| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Circulation. 2006;114:2663-2670.)
© 2006 American Heart Association, Inc.
Pediatric Cardiology |
From the Departments of Medicine (K.D., S.C., I.K., L.P.) and Epidemiology and Biostatistics (J.O., I.K., G.P.), McGill University, and Department of Medicine (J.T., P.H.), Centre hospitalier de lUniversité de Montréal (CHUM), Montreal, Canada.
Correspondence to Dr Kaberi Dasgupta, McGill University Health Centre, Division of Clinical Epidemiology, 687 Pine Ave West, V Building, Room V 1.08, Montreal, Quebec H3A 1A1. E-mail Kaberi.Dasgupta{at}mcgill.ca
Received March 20, 2006; revision received September 14, 2006; accepted October 12, 2006.
| Abstract |
|---|
|
|
|---|
Methods and Results Between 1999 and 2005, an adolescent cohort (n=1267) completed a questionnaire survey and underwent biannual blood pressure and anthropometric assessment (grades 7, 9, and 11). Boys accounted for
50% of those with high SBP at grade 7 and 9 assessments but 67% of those with high SBP at the grade 11 assessment. As computed through a generalized estimating equations logistic regression model (sex, age, sex and age interaction term, overweight, physical activity, sedentary behavior, heart rate, household income, tobacco use, and 4 language categories), the likelihood of high SBP values among boys compared with girls was 1.29 (95% CI, 0.77 to 2.16) in grade 7, 1.98 (95% CI, 1.35 to 2.93) in grade 9, and 2.74 (95% CI, 1.52 to 4.94) in grade 11. Although there was a significant interaction between sex and age, interaction terms of sex with overweight, sedentary behavior, and physical activity were not statistically significant. Overweight (odds ratio [OR], 2.63; 95% CI, 1.76 to 3.92) and sedentary behavior (OR, 1.17 for increment of 5 hours weekly; 95% CI 1.04 to 1.33) demonstrated positive associations with high SBP values. Physical activity was inversely associated with the presence of high SBP (OR, 0.92 for increment of 5 activities in 7 days; 95% CI, 0.84 to 1.00).
Conclusions Boys are more likely than girls to develop high SBP as they approach adulthood. Even among overweight adolescents, reducing sedentary behavior and increasing physical activity may lower the risk of high SBP.
Key Words: hypertension exercise obesity pediatrics epidemiology
| Introduction |
|---|
|
|
|---|
Clinical Perspective p 2670
No longitudinal study to date has investigated sex differences in the prevalence of high SBP over time. Overweight is a critical determinant of SBP in both girls and boys,6,7 and it is likely causally linked to recent increases in the prevalence of hypertension in this age group. However, despite accumulating evidence that childhood blood pressure levels are increasing,710 there are few studies that investigate a range of possible determinants of increased blood pressure in the pediatric population11 or that examine the influence of sex on these determinants. Of particular interest are modifiable determinants shown to be important in adult populations, including physical inactivity1214 and higher levels of alcohol intake.15 Using data available in a 5-year longitudinal investigation of adolescents, we studied sex differences in the early determinants of high SBP.
| Methods |
|---|
|
|
|---|
Over a 5-year follow-up period, participants completed self-report questionnaires at 3- to 4-month intervals, for a total of 20 survey cycles. Data on frequency of participation in physical activity were collected in each survey cycle in a 7-day recall adapted from the Weekly Activity Checklist,17 which has been validated against accelerometer-measured activity levels. In the 7-day recall, participants were asked to report on which days during the week preceding completion of the questionnaire they had participated in each of the following activities for 5 minutes or more: swimming/diving, basketball, baseball/softball, football, soccer, volleyball, racket sports, ice/ball hockey, jump rope, downhill skiing/snowboarding, cross-country skiing, ice skating, rollerblading/skateboarding, gymnastics, exercise/physical conditioning (eg, push-ups, weights), ball playing (eg, dodgeball), track and field, games (eg, chase, tag), jazz/classical ballet, dancing (aerobic, party), outdoor play (eg, hide and seek, climbing trees), martial arts, outdoor chores (eg, mowing, raking), indoor chores (eg, mopping, vacuum cleaning), walking, running/jogging, and other. A continuous estimate of the frequency of participation in physical activity was obtained by summing the total number of activities checked in the recall. To assess sedentary behavior, participants were asked to estimate separately for weekdays and weekends how many hours of television or videos they watched and how many hours they played computer games or used the Internet in a single day. A continuous estimate of the number of hours of sedentary behavior during a 1-week period was computed by combining hours reported for television viewing, computer games, and Internet use.
