Range Of Metabolic Risk Factors Research Articles

Pacific Islands Families Study: Physical growth to age 14 and metabolic risk.

The relationships between the trajectories of weight gain from early childhood to adolescence and risk for metabolic disease are not well understood. The objective of the study is to examine the relationships between weight gain from 2 to 14years and metabolic risk factors at age 14years in Pacific Island children. z scores for weight were calculated at each of the ages 2.5, 4, 6, 9, 11, and 13.5years in 1053 children. Growth trajectories were determined by estimating the linear trend of z scores with age for each child. In a subgroup of 204 children, biomarkers of metabolic risk were measured and related to linear trend intercepts and slopes. More rapid growth (greater slope of z score trajectory) was associated with higher concentrations of insulin, leptin (boys), urate, and markers of liver function, insulin resistance and inflammation. Children with higher weights in early life (greater intercept) showed fewer associations with metabolic markers, but considered together, intercept and slope were independently associated with a range of metabolic risk factors. Both rapid weight gain and a higher body weight in early childhood were associated with higher risk for metabolic disease. Monitoring growth trajectories may help target interventions to optimize nutrition, physical activity, and growth.

Evolution of metabolic risk factors over a two-year period in a cohort of first episodes of psychosis

Patients with a first episode of psychosis (FEP) display a broad range of metabolic risk factors related to the development of diverse medical comorbidities. Initial stages of these disorders are essential in understanding the increased vulnerability of developing cardiometabolic disturbances, associated with a reduced life expectancy. This study aimed to evaluate the metabolic profile of a cohort of patients with a FEP and its evolution during a two year follow-up, as well as the factors that influence the changes in their metabolic status.16 participating centers from the PEPs Project recruited 335 subjects with a FEP and 253 matched healthy controls, aged 9–35years. We investigated a set of anthropometric measures, vital signs and laboratory data obtained from each participant over two years in a prospective, naturalistic study.From the beginning of the study the FEP group showed differences in the metabolic profile compared to the control group, together with a progressive worsening in the major part of the analyzed variables during the follow-up period, with higher rates of obesity and metabolic syndrome. Certain risk factors were related to determinate clinical variables such as male gender, the presence of affective symptoms or an early onset or to treatment variables such as the use of antipsychotic polypharmacy, antidepressants or mood stabilizers.Our results highlight the extremely high risk of patients at early phases of schizophrenia and other psychotic disorders of developing cardiovascular comorbidity and the fast worsening of the metabolic profile during the first two years.

Proteomics reveals the effects of sustained weight loss on the human plasma proteome.

Sustained weight loss is a preferred intervention in a wide range of metabolic conditions, but the effects on an individual's health state remain ill‐defined. Here, we investigate the plasma proteomes of a cohort of 43 obese individuals that had undergone 8 weeks of 12% body weight loss followed by a year of weight maintenance. Using mass spectrometry‐based plasma proteome profiling, we measured 1,294 plasma proteomes. Longitudinal monitoring of the cohort revealed individual‐specific protein levels with wide‐ranging effects of losing weight on the plasma proteome reflected in 93 significantly affected proteins. The adipocyte‐secreted SERPINF1 and apolipoprotein APOF1 were most significantly regulated with fold changes of −16% and +37%, respectively (P < 10−13), and the entire apolipoprotein family showed characteristic differential regulation. Clinical laboratory parameters are reflected in the plasma proteome, and eight plasma proteins correlated better with insulin resistance than the known marker adiponectin. Nearly all study participants benefited from weight loss regarding a ten‐protein inflammation panel defined from the proteomics data. We conclude that plasma proteome profiling broadly evaluates and monitors intervention in metabolic diseases.

Childhood obesity and risk of the adult metabolic syndrome: a systematic review.

