Controversial surgical center for teens

On January 15, 2010, in Uncategorized, by Andrea

I’m of two minds of this.

At 17, I would not have been ready for a life-altering event like this.  At times, I don’t think I was really ready at 25.  At 17, I would not have been ready for the responsibility of the vitamin regimen for RNY.  Maybe a non-malabsorptive surgical option like VSG or AGB — but not DS or RNY.  But I know there has to be an option for those that ARE.

From the Denver Post:

Surgical hope for obese teens

Rose opens the first bariatric program for youths in Colorado — amid controversy

Kat Borst tried low-carb and no-carb and South Beach and Weight Watchers and so many other diets she “can’t even list them all.” None worked.

So at 17 years old and 280 pounds, Borst underwent surgery to squeeze her stomach smaller. She’s lost 54 pounds since June and now hits the gym with her dad, even though she couldn’t climb a flight of stairs without wheezing before.

Borst’s weight loss, and the success of other teens who’ve had Lap-Band or gastric-bypass surgery at Rose Medical Center in Denver, have led the hospital to open a new bariatric program for teens — the first of its kind in Colorado.

The new center comes as childhood obesity has reached epic levels — about 17 percent of American children and teens are considered obese — but also as controversy looms about the safety of bariatric surgery for adolescents.

The program at Rose is tailored to teens, with several weeks of pre- and post-surgery sessions on nutrition, psychology and behavioral changes.

“Being 17 is really hard,” said Dr. Michael A. Snyder, a bariatric surgeon who will direct the center. “Being a teen with bariatric surgery is very difficult. Being a morbidly obese teen is a total nightmare.”

Snyder, who has done more than 2,800 bariatric surgeries and developed a special high-nutrition food for his patients, said he makes sure teens “are ready for a life-long commitment” before he performs surgery, which costs about $9,500 and is only sometimes covered by insurance. For most adolescents, Snyder places a Lap-Band, which is gradually tightened to reduce stomach capacity to about 10 to 20 percent of its original space.

It should take about 4 ounces of protein — a chicken breast about as big as a computer mouse, for example — to make a patient with a Lap-Band feel “Thanksgiving full” for two or three hours, Snyder said. The bariatric center counsels teens not to waste calories on frappachinos or sodas or really anything without protein — otherwise they don’t lose the weight and could suffer from malnutrition.

Doctors disagree on rules

Snyder, one of few bariatric surgeons in the state who will operate on people younger than 18, said the ideal patient is at least 100 pounds overweight and has tried dieting and exercise without success. The doctor cites studies showing a less than 3 percent chance that a morbidly obese person will lose the excess weight and keep it off on their own.

“It’s the safest bet in Vegas,” he said. “If you are morbidly obese, the rules are different for you.”

But other physicians argue Lap-Band and gastric-bypass surgery on adolescents is irresponsible and unsafe.

“I am so disgusted with this,” said Dr. Wendy Scinta, a pediatric bariatrician on the board of the American Society of Bariatric Physicians. “In children, it’s still considered experimental.”

Scinta, who runs a medical weight-loss clinic for children and teens in Syracuse, N.Y., said adolescents who have bariatric surgery could end up with severe vitamin deficiencies and require surgery later to remove “elephant skin,” the kind that hangs off the body when weight loss happens too quickly without maintaining muscle mass.

“It’s kind of young to be going through something so drastic,” she said. “We’re at the point where the obesity epidemic is happening faster than we can get our arms around it, but especially with children, we do

have some time. We need to give them a shot at doing something less aggressive at first.”At Scinta’s clinic, kids take medication to control their insulin levels, they learn — with their parents — to change the family diet to five small meals per day, and they are hooked up with pedometers and an exercise program. Childhood obesity often is caused by family or medical problems, Scinta said.

“Kids are easy,” she said. “You really give them their life back or give them a life if they have never had one.”

Scinta said she would recommend bariatric surgery — and she never has for a child or teen — only for a kid who weighed 600 or 700 pounds, couldn’t get out of bed and was “truly on death’s door.”

Doctors said it’s often difficult to discern the parents’ desires from the child’s when considering bariatric surgery for an adolescent.

