Association of Fatness and Leg Power with Blood Pressure in Adolescents

Abstract

This cross-sectional study examined the independent and joint association of fatness and leg power (LP) with resting blood pressure (BP) in adolescents (12 to 15 years) in Benue state of Nigeria. The present study comprised 2047 adolescents, including 1087 girls. Participants were assessed for body mass index (BMI), LP, and resting BP. Multivariate regression models assessing the associations of the independent variables with BP were conducted. Fatness and LP were independent predictors of resting BP among participants and the relationship of LP with BP was more robust in girls than boys. Combined fatness and LP in predicting BP was modest (R2 = 10.4–14.3%) after controlling for maturity status. Low LP was associated with systolic blood pressure (SBP) in both girls (R2 = 9.0%, β = 0.260, p = 0.001) and boys (R2 = 11.0%, β = 0.226, p = 0.001). In the model for diastolic blood pressure (DBP), only fatness was associated with BP in girls (p = 0.001). The odd of hypertension (HTN) risk among overweight girls was 2.6 times that compared to their healthy-weight peers. Girls with low LP were 0.40 times more likely to develop HTN risk compared to their counterparts with high LP. This study has demonstrated that lower body muscle power is more important than fatness in predicting HTN in adolescent boys and girls.

1. Introduction

Hypertension (HTN) is a global health problem because of its high prevalence with concomitant risk of cardiovascular disease (CVD), kidney disease, and other co-morbidities [1]. Although HTN like many other CVD risk factors was previously considered an adult health problem, recent evidence has shown that it is increasingly becoming a pediatric health problem with its prevalence tracking into adulthood [2, 3]. Therefore, if youth at risk of this disorder are identified early, proactive steps can be initiated to enhance better health prospects in later life.

Previous studies in the pediatric population have identified HTN as a potent antecedent of CVD and its rising prevalence is noticeable not only in industrialized countries but more so in developing countries including those in Africa [3, 4, 5]. It has been documented that elevated blood pressure (BP) in adolescence can be associated with target organ damage, renal failure, and adverse changes in sympathetic nervous system, all of which can negatively impact cardiac output with resultant imbalance in cardiovascular homeostasis [2]. Although the specific etiology of HTN remains nebulous, high levels of body fat and low physical activity (PA) or fitness level have been found to be major predisposing factors [6]. Several studies in youth have demonstrated positive relationships between body fat and resting blood pressure [4, 7]. For instance, a cross-sectional study [7] found fatness as well as fitness to be independent predictors of resting blood pressure. There is increasing evidence linking muscle fitness including muscle power to cardiovascular health in youth [8, 9]. A population-based study of American adolescents [10] documented an independent association between lower body muscle strength and cardiometabolic risk including blood pressure.

Despite the emerging evidence linking muscle fitness to health outcomes in youth, studies examining the independent association of lower body muscle power (here-in referred to as LP or vertical jump power-VJP) and fatness with BP are exiguous. Further, the interactive effect of fatness and LP on BP needs to be explored. The present study aimed to examine the independent and combined associations of BMI and VJP with resting BP among in-school adolescents in Benue State, North central Nigeria. Specifically, the study determined the independent and joint associations of BMI and VJP with resting BP among adolescent girls and boys. The study further examined the relationships among BMI, VJP, and BP to determine population-specific thresholds for BMI and VJP for predicting risk of HTN among participants. The study also examined variations in fatness categories by VJP levels. A better understanding of these relationships will help inform more effective intervention programs that could lead to improved LP with a concomitant reduction in disease risk among youth including the overweight. Thus, it was hypothesized that LP would reduce BP values regardless of fatness levels.

2. Methods

2.1 Participants

This cross-sectional study included volunteer participants from selected secondary schools in Benue State, North Central Nigeria. Participants were eligible to participate in the study if they had no musculoskeletal problems, history of CVD, other reported health problems and sickness or had not participated in organized exercise programs at least 6 months before data collection. The study purpose and test procedures were fully explained to participants after permission was duly obtained from the heads of participating schools. The study protocol was approved by the health research ethics committee of Benue State University (Ref. No. BSUTHMKD/HREC/2013/017). Written informed consent of parents/guardians and assent of participants were sought before data collection. All tests were conducted in accordance with the ethical guidelines of the Helsinki declaration.