Background:While many studies have demonstrated positive associations between childhood obesity and adult metabolic risk, important questions remain as to the nature of the relationship. In particular, it is unclear whether the associations reflect the tracking of body mass index (BMI) from childhood to adulthood or an independent level of risk. This systematic review aimed to investigate the relationship between childhood obesity and a range of metabolic risk factors during adult life.Objective:To perform an unbiased systematic review to investigate the association between childhood BMI and risk of developing components of metabolic disease in adulthood, and whether the associations observed are independent of adult BMI.Design:Electronic databases were searched from inception until July 2010 for studies investigating the association between childhood BMI and adult metabolic risk. Two investigators independently reviewed studies for eligibility according to the inclusion/exclusion criteria, extracted the data and assessed study quality using the Newcastle–Ottawa Scale.Results:The search process identified 11 articles that fulfilled the inclusion and exclusion criteria. Although several identified weak positive associations between childhood BMI and adult total cholesterol, low-density lipo protein-cholesterol, triglyceride and insulin concentrations, these associations were ameliorated or inversed when adjusted for adult BMI or body fatness. Of the four papers that considered metabolic syndrome as an end point, none showed evidence of an independent association with childhood obesity.Conclusions:Little evidence was found to support the view that childhood obesity is an independent risk factor for adult blood lipid status, insulin levels, metabolic syndrome or type 2 diabetes. The majority of studies failed to adjust for adult BMI and therefore the associations observed may reflect the tracking of BMI across the lifespan. Interestingly, where adult BMI was adjusted for, the data showed a weak negative association between childhood BMI and metabolic variables, with those at the lower end of the BMI range in childhood, but obese during adulthood at particular risk.

Effect of a lifestyle intervention in patients with abnormal liver enzymes and metabolic risk factors

Non-alcoholic fatty liver disease associated with insulin resistance is the most common cause of abnormal liver tests in clinical practice. To date, practical and effective strategies to improve the metabolic profile of this large group of patients have not been well characterised. We sought to assess the effect at 3 months of a behavior change-based lifestyle intervention on the metabolic profile of patients characterised by elevated liver enzymes. A total of 152 patients with elevated liver enzymes, central obesity and a range of metabolic risk factors were randomised to either a moderate- (6 sessions/10 weeks) or low-intensity (3 sessions/4 weeks) lifestyle counselling intervention or control group. There was improvement in all metabolic risk factors in the moderate-intensity group, versus a smaller number of changes in the low-intensity intervention group and no change in any metabolic risk factors in control subjects. Reduction in liver enzymes was greatest in the moderate-intensity intervention group and least in the control group. The likelihood of elevated alanine aminotransferase (ALT) levels in both the moderate and low-intensity groups was reduced by over 70% compared to controls. The proportion of subjects achieving weight loss (>or= 2%) was significantly higher in the moderate-intensity intervention group (66%) versus the low-intensity intervention group (39%; P < 0.05) and controls (29%; P < 0.001). Moderate and even low-intensity lifestyle counselling interventions targeting improvement in physical activity and nutritional behaviors and modest weight loss are a practical and effective method for improving the health of patients with elevated liver enzymes and a range of metabolic risk factors.

Is there a menopausal metabolic syndrome?

Estradiol-17β has beneficial effects on a range of metabolic risk factors for coronary heart disease and the decline in estrogen concentrations at the menopause would be expected to have adverse effects. Review of the literature on effects of the menopause and of estradiol-17β provides evidence for the following changes occuring at or after the menopause: increased total cholesterol and triglycerides; decreased high density lipoprotein (HDL) and HDL subfraction 2; increased low density lipoprotein, particularly in the small, dense subfraction; increased lipoprotein (a); increased insulin resistance; decreased insulin secretion; decreased insulin elimination; increased android fat distribution; impaired vascular function; increased factor VII and fibrinogen, and reduced sex-hormone binding globulin. Many of these changes will themselves have adverse effects on other metabolic risk factors. This complex of inter-correlated adverse changes in metabolic risk factors justifies identification of a distinct menopausal metabolic syndrome which originates in estrogen deficiency and which could contribute to the increased risk of coronary heart disease seen in postmenopausal women. Estrogen replacement can diminish the expression of this syndrome.