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Primary Care Corner with Geoffrey Modest MD: physical activity energy expenditure, a new paradigm

12 Apr, 17 | by gmodest

by  Dr Geoffrey Modest

​​The Scientific American magazine just had an article which made the point that in cross-cultural studies, human beings expend the same number of calories whether they are doing intense exercise or sitting around (see ). These anthropologists studied several human populations, though this report was largely on the Hadza people who lived in the dry savanna wilderness of northern Tanzania. In particular they found that Hazda men who spent days hunting and tracking game, ate and burned 2600 cal a day. Hadza women, who also did a lot of physical work, ate and burned 1900 cal a day. This is pretty much the same as adults in the US or Europe, and was independent of body size, fat percentage, or age. Similarly, research has shown that rural Nigerian women and African-American women in Chicago have similar energy expenditure, despite large differences in activity level. And, a large collaborative effort on non-human primates found that captive primates living in labs or zoos expended the same number of calories as those in the wild.

They posit that there might be differences in calories spent on different activities, and those who are sedentary may spend more energy on other things. For example exercise reduces inflammation, so sedentary individuals may have to spend more energy reducing inflammation. In addition women who exercise a lot may have decreased estrogen levels and fewer ovulatory cycles (ie, less energy spent there), perhaps to compensate for their increased exercise-related energy expenditure. Other studies have found that those who do long-term exercise have reduced basal metabolic rates [and, my addition, have slower heart rates, which may itself be associated with longer life], expending less energy in this manner

A more scientific study published by the author of the above article looked at total energy expenditure over a range of physical activity, finding that there was a positive relationship between total energy expenditure and physical activity but only at the lower ranges of physical activity. Energy expenditure plateaued at the upper ranges of physical activity (see Pontzer H. Current Biology 2016: 26, 410.)


— 332 adults age 25 to 45, 55% female, from 5 populations across Africa North America (Ghana, South Africa, Seychelles, Jamaica, and the US)

— total energy expenditure was measured using doubly labeled water, considered the most accurate measurement (where each subject would ingest radioactively labeled water and assess urinary excretion of the isotopes)

— physical activity was measured by wearable accelerometers, measured in counts/minute


–there was a small increase in the total energy expenditure from a baseline of about 600 kcal/d with 0 counts/min (cpm) on the accelerometer to about 800 kcal/min as this increased to 230 cpm, with no significant further increase up to >700 cpm


— these articles are consistent with the repeated finding that exercise by itself does not lead to weight loss, though is an important factor in maintaining weight loss in those on a diet; these data undercut an Additive model (where total energy expenditure is a simple linear function of physical activity and that this determines variations in total energy expenditure) to more of a Constrained total energy expenditure model (where the body adapts to changes in physical activity to maintain total energy expenditure within a narrow range). And perhaps there is an evolutionary aspect as to why those who exercise have to conserve energy in other ways, such as lowering basal metabolic rate, decreasing population (and the decrease in estrogen/ovulatory cycles in women also decreases energy expenditure on growth, perhaps with the added issue that those who exercise lots to get food may need to have fewer mouths to feed to survive),  etc.

— But, of course, even if exercise does not lead to weight loss, it is important to maintain the perspective that physical activity has a multitude of important healthy benefits, both mentally and physically, and I believe we as clinicians should be encouraging it regularly with our patients. Increasingly, we are learning of the benefits of exercise even where physicians initially felt it was potentially harmful, including in patients with severe heart failure for example. (and in the old days, clinicians prescribed prolonged strict bedrest post-MI, or back pain…)

— A recent meta-analysis for example found that lower levels of exercise was associated with excess mortality (see ), and, as opposed to other studies, this one looked at total physical activity and not just leisure-time activity:

— a review of articles from 1981 to 2016, prospective international cohort studies examining association between total physical activity and least one of the 5 diseases studied: 35 for breast cancer, 19 for colon cancer, 55 for diabetes, 43 for ischemic heart disease, and 26 for ischemic stroke, yielding 174 identified articles.

— Higher levels of physical activity are associated with low risk for all of these outcomes, at 3000-4000 metabolic equivalent minutes per week, or METs/wk.

— overall, comparing those with < 600 METs/wk to those with > 8000 METs/wk was associated with:

— 14% decreased risk of breast cancer

— 12% decreased risk of colon cancer

— 28% decreased risk for diabetes

— 25% decrease risk for ischemic heart disease

— 26% decreased risk for stroke

–but for all of these, the major risk reductions occurred at lower levels of activity, with diminishing returns after 3000-4000 MET minutes/wk.

–and, another recent study (see Ekelund U. Lancet 2016; 388: 1302–10) did a meta-analysis of 13 studies with over 1 million individuals followed for 2 to 18 years, assessing sitting time, TV time and physical activity. They found that, as compared to those in the most-active quartile (35.5 MET-h/week):

— those performing < 16 MET-h/week had a 12% higher mortality rate

— those with the lowest quartile of physical activity (<2.5 MET-h/week and sitting > 8 h/ day) had mortality rates 59% higher

— And, subgroup analysis revealed that it was the exercise level determined risk, independent of the sitting time (comparing <4 h/d and up to >8 h/d of sitting time).

— However, watching TV for >5 hours per day was associated with increased mortality regardless of physical activity, with noticeable increases in the group watching 3-5 hours TV/d.

–of course, these are observational studies, though large and consistent in their conclusions. but those doing less exercise may be very different from those doing more (poorer health, different social determinants of health, etc)

So, what does all of this mean? A few points:

–exercise is really important in maintaining a healthy life (as above, but also as shown in smaller randomized controlled trials: see here ​ for an array of blogs)

–the first studies suggest that there is a conservation of total energy expenditure, largely independent of how much exercise is done. This is likely evolutionarily determined. And perhaps the energy expenditure on exercise is in part diverting energy away from what would be unnecessary bodily functions needed for the sedentary (eg decreasing inflammation, which exercise itself helps). But this finding of conservation of energy expenditure may help explain in part why increasing exercise is not associated by itself with weight loss.

–and it is interesting in the last study how TV watching seems to be a particularly bad sedentary activity, much worse than just sitting time (which would include such things as sitting at work, which might involve more thought, fidgeting, other activities than the more typically passive “vegging out” in front of the tube).

Primary Care Corner with Geoffrey Modest MD: physical activity and depression in childhood

2 Mar, 17 | by EBM

By Dr. Geoffrey Modest

And, perhaps the last blog on exercise, at least for now…

A Norwegian study assessed the relationship between physical activity, sedentary lifestyle, and DSM-IV defined major depressive disorder (MDD) in kids aged 6 to 10 years old (see DOI: 10.1542/peds.2016-1711​).


  • Community sample of 6-year-old children (n=795) in Trondheim, Norway were followed-up at 8 and 10 years of age.
  • Physical activity was recorded by accelerometry – wearing an accelerometer for 7 consecutive days, 24 hours a day, and only removing when bathing or showering; they assessed the time period of 6 AM till midnight and excluded periods of time where there were greater than 20 minutes of 0 counts (suggesting they were not wearing the unit); sedentary activity was <100 counts per minute; and moderate-to-vigorous physical activity, MVPA, was >2296 counts per minute). Major depression was assessed through semistructured clinical interviews of parents and children using the Preschool Age Psychiatric Assessment (PAPA), with a summed score creating the DSM-IV defined MDD; and the Child and Adolescent Psychiatric Assessment (CAPA) was used as well for children 8 and 10 years old.


