There is little doubt that changes in diet and physical activity can seriously reduce risk for cardiovascular disease (and countless other conditions from arthritis to cancer).

But changing diet and activity levels both at individual and population levels remains a major challenge. Not that these changes are not possible (they are), but rather that practitioners don’t know where to start and often default to well-meaning but useless advise (eat less - move more).

Last week, the American Heart Association (AHA) Prevention Committee of the Council on Cardiovascular Nursing released a comprehensive collation of the current evidence regarding interventions to promote physical activity and dietary lifestyle changes for cardiovascular risk factor reduction in adults.

Although the document does not specifically address weight management, the principles and learnings from this document certainly apply as much to managing excess weight as they do to dealing with other chronic conditions like hypertension, dyslipidemia or diabetes.

The following intervention strategies and principles meet the highest levels of evidence (Level A or B):

Cognitive-behavioral strategies for promoting behavior change:

• Design interventions to target dietary and PA behaviors with specific, proximal goals/goal setting (Level of evidence: A)

• Provide feedback on progress toward goals. (Level of evidence: A)

• Provide strategies for self-monitoring. (Level of evidence: A)

• Establish a plan for frequency and duration of follow-up contacts (eg, in-person, oral, written, electronic) in accordance with individual needs to assess and reinforce progress toward goal achievement. (Level ofevidence: A)

• Utilize motivational interviewing strategies, particularly when an individual is resistant or ambivalent about dietary and PA behavior change. (Level of evidence: A)

• Provide for direct or peer-based long-term support and follow-up, such as referral to ongoing community-based programs, to offset the common occurrence of declining adherence that typically begins at 4–6 months in most behavior change programs. (Level of evidence: B)

• Incorporate strategies to build self-efficacy into the intervention. (Level of evidence: A)

• Use a combination of the above strategies (eg, goal setting, feedback, self-monitoring, follow-up, motivational interviewing, self-efficacy) in an intervention. (Level of evidence: A)

• Use incentives, modeling, and problem solving strategies. (Level of evidence: B)

Intervention processes and/or delivery strategies:

• Use individual- or group-based strategies. (Level of evidence: A)

• Use individual-oriented sessions to assess where the individual is in relation to behavior change, to jointly identify the goals for risk reduction or improved cardiovascular health, and to develop a personalized plan to achieve it. (Level of evidence: A)

• Use group sessions with cognitive-behavioral strategies to teach skills to modify the diet and develop a PA program, to provide role modeling and positive observational learning, and to maximize the benefits of peer support and group problem solving. (Level of evidence: A)

• For appropriate target populations, use Internet- and computer-based programs to target dietary and PA change; evidence is less for targeting PA alone; adding a form of E-counseling improves outcomes. (Level of evidence: B)

• Use individualized rather than nonindividualized print- or media-only delivery strategies. (Level of evidence: A)

Addressing cultural and social context variables that influence behavioral change:

• Utilize church, community, work, or clinic settings for delivery of interventions. (Level of evidence: B)

• Use a multiple-component delivery strategy that includes a group component rather than individual-only or group-only approaches. (Level of evidence: A)

• Use culturally adapted strategies, including use of peer or lay health advisors to increase trust; tailor health messages and counseling strategies to be sensitive to the cultural beliefs, values, language, literacy, and customs of the target population. (Level of evidence: A)

• Use problem solving to address barriers to PA and dietary change, such as lack of access to affordable healthier foods, lack of resources for PA, transportation barriers, and poor local safety. (Level of evidence: B)
• Nothing revolutionary here or in fact very different from the way most evidence-based weight management programs already work (scams excluded). In fact this list of recommendations provides a valuable checklist to make sure your program is hitting all the relevant buttons

Good to know that there is actually strong scientific evidence to support most of what we do at WeightWise.

AMS
Edmonton, Alberta

Hat tip to Sebely for pointing me to this article

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Artinian NT, Fletcher GF, Mozaffarian D, Kris-Etherton P, Van Horn L, Lichtenstein AH, Kumanyika S, Kraus WE, Fleg JL, Redeker NS, Meininger JC, Banks J, Stuart-Shor EM, Fletcher BJ, Miller TD, Hughes S, Braun LT, Kopin LA, Berra K, Hayman LL, Ewing LJ, Ades PA, Durstine JL, Houston-Miller N, Burke LE, & on behalf of the American Heart Association Prevention Committee of the Council on Cardiovascular Nursing (2010). Interventions to Promote Physical Activity and Dietary Lifestyle Changes for Cardiovascular Risk Factor Reduction in Adults. A Scientific Statement From the American Heart Association. Circulation PMID: 20625115

Yesterday, I blogged about the finding that increased body fat appears to precede lower activity levels and not the other way round (which is probably why attempts to increase physical activity in kids has so far not done much in terms of obesity prevention).