Frequency of alcohol consumption was recorded as never, a bit to try, monthly, weekly, or daily. In the present analysis, alcohol consumption was categorized as less than once per month or greater than or equal to once per month. Use of tobacco (cigarettes) was measured in each of the 3 months preceding each questionnaire. Participants reporting any tobacco use were classified as "tobacco useever" and those reporting no use were classified as "tobacco usenever." Sociodemographic characteristics included age, sex, language spoken at home (English, French, both English and French, other), and household income. In the province of Quebec (Canada), 80% of the population report French as their first language. Specifically in Montreal, 58% report French as their first language, 10% report English, and 31% report a language other than French or English.18 An estimate of the mean household income of families with children attending each of the 10 study schools was obtained from a report prepared for the Quebec government.19
Height, weight, and blood pressure were assessed in survey cycles 1 (at baseline when participants were in grade 7), 12 (grade 9), and 19 (grade 11) by technicians who had been trained and certified according to a standardized protocol.20 Two measures of height to the nearest 0.1 cm and weight to the nearest 0.2 kg were obtained for each subject. If discrepancies >0.5 cm for height or 0.2 kg for weight were observed between the 2 measures, a third measure was obtained, and the average of the 2 closest measures was recorded. To assess interrater reliability, repeat measures of height and weight were obtained in a systematic 1-in-10 subsample of students. Interrater reliabilities (split-half coefficients) of 0.99 were obtained for height and for weight. Body mass index (BMI) was computed as weight divided by height squared (kg/m2). Absolute BMI was converted to a BMI percentile value based on standardized sex-specific BMI percentile curves for adolescents.21,22 In the present analysis, participants were classified as being overweight if their BMI was at or above the 85th percentile. Our definition of overweight includes both those considered to be "at risk" for overweight (between the 85th and 95th percentiles) and those considered to be overweight (at or above the 95th percentile) by the Expert Committee on Clinical Guidelines for Overweight in Adolescent Preventive Services.23
Blood pressure and resting pulse were assessed in the right arm after a 5-minute rest period, with an oscillometric device (Dinamap XL, model CR9340, Critikon Co, Tampa, Fla).24 Three consecutive measures were obtained at 1-minute intervals, and the average of the last 2 measures was used in the analyses. Oscillometric devices were calibrated against a mercury manometer before each data collection period. SBP values at or above the 90th percentile values from the National High Blood Pressure Education Program (NHBPEP) Working Group were considered to be increased in the present analysis.5 These 90th percentile values are specific for sex, age, and height and are based on NHANES (National Health and Nutrition Examination Survey) 1999 to 2000 data. Our definition of high SBP includes NHBPEP definitions of both high-normal (90th to 95th percentile) and elevated (at or above 95th percentile) SBP.
Statistical Analysis
With data for participants who completed all 3 blood pressure assessments, sex-specific curves were fitted to a scatterplot of SBP values using kernel smoothing.25 To examine tracking of SBP, an intraclass correlation coefficient was calculated simultaneously to examine all 3 blood pressure measures among those who completed 3 assessments. Characteristics of participants with and without high SBP were examined for grade 7, 9, and 11 assessments. Characteristics of participants who completed all 3 blood pressure assessments were compared with those who completed fewer than 3 assessments.
All available data on SBP and candidate correlates were collapsed across the 3 assessments (ie, those of participants who completed all 3 assessments and those of participants who completed fewer than 3 assessments), and independent correlates of SBP
90th percentile (yes, no) were identified in sex-specific logistic regression models with the generalized estimating equations approach with an unstructured working correlation matrix to estimate all possible correlations between repeated measures.26,27 Candidate correlates investigated included overweight status, frequency of participation in physical activity, sedentary behavior, tobacco use (never/ever), frequency of alcohol consumption, resting pulse, language spoken at home and household income. For physical activity and sedentary behavior, we report associations with high SBP according to increments of 5 activities weekly on the 7-day physical activity recall and according to increments of 5 hours weekly of sedentary behavior. Models were additionally adjusted for resting heart rate. We report associations of high SBP with 5-bpm increments of resting heart rate.