  • DSM-IV defined MDD decreased from age 6 to 8 but then increase from age 8 to 10. (the prevalence of MDD was around 0.5% in all of the age groups)
  • Minutes of MVPA did not change from age 6 to 8 but decreased from age 8 to 10
  • Sedentary activity increased from age 6 to 8 and increased further from age 8 to 10
  • The symptoms of MDD and sedentary activity were modestly stable over this time. MVPA was more stable.
  • Cross-sectional findings
    • The symptoms of MDD were negatively correlated with MVPA at age 8 and 10, but were unrelated to sedentary activity.
    • At both ages of 6 and 8, higher levels of MVPA predicted fewer symptoms of MDD 2 years later, with a reduction of 0.2 symptoms of depression per daily hour spent in MVPA
    • There was no difference between males and females.
    • MVPA predicted reduced numbers of MDD symptoms from age 6 to 8, but depression did not predict later MVPA (i.e. it seems to be unidirectional). And there were no effects of sedentary activity on depression or vice versa


  • Some studies have found that physical activity may reduce the likelihood of the symptoms of major depressive disorder in adolescents and adults (see Craft LL. Prim Care Companion J Clin Psychiatry 2004; 6: 104, which includes meta-analyses showing exercise’s therapeutic benefit, on the order of cognitive therapy).It has been unclear whether this was related to the physical activity or the lack of sedentary behavior (these 2 are not perfectly correlated, and, for example, children may do periods of intense activity but have a lot of sedentary behavior time). This Norwegian study assessed these factors prospectively in younger children, finding that MVPA mattered but sedentary behavior time did not
  • One particular strength of this study is that they did look at symptoms of depression over time, since these often wax and wane. Also the study allows us to looks at the bi-directionality of the relationship between physical activity and depression, finding that the results were unidirectional from MVPA to MDD. Another advantage of the study over others is that they used a formal assessment of depression as well as a formal assessment of exercise.
  • The effect size of MVPA on MDD symptoms was small, but still on the order of magnitude of those of psychosocial intervention programs in children. And medications do not always work (and probably have more adverse effects than exercise…). So, exercise may well be an important therapeutic approach to treating depression in kids (i.e., not just preventative, as suggested in this study, and should probably be formally evaluated).
  • Some postulates as to why physical activity might decrease depressive symptoms include: these activities might distract children from thinking about negative events; physical activity in children also may bolster their self-esteem; and physically active children are more socially integrated into peer groups.
  • The mechanism by which physical activity might have helped include: higher availability of neurotransmitters which are depleted in people with depression and which may have antidepressant effects if augmented (e.g. serotonin, dopamine and norepinephrine); the potentially positive role for exercise-induced endorphins (see above cited article by Craft); also, there is evidence of increased cerebral blood flow and cognitive function with exercise. Other studies have shown that children taking exams in school do better when they are more physically active prior to taking those exams.
  • One quite concerning social evolution is that many schools have cut out physical education/activity in order to cram in more academic subjects. Unfortunately, this could not just lead to decrease school performance, but also reinforce future patterns of inadequate physical activity. It is concerning in this study that exercise decreased and sedentary time increased from ages 8 to 10.

So, MVPA did predict fewer future MDD symptoms in children, and such symptoms were relatively stable from ages 6 to 10. Sedentary activity however did not affect the risk of future symptoms of depression, and depression does not seem to influence the likelihood of MVPA or sedentary behavior. Their conclusion was that increasing MVPA at a population level may prevent depressive symptoms or MDD. And I think it makes sense for us in primary care to strongly encourage physical activity and advocate for more exercise in schools, and that exercise be considered an integral part of the curriculum, emphasized and promoted by the school system. And that there be more neighborhood-friendly and safe exercise venues, etc. Per the prior blogs and the myriad articles on the benefits of exercise, this is not just to prevent depression…

Primary Care Corner with Geoffrey Modest MD: leisure time activity and lower cancer risk

27 Feb, 17 | by EBM

By Dr. Geoffrey Modest

There have been a plethora of articles in the past year on the beneficial effects of exercise. I will use the next several blogs to sample some of these.

One article looked at the beneficial effects of leisure-time physical activity on 26 cancer types (see doi:10.1001/jamainternmed.2016).


  • 44 million participants from 12 prospective US and European cohorts had self-reported leisure-time physical activity at baseline (1987 to 2004). Leisure-time physical activity levels were assessed as cohort-specific percentiles on a continuous basis. Hazard ratios are based on high vs low activity levels (comparing the 90th versus 10th percentiles of activity)
  • Median age 59 years, 57% females, BMI 26.
  • 186,932 participants with cancer were included in the analysis
  • Moderate activity in general was defined as intensity of >=3 more METS; vigorous activity as >=6 METS (see below for a definition for METS, or Metabolic Equivalents


  • There was a lower risk for 13 cancers with higher levels of leisure-time physical activity (the statistical models controlled for age, sex, smoking, alcohol, race/ethnicity, education; as well as specific risk factors for some cancers, such as hormone therapy, age at menarche, age at menopause, and parity for several of the female-only cancers, etc.):
    • Esophageal adenocarcinoma, decreased 42%, HR 0.58 (0.37-0.89)
    • Liver, decreased 27%, HR 0.73 (0.55-0.98)
    • Lung, decreased 26%, HR 0.74 (0.71-0.77)
    • Kidney, decreased 23%, HR 0.77 (0.70-0.85)
    • Gastric cardia, decreased 22%, HR 0.78 (0.64-0.95)
    • Endometrial, decreased 21%, HR 0.79 (0.68-0.92)
    • Myeloid leukemia, decreased 20%, HR 0.80 (0.70-0.92)
    • Myeloma, decreased 17%, HR 0.83 (0.72-0.95)
    • Colon, decreased 16%, HR 0.84 (0.77-0.91)
    • Head and neck, decreased 15%, HR 0.85 (0.78-0.93)
    • Rectal, decreased 13%, HR 0.87 (0.80-0.95)
    • Bladder, decreased 13%, HR 0.87 (0.82-0.92)
    • Breast, decreased 10%, HR 0.90 (0.87-0.93)
  • But there were higher risks of:
    • Malignant melanoma, increased 27%, HR 1.27 (1.16-1.40)
    • Prostate cancer, increased 5%, HR 1.05 (1.03-1.08): but specifically for non-advanced prostate cancer (HR 1.08), with no association for advanced prostate cancer (HR 0.99)
    • Cancers that did not reach statistical significance included non-Hodgkin’s lymphoma (though this was borderline significant at the P=0.05 level, with an 8% decrease with increased leisure-time activity), thyroid, gastric non-cardia, soft-tissue, pancreas, lymphocytic leukemia, ovary, and brain
    • Controlling for BMI decreased the statistical significance for esophageal carcinoma, and rendered the associations with endometrial cancer, liver and gastric cardia to be nonsignificant
    • Associations were generally similar with overweight/obese versus normal weight individuals
    • Smoking status modified  the association for lung cancer but not the other smoking-related cancers


