Supplemental Digital Content is available in the text
Abstract
Several studies have reported high prevalence of risk factors for cardiovascular disease in adolescents.
To perform: i) systematically review the literature on the prevalence of high blood pressure (HBP) in adolescents; ii) analyze the possible methodological factors associated with HBP; and iii) compare the prevalence between developed and developing countries.
We revised 10 electronic databases up to August 11, 2013.
Only original articles using international diagnosis of HBP were considered. The pooled prevalence's of HBP were estimated by random effects. Meta-regression analysis was used to identify the sources of heterogeneity across studies.
Fifty-five studies met the inclusion criteria and total of 122,053 adolescents included. The pooled-prevalence of HBP was 11.2%, 13% for boys, and 9.6% for girls (P < 0.01). Method of measurement of BP and year in which the survey was conducted were associated with heterogeneity in the estimates of HBP among boys.
The data indicate that HBP is higher among boys than girls, and that the method of measurement plays an important role in the overall heterogeneity of HBP value distributions, particularly in boys.
INTRODUCTION
Cardiovascular diseases (CVD) are the main sources of disease burden worldwide, and constitute a major public health problem in many countries.1 High blood pressure (HBP) is an established major risk factor for stroke and coronary heart disease.2 Studies have shown that blood pressure (BP) in childhood and adolescence are crucial factors in developing hypertension in adulthood.3
Several studies have reported high prevalence of factors such as abdominal obesity,4 inflammation markers,5 metabolic syndrome,6 and clustered metabolic risk,7 among the risk factors for CVD. Between the cardiovascular risk factors, some article highlights increased BP values among adolescents as being particularly noteworthy.8,9 Because the prevalence of obesity has been increasing,4 we would expect to observe an increase in the prevalence of HBP, since there is a strong association between obesity and hypertension. Freedman et al10 also found that the prevalence of obesity increased but no increase in BP was observed.
Because of these major discrepancies in the literature and there has not been any systematic review verifying either the prevalence of HBP among adolescents or the for identifying the factors associated with this important aspect of adolescent health, we systematically reviewed the literature to collate the prevalence data of HBP among adolescents. Thus, we hypothesized the: i) the prevalence of HBP is high in adolescents and has increased over the past years; ii) the characteristics of the study are associated with HBP variation; iii) and the prevalence of HBP is different between developed and developing countries.
METHODS
Identification of Studies
This study followed the systematic review methodology proposed in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.11 This is a systematic review article and as no data were collected on humans or animals, there was no need to be submitted to ethics committee. The study is registered in the PROSPERO database (CRD42011001422). Searches involved 10 electronic databases: BioMed Central, Cinahl, Embase, ERIC, Medline/PubMed, PsyINFO, Scielo, Scopus, SportDiscus, and Web of Science. Articles listed in the databases through August 11, 2013 were evaluated for inclusion in the analysis. This extended number of databases was used in order to minimize selection bias. The articles identified in the search were reviewed and contact made with the corresponding authors to solicit other relevant details, and studies that may have been missed in our search.
An ethics statement was not required for this work and no funding was received for this work, no funding bodies played any role in the design, writing or decision to publish this manuscript.
Three command groups (according to key words) were used for the database search. Within each group, we used the Boolean operator “OR” and between groups we used the Boolean operator “AND.” In the first group we included terms related to BP: high blood pressure, blood pressure, and hypertension. In the second group we included terms related to age: adolescent, adolescence, young, youth, teenager, and teenage. Given that the aim of the present review was to verify the prevalence of HBP, in the third group we added a set of commands to restrict study design to cross-sectional studies, because this type of epidemiological study is the most appropriate for studies that attempt to estimate the prevalence. These terms were: prevalence studies, cross-sectional studies, and survey.
Inclusion of Studies
We included studies that published original data, in cases of duplicated data, the studies presenting outcomes related to our systematic review were retained and the articles that did not meet the inclusion criteria were excluded. The duplicates were removed using EndNote Web® reference management software, Thomson Reuters, Carlsbad, CA.
Potentially relevant articles were selected by: i) screening the titles; ii) screening the abstracts; iii) and if abstracts were not available or did not provide sufficient data, the entire article was retrieved and screened to determine whether it met the inclusion criteria. Abstracts were reviewed independently by 2 authors (ACdeM and MBL) and were selected based on their consensus according to the same criteria used described bellow. If consensus was not reached, the abstract was set aside for further evaluation. Full-text articles of abstracts selected were retrieved and reviewed. Inclusion was based on consensus between 2 investigators (ACdeM and MBL). To be included the study the article needed to: 1) have a representative population-based sample that included adolescents (aged between 10 and 19 years old; eg: if some studies had prevalence data of 10–15 yo or 15–19 yo, they were included); 2) be a cross-sectional design (because we are interested in verifying the prevalence of HBP, cross-sectional studies are the kind of epidemiological study more appropriate to check the prevalence, however we know the limitations and were considered); 3) have employed a probabilistic method to sample the population1; 4) present the HBP prevalence; 5) be an original study presenting the prevalence of HBP for both genders; 6) and have diagnosed HBP according to international guidelines: SBP and/or DBP ≥95th percentile for gender, age, and height (currently just there are 2 guidelines; one of the American Academy of Pediatrics12 and other European Society of Hypertension13). We also included those articles that did not present the prevalence per se, but contained an estimation of prevalence by gender. Also included were those articles that contained the confidence interval (95% CI) according to gender. The STROBE checklist for cross-sectional studies was applied by 2 members of the research team in assessing the percentage of items correctly related to the individual articles14,15 and, in case of disagreement between the assessors, the article was evaluated by a 3rd member of the team (see Figure 1). We not used the STROBE for to available the quality of the studies, just check the important methodological aspects this type of study.
