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Introduction
Physical fitness is a set of attributes that people acquire or improve and is related to the ability to perform activities of daily living without excessive fatigue. The components of health-related fitness include cardiorespiratory fitness (CRF), musculoskeletal fitness, balance, and body composition. The potential protective role of fitness against high blood pressure in childhood is a relevant topic, as high blood pressure in childhood commonly leads to hypertension in adulthood1, which in turn is a risk factor for coronary heart disease, heart failure, and stroke2.
Most research in pediatric populations has documented a negative association between CRF and hypertension3-5. In a systematic review6 of 20 longitudinal studies, CRF in childhood and adolescence was a predictor of cardiovascular disease risk factors (e.g., abnormal blood lipids or high blood pressure), metabolic syndrome, and arterial stiffness later in life. One limitation of this type of research is that, in most cases3,4, the potential role of body mass as a confounding variable of the association between fitness and blood pressure has not been considered. Only one study has performed this adjustment5. The confounding role of body mass is produced by its negative relationship with CRF7,8 and its positive association with blood pressure3,9,10. The clinical relevance of making the distinction between the effect of CRF and body mass on blood pressure is to collect information to guide individuals for the prevention and reduction of high blood pressure risk. In other words, if the CRF has an independent effect on blood pressure, it should be a priority to intensify CRF to promote healthy blood pressure. In contrast, if the effect disappears after the adjustment by body mass index (BMI), the attention should be focused on preventing excessive weight gain.
In the pediatric population, the effects of other components of fitness (such as flexibility and muscular fitness) on blood pressure have been less studied. For example, there is less and inconclusive evidence6 about the relationship between muscular strength and cardiovascular risk factors (e.g., systolic blood pressure or blood lipids). In a review, only five longitudinal studies analyzed this association; in two of them, muscular strength was not associated with systolic or diastolic blood pressure, and the correlation between the neuromotor fitness index and the systolic and diastolic blood pressure was positive6. In another study, the association of strength with systolic blood pressure was negative.
More research is necessary to identify the factors that determine blood pressure in childhood, especially in children from middle-income countries, as they are exposed to a different socioeconomic environment and have distinct genetic characteristics from those in high-income countries. Therefore, the objective of this study was to evaluate whether the association between fitness and blood pressure in Mexican schoolchildren was independent of body mass.
Methods
A cross-sectional design was conducted with a convenience sample of children aged 9-12 years from 13 elementary schools in Mexico City. Before the study, an informed consent form was signed by parents or guardians and written assent from children was obtained. Fieldwork was conducted between June 2011 and February 2012. The project was approved by the Divisional Council of Biological Sciences and Health of the Universidad Autónoma Metropolitana, Unidad Xochimilco.
The sample size was estimated with an expected prevalence of hypertension of 22% and an odds ratio (OR) of 1.75 with the Epidat software11,12. Although previous research had reported an OR of 2.00 or higher4, a conservative estimate was used for this study because, in past studies, a few variables were considered as confounders and not included as covariates in the regression models. With these parameters, an estimated sample size of 915 participants was obtained. After fieldwork and database cleaning, the sample consisted of 1010 participants.
Fitness was evaluated using the FitnessGram® battery procedures developed by the Cooper Institute. The procedures and validity of the tests have been described elsewhere13. The research assistants received training, and pilot tests were conducted prior to fieldwork to ensure that they followed the procedures. The fitness components assessed in this study were as follows:
a. CRF. The number of laps in the 20-m progressive aerobic cardiovascular endurance run test was recorded. Maximal aerobic capacity (VO2max) was estimated using the Mahar equation14.
b. Muscular strength and endurance. The number of curl-ups (which is a proxy for core strength), push-ups (upper body strength), and trunk lifts (trunk extensor strength) was documented.
c. Flexibility. The back-saver, sit-and-reach, and shoulder stretch tests were used to measure the flexibility of the back, legs, and shoulders, respectively.
The recorded audio from the FitnessGram® battery was used to instruct children to follow the pace in all tests and they were encouraged to perform their maximal effort. Due to the sex- and age-related differences in fitness, specific standards for these variables should be used to classify the fitness level of children. The criteria of the California Department of Education15 were used to classify this fitness level. More research has been done about the effects of CRF on health. Therefore, this dimension of physical fitness can be categorized in three levels: healthy zone (minimal disease risk), needs improvement (subject should be encouraged to increase his/her fitness because there is moderate risk of disease), and needs improvement-health risk (there is high risk of disease risk and subjects should be cautioned to improve her/his fitness)13. For the rest of the fitness indicators, only two categories are described: a healthy zone and needs improvement.