To study the independent effect of sex on high SBP, we combined data across sexes in a secondary analysis and constructed a generalized estimating equations logistic regression model that included sex and the candidate correlates described above. Additionally, we tested sex interaction terms for each candidate correlate. The final model included only sex interaction terms for variables that appeared to have different effects among boys and girls in sex-specific models and for which an interaction term with sex was significant in a model that included data from both boys and girls. All analyses were performed with SAS version 9.1 statistical software (SAS Institute Inc, Cary, NC). Generalized estimating equation models were fitted by the GENMOD procedure.
The authors had full access to the data and take full responsibility for its integrity. All authors have read and agree to the manuscript as written.
| Results |
|---|
|
|
|---|
60% had a high SBP at 2 or more assessments, and
40% had high SBP at only 1 assessment (Table 1). Mean SBP values (SD) among girls were relatively stable over time; values were 104.1 (9.8), 103.9 (10.2), and 106.2 (10.0) mm Hg over the 3 assessments. In boys, the mean SBP values increased over time from 105.4 (10.6) to 108.5 (10.6) and 114.9 (11.3) mm Hg (Figure 1). At both grade 7 and grade 9 assessments, prevalence of high SBP (ie, SBP above sex-, age-, and height-specific 90th percentile thresholds based on NHANES 1999 to 2000 data) was 5% among girls and 6% among boys. At the grade 11 assessment, the prevalence was 4% among girls and 8% among boys. High diastolic blood pressure (ie, above sex-, age-, and height-specific 90th percentile thresholds based on NHANES 1999 to 2000 data) was infrequent, occurring among 4 participants at the grade 7 assessment (3 girls, 1 boy) and in 1 participant at the grade 11 assessment (1 girl).
|
|
Table 2 describes selected characteristics of participants who completed 3 blood pressure assessments, stratified by presence or absence of high SBP. The proportion of girls was
50% among both those with and those without high SBP at grade 7 and grade 9 assessments. However, in grade 11, 33% of those with high SBP were girls, compared with 53% of those without high SBP. Compared with those without high SBP, a greater proportion of those with high SBP across the 3 assessments were overweight and reported speaking French only or both English and French at home. A greater proportion with high SBP reported alcohol consumption once or more per month in grade 7, but a lower proportion reported such consumption at grade 9 and grade 11 assessments. Those with high SBP reported a lower frequency of physical activity and had a somewhat lower household income across assessments. There were no substantive differences with the inclusion of data for those who did not present for all 3 blood pressure assessments. Although Table 2 provides values only for those who presented for 3 blood pressure assessments, all data, including those from individuals who did not present for all 3 assessments, were included in the multivariate analyses (generalized estimating equation logistic regression models) described below.
|
The sex-specific multivariate analyses (Figure 2) suggested that overweight and resting pulse were positively associated with the presence of high SBP among girls, whereas increased frequency of physical activity was protective. Among boys, in addition to overweight and resting pulse, age and sedentary behavior were positively associated with the presence of high SBP. An inverse association between physical activity and high SBP was not statistically significant in the boys-only model. Among both girls and boys, participants whose first language was French were more likely to have high SBP than those whose first language was English. The sex-specific models presented in Figure 2 are based on 67 high-SBP outcomes in boys and 50 high-SBP outcomes in girls. Given that it is generally recommended that for every additional variable tested in a multivariate model, there should be
10 outcomes of interest, we repeated the sex-specific analyses including only age, heart rate, overweight, physical activity, sedentary behavior, and language (dichotomous classification: English-only language at home, yes/no). The ORs obtained and corresponding CIs were similar to those calculated through the 11-variable sex-specific models.
|
In models that combined data across sexes, there were significant interactions between sex and age and between sex and tobacco use with respect to impact on the presence of high SBP (Figure 2). Other interaction terms with sex were not statistically significant (Figure 2). The significant interaction between sex and age was consistent with the results of the sex-specific models (positive association of age with likelihood of high SBP in boys but not in girls); however, the significant interaction between sex and tobacco use was not consistent with sex-specific models, which identified no significant association of tobacco use with high SBP among either girls or boys. To better understand any possible association between tobacco use and SBP values among either girls or boys, curves were fitted to scatterplots of SBP values (kernel smoothing) separately for girls and boys with and without any history of tobacco use (Figure 3). Among girls, in early and late adolescence, SBP values appeared similar for those with and those without a history of tobacco use. In mid adolescence, however, SBP levels appeared to be somewhat lower among girls with a history of tobacco use. Among boys, history of tobacco use appeared to be associated with higher SBP values throughout adolescence.