  • This observational study found the quite impressive result that exercise was associated with major decreases in 13 cancers (10, after adjusting for BMI), and the decrease was 20+ % (i.e., really large) for 7 of them.
  • There are obvious concerns with such a study, including the fact that they compared only the top 10th percentile to the lowest 10th percentile of leisure-time activity, which also likely includes more unaccounted-for biases (e.g., those in the highest percentile group being much more likely to have generally healthy lifestyles, which may not be fully reflected in the multivariate analysis). Also, as with any meta-analyses, there are bound to be significant differences in the methodology of each individual study, making the strict combination of them less rigorous. The measures of physical activity were self-reported, and the cutpoints of high vs low varied between the individual studies. Also, some of the measurements (e.g. BMI) were considered as dichotomous variables (either above or below 25) which could conceal their true contribution (i.e. a BMI of 25.1 may confer a very different risk from a BMI of 35.1; on the other hand a BMI of 24.9 may not be so different from a BMI of 25.1)
  • Another issue is that leisure-time activity reflects only part of the picture. Many of the old studies only looked at leisure-time activity because they could not figure out how to incorporate work-related activity into the metric. Work-related activity requires very detailed analyses of individual workplaces, given that people doing the same job in different workplaces may have amounts of physical exertion, depending on such factors as degree of automation, how large the workplace is and what the division-of-labor is, and, in general, how the specific job was structured, including the role of labor unions requiring employers to decrease the intensity or potential risks of many jobs. Also, since leisure-time activity typically reflects voluntary participation that would reinforce the above-stated potential bias that these people lead generally healthier lifestyles.
  • Another recent systematic/meta-analysis (see 174 world-wide studies, looked at the levels of total physical activity (leisure-time, occupational, domestic, transportation) and the risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic strokes, finding:
    • Overall, major gains for all outcomes occurred at lower levels of physical activity (3000-4000 MET minutes/week)
    • Even 600 MET/week (the lowest level in the studies), had a 2% lower risk of diabetes (vs no reported physical activity)
    • But going from 600 to 3600 MET minutes/week reduced the risk additionally by 19%. further increases did not add much (e.g., 0.6% if increase from 9000 to 12000 MET minutes/week)
    • At higher levels of physical activity (>8000 MET minutes/week), they found:
      • 14% reduction in breast cancer
      • 21% reduction in colon cancer
      • 28% reduction in diabetes
      • 25% reduction in ischemic heart disease
      • 26% reduction in ischemic stroke
    • But, looking at the curves: for all endpoints but breast cancer, there was the most dramatic improvement going from about 1500 to 4000 MET minutes/week, with leveling off thereafter. For breast cancer, the curve showed a relatively linear decline with more activity. [Remember: this study included all physical activity: i.e. it is hard to translate the current US recommendation of 75-150 minutes/week of exercise into the above 1500-4000 MET minutes/week.]​
  • Potential mechanisms connecting exercise with decreased cancer include: decreased body fat (body fat could confer various risks, including increased estradiol levels; they did note that BMI did decrease the association with several cancers, however I would add that BMI is not the most specific measurement of body fat, and does not differentiate from the much more metabolically active and less healthy visceral fat from subcutaneous fat); also many/most hormonal systems are changed with exercise, including cortisol levels (which in themselves affect most other hormone levels), male and female sex steroids, insulin and insulin-like growth factors, and adipokines (and many of these hormone systems could be related to carcinogenesis, e.g. by altering immune function); as well as changes in inflammation, oxidative stress (which are especially related to  visceral fat), and the reduced colonic transit time which could affect colon cancer incidence.

So, a pretty quick and dirty study, but it does really reinforce the potential role of exercise in cancer prevention. This becomes even more of an issue given the predictions that the global cancer burden will increase dramatically (one model suggesting a doubling by the year 2030), especially as unhealthy lifestyles such as smoking and poor diet increase in resource-poor countries: there are increasing obesity trends and less physical activity as more people move to crowded and often quite polluted cities — these changes are associated with a pretty dramatic shift from mortality associated with infectious diseases to that associated with chronic, western-type diseases).

From blog of 1/3/17 on cardiovascular fitness as a vital sign:

  • As a quick guide to METs:
    • Light activity (<3 METs): includes walking 2.5 mph (2.9 METs)
    • Moderate activity (3-6 METS): includes walking 3.0 mph (3.3 METs), walking 3.4 mph (3.6 METs), stationary biking (light effort) 5.5 METs
    • Vigorous activity (>6 METs):  jogging (7.0 METs), calisthenics/pushups/situps (8.0 METs), rope jumping (10.0 METs)​

Primary Care Corner with Geoffrey Modest MD: Physical activity and decreased recurrent strokes

19 Jan, 17 | by EBM

By Dr. Geoffrey Modest

The SAMMPRIS trial (Stenting and Aggressive Medical Management for Preventing Recurrent Stroke in Intracranial Stenosis) compared aggressive medical management of patients with intracranial stenosis and a non-disabling stroke/TIA, versus stenting plus aggressive medical management, finding that aggressive medical management was superior (see  doi 10.1212/WNL.0000000000003534​).​ In a prespecified analysis, they looked at the relationship between risk factor control during follow-up and outcomes in the aggressive medical arm.


  • 227 patients were analyzed, with risk factors recorded at baseline, 30 days, 4 months, and then every 4 months for up to 32 months.
  • Aggressive medical therapy included aspirin 325 mg per day along with clopidogrel 75 mg daily for the first 90 days, as well as treating the systolic blood pressure and LDL cholesterol to target (see below). Secondary risk factors included the non-HDL cholesterol, hemoglobin A1c in diabetics, smoking, weight management, and physical activity. Coaching on healthy lifestyle behaviors was done at regularly scheduled times throughout the follow-up
  • Target for risk factors:
    • Cholesterol: LDL <70 mg/dl (47% in target over the course of the study)
    • Blood pressure: systolic blood pressure < 140, or <130 if diabetic (53% in target)
    • Hemoglobin A1c < 7% if diabetic (42% in target)
    • Smoking cessation (65% target)
    • Weight management (if initial BMI 25-27, target <25;  initial BMI >27, target 10% weight loss; 19% in target)
    • Physical activity, assessed using the 8 point Physician-based Assessment and Counseling for Exercise (PACE) questionnaire (target score 4-8; 44% in target), where:
      • PACE 3= trying to do vigorous or moderate exercise but not exercising regularly
      • PACE 4= moderate exercise (brisk walking or slow cycling for at least 10 minutes at a time) <5 times per week or vigorous exercise (jogging or fast cycling for at least 20 minutes at a time) <3 times a week
      • PACE 6= at least 30 minutes of moderate exercise a day for at least 5 days a week for the past 6 months or more


  • At 3 years, the likelihood of the endpoint of a recurrent stroke, MI, or vascular disease in multivariate analysis, controlling for the above risk factors:
    • Higher PACE score decreased the likelihood by 40% [OR 0.6 (0.4 0.8)], with a dose effect for exercise (i.e., more exercise, more benefit)
    • Blood pressure, cholesterol, as target variables (i.e., dichotomized to above and below target) were nonsignificant. smoking, BMI, and hemoglobin A1c were also not significant
    • For recurrent ischemic stroke as the only endpoint at 3 years:
      • PACE had a highly significant odds ratio of 6.7 (2.5- 18.1)
      • LDL overall was not statistically significant as a dichotomized variable, though there was a significant odds ratio of 1.1 (1.0- 1.3) looking at it as a continuous variable, for each increase of 10 mg/dL)
      • Systolic blood pressure was similarly nonsignificant though had a significant odds ratio 1.2 (1.0- 1.6) as a continuous variable, for each increase of 10 mmHg
      • Hemoglobin A1c for diabetic patients had an odds ratio of 2.3 (1.0-5.0)
      • Smoking, BMI remained nonsignificant


  • Patients with intracranial atherosclerotic stenosis are at particularly high risk of recurrent stroke. Other trials had found that poorly controlled blood pressure and elevated cholesterol are important risk factors for this. The above SAMMPRIS trial was an NIH-funded trial for intensive risk factor management, evaluating patients within 30 days of a TIA or non-disabling stroke caused by a 70-99% stenosis of a major intracranial artery. And the primary outcomes were stroke, MI or vascular death within 30 days after enrollment, as well as ischemic stroke in the territory of the qualifying artery beyond 30 days
  • Although the study did show that controlling blood pressure and cholesterol were important for reducing vascular events, the independent effect of physical activity was considerably stronger for the prevention of recurrent vascular events, and especially for recurrent ischemic stroke. Other studies had shown that exercise decreased mortality among stroke patients and decreased the incidence of incident stroke among healthy people.
  • Although the above trial was an observational trial, and there is certainly a potential bias from post-stroke depression, they did note that the percentage of patients involved in physical activity increased from 32% at 30 days to 56% at the 4-month follow-up visit, perhaps reflecting the focus on lifestyle modification by the researchers. This increase in exercise would make less likely but not eliminate the potential depression bias.
  • One side concern in post-stroke patients is how rapidly to lower blood pressure. This study did suggest that in those enrolled within 30 days of a TIA or nondisabling stroke, they did better with more intensive blood pressure control (33.8% had blood pressure at the target at baseline, increasing to 47.6% at 30 days). As in another study, they did not find that diabetes, weight, or smoking cessation were significantly related to recurrent vascular events, though part of this may be due to lack of power to detect a significant effect.
  • The likely mechanisms for the positive effect of exercise include augmented arterial blood to the brain (including collaterals), improvement in other risk factors (HDL, insulin resistance, blood pressure), and decreased arterial stiffness.