FIGURE 1.

Flowchart of search strategy and results. DBP = diastolic blood pressure, HBP = high blood pressure, SBP = systolic blood pressure.
Assessment, Data Extraction, and Analysis
The evaluation and data extraction were performed independently by 2 members of the research team (ACdeM and MBL). Disagreements were resolved by consultation within the team until consensus was reached.
The data extracted from each study were: author, country, publication year, year of survey, journal in which the article was published, total study sample size, sample size of adolescents, age of subjects in years, proportion of girls, prevalence of HBP, and risk factors associated with HBP. The 95% CI was obtained from the articles16–28 whenever possible, or was calculated using Stata 12.0 “cii” command (95% CI exact for binomial distribution).29–62
The outcome of this review is the HPB prevalence's, diagnosed in the articles included in accordance with international guidelines. The pooled prevalence's of HBP (total sample and for each gender) were estimated by random effects (estimated pooled-prevalence adjusting variation between levels and the variation within each level). Test of heterogeneity (Q test) was used to evaluate whether the differences in prevalence estimates across studies were higher than expected by chance. Meta-regression analysis was used to identify the sources of heterogeneity across studies by I2, initially to assess the contribution of each variable (year of survey; geographic location; characteristic of countries; study population; method of BP measurement) to the overall heterogeneity.63 Those variables that were significantly associated with the heterogeneity (P < 0.20) were included in a multivariate hierarchical model.64 At the first level, year of survey (1988–1998, 1999–2004, and 2005–2009) was introduced, at the second level were geographic location (North America, Europe, Asia, Latin America, Oceania, Middle East, and Africa), characteristic of countries according International Monetary Fund classification (developed or developing), and study population (community or school); at the third level were the devices used to measure BP (sphygmomanometer or automatic digital monitor). This hierarchical model was constructed following the methodology proposed by Victora et al64 where the effect of variables increases as the level increases, approaching the outcome, for example: the year of research theoretically has less influence on the HBP prevalence, the geographic location, and this has less effect that the measuring method of BP. A P value of <0.05 was considered statistically significant in all the analyses. The Stata 12 (Stata Corp., College Station, TX) was used for all statistical calculations.
RESULTS
Literature Search
The literature search yielded 727 titles of potentially relevant articles (see Figure 1 for selection procedure flow diagram). Of these, 55 articles were eligible according to the inclusion criteria established for this review.9,16,19–21,23,24,29–31,33–36,38,40,42–44,46–52,54,56–62,65–85 The supplement file presents a description of the 55 articles with the relevant inclusion criteria including: lead author, year of publication, country where the study was performed, year of survey, total number of participants in the study, number of adolescents, proportion of girls, age range, study population, method of measurement, overall and gender-based prevalence, and the respective 95% CI.
Among the study that used automatic digital monitors for measuring BP, 77% used Omron BP device (Omron Healthcare Inc., Tokyo, Japan); 22.3% did not describe which model and 0.7% used the Space Labs device.
Five articles evaluated the secular trend of prevalence, 2 of which were from USA. The continents with the highest numbers of studies included in this review were Asia and Latin America (n = 18 in each), and only 1 study from Oceania was identified. Of the populations studied, 55.6% were from high-school samples; 75.5% of studies used sphygmomanometer to measure BP; 63.5% of surveys were conducted in low- and middle-income countries (supplementary file, http://links.lww.com/MD/A83). Total of 122,053 adolescents included in this review (61,049 girls).
Prevalence
In the overall sample, the pooled-prevalence estimated by random effects was of HBP was 11.2% (Table 1), 13% for boys, and 9.6% for girls (P < 0.01). The analyses revealed significant heterogeneity across studies for all analyses (P < 0.001): the overall sample (Table 1), girls (Table 2) and boys (Table 3), rejecting the hypothesis of homogeneity of results.
TABLE 1.
Association Between Prevalence of High Blood Pressure With Methodological Covariates for Total (n = 122,053) of Sample of the Studies

TABLE 2.
Association Between Prevalence of High Blood Pressure With Methodological Covariates for Girls (n = 61,049) of the Studies

TABLE 3.
Association Between Prevalence of High Blood Pressure With Methodological Covariates for Boys (n = 61,004) of the Studies

Table 1 summarizes the associations between HBP prevalence and characteristics of the study in the overall sample. In the overall sample, the significant association of geographical location lost significance in the adjusted model. The year of survey was not significantly associated with the prevalence of HBP while, conversely, the characteristic of countries and method of measuring BP retained their significant associations.
Table 2 depicts the HBP prevalence in the girls in relation to the methodological characteristics. Those studies from Africa showed higher prevalence while the lowest were those studies from Latin America. We found no significant associations between prevalence of HBP in girls and methodological characteristics.
Table 3 shows the prevalence in the boys in relation to methodological characteristics. The highest prevalence was observed in Oceania and the lowest in the studies conducted in Middle East/Latin America, and North America.
Among boys, all the variables were associated with heterogeneity in the distributions of HBP in the univariate model, but only the year in which the survey was conducted, the geographical location, and the method of measuring BP maintain the significance in the adjusted model.
DISCUSSION
We conducted a comprehensive systematic review of studies addressing the prevalence of HBP in adolescents, and we used meta-regression to examine the possible sources of heterogeneity in the data presented in the articles. The prevalence of HBP was higher among boys, and the heterogeneity across studies was due to methodological differences, especially method of measuring BP. Further, the prevalence of HBP was higher among studies from low- and middle-income countries in boys. To the best of our knowledge, this is the first systematic review article analysing the associations between HBP prevalence and studies characteristic's in adolescents, and is the most extensive systematic review on this subject, to date.
