Type 2 Diabetes Could Be a Cause of Erectile Dysfunction


Type 2 diabetes may be a causal factor in the development of erectile dysfunction (ED), with insulin resistance a likely mediating pathway, results of a large-scale genomic analysis suggest. The data also uncovered a genetic locus linked to ED.

Jonas Bovijn, MD, DPhil, Big Data Institute at the University of Oxford, United Kingdom, and colleagues gathered data on more than 220,000 men across three cohorts, of whom more than 6000 had ED.

The researchers initially showed that a region on chromosome 6 is linked to the development of ED. The location suggested that the condition is associated with dysregulation of the hypothalamus.

Next, they performed a Mendelian randomization analysis, which examined the relationship between gene mutations known to be associated, in this case, with cardiometabolic factors and the outcome of ED.

The research, published online December 20 in the American Journal of Human Genetics, showed that a genetic predisposition to type 2 diabetes increased the risk for ED. The risk was driven primarily by susceptibility to insulin resistance.

Bovijn said in a release: “We know that there is observational evidence linking erectile dysfunction and type 2 diabetes, but until now there has not been definitive evidence to show that predisposition to type 2 diabetes causes erectile dysfunction.”

“Further research is needed to explore the extent to which drugs used in the treatment of type 2 diabetes might be repurposed for the treatment of ED,” the team notes.

Co–senior author Anna Murray, PhD, University of Exeter Medical School, United Kingdom, said in the release that “until now little has been known” about the cause of ED.

Previous studies have suggested there is a genetic basis for ED. The new study goes further by demonstrating that a genetic predisposition to type 2 diabetes is linked to ED, according to Murray.

“That may mean that if people can reduce their risk of diabetes through healthier lifestyles, they may also avoid developing erectile dysfunction,” she said.

Michael Holmes, MD, PhD, of the Nuffield Department of Population Health at the University of Oxford, who was one of the senior authors, agreed.

“Our finding is important, as diabetes is preventable, and indeed one can now achieve ‘remission’ from diabetes with weight loss, as illustrated in recent clinical trials.

“This goes beyond finding a genetic link to erectile dysfunction to a message that is of widespread relevance to the general public, especially considering the burgeoning prevalence of diabetes,” Holmes said.

Large Studies Key

Although the prevalence of ED is known to increase with age, rising to 20% to 40% among men aged 60 to 69 years, the genetic architecture of the condition remains poorly understood. This is at least in part due to a lack of well-powered studies.

The researchers therefore conducted a genome-wide association study (GWAS) using data on 199,362 individuals from the UK Biobank cohort and 16,787 people from the Estonian Genome Center of the University of Tartu (EGCUT) cohort, both of which are population based.

In addition, they included information on 7666 participants in the hospital-recruited Partners HealthCare Biobank (PHB) cohort.

The prevalence of ED, which was determined on the basis of self- or physician-reported ED, the use of oral ED medication, or a history of ED surgical intervention, was 1.53% in the UK Biobank, 7.04% in EGCUT, and 25.35% in PHB.

The researchers believe that the difference in prevalence rates between the cohorts may relate to the older average age for men in PHB, at 65 years, vs 59 years in the UK Biobank and 42 in EGCUT. In addition, the prevalence in the UK Biobank cohort may have been affected by a “healthy volunteer” selection bias and a lack of primary care data.

GWAS on the UK Biobank data indicated that there was a single genome-wide significant locus at 6q16.3 between the MCHR2 and SIM1 genes, with rs57989773 the lead variant.

Pooled meta-analysis of the combined cohorts indicated that rs57989773 was associated with ED at an odds ratio of 1.20 per C-allele (P = 5.71 × 10-14).

Synthesizing previous research on SIM1, which is highly expressed in the hypothalamus, in both human and rodent models, the team found that rs57989773 is associated with syncope, orthostatic hypotension, and urinary incontinence.

Moreover, the common risk variant for ED at 6q16.3 is linked to blood pressure and adiposity, as well as male sexual behavior in mice.

The researchers, therefore, suggest that a potential mechanism for the effect of the MCHR2-SIM1 locus on ED could be the hypothalamic dysregulation of SIM1.

The team also performed Mendelian randomization analyses to examine the potential causal role of cardiometabolic traits in ED risk.

Factors included type 2 diabetes, insulin resistance, systolic blood pressure (SBP), low-density lipoprotein (LDL) cholesterol levels, smoking heaviness, alcohol consumption, body mass index, coronary heart disease, and educational attainment.

The analysis revealed that type 2 diabetes was causally implicated in ED, with the risk for ED increased 1.11-fold with each 1-log higher genetic risk for type 2 diabetes (P = 3.5 × 10-4).

Insulin resistance was found to be a likely mediating pathway for the relationship, with an odds ratio for ED of 1.36 per 1 SD genetic increase in insulin resistance (P = .042).

SBP also had a causal effect on ED risk, at an odds ratio of 2.34 per 1 SD increase in SBP (P = .007).

LDL cholesterol was found to have a minor impact on the risk for ED, at an odds ratio of 1.07 per 1 SD increase in levels (P = .113). There was no association between ED and either smoking heaviness or alcohol use.