“The hardest thing in the pediatric population is determining who is deciding they should have surgery,” said Dr. Scott Fisher, director of bariatrics at Penrose-St. Francis Health Services in Colorado Springs. “Is it society? Is it the parents who are embarrassed of their child’s weight? For 40-year-olds, it is because they are choosing themselves to make themselves healthier.”

The Penrose bariatric surgery center has operated on only 10 to 15 teens in the last eight years, Fisher said.

Diet still a challenge

Borst, who is 18 now and working toward her goal weight of 145 pounds, wishes she would have had her Lap-Band surgery sooner in life. She struggled with her weight since age 4, was ridiculed throughout elementary school and left high school for an online program because of all the teasing.

Now she’s planning on college next fall.

“I’m getting more confident,” she said. “It’s not fully built up yet because I’m still pretty big.”

Still, Borst’s life is different now. Before her surgery she “was feeling like absolute death.” Now she enjoys hopping on a treadmill or stationary bike and playing badminton. Her clothes, she said, are “falling off.”

Changing her diet has been the biggest challenge.

“I’m not going to lie; I have a lot of spells where I lose my determination,” she said. “I get disappointed in myself. Every teenager that goes into this has to know it’s not easy.”

Jennifer Brown: 303-954-1593 or

The WLS world is buzzing today.  And being the conformist that I am, you know that I’m going to add to it — right?  Cause I’m so meek and un-opnionated and all.  (you really should have put that drink down before reading that, eh?)

So one of our stars — Carnie Wilson — had her new show on last night.  I didn’t watch it.  No other reason than I was desperate for the silence.  To be honest, I’m not certain I get that channel anyway.  But after a day of two sick kids whining, a sick husband that I will not discuss too much in the blog because he may actually read this, and children’s programming droning on and on all day long, I longed for silence.  The TV was off as soon as the kids went to bed.  Not that I could have concentrated on a show because the kids did not actually go to sleep, just to bed.  Which is a misnomer as well since the toddler can get out of his bed and does not appreciate “bed time” as much as I do.

In any case, without having watched the show, I can still gather what happened on the show from all of the buzz.   Carnie has regained weight from her low weight after gastric bypass.  Considering her two pregnancies post RNY and her cross-addictions, her life in the spotlight, and all of the stress therein — not shocking.  Hell, I’ve been in her shoes for part of this, and so I get where she is.

Twice, actually.

And until you’ve been pregnant post RNY, don’t you dare condemn her.

Let me tell you something about post RNY pregnancy:  RNY rules go completely out the window.

RNYers are told to go protein first.  But when pregnant, you have to stay out of ketosis to avoid fetal brain damage.  So that sandwich?  Yeah, eat it.

RNYers are supposed to lose weight.  But when pregnant, you’re supposed to gain it.  So the scale is supposed to go up?  Wha?

And vitamins.  Really?  Who do you listen to?  The OB who has never had an RNY patient in their entire career?  The skinny nutritionist that is only going off book learning?  The surgeon who hasn’t had a nutrition class in ten years and is male (and thus has never had the hormones swimming through his veins that are making you want that doughnut from Krispy Kreme?).  Cause, well, each tells you something completely different and are completely contradicting each other.

How about that special level of hell called a glucose tolerance test that determines gestational diabetes?  50g of glucose in a slightly carbonated, traffic-cone orange syrupy-sweet liquid form that can reduce a hormonal RNYer into a fetal ball of hypoglycemic dumpage in ten minutes flat.  It’s great when our doctors guilt us into this test — “if you don’t do this, you’re putting your baby at risk” — and I wish I were kidding on that but yes I was told that very line.  This is the guilt trip I got by telling the doctor that I would NOT put myself through this I would be putting my baby at risk despite the fact that dumping and the severe reactive hypoglycemic reaction that I WOULD HAVE would maybe stress the baby and put the baby at risk.  Because telling a mother-to-be this is just what we should do, yes?