Almost on cue, the latest issue of the Canadian Medical Association Journal (CMAJ) publishes a study by McMaster University’s John Cairney and colleagues, suggesting that kids with developmental coordination problem (perhaps unfairly described as “clumsiness”) may be particularly prone to weight gain.

The study builds on previous reports that kids with developmental coordination disorder were found to be less likely to participate in physical activities.

The researchers studied 2278 (95.8%) of 2378 fourth grade kids (ages 9 to 10) from 75 schools in southwestern Ontario, Canada. Children were followed up over two years, from the spring of 2005 to the spring of 2007.

Not only did the 111 children (46 boys and 65 girls) who had possible developmental coordination disorder have a higher mean BMI and waist circumference at baseline than the other kids, but these differences persisted or increased slightly over time.

In fact, kids with with possible developmental coordination disorder were four times more likely to become obese over the course of the study.

While this study is of course strongly suggestive of less physical activity being a risk factor for childhood obesity, it should be noted that the researchers did not directly measure activity levels. There was also no report of their energy intake or their mental health status (e.g. cognitive ability, depression, attention deficit disorder, etc.), which may significantly affect ingestive behaviours.

There was also no mention of low birth weight, which may be associated both with developmental coordination disorder and excess post-partum weight gain.

Finally, as the authors themselves are careful to note, obese kids have been noted to be less coordinated - so again, it is not clear if the sequence here is “clumsiness -> inactivity -> obesity” or “obesity -> inactivity -> clumsiness” or even “obesity -> clumsiness -> inactivity”.

As always, solving ‘chicken or egg’ questions from cross-sectional or even longitudinal data remains challenging. This is exactly why we need more intervention studies.

AMS
Edmonton, Alberta

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The current dogma is that our kids are getting bigger because of sedentariness and inactivity. Based on this dogma, attempts at reversing the childhood obesity epidemic focus largely on increasing physical activity -so far with little to show for.

Now, a study by Brad Metcalf and colleagues from Plymouth, UK, published online in the Archives of Disease in Childhood, suggests that it may be fatness leading to inactivity rather than the other way round.

For this study, the researchers analyse data from a prospective cohort study examining children annually from 7 to 10 years. Participants were 202 children (53% boys, 25% overweight/obese) recruited from 40 Plymouth primary schools as part of the EarlyBird study.

Importantly, the researchers used accelerometers worn by the children for 7 consecutive days at each annual time point to measure actual levels of physical activity.

In addition, actual body fat per cent was measured annually by dual energy x ray absorptiometry.

While body fat percentage was predictive of changes in physical activity over the following 3 years, physical activity levels were not predictive of subsequent changes in body fat.

Thus, while a 10% higher body fat at age 7 years predicted a relative (albeit modest) decrease in daily moderate and vigorous intensities of 4 min from age 7 to 10 years, greater physical activity at 7 years did not predict a relative decrease in body fat between 7 and 10 years.

The authors conclude that the often found association between lower activity levels and higher body fat may be the result of fatness driving inactivity rather than inactivity driving body fat. Thus, physical inactivity appears to be the result of fatness rather than its cause.

Not surprisingly perhaps, they also note that this “reverse causality” may nicely explain why attempts to tackle childhood obesity by promoting physical activity have been largely unsuccessful.

Given, as blogged previously, that the key determinant of body fatness may well be determined by what happens in utero - the causal sequence for the childhood obesity epidemic may well be:

in utero epigenetic programing > fatter offspring > less active kids.

Thus, while interventions to increase physical activity in kids may well have an important benefits on fitness, balance, coordination and numerous other aspects of health - anyone expecting more activity in kids to reverse the childhood obesity epidemic may well be barking up the wrong tree.

