Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among Canadian preschool-aged children using compositional analyses

Abstract Background Sleep duration, sedentary behaviour, and physical activity are three co-dependent behaviours that fall on the movement/non-movement intensity continuum. Compositional data analyses provide an appropriate method for analyzing the association between co-dependent movement behaviour data and health indicators. The objectives of this study were to examine: (1) the combined associations of the composition of time spent in sleep, sedentary behaviour, light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA) with adiposity indicators; and (2) the association of the time spent in sleep, sedentary behaviour, LPA, or MVPA with adiposity indicators relative to the time spent in the other behaviours in a representative sample of Canadian preschool-aged children. Methods Participants were 552 children aged 3 to 4 years from cycles 2 and 3 of the Canadian Health Measures Survey. Sedentary time, LPA, and MVPA were measured with Actical accelerometers (Philips Respironics, Bend, OR USA), and sleep duration was parental reported. Adiposity indicators included waist circumference (WC) and body mass index (BMI) z-scores based on World Health Organization growth standards. Compositional data analyses were used to examine the cross-sectional associations. Results The composition of movement behaviours was significantly associated with BMI z-scores (p = 0.006) but not with WC (p = 0.718). Further, the time spent in sleep (BMI z-score: γ sleep  = −0.72; p = 0.138; WC: γ sleep  = −1.95; p = 0.285), sedentary behaviour (BMI z-score: γ SB  = 0.19; p = 0.624; WC: γ SB  = 0.87; p = 0.614), LPA (BMI z-score: γ LPA  = 0.62; p = 0.213, WC: γ LPA  = 0.23; p = 0.902), or MVPA (BMI z-score: γ MVPA  = −0.09; p = 0.733, WC: γ MVPA  = 0.08; p = 0.288) relative to the other behaviours was not significantly associated with the adiposity indicators. Conclusions This study is the first to use compositional analyses when examining associations of co-dependent sleep duration, sedentary time, and physical activity behaviours with adiposity indicators in preschool-aged children. The overall composition of movement behaviours appears important for healthy BMI z-scores in preschool-aged children. Future research is needed to determine the optimal movement behaviour composition that should be promoted in this age group

Association of general and central adiposity with blood pressure among Chinese adults: results from the China National Stroke Prevention Project

Background: The American Heart Association concluded that waist circumference was a better predictor of blood pressure risk than BMI in Asians. However, data are inconsistent and information in Chinese, the largest global population group, is limited.  Methods: Data was obtained from the Chinese National Stroke Prevention Project Survey of a nationally representative sample of middle-aged and older Chinese adults. A total of 135 825 individuals not taking any antihypertensive drugs were included in this study. Multiple linear regression analyses were conducted to examine the association between blood pressure and parameters of general adiposity, including BMI, height-adjusted weight, and parameters of central adiposity, including waist circumference, hip circumference, waist–hip ratio, and waist–height ratio. Results were shown as mean difference in blood pressure associated with one standard deviation higher level of adiposity.  Results: The overall means ± standard deviation of BMI and waist circumference were 24.3 ± 3.18 kg/m2 and 84.0 ± 8.88 cm, respectively. BMI seemed more strongly associated with SBP/DBP (4.22 mmHg/SD; 2.60 mmHg/SD) than central adiposity markers. In addition, there were sex differences. For men, waist circumference showed a stronger association with SBP/DBP than BMI (4.04 vs. 3.79, P < 0.05; 2.26 vs. 2.13, P < 0.05). For women, BMI was more closely related to SBP/DBP than central adiposity parameters, such as waist circumference (4.59 vs. 3.41, P < 0.05; 2.98 vs. 2.24, P < 0.05). Additionally, in both urban and rural areas, waist circumference was mostly associated with SBP/DBP among men, whereas it was BMI among women.  Conclusion: Compared with central adiposity, blood pressure is more strongly associated with general adiposity in Chinese adults. Interestingly, there are significant sex differences in the relationship of blood pressure with general and central adiposity. Waist circumference is the strongest predictor for men but suboptimal for women, and BMI tend to a better predictor of blood pressure for women. In addition, our results for men are consistent with the recommendation of the American Heart Association in 2015 that waist circumference could be used for assessing the risk of blood pressure

Healthy Hearts – A community-based primary prevention programme to reduce coronary heart disease