Each prenatal appointment had a scale — banishing my own did no good.  I cannot tell you how hard it is to see the scale go up.  And up.  And up more.  Knowing that it HAD to go up for the safety of the baby.  Knowing that I had to eat despite not really wanting to.  How many times I stared at my reflection in the mirror in horror — where normal mothers would stare in awe at their bellies I would be in disgust at the fat — because I didn’t get a cute baby belly — my skin just filled back out with fat.  It was ironic that when I was fat people thought I was pregnant and when I was pregnant people just thought I was fat.  Jeans I swore I’d never wear again, but had kept “just in case” were pulled back out and worn again.  Stores I swore I’d never walk back in?  Yeah, you guessed it.

I had horrible hypoglycemia with my first pregnancy.  To the tune of passing out every five minutes.  We couldn’t figure it out — until I added in a SERIOUS amount of simple carbs back into my life.  Guess what — they ARE addictive.  Do you know how hard it is to get those back out of your life after you’re told to rely on them to keep you upright for 9 months?  While trying to deal with all the hormones that come with pregnancy?  OMG my house was not a happy place to be after the baby came — detox off carbs AND post-partum hormones?  It’s a wonder I didn’t end up divorced.

The family

But all of this was mixed with happiness of having a child.  Knowing that I had this surgery that gave me the opportunity to have a baby.  If I had not had the surgery, there was a chance of not having a child.  I’ll never know since I never tried to get pregnant prior to surgery.

And then there’s the “after.”

Some women are lucky to lose all their pregnancy weight — and some even lost more than their pregnancy weight.  I wasn’t that lucky.  Sure, I lost some of it, but not all of it.  I wasn’t one of the lucky ones.  I had to work at it.  Even now, I’ve recently just lost all of my pregnancy weight from my first post op pregnancy.

The point is this — it’s easy to sit back and criticize and judge someone — especially someone who is out there in the spotlight.  But unless you’ve been in those shoes you have no idea what it’s like.  A post-op pregnancy is not like a standard pregnancy at all.  It bends, if not breaks WLS rules — and sometimes it’s really really hard to go back to those rules after almost a year off them.  It takes seven days to make a habit — so what happens in 40 weeks?

Carnie is one of us.  She has the same struggles as we all do, but we have one luxury that she doesn’t have — privacy.  Maybe she could choose to make her life a bit less public, but to some degree, her life will never be private given her past.  So let’s give her what we would all want for ourselves — support and compassion.  Cause who knows — maybe YOU would end up in the same position as she is in, despite saying “That will never be me.”

Osteoporosis Basics

On January 14, 2010, in Minerals, by Andrea

Good, basic info.


Childhood obesity stats in preschoolers

On January 13, 2010, in Uncategorized, by Andrea

Obesity Prevalence Among Low-Income, Preschool-Aged Children—United States, 1998-2008

JAMA. 2010;303(1):28-30.

MMWR. 2009;58:769-773

1 figure, 1 table omitted

Childhood obesity continues to be a leading public health concern that disproportionately affects low-income and minority children.1 Children who are obese in their preschool years are more likely to be obese in adolescence and adulthood2 and to develop diabetes, hypertension, hyperlipidemia, asthma, and sleep apnea.3 One of the Healthy People 2010 objectives (19-3) is to reduce to 5% the proportion of children and adolescents who are obese.4 CDC’s Pediatric Nutrition Surveillance System (PedNSS) is the only source of nationally compiled obesity surveillance data obtained at the state and local level for low-income, preschool-aged children participating in federally funded health and nutrition programs. To describe progress in reducing childhood obesity, CDC examined trends and current prevalence in obesity using PedNSS data submitted by participating states, territories, and Indian tribal organizations during 1998-2008. The findings indicated that obesity prevalence among low-income, preschool-aged children increased steadily from 12.4% in 1998 to 14.5% in 2003, but subsequently remained essentially the same, with a 14.6% prevalence in 2008. Reducing childhood obesity will require effective prevention strategies that focus on environments and policies promoting physical activity and a healthy diet for families, child care centers, and communities.

