The prevalence of obesity and associated cardiometabolic risk factors such as diabetes, hyperlipidemia and hypertension is increasing significantly for all demographic groups.
The 2000 and 2002 Medical Expenditure Panel Survey (MEPS), a nationally representative survey of the U.S. population, was used to estimate the marginal impact of obesity on health function, perception, and preferences for individuals with diabetes, hyperlipidemia, and hypertension using multivariate regression methods controlling for age, sex, race, ethnicity, education, income, insurance, smoking status, comorbidity, and proxy response. Three different instruments were used: SF-12 physical component scale (PCS-12) and mental component scale (MCS-12); EQ-5D index and visual analogue scale (VAS). Censored least absolute deviation was used for the EQ-5D and VAS (due to censoring) and ordinary least squares (OLS) was used for the PCS-12 and MCS-12.
After controlling for sociodemographic characteristics, diabetes, hyperlipidemia, and hypertension were associated with significantly lower scores compared to normal weight individuals without the condition for all four instruments. Obesity significantly exacerbated this association. Controlling for comorbidity attenuated the negative association of obesity and cardiometabolic risk factors on instrument scores. In addition, scores decreased for increasing weight and number of risk factors.
Obesity significantly exacerbates the deleterious association between diabetes, hyperlipidemia, and hypertension, and health function, health perception, and preference-based scores in the United States.
"However, only two body weight categories were included in the analyses: normal and obese. The authors did not define the BMI ranges for these categories, and this omission limits the generalizability of these results (Sullivan et al., 2008). "
[Show abstract][Hide abstract] ABSTRACT: Obesity is a chronic, progressive, multifactorial medical condition. It is known that obesity is associated with cardiovascular disease, metabolic disorders, degenerative joint disorders, and decreased health-related quality of life (HRQoL). In addition, there are socio-economic, gender, age, and racial differences in the population distribution of obesity. The extent to which HRQoL is impaired by obesity independent of associated chronic disease and known demographic risk factors is less well understood by nurses. A secondary analysis of the National Health Measurement Study (NHMS) was conducted to illustrate this relationship. Regression analyses were used to assess the association between body mass index (BMI) and HRQol. BMI was categorized as normal, overweight, obese, and morbidly obese. HRQoL was measured using the EQ-5D and EQ-VAS. After adjusting for chronic health conditions and demographic factors, lower HRQoL was observed as BMI category increased for both the EQ-5D, F = 40.49, 15 df, p < .001, and EQ-VAS, F = 35.5, 15 df, p < .001.
Western Journal of Nursing Research 01/2014; 36(8). DOI:10.1177/0193945913520415 · 1.03 Impact Factor
"Nearly three-fourths of the 5.7 million Veterans  who receive their medical care from the Veterans Health Administration (VHA) are overweight or obese . Overweight and obesity are associated with substantial morbidity and mortality [5-8] and increased healthcare costs for patients, healthcare systems, and payers [7,9,10]. In 2001, VHA primary care providers cited effective weight management programs as the most pressing need in preventive services for Veterans . "
[Show abstract][Hide abstract] ABSTRACT: Background
In the United States, as in many other parts of the world, the prevalence of overweight/obesity is at epidemic proportions in the adult population and even higher among Veterans. To address the high prevalence of overweight/obesity among Veterans, the MOVE!® weight management program was disseminated nationally to Veteran Affairs (VA) medical centers. The objective of this paper is two-fold: to describe factors that explain the wide variation in implementation of MOVE!; and to illustrate, step-by-step, how to apply a theory-based framework using qualitative data.
Five VA facilities were selected to maximize variation in implementation effectiveness and geographic location. Twenty-four key stakeholders were interviewed about their experiences in implementing MOVE!. The Consolidated Framework for Implementation Research (CFIR) was used to guide collection and analysis of qualitative data. Constructs that most strongly influence implementation effectiveness were identified through a cross-case comparison of ratings.
