Source: Preventing Chronic Disease (CDC)
Many policy measures to control the obesity epidemic assume that people consciously and rationally choose what and how much they eat and therefore focus on providing information and more access to healthier foods. In contrast, many regulations that do not assume people make rational choices have been successfully applied to control alcohol, a substance – like food – of which immoderate consumption leads to serious health problems. Alcohol-use control policies restrict where, when, and by whom alcohol can be purchased and used. Access, salience, and impulsive drinking behaviors are addressed with regulations including alcohol outlet density limits, constraints on retail displays of alcoholic beverages, and restrictions on drink "specials." We discuss 5 regulations that are effective in reducing drinking and why they may be promising if applied to the obesity epidemic.
Source: Robert Wood Johnson Foundation
The number of obese adults, along with related disease rates and health care costs, are on course to increase dramatically in every state in the country over the next 20 years, according to F as in Fat: How Obesity Threatens America’s Future 2012, a report released today by Trust for America’s Health (TFAH) and the Robert Wood Johnson Foundation (RWJF).
For the first time, the annual report includes an analysis that forecasts 2030 adult obesity rates in each state and the likely resulting rise in obesity-related disease rates and health care costs. By contrast, the analysis also shows that states could prevent obesity-related diseases and dramatically reduce health care costs if they reduced the average body mass index of their residents by just 5 percent by 2030.
If obesity rates continue on their current trajectories, by 2030, 13 states could have adult obesity rates above 60 percent, 39 states could have rates above 50 percent, and all 50 states could have rates above 44 percent.
By 2030, Mississippi could have the highest obesity rate at 66.7 percent, and Colorado could have the lowest rate for any state at 44.8 percent. According to the latest data from the U.S. Centers for Disease Control and Prevention (CDC), obesity rates in 2011 ranged from a high of 34.9 percent in Mississippi to a low of 20.7 percent in Colorado.
To determine if state laws regulating nutrition content of foods and beverages sold outside of federal school meal programs (“competitive foods”) are associated with lower adolescent weight gain.
The Westlaw legal database identified state competitive food laws that were scored by using the Classification of Laws Associated with School Students criteria. States were classified as having strong, weak, or no competitive food laws in 2003 and 2006 based on law strength and comprehensiveness. Objective height and weight data were obtained from 6300 students in 40 states in fifth and eighth grade (2004 and 2007, respectively) within the Early Childhood Longitudinal Study–Kindergarten Class. General linear models estimated the association between baseline state laws (2003) and within-student changes in BMI, overweight status, and obesity status. Fixed-effect models estimated the association between law changes during follow-up (2003–2006) and within-student changes in BMI and weight status.
Students exposed to strong laws at baseline gained, on average, 0.25 fewer BMI units (95% confidence interval: −0.54, 0.03) and were less likely to remain overweight or obese over time than students in states with no laws. Students also gained fewer BMI units if exposed to consistently strong laws throughout follow-up (β = −0.44, 95% confidence interval: −0.71, −0.18). Conversely, students exposed to weaker laws in 2006 than 2003 had similar BMI gain as those not exposed in either year.
Laws that regulate competitive food nutrition content may reduce adolescent BMI change if they are comprehensive, contain strong language, and are enacted across grade levels.
Source: Centers for Disease Control and Prevention
In 2011, rates of adult obesity remain high, with state estimates ranging from 20.7 percent in Colorado to 34.9 percent in Mississippi. No state had a prevalence of adult obesity less than 20 percent, and 12 states (Alabama, Arkansas, Indiana, Kentucky, Louisiana, Michigan, Mississippi, Missouri, Oklahoma, South Carolina, Texas, and West Virginia) had a prevalence of 30 percent or more. The South had the highest prevalence of adult obesity (29.5 percent), followed by the Midwest (29 percent), the Northeast (25.3 percent) and the West (24.3 percent).
Being Normal Weight but Feeling Overweight in Adolescence May Affect Weight Development into Young Adulthood—An 11-Year Followup: The HUNT Study, Norway
To explore if self-perceived overweight in normal weight adolescents influence their weight development into young adulthood and if so, whether physical activity moderates this association.
A longitudinal study of 1196 normal weight adolescents (13–19 yrs) who were followed up as young adults (24–30 yrs) in the HUNT study. Lifestyle and health issues were assessed employing questionnaires, and standardized anthropometric measurements were taken. Chi square calculations and regression analyses were performed to investigate the associations between self-perceived overweight and change in BMI or waist circumference (WC) adjusted for age, age squared, sex, and other relevant cofactors.