2.2 Study setting

The present study was conducted among adolescents aged 12–16 years in the three senatorial districts of Benue State, Nigeria (Benue North, Benue Central, and Benue South). Benue state with its capital at Makurdi is located in the North central geopolitical zone of Nigeria. The predominant tribes are Tivs, Idomas, Igedes and Etulos. The study covered 11 secondary schools comprising 2100 adolescent girls and boys. Like any typical state in Nigeria, secondary schools in Benue State are in two main categories: public and private. The public schools are owned by the government while private schools are owned by private individuals and Christian missionaries. The schools start lessons by 8:00 am and close by 2:00 pm with a 45 minutes break at 10 am.

2.3 Physical characteristics measurement

Participants’ physical characteristic measurements were in accordance with the protocol of the International Society for the Advancement of Kinanthropometry (ISAK) [11]. Specifically, bare-foot body mass and stature were measured in light clothing without shoes and socks with the aid of a calibrated digital weighing scale (Model Sec-880, Seca Birmingham, UK) and wall-mounted stadiometer (Model Sec-206; Seca, Birmingham, UK) to the nearest 0.1 kg and 0.1 cm, respectively. BMI was computed by dividing body mass in kilograms by stature in meter-square (kg.m⁻²). BMI was used to estimate body fatness. Body fat was estimated from triceps and medial calf skinfolds with the aid of Harpenden skinfold calipers (Creative Health Products, Ann Arbor, MI, USA). Measurements were taken three times on the right side of a participant’s body and the median was recorded. The revised regression equations for black children were used to estimate percent body fat [12]. On the basis of their BMI values, participants were categorized into healthy weight (HW) and overweight (OW) according to FitnessGram revised data [12].

Waist circumference (WC) which estimates abdominal fat [13] was measured with a Lufkin non-extensible flexible anthropometric tape (W606PM Rosscraft, Canada) to the nearest 0.1 cm. Details of the measurement procedure have been previously described [7]. All physical characteristics measurements were conducted by an accredited ISAK-Certified level 2 Anthropometrist (Lead author).

2.4 Pilot test

Before data collection, a pilot test was conducted to refine test administration procedures and determine precision of the instruments for data collection. Forty adolescent girls and boys ranging in age from 12–15 years that did not form part of the sample were recruited for the pilot test. All measurements were made according to standard procedures and the Cronbach’s Alpha coefficients were calculated to determine test reliability. In all cases, the alpha coefficients ranged from 0.820 to 0.896, indicating good internal consistency [14].

2.5 Leg power testing

Leg muscle power, a component of muscle fitness was assessed using a vertical jump (VJ) field test. The test was conducted indoors on a flat floor with a smooth wall using the countermovement jump (CMJ) protocol. Participants were instructed to rub chalk on the fingertips of the dominant hand and had a couple of practice sessions and then took their turns for the test. In the CMJ protocol, a participant stood with the dominant shoulder about 15 cm from the wall with both feet flat on the floor, reached as high as possible with the dominant hand, and made a chalk mark on the wall. He/she lowered the dominant hand, performed a countermovement by flexing the knees and hips, moving the trunk forward and downward and swinging the arms backward, and jumped with a swiping motion as high as possible making a second mark on the wall. The score was the vertical distance between the two chalk marks. Participants’ scores were converted into VJP values using a regression equation [15]. Each participant was given two trials and the best recorded to the nearest centimeter. Detailed description of the protocol is available elsewhere [16]. Participants were categorized into high and low groups using their sex-specific VJP receiver operating characteristic (ROC) cut-off values.

2.6 Blood pressure measurement

Blood pressure of participants was assessed in the morning while they occupied a sitting position after 10 minutes of rest with an oscillometric device. (HEM-705 CP, Omron Tokyo, Japan). The resting systolic blood pressure (SBP) and diastolic blood pressure (DBP) were monitored on each participant’s right arm using appropriate cuff sizes. Measurements were taken 3 times at 2-min intervals, and the average was recorded. Specific details of the BP protocol have been previously described [7]. The cut-off points for HTN (95th percentile for age and sex) in this study were based on the standards of the fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents 2004 [17].