|
The final model that combined data across sexes included heart rate, overweight, physical activity, sedentary behavior, language spoken at home, household income, sex, age, and a sex-by-age interaction term. As computed from this model, the likelihood of high SBP values among boys compared with girls was 1.29 (95% CI, 0.77 to 2.16) in grade 7, 1.98 (95% CI, 1.35 to 2.93) in grade 9, and 2.74 (95% CI, 1.52 to 4.94) in grade 11. Overweight (odds ration [OR], 2.63; 95% CI, 1.76 to 3.92) and sedentary behavior (OR, 1.17; 95% CI, 1.04 to 1.33) demonstrated positive associations with high SBP values. Physical activity was inversely associated with the presence of high SBP (OR, 0.92; 95% CI, 0.84 to 1.00). Tobacco use (OR, 0.82; 95% CI, 0.53 to 1.26), alcohol consumption (OR, 0.91; 95% CI, 0.59 to 1.42), and household income (increment of $10 000 Canadian; OR, 1.02; 95% CI, 0.9 to 1.16) were not significantly associated with high SBP. Language spoken at home demonstrated a significant association with high SBP (English, reference; French, OR, 3.44 [95% CI, 1.74 to 6.81]; both French and English, OR, 2.12 [95% CI, 1.10 to 4.06]; other, OR, 0.83 [95% CI, 0.28 to 2.42]).
| Discussion |
|---|
|
|
|---|
The emergence of a sex difference in the risk of high SBP during adolescence that we have detected, the higher prevalence of hypertension reported among men compared with women in young and middle-aged adults,1,28 and the higher prevalence of hypertension among women compared with men in older adults28 suggest that sex steroids may have an important impact on blood pressure levels. In support of this possibility, in a genetic association study by the Victorian Family Heart Study investigators, men inheriting the "a" allele of the estrogen receptor-
single-nucleotide polymorphism had significantly higher SBP levels than men with other genotypes.29 No significant associations between estrogen receptor genes and blood pressure were detected among women.29 Recent long-term follow-up results from the Medical Research Council National Survey of Health and Development cohort30 suggest that in men, later onset of puberty may be associated with lower SBP at 53 years of age. An association between age of onset of puberty and later SBP levels was not demonstrated in women. Unfortunately, NDIT did not include measures of puberty. However, we believe that the genetic association study by the Victorian Family Heart Study investigators and the follow-up results of the Medical Research Council cohort study complement our detection of the emergence of a sex difference in likelihood of high SBP during adolescence: All support the possibility that sex differences in risk of high SBP may be somehow linked to the impact of sex steroids on blood pressure.
The prevalence of high SBP detected among both boys and girls (high SBP defined as SBP above sex-, age-, and height-specific 90th percentile thresholds based on NHANES 1999 to 2000 data) was lower across assessments than the 10% prevalence that would be expected given the 90th percentile threshold used. This is at least partly attributable to a lower prevalence of overweight among NDIT participants compared with the reference standard for pediatric blood pressure values (NHANES 1999 to 2000 cohort). Percentile thresholds for definitions of overweight are based on cohort data from National Health Examination Survey data and NHANES data collected before 1988.31 Among NHANES 1999 to 2000 cohort participants, prevalence of BMI above the 85th percentile in adolescents was
30% among both girls and boys. In the NDIT cohort, among 12- to 13-year-olds, prevalence of BMI above the 85th percentile was 29% among boys but 23% among girls.