PedNSS is a state-based surveillance system that monitors the nutritional status of children from birth through age 4 years enrolled in federally funded programs that serve low-income children. For all states except California and North Carolina, data come exclusively from the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).* In California, data are exclusively from Medicaid-funded programs. North Carolina submits data from both WIC (95.5%) and non-WIC programs (4.5%).{dagger} For the states included in this analysis, 21.0% of children aged 2-4 years are covered by PedNSS. On average, children are seen twice a year by the program; height and weight are measured each time. Data are collected at the clinic level and submitted to CDC for analysis. Federally funded programs submit data on weight, height (measured by trained staff using a standard protocol during clinic visits), age, sex, and the race/ethnicity reported by the child’s parent or caregiver. CDC uses weight, height, and age data to calculate body mass index (BMI) (weight [kg]/ height [m2]). For children aged 2-4 years, obesity is defined as BMI-for-age ≥95th percentile based on the 2000 CDC sex-specific growth charts.5 CDC performs routine edits to assess data quality. An error flag is applied to height or weight data that are either missing, miscoded, or biologically implausible (e.g., height-for-age z-score <–5.0 or >3.0, body mass index [BMI]-for-age [children aged ≥2 years] z-score <–4.0 or >5.0, weight-for-age z-score <–4.0 or >5.0, or BMI-for-age [children aged ≥2 years] z-score <–4.0 or >5.0). All flagged data are excluded from PedNSS analyses.

CDC randomly selected one record per child per year to estimate obesity prevalence in 1998, 2003, and 2008. To assess the change in obesity prevalence in PedNSS overall and by race/ethnicity, prevalence was estimated using data only from the subset of federally funded programs that participated in 1998, 2003, and 2008 (N = 37). The average annual change in obesity prevalence during 1998-2003 and 2003-2008 was estimated for each PedNSS program. If data for a program were unavailable for a given year but were available for the preceding or subsequent year, CDC substituted the data for the adjacent year and calculated the annual change to account for the shorter or longer period. Chi-square tests for difference in proportions were conducted across each period, and tests were statistically significant (p<0.05) unless otherwise noted in this report.

During 1998-2008, the number of federally funded programs reporting data to PedNSS varied from 43 to 52. In 2008, records on approximately 8 million children were submitted from 43 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, and six Indian tribal organizations. The overall prevalence of obesity among low-income, preschool-aged children increased from 12.4% (n = 1,999,970) in 1998 to 14.5% (n = 1,967,625) in 2003 and 14.6% (n = 2,222,410) in 2008. Obesity prevalence increased 0.43 percentage points annually during 1998-2003, but only 0.02 percentage points annually during 2003-2008. Obesity increased across all racial/ethnic groups during 1998-2003, with the exception of Asian/Pacific Islander (A/PI) children. However, during 2003-2008, obesity remained stable among all groups except American Indian/Alaska Native (AI/AN) children. In 2008, prevalence was highest among AI/AN (21.2%) and Hispanic (18.5%) children, and lowest among non-Hispanic white (12.6%), non-Hispanic black (11.8%), and A/PI (12.3%) children.

In 2008, only programs in Colorado and Hawaii had obesity prevalences ≤10%. The two federally funded programs with prevalence >20% were Indian tribal organizations. Of the 41 PedNSS programs supplying data for 1998-2003, a total of 38 (93%) reported an increase in obesity prevalence. In contrast, of the 44 programs supplying data for 2003-2008, 22 (50%) reported an increase in obesity, whereas 14 (32%) reported no change, and eight (18%) reported a decrease.

Reported by:

AJ Sharma, PhD, LM Grummer-Strawn, PhD, K Dalenius, MPH, D Galuska, PhD, M Anandappa, MS, E Borland, H Mackintosh, MSPH, R Smith, MS, Div of Nutrition, Physical Activity and Obesity, National Center for Chronic Disease Prevention and Health Promotion, CDC.

CDC Editorial Note:

Reduction of obesity among children and adolescents is a national priority in the United States.4 The results presented in this report indicate that among low-income, preschool-aged children participating in federally funded nutrition programs, the prevalence of obesity increased during 1998-2003, but stabilized during 2003-2008. In 2008, the national prevalence of obesity in this group remained highest among low-income Hispanic and AI/AN children and continued to increase among AI/AN children. These results suggest overall progress in stabilizing the prevalence of childhood obesity in a subset of low-income, preschool-aged children. However, these results should be confirmed through additional research using other data sets.