Source:Medscape.com

Why BMI is a Big Fat Scam


Story at-a-glance

  • Body mass index (BMI), a formula that divides your weight by the square of your height, is one of the most commonly used measures of overweight, obesity, and overall health
  • Initially, BMI was primarily a tool used by insurance companies to set premiums (people with BMIs in the “obese” category may pay 22 percent more for their insurance compared to those in the “normal” category
  • BMI is a flawed measurement tool, in part because it uses weight as a measure of risk, when it is actually a high percentage of body fat that increases your disease risk
  • BMI also tells you nothing about where fat is located in your body, and the location of the fat, particularly if it’s around your stomach (visceral fat), is more important than the absolute amount of fat when it comes to measuring certain health risks
  • Your waist-to-hip ratio is a more reliable indicator of your future disease risk because a higher ratio suggests you have more visceral fat.

 

BY DR. MERCOLA

In 1832, a Belgian mathematician named Adolphe Quetelet developed what is today known as the body mass index (BMI).1The formula divides a person’s weight by the square of his height, and is one of the most commonly used measures of excess weight, obesity, and overall health.

Initially, BMI was primarily a tool used by insurance companies to set premiums (people with BMIs in the “obese” category may pay 22 percent more for their insurance compared to those in the “normal” category2).

Today, however, BMI is an accepted tool used in medical research and in clinical practice. When you have your height and weight recorded at your doctor’s office, it will give him or her an automatic calculation of your BMI, classifying you as underweight if your BMI is below 18.5, normal if it’s 18.5-24.9, overweight if it’s 25-29.9, and obese if it’s 30 or over.

Your doctor may use this number to advise you on your weight, as well as your risk of related conditions like heart disease, high blood pressure, and type 2 diabetes. Unfortunately, BMI is an incredibly flawed tool, and a high BMI doesn’t automatically mean you’re unhealthy, the way many physicians and health insurance companies imply that it does.

The Obesity Paradox: Sometimes Higher BMI Is Healthier

Research involving data from nearly 3 million adults suggests that a having an overweight BMI may be linked to a longer life than one that puts you within a “normal” weight range.

The research, which analyzed 97 studies in all, found that people with BMIs under 30 but above normal (the overweight range) had a 6 percent lower risk of dying from all causes than those who were normal weight, while those whose BMIs fell into the obese range were 18 percent more likely to die of any cause.3

Separate research published in the Journal of the American College of Cardiology, also found that a high BMI was associated with a lower risk of death, a phenomenon known as the “obesity paradox.”4

Indeed, it is quite possible to be overweight and healthy, just as it’s possible to be normal weight and unhealthy. And in some cases, it may, in fact, be healthier to carry a few extra pounds. In a Journal of the American Medical Association (JAMA)editorial, Steven Heymsfield, M.D. and William Cefalu, M.D. explained:5

“The presence of a wasting disease, heart disease, diabetes, renal dialysis, or older age are all associated with an inverse relationship between BMI and mortality rate, an observation termed the obesity paradox or reverse epidemiology. 

The optimal BMI linked with lowest mortality in patients with chronic disease may be within the overweight and obesity range. 

Even in the absence of chronic disease, small excess amounts of adipose tissue may provide needed energy reserves during acute catabolic illnesses, have beneficial mechanical effects with some types of traumatic injuries, and convey other salutary effects that need to be investigated in light of the studies…” 

However, for the vast majority of those who carry around extra pounds, health problems will often result. So why would these studies suggest otherwise? They are likely examples of why BMI is such a flawed tool for measuring your health.

Makers of Weight Loss Drugs Altered BMI Categories, Making 29 Million Americans ‘Overweight’

BMI is used as the measure of national obesity rates, which currently stand at close to 35 percent for adults and 18 percent for kids. However, the cut-off for classifying a person as normal or overweight seems to be quite arbitrary – and at one point was significantly modified by a task force funded, primarily, by companies making weight loss drugs. Mother Jones reported:6

“In 1998, the National Institutes of Health lowered the overweight threshold from 27.8 to 25—branding roughly 29 million Americans as fat overnight—to match international guidelines. 

But critics noted that those guidelines were drafted in part by the International Obesity Task Force, whose two principal funders were companies making weight loss drugs. 

In his recent book ‘Fat Politics: The Real Story Behind America’s Obesity Epidemic,’ political scientist Eric Oliver reports that the chairman of the NIH committee that made the decision, Columbia University professor of medicine Xavier Pi-Sunyer, was consulting for several diet drug manufacturers and Weight Watchers International.”

BMI Uses Weight, Not Body Fat, to Measure Risk

Branding yourself as unhealthy or overweight simply based on your BMI is not recommended (unfortunately, your insurance company probably won’t see it this way). On the other hand, assuming you’re healthy just because your BMI is normal isn’t advised either.

Research suggests BMI may underestimate obesity rates and misclassify up to one-quarter of men and nearly half of women.7 According to researcher Dr. Eric Braverman, president of the nonprofit Path Foundation in New York City:8

“Based on BMI, about one-third of Americans are considered obese, but when other methods of measuring obesity are used, that number may be closer to 60%.”