So, this post hoc analysis (but of a prespecified endpoint) demonstrated the remarkable predictive power of exercise for fewer recurrent vascular events; and this relationship was increasingly evident as the amount of exercise increased. Unfortunately, they did not look at dietary interventions as part of their lifestyle modification. But, to me, bottom line is that we should be aggressively encouraging patients to increase their exercise as much as possible if they have intracranial-arterial stenosis causing a TIA or nondisabling stroke, as well as prescribing the usual culprits to control blood pressure, lipids, and give an antiplatelet drug.

Primary Care Corner with Geoffrey Modest MD: Cardiovascular Fitness — a new vital sign?

19 Jan, 17 | by EBM

By Dr. Geoffrey Modest

A recent scientific statement from the American Heart Association stresses the importance of assessing cardiorespiratory fitness (CRF) as part of the risk assessment for cardiovascular disease (see DOI: 10.1161/CIR.0000000000000461)​.


  • Studies since the 1950s have consistently found that CRF is a strong and independent marker of cardiovascular risk as well as all-cause mortality, adjusting for age and the other standard risk factors. This is been found in healthy men and women, those with known or suspected cardiovascular disease, and those with the co-morbidities of obesity, type 2 diabetes, hypertension, and hyperlipidemia. In many studies CRF is a more powerful predictor of mortality risk than traditional cardiovascular risk factors. It has even been shown to be a more powerful risk predictor than ST-segment depression, cardiovascular symptoms, or hemodynamic responses.
  • The survival benefit in 13 studies showed that each 1-MET (metabolic equivalent) higher CRF, a small increment, was associated with a marked 10-25% improvement in survival. And, one study found that men who improved from unfit to fit between two successive examinations had a reduction in mortality risk of 44% relative to those who remained unfit in both exams (i.e., those with higher CRF have dramatic clinical benefit)
  • As a quick guide to METs:
    • Light activity (<3 METs): includes walking 2.5 mph (2.9 METs)
    • Moderate activity (3-6 METS): includes walking 3.0 mph (3.3 METs), walking 3.4 mph (3.6 METs), stationary biking (light effort) 5.5 METs
    • Vigorous activity (>6 METs):  jogging (7.0 METs), calisthenics/pushups/situps (8.0 METs), rope jumping (10.0 METs)
  • Of note, even though the most dramatic differences in all-cause and cardiovascular mortality were found comparing the most fit to the least fit subjects (70% and 56% respectively), the greatest increase in mortality benefit was in comparing the least fit group to the next least fit category
  • A recommendation in the paper is that CRF should become an accepted “vital sign”, and should be part of the standard clinical encounter
  • CRF also is associated with heart failure exacerbations and mortality, with one study finding that for every 6% increase in CRF over three months there was a 4% lower risk of cardiovascular mortality or hospitalization, and an 8% decrease risk of cardiovascular mortality or heart failure hospitalization (for example, see which shows the benefit of vigorous exercise in patients with heart failure and reduced ejection fraction), timing of cardiac transplantation, preoperative surgical risk prediction (including studies of abdominal aortic aneurysm repair, liver transplant, lung cancer resection, upper GI surgery, intra-abdominal surgery, bariatric surgery, coronary artery bypass grafting). And interventions seem to help: in patients waiting for CABG surgery, those randomized into an exercise training group had superior outcomes to the control group, with a reduced rate of perioperative complications and shorter hospital stays. And observational studies have also shown that men with higher CRF had 68% lower stroke mortality, controlling for standard risk factors.
  • There were a few studies showing that those with a higher level of CRF had a reduced risk of developing dementia or Alzheimer’s, one study showing a 36% lower risk of developing dementia in those with the highest quartile of CRF. Higher levels of CRF are also associated with lower measures of anxiety or depression symptoms
  • Many studies have shown decreased risk of development of prediabetes, metabolic syndrome, and type 2 diabetes in those with higher CRF, again with the biggest difference in those going from lower CRF to the moderate range.
  • Lower levels of CRF at a younger age are also associated with a higher risk of disability at an older age. For example one study of obese adults with type 2 diabetes found that after four years, improvement of CRF decrease the likelihood of developing disability
  • Added value of CRF to the traditional risk calculators:
    • Several analyses have looked at various ways of incorporating the additional value of CRF. In one 30-year study of patients with stage II hypertension, the 30 year risk of cardiovascular mortality was 18.4% in those with low CRF versus 10.1 present in those with high CRF (i.e., a huge difference)
    • Overall, adding CRF to the traditional risk stratification led to actual CVD and all-cause mortality outcomes being correctly reclassified through the risk predictor as being decreased 23.3% and 20.6% respectively through correctly reclassifying patients as higher risk, and 55.8% and 46.0% respectively for correctly reclassifying patients as lower risk. The overall changes reflected a 30.5% and 24.5% correct reclassification for all-cause mortality, with larger changes in correctly reclassifying patients as lower risk because of CRF. [e., those at apparently high risk by a traditional risk calculator, in reality have significantly lower risk if they are more fit; there are changes apparent in the other direction as well, but less emphatically so]. Also as a point of comparison, when looking at the nontraditional risk factors, such as coronary artery calcium scores  (which seems to be the best of the lot), the level of correct reclassification from the traditional risk calculators is much lower
  • So, how does one measure CRF?
    • The most accurate and standardized quantification of CRF is through CPX (cardiopulmonary exercise testing), a combination of conventional exercise testing with ventilatory expired gas analysis
    • A step below that is to look at achieved treadmill speed/grade and duration, making sure the patient does not hold the hand rails
    • Another approach is to look at submaximal exercise testing or the 6-minute walk test to assess distance walked (walking <350 meters is associated with high risk).
    • And the easiest overall/least time-consuming/cheapest/easiest to implement is to do nonexercise prediction calculations. These are not standardized at this point, and each study seems to have somewhat different calculators. Perhaps the best is to use the one by Nes BM. Med Sci Sports Exerc 2011; 43: 2024, which incorporated an assessment of patient reported physical activity, age, waist circumference, and resting heart rate, and this is one of the studies which included a lot of people (n= 2067 men and 2193 women) and looked at actual clinical outcomes, finding that 90.2% of women and 92.5% of men in the lowest two quartiles of fitness were correctly classified. Their questions for physical activity included: frequency of exercise (never, <1x/wk, 1x/wk, 2-3x/wk, >3x/wk), intensity (“no sweat/heavy breathing, “heavy breath and sweat”, “push myself to exhaustion”), and duration (<15 in, 15-30 min, 30-60 min, >60 min).
    • Overall exercise recommendations:
      • Type: exercise should involve major muscle groups (legs, arms, trunk) that is continuous and rhythmic (e.g. brisk walking, jogging, cycling, swimming, rowing)
      • Intensity: moderate and/or vigorous intensity relative to the persons capacity
      • Frequency: at least five days per week of moderate or three days per week of vigorous intensity exercise
      • Time: 30 to 60 minutes per day (150 minutes per week) of moderate and 20 to 60 minutes per day (75 minutes per week) of vigorous exercise. Of note between 10 and 20 minutes can be beneficial in previously inactive people
      • Amount: a target of 500 to 1000 MET-min/wk
      • Pattern: one continuous session per day or multiple sessions per day of greater than 10 minutes each. Less than 10 minutes may work in deconditioned individuals.