Children in preschool age groups are a priority for surveillance because obesity trends in this group can serve as a bellwether for trends in older children and adults.2 PedNSS currently serves as the only source of national obesity prevalence data compiled specifically on low-income, preschool-aged children. Because PedNSS nutritional data are dependent on enrollments in participating federally funded programs, PedNSS results are subject to variations in enrollment in these programs in each state. However, the effect of such variations on PedNSS results is difficult to determine. Conditions within a state that differentially affect the enrollment of children with varying prevalences of obesity could affect state or national results. In addition, changes in the proportion of children from each state might alter the results. For example, California, the largest data contributor to PedNSS, has one of the highest prevalences of obesity. The percentage of the total PedNSS sample provided by California decreased from 20.2% in 1998 to 13.6% in 2008. However, even deletion of all California data would not alter the overall results; an increase from 1998 to 2003 would still be observed, followed by stabilization through 2008. Furthermore, stabilization or declines were observed in half of the individual federally funded programs in PedNSS.

To maintain the consistency of PedNSS data, methods for data collection and recording are set nationally and are uniform across states and participating federal programs. The procedures for collecting height and weight data did not change during 1998-2008, with the exception of an increasing use of digital scales. Given the procedures within the WIC program for regular calibration of scales, this change should not affect rates of obesity. CDC has stringent requirements for data quality and uses standardized procedures for data cleaning; data files that do not meet these standards are rejected, as are records that do not meet standards for acceptable heights and weights.

The reason for the stabilization of overall obesity prevalence among these children during 2003-2008 is not known and likely is complex. One factor might be prevention efforts within state and local WIC programs targeting behaviors related to obesity in children. For example, certain initiatives in WIC{ddagger} have attempted to raise public awareness, acceptance, and support of breastfeeding, increased the percentage of low-fat or fat-free milk vouchers issued for children aged >2 years,§ and reduced television viewing.6 Recommendations such as those from the Institute of Medicine’s Preventing Childhood Obesity report also might have spurred greater attention to obesity prevention for all children.7

The National Health and Nutrition Examination Survey (NHANES) also has found a stabilization of obesity prevalence in U.S. children. NHANES found no significant increase in obesity prevalence during 1999-2006 in children aged 2-19 years.8 This apparent plateau remained even after adjusting for differences in prevalence by age group. Trends in the 2-5 year age group were not analyzed separately because of small sample size. For NHANES 2003-2006, the overall prevalence of obesity (BMI-for-age ≥95th percentile) for children aged 2-5 years was 12.4% (standard error = 1.0%), lower than the rates for both 2003 and 2008 described in this report.

The findings in this report are subject to at least three limitations. First, the proportion of children participating in federally funded nutrition programs increased during 1998-2008, as evidenced by the 11% increase in the number of children in these analyses (i.e., from 1,999,970 in 1998 to 2,222,410 in 2008). However, how the addition of these children might have affected the prevalence of obesity is unknown. Second, the percentage of the total PedNSS dataset that is made up of WIC records increased from 76% in 1998 to 85% in 2008. If the prevalence of obesity were lower in WIC than in non-WIC programs, this increase could partially explain the observed trends. However, when the analysis was conducted using only data from WIC, results were not substantially different. Finally, PedNSS data are not representative of all low-income, preschool-aged children in the United States because not all states participate in PedNSS and not all low-income children participate in federally funded programs.

Childhood obesity remains a serious public health problem even among this subset, particularly among AI/AN children. A sustained and effective public health response is necessary across the United States to reduce childhood obesity. Strategies should emphasize improving environments and policies that promote physical activity and a healthy diet.


8 Available.

*Eligibility criteria for WIC includes a family income ≤185% of the poverty income threshold, based on U.S. Poverty Income Guidelines, available at A person who participates or has family members who participate in certain other benefit programs, such as the Medicaid or Aid to Families with Dependent Children/Temporary Assistance to Needy Families, automatically meets the income-eligibility requirement.

{dagger}Including the Early and Periodic Screening, Diagnosis, and Treatment Program, other Medicaid-funded child health programs, and Title V Maternal and Child Health Programs. Eligibility criteria includes a family income ≤200% of the poverty income threshold, based on U.S. Poverty Income Guidelines. The non-WIC records accounted for 24% of records in 1998, 19% in 2003, and 15% in 2008.