One of the primary reasons why BMI is such a flawed measurement tool is that it uses weight as a measure of risk, when it is actually a high percentage of body fat that increases your disease risk. Your weight varies according to the density of your bone structure, for instance, so a big-boned person may weigh more, but that certainly doesn’t mean they have more body fat or make them more prone to heart disease, for example.

Athletes and completely out-of-shape people can also have similar BMI scores, or a very muscular person could be classified as “obese” using BMI, when in reality it is mostly lean muscle accounting for their higher-than-average weight. BMI also tells you nothing about where fat is located in your body, and it appears that the location of the fat, particularly if it’s around your stomach, is more important than the absolute amount of fat when it comes to measuring certain health risks, especially heart disease.

Waist-to-Hip Measurement Is Superior to BMI, But Only 10 Percent of Physicians Use It

Your waist-to-hip ratio is a more reliable indicator of your future disease risk because a higher ratio suggests you have more visceral fat. Excess visceral fat—the fat that accumulates around your internal organs — is far more hazardous to your health than subcutaneous fat (the more noticeable fat found just under your skin) – a measure that BMI tells you nothing about. The danger of visceral fat is related to the release of proteins and hormones that can cause inflammation, which in turn can damage arteries and enter your liver, and affect how your body breaks down sugars and fats.

Unfortunately, according to Donna Ryan, a physician who has trained thousands of primary-care doctors in obesity screening, only about 10 percent use waist circumference as a health indicator. She told Mother Jones:9 “Doctors are so pressed for time… And it’s intrusive. You have to put your arms around the patient.” To determine your waist-to-hip ratio, get a tape measure and record your waist and hip circumference. Then divide your waist circumference by your hip circumference. For a more thorough demonstration, please review the video above.

Waist to Hip Ratio Men Women
Ideal 0.8 0.7
Low Risk <0.95 <0.8
Moderate Risk 0.96-0.99 0.81 – 0.84
High Risk >1.0 >0.85

How Much You Exercise Also Predicts Your Disease Risk

Your fitness level is also a far better predictor of mortality than your BMI. One study found that people who rarely exercised had a 70 percent higher risk of premature death than those who exercised regularly, independent of their BMI.10 If you want a simple test to gauge your fitness level, try the abdominal plank test (for a demonstration of how to do a plank, see the video below. If you can hold an abdominal plank position for at least two minutes, you’re off to a good start. If you cannot, you’re likely lacking in core strength, which is important for overall movement stability and strength.

A strong core will also help prevent back pain. Being unable to hold a plank for two minutes may also indicate that you’re carrying too much weight and would benefit from shedding a few pounds. Unfortunately, over 50 percent of American men, and 60 percent of American women, never engage in any vigorous physical activity lasting more than 10 minutes per week.11 This despite a growing body of research clearly showing that “exercise deficiency” threatens your overall health and mental well-being, and shortens your lifespan.

In fact, according to research published in the American Journal of Physiology, the best way to stay young is to simply start exercising, as it triggers mitochondrial biogenesis, a decline of which is common in aging.12 Researchers have also suggested that exercise is “the best preventive drug” for many common ailments, from psychiatric disorders to heart disease, diabetes, and cancer.13 According to Jordan Metzl, a sports-medicine physician at New York City’s Hospital for Special Surgery and author of The Exercise Cure: “Exercise is the best preventive drug we have, and everybody needs to take that medicine.”

So rather than stressing over an arbitrary number like your BMI, you’d be better served by coming up with a comprehensive fitness plan. I recommend incorporating high-intensity interval training (HIIT)strength training (including super slow), core exercises, stretching, and non-exercise activity into your routine. The key is to simply get moving, and work at a high enough intensity with enough variance to keep your muscles adequately challenged.

Every person is different, so there’s not just one “correct” way to exercise. Equally, if not more, important is incorporating regular intermittent movement into your day, as this will help to counteract some of the effects excess sitting has on your body. If you exercise correctly and keep moving throughout your day, and combine it with a healthy eating program, you will optimize your body-fat percentage naturally, and with it gain a predisposition for optimal health.

Weight Affects Survival in Cervical Cancer


Overweight and underweight women with cervical cancer did not live as long as their normal-weight counterparts, according to the results of a retrospective cohort study.

The median overall survival time in overweight/obese women was 6 months shorter than in women of normal weight (22 versus 28 months). For underweight women, median overall survival time was cut in half (14 versus 28 months), reported Leslie Clark, MD, of the University of North Carolina at Chapel Hill, and colleagues.

Being overweight or underweight, as determined by body-mass index (BMI), was also associated with worse recurrence-free survival and disease-free survival, Clark and colleagues said in Gynecologic Oncology.

“In understanding the effect of BMI on cervical cancer outcomes, it is important to recognize that both extremes of weight appear to negatively impact survival. Optimizing weight in cervical cancer patients may improve outcomes in these patients.”