Resting blood pressure was measured using OMRON digital Baumanometer (models HEM 781 IT and 705 IT), which has been previously validated in children and adolescents16. To measure blood pressure, standardized procedures were followed: children were seated quietly for 5 min with their back supported, their feet on the floor, and their right arm supported, with the cubital fossa at heart level17. Pediatric cuffs of different sizes were used according to the arm circumference of each child. Blood pressure measurement was repeated with the same monitor when the participants had values higher than 120/80 mmHg because the American guidelines17 consider this level as pre-hypertension and it is more convenient for the fieldwork.
For data analysis, children were classified as having hypertension if their blood pressure was > percentile 95 for sex, age, and height of the American reference17. The height of the participants was classified according to the 2000 Centers for Disease Control and Prevention Growth Charts18. Three variables were constructed: isolated systolic hypertension (i.e., systolic blood pressure > percentile 95 but diastolic blood pressure < percentile 95), isolated diastolic hypertension (elevated diastolic blood pressure but normal systolic blood pressure), and systolic-diastolic hypertension (raised systolic or diastolic blood pressure or both).
Nutritional status was assessed by anthropometric measures (weight, height, and sitting height), which was obtained following standardized measurement techniques19. Observers were trained and standardized before the study. The Z-scores of BMI-for-age and height-for-age were estimated using the World Health Organization references20. Low height was defined as a Z-score of height-for-age ≤ −2.00 standard deviation (SD) and normal height as a Z-score ≥ −1.99 SD. Three categories were defined according to the Z-score of BMI-for-age: normal weight (≤ 0.99 SD), overweight (1.00-1.99 SD), and obesity (≥ 2.00 SD).
Statistical analysis was conducted using SPSS version 21 (Chicago, IL). Descriptive statistics of anthropometric characteristics (Table 1) and physical fitness (Table 2) were estimated. Bivariate analyses were performed to identify differences in anthropometric characteristics according to hypertension classification (Table 1), hypertension rates according to fitness level (Table 3), or differences in fitness according to BMI-for-age (Table 4). For categorical variables, Chi-square tests were performed to determine the differences between groups, and for continuous variables, Students t-test. Subsequent analyses were performed only for variables with statistically significant differences between groups.
Table 1 Anthropometric characteristics of a sample of Mexican schoolchildren and differences by blood pressure
| Overall sample | Differences by blood pressure | |||
|---|---|---|---|---|
| n | % | Normal (%) | Hypertension (%) | |
| Sex | ||||
| Males | 436 | 43.2 | 42.7 | 44.7 |
| Females | 574 | 56.8 | 57.3 | 55.3 |
| BMI-for-age (Z-score) | ||||
| Low weight (≤ −2.0) | 22 | 2.2 | 2.6 | 0.8‡ |
| Normal (−1.9-0.9) | 553 | 54.8 | 60.3 | 37.4 |
| Overweight (1.0-1.9) | 241 | 23.9 | 23.0 | 26.4 |
| Obesity (≥ 2.0) | 194 | 19.2 | 14.0 | 35.4 |
| Height-for-age (Z-score) | ||||
| Low height (≤ −1.0) | 19 | 1.9 | 2.0 | 1.6 |
| Normal height (≥ −0.9) | 991 | 98.1 | 98.0 | 98.4 |
| Blood pressure | ||||
| Hypertension | 246 | 24.4 | ||
| Hypertension systolic | 200 | 19.8 | ||
| Hypertension diastolic | 109 | 10.8 | ||
| Mean | SD | Mean | Mean | |
| Age (years) | 10.3 | 0.9 | 10.4 | 10.4 |
| Weight (kg) | 40.4 | 10.8 | 39.9 | 45.0‡ |
| Height (cm) | 142.8 | 8.8 | 142.3 | 144.2‡ |
| BMI (kg/m2) | 19.6 | 4.0 | 19.0 | 21.4‡ |
| Height (Z score) | −0.01 | 1.07 | −0.09 | 0.22‡ |
| BMI (Z score) | 0.76 | 1.29 | 0.58 | 1.33‡ |
| Systolic blood pressure (mmHg) | 109.4 | 14.3 | ||
| Diastolic blood pressure (mmHg) | 65.9 | 12.1 | ||
| Heart rate (bpm) | 84.6 | 13.8 | 83.5 | 88.0‡ |
n, frequency; SD, standard deviation; BMI, body mass index; bpm, beats per minute. †p < 0.01;
‡p < 0.001.