{ddagger}Additional information available at

§Additional information available at

Metabolism shifts

On January 13, 2010, in Uncategorized, by Andrea

JAMA article  about metabolism shifts.

Extra Calories Cause Weight Gain—But How Much?

Martijn B. Katan, PhD; David S. Ludwig, MD, PhD

JAMA. 2010;303(1):65-66.

How much weight would an individual gain by eating an extra chocolate chip cookie every day for life? One approach to answering this question, frequently used in textbooks1 and scientific articles, is based on the assumption that a pound (454 g) of fat tissue has about 3500 kilocalories (kcal). Thus, a daily 60-kcal cookie would be expected to produce 0.2 kg (0.5 lb) weight gain in a month, 2.7 kg (6 lb) in a year, 27 kg (60 lb) in a decade, and many hundreds of pounds in a lifetime. This of course does not happen. In this article, the physiology of weight gain and loss is reviewed, and the amount of reduction of caloric intake necessary to avoid becoming overweight or obese is estimated.

Weight Change Is Self-limiting

Body weight remains stable as long as the number of calories consumed equals the number expended through physical activities and metabolic processes. When energy intake increases above expenditure, the excess is used to build new tissue, and weight gain results. However, weight gain does not continue indefinitely. Carefully controlled overfeeding experiments show that calorie expenditure increases progressively because of the energetic costs of maintaining the newly created tissue. A person who consumes an extra cookie every day will initially experience weight gain, but over time an increasing proportion of the cookie’s calories will go into repairing, replacing, and carrying the extra body tissue. After a few years of daily cookie eating, weight gain will level off at approximately 2.7 kg (6 lb).2 Thus, a one-time step-up in caloric intake will cause body weight to increase asymptotically to a new, stable level.

The converse occurs when an individual reduces food intake. As body size diminishes, so does the amount of fuel needed to maintain and move it, and weight settles at a new steady level. In addition, weight loss produces changes in hormones, the autonomic nervous system, and the intrinsic efficiency of muscle that serve to conserve energy.3 Therefore, additional weight loss can only be achieved by a more severe diet or a more arduous physical activity routine. Most individuals do the opposite: after having achieved some weight loss, they resume their original diet and exercise habits. Consequently, weight gain recurs rapidly.

How Much Are Americans Overeating?

According to the first National Health and Nutrition Examination Survey (NHANES)—a nationally representative study of the US population—women aged 20 to 29 years had a mean body mass index (BMI) of 23 in the early 1970s.4 The fourth NHANES, conducted in 1999 to 2002, found that women aged 50 to 59 years (who would have been in their 20s in the original study), had a mean BMI of 29,4 representing a weight gain of approximately 16 kg (35 lb) in 28 years (Figure, A). How much overeating is needed to gain this amount of weight? Physiologists and physicists have developed mathematical models that accurately predict the effect of a discrete change in energy intake on body weight.2, 5-6 These equations suggest that a young adult woman must increase energy intake by 370 kcal per day to increase BMI from 23 to 29.2 That increase probably occurs gradually. For example, adding 30 mL (1 oz) of sugar-sweetened beverage and walking 1 minute less per day creates a temporary energy surplus of about 13 kcal/d, leading to a weight gain of 0.6 kg (1.4 lb). Repeating changes in diet and physical activity of this magnitude on an annual basis for 28 years would produce the 370 kcal/d “energy gap” and 16-kg (35-lb) weight gain considered above.