The study included 632 women diagnosed with cervical cancer and treated at the university from 2000 to 2013. Their BMI was calculated using height and weight measurements taken at initial presentation to the oncology clinic. Four percent of the women were underweight (n=24), 30% were normal weight (n=191), and 66% were overweight or obese (n=417).

The investigators looked for connections between BMI at time of presentation and survival, controlling for factors including age, race, smoking, cancer stage, tumor grade, and histology.

Being overweight or obese was associated with significantly reduced median overall survival time compared with normal weight (22 versus 28 months; P=0.031). For underweight women, the reduced survival time was more dramatic (14 versus 28 months;P=0.018).

Compared with for normal-weight women, median recurrence-free survival time was also significantly shorter in obese/overweight women (7.6 versus 25 months; P=0.009) and in underweight women (20 versus 25 months; P=0.026).

There was a borderline-significant trend toward worse disease-specific survival in overweight/obese women compared with those of normal weight (22 versus 28 months; P=0.089). For underweight women, the difference was significant (14 versus 28 months; P=0.042).

Potential Underlying Mechanisms

“A potential unifying hypothesis connecting both extremes of weight to poor cancer prognosis is chronic systemic inflammation,” Clark and colleagues wrote. “Both patients with cancer cachexia/sarcopenia and overweight/obese patients are in a heightened inflammatory state, which may lead to increased cell proliferation and inhibition of apoptosis.

“However, this is likely not the only mechanism of poor outcomes. Co-morbid medical conditions might account for some of the differences in survival, particularly in morbidly obese patients.”

 Limitations of the study included its retrospective nature and the fact that all patients were treated at a single institution, which means the results may not be broadly generalizable, the investigators said.

“This study shows that the extremes of weight are detrimental to survival in women with cervical cancer, and further investigation regarding the cause of poor prognosis is warranted. Providers should optimize weight in underweight and overweight/obese patients to attempt to improve outcomes in these women. Interventions that target nutritional counseling and physical activity should be explored in these populations,” Clark and colleagues concluded.

Corroborating Evidence

A similar study presented at the recent Society of Gynecologic Oncology meeting corroborates the results of Clark et al.

That study, conducted by Aida Moeini, MD, of the University of Southern California, Los Angeles, and colleagues, examined the effect of weight change over time on disease-free survival rates in 665 women with endometrial cancer.

At 5 years, disease-free survival had fallen well below 50% for women who had either lost or gained 15% or more of their body mass. For women in the smallest weight-change category, those who had lost or gained less than 7.5% of body mass, disease-free survival was about 80%, Moeini and colleagues reported.

“Our results demonstrated that endometrial cancer patients continued to gain weight after hysterectomy, and post-treatment weight change had a bi-directional effect on survival outcome.”

Waist Circumference May Be More Accurate Method Of Predicting Heart Health Than Body Mass Index


New research presented this weekend at the American College of Cardiology’s Annual Scientific Session may add more fuel to the fire concerning the reliability of body mass index (BMI) as a precise measure of health.

The study authors reanalyzed data they obtained from an earlier randomized trial of 200 Type 2 diabetes patients with relatively healthy hearts who were given intensive CT screening in hopes of preventing future heart disease. This time around, the researchers examined whether their patients’ waist circumference had any relationship to their risk of future heart disease. They did the same calculation for BMI as well as body weight. After controlling for all other factors, the authors found that waist circumference consistently served as a better predictor of heart function over the other two.

“This study confirms that having an apple-shaped body — or a high waist circumference — can lead to heart disease and that reducing your waist size can reduce your risks,” said senior author Dr. Brent Muhlestein, a co-director of research at the Intermountain Medical Center Heart Institute in Salt Lake City, in a statement.

In an interview with Medical Daily, Muhlestein explained that his team, comprised of researchers from Intermountain as well as Johns Hopkins Hospital in Baltimore, was already well prepared to look at the connection.

“It has been proposed for some time that intra-abdominal fat may be more inflammatory and may contribute more to atherosclerosis progression than other forms of fat,” he said. “Therefore we measured abdominal circumference, which is a good surrogate marker for intra-abdominal fat, in all our patients.” And because the patients who received CT scans were also given a relatively new test called speckle tracking echocardiography, Muhlestein’s team was able to directly measure heart muscle function as well.

The study is only the latest to find that a person’s body shape, more so than their weight or BMI, can provide doctors with a clearer picture of their health. Other research has concluded that people with an apple-shaped body have a greater risk of disordered eatingfractures, andkidney disease when compared to those with similar BMI but a so-called pear-shaped body.

According to Muhlestein, while most obese people also tend to have higher than healthy levels of belly fat, our continuing reliance on BMI and weight alone may be leading doctors to miscategorize the cardiovascular health of many patients — not only those who are overweight, but also “skinny fat” people with a seemingly healthy BMI. “Based on my prior research and study of other trials, I estimate that more than 20 percent of patients might have a ‘reclassification’ of their cardiovascular risk if their waist circumference was measured along with their overall weight,” he said. The number of patients in the current study was too small, however, to determine if that could be the case here.

Regardless, if more research continues to affirm this connection, Muhlestein believes it may soon spark a change in how doctors determine disease risk. “If this trend holds, clinicians will need to begin measuring waist circumference on patients as an important vital sign,” he said.