The present analyses identified overweight as an important determinant of high SBP among both girls and boys, as indicated in several previous studies.3234 We additionally identified low frequency of participation in physically active behaviors and greater number of hours involved in sedentary behaviors as independent determinants of high SBP. A 5-activity increment in number of physically active behaviors during a 7-day period (physical activity) was significantly associated with a 20% reduced likelihood of high SBP in the girls-only model. The inverse association between physical activity and high SBP was in the same direction and approached statistical significance in the boys-only model (5% reduced likelihood) and the model that included both boys and girls (8% reduced likelihood). A 5-hour increment per week in hours of sedentary behavior (television/video games/Internet) was associated with a 24% increased likelihood of high SBP in the boys-only model and a 17% increased likelihood in the model that included both boys and girls. In constructing a model that included data from both girls and boys, interaction terms tested between sex and physical activity and between sex and sedentary behavior were not statistically significant. Lower amounts of television viewing were correlated with lower mean arterial pressure in previous studies among children and youth (Quebec Family Study, 342 boys and 268 girls 9 to 18 years of age from the Quebec City area)35 and older adults,36 but no significant association was identified in the CARDIA (Coronary Artery Risk Development In young Adults) study among young adults.37
Although the sex-specific models did not indicate any significant association between tobacco use and likelihood of high SBP, the interaction term between sex and tobacco use was significant when tested in a multivariate model that included all the variables indicated in Figure 2 and all available data from boys and girls. Given the absence of significant associations between tobacco use and high SBP in sex-specific models, we suspect that the significance of the sex-tobacco use interaction term may be attributable either to chance or to a 3-way interaction among sex, tobacco use, and overweight. For example, girls may smoke to lose weight, and lower body weight is associated with lower blood pressure levels. In the present study, however, the sample size was not sufficiently large for the examination of 3-way interaction terms.
As noted above, NDIT cohort assessments did not specifically incorporate questions concerning breast/genitalia development, age of menarche, or physical examination other than blood pressure, heart rate, and anthropometrics. Therefore, Tanner stage could not be estimated. Given recently reported results from the Medical Research Council National Survey of Health and Development cohort,30 it is possible that early onset of puberty may be a determinant of high SBP among boys but not among girls. This indicates a need for future studies designed to determine whether the sex-specific impact of age on likelihood of high SBP that we have identified is actually attributable to sex differences in the effect of time of puberty onset.
We did not have data on family history of hypertension or ethnic background, both of which have been demonstrated to be important determinants of increased blood pressure in previous studies. We did, however, have information on linguistic background. Univariate analyses indicated that among those with high SBP, a greater proportion were French-speaking than among those without high SBP. All multivariate models indicated that among both girls and boys, French-speaking Canadians were more than twice as likely as English-speaking Canadians to have a high SBP. Interestingly, in the cross-sectional Quebec Child and Adolescent Health and Social Survey, the prevalence of high SBP was 2- to 3-fold greater7 than in the present study, and the proportion of French-speaking students was also higher, at >80% compared with <35% in the present study. In contrast, the prevalence of hypertension and obesity in adult populations is lower in Quebec than in other parts of Canada, which largely include English-speaking populations.38,39 These findings indicate a need for future studies to examine differences in high SBP, as well as the origins of these differences, between French- and English-speaking adolescents and adults in Canada.
Male youth are progressively less likely to visit a healthcare professional during adolescence and young adulthood, in contrast to female youth, who seek medical attention more frequently as they become older.40 Given the progressive increase in likelihood of high SBP among adolescent boys that we have identified, targeted efforts may be necessary to encourage male youths and young adults to undergo blood pressure assessment for the detection of increased blood pressure levels. The results of the present study support the importance of weight control and an active lifestyle for the maintenance of optimal blood pressure levels during adolescence. Previous pediatric studies have identified a positive association between television viewing and overweight,41,42 and 1 randomized controlled trial demonstrated that an educational intervention that discouraged television, videotape, and video game use achieved a significant reduction in BMI.43 Given our identification of sedentary behavior as a determinant of high SBP, interventions that reduce television viewing, Internet use, and video game time may also have a favorable impact on blood pressure levels, even in the absence of weight change.
In conclusion, the results of the present study demonstrate that not only are boys more likely than girls to have high SBP in youth but that this risk difference increases in magnitude during the adolescent period, likely accounting for higher prevalence of hypertension among men compared with women in young and middle-aged adults. Greater understanding of sex differences in cardiovascular risk factors may ultimately lead to improved strategies for the prevention of cardiovascular disease in both women and men.
| Acknowledgments |
|---|
Data collection for this study was funded by the National Cancer Institute of Canada with funds from the Canadian Cancer Society. Funding for these analyses was through an interdisciplinary capacity enhancement grant to GENESIS (Gender and Sex Determinants of Cardiovascular Disease) from the Canadian Institutes of Health Research and the Heart and Stroke Foundation of Canada. GENESIS, a pan-Canadian group of researchers led by L. Pilote, seeks to achieve better understanding of sex and gender differences in the determinants of cardiovascular disease. Dr Dasgupta holds an investigator award from the Fonds de Recherche en Santé du Québec. Dr OLoughlin holds a Canada Research Chair in the Childhood Determinants of Adult Chronic Disease. Dr Pilote holds the William Dawson Chair of Medicine at McGill University.
