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1.

Objective:

Overweight (OW) and low fit children represent cardiovascular high‐risk groups. A multidimensional school‐based lifestyle intervention performed in 652 preschoolers reduced skinfold thickness and waist circumference, and improved fitness, but did not affect BMI. The objective of this study is to examine whether the intervention was equally effective in OW (≥90th national percentile) and/or low fit (lowest sex‐ and age‐adjusted quartile of aerobic fitness) children compared to their normal weight and normal fit counterparts.

Design and Methods:

Cluster randomized controlled single blinded trial, conducted in 2008/09 in 40 randomly selected preschool classes in Switzerland. The intervention included a playful physical activity program and lessons on nutrition, media use and sleeps. Primary outcomes were BMI and aerobic fitness; secondary outcomes included sum of four skinfolds, waist circumference and motor agility. Modification of intervention effects by BMI‐group and fitness‐group was tested by interaction terms.

Results:

Compared to their counterparts, OW children (n = 130) had more beneficial effects on waist circumference (p for interaction = 0.001) and low fit children (n = 154) more beneficial effects on all adiposity outcomes (p for interaction ≤0.03). The intervention effects on both fitness outcomes were not modified by BMI‐ or fitness‐group (all p for interaction ≥0.2). Average intervention effect sizes for BMI were ?0.12, ?0.05, ?0.26 and ?0.02 kg/m2 and for aerobic fitness were 0.40, 0.30, 0.12 and 0.36 stages for OW, normal weight, low fit and normal fit children, respectively. Conclusions: This multidimensional intervention was equally and for some adiposity measures even more effective in high‐risk preschoolers and represents a promising option for these children.
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2.

Objective:

The association between obesity and coronary heart disease (CHD) may have changed over time, for example due to improved pharmacological treatment of CHD risk factors. This meta‐analysis of 31 prospective cohort studies explores the influence of calendar period on CHD risk associated with body mass index (BMI).

Design and Methods:

The relative risks (RRs) of CHD for a five‐BMI‐unit increment and BMI categories were pooled by means of random effects models. Meta‐regression analysis was used to examine the influence of calendar period (>1985 v ≤1985) in univariate and multivariate analyses (including mean population age as a covariate).

Results:

The age, sex, and smoking adjusted RR (95% confidence intervals) of CHD for a five‐BMI‐unit increment was 1.28(1.22:1.34). For underweight, overweight and obesity, the RRs (compared to normal weight) were 1.11(0.91:1.36), 1.31(1.22:1.41), and 1.78(1.55:2.04), respectively. The univariate analysis indicated 31% (95%CI: ?56:0) lower RR of CHD associated with a five‐BMI‐unit increment and a 51% (95%CI: ?78: ?14)) lower RR associated with obesity in studies starting after 1985 (n = 15 and 10, respectively) compared to studies starting in or before 1985 (n = 16 and 10). However, in the multivariate analysis, only mean population age was independently associated with the RRs for a five‐BMI‐unit increment and obesity (?29(95%CI: ?55: ?5)) and ?31(95%CI: ?66:3), respectively) per 10‐year increment in mean age).

Conclusion:

This study provides no consistent evidence for a difference in the association between BMI and CHD by calendar period. The mean population age seems to be the most important factor that modifies the association between the risk of CHD and BMI, in which the RR decreases with increasing age.
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3.

Objectives:

Nonalcoholic fatty liver disease (NAFLD) is increasingly an indication for liver transplantation in adults. While severe obesity (SO, BMI ≥40 kg m?2) in adults is long standing, it is recent in duration in adolescents. With adolescent obesity on the rise, NAFLD is becoming the most frequent liver disease in adolescents. The hypothesis that SO adolescents and adults have different severity of NAFLD because of longer duration of obesity in SO adults was tested.

Design and Methods:

Preoperative clinical data, NAFLD activity and NASH (Nonalcoholic steatohepatitis) scores from intraoperative liver biopsies were extracted from a prospective database of consecutively operated SO adolescents and adults (n = 24 each). Fasting preoperative serum inflammatory mediators were evaluated by ELISA.

Results:

Other than age, baseline BMI, ethnicity and gender distribution, the incidence and extent of dyslipidemia, hypertension, and metabolic syndrome were comparable between groups. Histologic scores for steatosis and inflammation were similar. Adolescents have significantly higher NASH incidence, hepatocyte injury scores and fibrosis. This was associated with higher serum C‐reactive protein and sCD14 levels.