Rather than simply supplanting BMI, though, the measure should be seen as an another instrument in the doctor’s toolkit. “The major way that I can see abdominal waist circumference being useful at present is that it can show which patients, among all overweight ones, are especially at risk and therefore should be especially vigilant,” he said. While all overweight people can benefit from lifestyle interventions like diet and exercise, he added, people with excess belly fat may need treatments that aggressively manage their blood pressure, cholesterol, and blood glucose levels to remain healthy.

Less certain for the time being is exactly why this sort of fat seems to be especially dangerous not only to our arteries but to the heart.

“We were actually somewhat surprised to see that heart muscle function was found to be related to waist circumference,” he said. “At present we don’t have any idea why intra-abdominal fat, more so than fat from anywhere else, can affect heart function in the absence of prior myocardial infarction.”

Muhlestein and his colleagues are now trying to devise studies that can definitively get to the root of that lingering question, and they plan to keep tabs on the study patients to see if their predictions hold true as well.

Exercise Helps Menopause Symptoms and Quality of Life


Middle-aged women who exercise regularly report a higher quality of life and reduced symptoms of menopause, according to a population-based study published in the January 2015 issue of Maturitas.

“Women with the recommended level of physical activity had a higher self-perceived health level, better relative health, and better global quality of life in relation to other women their age,” write Kirsi Mansikkamäki, MSc, from the UKK Institute for Health Promotion, Tampere, Finland, and colleagues.

The investigators surveyed 2606 women from Finland’s population registry, representing a 52% response rate from an original random sample of 5000 women. All were born in 1963, making them 49 years old at the time of the study. Of those, 28% were still menstruating regularly, 31% were perimenopausal, and 23% had not menstruated in the past 12 months. The menopausal status of the other 18% could not be determined because they were taking hormone replacement therapy.

The questionnaire, delivered by mail, included a shortened form of the Women’s Health Questionnaire with questions about quality of life and perceived health, body mass index, education, and physical activity. Half had a body mass index below 25 kg/m2 and were considered to be of normal weight.

The researchers considered women to be physically active if they met the recommended 2.5 hours per week of moderate activity (eg, fast-paced walking) or 1.25 hours of vigorous activity (such as jogging or running), and if they also did any strength or balance training at least twice a week. Just more than half of the participants (51%) met the definition of being physically active.

The less-active women were more likely to score highly for anxiety or depressed mood (proportional odds ratio [POR], 1.44; 95% confidence interval [CI], 1.26 – 1.65), somatic symptoms not counting vasomotor symptoms (POR, 1.61; 95% CI, 1.40 – 1.85), and memory and concentration problems (POR, 1.48; 95% CI, 1.29 – 1.70). Vasomotor symptoms, or hot flashes, were more common in less-active women before adjusting for body mass index and education, but after these calculations, they were not statistically significant.

Overall, the more active women had greater self-perceived health (adjusted POR, 3.22; 95% CI, 2.76 – 3.74) and global quality of life (adjusted POR, 1.91; 95% CI, 1.65 – 2.20) compared with other women their age.
Writing in an accompanying editorial, Debra Anderson, PhD, and Charlotte Seib, PhD, both from the Institute of Health and Biomedical Innovation at the Queensland University of Technology in Brisbane, Australia, note that studies on the effects of exercise on symptoms of menopause have been inconsistent. They suggest several possibilities. One is that some women who engage in less than the recommended amount of exercise may still see some benefits, causing the observed effect of exercise to be smaller than it really is. Another is that women experiencing more severe symptoms, whether physical or mental, may be less likely to engage in exercise.

Still, they write, “[t]he emerging evidence that exercise may now be seen as a useful intervention strategy for the alleviation of menopausal symptoms provides health professionals, with a new intervention for use in the care of menopausal women.”

Public Transportation Commutes May Be Long, But They Promote Better Health In Americans: The Health Consequences Of Driving


Whether you walk, cycle, take public transportation, or drive your way to work, most people dread their morning commute that adds up to 25.5 minutes each way for the average American. UK researchers from the University of London weighed out the benefits of commuting to work and published their findings in The British Medical Journal on Tuesday.

Driving To Work Has A List Of Health Consequences

Health repercussions, both good and bad, come from commuting, but research has proven time and again when people drive to work every day, they tend to gain more weight than those who choose an alternative route. There’s a significant difference in the health between commuters who weave their way through traffic and those who hitch a ride on the subway line. What is it about driving for hours every day through traffic that harms our physical and mental health?

Researchers analyzed 7,534 participants from the United Kingdom Household Longitudinal Study and found correlations with how they commute to work and their body mass index (BMI) and body fat percentage. A large majority of men and women commute to work through private motor vehicle transportation, with a total of 76 percent of men, and 72 percent of women, respectively. Compare that to the 10 percent of men and 11 percent of women who report using public transportation on a daily basis, and it starts to make sense how the country is experiencing an obesity epidemic and environmental crisis with carbon monoxide pollution from vehicles.