Table 2 Physical fitness of a sample of Mexican schoolchildren and differences by blood pressure
| n | % | |
|---|---|---|
| Cardiorespiratory fitness | ||
| Needs improvement-health risk | 395 | 50.0 |
| Needs improvement | 161 | 20.3 |
| Healthy zone | 236 | 29.7 |
| Curl-ups | ||
| Needs improvement | 620 | 62.7 |
| Healthy zone | 369 | 37.3 |
| Push-ups | ||
| Needs improvement | 750 | 77.5 |
| Healthy zone | 218 | 22.5 |
| Trunk lift | ||
| Needs improvement | 462 | 45.8 |
| Healthy zone | 546 | 54.2 |
| Sit and reach | ||
| Needs improvement | 557 | 55.4 |
| Healthy zone | 449 | 44.6 |
| Shoulder stretch | ||
| Needs improvement | 488 | 48.7 |
| Healthy zone | 515 | 51.3 |
| Mean | SD | |
| PACER test (laps number) | 14.7 | 8.5 |
| VO2max (ml/kg/min) | 37.6 | 5.0 |
| Curl-ups (number) | 12.1 | 13.3 |
| Push-ups (number) | 21.6 | 5.4 |
| Trunk lift (cm) | 4.1 | 5.8 |
| Sit and reach (left leg) (cm) | 22.7 | 7.5 |
| Sit and reach (right leg) (cm) | 22.5 | 7.6 |
n, frequency; SD, standard deviation; PACER, progressive aerobic cardiovascular endurance run; VO2max, predicted maximal aerobic capacity.
Table 3 Prevalence of hypertension according to fitness and body mass index-for-age in a sample of Mexican schoolchildren
| Systolic or diastolic hypertension or both | Isolated systolic hypertension | Isolated diastolic hypertension | |
|---|---|---|---|
| n = 1010 | % | % | % |
| Cardiorespiratory fitness | |||
| Needs improvement-health risk | 29.1* | 24.3* | 10.6 |
| Needs improvement | 21.7 | 19.3 | 8.7 |
| Healthy zone | 20.3 | 15.7 | 9.7 |
| Curl-ups | |||
| Needs improvement | 24.8 | 20.3 | 11.6 |
| Healthy zone | 23.6 | 18.7 | 10.0 |
| Push-ups | |||
| Needs improvement | 26.1* | 21.5* | 11.3 |
| Healthy zone | 18.8 | 14.2 | 9.6 |
| Trunk lift | |||
| Needs improvement | 22.9 | 18.4 | 10.0 |
| Healthy zone | 25.6 | 21.1 | 11.5 |
| Sit and reach | |||
| Needs improvement | 23.7 | 18.5 | 9.7 |
| Healthy zone | 25.2 | 21.4 | 12.2 |
| Shoulder stretch | |||
| Needs improvement | 24.0 | 19.7 | 9.6 |
| Healthy zone | 24.7 | 19.8 | 11.8 |
| Body mass index-for-age | |||
| Normal | 16.3‡ | 12.2‡ | 9.4 |
| Overweight | 27.0 | 23.2 | 10.8 |
| Obesity | 44.8 | 38.1 | 14.9 |
Comparisons according to fitness categories (e.g., needs improvement vs. healthy zone) and to body mass index (e.g., normal vs. obesity).
*p < 0.05;
‡p < 0.001.
