A family operation: plastic surgeons who perform aesthetic surgery on spouses or other family members.
Plast Reconstr Surg. 2010 Mar;125(3):1018-23
Authors: Slavin SA, Slavin SA, Goldwyn RM
BACKGROUND:: The purpose of this study was to investigate whether plastic surgeons would perform elective cosmetic surgery on spouses or other family members and how many have done so, the type of procedures, the circumstances under which the surgery took place, and the results. METHODS:: Participants were 465 members of the American Society for Aesthetic Plastic Surgery, representing 30.7 percent of the overall sample pool of 1513 members recruited through anonymous, voluntary participation in an online survey. Approximately half (51.8 percent) were 51 to 65 years old, most were men (91.2 percent), and most were from large urban areas; respondents had been in practice for 1 to 40 years. RESULTS:: The plastic surgeons who returned the survey were comfortable performing elective cosmetic procedures on family members, the majority having already done so. Eighty-eight percent reported they would operate on a spouse or other family member, and 83.9 percent reported they already had. The main motivation (67 percent) was their belief that they were the best surgeon for the procedure. The most commonly listed operations were rhinoplasty, abdominoplasty, eyelidplasty, face lift, breast augmentation, and liposuction. Patients included spouses, children, parents, cousins, and in-laws, ranging from teenaged males to women in their 70s. The overwhelming majority (94.2 percent) reported no complications, and 99.5 percent believed the patients were satisfied with their outcome. CONCLUSIONS:: Survey participants are comfortable with the idea of performing elective cosmetic procedures on family members. Regardless of the invasiveness of the procedure or their relationship with the patient, respondents reported no complications and a high level of patient satisfaction anomalous for any patient-surgeon sample, suggesting that surgeons who operate on family members hold confident opinions of their surgical skills and results.
PMID: 20195128 [PubMed - in process]
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Surveillance of certain health behaviors and conditions among States and selected local areas — behavioral risk factor surveillance system, United States, 2007.
MMWR Surveill Summ. 2010 Feb 5;59(1):1-220
Authors: Chowdhury P, Balluz L, Town M, Chowdhury FM, Bartolis W, Garvin W, Akcin H, Greenlund KJ, Giles W,
Problem: Chronic diseases (e.g., heart disease, cancer, stroke, and diabetes) are the leading causes of death in the United States. Controlling health risk behaviors (e.g., smoking, physical inactivity, poor diet, and excessive drinking) and using preventive health-care services (e.g., cancer, hypertension, and cholesterol screenings) can reduce morbidity and mortality from chronic diseases. Monitoring health-risk behaviors, chronic health conditions, and preventive care practices is essential to develop health promotion activities, intervention programs, and health policies at the state, city, and county levels. Reporting Period Covered: January 2007–December 2007 Description of the System: The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based, on-going, random–digit-dialed household telephone survey of noninstitutionalized adults aged >/=18 years residing in the United States. BRFSS collects data on health-risk behaviors and use of preventative health services related to the leading causes of death and disability in the United States. This report presents results for 2007 for all 50 states, the District of Columbia, the Commonwealth of Puerto Rico, Guam, the Virgin Islands, 184 metropolitan and micropolitan statistical areas (MMSAs), and 298 counties. Results: In 2007, prevalence estimates of risk behaviors, chronic conditions, and the use of preventive services varied substantially by state and territory, MMSA, and county. The following is a summary of results listed by BRFSS question topic. Each set of proportions refers to the range of estimated prevalence for the disease, condition, or behavior, as reported by the survey subject. Adults who reported fair or poor health: 11% to 32% for states and territories and 6% to 31% for MMSAs and counties. Adults with health-care coverage: 71% to 94% for states and territories and 51% to 97% for MMSAs and counties. Annual influenza vaccination among adults aged >/=65 years: 32% to 80% for states and territories, 48% to 83% for MMSAs, and 44% to 88% for counties. Pneumococcal vaccination among adults aged >/=65 years: 26% to 74% for states and territories, 44% to 83% for MMSAs, and 39% to 87% for counties. Adults who had their cholesterol checked within the preceding 5 years: 66% to 85% for states and territories and 58% to 90% for MMSAs and counties. Adults who consumed at least 5 servings of fruits and vegetables per day: 14% to 33% for states and territories, 16% to 34% for MMSAs and 14% to 37% for counties. Adults who reported no leisure-time physical activity: 17% to 44% for states and territories and 9% to 38% for MMSAs and counties. Adults who engaged in moderate or vigorous physical activity: 31% to 61% for states and territories and 36% to 67% for MMSAs and counties. Adults who engaged