scholarly journals Association Between the Number of Cardiovascular Risk Factors and Each Risk Factor Level in Elementary School Children

2008 ◽  
Vol 72 (10) ◽  
pp. 1594-1597 ◽  
Author(s):  
Masao Yoshinaga ◽  
Koji Sameshima ◽  
Yuji Tanaka ◽  
Michiko Arata ◽  
Akihiro Wada ◽  
...  
Diabetes Care ◽  
2006 ◽  
Vol 29 (6) ◽  
pp. 1408-1410 ◽  
Author(s):  
M. Yoshinaga ◽  
K. Sameshima ◽  
M. Jougasaki ◽  
H. Yoshikawa ◽  
Y. Tanaka ◽  
...  

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Masao Yoshinaga ◽  
Ayumi Miyazaki ◽  
Machiko Aoki ◽  
Yoshiya Ito ◽  
Toshihide Kubo ◽  
...  

Background and Objectives: Recently, the prevalence of obese children is declining in Japan; however, longitudinal studies showed that the prevalence of obesity is still increasing during elementary school periods. Therefore, the present study aimed to evaluate the effect of lifestyles of children and their parents on the levels of cardiovascular (CV) risk factors in elementary school children. Subjects: The study have conducted since 2012 and announced through the local boards of education in seven areas in Japan. The study was included 1114 healthy volunteers (540 boys, 574 girls) aged from 6 to 12 years with a medical examination and a questionnaire. The medical examination included the measurement of height, weight, waist circumference, and blood pressures, and blood sampling for CV risk factors. The questionnaire collected data on the lifestyles of the subjects and their parents. Screen time included time spent watching TV and playing games. The subjects were asked to walk with pedometer for 7 days. Obesity in the present study was defined using the age- and sex-specific International Obesity Task Force standard. Results: Multivariate regression analyses showed that number of steps by pedometer measurement, screen time, sleeping time, and parental BMI were significantly and independently associated with the levels of one or more CV risk factors in elementary school children. Among these, screen time had a profound adverse effect on CV risk factor levels. Number of steps was positively associated with sleeping time and negatively associated with screen time. Screen time in children was strongly associated with parental screen time. The risk of obesity in boys was associated with paternal obesity (p=0.000), but not with maternal obesity (p=0.95). On the other hand, the risk of obesity in girls was associated with both paternal and maternal obesity (both p=0.000). Conclusions: Increase in number of steps and sleeping time and decrease in screen time may be the first-line approach for elementary school children to maintain favorable CV risk factor levels. An association between childhood obesity and paternal or maternal obesity and differs between genders in Japan; thus, approaches focusing on parents should take the gender of children into consideration.


2012 ◽  
Vol 22 (4) ◽  
pp. 374 ◽  
Author(s):  
Do-Soo Kim ◽  
Mi-Ran Park ◽  
Jung-Seok Yu ◽  
Ho-Suk Lee ◽  
Jung-Hyun Lee ◽  
...  

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Michelle C Odden ◽  
Andreea Rawlings ◽  
Alice Arnold ◽  
Mary Cushman ◽  
Mary Lou Biggs ◽  
...  

Introduction: Cardiovascular disease is the leading cause of mortality in old age, yet there is limited research on the patterns of cardiovascular risk factors that predict survival to 90 years. Hypothesis: The patterns of cardiovascular risk factors that portend longevity will differ from those that confer low cardiovascular risk. Methods: We examined repeated measures of blood pressure, LDL-cholesterol, and BMI from age 67 and survival to 90 years in the Cardiovascular Health Study (CHS). CHS is a prospective study of 5,888 black and white adults in two waves (1989-90 and 1992-93) from Medicare eligibility lists in four counties in the U.S. We restricted to participants aged 67 to 75 years at baseline to control for birth cohort effects and examined repeated measures of cardiovascular risk factors throughout the late-life course. We fit logistic regression models to predict survival to age 90 using generalized estimating equations, and modeled the risk factors as linear, a linear spline, and clinically relevant categories. Models were adjusted for demographics and medication use, and we also examined whether the association of each risk factor with longevity varied by the age of risk factor measurement. Best fit models are presented. Results: Among 3,645 participants in the birth cohort, 1,160 (31.8%) survived to 90 by June 16 th , 2015. Higher systolic blood pressure in early old age was associated with reduced odds for longevity, but there was an interaction with age such that the association crossed the null at 80 years. (Table) Among those with LDL-cholesterol <130 mg/dL, higher LDL-cholesterol was associated with greater longevity; at levels above 130 mg/dL there was no association between LDL-cholesterol and longevity. BMI had a u-shaped association with longevity. Conclusions: In summary, the patterns of risk factors that predict longevity differ from that considered to predict low cardiovascular risk. The risk of high systolic blood pressure appears to depend on the age of blood pressure measurement.