Women who commuted through any mode of transportation besides a private vehicle had a BMI score 0.7 lower than drivers, and they weighed 5.5 pounds less than the average woman. Non-car commuting men were an entire 1.0 lower than their counterparts and weighed 6.6 pounds less than the average man. BMI is a commonly used scale to evaluate the health range a man or woman falls into depending on their height and weight. Generally, a person with a BMI of 18.5 to 24.9 is within healthy range, while a person lower than 18.5 indicates they’re underweight and any number above 25 indicates a person may be overweight, and above 30 indicates obesity.

Aside from commute-related weight gain, traffic can be stressing, your neck can be straining, and you’re stuck in a seated position that can be hurting your spine. Driving just 10 miles or more each way to work is associated with high blood sugar and high cholesterol, according to a study published in the American Journal of Preventive Medicine. High blood glucose levels can lead to pre-diabetes and diabetes. Those same commuters are also more susceptible to depression, anxiety, and social isolation, along with lower levels of cardiovascular fitness and physical activity.

Commuting by car may be faster and easier than grabbing a bike or aligning your schedule up with the local bus route, but it’s the long-term health risks commuters must keep in mind. The short-term oftentimes does not outweigh the long-term risks and benefits, especially when convenience comes into play. If you work over an hour away, try going for a 10-minute walk or run to clear your mind and prepare your body for the sedentary ride you have ahead of you. Before you head home from work, find a gym at your mid-way point and release some tension and awaken your muscles with 30 to 60 minutes of well-deserved exercise.

Researchers said the differences between people who drove their car every day and people who took alternative routes, were “larger than those seen in the majority of individually focused diet and physical activity interventions to prevent overweight and obesity.” If communities and cities made alternative routes more accessible for commuters to get to work each day, obesity prevention campaigns could encourage people to choose healthier routes. “It is crucial that the public health community, including health care professionals, provide strong and consistent messages to politicians and the public, which frame these measures as positive public health actions,” researchers said.

Obesity has rapidly plagued the world over the last 30 years, and although intervention strategies are being implemented in small ways every day, there are still 34.9 percent of obese American adults living today and a growing number of obese children, according to the Centers for Disease Control and Prevention. Walking, cycling, and public transportation “should be considered as part of strategies to reduce the burden of obesity and related health conditions,” the authors wrote. “[Further research] is required in order to confirm the direction of causality in the association between active commuting and body weight.”

Source: Sacker A. Associations between active commuting, body fat, and body mass index: population based, cross sectional study in the United Kingdom. The British Medical Journal. 2014.

How Early Should Obesity Prevention Start?


Obesity has pervaded the United States and is spreading throughout the world. Following in its wake is type 2 diabetes, which will affect at least half a billion people worldwide by 2030. A majority of U.S. women of childbearing age are overweight or obese (as defined by a body-mass index [BMI, the weight in kilograms divided by the square of the height in meters] >25). These women are likely to gain excessive weight when they’re pregnant, making it harder for them to return to their prepregnancy weight after delivery. Postpartum weight retention not only portends increased lifelong risks for obesity-related complications but also an increased BMI at the inception of future pregnancies. During pregnancy, excessive weight gain, along with other risk factors such as gestational diabetes, can alter fetal growth and metabolism, leading to higher adiposity in the offspring. If the child is female, grows up obese, and becomes pregnant, the cycle begins again. It is time to interrupt this vicious cycle to prevent obesity and chronic diseases in mothers and children.

Once obesity is present, it is challenging to treat because of multiple physiological, behavioral, and cultural feedback loops. The good news is that the prenatal period and the first postnatal year hold critical clues that may lead to interventions to reduce obesity in women and prevent it in children. In a range of animal models (from rodents to nonhuman primates), dietary, hormonal, mechanical, and other perturbations that occur prenatally and during infancy induce lifelong, often irreversible derangements in the offspring’s adiposity and metabolism. These changes involve the environmental alteration of genetic expression, in part through epigenetic mechanisms, rather than changes in the genome itself. Thus, timely intervention during the early, plastic phases of development — unlike corrective efforts made later in life — may lead to improved lifelong health trajectories.

Because of challenges in measuring fetal exposures and the long latency between initial determinants and salient health outcomes, however, it is difficult to translate such proofs of principle in animals to human populations. The first generation of developmental-origins studies in humans linked birth weight to adult obesity-related morbidity and mortality. We now recognize that birth weight and each of its components, gestational duration and fetal growth, are low-resolution, momentary markers for myriad prenatal and perinatal influences. In the past decade, many such influences have been identified and quantified in epidemiologic studies that have involved the period before birth, used modern methods to mitigate confounding, and incorporated biomarkers. These studies have identified prenatal risk factors for obesity ranging from lifestyle factors such as the mother’s smoking status to psychosocial factors including antepartum depression, medical conditions such as gestational diabetes, physiological stress as reflected by fetal exposure to glucocorticoids, and epigenetic markers such as gene-specific DNA methylation levels in umbilical-cord tissue.