Contrary to expectations, the prevalence of HBP was inversely related to the year of the survey. Because the prevalence of obesity has been increasing4 we would expect to observe an increase in the prevalence of HBP, since there is a strong association between obesity and hypertension.10 Freedman et al10 also found that the prevalence of obesity increased but no increase in BP was observed. The authors emphasized that a possible explanation is the improvement of maternal and child health86,87 and increased prevalence of breastfeeding alone88 observed over the past 2 decades. These factors, which are inversely associated with adolescent BP levels,89 can be responsible for the decrease in HBP prevalence.
Boys had higher pooled prevalence than girls. There are 2 possible explanations for our finding: 1) studies showed that boys has a higher accumulation of visceral fat90 and intra-abdominal fat91 than girls, and visceral fat has been associated with higher sympathetic activity.92,93 This activation is a key mechanism underlying the effect of intra-abdominal fat accumulation on the development of hypertension.94 For example, increased sympathetic flow may increase sodium re-absorption and subsequent increased peripheral vascular resistance resulting in increased BP.95 Also, this increased sympathetic activation can be caused by increased testosterone concentrations in males. Testosterone, acting as a mediator of the androgen receptor gene function,96 has been associated not only with increased visceral fat but also with greater vasomotor sympathetic tone and BP in adolescent boys, compared to girls.96 However, pubertal stage is not included in the diagnostic criteria of HBP, and it can be a limitation, since the analysis cannot adjust for this variable is not included in the articles described. In our review, is not possible to analyze the influence of the obesity on the HBP prevalence, because the cut-off points to diagnosis the obesity in each article is different, and would introduce a classification bias in the analyses if us carried out.
2) The girls have a higher prevalence of healthy behavior patterns (healthy eating habits97; avoidance of tobacco smoking98; less alcohol abuse99; lower levels of sedentary behavior7) than boys, and these healthy life-style choices are associated with lower levels of BP and HBP prevalence.100–102 Additionally, it was not possible to adjust the analysis for other factors potentially associated with BP such as lifestyle, genetic factors, intrauterine development, because theses information's is not provided in the articles included.
Of considerable note is that the type of device used to measure BP was associated with heterogeneity in the prevalence of HBP. The pooled prevalence was higher in articles using the automatic “digital” monitors. However, all reported that the monitors used had been validated for measurement of BP in adolescents, according criteria by European Hypertension Society and American Academy of Pediatrics for differences between averages of the measures mercury column and tested monitor for a device to be validated, should be ≤5 mmHg and that the standard deviation of the differences of the averages is not larger than 8 mmHg. The differences in the prevalence can introduce differential or non-differential misclassification effects (errors due to disease status or exposure) and may cause underestimation or overestimation of the true prevalence.103 Our findings suggest that automatic monitors should not be used for diagnosis of hypertension, but may be used only as an initial assessment of current status of cardiovascular health of the adolescents and, should the teenager present with HBP, additional analysis with more accurate instruments must be performed. The logistics in epidemiological studies often preclude the measurement of BP with the gold standard; for example ambulatory BP monitoring or repeated office BP measurements. The technique is more difficult to master and is not cost-effective on an epidemiological scale. However, cost-effectiveness becomes evident104 if HBP diagnosis in adults; and the screening of the HBP in the adolescent can lead to better and more prompt treatment and so increase life expectancy of the adolescent, because HBP this age group is asymptomatic.
On the other hand, recently Thompson et al105 showed that there is no direct evidence that screening for hypertension in children and adolescents reduces adverse cardiovascular outcomes in adults. Are needed new research's to improve diagnosis and risk stratification of children with elevated BP and to quantify risks and benefits of interventions, because on this review we demonstrated higher prevalence of HBP. Secondary hypertension, although it might occasionally appear in our results, it was not described in any article, therefore disregarded in this review, because it is rare in the pediatric population and interfere little in the final result of the HBP prevalence's.
Another important factor could be influence of the classification of the HBP is the race and ethnicity, because the growth speed is influenced by these factors,106 but the guidelines (American Academy of Pediatrics12 and European Society of Hypertension13) highlights that newly revised CDC growth charts (www.cdc.gov/growthcharts) should be used for the height percentile classification.
We observed higher HBP prevalence in low- and middle-income countries. Previous studies conducted in these countries reported that the hypertension was associated with low socioeconomic status.83,107 However, the nutritional burden is shifting from deficiency to excess energy imbalance in these countries, while awareness of the problem is increasing in developed countries and, as such, the prevalence in higher income countries is becoming stabilized, albeit not as-yet normalized.108,109 Hence, strategies for changing lifestyles are necessary; the objectives being to decrease the prevalence and to increase early treatment of HBP.
CONCLUSIONS
Our systematic review indicated that HBP prevalence is high among adolescents; higher in boys and adolescents from low- and middle-income countries. The method of measurement plays an important role in HBP prevalence distribution in the overall sample, and especially in boys, but not in girls. Public health programs that aim to reduce HBP should focus primarily on adolescents from low- and middle-income countries.
Acknowledgments
Augusto César F. de Moraes is in receipt of a PhD scholarship from the São Paulo State Researh Foundation (FAPESP: proc. 2011/11137-1 and 2011/20662-2); and Maria Beatriz Lacerda is in receipt of an undergraduate research scholarship from the São Paulo State Research Foundation (FAPESP: proc. 2011/17211-9). Luis A. Moreno was given scholarship of visiting professor from Brazilian government by Science without Borders Program by CNPq (National Counsel of Technological and Scientific Development) and CAPES (Coordination of Improvement of Higher Education Personnel) (proc. 007/2012). The GENUD Research Group co-financed by the European Regional Development Fund (MICINN-FEDER).