Adolescents, defined as being normal weight, but who perceived themselves as overweight had a larger weight gain into young adulthood than adolescents who perceived themselves as normal weight (difference in BMI: 0.66 units [CI95%: 0.1, 1.2] and in WC: 3.46 cm [CI95%: 1.8, 5.1]). Level of physical activity was not found to moderate this association.
This study reveals that self-perceived overweight during adolescence may affect development of weight from adolescence into young adulthood. This highlights the importance of also focusing on body image in public health interventions against obesity, favouring a “healthy” body weight taking into account natural differences in body shapes.
See: Feeling Fat May Make You Fat, Study Suggests (Science Daily)
Source: BMC Public Health
The energy requirement of species at each trophic level in an ecological pyramid is a function of the number of organisms and their average mass. Regarding human populations, although considerable attention is given to estimating the number of people, much less is given to estimating average mass, despite evidence that average body mass is increasing. We estimate global human biomass, its distribution by region and the proportion of biomass due to overweight and obesity.
For each country we used data on body mass index (BMI) and height distribution to estimate average adult body mass. We calculated total biomass as the product of population size and average body mass. We estimated the percentage of the population that is overweight (BMI > 25) and obese (BMI > 30) and the biomass due to overweight and obesity.
In 2005, global adult human biomass was approximately 287 million tonnes, of which 15 million tonnes were due to overweight (BMI > 25), a mass equivalent to that of 242 million people of average body mass (5% of global human biomass). Biomass due to obesity was 3.5 million tonnes, the mass equivalent of 56 million people of average body mass (1.2% of human biomass). North America has 6% of the world population but 34% of biomass due to obesity. Asia has 61% of the world population but 13% of biomass due to obesity. One tonne of human biomass corresponds to approximately 12 adults in North America and 17 adults in Asia. If all countries had the BMI distribution of the USA, the increase in human biomass of 58 million tonnes would be equivalent in mass to an extra 935 million people of average body mass, and have energy requirements equivalent to that of 473 million adults.
Increasing population fatness could have the same implications for world food energy demands as an extra half a billion people living on the earth.
Source: British Medical Journal (open)
To determine the impact of sitting and television viewing on life expectancy in the USA.
Prevalence-based cause-deleted life table analysis.
Summary RRs of all-cause mortality associated with sitting and television viewing were obtained from a meta-analysis of available prospective cohort studies. Prevalences of sitting and television viewing were obtained from the US National Health and Nutrition Examination Survey.
Primary outcome measure
Life expectancy at birth.
The estimated gains in life expectancy in the US population were 2.00 years for reducing excessive sitting to <3 h/day and a gain of 1.38 years from reducing excessive television viewing to <2 h/day. The lower and upper limits from a sensitivity analysis that involved simultaneously varying the estimates of RR (using the upper and lower bounds of the 95% CI) and the prevalence of television viewing (±20%) were 1.39 and 2.69 years for sitting and 0.48 and 2.51 years for television viewing, respectively.
Reducing sedentary behaviours such as sitting and television viewing may have the potential to increase life expectancy in the USA.
Body Mass Index, Diabetes, Hypertension, and Short-Term Mortality: A Population-Based Observational Study, 2000–2006
Body Mass Index, Diabetes, Hypertension, and Short-Term Mortality: A Population-Based Observational Study, 2000–2006
Source: Journal of the American Board of Family Medicine
Published studies about the association of obesity with mortality have used body mass index (BMI) data collected more than 10 years ago, potentially limiting their current applicability, particularly given evidence of a secular decline in obesity-related mortality. The objective of this study was to examine the association between BMI and mortality in a representative, contemporary United States sample.
This was a population-based observational study of data from 50,994 adults aged 18 to 90 years who responded to the 2000 to 2005 Medical Expenditures Panel Surveys. Cox regression analyses were employed to model survival during up to 6 years of follow-up (ascertained via National Death Index linkage) by self-reported BMI category (underweight, <20 kg/m2; normal weight, 20-<25 [reference]; overweight, 25-<30; obese, 30-<35; severely obese, ≥35), without and with adjustment for diabetes and hypertension. Survival by BMI category also was modeled for diabetic and hypertensive individuals. All models were adjusted for sociodemographics, smoking, and Medical Expenditures Panel Surveys response year.
In analyses not adjusted for diabetes or hypertension, only severe obesity was associated with mortality (adjusted hazard ratio, 1.26; 95% confidence interval, 1.00–1.59). After adjusting for diabetes and hypertension, severe obesity was no longer associated with mortality, and milder obesity (BMI 30-<35) was associated with decreased mortality (adjusted hazard ratio, 0.81; 95% confidence interval, 0.68–0.97). There was a significant interaction between diabetes (but not hypertension) and BMI (F [4, 235] = 2.71; P = .03), such that the mortality risk of diabetes was lower among mildly and severely obese persons than among those in lower BMI categories.