After birth, rapid weight gain in the first 3 to 6 months of life is a potent predictor of later obesity and cardiometabolic risk. Lactation cannot be the entire explanation, because breast-fed babies tend to gain more weight than formula-fed babies in the first few months of life. The perinatal hormonal milieu may very well be a contributing factor. In one study, higher leptin levels in umbilical-cord blood, chiefly reflecting placental production, were associated with slower gain in infant weight-for-length and lower adiposity at the ages of 3 years and 7 years. In contrast, higher leptin levels at 3 years of age were associated with faster gains in BMI from 3 to 7 years, suggesting that leptin resistance develops between birth and 3 years of age.1 These findings are consistent with studies in animals showing a critical period of perinatal leptin exposure that allows normal maturation of appetite-regulating neurons in the hypothalamus. Features of infant feeding other than breast versus bottle may also play a role. Among formula-fed infants, the introduction of solids before 4 months was associated with a sixfold increase in the odds of obesity 3 years later.2

Emerging risk factors for obesity include exposure to endocrine disruptors, which appear to do the most damage during times of maximum developmental plasticity, and the gut microbiota. Our bodies contain about 1013 cells but as many as 1014 microorganisms. Certain modifications in the number and type of microorganisms during infancy are associated with excess weight gain, at least in rodents. The infant gut is normally colonized during transit through the birth canal, which could be one reason why children delivered by cesarean section appear to be at elevated risk for obesity.3

Given obesity’s numerous developmental determinants, it is logical that effective prevention would target multiple modifiable factors. In combination, two well-studied prenatal risk factors, excessive gestational weight gain and maternal smoking during pregnancy, and two postnatal factors, fewer months of breast-feeding and a shorter duration of daily sleep during infancy, are associated with wide variation in childhood obesity. In one study, preschool-age children whose mothers did not smoke or gain excessive weight during pregnancy and who were breast-fed for at least 12 months and slept for at least 12 hours per day during infancy had a predicted obesity prevalence of 6%, as compared with 29% among children for whom the opposite was true for all four risk factors4; the rates were similar (4% and 28%, respectively) when the children reached 7 to 10 years of age (see graphPredicted Probability of Obesity at 7 to 10 Years of Age for 16 Combinations of Four Modifiable Prenatal and Postnatal Risk Factors.). These observational data raise the possibility that avoiding some or all of these risk factors could substantially reduce the proportion of childhood obesity.

Preventing racial and ethnic disparities in obesity risk will also require a developmental approach. By school age, rates of obesity among black and Hispanic children in the United States are higher than the rates among white children, even after adjustment for socioeconomic circumstances. Many of the risk factors during pregnancy and early childhood are more prevalent among nonwhite persons, and they explain a substantial proportion of racial and ethnic differences in obesity in mid-childhood.5

Several features of pregnancy and infancy make the prenatal and postnatal periods conducive to behavior change to reduce the risk of obesity and its complications. First, women appear especially willing to modify their behavior during these periods to benefit their children. Second, since pregnant women and infants receive frequent routine medical care, interventions involving improved health care delivery have great potential. Third, these periods are relatively brief, and we know that behavior-change interventions are typically most successful in the short term. Fourth, if effective interventions begun during pregnancy are maintained after birth, they will reduce the risk of maternal obesity for future pregnancies and thus help to interrupt the intergenerational cycle.

Ongoing intervention studies promise to inform medical practice and public health. Many current trials target excessive gestational weight gain, including seven randomized, controlled trials funded by the National Institutes of Health that will together include more than 1000 overweight or obese women and follow infants through at least 1 year of age. It remains to be proven, however, that reducing gestational weight gain reduces the obesity risk in offspring. An alternative approach focuses on dietary quality, independent of calorie content, to ameliorate maternal insulin resistance and excessive placental nutrient transfer. Pilot studies have suggested that a multiple-risk-factor approach during infancy, targeting mothers as conduits for changes in their infants, can improve sleep duration and delay the introduction of solid foods.

But even as we await the results of obesity-prevention trials, some recommendations are warranted because of their beneficial effects on other health outcomes. Pregnant women should not smoke. Treatment of gestational diabetes reduces macrosomia at birth, although such treatment hasn’t been proven to prevent obesity. U.S. rates of elective cesarean sections have apparently leveled off, but reducing these rates, especially of cesarean sections performed before 39 weeks of gestation, is a public health goal. Simple sleep-hygiene measures are worth trying, even in early infancy. The ideal age, in terms of allergy prevention, for introducing solid foods appears to be 4 to 6 months, and further research may show that the same is true in terms of obesity prevention.

 

Source: NEJM

BMI may be most vital determinant of basal metabolic rate in PCOS.


The BMI of patients with polycystic ovary syndrome appeared to be the most important factor in basal metabolic rate, independent of the polycystic ovary syndrome phenotype and insulin resistance, according to Margareta D. Pisarska, MD, who presented the data at the conjoint meeting of the International Federation of Fertility Societies and the American Society for Reproductive Medicine.

“Based on our study — since we do think obesity does play a significant role — we believe it is important for endocrinologists to help counsel these women in a fashion similar to those who are obese by emphasizing that weight loss and lowering BMI are important,” Pisarska, director of the division of reproductive endocrinology and infertility; director of the Fertility and Reproductive Medicine Center at Cedars-Sinai Medical Center; associate professor at Cedars-Sinai Medical Center and the David Geffen School of Medicine at UCLA, told Endocrine Today.

