Obse patients have greater intra-operative blood loss, more complications and longer duration of surgery but pain and functional outcome are similar to non-obse patients. Based on these results, ob*sity is not a contraindication to lumbar spinal fusion.

Obse patients have greater intra-operative blood loss, more complications and longer duration of surgery but pain and functional outcome are similar to non-obse patients. Based on these results, ob*sity is not a contraindication to lumbar spinal fusion.

A common attempted “justification” for the healthcare inequalities that fat people face is the idea that fat people shouldn’t get the resources they need if they happen to need more resources than the average thin person. When added to a general focus on profit (especially in the US healthcare system) this leads to staff-to-patient ratios that make it impossible to correctly care for fat patients (for example, having adequate staff to safely turn patients to prevent bed sores or help them ambulate to improve post-surgery outcomes.) It can also mean not having the supplies that these patients need in order to have the best outcomes. Some examples are InterDry to prevent/treat skin fold infections or Hoyer lifts so that they can use a commode and avoid bedpans and chuck changes (both of which are made more difficult and dangerous for the patient and more likely to create negative outcomes when staff-to-patient ratios don’t allow for adequate care, even if the practitioners aren’t coming from a place of weight bias.)

All of this, in turn, can create practitioner bias when they blame higher-weight patients rather than the healthcare system that is leaving both patients and practitioners without what they need.   

When healthcare facilities are allowed to decide that they don’t want to spend the money to give higher-weight people the care they need, or they are not adequately funded to do so, then higher-weight patients suffer. Here again the negative impacts of this are often simply blamed on “obsity.” For example, research on post-operative complication rates will often suggest that “obsity” causes higher complication rates without exploring the ways that these size-based healthcare inequalities may actually be at the root of any elevated rate of complications.

Weight loss is the primary recommendation for health improvement in individuals with high body mass index (BMI) despite limited evidence of long-term success. Alternatives to weight-loss approaches (such as Health At Every Size – a weight-neutral approach) have been met with their own concerns and require further empirical testing. This study compared the effectiveness of a weight-neutral versus a weight-loss program for health promotion. Eighty women, aged 30–45 years, with high body mass index (BMI ≥ 30 kg/m2) were randomized to 6 months of facilitator-guided weekly group meetings using structured manuals that emphasized either a weight-loss or weight-neutral approach to health. Health measurements occurred at baseline, post-intervention, and 24-months post-randomization. Measurements included blood pressure, lipid panels, blood glucose, BMI, weight, waist circumference, hip circumference, distress, self-esteem, quality of life, dietary risk, fruit and vegetable intake, intuitive eating, and physical activity. Intention-to-treat analyses were performed using linear mixed-effects models to examine group-by-time interaction effects and between and within-group differences. Group-by-time interactions were found for LDL cholesterol, intuitive eating, BMI, weight, and dietary risk. At post-intervention, the weight-neutral program had larger reductions in LDL cholesterol and greater improvements in intuitive eating; the weight-loss program had larger reductions in BMI, weight, and larger (albeit temporary) decreases in dietary risk. Significant positive changes were observed overall between baseline and 24-month follow-up for waist-to-hip ratio, total cholesterol, physical activity, fruit and vegetable intake, self-esteem, and quality of life. These findings highlight that numerous health benefits, even in the absence of weight loss, are achievable and sustainable in the long term using a weight-neutral approach. The trial positions weight-neutral programs as a viable health promotion alternative to weight-loss programs for women of high weight.

Former Harvard Researcher Faked Sleep Apnea Study

Posted: April 13, 2009

A former Harvard researcher has admitted falsifying a medical study. According to Boston.com, Dr. Robert Fogel has been disciplined by the Department of Health and Human Services (HHS) for faking data in a sleep apnea study funded by federal research grants.

This is the second time in recent months that a medical researcher has been caught falsifying a study. As we reported last month, medical journals have been asked to retract <"https://www.yourlawyer.com/practice_areas/defective_drugs">drug studies involving Vioxx, Celebrex, Lyrica and other drugs that were conducted by Dr. Scott S. Reuben of Baystate Medical Center.