Figure 1
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Figure. The Effects of Graded Reductions in Calorie Intake Beginning at Age 25 Years on Body WeightSolid curves demonstrate the predicted effects of a decrease in energy intake initiated at age 25 years on the weight gain that results from progressive changes in diet and physical activity in 2 situations. Panel A represents deviations from the natural course of weight gain (the dashed line) for the average US women interpolated from National Health and Nutrition Examination Survey (NHANES) I to IV data covering a 28-year period.4 Panel B represents the hypothetical case of a man aged 25 years whose body mass index increased from 25 to 35 over 28 years (dashed line). Mathematical models were based on Hall et al.10

To become obese, a much larger cumulative change in lifestyle would be required. The 90th percentile of BMI is 35 for men aged 50 to 59 years.7 To reach this degree of adiposity from a BMI of 25 at age 25 years (Figure, B), an individual would need to increase energy intake, decrease physical activity, or both by 680 kcal per day.2 For obese children, this energy gap is even greater. An adolescent at the 95th percentile of BMI at age 15 to 17 years is approximately 26 kg (58 lb) over ideal body weight.6 Assuming normal weight at age 5 to 7 years, this individual must overconsume 700 to 1000 kcal every day during this period.6 It is difficult to determine with certainty how energy intake has changed since the early 1970s, but some studies suggest a per capita increase of up to 500 kcal/d.8

Preventing Weight Gain

Obesity is difficult to reverse. But what would it take for a lean young adult to stay that way, instead of gaining about 1 or 2 lbs every year? If the effect of excess energy intake on body weight were linear, a small, one-step change in energy balance initiated at age 25 years would be sufficient to prevent overweight by middle age for most individuals.9 However, any single change in diet or physical activity, even if permanent, will elicit compensatory mechanisms that limit long-term effect on body weight. Since the weight gain experienced by a typical American must be caused by repeated changes in diet, physical activity, or both, a small decrease in food intake or increase in physical activity will halt this increase only temporarily (Figure).


These calculations suggest that small changes in lifestyle would have a minor effect on obesity prevention. Walking an extra mile a day expends, roughly, an additional 60 kcal compared with resting—equal to the energy in a small cookie. Physiological considerations suggest that the apparent energy imbalance for much of the US population is 5- to 10-fold greater, far beyond the ability of most individuals to address on a personal level. Rather, an effective public health approach to obesity prevention will require fundamental changes in the food supply and the social infrastructure. Changes of this nature depend on more stringent regulation of the food industry, agricultural policy informed by public health, and investments by government in the social environment to promote physical activity.


Corresponding Author: Martijn B. Katan, PhD, Institute of Health Sciences, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands (

Financial Disclosures: Dr Katan reported receiving royalties from a book about nutrition and health, earning fees for periodically writing a newspaper science section column and for serving as a radio health commentator, and receiving grants from the Netherlands Heart Foundation and the Netherlands Organization for Health Research and Development for research on childhood obesity. Dr Ludwig reported receiving royalties from a book about childhood obesity and grants from foundations and the National Institutes of Health for obesity-related research, mentoring, and patient care.

Funding/Support: Dr Katan is supported by an Academy Professorship from the Royal Netherlands Academy of Sciences. Dr Ludwig is supported in part by career award K24DK082730 from the National Institute of Diabetes and Digestive and Kidney Diseases.

Role of Sponsors: Neither the National Institute of Diabetes and Digestive and Kidney Diseases nor the Royal Netherlands Academy of Sciences had any role in the preparation, review, or approval of the manuscript.

Disclaimer: The content of this commentary is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Diabetes and Digestive and Kidney Diseases or the National Institutes of Health.

Additonal Contributions: We thank Steven Gortmaker, PhD, Department of Society, Human Development, and Health, Harvard School of Public Health, Boston, Massachusetts; Kevin D. Hall, PhD, Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland; and Boyd Swinburn, MB, ChB, MD, FRACP, World Health Organization Collaborating Centre for Obesity Prevention, Deakin University, Melbourne, Australia, for their critical reading of the manuscript. We also thank Dr Hall for assistance in preparing the figure. None received remuneration for their contributions.

Author Affiliations: Institute of Health Sciences, VU University, Amsterdam, the Netherlands (Dr Katan); and Optimal Weight for Life Program, Department of Medicine, Children’s Hospital, Boston, Massachusetts (Dr Ludwig).

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3. Goldsmith RL, Joanisse DR, Gallagher D; et al. Effects of experimental weight perturbation on skeletal muscle work efficiency, fuel utilization, and biochemistry in human subjects [published online November 4, 2009]. Am J Physiol Regul Integr Comp Physiol. doi:10.1152/ajpregu.00053.2009. 2009. FREE FULL TEXT

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