Obesity-associated mortality risk was lower than estimated in studies employing older BMI data. Only severe obesity (but not milder obesity or overweight) was associated with increased mortality, an association accounted for by coexisting diabetes and hypertension. Mortality in diabetes was lower among obese versus normal weight individuals.
Factors Influencing the Implementation of School Wellness Policies in the United States, 2009
Source: Preventing Chronic Disease (CDC)
The quality of school wellness policy implementation varies among schools in the United States. The objective of this study was to characterize the school wellness policy environment nationally and identify factors influencing the quality and effectiveness of policy implementation.
We invited school administrators from 300 high schools to complete a questionnaire; 112 administrators responded. We performed a 2-step cluster analysis to help identify factors influencing the implementation of school wellness policies.
Eighty-two percent of schools reported making staff aware of policy requirements; 77% established a wellness committee or task force, 73% developed administrative procedures, and 56% trained staff for policy implementation. Most commonly reported challenges to implementation were lack of time or coordination of policy team (37% of respondents) and lack of monetary resources (33%). The core domains least likely to be implemented were communication and promotion (63% of respondents) and evaluation (54%). Cluster 1, represented mostly by schools that have taken action toward implementing policies, had higher implementation and effectiveness ratings than Cluster 2, which was defined by taking fewer actions toward policy implementation. In Cluster 1, accountability was also associated with high ratings of implementation quality and effectiveness.
The development of organizational capacity may be critical to ensuring an environment that promotes high-quality policy implementation. Assessing, preventing, and addressing challenges; establishing clear definitions and goals; and requiring accountability for enacting policy across all core domains are critical to ensuring high-quality implementation.
Collective behavior in the spatial spreading of obesity
Source: Scientific Reports
Obesity prevalence is increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the obesity epidemics. Here, we implement a spatial spreading analysis to investigate whether obesity shows spatial correlations, revealing the effect of collective and global factors acting above individual choices. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution indicating the presence of collective behavior, i.e., individual habits may have negligible influence in shaping the patterns of spreading. Interestingly, we find the same scale-free correlations in economic activities associated with food production. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies.
Youth Risk Behavior Surveillance — United States, 2011
Source: Morbidity and Mortality Weekly Report (CDC)
Problem: Priority health-risk behaviors, which are behaviors that contribute to the leading causes of morbidity and mortality among youth and adults, often are established during childhood and adolescence, extend into adulthood, and are interrelated and preventable.
Reporting Period Covered: September 2010–December 2011.
Description of the System: The Youth Risk Behavior Surveillance System (YRBSS) monitors six categories of priority health-risk behaviors among youth and young adults: 1) behaviors that contribute to unintentional injuries and violence; 2) tobacco use; 3) alcohol and other drug use; 4) sexual behaviors that contribute to unintended pregnancy and sexually transmitted diseases (STDs), including human immunodeficiency virus (HIV) infection; 5) unhealthy dietary behaviors; and 6) physical inactivity. In addition, YRBSS monitors the prevalence of obesity and asthma. YRBSS includes a national school-based Youth Risk Behavior Survey (YRBS) conducted by CDC and state and large urban school district school-based YRBSs conducted by state and local education and health agencies. This report summarizes results from the 2011 national survey, 43 state surveys, and 21 large urban school district surveys conducted among students in grades 9–12.
Results: Results from the 2011 national YRBS indicated that many high school students are engaged in priority health-risk behaviors associated with the leading causes of death among persons aged 10–24 years in the United States. During the 30 days before the survey, 32.8% of high school students nationwide had texted or e-mailed while driving, 38.7% had drunk alcohol, and 23.1% had used marijuana. During the 12 months before the survey, 32.8% of students had been in a physical fight, 20.1% had ever been bullied on school property, and 7.8% had attempted suicide. Many high school students nationwide are engaged in sexual risk behaviors associated with unintended pregnancies and STDs, including HIV infection. Nearly half (47.4%) of students had ever had sexual intercourse, 33.7% had had sexual intercourse during the 3 months before the survey (i.e., currently sexually active), and 15.3% had had sexual intercourse with four or more people during their life. Among currently sexually active students, 60.2% had used a condom during their last sexual intercourse. Results from the 2011 national YRBS also indicate many high school students are engaged in behaviors associated with the leading causes of death among adults aged ≥25 years in the United States. During the 30 days before the survey, 18.1% of high school students had smoked cigarettes and 7.7% had used smokeless tobacco. During the 7 days before the survey, 4.8% of high school students had not eaten fruit or drunk 100% fruit juices and 5.7% had not eaten vegetables. Nearly one-third (31.1%) had played video or computer games for 3 or more hours on an average school day.