Disclosures
None.
| References |
|---|
|
|
|---|
2. Lauer RM, Clarke WR. Childhood risk factors for high adult blood pressure: the Muscatine Study. Pediatrics. 1989; 84: 633641.
3. Sorof J, Lai D, Turner J, Poffenbarger T, Portman R. Overweight, ethnicity, and the prevalence of hypertension in school-aged children. Pediatrics. 2004; 113: 475482.
4. Davis CL, Flickinger B, Moore D, Bassali R, Domel BS, Yin Z. Prevalence of cardiovascular risk factors in schoolchildren in a rural Georgia community. Am J Med Sci. 2005; 330: 5359.[CrossRef][Medline] [Order article via Infotrieve]
5. National High Blood Pressure Education Program Working Group on Hypertension Control in Children and Adolescents. Update on the 1987 Task Force Report on High Blood Pressure in Children and Adolescents: a working group report from the National High Blood Pressure Education Program. Pediatrics. 1996; 98: 649658.
6. Kawabe H, Shibata H, Hirose H, Tsujioka M, Saito I, Saruta T. Determinants for the development of hypertension in adolescents: a 6-year follow-up. J Hypertens. 2000; 18: 15571561.[CrossRef][Medline] [Order article via Infotrieve]
7. Paradis G, Lambert M, OLoughlin J, Lavallee C, Aubin J, Delvin E, Levy E, Hanley J. Blood pressure and adiposity in children and adolescents. Circulation. 2004; 110: 18321838.
8. Luepker RV, Jacobs DR, Prineas RJ, Sinaiko AR. Secular trends of blood pressure and body size in a multi-ethnic adolescent population: 1986 to 1996. J Pediatr. 1999; 134: 668674.[CrossRef][Medline] [Order article via Infotrieve]
9. Gidding SS, Bao W, Srinivasan SR, Berenson GS. Effects of secular trends in obesity on coronary risk factors in children: the Bogalusa Heart Study. J Pediatr. 1995; 127: 868874.[CrossRef][Medline] [Order article via Infotrieve]
10. Morrison JA, James FW, Sprecher DL, Khoury PR, Daniels SR. Sex and race differences in cardiovascular disease risk factor changes in schoolchildren, 19751990: the Princeton School Study. Am J Public Health. 1999; 89: 17081714.
11. Muntner P, He J, Cutler J, Wildman R, Whelton P. Trends in blood pressure among children and adolescents. JAMA. 2004; 291: 21072113.
12. Whelton S, Chin A, Xin X, He J. Effect of aerobic exercise on blood pressure: a meta-analysis of randomized, controlled trials. Ann Intern Med. 2002; 136: 493503.
13. Kelley D, Goodpaster BH. Effects of exercise on glucose homeostasis in type 2 diabetes mellitus. Med Sci Sports Exerc. 2001; 33: S495S501.[CrossRef][Medline] [Order article via Infotrieve]
14. Kelley GA, Kelley KS. Progressive resistance exercise and resting blood pressure: a meta-analysis of randomized controlled trials. Hypertension. 2000; 35: 838843.
15. Wallace RB, Lynch CF, Pomrehn PR, Criqui MH, Heiss G. Alcohol and hypertension: epidemiologic and experimental considerations: the Lipid Research Clinics Program. Circulation. 1981; 64 (pt 2): III-41III-47.
16. OLoughlin J, DiFranza J, Tyndale R, Meshefedjian G, McMillan-Davey E, Clarke P, Hanley J, Paradis G. Nicotine-dependence symptoms are associated with smoking frequency in adolescents. Am J Prev Med. 2003; 25: 219225.[CrossRef][Medline] [Order article via Infotrieve]
17. Sallis JF, Condon SA, Goggin KJ, Roby JJ, Kolody B, Alcaraz JE. The development of self-administered physical activity surveys for 4th grade students. Res Q Exerc Sport. 1993; 64: 2531.[Medline] [Order article via Infotrieve]
18. Population by mother tongue, by census metropolitan areas (2001 Census): Sherbrooke, Trois-Rivières, Montréal, Ottawa-Gatineau, Oshawa [Statistics Canada Web page]. Available at: http://www40.statcan.ca/l01/cst01/demo12b.htm. Accessed May 26, 2006.