“Probability sampling relies on the principle of randomization to ensure that all individuals have a known chance of selection; it requires that members of the target population be identified through a sampling frame or listing of potential respondents. They may all have an equal chance of being selected or, if a stratified sampling method is used, the rate at which individuals from several subsets are sampled can be varied so as to produce greater representation of some classes than of others.” Porta M. A dictionary of epidemiology. Oxford: Oxford University Press, 6th edition. 2014.
Abbreviations: 95% CI = confidence interval, BPb = lood pressure, CVD = cardiovascular diseases, HBPh = igh blood pressure, PRISMAp = referred reporting items for systematic reviews and meta-analyses.
Augusto César Ferreira de Moraes and Maria Beatriz Lacerda contributed equally to this work.
Author Contributions: Augusto César F. de Moraes: Dr. de Moraes designed the data collection instruments, coordinated and supervised data collection, carried out the initial analyses and the interpreted the data critically, drafted the initial manuscript and reviewed the manuscript, and approved the final manuscript as submitted. Maria Beatriz Lacerda: Miss. Lacerda conceptualized and designed the study, drafted the initial manuscript, data collection, carried out the initial analyses and the interpreted the data critically and approved the final manuscript as submitted. Luis Alberto Moreno: Dr. Moreno drafted the initial manuscript and reviewed the manuscript, and approved the final manuscript as submitted. Bernardo L Horta: Dr. Horta carried out the initial, final analyses and the interpreted the data critically and approved the final manuscript as submitted. Heráclito Barbosa Carvalho: Dr. Carvalho designed the data collection instruments, coordinated and supervised data collection, critically reviewed the manuscript, and approved the final manuscript as submitted.
The authors report no conflicts of interest.
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (www.md-journal.com).
REFERENCES
- 1.Beaglehole R, Horton R. Chronic diseases: global action must match global evidence. Lancet 2010; 376:1619–1621. [DOI] [PubMed] [Google Scholar]
- 2.Go AS, Mozaffarian D, Roger VL, et al. Executive summary: heart disease and stroke statistics–2013 update: a report from the American Heart Association. Circulation 2013; 127:143–152. [DOI] [PubMed] [Google Scholar]
- 3.Lauer RM, Clarke WR. Childhood risk factors for high adult blood pressure: the Muscatine Study. Pediatrics 1989; 84:633–641. [PubMed] [Google Scholar]
- 4.de Moraes AC, Fadoni RP, Ricardi LM, et al. Prevalence of abdominal obesity in adolescents: a systematic review. Obes Rev 2011; 12:69–77. [DOI] [PubMed] [Google Scholar]
- 5.Martinez-Gomez D, Gomez-Martinez S, Ruiz JR, et al. Objectively-measured and self-reported physical activity and fitness in relation to inflammatory markers in European adolescents: the HELENA Study. Atherosclerosis 2012; 221:260–267. [DOI] [PubMed] [Google Scholar]
- 6.de Moraes A, Fulaz C, Netto-Oliveira E, Reichert F. [Prevalence of metabolic syndrome in adolescents: a systematic review]. Cad Saude Publica 2009; 25:1195–1202. [DOI] [PubMed] [Google Scholar]
- 7.Rey-López JP, Bel-Serrat S, Santaliestra-Pasías A, et al. Sedentary behaviour and clustered metabolic risk in adolescents: the HELENA study. Nutr Metab Cardiovasc Dis 2013; 23:1017–1024. [DOI] [PubMed] [Google Scholar]
- 8.Muntner P, He J, Cutler JA, et al. Trends in blood pressure among children and adolescents. JAMA 2004; 291:2107–2113. [DOI] [PubMed] [Google Scholar]
- 9.Ostchega Y, Carroll M, Prineas RJ, et al. Trends of elevated blood pressure among children and adolescents: data from the National Health and Nutrition Examination Survey 1988–2006. Am J Hypertens 2009; 22:59–67. [DOI] [PubMed] [Google Scholar]
- 10.Freedman DS, Goodman A, Contreras OA, et al. Secular trends in BMI and blood pressure among children and adolescents: the Bogalusa Heart Study. Pediatrics 2012; 130:e159–e166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol 2009; 62:e1–e34. [DOI] [PubMed] [Google Scholar]
- 12.NHBPEP: National High Blood Pressure Education Program Working Group on High Blood Pressure in Children, Adolescents. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 2004; 114:555–576. [PubMed] [Google Scholar]
- 13.O’Brien E, Asmar R, Beilin L, et al. European Society of Hypertension recommendations for conventional, ambulatory and home blood pressure measurement. J Hypertens 2003; 21:821–848. [DOI] [PubMed] [Google Scholar]
- 14.Vandenbroucke J, von Elm E, Altman D, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med 2007; 4:e297. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.von Elm E, Altman D, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. PLoS Med 2007; 4:e296. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Duncan GE, Li SM, Zhou XH. Prevalence and trends of a metabolic syndrome phenotype adolescents, 1999–2000. Diabetes Care 2004; 27:2438–2443. [DOI] [PubMed] [Google Scholar]