Table 4 Association of body mass index-for-age with low fitness in a sample of Mexican schoolchildren
| Normal (%) | Overweight (%) | Obesity (%) | p | |
|---|---|---|---|---|
| Subjects that need to improve or with health risk | ||||
| CRF-health risk | 32.1 | 60.6 | 87.7 | ‡ |
| CRF-need improvement | 24.5 | 20.7 | 7.8 | |
| Curl-ups | 57.5 | 64.4 | 76.1 | ‡ |
| Push-ups | 69.3 | 83.8 | 94.0 | ‡ |
| Trunk lifts | 50.9 | 41.1 | 36.8 | † |
| Sit and reach | 53.2 | 53.3 | 64.4 | * |
| Shoulder stretch | 40.7 | 49.4 | 71.6 | ‡ |
CRF, cardiorespiratory fitness.
*p < 0.05;
†p < 0.01;
‡p < 0.001.
Logistic regression models were estimated to determine whether the association of fitness with blood pressure was independent of BMI-for-age (Table 5). In the crude models, the blood pressure categories were introduced as dependent variables and fitness indicators as independent variables. Subsequently, for each dimension of fitness, two models were estimated: model A was adjusted by sex and age while model B was adjusted by the same covariates and BMI-for-age.
Table 5 Logistic regression models having hypertension as an outcome and cardiorespiratory fitness and push-ups test as exposures
| Outcome: hypertension exposure: CRF1 | Outcome: hypertension exposure: push-ups2 | |||
|---|---|---|---|---|
| OR | CI 95% | OR | CI 95% | |
| Crude model | ||||
| Physical fitness | ||||
| Healthy zone | Reference | Reference | ||
| Needs improvement | 1.09 | 0.66-1.77 | 1.53 | 1.05-2.22 |
| Needs improvement-health risk | 1.61 | 1.09-2.36 | ||
| Adjusted model A* | ||||
| Physical fitness | ||||
| Healthy zone | Reference | Reference | ||
| Needs improvement | 1.28 | 0.77-2.12 | 1.57 | 1.07-2.29 |
| Needs improvement-health risk | 2.05 | 1.33-3.15 | ||
| Adjusted model B** | ||||
| Physical fitness | ||||
| Healthy zone | Reference | Reference | ||
| Needs improvement | 0.94 | 0.56-1.59 | 1.12 | 0.75-1.68 |
| Needs improvement-health risk | 0.87 | 0.52-1.47 | ||
| Body mass index-for-age | ||||
| Normal | Reference | Reference | ||
| Overweight | 1.88 | 1.23-2.89 | 1.80 | 1.25-2.60 |
| Obesity | 4.48 | 2.71-7.39 | 3.59 | 2.44-5.28 |
Sample sizes:
1792 and
2968. CRF: cardiorespiratory fitness; OR: odds ratio; CI 95%: 95% confidence intervals; Reference: group of reference.
*Adjusted by sex and age;
**Adjusted by sex, age, and body mass index-for-age.
In the statistical analysis, the sample size decreased for some variables because children were unwilling to participate (due to either lack of motivation or physical issues), schoolchildren did not have enough time, and reference standards for VO2max were not available for children under 9 years of age (in this case, only the lap number was analyzed).
Results
The mean age of the schoolchildren was 10.3 ± 0.9 years and 56.8% were females (Table 1). A high percentage of participants (43.0%) were overweight or obese and 1.9% showed low height-for-age. The prevalence of systolic hypertension, diastolic hypertension, and hypertension was 19.8%, 10.8%, and 24.4%, respectively. Schoolchildren with hypertension were heavier and taller, and their heart rate was higher compared with those without hypertension (p < 0.05).
Over two-thirds of the children showed low levels of fitness for push-ups, CRF, and curl-ups (Table 2). Around half of the participants showed low scores in the following tests: sit-and-reach, shoulder stretch, and trunk lift.
A higher probability of hypertension and isolated systolic hypertension was predicted for schoolchildren who needed to improve their CRF or upper body strength, and those with overweight or obesity (Table 3).
A higher frequency of poor CRF, abdominal strength and endurance, upper body strength, back and legs flexibility, and shoulder flexibility was observed in obese children (Table 4).
Children classified at health risk by their CRF showed a higher probability of hypertension (Table 5). The higher risk of hypertension persisted after adjusting the model by age and sex. However, after including BMI-for-age, the differences disappeared. In model B, only BMI-for-age was associated with hypertension.
A higher risk of hypertension was estimated for children who needed to improve their upper body strength as well (Table 5). These associations remained after adjusting the model by age and sex. In contrast, after including BMI-for-age, the differences were not statistically significant. In model B, only BMI-for-age was associated with hypertension as well.
