European Journal of Sport Science Cardiorespiratory ...

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Cardiorespiratory fitness, fatness, and cardiovascular disease risk factors in children and adolescents from Porto Clarice L. Martins a; Francisco Silva b; Anelise R. Gaya a; Luisa Aires a; José C. Ribeiro a; Jorge Mota a a Research Centre in Physical Activity, Health and Leisure, Faculty of Sports Science, University of Porto, Porto, Portugal b Department of Physical Education and Health, Catholic University of Brasilia, Brasilia, Brazil Online publication date: 08 February 2010

To cite this Article Martins, Clarice L., Silva, Francisco, Gaya, Anelise R., Aires, Luisa, Ribeiro, José C. and Mota,

Jorge(2010) 'Cardiorespiratory fitness, fatness, and cardiovascular disease risk factors in children and adolescents from Porto', European Journal of Sport Science, 10: 2, 121 — 127 To link to this Article: DOI: 10.1080/17461390903307842 URL: http://dx.doi.org/10.1080/17461390903307842

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European Journal of Sport Science, March 2010; 10(2): 121127

ORIGINAL ARTICLE

Cardiorespiratory fitness, fatness, and cardiovascular disease risk factors in children and adolescents from Porto

CLARICE L. MARTINS1, FRANCISCO SILVA2, ANELISE R. GAYA1, LUISA AIRES1, ´ C. RIBEIRO1, & JORGE MOTA1 JOSE 1

Research Centre in Physical Activity, Health and Leisure, Faculty of Sports Science, University of Porto, Porto, Portugal, and Department of Physical Education and Health, Catholic University of Brasilia, Brasilia, Brazil

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2

Abstract In the present study, we examined different categories of cardiorespiratory fitness and obesity and their relationship with risk of cardiovascular disease (CVD) factors in youth. We hypothesized that youngsters with low cardiorespiratory fitness would be at greater risk of CVD risk factors, whether they are obese or not. This study was carried out as a part of a longitudinal research project conducted in the Porto and Braga districts, Portugal, with children and adolescents aged 1016 years of age. A total of 392 children (173 boys, 219 girls) participated in the study. We used a chi-square test to analyse the relationship between the participants’ cardiorespiratory fitness and body weight (non-overweight or overweight/obese). For the purpose of this study, a new variable with four groups was created: non-overweightunfit (37.4%), non-overweightfit (35%), overweight/obeseunfit (11%) and overweight/obesefit (10%). A one-way analysis of variance was used to compare the differences according to fitness and fatness groups. The main finding of this study was that regardless of fatness, participants with higher cardiorespiratory fitness presented with a lower prevalence of CVD risk factors.

Keywords: Cardiorespiratory fitness, fatness, cardiovascular disease risk factors, children and adsolescents

Introduction There is strong evidence that physical activity and cardiorespiratory fitness may protect both males and females from the adverse effects of obesity on health (Nassis, Psarra, & Sidossis, 2005). Many studies have shown that having a moderate to high cardiorespiratory fitness is associated with a lower risk of poor health outcomes (LaMonte et al., 2005; Lee et al., 2005), including cardiovascular diseases (Blair et al., 1996) and all-cause mortality (Wei, Gibbson, Kampert, Nichaman, & Blair, 2000). In young populations, observational studies have shown that childhood obesity is associated with a metabolic risk profile (Mesa et al., 2006) and a sedentary lifestyle is suggested to be implicated in this trend (Maffeis, Zaffanello, & Schutz, 1997). The results of several studies have shown that there is an inverse correlation between obesity and cardiorespiratory fitness in children and adolescents (Andersen et al., 2003; Gutin et al., 2005; Ruiz et al., 2006a,

2006b), thus when low cardiorespiratory fitness is associated with overweight and obesity, there is a risk of the development of other cardiovascular disease (CVD) risk factors in children and adolescents (Møller, Wedderkoop, Kristensen, Andersen, & Froberg, 2007). Moreover, Blair and colleagues have continuously demonstrated that within a fatness level, cardiorespiratory fitness could attenuate the risk of diseases (Lee et al., 2005). There is evidence that when individuals are cross-tabulated into categories, fitness levels could attenuate the prevalence of risk factors among fat children and adolescents, as in epidemiological approaches (Eisenmann et al., 2005; Eisenmann, Welk, Wickel, & Blair, 2007). Although there is a lack of consensus regarding the use of different procedures and the appropriate cutoff points to establish fitness performance related to health, difficulty in comparing and interpreting results, and the ongoing controversy of whether fit