Conclusion:

For comparable BMI and metabolic profile, SO adolescents have more advanced liver damage, more severe systemic inflammation, suggesting differences in NAFLD etiologies and more aggressive disease progression in the young obese population.
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4.

Objective:

We examined the risk of gestational diabetes mellitus (GDM) among foreign‐born and U.S.‐born mothers by race/ethnicity and BMI category.

Design and Method:

We used 2004‐2007 linked birth certificate and maternal hospital discharge data of live, singleton deliveries in Florida to compare GDM risk among foreign‐born and U.S.‐born mothers by race/ethnicity and BMI category. We examined maternal BMI and controlled for maternal age, parity, and height.

Results:

Overall, 22.4% of the women in our study were foreign born. The relative risk (RR) of GDM among women who were overweight or obese (BMI ≥ 25.0 kg m?2) was higher than among women with normal BMI (18.5‐24.9 kg m?2) regardless of nativity, ranging from 1.3 (95% confidence interval (CI) = 1.0, 1.9) to 3.8 (95% CI = 2.1, 7.2).Foreign‐born women also had a higher GDM risk than U.S.‐born women, with RR ranging from 1.1 (95% CI = 1.1, 1.2) to 2.1 (95% CI = 1.4, 3.1). This finding was independent of BMI, age, parity, and height for all racial/ethnicity groups.

Conclusions:

Although we found differences in age, parity, and height by nativity, these differences did not substantially reduce the increased risk of GDM among foreign‐born mothers. Health practitioners should be aware of and have a better understanding of how race/ethnicity and nativity can affect women with a high risk of GDM. Although BMI is a major risk factor for GDM, it does not appear to be associated with race/ethnicity or nativity.
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5.

Objective:

There are clear sex differences in the distribution of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in adults, with males having more VAT and less SAT than females. This study assessed whether these differences between the sexes were already present in preschool children. It also evaluated which measures of body composition were most appropriate for assessing abdominal obesity in this age group.

Design and Methods:

One‐hundred and five children (57 boys and 48 girls) participated in the study. Body composition was measured using dual‐energy X‐ray absorptiometry (DXA). Weight, height, and waist circumference (WC) were also recorded. Magnetic resonance imaging (MRI) of the entire abdomen using sixteen 10‐mm‐thick T1‐weighted slices was performed in a subgroup of 48 children (30 boys and 18 girls); SAT and VAT volumes were measured using semiautomated segmentation.

Results:

Boys had significantly more VAT than girls (0.17 versus 0.10 l, P < 0.001). Results showed that VAT correlated significantly with all measurements of anthropometry (P < 0.01) after adjusting for SAT and for total fat mass measured with DXA. The mean limits of agreement between DXA and MRI regarding truncal FM were calculated to be ?11.4 (range ?17.8 to ?3.6), using a Bland–Altman plot.

Conclusion:

Sex differences in adipose tissue distribution are apparent at an early age. MRI is the best method with which to study abdominal fat distribution in young children.
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6.

Objective:

Previous studies have consistently identified maternal obesity and gestational weight gain (GWG) as risk factors for macrosomia, but little is known about the effects of central adiposity and body fat distribution. Using self‐reported data from the Black Women's Health Study (BWHS), a large follow‐up study of US black women, we examined the risk of macrosomia in relation to prepregnancy waist circumference, prepregnancy waist‐to‐hip ratio (WHR), prepregnancy BMI, and GWG.

Design and Methods:

During 1995–2003, BWHS participants ages 21–44 years delivered 6,687 full‐term singleton births (gestational age >37 weeks). We compared mothers of 691 infants weighing ≥4,000 g with mothers of 5,996 infants weighing <4,000 g. Generalized estimating equation models (GEE) that accounted for more than one birth per mother were used to estimate multivariable odds ratios (OR) and 95% confidence intervals (CI).

Results:

Independent of prepregnancy BMI, prepregnancy waist circumference was positively associated with risk of macrosomia (OR = 1.58, 95% CI: 1.07–2.32, for ≥35.0 vs. <27.0 inches (≥88.9 vs. <68.6 cm); P trend = 0.04). As expected, prepregnancy BMI was also positively associated with macrosomia (OR = 1.74, 95% CI: 1.25–2.41 for BMI ≥35.0 vs. 18.5–24.9 kg m?2). GWG above the amount recommended by the 2009 Institute of Medicine report was associated with an increased risk of macrosomia and the association was present in each category of prepregnancy BMI (18.5–24.9, 25.0–29.9, and ≥30.0 kg m?2; P trend <0.001).