19. Marceau R, Cowley P, Bernier S. Report card on Quebecs secondary schools, 2001 edition [Fraser Institute Web page]. Available at: http://www.fraserinstitute.ca/shared/readmore.asp?sNav=pb&id=242. Accessed May 26, 2006.
20. Evers SE, Hooper MD. Dietary intake and anthropometric status of 7 to 9 year old children in economically disadvantaged communities in Ontario. J Am Coll Nutr. 1995; 14: 595603.[Abstract]
21. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, Wei R, Curtin LR, Roche AF, Johnson CL. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat 11. 2002; 1190.
22. Hammer LD, Kraemer HC, Wilson DM, Ritter PL, Dornbusch SM. Standardized percentile curves of body-mass index for children and adolescents. Am J Dis Child. 1991; 145: 259263.
23. Himes JH, Dietz WH. Guidelines for overweight in adolescent preventive services: recommendations from an expert committee: the Expert Committee on Clinical Guidelines for Overweight in Adolescent Preventive Services. Am J Clin Nutr. 1994; 59: 307316.
24. Webber LS, Osganian V, Luepker RV, Feldman HA, Stone EJ, Elder JP, Perry CL, Nader PR, Parcel GS, Broyles SL. Cardiovascular risk factors among third grade children in four regions of the United States: the CATCH Study: Child and Adolescent Trial for Cardiovascular Health. Am J Epidemiol. 1995; 141: 428439.
25. Muller H-G. Functional modeling and classification of longitudinal data. Scand J Stat. 2005; 32: 223240.[CrossRef]
26. Twisk J. Longitudinal data analysis: a comparison between generalized estimating equations and random coefficient analysis. Eur J Epidemiol. 2004; 19: 769776.[CrossRef][Medline] [Order article via Infotrieve]
27. Welsing P, Landewe R, van Riel P, Boers M, van Gestel A, van der Linden S, Swinkels H, van der Heijde D. The relationship between disease activity and radiologic progression in patients with rheumatoid arthritis: a longitudinal analysis. Arthritis Rheum. 2004; 50: 20822093.[CrossRef][Medline] [Order article via Infotrieve]
28. Martins D, Nelson K, Pan D, Tareen N, Norris K. The effect of gender on age-related blood pressure changes and the prevalence of isolated systolic hypertension among older adults: data from NHANES III. J Gend Specif Med. 2001; 4: 1013, 20.[Medline] [Order article via Infotrieve]
29. Ellis J, Infantino T, Harrap S. Sex-dependent association of blood pressure with oestrogen receptor genes ERalpha and ERbeta. J Hypertens. 2004; 22: 11271131.[CrossRef][Medline] [Order article via Infotrieve]
30. Hardy R, Kuh D, Whincup PH, Wadsworth ME. Age at puberty and adult blood pressure and body size in a British birth cohort study. J Hypertens. 2006; 24: 5966.[Medline] [Order article via Infotrieve]
31. Ogden CL, Flegal KM, Carroll MD, Johnson CL. Prevalence and trends in overweight among US children and adolescents, 19992000. JAMA. 2002; 288: 17281732.
32. Srinivasan SR, Bao W, Wattigney WA, Berenson GS. Adolescent overweight is associated with adult overweight and related multiple cardiovascular risk factors: the Bogalusa Heart Study. Metabolism. 1996; 45: 235240.[CrossRef][Medline] [Order article via Infotrieve]
33. Field A, Cook N, Gillman M. Weight status in childhood as a predictor of becoming overweight or hypertensive in early adulthood. Obes Res. 2005; 13: 163169.[Medline] [Order article via Infotrieve]
34. Freedman DS, Dietz WH, Srinivasan SR, Berenson GS. The relation of overweight to cardiovascular risk factors among children and adolescents: the Bogalusa Heart Study. Pediatrics. 1999; 103: 11751182.