Correspondence: C. L. Martins, Research Centre in Physical Activity, Health and Leisure, Faculty of Sports Science, University of Porto, Rua Dr. Pla´cido Costa, 4200-450 Porto, Portugal. E-mail: [email protected] ISSN 1746-1391 print/ISSN 1536-7290 online # 2010 European College of Sport Science DOI: 10.1080/17461390903307842

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youth have fewer CVD risk factors than their unfit peers, the effect of being obese or not remains unclear. Additionally, low cardiorespiratory fitness could be partially responsible for deleterious consequences of CVD risk factors in youth (Katzmarzyk, Malina, & Bouchard, 1999). Based on the above, the present study analysed different categories of cardiorespiratory fitness and obesity and their relationship with CVD risk factors in youth. We hypothesized that youngsters with low cardiorespiratory fitness would have higher risk of CVD risk factors, regardless of whether they are obese or not.

Blood pressure Systolic and diastolic blood pressure (BP) was measured using Dinamap adult/paediatric and neonatal vital signs monitors (model BP8800). Measurements were taken by a trained technician and with all children seated after at least 5 min rest. Two measurements were taken after 5 and 10 min of rest. The mean of these two measurements was used for statistical analysis. If the two measurements differed by 2 mmHg or more, the protocol was repeated (two new measurements, which were not to exceed 2 mmHg). The detailed process has been described elsewhere (Ribeiro et al., 2004). The data analysed correspond to the medium blood pressure calculated as follows: (systolic BP2 diastolic BP)/3.


Methods and participants Design and sample

Anthropometry

This study was undertaken as a part of a longitudinal research project on the prevalence of CVD risk factors and levels of physical fitness in children and adolescents aged 1016 years, and conducted in Porto and Braga districts, Portugal. Children and adolescents were chosen at random from the third to the twelfth grade, according to general school system rules and as previously described (Ribeiro et al., 2004). A total of 392 children participated in the study (173 boys, 219 girls). Parents and schools approved the study protocol and all parents signed an informed consent. Students were apparently healthy and not taking any medications. All measures were carried out by specialists (physical education teachers, medical doctor).

Height was measured to the nearest millimetre barefoot or in stockings with the adolescent standing upright against a Holtain stadiometer. Weight was measured to the nearest 0.1 kg, with the participant lightly dressed and after having had breakfast, using an electronic weight scale (Seca 708 portable digital beam scale). Body mass index (BMI) was calculated from the ratio of body weight (kg) to body height (m2). For purposes of this study, participants were classified as being overweight or of normal weight, according to internationally accepted BMI cut-off points (Cole, Bellizzi, Flegal, & Dietz, 2000). To measure waist circumference, we followed the NHANES protocol (US Department of Health and Human Services, 1996). A bony landmark is first located and marked. The participant stands and the examiner, positioned to the right of the participant, palpates the upper hip bone to locate the right iliac crest. Just above the uppermost lateral border of the right iliac crest, a horizontal mark is drawn, and then crossed with a vertical mark on the mid-axillary line. The measuring tape is placed in a horizontal plane around the abdomen at the level of this marked point on the right side of the trunk. The plane of the tape is parallel to the floor and the tape is held snug, but does not compress the skin. The measurement is made at a normal minimal respiration. Body fat was determined by tricipital and subscapular skinfolds, according to Heyward (1991). Each skinfold was measured twice in succession, on the right side of the body. However, if the difference between these two measurements was more than 5%, a third measurement was performed. The mean of the two or three measurements for each skinfold was used for analysis. We used a Harpender caliper with a constant pressure of 10 g × mm2 and all measurements were completed by the same observer. Percent

Daily evaluation protocol First, the participants were identified through his or her code number and code of the school. Second, blood samples were taken followed by blood pressure measurements. Then the children had breakfast, followed by the determination of their maturational stage. Finally, the participants performed a shuttle run test. The variables were measured between 08.00 and 11.00 h.

Blood sampling Capillary blood samples were taken from the earlobe after a fast of at least 12 h for analysis of plasma total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), fasting glucose, and triglycerides. The blood samples were drawn into capillary tubes (33 ml, Selzer) coated with lithium heparin and immediately assayed using Colestech LDX Analyser.

Fitness, fatness, and CVD risk factors body fat was estimated from skinfolds, according to the equations of Slaughter et al. (1988). Maturational stage


For maturational stage, the adolescents were assessed separately during their physical examination. Each participant self-assessed his or her stages of secondary sex characteristics. Stage of breast development in females and pubic hair in males was evaluated according to the criteria of Tanner (1962). In a previous study, Mota and colleagues (Mota, Guerra, Leandro, Ribeiro, & Duarte, 2002) reported a correlation of 0.73 between ratings on two occasions (3-day interval) in a sub-sample of 50 individuals, and concordance between self-assessments of sexual maturity status and physician assessment of 63% for girls and 89% for boys.