Conclusions:

Our data suggest that overall obesity, high GWG, and high waist circumference are independent risk factors for macrosomia among US black women.
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7.

Objective:

To examine the effects of naltrexone/bupropion (NB) combination therapy on weight and weight‐related risk factors in overweight and obese participants.

Design and Methods:

CONTRAVE Obesity Research‐II (COR‐II) was a double‐blind, placebo‐controlled study of 1,496 obese (BMI 30‐45 kg/m2) or overweight (27‐45 kg/m2 with dyslipidemia and/or hypertension) participants randomized 2:1 to combined naltrexone sustained‐release (SR) (32 mg/day) plus bupropion SR (360 mg/day) (NB32) or placebo for up to 56 weeks. The co‐primary endpoints were percent weight change and proportion achieving ≥5% weight loss at week 28.

Results:

Significantly (P < 0.001) greater weight loss was observed with NB32 versus placebo at week 28 (?6.5% vs. ?1.9%) and week 56 (?6.4% vs. ?1.2%). More NB32‐treated participants (P < 0.001) experienced ≥5% weight loss versus placebo at week 28 (55.6% vs. 17.5%) and week 56 (50.5% vs. 17.1%). NB32 produced greater improvements in various cardiometabolic risk markers, participant‐reported weight‐related quality of life, and control of eating. The most common adverse event with NB was nausea, which was generally mild to moderate and transient. NB was not associated with increased events of depression or suicidality versus placebo.

Conclusion:

NB represents a novel pharmacological approach to the treatment of obesity, and may become a valuable new therapeutic option.
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8.

Objective:

This study aimed to determine whether (( 1 ) ) initial and/or (( 2 ) ) changes in psychosocial functioning predict body mass index (BMI) z‐score change over 4 years in overweight/mildly obese 5‐ to 9‐year old children presenting to primary care.

Design and Methods:

Eligible participants (n = 258) were overweight/mildly obese children (IOTF criteria) recruited into the LEAP2 trial (ISRCTN52511065) from 3,958 children visiting general practitioners in Melbourne, Australia from May 2005 to July 2006. Predictors were change scores calculated from repeated measures of parent‐ and child‐reported child health‐related quality of life (PedsQL) and self‐esteem; child‐reported desire to be thinner; and parent‐reported child weight concern. Outcome was measured BMI z‐score change from baseline to 4 years.

Results:

The 189 respondents (61% female; 73% retention) showed little mean change in BMI z‐score (?0.08) but wide variation (standard deviation 0.50, range ?1.32 to 1.20). Only one baseline measure (better parent‐reported PedsQL School Functioning) predicted improving BMI z‐score. However, parents and children consistently reported that changes in psychosocial functioning (i.e., PedsQL Social and Global Self‐esteem) were inversely related to BMI z‐score change scores. The strongest predictors of decreases in BMI z‐scores were changes in child‐reported body‐image variables, i.e., improvements in Physical Appearance Self‐esteem (β =0.40, 95% CI ?0.98 to ?0.15, P < 0.01) and declines in Desire to be Thinner (β = 0.33, 95% CI 0.04 to 0.23, P < 0.01).

Conclusions:

At presentation to primary care, it seems unlikely that targeting the psychosocial factors measured in this study would influence BMI z‐score change in overweight/mildly obese children. Subsequent change in psychosocial well‐being covaries with BMI z‐score change and may have important adolescent ramifications; the causal directions for these associations require further research.
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9.

Objective:

The purpose of this study was to determine the association between anthropometric measures of obesity and all‐cause mortality in white and African American men and women.

Design and Methods:

The sample included 14,343 adults 18‐89 years of age. Height, weight, and waist and hip circumferences were measured, and the BMI (kg m?2), body adiposity index (BAI = ([hip circumference in centimeters]/[height in meters])1.5 – 18), waist‐to‐height ratio (WHtR) and waist‐to‐hip ratio (WHR) were computed. Vital status of the participants was determined from linkage with the National Death Index through 2009. Cox regression was used to assess the association between anthropometry and all‐cause mortality, adjusting for age, sex, year of baseline examination, study code, smoking status, alcohol consumption and physical activity. Hazard ratios (HR) are expressed per standard deviation of each variable.