2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
C Morbach ◽  
G Gelbrich ◽  
T Tiffe ◽  
F Eichner ◽  
M Breunig ◽  
...  

Abstract Background and aim Prevention of heart failure (HF) relies on early identification and elimination of cardiovascular risk factors. ACC/AHA guidelines define consecutive asymptomatic precursor stages of HF, i.e. stage A (with risk factors for HF), and stage B (asymptomatic cardiac dysfunction). We aimed to identify frequency and characteristics of individuals at risk for HF, i.e. stage A and B, in the general population. Methods The prospective Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression (STAAB) cohort study phenotyped a representative sample of 5000 residents (aged 30–79 y) of a medium sized German town, reporting no previous HF diagnosis. Echocardiography was highly quality-controlled. We applied these definitions: HF stage A: ≥1 risk factor for HF (hypertension, arteriosclerotic disease, diabetes mellitus, obesity, metabolic syndrome), but no structural heart disease (SHD); HF stage B: asymptomatic but SHD [reduced left ventricular (LV) ejection fraction, LV hypertrophy, LV dilation, stenosis or grade 2/3 regurgitation of aortic/mitral valve, grade 2/3 diastolic dysfunction], or prior myocardial infarction; Normal (N): no risk factor and no SHD. We focused on subjects in stage B without apparent cardiovascular risk factors qualifying for A (B-not-A) compared to those with risk factors (BA) and N. The first half of the sample (n=2473) served as derivation set (D), the second half (n=2434) as validation set (V). Results We found 42% (D)/45% (V) of subjects in stage A, and 18% (D)/17% (V) in stage B. Among stage B subjects, 31% (D)/29% (V) were B-not-A. Compared to BA, B-not-A subjects were younger [47 vs. 63 y (D)/50 vs 63 years (V); both p<0.001] and more often female [78% vs 56% (D)/79% vs 62% (V); both p<0.001], had higher LV ejection fraction [59% vs 56% (D)/53% vs 48% (V); both p<0.05], lower E/e' [6.7 vs 9.9 (D)/6.9 vs. 9.3 (V); both p<0.001], higher LV volume [64 vs 59 mL/m2 (D)/54 vs 48 mL/m2 (V); both p≤0.01], lower hemoglobin [13.3 vs 13.9 g/dL (D, p=0.02)/13.4 vs 13.8 g/dL (V, p=0.08); both adjusted for sex], and lower QTc interval [423 vs 433 ms (D)/427 vs 438 ms (V); both p≤0.001). Compared to N, subjects in B-not-A were more often female [78% vs 56% (D)/79% vs 61% (V); both p<0.001], had larger QTc interval [423 vs 418 ms (D)/427 vs 420 ms (V); both p<0.05], and more often anemia [11% vs 5% (D, p=0.02)/9% vs 5% (V, p=0.12)]. Conclusions We confirmed, by extensive internal validation, the presence of a hitherto undescribed group of individuals with relevant myocardial alterations, but lacking respective risk factors. Since algorithms in primary prevention do not include echocardiography, this subgroup might be missed. Further investigations should 1) externally validate our finding, 2) study the prognostic course of subjects in group B-not-A, and 3) elaborate the material differences between B-not-A and N to identify potential further novel risk factors for HF. Acknowledgement/Funding German Ministry of Research and Education within the Comprehensive Heart Failure Centre Würzburg (BMBF 01EO1004 and 01EO1504)


Sign in / Sign up

Export Citation Format

Share Document