- 17.Esmaillzadeh A, Mirmiran P, Azadbakht L, et al. High prevalence of the metabolic syndrome in Iranian adolescents. Obesity (Silver Spring) 2006; 14:377–382. [DOI] [PubMed] [Google Scholar]
- 18.Halley Castillo E, Borges G, Talavera J, et al. Body mass index and the prevalence of metabolic syndrome among children and adolescents in two Mexican populations. J Adolesc Health 2007; 40:521–526. [DOI] [PubMed] [Google Scholar]
- 19.Daratha KB, Bindler RC. Effects of individual components, time, and sex on prevalence of metabolic syndrome in adolescents. Arch Pediatr Adolesc Med 2009; 163:365–370. [DOI] [PubMed] [Google Scholar]
- 20.Johnson WD, Kroon JJ, Greenway FL, et al. Prevalence of risk factors for metabolic syndrome in adolescents: National Health and Nutrition Examination Survey (NHANES), 2001–2006. Arch Pediatr Adolesc Med 2009; 163:371–377. [DOI] [PubMed] [Google Scholar]
- 21.Lambert M, O’Loughlin J, Delvin EE, et al. Association between insulin, leptin, adiponectin and blood pressure in youth. J Hypertens 2009; 27:1025–1032. [DOI] [PubMed] [Google Scholar]
- 22.Orth SR, Schroeder T, Ritz E, Ferrari P. Effects of smoking on renal function in patients with type 1 and type 2 diabetes mellitus. Nephrol Dial Transplant 2005; 20:2414–2419. [DOI] [PubMed] [Google Scholar]
- 23.Feliciano-Alfonso JE, Mendivil CO, Ariza IDS, Pérez CE. Cardiovascular risk factors and metabolic syndrome in a population of young students from the national university of Colombia. Rev Assoc Med Bras 2010; 56:293–298. [DOI] [PubMed] [Google Scholar]
- 24.Rosa ML, Mesquita ET, da Rocha ER, Fonseca Vde M. Body mass index and waist circumference as markers of arterial hypertension in adolescents. Arq Bras Cardiol 2007; 88:573–578. [DOI] [PubMed] [Google Scholar]
- 25.Singh R, Bhansali A, Sialy R, Aggarwal A. Prevalence of metabolic syndrome in adolescents from a north Indian population. Diabet Med 2007; 24:195–199. [DOI] [PubMed] [Google Scholar]
- 26.Pedrozo W, Rascon MC, Bonneau G, et al. Metabolic syndrome and risk factors associated with life style among adolescents in a city in Argentina. Pan Am J Public Health 2008; 24:149–160. [DOI] [PubMed] [Google Scholar]
- 27.Pan Y, Pratt CA. Metabolic syndrome and its association with diet and physical activity in US adolescents. JAMA 2008; 108:276–286. [DOI] [PubMed] [Google Scholar]
- 28.Nguyen T, Tang H, Kelly P, et al. Association between physical activity and metabolic syndrome: a cross sectional survey in adolescents in Ho Chi Minh City, Vietnam. BMC Public Health 2010; 10:141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Aboul Ella NA, Shehab DI, Ismail MA, Maksoud AA. Prevalence of metabolic syndrome and insulin resistance among Egyptian adolescents 10 to 18 years of age. J Clin Lipidol 2010; 4:185–195. [DOI] [PubMed] [Google Scholar]
- 30.Addor V, Wietlisbach V, Narring F, Michaud PA. Cardiovascular risk factor profiles and their social gradient from adolescence to age 74 in a Swiss region. Prev Med 2003; 36:217–228. [DOI] [PubMed] [Google Scholar]
- 31.Kelishadi R, Sadri G, Tavasoli AA, et al. Cumulative prevalence of risk factors for atherosclerotic cardiovascular diseases in Iranian adolescents: IHHP-HHPC. J Ped 2005; 81:447–453. [DOI] [PubMed] [Google Scholar]
- 32.Sadeghi M, Roohafza HR, Kelishadi R. High blood pressure and associated cardiovascular risk factors in Iran: Isfahan Healthy Heart Programme. Med J Malaysia 2004; 59:460–467. [PubMed] [Google Scholar]
- 33.Harding S, Maynard MJ, Cruickshank K, Teyhan A. Overweight, obesity and high blood pressure in an ethnically diverse sample of adolescents in Britain: the Medical Research Council DASH study. Int J Obes 2008; 31:82–90. [DOI] [PubMed] [Google Scholar]
- 34.Juarez-Rojas JG, Cardoso-Saldana GC, Posadas-Sanchez R, et al. Blood pressure and associated cardiovascular risk factors in adolescents of Mexico City. Arch Cardiol Mex 2008; 78:384–391. [PubMed] [Google Scholar]
- 35.Agyemang C, Oudeman E, Zijlmans W, et al. Blood pressure and body mass index in an ethnically diverse sample of adolescents in Paramaribo, Suriname. BMC Cardiovasc Dis 2009; 9:19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Azizi F, Farahani ZK, Ghanbarian A, et al. Familial aggregation of the metabolic syndrome: Tehran lipid and glucose study. Ann Nutr Metabol 2009; 54:189–196. [DOI] [PubMed] [Google Scholar]
- 37.Vik A, Mathiesen EB, Brox J, et al. Relation between serum osteoprotegerin and carotid intima media thickness in a general population—the Tromsø Study. J Thromb Haemos 2010; 8:2133–2139. [DOI] [PubMed] [Google Scholar]
- 38.Pitanga FJG. Anthropometric indicators as predictors of high blood pressure in adolescents. Arq Bras Cardiol 2011; 96:126–132. [DOI] [PubMed] [Google Scholar]