Results:

A total of 438 deaths occurred during 120,637 person‐years of follow‐up. All anthropometric markers demonstrated significant associations with all‐cause mortality in white subjects. In multivariable‐adjusted models, BMI (HR 1.34; 95% CI: 1.19‐1.50), waist circumference (1.41; 1.25‐1.60), BAI (1.34; 1.17‐1.53), WHtR (1.46; 1.28‐1.65), and WHR (1.40; 1.23‐1.61) all demonstrated significant relationships with mortality in white participants, but not in African Americans. In categorical analyses, there was a significant association between BMI status and mortality in whites but not African Americans. However, the risk associated with elevated waist circumference was similar in whites (1.49; 1.15‐1.94) and African Americans (1.60; 1.06‐2.40).

Conclusion:

In summary, this study has demonstrated race differences in the association between anthropometry and all‐cause mortality.
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10.
11.

Objective:

The purpose of this study is to determine whether time spent in objectively measured physical activity is associated with change in body mass index (BMI) from ages 9 to 15.

Design and Methods:

The participants were enrolled in the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (n = 938). At ages 9, 11, 12, and 15 the time spent in moderate‐to‐vigorous physical activity (MVPA) was objectively measured, and BMI was calculated (kg/m2). Longitudinal quantile regression was used to analyze the data. The 10th, 25th, 50th, 75th, and 90th BMI percentiles were modeled as the dependent variables with age and MVPA (h/day) modeled as predictors. Adjustment was also made for gender, race, sleep, healthy eating score, maternal education, and sedentary behavior.

Results:

A negative association between MVPA and change in BMI was observed at the 90th BMI percentile (?3.57, 95% CI ?5.15 to ?1.99 kg/m2 per hour of MVPA). The negative association between time spent in MVPA and change in BMI was progressively weaker toward the 10th BMI percentile (?0.27, 95% CI ?0.62 to 0.07 kg/m2 per hour of MVPA). The associations remained similar after adjusting for the covariates, and when the analyses were stratified by gender.

Conclusion:

Time spent in MVPA was negatively associated with change in BMI from age 9 to 15. The association was strongest at the upper tail of the BMI distribution, and increasing time spent in MVPA could help reduce the prevalence of childhood obesity.
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12.

Objective:

Although obesity is a serious public health problem, there are few reliable measures of its health hazards in the United States. The objective of this study was to estimate how much earlier mortality is likely to occur for Americans who are obese (body mass index [BMI], ≥ 30).

Design and Methods:

Data from the National Health and Nutrition Examination Survey (NHANES) I (1971–1975), NHANES II (1976–1980), and NHANES III (1988–1994) for 37,632 participants who experienced 8,791 deaths during 15 years of follow‐up were prospectively analyzed. The relative risk of death from all causes and its advancement period, adjusted for covariates, were calculated. Stratification was used to investigate the effects of pre‐existing illness, smoking, and older age on the advancement period.

Results:

Compared to the participants of reference weight (BMI, 23 to <25 kg/m2), mortality was likely to occur 9.44 years (95% confidence interval [CI]: 0.72, 18.16) earlier for those who were obese (BMI, ≥ 30). For overweight (25 to <30 kg/m2), grade 1 obesity (BMI, 30 to <35) and grades 2–3 obesity (BMI, ≥ 35.0), the mortality was likely to occur earlier by 4.40 (?3.90, 12.70), 6.69 (?2.06, 15.43), and 14.16 (3.35, 24.97) years, respectively. These estimates apply to healthy nonsmoker young‐ and middle‐aged (21–55 years) adults, who constituted an estimated 32.8% of Americans with age of >21 years between 1988 and 1994. Without stratifying simultaneously for preexisting illness, smoking, and age, values of the advancement period for obesity were markedly smaller than those observed for healthy nonsmoker young and middle‐aged adults.

Conclusions:

For healthy nonsmokers young‐ and middle‐aged adults who constitute about one‐third of American adults, being obese is likely to hasten mortality by 9.44 years.
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13.

Objective:

Previous research has examined the association between screen time and average changes in adolescent body mass index (BMI). Until now, no study has evaluated the longitudinal relationship between screen time and changes in the BMI distribution across mid to late adolescence.