  • Incorporating CRF reflects a more individualized physiologic approach (assessing the constellation of how well the heart, lung, circulation, and oxygen extraction by muscles works). It is clear from epidemiologic data that on a community basis, as well as individual basis, the traditional risk factors of smoking, hypertension, hyperlipidemia, and diabetes confer an increased risk of cardiovascular disease. However, CRF is a truly specific individual physiologic risk factor, reflecting how these risk factors and more play out in the individual’s body. For example, hypertension itself confers different levels of individual risk dependent on CRF.
  • One note of caution: there is no uniformity in clinical practice as to which of the traditional risk calculators is the best: the Am Heart Association/Am College of Cardiology just published an updated tool, including a spreadsheet calculator (see org/10.1161/CIR.0000000000000467 for the article, and the spreadsheet to calculate risk. BUT, this tool also needs to be validated in different populations prior to being accepted (also, see for a critique of the 2013 ACC/AHA lipid guidelines.)
  • Interestingly, several studies suggest that CRF is a more potent predictor of cardiovascular disease than any of the individual risk factors we have incorporated into our predictive models
  • Why is CRF so important? There are several explanations: improved traditional cardiovascular risk profiles (though most of the studies did control for the major ones we know), changes in autonomic tone that may reduce arrhythmogenic risk, fewer thrombotic events (exercise decreases fibrinogen levels, for example), improved endothelial function, lower levels of visceral adiposity/improved insulin sensitivity, lower levels of inflammation, as well as perhaps improved mental health and sense of well-being. And, there might be important positive changes in the gut microbiome with exercise, which is clear in animal models, less clear in humans where those who exercise tend to eat differently from those who do not, so hard to control well).
  • I should add a couple of caveats here: it is important not to confound fitness with doing lots of exercise; a significant component of fitness (on the order of 30+%) is genetic and not related to regular exercise. And most of the studies above are observational, not intervention studies (i.e., only a few actually randomized patients to exercise programs vs none and looked at long-term outcomes. Though the one on pre-surgery exercise programs was pretty impressive. And, the overall data on the benefits of exercise overall are quite robust)
  • For ballpark figures, those with a CRF level less than 5 METs have a particularly high risk of mortality, whereas those with CRF levels of greater than 8 to 10 METS seem to have much more protection. And, more than half the reduction in all-cause mortality occurs between those who are least fit (e.g. CRF less than 5 METs) and those in the next least fit group (e.g. CRF 5-7METS); i.e., benefits for cardiorespiratory fitness are particularly strong in those people in the least fit as compared to the next higher category (i.e., one does not need to be an Olympic athlete to achieve the benefits)

So, the key points here are:

  • Cardiorespiratory fitness is an independent in additive risk assessor for total and cardiovascular mortality
  • Improving CRF dramatically decreases cardiovascular and all-cause mortality
  • This clinical improvement is especially profound in those who are the least fit, finding a greater than 50% risk reduction by moving one step up to the next least fit group. An increase in CRF of only one MET is associated with the 10 to 20% decrease in mortality rate
  • There is a reasonable argument based on studies that have been done to propose that a simple, non-exercise based calculator should be added as a vital sign. This could easily be measured by nonclinical staff and would provide clinicians important information to help encourage patient-specific exercise programs. This should to be evaluated more completely in different populations to assess its generalizability. However, even without those studies, given the documented benefits of exercise and the dramatic relationship in the above studies of CRF as a risk predictor, I personally will ask patients about CRF more and further reinforce the importance of exercise as part of a healthy lifestyle.

For other blogs on exercise, see

Primary Care Corner with Geoffrey Modest MD: Vigorous Exercise Helps Those with Heart Failure

9 Nov, 16 | by EBM

By Dr. Geoffrey Modest

There was a recent systematic review/meta-analysis finding that in patients who have heart failure with reduced ejection fraction, vigorous exercise training significantly improved their quality of life (see DOI: 10.1159/000448088).

  • 25 studies were included with 2385 participants (1223 exercising and 1162 controls) [of note, 8 of these studies had <30 patients, and 6 studies had >100]
  • They used the Minnesota living with heart failure total score (MLWHF), a 6-part inventory, all graded 0 to 5, assessing physical and emotional symptoms. A 5-point change is considered clinically meaningful.
  • They did not specifically define the different exercise groups, but an example of high-intensity is cycling 45 minutes at 90% peak work three days per week. An example of vigorous-intensity exercise was cycling for 30 minutes at 60-70% peak VOthree times a week. An example of moderate-intensity exercise was 15 minutes of cycling and 15 minutes of treadmill at 50% peak VO2 three times a week.


  • MLWHF total score was significantly reduced after high-intensity (mean difference -13.74, P=0.0004) and vigorous-intensity training (mean difference -8.56, P<0.0001). No difference with moderate-intensity training.
  • Significant differences were noted with aerobic training (mean difference -3.87, p=0.01) and combined aerobic and resistance training (difference -9.82, p=0.001), but no difference with resistance training alone.


  • There was concern many years ago that vigorous exercise might put too much stress on the heart in those with heart failure. This changed considerably over the past several years, as some of the above studies came out.
  • Review of the forest plot in the above article, which displays the individual studies, found that in all 3 studies where high-intensity exercise was done there was statistically significant benefit; those looking at vigorous-intensity training were pretty consistently favoring the exercise group, with only one study finding statistically significant benefit in the control group (and, that study included only 60 patients, out of a total of 924 overall)
  • This study, as well as some other recent ones, suggest that there is more general benefit with the combo of aerobic and resistance training (i.e., not just aerobic)
  • So, I think this analysis confirms that we should encourage exercise in patients with heart failure and reduced ejection fraction, and that patients should anticipate improved physical and emotional symptoms as they progress to higher intensity exercise. Of course, those with potentially ischemic symptoms should have an appropriate workup prior to beginning an intensive exercise program.

Primary Care Corner with Geoffrey Modest MD: Normal BMI/Exercise Lower Cancer Risk

23 Sep, 16 | by EBM

By Dr. Geoffrey Modest

The International Agency for Research on Cancer (IARC) working group just assessed the relationship between overweight/obesity and cancers, finding 8 more cancers associated with obesity (see Lauby-Secretan B. N Engl J Med 201; 375: 794). They relied on over 1000 epidemiological/observational studies to assess this association, since there really are no large randomized clinical intervention trials with long-term follow-up assessing the effects of weight-loss vs maintaining weight to see if there is a difference in cancer incidence.

  • Background, worldwide estimates:
    • In 2014: 640 million adults in 2014 (an increase by a factor of 6 since 1975) were obese
    • In 2013: 110 million children and adolescents (an increase by a factor of 2 since 1980) were obese
    • In 2014: prevalence of obesity was 10.8% among men, 14.9% among women, and 5.0% among children; and globally more people are overweight or obese than are underweight.
    • In 2013: 4.5 million deaths worldwide were caused by overweight and obesity; the obesity-related cancer burden represents up to 9% of the cancer burden among women in North America, Europe, and the Middle East.
    • In 2012: 1 million new cancer cases and 8.2 million cancer-related deaths
  • The 8 new cancer associations:
    • Colon or rectum, RR = 1.3, with positive dose response relationships (e., the more overweight, the higher the risk)
    • Gastric cardia, RR = 1.8, with positive dose response relationships
    • Liver, RR = 1.8, with positive dose response relationships
    • Gallbladder, RR = 1.3, with positive dose response relationships (though in their analysis, comparing the top vs bottom decile of activity, this achieved a P=0.06 only)
    • Pancreas, RR = 1.5, with positive dose response relationships
    • Kidney, RR = 1.8, with positive dose response relationships
    • Esophageal adenocarcinoma, RR=8, with positive dose response relationships
  • In general the relative risks increased from 1.2 to 1.5 for overweight and from 1.5 to 1.8 for obesity for cancers of the colon, gastric cardia, liver, gallbladder, pancreas and kidney
  • These results were consistent in different geographic regions, and were similar for men and women
  • The previously known cancers with associations:
    • Breast cancer in postmenopausal women, RR of 1.1 per 5 BMI units, esp in estrogen-receptor positive tumors
    • Endometrial cancer: RR=1.5 for overweight,5 for BMI 30-35, 4.5 for BMI 35-40, and 7.1 for BMI>40
    • Ovarian cancer (epithelial): RR=1.1
    • Multiple myeloma, RR=1.2 for overweight, 1.2 for BMI 30-35, 1.5 for BMI 35-40, and 1.5 for BMI>40
    • Meningioma, RR = 1.5
    • Thyroid, RR=1.1
  • And there is some limited evidence of an obesity association with male breast cancer, fatal prostate cancer, and diffuse large B-cell lymphoma
  • For breast cancer, there was an association between increased BMI at the time of diagnosis and reduced survival
  • In terms of weight loss: the quality of the data are not great, but there are some suggestions that weight loss (including by bariatric surgery) may reduce the breast and endometrial cancer risks.
  • As supporting evidence:
    • Animal data (different animals) confirm an association between obesity and cancer at many different sites
    • Animal data also supports the effect of limiting weight gain vs food ad libitum for some cancers (mammary gland, colon, liver, pancreas, skin, pituitary) but inverse relationship with others (prostate, lymphoma, leukemia)