- 39.Bibiloni MD, Martinez E, Llull R, et al. Prevalence and risk factors for obesity in Balearic Islands adolescents. Br J Nutr 2010; 103:99–106. [DOI] [PubMed] [Google Scholar]
- 40.Uçar B, Kiliç Z, Çolak O, et al. Coronary risk factors in Turkish schoolchildren: randomized cross-sectional study. Pediatr Int 2000; 42:259–267. [DOI] [PubMed] [Google Scholar]
- 41.Martinez CA, Ibanez JO, Paterno CA, et al. Overweight and obesity in children and adolescents of Corrientes city. Relationship with cardiovascular risk factors. Medicina-Buenos Aires 2001; 61:308–314. [PubMed] [Google Scholar]
- 42.Uscategui Penuela RM, Perez Giraldo JA, Aristizabal Rivera JC, Camacho Perez JA. [Excess of weight and their relationship with high blood pressure in schoolchildren and adolescents of Medellin, Colombia]. Arch Latinoam Nutr 2003; 53:376–382. [PubMed] [Google Scholar]
- 43.Moura AÁ, Silva MAM, Ferraz MRMT, Rivera IR. Prevalence of high blood pressure in children and adolescents from the city of Maceió, Brazil. Arq Bras Cardiol 2004; 80:35–40. [DOI] [PubMed] [Google Scholar]
- 44.Lawlor DA, O’Callaghan MJ, Mamun AA, et al. Socioeconomic position, cognitive function, and clustering of cardiovascular risk factors in adolescence: findings from the Mater University Study of Pregnancy and its outcomes. Psychosom Med 2005; 67:862–868. [DOI] [PubMed] [Google Scholar]
- 45.Ramos E, Barros H. Prevalence of hypertension in 13-year-old adolescents in Porto, Portugal. Rev Port Cardiol 2005; 24:1075–1087. [PubMed] [Google Scholar]
- 46.Monego ET, Jardim PC. [Determinants of risk of cardiovascular diseases in schoolchildren]. Arq Bras Cardiol 2006; 87:37–45. [DOI] [PubMed] [Google Scholar]
- 47.Pollex RL, Hanley AJG, Zinman B, et al. Metabolic syndrome in aboriginal Canadians: prevalence and genetic associations. Atherosclerosis 2006; 184:121–129. [DOI] [PubMed] [Google Scholar]
- 48.Rodrigues AN, Moyses MR, Bissoli NS, et al. Cardiovascular risk factors in a population of Brazilian schoolchildren. Braz J Med Biol Res 2006; 39:1637–1642. [DOI] [PubMed] [Google Scholar]
- 49.Yamamoto-Kimura L, Posadas-Romero C, Posadas-Sanchez R, et al. Prevalence and interrelations of cardiovascular risk factors in urban and rural Mexican adolescents. J Adolesc Health 2006; 38:591–598. [DOI] [PubMed] [Google Scholar]
- 50.McNiece KL, Poffenbarger TS, Turner JL, et al. Prevalence of hypertension and pre-hypertension among adolescents. J Pediatr 2007; 150:640–644. [DOI] [PubMed] [Google Scholar]
- 51.Ng VWS, Kong APS, Choi KC, et al. BMI and waist circumference in predicting cardiovasular risk factor clustering in Chinese adolescents. Obesity 2007; 15:494–503. [DOI] [PubMed] [Google Scholar]
- 52.Ryu SY, Kweon SS, Park HC, et al. Obesity and the metabolic syndrome in Korean adolescents. J Korean Med Sci 2007; 22:513–517. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Lozada M, Machado S, Manrique M, et al. Risk factors associated with metabolic syndrome in adolescents. Gac Méd Caracas 2008; 116:323–329. [Google Scholar]
- 54.Nur N, Cetinkaya S, Yilmaz A, et al. Prevalence of hypertension among high school students in a middle anatolian province of Turkey. J Health Popul Nutr 2008; 26:88–94. [PMC free article] [PubMed] [Google Scholar]
- 55.Ostchega Y, Carroll M, Prineas RJ, et al. Trends of elevated blood pressure among children and adolescents: data from the National Health and Nutrition Examination Survey 1988–2006. Am J Hypertens 2009; 22:59–67. [DOI] [PubMed] [Google Scholar]
- 56.Park MJ, Boston BA, Oh M, Jee SH. Prevalence and trends of metabolic syndrome among Korean adolescents: from the Korean NHANES survey, 1998–2005. J Pediatr 2009; 155:529–534. [DOI] [PubMed] [Google Scholar]
- 57.Lee YJ, Shin YH, Kim JK, et al. Metabolic syndrome and its association with white blood cell count in children and adolescents in Korea: the 2005 Korean National Health and Nutrition Examination Survey. Nutr Metab Cardiovasc Dis 2010; 20:165–172. [DOI] [PubMed] [Google Scholar]
- 58.Muller-Riemenschneider F, Nocon M, Willich SN. Prevalence of modifiable cardiovascular risk factors in German adolescents. Eur J Prev Cardiol 2010; 17:204–210. [DOI] [PubMed] [Google Scholar]
- 59.Moreira C, Santos R, Vale S, et al. Metabolic syndrome and physical fitness in a sample of Azorean adolescents. Metab Syndr Relat Disord 2010; 8:443–449. [DOI] [PubMed] [Google Scholar]
- 60.Schwandt P, Kelishadi R, Haas GM. Ethnic disparities of the metabolic syndrome in population-based samples of German and Iranian adolescents. Metab Syndr Relat Disord 2010; 8:189–192. [DOI] [PubMed] [Google Scholar]
- 61.Liang YJLYJ, Xi B, Hu YH, et al. Trends in blood pressure and hypertension among Chinese children and adolescents: China Health and Nutrition Surveys. Blood Pres 2011; 20:45–53. [DOI] [PubMed] [Google Scholar]