in only vigorous physical activity: 19% to 40% for states and territories and 15% to 45% for MMSAs and counties. Cigarette smoking among adults: 9% to 31% for states and territories, 7% to 34% for MMSAs, and 7% to 30% for counties. Binge drinking among adults: 3% to 8% for states and territories. Adults classified as overweight: 33% to 40% for states and territories and 26% to 47% for MMSAs and counties. Adults aged >/=20 years who were obese: 20% to 34% for states and territories and 14% to 38% for MMSAs and counties. Adults who were told of a diabetes diagnosis: 5% to 13% for states and territories and 2% to 17% for MMSAs and counties. Adults with high blood pressure diagnosis: 21% to 35% for states and territories and 16% to 38% for MMSAs and counties. Adults who had high blood cholesterol: 28% to 43% for states and territories, 29% to 49% for MMSAs, and 26% to 51% for counties. Adults with a history of coronary heart disease: 2% to 14% for states and territories, MMSAs, and counties. Adults who were told of a stroke diagnosis: 1% to 7% for states and territories, MMSAs, and counties. Adults who were diagnosed with arthritis: 14% to 36% for states and territories and 16% to 40% for MMSAs and counties. Adults who had asthma: 5% to 10% for states and territories and 3% to 13% for MMSAs and counties. Adults with activity limitation associated with physical, mental, or emotional problems: 10% to 26% for states and territories. Adults who required special equipment because of health problems: 3% to 10% for states and territories and 3% to 14% for MMSAs and counties. Interpretation: The findings in this report indicate substantial variation in self-reported health status, health-care coverage, use of preventive health-care services, health behaviors leading to chronic health conditions, and disability among U.S. adults at the state and territory, MMSA, and county levels. The findings underscore the continued need for surveillance of health-risk behaviors, chronic diseases and conditions, and the use of preventive services. Public Health Actions: Healthy People 2010 (HP 2010) objectives have been established to monitor health behaviors and the use of preventive health services. Local and state health departments and federal agencies use BRFSS data to identify populations at high risk for certain health behaviors, chronic diseases and conditions and to evaluate the use of preventive services. In addition, BRFSS data are used to direct, implement, monitor, and evaluate public health programs and policies that can lead to a reduction in morbidity and mortality.
PMID: 20134401 [PubMed - in process]
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Surveillance of certain health behaviors and conditions among States and selected local areas — behavioral risk factor…
Development and Validation of a Patient Self-assessment Score for Diabetes Risk.
Ann Intern Med. 2009 Dec 1;151(11):775-83
Authors: Bang H, Edwards AM, Bomback AS, Ballantyne CM, Brillon D, Callahan MA, Teutsch SM, Mushlin AI, Kern LM
Background: National guidelines disagree on who should be screened for undiagnosed diabetes. No existing diabetes risk score is highly generalizable or widely followed. Objective: To develop a new diabetes screening score and compare it with other available screening instruments (Centers for Disease Control and Prevention, American Diabetes Association, and U.S. Preventive Services Task Force guidelines; 2 American Diabetes Association risk questionnaires; and the Rotterdam model). Design: Cross-sectional data. Setting: NHANES (National Health and Nutrition Examination Survey) 1999 to 2004 for model development and 2005 to 2006, plus a combined cohort of 2 community studies, ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study), for validation. Participants: U.S. adults aged 20 years or older. Measurements: A risk-scoring algorithm for undiagnosed diabetes, defined as fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater without known diabetes, was developed in the development data set. Logistic regression was used to determine which participant characteristics were independently associated with undiagnosed diabetes. The new algorithm and other methods were evaluated by standard diagnostic and feasibility measures. Results: Age, sex, family history of diabetes, history of hypertension, obesity, and physical activity were associated with undiagnosed diabetes. In NHANES (ARIC/CHS), the cut-point of 5 or more points selected 35% (40%) of persons for diabetes screening and yielded a sensitivity of 79% (72%), specificity of 67% (62%), positive predictive value of 10% (10%), and positive likelihood ratio of 2.39 (1.89). In contrast, the comparison scores yielded a sensitivity of 44% to 100%, specificity of 10% to 73%, positive predictive value of 5% to 8%, and positive likelihood ratio of 1.11 to 1.98. Limitation: Data during pregnancy were not available. Conclusion: This easy-to-implement diabetes screening score seems to demonstrate improvements over existing methods. Studies are needed to evaluate it in diverse populations in real-world settings. Primary Funding Source: Clinical and Translational Science Center at Weill Cornell Medical College.
PMID: 19949143 [PubMed - in process]
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