Design and Methods:

Participants (n = 1,336) were adolescents who were followed from age 14 to age 18 and surveyed every 6 months. Time spent watching television/videos and playing video games was self‐reported (<1 h day?1, 1 h day?1, 2 h day?1, 3 h day?1, 4 h day?1, or 5+ h day?1). BMI (kg m?2) was calculated from self‐reported height and weight. Longitudinal quantile regression was used to model the 10th, 25th, 50th, 75th, and 90th BMI percentiles as dependent variables. Study wave and screen time were the main predictors, and adjustment was made for gender, race, maternal education, hours of sleep, and physical activity.

Results:

Increases at all the BMI percentiles over time were observed, with the greatest increase observed at the 90th BMI percentile. Screen time was positively associated with changes in BMI at the 50th (0.17, 95% CI: 0.06, 0.27), 75th (0.31, 95% CI: 0.10, 0.52), and 90th BMI percentiles (0.56, 95% CI: 0.27, 0.82). No associations were observed between screen time and changes at the 10th and 25th BMI percentiles.

Conclusions:

Positive associations between screen time and changes in the BMI at the upper tail of the BMI distribution were observed. Therefore, lowering screen time, especially among overweight and obese adolescents, could contribute to reducing the prevalence of adolescent obesity.
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14.

Objective:

To investigate whether a combination of a selected but limited number of anthropometric measurements predicts visceral adipose tissue (VAT) better than other anthropometric measurements, without resort to medical imaging.

Hypothesis:

Abdominal anthropometric measurements are total abdominal adipose tissue indicators and global measures of VAT and SAAT (subcutaneous abdominal adipose tissue). Therefore, subtracting the anthropometric measurement the more correlated possible with SAAT while being the least correlated possible with VAT, from the most correlated abdominal anthropometric measurement with VAT while being highly correlated with TAAT, may better predict VAT.

Design and Methods:

BMI participants' range was from 16.3 to 52.9 kg m?2. Anthropometric and abdominal adipose tissues data by computed tomography (CT‐Scan) were available in 253 patients (18‐78 years) (CHU Nord, Marseille) and used to develop the anthropometric VAT prediction models.

Results:

Subtraction of proximal thigh circumference from waist circumference, adjusted to age and/or BMI, predicts better VAT (Women: VAT = 2.15 × Waist C ? 3.63 × Proximal Thigh C + 1.46 × Age + 6.22 × BMI ? 92.713; R2 = 0.836. Men: VAT = 6 × Waist C ? 4.41 × proximal thigh C + 1.19 × Age ? 213.65; R2 = 0.803) than the best single anthropometric measurement or the association of two anthropometric measurements highly correlated with VAT. Both multivariate models showed no collinearity problem. Selected models demonstrate high sensitivity (97.7% in women, 100% in men). Similar predictive abilities were observed in the validation sample (Women: R2 = 76%; Men: R2 = 70%). Bland and Altman method showed no systematic estimation error of VAT.

Conclusion:

Validated in a large range of age and BMI, our results suggest the usefulness of the anthropometric selected models to predict VAT in Europides (South of France).
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15.

Objective:

Clinical evidences reported subclinical alterations of thyroid function in obesity, although the relationship between thyroid status and obesity remains unclear. We cross‐sectionally investigated the influence of metabolic features on hypothalamic–pituitary–thyroid axis in obesity.

Design and Methods:

We enrolled 60 euthyroid subjects with no history of type 2 diabetes mellitus and assessed the relationship of thyroid function with insulin resistance, measured using euglycemic clamp, and abdominal fat volume, quantified by computed tomography scan (CT scan). Thyroid stimulating hormone (TSH) correlated with BMI (r = 0.46; P = 0.02), both visceral (r = 0.58; P = 0.02) and subcutaneous adipose tissue volumes (r = 0.43; P = 0.03) and insulin resistance (inverse relationship with insulin sensitivity–glucose uptake: r = ?0.40; P = 0.04).

