correlation between total fundamental movement skills and muscle strength and endurance.

Regarding the subitems of fundamental movement skills, seven studies (23, 29, 34, 36, 39, 64, 66) showed a positive correlation between locomotor skills and muscle strength and endurance, eight studies (23, 28, 29, 34, 36, 39, 64, 66) showed a significant correlation of object manipulation skills with muscle strength and endurance, and three studies (34, 40, 68) showed a significant correlation between balance skills and muscle strength and endurance. All studies supported the conclusion that the total and subitems of fundamental movement skills were significantly positively correlated with muscle strength and endurance.

Six studies examined the correlation between fundamental movement skills and flexibility. Four studies (23, 28, 36, 66) showed a significant correlation between fundamental movement skills and flexibility, and 2 showed no significant correlation (29, 64).

Moreover, as to the subitems of fundamental movement skills, one study showed that locomotor skills were significantly associated with flexibility, but the correlations between object manipulation skills and flexibility were not significant (66). Another study (23) found that three subitem skills in the 9–10 age group and the flexibility association were significant; however, in the 11–12 age group, locomotor, and balance skills were still significant, while object manipulation skills were no longer significant. These results indicate that the evidence of the relationship between the total and subitems of fundamental movement skills and flexibility is uncertain.

Forty-three studies examined the correlation between fundamental movement skills and body composition. Twenty-nine studies showed a significant association of overall fundamental movement skills with body composition, and 14 showed no significant association with body composition. Of the 29 significantly related studies, 18 studies used BMI alone as an assessment, four studies (26, 29, 31, 33) used BMI and BF, two studies (24, 53) used BMI and waist circumference, one study (50) used BMI and skinfold thickness, one study (45) used BMI, waist circumference and skinfold thickness, 1 used BF%, AF%, BMI, and waist circumference (58), 1 used FMI and FFM (42), and 1 used BF%, BMI, FMI, and FFMI (62). Of the 14 studies showing no significant association with body composition, 13 studies (19, 22, 27, 35, 37, 40, 47, 53, 55, 56, 59, 64, 67) used BMI as a single body composition assessment method, and one article (24) used both waist circumference and BMI. Overall, studies that used skinfold, AF%, BF%, FM, and FFMI as evaluation methods obtained consistently significant negative correlation results, while in studies that used BMI or waist circumference as evaluation criteria, there was no consistent significant correlation result.

Furthermore, as to the subitems of fundamental movement skills, three studies (23, 29, 39) showed a consistent inverse correlation of balance skills with body composition. Meanwhile, locomotor skills and body composition reflected a more significant correlation than object manipulation skills. Six studies (34, 35, 45, 54, 57, 62) showed that object manipulation skills were not associated with body composition, while locomotor skills were significantly associated with body composition. Therefore, there is evidence that the relationship between locomotor skills and body composition is closer than that of object manipulation skills.

Our study has limitations. Due to the lack of longitudinal research literature, this study only analyzed cross-sectional outcomes. Due to the various evaluation tools and large differences in the outcome data types of the reviewed articles, this review does not offer a quantitative summary (i.e., meta-analysis). With the increase in the research literature, future reviews can analyze the impact of fundamental movement skills on health-related fitness from a longitudinal perspective, explore scientific teaching strategies of fundamental movement skills, and conduct quantitative research data analysis to obtain more accurate correlations.