  • As with all of these observational studies, association does not imply causality. For example, is it the obesity itself which is associated with cancer? Or, are there specific things that obese people do differently than normal weight ones (e.g., eating certain oncogenic foods? not exercising enough? living in more toxic environments?)
  • The above results were similar for BMI and waist circumference when that data was available (waist circumference has a higher correlation with visceral obesity, which is the metabolically more active obesity associated with metabolic syndrome, increased inflammatory markers, )
  • In many of the above associations, the associations persisted in studies using mendelian randomization (see , which describes mendelian randomization and some of its limitations, but overall it is a process that assesses known genetic markers for a disease to help assess causality (to differentiate in this case whether the causality is if those genetically predisposed to obesity are more likely to get the cancer, not vice-versa or as independent phenomena)
  • Possible mechanisms: increased body fat is associated with multiple metabolic and endocrine changes (sex hormones, insulin and insulin-like growth factor, inflammation), which could promote tumor initiation and/or growth
  • It is important to keep in mind the strength of the associations above. Typically, in observational studies, a relative risk of under 1.5-2 often does not pan out as being really significant, despite the fact that it can be really significant in randomized controlled trials. So, a bit of a caution in over interpreting the above results for many of the cancers. The dose-response relationship does add some support the associations, however.


Another recent article came out on the relationship between physical activity and cancer (see doi:10.1001/jamainternmed.2016), finding that leisure-time physical activity was associated with lower risk of many cancers. Details:

  • 12 prospective US and European cohorts with self-reported physical activity from 1987-2004, including 1.44 million participants, looking at 26 different cancers
  • Mean age 59 (19-98), 57% female, mean follow-up 11 years (7-21), mean BMI 26, 54% ever-smokers
  • 186,932 cancers diagnosed
  • Leisure-time activity, defined as high if 6 or more METs. Median activity was 8 MET-h/week (equivalent to 150 minutes of moderate-intensity exercise, e.g. walking)
  • Results:
    • High vs low leisure-time activity was associated with lower risk of:
      • Esophageal adenocarcinoma (HR 0.58, i.e., 42% decreased risk)
      • Liver cancer (HR 0.73)
      • Lung cancer (HR 0.74)
      • Gastric cardia (HR 0.78)
      • Endometrial (HR 0.79)
      • Myeloid leukemia (HR 0.80)
      • Myeloma (HR 0.83)
      • Colon (HR 0.84)
      • Head and neck (HR 0.85)
      • Rectal (HR 0.87)
      • Bladder (HR 0.87)
      • Breast (HR 0.90)
    • In aggregate, there was a 7% lower risk of total cancer in those performing higher levels of physical activity [HR 0.93 (0.90-0.95)]
    • Adjusting for BMI (nullied the relationship above for liver, gastric cardia and endometrium) but otherwise only a small attenuation of the risk, on the order of 5-11% of the HR’s. Smoking status affected lung cancer but not the others
    • Some cancers were associated with more activity
      • Melanoma (HR 1.27)
      • Prostate cancer (HR 1.05)


  • One striking finding is the overlap of cancers which seem to be affected by both BMI and exercise, reinforcing that these lifestyle/environmental issues seem to be particularly important.
  • But, one needs to be particularly careful in meta-analyses in general and huge ones in particular: it is very hard to get granular data over time (what is “ever-smokers”? a few cigarettes at the beginning of the study? stopping smoking 2 packs/day near the end of the study?); how often did they track information, such as changes in BMI or physical activity over time? Was it just a one-shot assessment at the beginning of the study? And how did they then quantitate these typically changing variables over such a long follow-up?  This data acquisition is done differently in different studies, so how is this all put together mathematically? It is pretty striking the range of ages (19-98) and years of follow-up (7-21) in the individual studies, suggesting they were pretty heterogeneous. And, in general, the people in this large meta-analysis were reasonably lean (BMI=26), so it may be difficult to really control for BMI in their data (they divided the patients into BMI <25 vs >25, but did not have the BMI spread of the IARC study). This limits the interpretation of their finding in this exercise study that 3 of the highest risk cancers in the AIRC study for BMI had no relationship to exercise when controlling for BMI.
  • They only looked at leisure-time physical activity. It seems pretty intuitive that people with very physical jobs do have more exercise at work than those with office jobs (i.e., many of my patients are on their feet all day, walking around cleaning office buildings, etc. And it seems they should get some “exercise” credit for that.) There are not great studies which have looked at occupationally-related exercise, probably because it is hard to measure on an individual basis: even those with the same job category may have very different amounts of exercise if they clean a small office vs a large automated office building)
  • One concern is that the burden of obesity and lack of exercise is increasing, especially with migration to larger cities and with increasing Westernization around the world
  • But one potentially positive finding is that exercise is associated with lower cancer risk independent of BMI for many cancers (with above caveat): it is much easier to help people do exercise than to achieve sustained weight loss (see ). And there are reasonable postulated mechanisms by which exercise could decrease cancer: hormonal changes (sex steroids, insulin and insulin-like growth factos, adipokines; similar to the BMI mechanisms postulated above) as well as nonhormonal (decrease inflammation, improve immune function/surveillance, decrease oxidative stress, and increase GI transit time, the latter of which could decrease colon cancer incidence)
  • There are still many questions, even if one accepts the conclusions of these studies
    • Does instituting a more aggressive exercise program lead to decreased cancer (i.e., an intervention study would provide stronger conclusions than an observational study)
    • And how much exercise works? Is there a threshold? Is it different for different cancers? (this might be important in different parts of the world where different cancers predominate)
  • But, the real bottom line is that there have been many studies over the years showing that lifestyle/environment are associated with pretty much all of the chronic diseases in the world. The above studies simply reinforce the association with cancer. And it offers us as clinicians yet another way to talk with patients about the importance of a healthy lifestyle. The association with cancer may be a particularly useful tool in motivating patients to avoid progressing to a less healthy lifestyle over time or instituting changes to improve their lifestyle (for better or worse, patients given equal mortality scenarios from cancer or heart disease, for example, are more afraid of the cancer one…it just sounds scarier)

Primary Care Corner with Geoffrey Modest MD: Exercise Benefits in Elderly at Lower Levels

17 Dec, 15 | by EBM

By Dr. Geoffrey Modest

A couple of concerns about the exercise prescriptions we give patients: How realistic are they are for the elderly; and when older people cannot do the moderate-to-vigorous activities recommended, is there benefit in less aggressive exercise? A systematic review and meta-analysis was recently done to answer these questions (see doi:10.1136/bjsports-2014-094306).


