Body Fat Percentage Was Linked to Lower Motor Fitness in 306 Croatian Children

Body fat percentage, not body mass index, tracked most closely with motor fitness in 306 Croatian schoolchildren. Muscle mass showed no independent association with motor fitness once age and sex were accounted for.

Motor fitness in late childhood was tied more closely to how much fat a child carried than to body mass index, according to a cross-sectional study of 306 nine- to eleven-year-olds published on October 6, 2026 in Frontiers in Sports and Active Living.

The analysis was carried out by Leona Roca Badrić, Marko Badrić and Igor Vrga of the Faculty of Teacher Education at the University of Zagreb, with Dario Novak of the same university Faculty of Kinesiology. Children were recruited from 11 primary schools in the City of Zagreb, Zagreb County and Sisak-Moslavina County during the 2024/2025 school year.

The sample held 163 girls and 143 boys with a mean age of 9.89 years and a standard deviation of 0.60. Standing height came from a SECA 213 stadiometer. Body composition came from a Tanita DC-360 P bioelectrical impedance analyzer, which supplied body mass index, body fat percentage, fat mass, muscle mass and waist-to-height ratio.

Motor fitness was not reduced to a single test. The researchers ran hand tapping over 15 seconds, a standing long jump scored on the better of two attempts, a sit-up count and a 10 x 5 m shuttle run, then converted each result into a standardized Z-score and combined the four into a composite index they label MOTOFIT.

What the Four Tests Were Asked to Capture

Each of the four items loads a different quality. Hand tapping reads speed of limb movement. The standing long jump reads explosive lower-body power. Sit-ups read trunk muscular endurance. The shuttle run reads agility and change of direction under time pressure. Pooling them into a single motor fitness index is an attempt to describe general movement competence rather than one narrow trait.

That pooling matters for how the results should be read. A composite motor fitness score smooths out a child who happens to be a strong jumper but a slow tapper. It also means no single test result drives the headline motor fitness association on its own.

Body Fat Percentage Outperformed Body Mass Index

In the simple correlations, body fat percentage held the strongest negative relationship with motor fitness at r = -0.252 and p below 0.001. Waist-to-height ratio came next at r = -0.209, fat mass at r = -0.205 and body mass index last among the significant measures at r = -0.170 with p = 0.003.

The ordering held after the authors adjusted for age and sex in separate hierarchical regression models. Body fat percentage added an incremental R-squared of 0.057 to the explained variance in motor fitness. Waist-to-height ratio added 0.051, fat mass 0.042 and body mass index 0.037.

The gap between 0.057 and 0.037 is not dramatic, but it points in a consistent direction. Measures that describe how much fat a child carries, and where, related more closely to movement performance than the height-and-weight ratio that school screening programs lean on most heavily.

Why Muscle Mass Added Nothing to the Motor Fitness Model

The null finding is as interesting as the positive one. Muscle mass correlated with motor fitness at r = -0.009 with p = 0.875, which is indistinguishable from no relationship, and it did not contribute significantly to the adjusted model either.

One plausible reading is that absolute muscle mass in nine- to eleven-year-olds says little about how well a child moves a body of that size. Three of the four tests are weight-bearing, so extra tissue has to be accelerated, lifted or turned. Our earlier report on resistance training and muscle growth across 1,443 young people found only small hypertrophy effects at these ages, which fits a picture in which muscle size is not yet the limiting factor.

Central Fat Carried Almost as Much Information

Waist-to-height ratio sat close behind body fat percentage on both the correlation and the regression measures of motor fitness. That is useful in practice, because a tape measure costs almost nothing and needs no electrical current, no hydration control and no calibration.

The authors group children by adiposity status as a separate check. The grouped comparison was significant, F(2,301) = 11.764, p below 0.001, with a partial eta squared of 0.072. Children in the normal body fat group recorded higher adjusted composite scores than children with elevated body fat, p = 0.004, and than children with obesity, p below 0.001.

Girls and Boys Did Not Score the Same

Boys recorded higher composite motor fitness scores than girls, t = -2.68, p = 0.008, with a Cohen d of -0.31. Boys also carried more muscle mass, t = -3.00, p = 0.003, d = -0.35, and jumped further in the standing long jump, t = -2.09, p = 0.037, d = -0.24. Body mass index also differed, t = -2.31, p = 0.021, d = -0.27.

These are small effects by conventional standards, and every regression model in the paper was adjusted for sex before the adiposity results were reported. The sex differences therefore sit alongside the main finding rather than explaining it.

What a Single Snapshot Cannot Show

Everything here was measured on one occasion, so the direction of the relationship is open. Children with less body fat may move better because they have less mass to shift, or children who move more may accumulate less fat, or both may run together. The authors say as much, noting that bidirectional relationships are plausible.

The design is also missing variables that would plausibly matter. Habitual physical activity, biological maturation, diet and socioeconomic context were not in the models. That is a real gap at an age when two children of the same height can be a year apart in maturation, a point we have run into before in reporting on physical fitness and arithmetic fluency in 1,166 adolescents.

What This Does and Does Not Mean for Families

The practical reading is narrow. A single body-composition number does not predict what any individual child can do on a field, and an association of this size leaves most of the variation in motor fitness unexplained. What the study supports is a measurement argument rather than a training prescription.

For anyone tracking children at school or in a club, the findings suggest a few modest habits:

• Treat body mass index as a screening number, not a description of how a child moves.
• Add a waist measurement, which tracked motor fitness nearly as well as impedance-derived fat.
• Score motor fitness across several tasks rather than one, since a composite is harder to distort.
• Read any single assessment as a starting point and look for change over a school year.

None of that replaces ordinary advice to keep children playing and moving. Readers interested in how body-composition estimates themselves can mislead may want our coverage of large errors in body fat prediction formulas, and for the training side, our report on suspension training adding jump height in 71 untrained teenagers shows how quickly movement scores can shift at these ages.