Background The ten year probability of cardiovascular events can be calculated, but many people are unaware of their risk and unclear how to reduce it. The aim of this study was to assess whether a community based intervention, for men and women aged between 45 and 64 years without pre-existing coronary heart disease, would reduce their Framingham scores when reassessed one year later. Methods Individuals in the relevant age group from a defined geographical area were sent an invitation to attend for an assessment of their cardiovascular risk. Individuals with pre-existing cardiovascular disease or terminal illness were excluded. The invitation was in the form of a "Many Happy Returns" card with a number of self-screening questions including the question, "If you put the enclosed string around your waist, is it too short?" The card contained a red 80 cm piece of string in the case of women, or a green 90 cm piece of string in the case of men. At the assessment appointment, Framingham scores were calculated and a printout was given to each individual. Advice was provided for relevant risk factors identified using agreed guidelines. If appropriate, onward referral was also made to a GP, dietician, an exercise referral scheme, or to smoking cessation services, using a set of guidelines. Individuals were sent a second invitation one year later to return for re-assessment. Results and discussion 2031 individuals were asked to self-assess their eligibility to participate, 596 individuals attended for assessment and 313 of these attended for follow-up one year later. The mean reduction in the Framingham risk score, was significantly lower at one year (0.876, 95% CI 0.211 to 1.541, p = 0.01). The mean 10-year risk of CHD at baseline was 13.14% (SD 9.18) and had fallen at follow-up to 12.34% (SD 8.71), a mean reduction of 6.7% of the initial 10-year Framingham risk. If sustained, the estimated NNT to prevent each year of CHD would be 1141 (95% CI 4739 to 649) individual appointments. Conclusion This community intervention for primary prevention of CHD reduces Framingham risk scores at one year in those who engage with the programme

To treat or not to treat: comparison of different criteria used to determine whether weight loss is to be recommended

Background: Excess body fat is a major risk factor for disease primarily due to its endocrine activity. In recent years several criteria have been introduced to evaluate this factor. Nevertheless, treatment need is currently assessed only on the basis of an individual's Body Mass Index (BMI), calculated as body weight (in kg) divided by height in m2. The aim of our study was to determine whether application of the BMI, compared to adiposity-based criteria, results in underestimation of the number of subjects needing lifestyle intervention. Methods: We compared treatment need based on BMI classification with four adiposity-based criteria: percentage body fat (%BF), considered both alone and in relation to metabolic syndrome risk (MS), waist circumference (WC), as an index of abdominal fat, and Body Fat Mass Index (BFMI, calculated as fat mass in kg divided by height in m2) in 63 volunteers (23 men and 40 women, aged 20 – 65 years). Results: According to the classification based on BMI, 6.3% of subjects were underweight, 52.4% were normal weight, 30.2% were overweight, and 11.1% were obese. Agreement between the BMI categories and the other classification criteria categories varied; the most notable discrepancy emerged in the underweight and overweight categories. BMI compared to almost all of the other adiposity-based criteria, identified a lower percentage of subjects for whom treatment would be recommended. In particular, the proportion of subjects for whom clinicians would strongly recommend weight loss on the basis of their BMI (11.1%) was significantly lower than those identified according to WC (25.4%, p = 0.004), %BF (28.6%, p = 0.003), and MS (33.9%, p = 0.002). Conclusion: The use of the BMI alone, as opposed to an assessment based on body composition, to identify individuals needing lifestyle intervention may lead to unfortunate misclassifications. Population-specific data on the relationships between body composition, morbidity, and mortality are needed to improve the diagnosis and treatment of at-risk individual

Overweight and obesity in relation to cardiovascular disease risk factors among medical students in Crete, Greece

BACKGROUND: Recent data indicate increasing rates of adult obesity and mortality from cardiovascular disease (CVD) in Greece. No data, however, are available on prevalence of overweight and obesity in relation to CVD risk factors among young adults in Greece. METHODS: A total of 989 third-year medical students (527 men, 462 women), aged 22 ± 2 years, were recruited from the University of Crete during the period 1989–2001. Anthropometric measures and blood chemistries were obtained. The relationships between obesity indices (body mass index [BMI], waist circumference [WC], waist-to-hip ratio [WHpR], waist-to-height ratio [WHtR]) and CVD risk factor variables (blood pressure, glucose, serum lipoproteins) were investigated. RESULTS: Approximately 40% of men and 23% of women had BMI ≥ 25.0 kg/m(2). Central obesity was found in 33.4% (average percentage corresponding to WC ≥ 90 cm, WHpR ≥ 0.9 and WHtR ≥ 50.0) of male and 21.7% (using WC ≥ 80 cm, WHpR ≥ 0.8, WHtR ≥ 50.0) of female students. Subjects above the obesity indices cut-offs had significantly higher values of CVD risk factor variables. BMI was the strongest predictor of hypertension. WHtR in men and WC in women were the most important indicators of dyslipidaemia. CONCLUSION: A substantial proportion of Greek medical students were overweight or obese, obesity status being related to the presence of hypertension and dyslipidaemia. Simple anthropometric indices can be used to identify these CVD risk factors. Our results underscore the need to implement health promotion programmes and perform large-scale epidemiological studies within the general Greek young adult population