  • 9 prospective cohort studies were found, with 122,417 participants (73,745 women and 48,672 men, mean age 72.9, average cohort size 13,602, six cohorts were American/2 from Pacific region/1 Asian, follow-up of 9.8 years and with 18,122 deaths (14.8%)
  • They defined 4 activity levels, by Metabolic Equivalent of Task, or MET) minutes: inactive, low (1-499 MET-minutes), medium (500-999) and high (>1000)
  • Results, with inactive being the reference:
    • ​Low activity had a 22% reduction in mortality [RR 0.78 (0.71-0.87), p<0.0001]
    • ​Moderate  activity had a 28% reduction in mortality [RR 0.72 (0.65-0.80), p<0.0001]
    • High activity had a 35% reduction in mortality [RR 0.665 (0.61-0.70), p<0.001]
  • Most of this association was for a reduction in cardiovascular disease (i.e. 25% reduction in low, 26% medium and 40% high activity), though the reduction in cancer mortality was also significant (ie 11% reduction in low, 16% medium and 31% high activity)
  • There was a dose-response curve, with more exercise intensity having more mortality benefit. But, the greatest decrease in mortality was associated with increasing from inactivity to the lowest level, with gradually more benefit as the intensity increases further.
  • Women benefited more than men: for those performing low activity exercise — men had 14% mortality reduction vs 32% in women (??do men overestimate their amount of exercise and women underestimate it??)

So, a few points:

  • For further clarification of METs and MET-minutes, see​ . As a rough guide: sedentary/resting energy expenditure is 1 MET; moderate activity is 3-5.9 METs, and walking 3 miles per hour is 3.3 METs; high activity is >6.0 METs, and running at 10 minutes/mile is a 10 MET activity.
  • Approximately 60% of older people cannot do 150 min of moderate-to-vigorous activity/week
  • These 9 studies were observational, though they controlled for many risk factors for mortality, such as smoking, blood pressure, fasting blood sugar, lipids, parental history of heart disease, etc. (e.g., see JAMA 1989; 262: 2395). Others of the studies in the meta-analysis also controlled for depression, mobility, chronic diseases, BMI, alcohol, education, diabetes, early parental mortality, and even red meat consumption — though it varied from study to study. The power of this paper is that it combines many studies with many participants showing mortality benefit from lower amounts of physical activity, and in that way gets a bigger picture of the results than a single study can. But, as with all observational studies, are there unanticipated confounders?? (i.e., are there other factors not taken into account which predispose some people to have less activity but put them at higher mortality risk? Perhaps they have unanticipated neurologic conditions? Or have they fallen and are afraid to do exercise, but are at higher mortality risk because of a condition predisposing them to fall?)
  • But, despite this significant limitation (i.e., not having a randomized controlled study with allotment of individuals to differing levels of exercise and seeing what happens), perhaps the strongest message we can give patients is: exercise is good for you and you should do whatever you can (the concern is that by prescribing/insisting on too much exercise for an individual, some people end up doing nothing). I have had success in just getting people to walk 15-20 minutes/day (15 minutes of walking/day is the midpoint of the low activity group, with 250 MET-min), and some of them are able to increase that over time. And many people actually feel better after doing exercise…

Primary Care Corner with Geoffrey Modest MD: New Diabetes Cases Decreasing

14 Dec, 15 | by EBM

By Dr. Geoffrey Modest 

The CDC just released a somewhat encouraging report showing that newly diagnosed cases of diabetes in the US has started to decline (see overall graph below, and the various articles/subgroup analyses at ). A few observations:

  1. There seems to be an overall consistent trend to fewer cases since 2009, though the number of new cases is way above 1980 (the age-adjusted incidence in 1980 was about 3.5/1000 and in 2014 was 6.6/1000) and is basically the same as in 2004-5. Of note, the criteria for diagnosis of diabetes did change in 2010 to include the A1C>=6.5. No doubt this increased the number of diagnoses of diabetes, so the subsequent falloff may even be more significant.
  2. These data includes only those with diagnosed diabetes, and from current epidemiologic studies, it seems that about 25% of diabetics are currently unaware of their diagnosis
  3. The age-adjusted incidence of diagnosed diabetes has trended down for whites, blacks and hispanics, but was only significant for whites. Also, the overall incidence has consistently been much lower in whites (in 2014, was 6.4/1000, in 2009 was 8.0/1000) than blacks (was 8.4/1000 in 2014 and 11.5/1000 in 2009) and hispanics (was 8.5/1000 in 2014 and 11.9/1000 in 2009)
  4. The age-adjusted incidence of diagnosed diabetes has trended down for those with less than high-school education, those with high-school education and those with greater than high-school education, but was only significant for those with greater than high-school education. Also the overall incidence has consistently been much lower in those with greater than high-school education (in 2014, was 5.3/1000, in 2009 was 6.7/1000) than those with high-school education (was 7.8/1000 in 2014 and 9.0/1000 in 2009) and those with less than high-school education​ (was 11.1/1000 in 2014 and 15.4/1000 in 2009)​

So, what does this all mean and how do we interpret it?

  • Part of the issue may be that diabetes has a strong genetic component and some of the leveling off of new cases may be that the steep rise prior to 2008 reflected obesity/lifestyle issues in conjunction with genes, and we have perhaps reached the saturation point for the genetic component (i.e., those predisposed genetically to diabetes have largely already become diabetic)
  • Part of the issue may be changes in obesity. Hard to compare CDC data over the past 20 years, since there was a change in CDC methodology in 2011, but it appears at least that obesity has plateaued and downtrended a bit in adolescents.
  • Some really positive changes have been the decrease in soda consumption: over the past 20 years, there has been a >25% decrease in sales of full-calorie soda, with a “serious and sustained decline”. From 2004-12, children consumed 79% fewer sugar-sweetened beverage calories a day (4% cut in overall calories) — see
  • These changes seem to reflect public health initiatives to decrease soda consumption (since the changes are not related to increased taxes or other financial incentives)
  • McDonalds, for the first time, is closing more stores than they are opening…
  • More people are doing daily exercise than before
  • Unfortunately, the CDC data really shows that the significant changes in new diabetes incidence pertains mostly to white and more-educated people. That being noted, I should add that my experience in a poor minority community is that there really have been pretty consistent improvements overall in lifestyle. I have many more patients who eat better (much less soda/more water for drinks, decreases in junk food) and much more consistently do exercise (mostly walking outside when the weather is nice, or climbing up and down stairs for 10-15 minutes when not. And some who ride bikes or have some home exercise machines, or go to gyms). This has been a pretty striking change over the past 10 years or so. I suspect part of the issue is that I have spent a long time discussing lifestyle changes with my patients over many years, but also (and perhaps more important) is that there has been more general awareness of the importance of eating well and exercising which i am supporting and reinforcing.
  • Though, an important cautionary note. One concern I have raised in many past blogs is that we (scientists and physicians alike) often develop our models of disease based on what seem to be reasonable physiologic data, then generalize it and formalize it as recommendations. We always do this, and there really is no way around it. But we are often wrong. In the 1970s, it seemed reasonable to note that dietary fats are related to atherosclerotic disease (which was a particularly big killer then), and that some fats were worse than others (saturated fats seemed to be the worst then, though there were early data that trans fats were actually the worst by far and still took another 4 decades to be reduced/eliminated, polyusaturated were better but lowered HDL as well as LDL, then the best were monousaturates which raised HDL while lowering LDL). So, we endorsed a low-fat diet, which translated to a high-carb diet (e.g., low fat ice cream, etc., had fewer fats and more carbs). Many of us realized subsequently (though a lot of the data was available many years ago), that eggs really were not so bad in terms of clinical outcomes, and that the high glycemic/high carb diets may well have been the major factor propelling the obesity epidemic and diabetes. So, I think the take-home message here is that we will always be constucting biological/medical models (whether they be about dietary fat, homocysteine, postmenopausal estrogens, etc. etc.); that these models are natural for us to do and really important in determining policy (though best after the appropriate studies with important clinical outcomes are performed, but these often take many years to do, if done at all); but that we always need to be really vigilant in continually questioning the basis of these models through introspection and further studies, and not allowing a model such as the low-fat diet above to last for so long (I believe the goal is something like: do no harm….)