Of the 31 CFIR constructs assessed, ten constructs strongly distinguished between facilities with low versus high program implementation effectiveness. The majority (six) were related to the inner setting: networks and communications; tension for change; relative priority; goals and feedback; learning climate; and leadership engagement. One construct each, from intervention characteristics (relative advantage) and outer setting (patient needs and resources), plus two from process (executing and reflecting) also strongly distinguished between high and low implementation. Two additional constructs weakly distinguished, 16 were mixed, three constructs had insufficient data to assess, and one was not applicable. Detailed descriptions of how each distinguishing construct manifested in study facilities and a table of recommendations is provided.
This paper presents an approach for using the CFIR to code and rate qualitative data in a way that will facilitate comparisons across studies. An online Wiki resource (http://www.wiki.cfirwiki.net) is available, in addition to the information presented here, that contains much of the published information about the CFIR and its constructs and sub-constructs. We hope that the described approach and open access to the CFIR will generate wide use and encourage dialogue and continued refinement of both the framework and approaches for applying it.
"It is an alarming fact that, during the last 6 years only, the number of obese subjects has increased by 5% in the total population of 10.3 million, which makes 425,000 people . Recently, a series of epidemiologic studies has evidenced a close link between morbid obesity and type 2 diabetes mellitus, hypertension, hyperlipidemia, obstructive sleep apnea, metabolic syndrome and insulin resistance [4, 5]. The scale of the problem is also confirmed by the fact that obesity, when exceeding 40 kg/m2, shortens life span, on average, by 20 years, while obesity consequences are more severe than the consequences of tobacco smoking or alcohol consumption [6, 7]. "
[Show abstract][Hide abstract] ABSTRACT: Surgical intervention in obesity is today the most effective treatment method in high level obesity management with long-term clinical results and satisfaction of operated patients. Bariatric interventions not only ensure body weight reduction, but may influence lipid and saccharide metabolism as well.
To monitor the dynamics of changes in selected lipid and glucose metabolism parameters after laparoscopic sleeve gastrectomy (LSG) in obese women.
During the period from September 2010 to June 2011, 35 women, operated on by sleeve gastrectomy, were monitored within a pilot open study. Parameters of lipid and glucose metabolism were measured, and body composition was evaluated, using dual X-ray absorptiometry (DXA). Laboratory parameters were assessed prior to LSG and at 3 and 6 months after the surgery.
Data of the 35 study subjects are presented. Average age was 41.9 years (27-68 years). Six months after LSG, body weight reduction was achieved from 117.7 ±17.1 kg to 91.2 ±17.2 kg (p < 0.001). The body mass index (BMI) dropped from 42.7 ±4.7 kg/m(2) to 33.0 ±4.9 kg/m(2) (p < 0.001). The excess weight loss (EWL) was 49.01%. High density lipoprotein (HDL) cholesterol increased from 1.29 mmol/l to 1.39 mmol/l (p < 0.025). Triacylglycerols dropped from 1.97 mmol/l to 1.31 mmol/l (p < 0.001). Glycated hemoglobin dropped from 4.03% to 3.59% (p < 0.001), and C-peptide decreased from 1703 pmol/l to 1209 pmol/l (p < 0.002). The observed changes of low density lipoprotein (LDL) cholesterol, total cholesterol or fasting glucose levels were not significant. Six months after LSG, both weight and BMI significantly decreased.
Six months after the operation, glucose homeostasis was improved. Despite the rather short-term monitoring period, our study did confirm LSG to influence not only total weight loss and fat tissue reduction but to improve risk factors, mainly glucose homeostasis and dyslipidemia, as well.
Videosurgery and Other Miniinvasive Techniques / Wideochirurgia i Inne Techniki Malo Inwazyjne 03/2013; 8(1):22-8. DOI:10.5114/wiitm.2011.31631 · 1.09 Impact Factor
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