The "lipid accumulation product" performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison

BACKGROUND: Body mass index (BMI, kg/m(2)) may not be the best marker for estimating the risk of obesity-related disease. Consistent with physiologic observations, an alternative index uses waist circumference (WC) and fasting triglycerides (TG) concentration to describe lipid overaccumulation. METHODS: The WC (estimated population minimum 65 cm for men and 58 cm for women) and TG concentration from the third National Health and Nutrition Examination Survey (N = 9,180, statistically weighted to represent 100.05 million US adults) were used to compute a "lipid accumulation product" [LAP = (WC-65) × TG for men and (WC-58) × TG for women] and to describe the population distribution of LAP. LAP and BMI were compared as categorical variables and as log-transformed continuous variables for their ability to identify adverse levels of 11 cardiovascular risk factors. RESULTS: Nearly half of the represented population was discordant for their quartile assignments to LAP and BMI. When 23.54 million with ordinal LAP quartile > BMI quartile were compared with 25.36 million with ordinal BMI quartile > LAP quartile (regression models adjusted for race-ethnicity and sex) the former had more adverse risk levels than the latter (p < 0.002) for seven lipid variables, uric acid concentration, heart rate, systolic and diastolic blood pressure. Further adjustment for age did not materially alter these comparisons except for blood pressures (p > 0.1). As continuous variables, LAP provided a consistently more adverse beta coefficient (slope) than BMI for nine cardiovascular risk variables (p < 0.01), but not for blood pressures (p > 0.2). CONCLUSION: LAP (describing lipid overaccumulation) performed better than BMI (describing weight overaccumulation) for identifying US adults at cardiovascular risk. Compared to BMI, LAP might better predict the incidence of cardiovascular disease, but this hypothesis needs prospective testing

CHARGE syndrome

CHARGE syndrome was initially defined as a non-random association of anomalies (Coloboma, Heart defect, Atresia choanae, Retarded growth and development, Genital hypoplasia, Ear anomalies/deafness). In 1998, an expert group defined the major (the classical 4C's: Choanal atresia, Coloboma, Characteristic ears and Cranial nerve anomalies) and minor criteria of CHARGE syndrome. Individuals with all four major characteristics or three major and three minor characteristics are highly likely to have CHARGE syndrome. However, there have been individuals genetically identified with CHARGE syndrome without the classical choanal atresia and coloboma. The reported incidence of CHARGE syndrome ranges from 0.1–1.2/10,000 and depends on professional recognition. Coloboma mainly affects the retina. Major and minor congenital heart defects (the commonest cyanotic heart defect is tetralogy of Fallot) occur in 75–80% of patients. Choanal atresia may be membranous or bony; bilateral or unilateral. Mental retardation is variable with intelligence quotients (IQ) ranging from normal to profound retardation. Under-development of the external genitalia is a common finding in males but it is less apparent in females. Ear abnormalities include a classical finding of unusually shaped ears and hearing loss (conductive and/or nerve deafness that ranges from mild to severe deafness). Multiple cranial nerve dysfunctions are common. A behavioral phenotype for CHARGE syndrome is emerging. Mutations in the CHD7 gene (member of the chromodomain helicase DNA protein family) are detected in over 75% of patients with CHARGE syndrome. Children with CHARGE syndrome require intensive medical management as well as numerous surgical interventions. They also need multidisciplinary follow up. Some of the hidden issues of CHARGE syndrome are often forgotten, one being the feeding adaptation of these children, which needs an early aggressive approach from a feeding team. As the child develops, challenging behaviors become more common and require adaptation of educational and therapeutic services, including behavioral and pharmacological interventions

CHARGE syndrome: Genetic aspects and dental challenges, a review and case presentation

CHARGE syndrome (CS) is a rare genetic condition (OMIM #214800). The condition has a variable phenotypic expression. Historically, the diagnosis of CHARGE syndrome was based on the presence of specific clinical criteria. The genetic aetiology of CS has since been elucidated and attributed to pathogenic variation in the CHD7 gene (OMIM 608892) at chromosome locus 8q12