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Ruiz, Hurting-Wennlof, Ortega, & Sjostrom, (2007). Since the variables differed between the sexes, an independent sample t-test was used to compare mean values. To analyse the dependence between the participants’ cardiorespiratory fitness and level of obesity (non-overweight and overweight/obese), a chi-square test was used. For the purpose of this study, a new variable with four groups was created: non-overweightunfit (37.4%), non-overweightfit (35%), overweight/obeseunfit (11%), and overweight/ obesefit (10%). A one-way analysis of variance (ANOVA) was used to compare differences according to fitness and fatness groups. All analyses were performed with the statistical software package SPSS v.14.0 for Windows. Statistical significance was set at P50.05. Results

Cardiorespiratory fitness Cardiorespiratory fitness was based on the maximal multi-stage 20-m shuttle run test according to the procedures outlined for the FITNESSGRAM (Morrow, Falls, & Kohl, 1994). The FITNESSGRAM was selected because of its ease of administration to large samples of participants, and its choice of reliable and valid health-related physical fitness measures. Furthermore, the 20-m shuttle run test was reported to be strongly correlated with directly measured maximal oxygen uptake (VO2max; r 0.80), suggesting that it could be used as a measure of aerobic fitness in children (Ahmaidi, Collomp, Caillaud, & Pre´ faut, 1992). However, the use of VO2max expressed per unit of body mass (ml × kg 1 × min 1) has been criticized (Armstrong & Welsman, 1997). Therefore, cardiorespiratory fitness was expressed as the number of completed laps achieved in the shuttle run test, as done previously (e.g. Psarra, Nassis, & Sidossis, 2006). Statistical analysis Descriptive statistics were used to characterize the sample. In childhood, there is no widely agreed clinical criterion for metabolic syndrome. Previous studies have differed in detail and inclusion criteria (Eckel, Grundy, & Zimmet, 2005), and none of the cut-off points apply specifically to children (De Ferrati et al., 2004). Thus, a specific metabolic score was computed. The values presented for glucose, triglycerides, HDL-C/TC, LDL, HDL, TC, and systolic and diastolic blood pressure consist of a computed standardized value by age, sex, and maturational stage for each of the variables as follows: standardized value(valuemean)/standard deviation. Similar procedures have been described elsewhere (Rizzo,

Because the aim of this study was to investigate differences between fitness and fatness groups, and not age or gender differences per se, only main effects of obesity and fitness on CVD risk factors are discussed. Participants’ anthropometric and physical characteristics are presented in Table I. Of the 392 children, 22.45% were overweight and obese. Body mass index was significantly lower and laps completed in the shuttle run test were significantly higher (P 5 0.05) in fit children. Weight and height did not differ between the groups. As the main statistical analysis was done taking into account the z-score values by age and gender, Table II presents the absolute medium values for each of the risk factors, presenting sample characteristics by gender. Females presented a significantly higher medium value for triglycerides, total cholesterol, and LDL cholesterol, and lower values for completed laps in the shuttle run test, than males. After the descriptive analysis, we divided the sample into four groups: Group 1 represented nonoverweight and unfit individuals; Group 2 comprised non-overweight and fit individuals; Group 3 consisted of overweight and unfit individuals; and Group 4 included those individuals who were overweight and fit. Table III presents findings for comparisons of CVD risk factors between the four groups. The results showed that, between the overweight groups, the unfit participants had higher waist circumferences than fit participants. Comparing non-overweight and unfit individuals (Group 1) with overweight but fit individuals (Group 4), we found statistically significant differences in waist circumference, triglycerides, sum of skinfolds, and LDL cholesterol. To better understand the relationships between the variables, Table IV shows all significant comparisons between groups.