Because of Reuben’s “research”, it had become routine for doctors to combine the use of painkillers like Celebrex and Lyrica for patients undergoing common procedures such as knee and hip replacements. Not surprisingly, Reuben has strong ties with the pharmaceutical industry. According to the Journal, he had been a paid speaker on behalf of Pfizer – the maker of Lyrica and Celebrex – and it paid for some of his research. Wyeth provided $10,000 in grant money to. Reuben from 2001 to 2003, the Journal said. Merck also funded some of Reuben’s work.

Fogel also has ties to the pharmaceutical industry. Since leaving Harvard, Fogel has been employed by Merck Research Laboratories, where he is now director of clinical research at its respiratory and allergy division in Rahway, N.J.

According to The Wall Street Journal, in 2006 Fogel apparently confessed to his former supervisor at Harvard’s Brigham and Women’s Hospital that he had falsified data in the 2003 sleep apnea study. According to the Office of Research Integrity at HHS, Fogel:

• Changed/falsified roughly half of the physiologic data
• Fabricated roughly 20% of the anatomic data that were supposedly obtained from Computed Tomography (CT) images
• Changed/falsified 50 to 80 percent of the other anatomic data
• Changed/falsified roughly 40 to 50 percent of the sleep data so that those data would better conform to his hypothesis.
• Published some of the falsified and fabricated data in an abstract in the journal Sleep in 2001.

According to Boston.com, Fogel falsified the data so that it would conform with his hypothesis. The falsified paper concluded that the shape and volume of a person’s airway combines with obesity to make those patients more likely to suffer sleep apnea.

According to the Office of Research Integrity at HHS, Fogel has entered into a voluntary disciplinary settlement, in which he agreed, among other things, to be excluded from research funded by the US Public Health Service for three years unless he is actively supervised.

Fogel told the publication The Scientist that since his admission, Harvard’s office of research integrity reviewed 30 studies in which he was involved. He told The Scientist that the 2003 sleep apnea study was the only one that included fake data.

“What I did was obviously horrendously wrong,” Fogel told the magazine. “I never really thought through the consequences, and once I did this I got myself into a loop that I found I couldn’t get out of.”

large gowns and seatbelt extenders (and rainbow umbrellas!)

Using an ethical lens, this review evaluates two methods of working within patient care and public health: the weight-normative approach (emphasis on weight and weight loss when defining health and well-being) and the weight-inclusive approach (emphasis on viewing health and well-being as multifaceted while directing efforts toward improving health access and reducing weight stigma). Data reveal that the weight-normative approach is not effective for most people because of high rates of weight regain and cycling from weight loss interventions, which are linked to adverse health and well-being. Its predominant focus on weight may also foster stigma in health care and society, and data show that weight stigma is also linked to adverse health and well-being. In contrast, data support a weight-inclusive approach, which is included in models such as Health at Every Size for improving physical (e.g., blood pressure), behavioral (e.g., binge eating), and psychological (e.g., depression) indices, as well as acceptability of public health messages. Therefore, the weight-inclusive approach upholds nonmaleficience and beneficience, whereas the weight-normative approach does not. We offer a theoretical framework that organizes the research included in this review and discuss how it can guide research efforts and help health professionals intervene with their patients and community.

Weight stigma is likely to drive weight gain and poor health and thus should be eradicated. This effort can begin by training compassionate and knowledgeable healthcare providers who will deliver better care and ultimately lessen the negative effects of weight stigma.

Not fat-friendly but at least weight-neutral.

Surprising no one who has ever listened to a fat, Black or brown, or chronically ill person:

Researchers who study Type 2 diabetes have reached a stark conclusion: There is no device, no drug powerful enough to counter the effects of poverty, pollution, stress, a broken food system, cities that are hard to navigate on foot and inequitable access to health care, particularly in minority communities.

“Healthy lifestyle habits are associated with a significant decrease in mortality regardless of baseline body mass index.”

The other manipulation of significant is a misuse of the concept of “statistical significance.” When a study looks at an intervention’s outcomes and find that those outcomes are “statistically significant” it simply means that it is more likely that the outcomes are a result of the intervention than that they were the result of chance. So if a study had a statistically significant finding that people using some weight loss method lost 3% of their body weight, that would mean that it was more likely that the small amount of weight loss was due to the weight loss method than that it was by chance. However, if the study conclusion were to say that people lost a “significant amount of weight” when what they meant was that the weight loss was statistically significant, they might mislead people into thinking that “significant” in this case meant “a lot of” weight.