35. Katzmarzyk PT, Malina RM, Bouchard C. Physical activity, physical fitness, and coronary heart disease risk factors in youth: the Quebec Family Study. Prev Med. 1999; 29: 555562.[CrossRef][Medline] [Order article via Infotrieve]
36. Jakes RW, Day NE, Khaw KT, Luben R, Oakes S, Welch A, Bingham S, Wareham NJ. Television viewing and low participation in vigorous recreation are independently associated with obesity and markers of cardiovascular disease risk: EPIC-Norfolk population-based study. Eur J Clin Nutr. 2003; 57: 10891096.[CrossRef][Medline] [Order article via Infotrieve]
37. Sidney S, Sternfeld B, Haskell WL, Jacobs DR Jr, Chesney MA, Hulley SB. Television viewing and cardiovascular risk factors in young adults: the CARDIA study. Ann Epidemiol. 1996; 6: 154159.[CrossRef][Medline] [Order article via Infotrieve]
38. Joffres MR, MacLean DR. Comparison of the prevalence of cardiovascular risk factors between Quebec and other Canadian provinces: the Canadian heart health surveys. Ethn Dis. 1999; 9: 246253.[Medline] [Order article via Infotrieve]
39. Joffres M, Ghadirian P, Fodor J, Petrasovits A, Chockalingam A, Hamet P. Awareness, treatment and control of hypertension in Canada. Am J Hypertens. 1997; 10: 10971102.[CrossRef][Medline] [Order article via Infotrieve]
40. Marcell A, Klein J, Fischer I, Allan M, Kokotailo P. Male adolescent use of health care services: where are the boys? J Adolesc Health. 2002; 30: 3543.[CrossRef][Medline] [Order article via Infotrieve]
41. Armstrong CA, Sallis JF, Alcaraz JE, Kolody B, McKenzie TL, Hovell MF. Childrens television viewing, body fat, and physical fitness. Am J Health Promot. 1998; 12: 363368.[Medline] [Order article via Infotrieve]
42. Tucker LA. The relationship of television viewing to physical fitness and obesity. Adolescence. 1986; 21: 797806.[Medline] [Order article via Infotrieve]
43. Robinson TN. Reducing childrens television viewing to prevent obesity: a randomized controlled trial. JAMA. 1999; 282: 15611567.
![]() |
W. Tu, G. J. Eckert, C. Saha, and J. H. Pratt Synchronization of Adolescent Blood Pressure and Pubertal Somatic Growth J. Clin. Endocrinol. Metab., December 1, 2009; 94(12): 5019 - 5022. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. Syme, M. Abrahamowicz, G. T. Leonard, M. Perron, L. Richer, S. Veillette, Y. Xiao, D. Gaudet, T. Paus, and Z. Pausova Sex Differences in Blood Pressure and Its Relationship to Body Composition and Metabolism in Adolescence Arch Pediatr Adolesc Med, September 1, 2009; 163(9): 818 - 825. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. Syme, M. Abrahamowicz, G. T. Leonard, M. Perron, A. Pitiot, X. Qiu, L. Richer, J. Totman, S. Veillette, Y. Xiao, et al. Intra-abdominal Adiposity and Individual Components of the Metabolic Syndrome in Adolescence: Sex Differences and Underlying Mechanisms Arch Pediatr Adolesc Med, May 1, 2008; 162(5): 453 - 461. [Abstract] [Full Text] [PDF] |
||||
![]() |
O. Seda, J. Tremblay, D. Gaudet, P.-L. Brunelle, A. Gurau, E. Merlo, L. Pilote, S. N. Orlov, F. Boulva, M. Petrovich, et al. Systematic, Genome-Wide, Sex-Specific Linkage of Cardiovascular Traits in French Canadians Hypertension, April 1, 2008; 51(4): 1156 - 1162. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. S. Gidding Special Article: Physical Activity, Physical Fitness, and Cardiovascular Risk Factors in Childhood American Journal of Lifestyle Medicine, December 1, 2007; 1(6): 499 - 505. [Abstract] [PDF] |
||||
![]() |
J. Mcgavock, E. Sellers, and H. Dean Physical activity for the prevention and management of youth-onset type 2 diabetes mellitus: focus on cardiovascular complications Diabetes and Vascular Disease Research, December 1, 2007; 4(4): 305 - 310. [Abstract] [PDF] |
||||
![]() |
S. E. Hofkamp, C. A. Henrikson, and S. T. Wegener An Interactive Model of Pain and Myocardial Ischemia Psychosom Med, September 1, 2007; 69(7): 632 - 639. [Abstract] [Full Text] [PDF] |
||||
![]() |
L. Pilote and for the GENESIS Investigators Sex-specific issues related to cardiovascular disease: a synopsis of the 2007 supplement Can. Med. Assoc. J., March 13, 2007; 176(6): 789 - 791. [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Circulation Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search Copyright © 2006 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. |