 

The researchers conducted the case-control study examining the metabolic changes (ie, lean body mass, body fat mass, body fat percentage, skeletal muscle mass, BMI and basal metabolic rate) in 128 patients with PCOS (mean age, 28.1 years) and 72 eumenorrheic, non-hirsute controls (mean age, 32.9 years).

In terms of hormonal profile, patients with PCOS had greater testosterone, dehydroepiandrosterone sulfate (DHEA-sulfate), fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR) levels compared with controls.

After controlling for age and BMI differences, there was no difference in body composition parameters between patients with PCOS and controls. There were no significant results regarding changes to the basal metabolic rate (P=.0162), lean body mass (P=.0153) or skeletal muscle mass (P=.0169), she said.

However, differences in fasting insulin and HOMA-IR remained significant. When looking at insulin resistance in women with PCOS as a potential factor affecting body composition and metabolic rates, there was also no difference between these groups.

“It is not necessarily PCOS; BMI and age are probably the more important determinants of basal metabolic rate, regardless of PCOS phenotype and insulin resistance,” Pisarska said.

Phentermine-topiramate reduced incident type 2 diabetes by nearly 80%.


Patients with prediabetes and/or metabolic syndrome demonstrated significant weight loss and a markedly reduced progression to type 2 diabetes after 2 years of treatment with phentermine-topiramate extended-release plus lifestyle modifications, according to data published in Diabetes Care.

The medically assisted weight-loss intervention was highly effective in preventing diabetes among high-risk patients by 78.7%, W. Timothy Garvey, MD, chairman of the department of nutrition sciences at the University of Alabama at Birmingham, told Endocrine Today.

“If we can prevent 80% of diabetes in America, we’d go a long way toward reducing health care costs and the burden of diabetes on patients and the suffering that it causes,” Garvey said.

The researchers conducted SEQUEL, a subanalysis of the phase 3, randomized, placebo-controlled, double blind CONQUER trial, consisting of overweight or obese patients (BMI ≥27 to ≤45) with more than two comorbidities, according to data.

Patients with prediabetes (n=292) and metabolic syndrome (n=451) were included in the subanalysis.

After 108 weeks of random assignment to either placebo or phentermine-topiramate (Qsymia, Vivus), the cohort lost 10.9% of their body weight in the phentermine-topiramate 7.5-mg/46-mg treatment arm and 12.1% of their body weight in the 15-mg/92-mg treatment arm (P<.0001), compared with 2.5% in the placebo group.

There also was a 70.5% decreased annual incidence rate of type 2 diabetes for those assigned to 7.5 mg/46 mg and 78.7% for those assigned to 15 mg/92 mg (P<.05), compared with placebo.

“Here, we have two diagnostic codes for prediabetes and metabolic syndrome; you identity those patients, you know they have high risk for diabetes and cardiovascular disease and risk factors,” Garvey said. “These can be improved with weight loss. In this case, medicine-assisted weight loss particularly yielded up to 10% or more loss of body weight.” – by Samantha Costa

BMI may be most vital determinant of basal metabolic rate in PCOS.


The BMI of patients with polycystic ovary syndrome appeared to be the most important factor in basal metabolic rate, independent of the polycystic ovary syndrome phenotype and insulin resistance, according to Margareta D. Pisarska, MD, who presented the data at the conjoint meeting of the International Federation of Fertility Societies and the American Society for Reproductive Medicine.

“Based on our study — since we do think obesity does play a significant role — we believe it is important for endocrinologists to help counsel these women in a fashion similar to those who are obese by emphasizing that weight loss and lowering BMI are important,” Pisarska, director of the division of reproductive endocrinology and infertility; director of the Fertility and Reproductive Medicine Center at Cedars-Sinai Medical Center; associate professor at Cedars-Sinai Medical Center and the David Geffen School of Medicine at UCLA, told Endocrine Today.

The researchers conducted the case-control study examining the metabolic changes (ie, lean body mass, body fat mass, body fat percentage, skeletal muscle mass, BMI and basal metabolic rate) in 128 patients with PCOS (mean age, 28.1 years) and 72 eumenorrheic, non-hirsute controls (mean age, 32.9 years).

In terms of hormonal profile, patients with PCOS had greater testosterone, dehydroepiandrosterone sulfate (DHEA-sulfate), fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR) levels compared with controls.

After controlling for age and BMI differences, there was no difference in body composition parameters between patients with PCOS and controls. There were no significant results regarding changes to the basal metabolic rate (P=.0162), lean body mass (P=.0153) or skeletal muscle mass (P=.0169), she said.

However, differences in fasting insulin and HOMA-IR remained significant. When looking at insulin resistance in women with PCOS as a potential factor affecting body composition and metabolic rates, there was also no difference between these groups.

“It is not necessarily PCOS; BMI and age are probably the more important determinants of basal metabolic rate, regardless of PCOS phenotype and insulin resistance,” Pisarska said.