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      Comparing the SF-12 and SF-36 health status questionnaires in patients with and without obesity

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      Health and Quality of Life Outcomes
      BioMed Central

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          Abstract

          Objective

          To assess how well the SF-36, a well-validated generic quality of life (QOL) instrument, compares with its shorter adaptation, the SF-12, in capturing differences in QOL among patients with and without obesity.

          Methods

          We compared the correlation between the physical (PCS) and mental (MCS) component summary measures of the SF-12 and SF-36 among 356 primary care patients using Pearson coefficients (r) and conducted linear regression models to see how these summary measures captures the variation across BMI. We used model R 2 to assess qualitatively how well each measure explained the variation across BMI.

          Results

          Correlations between SF-12 and SF-36 were higher for the PCS in obese (r = 0.89) compared to overweight (r = 0.73) and normal weight patients (r = 0.75), p < 0.001, but were similar for the MCS across BMI. Compared to normal weight patients, obese patients scored 8.8 points lower on the PCS-12 and 5.7 points lower on the PCS-36 after adjustment for age, sex, and race; the model R 2 was higher with PCS-12 (R 2 = 0.22) than with PCS-36 (R 2 = 0.16). BMI was not significantly associated with either the MCS-12 or MCS-36.

          Conclusion

          The SF-12 correlated highly with SF-36 in obese and non-obese patients and appeared to be a better measure of differences in QOL associated with BMI.

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          Most cited references16

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          Comparisons of the costs and quality of norms for the SF-36 health survey collected by mail versus telephone interview: results from a national survey.

          Many health status surveys have been designed for mail, telephone, or in-person administration. However, with rare exception, investigators have not studied the effect the survey mode of administration has on the way respondents assess their health and other important parameters (such as response rates, nonresponse bias, and data quality), which can affect the generalizability of results. Using a national sampling frame of noninstitutionalized adults from the General Social Survey, we randomly assigned adults to a mail survey (80%) or a computer-assisted telephone survey (20%). The surveys were designed to provide national norms for the SF-36 Health Survey. Total data collection costs per case for the telephone survey ($47.86) were 77% higher than that for the mail survey ($27.07). A significantly higher response rate was achieved among respondents randomly assigned to the mail (79.2%) than telephone survey (68.9%). Nonresponse bias was evident in both modes but, with the exception of age, was not differential between modes. The rate of missing responses was higher for mail than telephone respondents (1.59 vs. 0.49 missing items). Health ratings based on the SF-36 scales were less favorable, and reports of chronic conditions were more frequent, for mail than telephone respondents. Results are discussed in light of the trade-offs involved in choosing a survey methodology for health status assessment applications. Norms for mail and telephone versions of the SF-36 survey are provided for use in interpreting individual and group scores.
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            Bariatric analysis and reporting outcome system (BAROS)

            The lack of standards for comparison of results was identified by the NIH Consensus Conference panelists as one of the key problems in evaluating reports in the surgical treatment of severe obesity. The analysis of outcomes after bariatric surgery should include weight loss, improvement in comorbidities related to obesity, and quality-of-life (QOL) assessment. Definitions of success and failure should be established and the presentation of results standardized. A survey among experienced bariatric surgeons was conducted to study the reporting of results. The concept of evaluating outcomes by using a scoring system was introduced in 1997 and has now been refined further. Psychologists with expertise in bariatrics were asked to recommend a disease-specific instrument to analyze QOL after surgery. The system defines five outcome groups (failure, fair, good, very good, and excellent), based on a scoring table that adds or subtracts points while evaluating three main areas: percentage of excess weight loss, changes in medical conditions, and QOL. To assess changes in QOL after treatment, this method incorporates a specifically designed patient questionnaire that addresses self-esteem and four daily activities. Complications and reoperative surgery deduct points, thus avoiding the controversy of considering reoperations as failures. The Bariatric Analysis and Reporting Outcome System (BAROS) analyzes outcomes in a simple, objective, unbiased, and evidence-based fashion. It can be adapted to evaluate other forms of medical intervention for the control of obesity. This method should be considered by international organizations for the adoption of standards for the outcome assessment of bariatric treatments, and for the comparison of results among surgical series. These standards could also be used to compare the long-term effects of surgery with nonoperative weight loss methods.
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              Impact of obesity on health-related quality of life in patients with chronic illness.

              To determine the association between overweight and obesity and health-related quality of life (HRQOL) in patients with chronic conditions typical of those seen in general medical practice, after accounting for the effects of depression and medical comorbidities. Cross-sectional analysis of data from the Medical Outcomes Study. Offices of physicians practicing family medicine, internal medicine, endocrinology, cardiology, and psychiatry in three U.S. cities. We surveyed 2,931 patients with chronic medical and psychiatric conditions. The patients completed a self-administered questionnaire at enrollment and had complete data on height and weight. Body mass index (BMI), chronic medical conditions, and depression were obtained by structured interview. Health-related quality of life was measured by the SF-36 Health Survey. Patients who were overweight (BMI 25.0-29.9 kg/m2), patients with class I obesity (BMI 30.0-34.9 kg/m2), and patients with class II-III obesity (BMI > or = 35 kg/m2) had significantly lower adjusted physical function scores (by 3.4, 7.8, and 13.8 points, respectively) compared with nonoverweight patients. Patients with class I and class II-III obesity also had significantly lower adjusted general health perceptions scores (by 2.8 and 4.4 points, respectively) and lower adjusted vitality scores (by 4.0 and 7.1 points, respectively), compared with nonoverweight patients. No significant differences between nonoverweight, overweight, and obese patients were observed for the mental health scale. Women with elevated BMI had significantly lower HRQOL scores compared with the scores of obese men in several domains. Additionally, blacks with elevated BMI had significantly lower scores than whites in several domains of HRQOL. Overweight and obesity have the largest association with physical function measures. Recent national standards, which have lowered the threshold for defining overweight, identify patients who are more likely to have clinically significant reductions in HRQOL and functional impairment.
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                Author and article information

                Journal
                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central
                1477-7525
                2008
                30 January 2008
                : 6
                : 11
                Affiliations
                [1 ]Division of General Medicine and Primary Care, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
                Article
                1477-7525-6-11
                10.1186/1477-7525-6-11
                2270807
                18234099
                fd661b6a-25da-41b2-91cb-fb1fd135d0e5
                Copyright © 2008 Wee et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 August 2007
                : 30 January 2008
                Categories
                Research

                Health & Social care
                Health & Social care

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