- 62.Lin FH, Chu NF, Hsieh AT. The trend of hypertension and its relationship to the weight status among Taiwanese young adolescents. J Hum Hypertens 2012; 26:48–55. [DOI] [PubMed] [Google Scholar]
- 63.Thompson SG, Higgins JP. How should meta-regression analyses be undertaken and interpreted? Stat Med 2002; 21:1559–1573. [DOI] [PubMed] [Google Scholar]
- 64.Victora C, Huttly S, Fuchs S, Olinto M. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. Int J Epidemiol 1997; 26:224–227. [DOI] [PubMed] [Google Scholar]
- 65.Martínez CA, Ibáñez JO, Paterno CA, et al. Overweight and obesity in children and adolescents of Corrientes city. Relationship with cardiovascular risk factors. Medicina 2001; 61:308–314. [PubMed] [Google Scholar]
- 66.Ramos E, Barros H. Prevalence of hypertension in 13-year-old adolescents in Porto, Portugal. Rev Port Cardiol 2005; 24:1075–1087. [PubMed] [Google Scholar]
- 67.Esmaillzadeh A, Mirmiran P, Azadbakht L, et al. High prevalence of the metabolic syndrome in Iranian adolescents. Obesity (Silver Spring, MD) 2006; 14:377–382. [DOI] [PubMed] [Google Scholar]
- 68.Jago R, Harrell JS, McMurray RG, et al. Prevalence of abnormal lipid and blood pressure values among an ethnically diverse population of eighth-grade adolescents and screening implications. Pediatrics 2006; 117:2065–2073. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Castillo EH, Borges G, Talavera JO, et al. Body mass index and the prevalence of metabolic syndrome among children and adolescents in two Mexican populations. J Adolesc Health 2007; 40:521–526. [DOI] [PubMed] [Google Scholar]
- 70.Singh R, Bhansali A, Sialy R, Aggarwal A. Prevalence of metabolic syndrome in adolescents from a north Indian population. Diabetic Med 2007; 24:195–199. [DOI] [PubMed] [Google Scholar]
- 71.Pedrozo W, Rascón MC, Bonneau G, et al. Metabolic syndrome and risk factors associated with life style among adolescents in a city in Argentina. Pan Am J Public Health 2008; 24:149–160. [DOI] [PubMed] [Google Scholar]
- 72.Seo SJ, Lee HY, Lee SW. The prevalence of the metabolic syndrome in Korean children and adolescents: comparisons of the criteria of Cook et al., Cruz and Goran, and Ferranti et al. Yons Med J 2008; 49:563–572. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Pan Y, Pratt CA. Metabolic syndrome and its association with diet and physical activity in US adolescents. JAMA 2008; 108:276–286. [DOI] [PubMed] [Google Scholar]
- 74.Romanzini M, Reichert FF, Lopes Ada S, et al. [Prevalence of cardiovascular risk factors in adolescents]. Cad Saude Publica 2008; 24:2573–2581. [DOI] [PubMed] [Google Scholar]
- 75.Candido APC, Benedetto R, Castro APP, et al. Cardiovascular risk factors in children and adolescents living in an urban area of Southeast of Brazil: Ouro Preto Study. Eur J Pediatr 2009; 168:1373–1382. [DOI] [PubMed] [Google Scholar]
- 76.Bal C, Yalçin BM, Mazicioğlu MM, et al. Blood pressure percentiles for the children between 11–17 years of age in Kayseri. Turkiye Klinikleri J Med Sci 2009; 29:1412–1420. [Google Scholar]
- 77.Bal C, Yalçin BM, Mazicioĝ lu MM, Öztürk A, Bayat M, Üstünbaş HB, et al. Blood pressure percentiles for the children between 11–17 years of age in Kayseri. Turkiye Klinikleri J Med Scien 2009; 29:1412–1420. [Google Scholar]
- 78.Bibiloni MM, Martinez E, Llull R, et al. Metabolic syndrome in adolescents in the Balearic Islands, a Mediterranean region. Nutr Metab Cardiovasc Dis 2011; 21:446–454. [DOI] [PubMed] [Google Scholar]
- 79.Ejike C, Ugwu C, Ezeanyika L. Variations in the prevalence of point (pre)hypertension in a Nigerian school-going adolescent population living in a semi-urban and an urban area. BMC Pediatrics 2010; 10:13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 80.Nguyen T, Tang H, Kelly P, et al. Association between physical activity and metabolic syndrome: a cross sectional survey in adolescents in Ho Chi Minh City, Vietnam. BMC Public Health 2010; 10:141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Schwandt P, Kelishadi R, Ribeiro RQ, et al. A three-country study on the components of the metabolic syndrome in youths: the BIG Study. Int J Pediatr Obes 2010; 5:334–341. [DOI] [PubMed] [Google Scholar]
- 82.Pérez Fernández GA, Grau Avalo R. Cardiopatía hipertensiva en la adolescencia. resultados preliminares del estudio PESESCAD-HTA. Hipertens Riesgo Vasc 2012; 29:75–85. [Google Scholar]
- 83.Aounallah-Skhiri H, Romdhane H, Traissac P, et al. Nutritional status of Tunisian adolescents: associated gender, environmental and socio-economic factors. Public Health Nutr 2008; 11:1306–1317. [DOI] [PubMed] [Google Scholar]
- 84.Durrani AM, Fatima W. Determinants of blood pressure distribution in school children. Eur J Public Health 2012; 22:369–373. [DOI] [PubMed] [Google Scholar]
- 85.Ochoa-Avilés A, Andrade S, Huynh T, et al. Prevalence and socioeconomic differences of risk factors of cardiovascular disease in Ecuadorian adolescents. Pediatr Obes 2012; 7:274–283. [DOI] [PubMed] [Google Scholar]