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Table I. Anthropometric and physical characteristics of the participants (mean9s) Non-overweight Variables

Fit (n 147)

Unfit (n157)

Age (years) Weight (kg) Height (m) BMI CRF (laps)

Overweight/obese

14.47 (1.80) 51.38 (8.44) 1.60 (0.08) 20.23.(223) 27.53 (9.60)

13.60 51.53 1.62 19.44 53.95

Unfit (n 46)

(2.05) (10.84) (0.12) (1.93)* (21.03)*

13.85 66.75 1.60 26.00 21.04

(1.94) (9.30) (0.09) (2.25) (9.63)

Fit (n 42) 12.14 62.60 1.62 23.73 42.95

(2.04) (12.59) (0.11) (1.93)* (20.35)*

Note: BMIbody mass index; CRFcardiorespiratory fitness. *P50.05 between fit and unfit within the same BMI category.

circumference and sum of seven skinfolds) than their unfit but normal-weight peers, which, in turn, suggests that most of the health benefits of leanness are limited to fit youngsters. There is a lack of consensus about the use of different procedures and the appropriate use of cutpoints to establish fitness performance related to health. Although there is controversy over whether fit youth have fewer CVD risk factors than their unfit peers, even when obese, and difficulty comparing and interpreting results, our results are in line with those for adults. Indeed, it has been shown in adulthood that self-reported physical activity and functional capacity were more important than weight status for cardiovascular risk stratification in women, suggesting that that the CVD risks of obesity may be explained, in part, by the adverse effects of low fitness (Wesel, Arant, Olson, Johnson, & Reis, 2004). Another study found that unfit, lean men also had a higher risk of all-cause and CVD mortality than men who were fit and obese (Lee, Blair, & Jackson, 1999).


Discussion The aim of this study was to examine different categories of cardiorespiratory fitness with regard to obesity status and its relationship with CVD risk factors in youth. The independent contributions of body mass index and fitness to cardiovascular disease are unclear. Since the onset of CVD risk factors as well as obesity might lie in youth (Andersen et al., 2008), it is important to examine the associated risks so that effective preventive strategies can be targeted at those at risk as early as possible. The main finding of the present study was that regardless of body fatness, the fit participants showed a better lipid profile (LDL cholesterol) than their unfit counterparts. This was also true for waist circumference, which highlights that being fit may reduce some of the negative health implications of obesity. Furthermore, our results showed that individuals who were unfit and obese had a significantly worse lipid profile (total, HDL, and LDL cholesterol) and anthropometric variables (waist Table II. Sample characteristicsa

95% Confidence interval of the difference CVD risk factors Triglycerides (mg × dl 1) TC/HDL (mg × dl 1) Total cholesterol (mg × dl 1) HDL cholesterol (mg × dl 1) Glucose (mg × dl 1) LDL cholesterol (mg × dl 1) Blood pressure (mmHg) Shuttle run test (# laps) a

Independent sample t-test. *P50.05 between the sexes.

Sex

Mean

s

Females Males Females Males Females Males Females Males Females Males Females Males Females Males Females Males

59.25 53.20 4.117 4.150 150.53 143.90 45.92 43.32 83.90 85.87 92.7672 89.9308 141.3942 142.4444 28.32 51.00

19.156 17.515 4.3319 4.3611 25.318 26.013 10.861 11.497 7.092 7.337 24.34674 23.86099 16.02733 17.81220 10.789 23.353

t 3.327

P (two-tailed) 0.001*

Lower

Upper

2.475

9.623

0.077

0.939

8.877

0.811

2.631

0.009*

11.597

1.679

2.363

0.019*

4.748

0.435

2.772

0.006*

3.358

0.571

1.197

0.232

1.823

7.496

0.625

0.532

4.353

2.253

12.760

0.000*

26.185

19.193

Fitness, fatness, and CVD risk factors

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Table III. F-values showing differences in CDV risk factors by fitness/fatness groups 95% CI CVD risk factor z-scores

Groups

Waist circumference (cm)

1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total 1 2 3 4 Total

Total cholesterol (mg × dl 1)

HDL cholesterol (mg × dl 1)


Triglycerides (mg × dl 1)

TC/HDL (mg × dl 1)

Glucose (mg × dl 1)

Blood pressure (mmHg)

Sum of 7 skinfolds (mm)

LDL cholesterol (mg/dL)

n 156 147 45 42 390 157 147 46 42 392 157 147 46 42 392 157 147 46 42 392 157 147 46 42 392 157 147 46 42 392 157 147 46 42 392 390 157 147 46 390 157 147 46 42 392

Mean 0.235 0.365 1.302 0.790 0.003 0.102 0.421 0.349 0.132 0.001 0.051 0.125 0.445 0.182 0.004 0.062 0.173 0.343 0.396 0.007 0.016 0.049 0.153 0.044 0.011 0.027 0.028 0.152 0.124 0.009 0.483 0.410 0.098 0.063 0.342 0.016 0.107 0.040 0.349 0.016 0.360 0.323 1.342 0.944 0.006

s 0.770 0.703 1.039 0.893 0.982 0.959 0.918 1.007 0.987 0.960 0.969 0.801 1.314 1.125 0.990 0.888 0.638 1.372 1.461 0.975 1.009 0.986 0.732 0.896 0.958 0.982 1,013 0.910 0.882 0.975 2.331 2.222 2.004 2.125 2.233 1.745 0.918 1.006 0.977 1.745 0.748 0.722 0.735 0.736 0.967