2.7 Data analysis

Data were checked for normality before analyses with the Kolmogorov–Smirnov test. Complete data for all variables were available for 2047 out of 2100 adolescents, with a compliance rate of 97.5%. Descriptive statistics were presented as means ± SDs, frequencies, and percentage distributions. Student's t-test was used to compare the means of both genders on all study variables. Zero-order correlation coefficients were calculated to assess the relationships among BMI, VJP, and BP of participants. Multiple linear regression analyses were conducted to determine the independent and combined associations of BMI, VJP, and resting BP. All analyses were adjusted for biological maturation. Biological maturation was estimated from height and chronological age using the regression equation of Moore and Co-workers [18]. The equation estimates maturity offset (MO) directly. Then, age at peak height velocity (APHV) was estimated as the difference between chronological age and MO. The independent association of BMI and VJP with BP was further examined using binary logistics regression models. Separate analyses were conducted for girls and boys. Odd ratios (95%CI) of being hypertensive were calculated between BMI and VJP categories. The amount of variation in BP explained by the model was determined using the Cox and Snell R square and Nergelkerke R square [14]. Models were adjusted for MO as a potential confounding variable. The predictive capacities of the independent variables for the risk of BP were determined through the ROC analysis with 95% confidence intervals (95%CI). Threshold values for identifying risk of HTN were determined through area under curve (AUC) values, sensitivity, and specificity. A diagnostic test with AUC equal to 1 is perfectly accurate and another with a value of 0.5 has no discriminatory power. Tests with the AUC of 0.9–1.0 = highly accurate; 0.7–0.9 = moderate; and < 0.7 = less accurate [19]. All analyses were conducted using the statistical package for the social sciences (SPSS Version 20, IBM corporation, Armonk, NY, USA).

3. Results

3.1 Physical and performance characteristics

Participants’ general characteristics are summarized in Table 1. Girls were taller (p = 0.032), heavier (p < 0.001), fatter (p < 0.001), had larger WC (p < 0.001), higher BMI (p = 0.021), and higher MO (p < 0.001) than boys. Boys had significantly higher lean body mass (LBM) (p = 0.003), greater vertical jump height (VJH) (p < 0.001), and APHV (p < 0.001) than girls. There were no gender differences in chronological age (p = 0.432) and VJP (p = 0.617). Prevalence of HTN among participants is presented in Figure 1. The average prevalence of HTN (combined) is 9.8% for systolic HTN and 8.9% for diastolic HTN. Details of the gender-specific prevalence are displayed in Figure 1. Prevalence of OW in the total sample is 4.7% (Girls = 5.0%; boys =4.7%). In the case of LP, the prevalence of low LP was 54.6% (girls = 54.4%; Boys =54.8%). Although, both genders had healthy BMI, the correlation coefficients between fatness and VJP were generally moderate.

Variable	Combined (n = 2047)	Girls (n = 1087)	Boys (n = 960)	t-value	p-value
Age (y)	13.6 ± 1.3	13.6 ± 1.3	13.6 ± 1.3	0.786	0.432
APHV (y)	13.4 ± 1.1	12.6 ± 0.7	14.2 ± 0.7	50.075	<0.001
Stature (cm)	150.3 ± 11.6	150.8 ± 11.0	149.7 ± 12.2	2.149	0.032
MO (y)	0.2 ± 1.4	1.0 ± 1.0	−0.6 ± 1.0	33.6	<0.001
Body mass (kg)	43.5 ± 9.0	44.2 ± 8.7	42.6 ± 9.3	3.931	<0.001
BMI (kg.m^−2)	19.3 ± 3.8	19.5 ± 3.7	19.1 ± 3.9	2.319	0.021
Fat (%)	16.0 ± 6.5	18.4 ± 5.6	13.4 ± 6.4	18.597	<0.001
WC (cm)	66.2 ± 8.4	67.1 ± 8.2.	65.1 ± 8.5	5.460	<0.001
LBM (kg)	36.4 ± 7.4	35.9 ± 6.5	36.9 ± 8.3	2.935	0.003
VJH (cm)	23.8 ± 7.6	22.7 ± 7.1	25.0 ± 7.9	6.774	<0.001
VJP (w)	1397.9 ± 507.9	1392.6 ± 481.7	1403.9 ± 536.2	0.501	0.617
SBP (mmHg)	113.6 ± 17.4	115.5 ± 18.1	111.5 ± 16.4	5.174	<0.001
DBP (mmHg)	69.2 ± 13.7	68.8 ± 13.7	69.7 ± 13.7	1.465	0.143
r between BMI and VJP		0.504	0.517

Table 1.

General characteristics of participants (n = 2047).

Figure 1.

Prevalence of hypertension in participants.

