Could a child’s aerobic fitness be linked to how efficiently they process information? This study examines attention, fitness, age, and sex together—and finds a pattern that is real, but far from uniform. Current sedentary behavior of children over the last decade has created a huge problem for society.

The development of video games and mobile screens has led to children spending more time playing video games to the detriment of physical activity. Sedentary lifestyles in children trigger metabolic diseases such as obesity or other psychological illnesses such as depression.

Levels of physical activity are reported to be lower than in previous years and continue to decline, exacerbated by the pandemic situation. A high number of children and pre-adolescents do not achieve the recommended level of physical activity. Aerobic capacity has been suggested as the best predictor of cognitive function, and oxygen consumption as the best predictor of attentional parameters.

A recent systematic review reported that higher aerobic capacity is related to higher academic performance, so research on physical activity levels, academic performance, and attention has been booming in recent years. Physical activity involves the development of attention in childhood, especially in open-task sports, which require decision-making in which the child needs to be highly attentive.

An association between the D2 attention test and fitness level has also been reported. This study followed a cross-sectional design, and convenience sampling was performed. The study was conducted in January 2022, and students were assessed three times, with the first, second, and third assessments separated by one week.

The purpose was to understand the relationship between cognitive ability reflected in the D2 attention test and physical fitness through the 6 min walking test, considering sex and age as moderators. During the assessment, 12 participants were excluded: six could not perform the D2 attention test, and six performed only one or two assessments.

Finally, 187 participants remained and completed the entire experiment. The 6 min Walking Test is a sub-maximal exercise test used to assess aerobic capacity and endurance, developed by the American Thoracic Society.

Participants walked back and forth in a straight line as fast as possible, with a self-paced effort, over a 6-minute period of time. Heart rate was measured during the 6 min Walking Test by telemetry, using a Heart Rate Transmitter Model T34 from Polar. Once the test was over, the total distance carried out over 6 minutes was registered as the result of the 6MWD test.

Eighty boys were asked to repeat the test after one week to confirm reproducibility. Selective attention was measured individually with the D2 attention test, which analyzes the visual ability to scan and select relevant aspects of a task while ignoring irrelevant ones quickly and accurately.

The test consists of 14 rows of 47 characters each, with a total of 658 elements. Subjects have 20 seconds per row and have to mark as many of the target d’s as possible. The scores include TR, processed elements; TA, successes; O, omissions; C, commissions or errors; and additional measures of effectiveness, concentration, variation, and the most and least attempted rows.

This test has a test–retest reliability in the original study up to 0.90. Table one summarizes participant characteristics for the one hundred eighty-seven individuals, divided into age groups from nine to fifteen years.

It reports sample size, height, body weight, body mass index, and maximal oxygen consumption as mean plus or minus standard deviation. This descriptive baseline matters because it shows how the study population is distributed across ages and documents variation in physical and aerobic characteristics before interpreting the later analyses.

The two-factor ANOVAs examined different D2 attention scores, including TR, TA, TR plus, TR minus, omissions, commissions, and the DA score. They showed no statistically significant interaction between sex and age in any case, with p greater than 0.05.

Tukey HSD showed significant differences in TR between the 9-, 10-, and 11-year-old groups and the 13-, 14-, and 15-year-old groups. For TA, significant differences appeared between the 9- and 10-year categories and the 15-year-old category. For TR plus, differences appeared between the 10-year group and the 14- and 15-year-old groups, and between the 11-year group and the 13-, 14-, and 15-year-old groups.

For TR minus, significant differences appeared between the 9-year-old group and the 13-, 14-, and 15-year-old groups, and between the 10- and 11-year-old groups. Table Two summarizes two-way ANOVAs testing sex, age category, and their interaction across six DA scores.

Age category is statistically significant for TR, with p less than or equal to zero point zero zero zero one, for TA, with p equal to zero point zero zero four, and for both TR plus and TR minus, with p less than or equal to zero point zero zero zero one. Sex is not significant for any score, and none of the interactions is statistically significant, supporting the authors’ conclusion that sex and age do not interact in these measures.

For correlations between the different D2 attention scores and VO2max obtained in the 6 min Walking Test, a positive moderate correlation was found for TA in the 11-to-12-year-old group and for O in the 9-year-old group. A negative moderate correlation was found for O in the 11-to-12-year-old group.

A positive large correlation was found for TR, TR plus, and TR minus in students who were 15 years old. Figure two shows regression lines linking attention-task scores with estimated VO2 max in fifteen-year-old children, and linking the O score with BMI in eleven- and twelve-year-olds.

The first three panels use TR, TR plus, and TR minus scores, with reported R-squared values of zero point three four nine nine, zero point two seven nine two, and zero point two six five four. The BMI panel reports an R-squared of zero point two five one three, illustrating the associations examined by the authors.

The research has limitations, including the absence of contextual factors that could act as covariables, such as academic level and achievements and other cognitive functions. Physical activity time and intensity per week would be beneficial to characterize the sample and combine with information on body mass index and aerobic fitness.

The study had an observational character, allowing only correlations between variables considering different ages and genders, and not the effect that a possible improvement in aerobic capacity would have on cognition. Future studies are suggested to evaluate this possible influence, although the study represents an opportunity to differentiate cognitive function between ages, sexes, and physical fitness and anthropometry levels of students.

Students with better aerobic fitness can present better-processed elements and smaller omission errors. Girls and older students seem to present better cognitive functioning scores than boys and younger students. The results may not be generalized because the specific relationships were not global for all ages, and differences between sexes and ages were not always significant for all cognitive functioning scores.

The study links better aerobic fitness with more processed elements and fewer omission errors, while girls and older students generally show better cognitive functioning scores. But the observational design cannot prove that fitness causes better cognition.