AMS
Edmonton, Alberta

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Metcalf BS, Hosking J, Jeffery AN, Voss LD, Henley W, & Wilkin TJ (2010). Fatness leads to inactivity, but inactivity does not lead to fatness: a longitudinal study in children (EarlyBird 45). Archives of disease in childhood PMID: 20573741

One of my favourite memories of Berlin (my home town) is the annual bicycle day, when hundreds of thousands of cyclists from all corners of Berlin converge to the centre of the city, essentially stopping all other traffic (at least for a while).

Yesterday, as I arrived in Berlin it was hard to overlook the fact that the city was firmly in the grip of bicyclists - over 200,000 of them!

Old and young, families, retirees, on all kinds of bicycles and bike-like contraptions.

Berlin is certainly one of the most bikeable cities in Europe. Indeed bicycling to university and later to work was part of my regular routine (a habit that regular readers will recall I still try to maintain in Edmonton).

I well remember riding around Berlin with two kids on my bike - one in front, one in the back - nothing to it. In fact that was pretty much standard practice. And, this was well before bike helmets (those were for racers and people who liked to show off).

In fact the lack of bike helmets in Europe is pretty standard - it’s still the rare cyclist who will bother to wear one - especially on a day like yesterday, where the city essentially belongs to bikes. Notably, a study by Dankmar Boehning and colleagues reported only 4% helmet usage amongst Berlin bycylists in 1999 - probably not much has happened since.

In any case, I wish I’d known about the bicylce day earlier. Also wish I had had a bike - I would have joined in for sure.

Maybe next time - or even better - let’s have bike only days in Edmonton! (we already have a bike month)

AMS,
Berlin, Germany

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Böhning D, Boose R, Kurzawski S, & Saul N (2002). Bicycle safety helmet usage in Berlin 1999: an observational study. Sozial- und Praventivmedizin, 47 (2), 124-7 PMID: 12134730

Dr. John Blundell

Yesterday, I had the pleasure of hosting John Blundell, at the Research in Progress seminar series at the Alberta Diabetes Institute.

Dr. Blundell is Professor of bio-psychology at the University of Leeds, UK, and is certainly one of the preeminent authorities on the bio-psychology of ingestive behaviour.

His presentation with the rather provocative title, “Will exercise make you fat?”, started with a broadside at the media, which lately has been quite active in promoting this notion.

However, as Blundell pointed out, this simplistic message is far from accurate in that the relationship between physical activity and its impact on ingestive behaviour and body weight is anything but straightforward.

For one, although short-term studies (days) do often show an increase in appetite, this is by no means regularly observed in longer-term studies (weeks).

In a paper he recently published in the Journal of Clinical Endocrinology and Metabolism, Blundell recently examined the effects of medium-term exercise on fasting and post-prandial levels of appetite-related hormones and subjective appetite sensations in overweight and obese individuals.

The study included 22 sedentary individuals who took part in a 12-wk supervised exercise programme (five times per week, 75% maximal heart rate) and were requested not to change their food intake during the study.

Not only did exercise result in a significant, albeit modest (~3 Kg), reduction in body weight and fasting insulin and an increase in ghrelin plasma levels but also in a reduction in fasting hunger sensations.

A significant reduction in postprandial insulin plasma levels and a tendency toward an increase in the delayed release of glucagon-like peptide-1 (90-180 min) and a greater suppression of postprandial ghrelin.

Thus, although exercise-induced weight loss was associated with physiological and biopsychological changes towards an increased drive to eat in the fasting state, this compensatory effect seems to be balanced by an improved satiety response to a meal and improved sensitivity of the appetite control system.

However, as Blundell pointed out, these mean changes hide the immense diversity between individuals.

Based on these studies it appears impossible to predict in advance how individuals will respond: Some people, in response to exercise, will be hungry and may overeat – others may find that they are much better in controlling their food intake.

Importantly, all subjects, irrespective of their body weight, showed a reduction in their amount of body fat and improvements in risk markers like physical fitness and blood pressure.

Thus, Blundell concludes, exercise does reduce body fat (even in people who do not lose weight) and has beneficial effects on important health parameters.

The answer therefore clearly is: no, exercise does not make you fat, but don’t expect to lose a lot of weight.

The many important benefits of exercise can, unfortunately, not be measured on a scale.

AMS
Edmonton, Alberta

Martins C, Kulseng B, King NA, Holst JJ, & Blundell JE (2010). The effects of exercise-induced weight loss on appetite-related peptides and motivation to eat. The Journal of clinical endocrinology and metabolism, 95 (4), 1609-16 PMID: 20150577