Lower

Upper

0.357 0.480 0.989 0.511 0.094 0.048 0.107 0.648 0.440 0.093 0.203 0.256 0.055 0.168 0.093 0.202 0.278 0.063 0.058 0.104 0.175 0.210 0.063 0.323 0.107 0.182 0.194 0.117 0.150 0.087 0.115 0.048 0.693 0.599 0.120 0.833 0.515 1.014 0.890 0.1901 0.478 0.441 1.123 0.714 0.102

0.113 0.251 1.614 1.068 0.101 0.253 0.192 0.049 0.175 0.097 0.101 0.005 0.835 0.533 0.102 0.077 0.069 0.751 0.852 0.089 0.142 0.110 0.371 0.234 0.083 0.127 0.136 0.422 0.399 0.106 0.850 0.772 0.497 0.725 0.564 0.321 0.081 2.326 1.606 0.1574 0.242 0.205 1.560 1.173 0.089

F

P

68.790

0.000*

3.026

0.029*

4.626

0.003*

6.222

0.000*

0.551

0.648

0.674

0.568

1.069

0.362

35.451

0.000*

96.010

0.000*

Note: One-way ANOVA, all variables were adjusted for age, sex, and maturational stage *P50.05.

With regard to adolescents, our results are consistent with some data reported in the literature, which suggested that higher cardiorespiratory fitness is associated with a better lipid profile even in obese individuals. In a study of 4072 European children and adolescents, curvilinear relationships were observed between cardiorespiratory fitness, waist circumference, sum of skinfolds, and blood pressure (KlassonHeggebo et al., 2006). In the Que´ bec Family Study of 610 children and adolescents, 1130% of the variance in the risk profile was explained by physical fitness,

including cardiorespiratory fitness (Katzmarzyk et al., 1999). A recent study showed that low levels of childhood physical activity and cardiorespiratory fitness are associated with metabolic syndrome in adolescence (McMurray, Bangdiwala, Harrell, & Amorium, in press).When examining the relationship between fatness and cardiorespiratory fitness with indices of insulin resistance and sensitivity in children, it was observed that cardiorespiratory fitness attenuates the differences in insulin sensitivity within BMI categories, thus reinforcing the important role of

126


Table IV. Multiple comparisons between groups CVD risk factors Waist circumference (cm)

Total cholesterol (mg × dl 1)

HDL cholesterol (mg × dl 1)


Triglycerides (mg × dl 1)

Sum of 7 skinfolds (mm)

LDL cholesterol (mg × dl 1)

Fitnessfatness groups 1 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

* * * 1 * * * 1 * * * 1 * * * 1 * * * 1 * * *

2 * * * 2 * * * 2 * * * 2 * * * 2 * * * 2 * * *

3 * * * 3 * * * 3 * * * 3 * * * 3 * * * 3 * *

4 * * * 4 * * * 4 * * * 4 * * * 4 * * * 4 * * *

*

*P50.05.

fitness even among obese children (Eisenmann, DuBose, & Donnelly, 2007). Also, when evaluating obesity in children, it was observed that both central and total obesity were lower in overweight and obese children with high cardiorespiratory fitness (Nassis et al., 2005). Rizzo et al. (2007) suggest that because of the strong inverse correlation between cardiorespiratory fitness and fatness, a low cardiorespiratory fitness could, in part, serve as the onset of some adverse consequences attributed to fatness. All these studies provide some support for our findings and highlight the important need to increase cardiorespiratory fitness in children and adolescents to minimize the prevalence of CVD risk factors in this population. Nevertheless, some limitations of the present study should be highlighted. First, the small sample size might explain some of the lack of association. Second, cardiorespiratory fitness was assessed indirectly. Indeed, there are many concerns regarding the use of running tests as an indicator of cardiorespiratory fitness in young children. However, the easy administration of the shuttle run test and its widespread use in large-scale studies makes it a valuable tool for studying cardiorespiratory fitness in youth.

Furthermore, this study could benefit from additional data, such as combined behavioural variables, levels of physical activity, and socio-economic characteristics, which could enhance the outcomes. In conclusion, the main finding of this study was that irrespective of fatness, participants with higher cardiorespiratory fitness presented a lower prevalence of CVD risk factors.

Acknowledgements This study was supported by Foundation for Science and Technology awards SFRH/BD/15867/2005 and PTDC/DES-72424-2006.

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