Interpretation: Since 1991, the prevalence of many priority health-risk behaviors among high school students nationwide has decreased. However, many high school students continue to engage in behaviors that place them at risk for the leading causes of morbidity and mortality. Variations were observed in many health-risk behaviors by sex, race/ethnicity, and grade. The prevalence of some health-risk behaviors varied substantially among states and large urban school districts.
Public Health Action: YRBS data are used to measure progress toward achieving 20 national health objectives for Healthy People 2020 and one of the 26 leading health indicators; to assess trends in priority health-risk behaviors among high school students; and to evaluate the impact of broad school and community interventions at the national, state, and local levels. More effective school health programs and other policy and programmatic interventions are needed to reduce risk and improve health outcomes among youth.
Q&A: ‘Toxic’ effects of sugar: should we be afraid of fructose?
Source: BMC Biology
Fructose is a hexose with the same chemical formula, C6H12O6, as glucose. These two sweet-tasting molecules differ structurally, however, as fructose has a keto-group on the second carbon while glucose presents an aldehyde group on the first carbon. Free fructose, together with free glucose, is present in small amounts in fruits and honey. The main part of today’s dietary fructose intake comes from sucrose, a disaccharide composed of one molecule of glucose linked to a molecule of fructose through an alpha 1-4 glycoside bond.
The link with metabolic disease is partly circumstantial. Fructose consumption has been low throughout most of human history, but started to increase after the crusades, when Europeans became acquainted with sucrose produced from sugar cane in Asia. It was at first a luxury product, but consumption rapidly increased in the 16th and 17th centuries when sugar became more widely available as a consequence of colonial trading. Its consumption was boosted, first by the introduction of new beverages – tea, coffee, and cocoa in the 17th to 18th centuries; and second with the production of chocolate bars, ice-creams, and sodas at the beginning of the 20th century. Total sugar consumption thus increased from less than 5 kg/person/year in the 1800s to about 40 kg at the turn of the 19th century, and about 70 kg/person/year in 2006. In short, a rapid and continuous increase in consumption has been observed from 1750 until the present day.
In the 1960s, a novel food technology allowed the large-scale, industrial conversion of glucose into fructose. As a result, the US corn industry started preparing what is now known as high fructose corn syrup (HFCS), that is, a concentrated solution of corn-derived glucose and fructose mixed in various relative proportions. Mainly because of its low cost, HFCS consumption replaced approximately one-third of the total sugar consumption in the USA between 1970 and 2000, paralleling to some extent the increasing prevalence of obesity during this period. Consequently, HFCS has been a particular focus of possible blame for the obesity epidemic. However, HFCS consumption has remained very low in other parts of the world where obesity has also increased, and the most commonly used form of HFCS contains about 55% fructose, 42% glucose, and 3% other sugars, and hence is associated with similar total fructose and glucose intakes as with sugar. Furthermore, sucrose is hydrolyzed in the gut and absorbed into the blood as free glucose and fructose, so one would expect HFCS and sucrose to have the same metabolic consequences. In short, there is currently no evidence to support the hypothesis that HFCS makes a significant contribution to metabolic disease independently of the rise in total fructose consumption.
The Number of X Chromosomes Causes Sex Differences in Adiposity in Mice
Source: PLoS Genetics
Sexual dimorphism in body weight, fat distribution, and metabolic disease has been attributed largely to differential effects of male and female gonadal hormones. Here, we report that the number of X chromosomes within cells also contributes to these sex differences. We employed a unique mouse model, known as the “four core genotypes,” to distinguish between effects of gonadal sex (testes or ovaries) and sex chromosomes (XX or XY). With this model, we produced gonadal male and female mice carrying XX or XY sex chromosome complements. Mice were gonadectomized to remove the acute effects of gonadal hormones and to uncover effects of sex chromosome complement on obesity. Mice with XX sex chromosomes (relative to XY), regardless of their type of gonad, had up to 2-fold increased adiposity and greater food intake during daylight hours, when mice are normally inactive. Mice with two X chromosomes also had accelerated weight gain on a high fat diet and developed fatty liver and elevated lipid and insulin levels. Further genetic studies with mice carrying XO and XXY chromosome complements revealed that the differences between XX and XY mice are attributable to dosage of the X chromosome, rather than effects of the Y chromosome. A subset of genes that escape X chromosome inactivation exhibited higher expression levels in adipose tissue and liver of XX compared to XY mice, and may contribute to the sex differences in obesity. Overall, our study is the first to identify sex chromosome complement, a factor distinguishing all male and female cells, as a cause of sex differences in obesity and metabolism.