Results:

After performing multivariate regression, visceral adipose tissue volume was found to be the most powerful predictor of TSH (β = 3.05; P = 0.01), whereas glucose uptake, high‐density lipoprotein (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, subcutaneous adipose tissue volume, and triglycerides were not. To further confirm the hypothesis that high‐normal TSH values could be dependent on adipose tissue, and not on insulin resistance, we restricted our analyses to moderately obese subjects' BMI ranging 30‐35 kg/m2. This subgroup was then divided as insulin resistant and insulin sensitive according to the glucose uptake (≤ or >5 mg·kg?1·min?1, respectively). We did not find any statistical difference in TSH (insulin resistant: 1.62 ± 0.65 µU/ml vs. insulin sensitive: 1.46 ± 0.48; P = not significant) and BMI (insulin resistant: 32.2 ± 1.6 kg/m2 vs. insulin sensitive: 32.4 ± 1.4; P = not significant), thus confirming absence of correlation between thyroid function and insulin sensitivity per se.

Conclusion:

Our study suggests that the increase in visceral adipose tissue is the best predictor of TSH concentration in obesity, independently from the eventual concurrent presence of insulin resistance.
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16.

Objective:

Stearoyl‐coenzyme A desaturase‐1 (SCD1) is a key enzyme in fatty acid and energy metabolism. Increased hepatic SCD1 activity is associated with obesity and obesity‐related diseases. We examined the relations of two plasma SCD activity indices (16:1n‐7/16:0, 18:1n‐9/18:0) with body composition, and the association of lifestyle and dietary variables with the plasma SCD indices.

Design and Methods:

This population‐based, cross‐sectional study of 2021 elderly (71–74 y) men and women from the Hordaland Health Study in Western Norway was conducted using a validated food frequency questionnaire, body composition measurements by dual‐energy X‐ray absorptiometry and determination of the plasma fatty acid profile.

Results:

In multivariate regression analyses, plasma SCD indices were positively associated with BMI and body fat (P < 0.001 for both). From the 2.5th to 97.5th percentiles of plasma SCD‐16 and SCD‐18 indices, fat mass differed by about 8 kg and 5 kg, respectively. Intake of polyunsaturated fatty acids were negatively associated with SCD‐16 (partial r = ?0.30) and SCD‐18 (partial r = ?0.24) (P < 0.001 for both). Alcohol intake was positively associated with SCD‐16 (partial r = 0.26) and SCD‐18 (partial r = 0.16) (P < 0.001 for both), whereas coffee consumption and physical activity were inversely associated with SCD‐16 (P = 0.026 and P = 0.006, respectively) and SCD‐18 (P = 0.001 and P = 0.022, respectively).

Conclusions:

In this elderly population, plasma markers of SCD1 activity are associated with increased adiposity. Furthermore, modifiable dietary habits and lifestyle are associated with plasma SCD indices. These results suggest that SCD1 activity may be a promising target for weight control.
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17.

Objective

Early lifestyle interventions in children with obesity decrease risk of obesity and metabolic disorders during adulthood. This study aimed to identify metabolic signatures associated with lifestyle intervention in urine samples from prepubertal children with obesity.

Methods

Thirty‐four prepubertal children with obesity were studied before and after a 6‐month lifestyle intervention program, and anthropometric, metabolic, and nutritional variables were collected. A nuclear magnetic resonance approach was applied to obtain the metabolomic profile from urine samples. Partial least squares‐discriminant analysis (PLS‐DA) was used to achieve group classification and variable importance on projection (VIP) for biomarker selection.

Results

The intervention reduced caloric intake by 10% (P < 0.05) and BMI standard deviation score by 0.47 SD (P < 0.001). PLS‐DA identified trimethylamine N‐oxide (TMAO, VIP = 2.21) as the metabolite with the highest discrimination properties between groups. Urine TMAO levels were reduced after the intervention (P < 0.05). TMAO is a biomarker of cardiovascular disease risk and is a product of gut microbiota‐dependent metabolism of certain dietary compounds, including choline. Notably, changes in TMAO levels after the intervention did not correlate to differences in choline intake but were inversely associated with fiber intake (P < 0.05).

Conclusions

These results indicate that lifestyle intervention decreases TMAO levels in children with obesity.
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18.

Objective:

This study examines the associations between objectively measured sedentary behavior, light physical activity (LPA), and moderate‐to‐vigorous physical activity (MVPA), and plasma lipids in overweight and obese children.

Design and Methods:

Cross‐sectional analyses were conducted among 126 children aged 5.5‐9.9 years. Sedentary behavior, LPA, and MVPA were assessed using accelerometry. Fasting blood samples were analyzed for plasma lipids (high‐density lipoprotein cholesterol [HDL‐C], low‐density lipoprotein cholesterol [LDL‐C], total cholesterol [TC], and triglycerides [TG]).