Discussion
The purpose of this study was to determine whether the relationship of fitness with blood pressure in Mexican schoolchildren was independent of body mass. In this Mexican children sample, poor CRF and upper body strength were related to a higher risk of systolic hypertension. However, this relationship disappeared after adjusting for BMI. In addition, higher levels of BMI were negatively correlated with most fitness levels.
Except for the trunk lift test, children with overweight or obesity performed poorly in the fitness tests. Although the association of flexibility with BMI has been inconsistent21,22, a negative correlation of BMI with CRF7,8,21,23 and muscular strength and endurance21,24,25 has been systematically observed in pediatric populations. Some of the characteristics of children with overweight or obesity, such as a tendency to a more sedentary lifestyle26, to experience fatigue faster27, and to present lower performance in aerobic tests28 can explain these differences. Furthermore, they perceive more difficulty with several activities of daily living29, and these difficulties may limit their performance during fitness tests because they face unfamiliar situations such as effort exertion, muscle fatigue, and discomfort.
Unexpectedly, Mexican children with normal weight showed a higher probability of poor performance in the trunk lift test than those with overweight or obesity. In two samples of American children, BMI was not associated with performance in this test21,30. One possible explanation is that trunk extensor strength is influenced by body size, i.e., trunk weight serves as natural resistance. Therefore, heavier subjects may develop more strength in this region. However, this association could be spurious and adjustments for potential confounders are needed in future research.
In the present sample, poor CRF was associated with a higher risk of hypertension, but this association disappeared after adjusting for BMI. In previous studies, a negative association with CRF has been reported3-5,31. However, the potential role of body mass or adiposity was not taken into account. In contrast, in one study5, this association disappeared after adjusting for BMI, consistent with these results. These findings could suggest that rather than having a direct and independent effect on blood pressure, CRF is a mediating variable between body weight and blood pressure. However, other mediating variables could exist, as the relationship between BMI and blood pressure remained after adjusting for fitness.
In this Mexican children sample, upper body strength was negatively related to blood pressure; however, this association disappeared after adjusting for BMI. This relationship may emerge clearly during adolescence, as shown in a study with Spanish schoolchildren25, but this relationship disappeared after adjusting for BMI (similar results as obtained in this research). In adolescents, weak to moderate negative correlations were observed for muscle fitness and CRF with cardiovascular risk factors and this correlation was stronger between systolic blood pressure and muscle fitness than with CRF. This relationship remained after stratifying by BMI32. In Norwegian children and adolescents31 and Spanish adolescents33, muscle fitness was negatively related to cardiometabolic risk, independent of CRF. Unfortunately, in both studies, adjustment for body weight was not performed. Although strength training could lower blood pressure34, the evidence regarding the association of muscle fitness with blood pressure for children is insufficient and inconclusive.
The strengths of this study include the sample size and the heterogeneity of the participants, as they were recruited from different schools in Mexico City. However, the results should be interpreted with caution considering the limitations of the design. Furthermore, the use of automatic blood pressure monitors which are not the recommended method because, in older people, they provide underestimated measures should be considered35. However, the validity of these devices has been tested16 and they have advantages, such as the elimination of the observer error, the minimizing of the white coat effect, and the opportunity to reduce costs associated with the training of observers35.
The cross-sectional design of the study precludes from making causal conclusions and convenience sampling limits the possibility of extrapolation. In the case of the logistic regression model with CRF as exposure, the lack of reference to classify younger children yields that more than 20% of the data of the participants were excluded, which reduces the validity of the model. Besides, the models were not adjusted by sexual maturity, which can affect physical fitness.
In summary, in this group of Mexican children, low CRF and muscle fitness were negatively related to the risk of hypertension. However, these associations disappeared when controlling for BMI. With one exception5, most studies3,4 have not accounted for the potential role of BMI as a confounding variable in the relationship between fitness and blood pressure. This confounding effect can explain the discrepancies between the present results and those previously reported.
Ethical disclosures
Protection of human and animal subjects. The authors declare that no experiments were performed on humans or animals for this study.
Confidentiality of data. The authors declare that they have followed the protocols of their work center on the publication of patient data.
Right to privacy and informed consent. The authors declare that no patient data appear in this article.
