Schofield et al.1818 Schofield G, Schofield L, Hinckson EA, Mummery WK. Daily step counts and selected coronary heart disease risk factors in adolescent girls. J Sci Med Sport 2009;12(1):148-55.
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|
2009 |
|
Queensland, Australia |
|
Cross sectional |
|
415 adolescent girls, mean age of 16 years |
|
Monitoring for 4 days with a Yamax Digi-walker SW-700 pedometer |
|
High blood pressure |
|
Logistic regression |
Telford et al.2020 Telford RD, Cunningham RB, Shaw JE, Dunstan DW, Lafferty AR, Reynolds GJ, et al. Contrasting longitudinal and cross-sectional relationships between insulin resistance and percentage of body fat, fitness, and physical activity in children-the LOOK study. Pediatr Diabetes 2009;10(8):500-7.
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|
2009 |
|
Canberra, Australia |
|
Cohort |
|
498 children (257 girls), follow-up from 8 to 10 years |
|
Monitoring for 7 days with a Walk4Life pedometer |
|
Insulin resistance
|
|
Generalized linear mixed model |
Moreira et al.2525 Moreira C, Santos R, de Farias Junior JC, Vale S, Santos PC, Soares-Miranda L, et al. Metabolic risk factors, physical activity and physical fitness in Azorean adolescents: a cross-sectional study. BMC Public Health 2011;11:214.
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|
2011 |
|
Açores, Portugal |
|
Cross sectional |
|
417 adolescents (243 girls), age from 15 to 18 years |
|
Monitoring for 7 days with a Kenz Lifecorder Plus pedometer |
|
Presence of one or more of the following cardiometabolic risk factors: abdominal obesity, hyperglycemia, low HDL-cholesterol, hypertriglyceridemia, and high blood pressure |
|
Logistic regression |
Telford et al.21 |
|
2012 |
|
Canberra, Australia |
|
Cohort |
|
534 children (278 girls), follow-up from 8 to 12 years |
|
Monitoring for 7 days with a Walk4Life pedometer |
|
Insulin resistance
|
|
Generalized linear mixed model |
Andaki et al.2424 Andaki ACR TA, Andaki Júnior R, Santos A, Brito CJ, Mendes EL. Physical activity level as a predictor of cardiovascular risk factors in children. Motriz: Rev Educ Fis 2013;19(3):S8-15.
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|
2014 |
|
Viçosa, Minas Gerais, Brazil |
|
Cross sectional |
|
187 children (106 girls), mean age of 9.90 years |
|
Monitoring for 7 days with a DX-8897 pedometer |
|
Hypertriglyceridemia, low HDL-cholesterol, high blood pressure, and metabolic syndrome
|
|
ROC curve |
Andaki et al.2323 Andaki AC, Tinoco AL, Mendes EL, Andaki Junior R, Hills AP, Amorim PR. Anthropometry and physical activity level in the prediction of metabolic syndrome in children. Public Health Nutr 2014;17(10):2287-94.
|
|
2014 |
|
Viçosa, Minas Gerais, Brasil |
|
Cross sectional |
|
187 children (106 girls), mean age of 9.90 years |
|
Monitoring for 7 days with a DX-8897 pedometer |
|
Metabolic syndrome
|
|
ROC curve |
Telford et al.22 |
|
2015 |
|
Canberra, Australia |
|
Cohort |
|
469 children (240 girls), follow-up from 8 to 12 years |
|
Monitoring for 7 days with a Walk4Life pedometer |
|
Altered lipid profile |
|
Generalized linear mixed model |
Quadros et al.1919 Quadros TM, Gordia AP, Silva LR, Silva DA, Mota J. Epidemiological survey in schoolchildren: determinants and prevalence of cardiovascular risk factors. Cad Saude Publica 2016;32(2):e00181514.
|
|
2016 |
|
Amargosa, Bahia, Brazil |
|
Cross sectional |
|
1,139 children and adolescents (633 girls), age from 6 to 18 years |
|
Monitoring for 7 days with a Yamax Digi-walker SW-200 pedometer |
|
Dyslipidemia, hyperglycemia, and high blood pressure |
|
Poisson regression |