Results:

MVPA was not related to plasma lipids (P > 0.05). Independent of age, sex, energy intake, and waist circumference z‐score, sedentary behavior and LPA were associated with HDL‐C (β = ?0.23, 95% CI ?0.42 to ?0.04, P = 0.020; β = 0.20, 95% CI 0.14 to 0.39, P = 0.036, respectively). The strength of the associations remained after additionally adjusting for MVPA (sedentary behavior: β = ?0.22, 95% CI ?0.44 to 0.006, P = 0.056; LPA: β = 0.19, 95% CI ?0.005 to 0.38, P = 0.056, respectively).

Conclusion:

Substituting at least LPA for sedentary time may contribute to the development of healthy HDL‐C levels among overweight and obese children, independent of their adiposity. Comprehensive prevention and treatment strategies to improve plasma HDL‐C among overweight and obese children should target reductions in total sedentary time and promote the benefits of LPA, in addition to promoting healthy levels of adiposity, healthy dietary behaviors, and MVPA.
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19.

Objective:

Sedentary behavior in children is positively associated with an increased risk of both obesity and insulin resistance. Children spend a considerable portion of their awake time in sedentary behavior; however, the pattern of accumulation is not known. Thus the objective of this study was to describe the patterning of sedentary behavior of children at and away from school.

Design and Methods:

The patterns of sedentary time in a sample of 53 children (28 girls) aged 10‐12 years during school‐term time were examined. Children wore an accelerometer for 1 week. Total sedentary time, prolonged sequences (bouts) of sedentary time, and frequency of active interruptions to sedentary were examined on school days and weekends and within school time and non‐school time on school days.

Results:

The data did not support our hypothesis that children accumulated more sedentary time on school days when compared with weekend days (mean [SD]: 64.4% [5.3] vs. 64.9% [9.0], P = 0.686). However, when comparing school time with non‐school time on school days, children accumulated more sedentary time at school (66.8% [7.3] vs. 62.4% [5.2], P < 0.001) and spent more time at school in sustained sedentary sequences, that is, uninterrupted sedentary time for 30 min or more (75.6 min [45.8] vs. 45.0 min [26.8], P < 0.002). The children also recorded less breaks per sedentary hour within school time when compared with non‐school time (8.9 h?1 vs. 10.2 h?1, P < 0.001).

Conclusion:

Reducing total sedentary time spent both in and out of school remains an important challenge. Interrupting sedentary time more often in the “working” (school) day could also reap important musculoskeletal and metabolic health rewards for children.
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20.

Objective:

To determine the cardiometabolic risks of testosterone and growth hormone (GH) replacement therapy to youthful levels during aging.

Design and Methods:

A double‐masked, partially placebo controlled study in 112 men 65‐90 years‐old was conducted. Transdermal testosterone (5 g vs. 10 g/day) using a Leydig Cell Clamp and subcutaneous recombinant GH (rhGH) (0 vs. 3 vs. 5 μg/kg/day) were administered for 16‐weeks. Measurements included testosterone and IGF‐1 levels, body composition by DEXA, and cardiometabolic risk factors (upper body fat, blood pressure, insulin sensitivity, fasting triglycerides, HDL‐cholesterol, and serum adiponectin) at baseline and after 16 weeks of treatment.

Results:

Some cardiometabolic factors improved (total and trunk fat, triglycerides, HDL‐cholesterol) and others worsened (systolic blood pressure, insulin sensitivity index [QUICKI], adiponectin). Cardiometabolic risk composite scores (CRCSs) improved (?0.69 ± 1.55, P < 0.001). In multivariate analyses, QUICKI, triglycerides, and HDL‐cholesterol contributed 33%, 16%, and 14% of the variance in CRCS, respectively. Pathway analyses indicated that changes in fat and lean mass were related to individual cardiometabolic variables and CRCS in a complex manner. Changes in BMI, reflecting composite effects of changes in fat and lean mass, were more robustly associated with cardiometabolic risks than changes in fat mass or LBM individually.

Conclusions:

Testosterone and rhGH administration was associated with diverse changes in individual cardiometabolic risk factors, but in aggregate appeared not to worsen cardiometabolic risk in healthy older men after 4‐months. The long‐term effects of these and similar anabolic therapies on cardiovascular events should be investigated in populations with greater functional limitations along with important health disabilities including upper body obesity and other cardiometabolic risks.
  相似文献   

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