Primary Care Corner with Geoffrey Modest MD: Lifestyle Interventions and Cognition

14 Dec, 15 | by EBM

By Dr. Geoffrey Modest

There have been several recent articles on interventions to prevent cognitive decline, including

  1. An op-ed piece in the NY Times (see​ ) . A few of their points, expanded a bit with the references:
  • A 6-week on-line study with 11,430 participants trained several times a week on cognitive tasks: there were 3 groups–one with 6 training tasks emphasizing reasoning, planning and problem-solving; another group was exposed to a broader range of cognitive tasks including tests of short-term memory, attention, visuospatial processing and mathematics, as is found in commercially available brain training devices; and a control group who did not do specific cognitive tasks but answered obscure questions using online resources (i.e., like Google). They found that each of these tasks improved through this training, but “no evidence was found for transfer effects to untrained tasks, even when those tasks were cognitively closely related” – i.e., there is no evidence that regular use of computerized specific cognitive tasks improves general cognitive function (see Nature. 2010 June 10; 465: 775)
  • Exercise does seem to help:
    • Mice who have regular exercise have more neurons in their hippocampus (that is the site where new memories are formed and converted to long-term memories, and one of the first sites affected by Alzheimer Disease (AD)
    • A small study of 86 women with subjective memory complaints were assigned to 3 groups: resistance training, aerobic training, or balance/tone (the control group). Those in the aerobic training group remembered more items; both aerobic and resistance training led to better spatial memory performance; and there was a significant correlation between spatial memory performance and overall physical capacity (see doi: 10.1155/2013/861893)
    • A study of 155 community-dwelling women 65-75 yo were randomized to resistance training vs balance/tone (control group) and found that resistance training reduced the progression of brain MRI white matter lesions (which are associated with cognitive impairment, and are markers of cerebral small-vessel disease — see J Am Geriatr Soc 2015; 63(10): 2052)
  • They note that BNDF levels (brain-derived neurotrophic factor, which is released in response to neuronal activity) are associated with brain size and function, and is increased with exercise (more below).
  1. A JAMA perspective on mitigating cognitive decline (see doi:10.1001/jama.2015.15390​)
  • In assessing >1200 brains in 2 different aging studies, there was not a great correlation between anatomic findings and cognitive health:
    • The Rush Memory and Aging Project  [Curr Alzheimer Res. 2012; 9(6): 646] of 1556 elders without dementia enrolled from retirement communities beginning in 1997, tracked cognitive function, relying on clinical diagnoses and an array of 21 cognition tests, found that:
      • Physical activity was associated with cognition
      • Incident Alzheimer dementia (AD) was associated with a decline in motor function
      • Social engagement (social activity and support) was associated with global cognition and a slower rate of cognitive and motor decline and disability
      • But at autopsy, the correlation between anatomic changes and cognition were not great: 90% of those meeting clinical criteria of AD did meet pathologic criteria for AD, but 1/2 of those with mild cognitive impairment and 1/3 of those without cognitive impairment also met pathologic criteria for AD.
    • The Religious Orders Study [Curr Alzheimer Res. 2012; 9(6): 628], a study from 1994-2011 of 1162 Catholic nuns, priests, and brothers from 40 groups across the US initially without dementia, similarly used a battery of 21 cognitive tests, also found the same relatively poor correlation as the Rush study between anatomic pathology and AD.
    • ​And, overall overt brain pathology accounted for only 1/2 of the cognitive decline documented
  • Animal studies support the role of BDNF in improving neuronal survival and function (especially in the hippocampus and cortex), and improve synaptic plasticity and long-term memory. Human epidemiologic studies find a correlation between low BDNF levels and AD (though unclear which came first). In this light the community-based Framingham Study was reviewed to see if higher BDNF levels in cognitively healthy adults seemed to protect against future development of AD, found that in 10 years of followup, 140 people developed dementia (117 with AD), and each SD increase in BDNF levels was associated with a 33% decreased risk of dementia overall and AD in particular. Comparing the top to bottom quintile of BDNF levels, there was a 51% decrease in risk of dementia (HR49, p=0.01) and AD (HR.46, p=0.02),  specifically in subgroups of women, people >80 yo and those with college degrees (see  JAMA Neurol. 2014; 71(1): 55)
  • Depression is associated with lower BNDF levels and more hippocampal shrinkage, and antidepressants block the depression-induced drop in BDNF.
  • And what increases BDNF levels??? Increased physical activity, reduced caloric intake, social support (and lack thereof is associated with lower BDNF levels). A review found that aerobic exercise increases BDNF as well as improves hippocampal atrophy, improves memory function, and reduces depression [see Neuroscientist 2012: 18(1): 82].  By the way, there are also data showing exercise is associated with decreases in b-amyloid in a transgenic Alzheimer mouse model.
  • Increased BDNF also reduces risk of stroke (I could not find this reference to review the primary data).
  • Also there are data finding that blood VEGF levels (vascular endothelial growth factor) may be protective of brain function. For example, a study found that VEGF levels in the CSF were higher in those with higher cognitive abilities, in comparing those with normal cognition to mild cognitive impairment to those with AD. And, exercise boosts VEGF.. ​
  1. A more recent article undercut the exercise/dementia link: the LIFE trial (Lifestyle Interventions and Independence for Elders) looked at the effects of a 24-month physical activity program for 1635 community-living people in the US, aged 70-89, who were at risk for mobility disability but able to walk 400 meters (seeJAMA. 2015;314(8):781-790). They assessed cognitive function as a secondary outcome (though this study was not specifically powered for this outcome) using several instruments, especially the Digit Symbol Coding subtest of Wechsler Adult Intelligance Scale and the revised Hopkiins Verbal Learning Test (12-item word list recall), comparing those in the structured moderate-intensity physical activity program of walking, resistance training, and flexibility exercises, to those in a health education program. They found no overall benefit to exercise, except in those >80 yo and in those with poorer baseline physical performance, noting an improvement in executive function in these groups (p=0.01). However, they did not measure BDNF levels, which may be particularly important in a group of patients who were physically challenged at baseline and perhaps unable to exercise very much. Also, only 57 patients overall developed dementia though 132 developed mild cognitive impairment (this LIFE was a well-educated cohort, and therefore more likely to show less cognitive decline by the cognitive tests).

So, things are usually more complicated than they seem. We are all (myself certainly included) prone to look for simple solutions that make sense physiologically. It makes sense that AD and dementia in general are neurologic degenerative disorders associated with specific anatomic pathology, but the actual correlation is not so clear. It also makes sense that keeping the brain active, through suduko or other cognitive puzzles would help preserve brain function, but it seems that overall brain function does not improve (though performance of the specific task, suduko in this case, does get better….).  However, the above studies suggest that there do seem to be a large array of potential benefits from exercise, including decreased depression, improved memory, and decreased progression of cognitive decline. And the data also support the benefit of a Mediterranean diet. Bottom line: I think it is not so useful to try to break down the specific components of diet or exercise which is beneficial (a tad reductionist), that cognitive decline is undoubtedly multifactorial (again arguing against a reductionist approach), but that nutrition and exercise are very likely necessary for brain health and likely more so than the too-often-advertized easy fixes of on-line memory games, etc. And this realization is a bit of a game-changer, in that perhaps our primary therapeutic focus in elderly people concerned about cognitive decline really should be on a healthy diet and exercise, which not only are good for the body but also for the mind.

For some other blogs on cognitive function, see: showing that chocolae improves cognitive function reviewed the Mediterranean diet and cogntive decline, showing decreased AD and also larger brain volumes, which tracked with the degree of adherence to a Mediterranean diet. ​


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