3.2 Predicators of BP

As shown in Table 2, VJP had the strongest correlation with the dependent variables, especially SBP. Because MO also had strong relationship with the dependent variables, models were adjusted for MO in both genders. Multiple regression was conducted to determine independent association of fatness and LP with resting BP (Table 3). LP was the only independent predictor (p < 0.001) of SBP and DBP in both genders, the association with the SBP being stronger. Fatness was not significantly associated (p > 0.005) with SBP and DBP in both genders.

		SBP			DBP
Group	MO	BMI	VJP	MO	BMI	VJP
Girls	0.207**	0.147**	0.314**	0.120**	0.110**	0.118**
Boys	0.298**	0.172**	0.334**	0.076*	0.072*	0.094*

Table 2.

Correlation coefficients among BMI, VJP, and blood pressure.

* p < 0.05 ** p < 0.01.

Group	Dependent variable	Predictors	r^2	Β	P
Girls	SBP	BMI	0.099	−0.016	0.662
		VJP		0.321	<0.001
	DBP	BMI	0.017	0.068	0.051
		VJP		0.084	0.016
Boys	SBP	BMI	0.111	−0.001	0.968
		VJP		0.335	<0.001
	DBP	BMI	0.010	0.032	0.398
		VJP		0.078	0.039

Table 3.

Fatness and leg power as predictors of SBP and DBP among participants.

3.3 Multivariate models for predicting BP

Hierarchical multiple regression analyses were conducted to determine the joint associations of fatness and LP with BP controlling for MO in both genders (Table 4). For the girls’ SBP model, the covariate explained only 4.3% of the variance in step 1. The addition of BMI and VJP in step 2 increased the total variance to 10.4% indicating that both the independent variables explained an additional variance of 6.1%. LP (p < 0.001) and MO (p = 0.014) were the significant predictors, with VJP presenting greater explanatory capacity. In the model for boys, fatness and LP explained 23.1% with only 8.9% contribution from MO. All variables made significant contributions, but MO presented the greatest explanatory power. In the model for DBP, only MO and BMI made significant (p < 0.05) contributions in girls, while in the boys’ model, no independent variable made any statistically significant (P > 0.005) contribution. Details of the results can be found in Table 4.

		Predictor	Model 1			Model 2
Group	variable		r^2	Β	P	r^2	Β	p
Girls	SBP	MO	0.043	0.207	<0.001	0.104	0.087	0.014
		BMI	—	—	—	—	0.021	0.568
		VJP	—	—	—	—	0.263	<0.001
Boys		MO	0.089	0.298	<0.001	0.143	0.231	<0.001
		BMI	—	—	—	—	0.111	0.005
		VJP	—	—	—	—	0.165	<0.001
Girls	DBP	MO	0.014	0.120	<0.001	0.029	0.130	<0.001
		BMI	—	—	—	—	0.121	0.001
		VJP	—	—	—	—	−0.003	0.949
Boys		MO	0.006	0.076	0.019	0.013	0.071	0.091
		BMI	—	—	—	—	0.066	0.122
		VJP	—	—	—	—	0.026	0.592

Table 4.

Multiple regression analysis among Fatness, leg power, and BP among participants.

Results of the logistic regression models (Table 5) indicated that in general only VJP and BMI made significant contributions, which were greater in girls. In the girls’ model, both fatness (OR = 2.6, 95% CI = 1.29–5.35; p = 0.008) and LP (OR = 0.40, 95% CI = 0.25–0.64; p < 0.001) were associated with SBP. These results indicate that fat girls were 2.6 times likely to develop risk of HTN compared to their healthy weight peers. Further, the odd of HTN risk in girls with low LP was 0.40 times that of their counterparts with greater LP. As a whole, the model was able to explain between 4–9% of the variance in SBP and correctly classified 90.2% of the cases. In the Boys’ model, no variable made any significant contribution. However, the model also explained between 4–9% of the variation in SBP and correctly classified 90.2% of the cases. For the DBP models, only MO (OR = 1.40, 95%CI = 1.15–1.62, p < 0.001) in girls made a significant contribution to the model. The model for boys was not significant (p < 0.001). Details of the results are in Table 5.