- 86.Victora CG, Aquino EM, do Carmo Leal M, et al. Maternal and child health in Brazil: progress and challenges. Lancet 2011; 377:1863–1876. [DOI] [PubMed] [Google Scholar]
- 87.Victora CG, Barros AJ, Axelson H, et al. How changes in coverage affect equity in maternal and child health interventions in 35 Countdown to 2015 countries: an analysis of national surveys. Lancet 2012; 380:1149–1156. [DOI] [PubMed] [Google Scholar]
- 88.Cai X, Wardlaw T, Brown DW. Global trends in exclusive breastfeeding. Int Breastfeed J 2012; 7:12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Brion MJ, Lawlor DA, Matijasevich A, et al. What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts. Int J Epidemiol 2011; 40:670–680. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Pausova Z, Mahboubi A, Abrahamowicz M, et al. Sex differences in the contributions of visceral and total body fat to blood pressure in adolescence. Hypertension 2012; 59:572–579. [DOI] [PubMed] [Google Scholar]
- 91.Syme C, Abrahamowicz M, Leonard GT, et al. Intra-abdominal adiposity and individual components of the metabolic syndrome in adolescence. Arch Pediatr Adol Med 2008; 162:453–461. [DOI] [PubMed] [Google Scholar]
- 92.Esler M, Straznicky N, Eikelis N, et al. Mechanisms of sympathetic activation in obesity-related hypertension. Hypertension 2006; 48:787–796. [DOI] [PubMed] [Google Scholar]
- 93.Alvarez GE, Beske SD, Ballard TP, Davy KP. Sympathetic neural activation in visceral obesity. Circulation 2002; 106:2533–2536. [DOI] [PubMed] [Google Scholar]
- 94.Huggett RJ, Burns J, Mackintosh AF, Mary DA. Sympathetic neural activation in nondiabetic metabolic syndrome and its further augmentation by hypertension. Hypertension 2004; 44:847–852. [DOI] [PubMed] [Google Scholar]
- 95.Weise M, Eisenhofer G, Merke DP. Pubertal and gender-related changes in the sympathoadrenal system in healthy children. J Clin Endocrinol Metab 2002; 87:5038–5043. [DOI] [PubMed] [Google Scholar]
- 96.Pausova Z, Abrahamowicz M, Mahboubi A, et al. Functional variation in the androgen-receptor gene is associated with visceral adiposity and blood pressure in male adolescents. Hypertension 2010; 55:706–714. [DOI] [PubMed] [Google Scholar]
- 97.de Moraes AC, Adami F, Falcão MC. Understanding the correlates of adolescents’ dietary intake patterns. A multivariate analysis. Appetite 2012; 58:1057–1062. [DOI] [PubMed] [Google Scholar]
- 98.Sun W, Andreeva VA, Unger JB, et al. Age-related smoking progression among adolescents in China. J Adolesc Health 2006; 39:686–693. [DOI] [PubMed] [Google Scholar]
- 99.Donath C, Grässel E, Baier D, et al. Predictors of binge drinking in adolescents: ultimate and distal factors—a representative study. BMC Public Health 2012; 12:263. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Khang YH, Lynch JW. Exploring determinants of secular decreases in childhood blood pressure and hypertension. Circulation 2011; 124:397–405. [DOI] [PubMed] [Google Scholar]
- 101.Lazarou C, Panagiotakos DB, Kouta C, Matalas AL. Dietary and other lifestyle characteristics of Cypriot school children: results from the nationwide CYKIDS study. BMC Public Health 2009; 9:147. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102.Nettlefold L, McKay HA, Naylor PJ, et al. The relationship between objectively measured physical activity, sedentary time, and vascular health in children. Am J Hypertens 2012; 25:914–919. [DOI] [PubMed] [Google Scholar]
- 103.Mertens T. Estimating the effects of misclassification. Lancet 1993; 342:418–421. [DOI] [PubMed] [Google Scholar]
- 104.Lovibond K, Jowett S, Barton P, et al. Cost-effectiveness of options for the diagnosis of high blood pressure in primary care: a modelling study. Lancet 2011; 378:1219–1230. [DOI] [PubMed] [Google Scholar]
- 105.Thompson M, Dana T, Bougatsos C, et al. Screening for hypertension in children and adolescents to prevent cardiovascular disease. Pediatrics 2013; 131:490–525. [DOI] [PubMed] [Google Scholar]
- 106.Natale V, Rajagopalan A. Worldwide variation in human growth and the World Health Organization growth standards: a systematic review. BMJ Open 2014; 4:e003735.8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 107.Barreto SM, Miranda JJ, Figueroa JP, et al. Epidemiology in Latin America and the Caribbean: current situation and challenges. Int J Epidemiol 2012; 41:557–571. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108.May AL, Kuklina EV, Yoon PW. Prevalence of cardiovascular disease risk factors among US adolescents. Pediatrics 2012; 129:1035–1041. [DOI] [PubMed] [Google Scholar]
- 109.Thomas NE, Jasper M, Williams DRR, et al. Secular trends in established and novel cardiovascular risk factors in Welsh 12–13 year olds: a comparison between 2002 and 2007. Ann Human Biol 2011; 38:22–27. [DOI] [PubMed] [Google Scholar]