Residual Obesity Stigma: An Experimental Investigation of Bias Against Obese and Lean Targets Differing in Weight-Loss History
This study investigated stigma directed at formerly obese persons who lost weight and became lean (through behavioral or surgical methods), or lost weight but remained obese, relative to weight-stable obese and weightstable lean persons. This study also compared stigma directed at obese persons following exposure to descriptions of persons who lost weight vs. remained weight stable. In a between-subject experimental design, participants (n = 273) were randomly assigned to read vignettes describing targets varying across two dimensions, weight stability (i.e., weight stable or weight lost) and current weight (i.e., currently obese or currently lean). Participants completed measures of stigma against specific targets and measures of stigma against obese individuals in general. Lean individuals who were formerly obese were stigmatized more on attractiveness than weight-stable lean individuals, and as much as currently obese individuals. Stigma across domains was greater among currently obese individuals (regardless of whether they had lost weight from a higher weight) than among currently lean individuals. After reading vignettes describing weight loss, participants demonstrated greater obesity stigma than after reading vignettes describing weight-stable individuals. These results suggest that residual stigma remains against people who have previously been obese, even when they have lost substantial amounts of weight and regardless of their weight-loss method. Exposure to portrayals of the malleability of body weight, such as those promoted in the popular media, may significantly worsen obesity stigma.
Many policy measures to control the obesity epidemic assume that people consciously and rationally choose what and how much they eat and therefore focus on providing information and more access to healthier foods. In contrast, many regulations that do not assume people make rational choices have been successfully applied to control alcohol, a substance — like food — of which immoderate consumption leads to serious health problems. Alcohol-use control policies restrict where, when, and by whom alcohol can be purchased and used. Access, salience, and impulsive drinking behaviors are addressed with regulations including alcohol outlet density limits, constraints on retail displays of alcoholic beverages, and restrictions on drink “specials.” We discuss 5 regulations that are effective in reducing drinking and why they may be promising if applied to the obesity epidemic.
Accelerating Progress in Obesity Prevention: Solving the Weight of the NationSource: Institute of Medicine
Two-thirds of adults and one-third of children are overweight or obese. Left unchecked, obesity’s effects on health, health care costs, and our productivity as a nation could become catastrophic.
The staggering human toll of obesity-related chronic disease and disability, and an annual cost of $190.2 billion for treating obesity-related illness, underscore the urgent need to strengthen prevention efforts in the United States. The Robert Wood Johnson Foundation asked the IOM to identify catalysts that could speed progress in obesity prevention.
The IOM evaluated prior obesity prevention strategies and identified recommendations to meet the following goals and accelerate progress
- Integrate physical activity every day in every way
- Market what matters for a healthy life
- Make healthy foods and beverages available everywhere
- Activate employers and health care professionals
- Strengthen schools as the heart of health
On their own, accomplishing any one of these might help speed up progress in preventing obesity, but together, their effects will be reinforced, amplified, and maximized.
Sleep duration has progressively fallen over the last 100 years while obesity has increased in the past 30 years. Several studies have reported an association between chronic sleep deprivation and long-term weight gain. Increased energy intake due to sleep loss has been listed as the main mechanism. The consequences of chronic sleep deprivation on energy expenditure have not been fully explored. Sleep, body weight, mood and behavior are subjected to circannual changes. However, in our modern environment seasonal changes in light and ambient temperature are attenuated. Seasonality, defined as cyclic changes in mood and behavior, is a stable personality trait with a strong genetic component. We hypothesize that the attenuation in seasonal changes in the environment may produce negative consequences, especially in individuals more predisposed to seasonality, such as women. Seasonal affective disorder, a condition more common in women and characterized by depressed mood, hypersomnia, weight gain, and carbohydrate craving during the winter, represents an extreme example of seasonality. One of the postulated functions of sleep is energy preservation. Hibernation, a phenomenon characterized by decreased energy expenditure and changes in the state of arousal, may offer useful insight into the mechanisms behind energy preservation during sleep. The goals of this article are to: a) consider the contribution of changes in energy expenditure to the weight gain due to sleep loss; b) review the phenomena of seasonality, hibernation, and their neuroendocrine mechanisms as they relate to sleep, energy expenditure, and body weight regulation.