		SBP				DBP
Group		Pred	β	OR	95%CI	P	β	OR	95%CI	p
Girls	MO	0.30	1.35	1.12–1.64	0.002	0.34	1.40	1.15–1.72	0.001
	BMI
	HW; OW	0.966	1; 2.63	1.29–5.35	0.008	0.82	1; 2.27	0.96–5.34	0.061
	VJP
	High; Low	−0.923	1; 0.40	0.25–0.64	<0.001	0.431	1; 1.54	.96–2.48	0.076
Boys	MO	0.595	1.81	1.44–2.29	<0.001	0.194	1.20	0.96–1.53	0.103
	BMI
	HW; OW	0.920	1; 2.51	0.96–6.56	0.060	−1.426	1; 0.24	.032–1.80	0.165
	VJP
	High; Low	−0.289	1; 0.75	0.46–1.23	0.252	−0.312	1; 0.73	0.45–1.19	0.208

Table 5.

Odds of risk of HTN are stratified according to gender (n = 2047).

Pred = predictor.

3.4 Threshold of independent variables for detecting HTN

The ROC curve analyses are presented in Table 6. In both genders, the AUCs were significantly greater than 0.5 for both VJP and BMI (p < 0.05). The optimal threshold in girls for VJP and BMI were 1501.5 W and 18.9 kg.m⁻², respectively. Corresponding values for boys were 1340.7 W and 18.9 kg.m⁻², respectively. Details of the results are shown in Table 5. The gender-specific ROC curves are presented in Figures 2 and 3.

Group	Variable	AUC	95%CI	Cut-point	Se	Sp	p-value
Girls	BMI	0.573	.518–.627	18.9	0.575	0.516	0.014
	VJP	0.696	.649–.743	1501.5	0.698	0.373	<0.001
Boys	BMI	0.607	.547–.667	18.9	0.606	0.413	0.001
	VJP	0.667	.605–.729	1340.7	0.670	0.484	<0.001

Table 6.

Receiver operating characteristic analysis for risk of HTN (n = 2047).

Figure 2.

Areas under the curve for BMI and VJP in girls.

Figure 3.

Areas under the curve for BMI and VJP in boys.

In order to further evaluate the influence of fatness and LP on BP, participants were divided into four fat/power groups and the results are presented in Table 7. The proportion of girls within these categories was 42.1%, 53.0%, 3.6%, and 1.3% for low fat/high power, low fat/low power, high fat/high power, and high fat/low power, respectively. Corresponding values for boys were 42.2%, 53.3%, 3.0%, and 1.3%. There were significant group differences in SBP for both girls (F_(3,1083) = 7.50, p < 0.001) and boys (F_(3,956) = 4.99, p < 0.002). For both genders, the differences were between the fat/low power group and three other groups (low fat/high power, low fat/high power, and high fat/high power). The same group differences were documented for boys. For DBP in girls, there was a significant (F_(3,1083) = 3.66, p = 0.012) group difference, the difference was between the two extreme groups. In boys, there were no group differences (p = 0.0165).

		Girls (n = 1087)			Boys (n = 960)
Group	n	SBP	DBP	n	SBP	DBP
Low fat/High power	458	108.6 ± 21.3	70.0 ± 13.5	407	106.2 ± 18.9	70.7 ± 13.7
Low fat/Low power	576	111.0 ± 16.3	67.6 ± 13.8	512	107.6 ± 15.2	68.8 ± 13.7
Fat/High power	39	108.3 ± 17.6	69.9 ± 12.3	29	102.8 ± 15.9	72.0 ± 13.1
Fat/Low power	14	128.0 ± 17.6	74.8 ± 19.6	12	123.4 ± 24.6	69.8 ± 12.2

Table 7.

Differences in BP according to fat/power groups (n = 2047).

HP=High power; LP = Low power.

4. Discussion

Recent evidence from both observational and prospective studies in high-and middle-income societies has shown overweight youth with low leg muscle power exhibit unfavorable cardiometabolic disease risk, including high BP [20, 21]. Although HTN, like in the developed world is becoming a health problem in sub-Saharan Africa, the significance of fatness and leg muscle power in the development of HTN remains to be fully investigated among Nigerian youth.

The main findings of this study include: First, the prevalence of HTN is comparable with prevalent rates documented in both industrialized and developing countries [22, 23] and it is higher in girls. Second, the relationships among the independent and dependent variables are generally weak to moderate. Third, Fatness and LP are independent predictors of BP, but LP demonstrated a greater explanatory capacity than fatness in girls. Fourth, the joint contribution of fatness and LP in predicting blood pressure is modest (10.4–14.3%). Finally, SBP and DBP values varied by fat-power groups, with the low fat-high power group indicating the most favorable BP profile compared to the fat-low power group with the most adverse profile.

For the total sample documented in this study, the systolic and diastolic HTN prevalence of 9.8% and 8.9, respectively, is higher than the rates of 4.9 and 6.5% reported for South African adolescents [22]. Similarly, the Global prevalence rate of 6.9% for African children [23] is also lower than the rates documented in the present study. This result implies that HTN in Nigerian youth is increasing at a disturbing rate.

In this study, both fatness and LP are weakly related to BP in both genders, though the relationship between leg power and BP is stronger. However, the relationship between fatness and LP can be said to be moderate. These results are in agreement with previous research [21, 24]. A probable reason for these weak correlations may be the low prevalence of overweight among study participants. This has been previously observed [25]. Despite the modest relationship between the independent variables and BP, the link is still important in health terms.

Results of this study clearly show that LP but not fatness was the independent predictor of SBP and DBP in both girls and boys. Our results are consistent with some previous reports [20, 25]. These results indicate that leg muscle power is a problem among the study participants. As indicated, large proportions of both girls (54.4%) and boys (54.8%) had low LP. This result highlights the need to focus on this aspect of fitness among this cohort of adolescents. Muscle power is now considered an important component of health-related physical fitness, which is associated with a positive health prognosis and a lower risk of developing CVD risk in the pediatric population [8].

The present study shows the joint contribution of fatness and LP in predicting resting SBP was moderate (Girls = 10.4%; Boys = 14.3%). But the major determinant of SBP in girls was LP while in boys, maturity status. The association of LP with SBP was stronger in girls than boys. A plausible reason for the result in girls may be early maturation (Table 1), they also often participate in less vigorous physical activities than boys, hence the higher BP levels. Our results are in agreement with those of several investigators [20, 21, 26]. But surprisingly, the relationship between LP and BP was positive, indicating that participants with greater leg power also had higher SBP. It has been observed that confounding variables such as excessive intake of salt, alcohol, and cigarette could lead to these results [20]. We are in agreement with these speculations as they appear plausible. Fatness was significantly associated with only SBP in boys and DBP in girls.

Findings from the present study clearly indicate that resting BP levels varied by cut-points of fatness and LP. The poorest BP profile was documented in adolescents who are overweight with low leg muscle power. Specifically, high levels of LP resulted in lower resting BP irrespective of fatness status. This result is supported by previous research in Norwegian adolescents [21]. This finding is of public health significance.

Based on our results and those of others, it may be realistic to believe that fatness and LP are important variables that contribute to the development of HTN in adolescents. Worthy of note is the importance of lower body muscle power in cardiovascular and musculoskeletal health. For instance, there is increasing evidence linking muscle fitness, including muscle power to cardiovascular and general health in youth [9, 26, 27]. Indeed, current physical activity guidelines for youth emphasize muscle-strengthening activities on a regular basis for improvement in muscle fitness [28, 29]. Based on empirical evidence, several authorities have emphasized the development of muscle fitness due to its overall health benefits [30, 31, 32]. Therefore, evidence from the present study and others should serve to stimulate effective public health strategies to minimize HTN in adolescents by improving leg muscle power and reducing fatness.

Findings from this study should be interpreted in the light of some limitations. The cross-sectional design precludes confirmation of cause-and-effect relationship. A major strength of this study was the use of valid field tests of health-related physical fitness. These tests use standards that discriminate well between children with more favorable cardiovascular health profiles from those with less favorable profiles. For instance, results from the logistic regression models showed a very high percentage accuracy classification (PAC) in both genders (Girls = 90.2%; Boys = 90.2%).

5. Conclusions

In conclusion, LP was independently associated with resting BP in Nigerian adolescents. The relationship of LP with BP was more robust in girls. Combination of fatness and LP in predicting BP was modest. Variation in BP for girls was best predicted by LP while that of boy was biological maturation. The combination of low LP and high fatness resulted in the most unfavorable BP profile. These results suggest that intervention targeting BP control in adolescents should focus more on leg muscle power with less emphasis on body composition, and this should be considered an important public health goal.

Acknowledgments

The authors gratefully acknowledge the cooperation of students, teachers, and head teachers of schools that participated in the project. The contribution of the research assistants who made data collection possible is gratefully acknowledged.

Conflict of interest

The authors declare no conflict of interest.