Aspartame and seizure susceptibility: results of a clinical study in reportedly sensitive individuals.
Association between Class III Obesity (BMI of 40–59 kg/m2) and Mortality
Discrepancy between Self-Reported and Actual Caloric Intake and Exercise in Obese Subjects
Do weight perceptions among obese adults in Great Britain match clinical definitions?
Fast Food Consumption Among Adults in the United States, 2013–2016
Impact of weight maintenance and loss on diabetes risk and burden: a population-based study in 33,184 participants
NIH study finds extreme obesity may shorten life expectancy up to 14 years
Nonlinear association of BMI with all-cause and cardiovascular mortality in type 2 diabetes mellitus
Quantification of the effect of energy imbalance on bodyweight
Relation between BMI and diabetes mellitus and its complications among US older adults.
The Natural Course of Healthy Obesity Over 20 Years

Aspartame and seizure susceptibility: results of a clinical study in reportedly sensitive individuals.

https://www.ncbi.nlm.nih.gov/pubmed/7614911

The high intensity sweetener aspartame has been implicated anecdotally in seizure provocation. This possibility was investigated with a randomized, double-blind, placebo-controlled, cross-over study. After an extensive search, 18 individuals (16 adults and 2 children) who had seizures allegedly related to aspartame consumption were admitted to adult or pediatric epilepsy monitoring units where their EEG was monitored continuously for 5 days. Aspartame (50 mg/kg) or identically enpackaged placebo was administered in divided doses at 0800, 1000, and 1200 h on study days 2 and 4. All meals were uniformly standardized on treatment days. No clinical seizures or other adverse experiences were observed after aspartame ingestion. Mean plasma phenylalanine (Phe) concentrations increased significantly after aspartame ingestion (83.6 microM) as compared with placebo (52.3 microM). Results suggest that aspartame, in acute dosage of approximately 50 mg/kg, is no more likely than placebo to cause seizures in individuals who reported that their seizures were provoked by aspartame consumption.

Association between Class III Obesity (BMI of 40–59 kg/m2) and Mortality

https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001673

Background The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity.

Methods and Findings In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per 100,000 persons per year) and multivariable-adjusted hazard ratios for adults, aged 19–83 y at baseline, classified as obese class III (BMI 40.0–59.9 kg/m2) compared with those classified as normal weight (BMI 18.5–24.9 kg/m2). Participants reporting ever smoking cigarettes or a history of chronic disease (heart disease, cancer, stroke, or emphysema) on baseline questionnaires were excluded. Among 9,564 class III obesity participants, mortality rates were 856.0 in men and 663.0 in women during the study period (1976–2009). Among 304,011 normal-weight participants, rates were 346.7 and 280.5 in men and women, respectively. Deaths from heart disease contributed largely to the excess rates in the class III obesity group (rate differences = 238.9 and 132.8 in men and women, respectively), followed by deaths from cancer (rate differences = 36.7 and 62.3 in men and women, respectively) and diabetes (rate differences = 51.2 and 29.2 in men and women, respectively). Within the class III obesity range, multivariable-adjusted hazard ratios for total deaths and deaths due to heart disease, cancer, diabetes, nephritis/nephrotic syndrome/nephrosis, chronic lower respiratory disease, and influenza/pneumonia increased with increasing BMI. Compared with normal-weight BMI, a BMI of 40–44.9, 45–49.9, 50–54.9, and 55–59.9 kg/m2 was associated with an estimated 6.5 (95% CI: 5.7–7.3), 8.9 (95% CI: 7.4–10.4), 9.8 (95% CI: 7.4–12.2), and 13.7 (95% CI: 10.5–16.9) y of life lost. A limitation was that BMI was mainly ascertained by self-report.

Conclusions Class III obesity is associated with substantially elevated rates of total mortality, with most of the excess deaths due to heart disease, cancer, and diabetes, and major reductions in life expectancy compared with normal weight.

Discrepancy between Self-Reported and Actual Caloric Intake and Exercise in Obese Subjects

https://www.nejm.org/doi/full/10.1056/NEJM199212313272701

BACKGROUND AND METHODS
Some obese subjects repeatedly fail to lose weight even though they report restricting their caloric intake to less than 1200 kcal per day. We studied two explanations for this apparent resistance to diet — low total energy expenditure and underreporting of caloric intake — in 224 consecutive obese subjects presenting for treatment. Group 1 consisted of nine women and one man with a history of diet resistance in whom we evaluated total energy expenditure and its main thermogenic components and actual energy intake for 14 days by indirect calorimetry and analysis of body composition. Group 2, subgroups of which served as controls in the various evaluations, consisted of 67 women and 13 men with no history of diet resistance.
RESULTS
Total energy expenditure and resting metabolic rate in the subjects with diet resistance (group 1) were within 5 percent of the predicted values for body composition, and there was no significant difference between groups 1 and 2 in the thermic effects of food and exercise. Low energy expenditure was thus excluded as a mechanism of self-reported diet resistance. In contrast, the subjects in group 1 underreported their actual food intake by an average (±SD) of 47±16 percent and overreported their physical activity by 51±75 percent. Although the subjects in group 1 had no distinct psychopathologic characteristics, they perceived a genetic cause for their obesity, used thyroid medication at a high frequency, and described their eating behavior as relatively normal (all P<0.05 as compared with group 2).
CONCLUSIONS
The failure of some obese subjects to lose weight while eating a diet they report as low in calories is due to an energy intake substantially higher than reported and an overestimation of physical activity, not to an abnormality in thermogenesis. (N Engl J Med 1992; 327:1893–8.)

Do weight perceptions among obese adults in Great Britain match clinical definitions?

https://bmjopen.bmj.com/content/4/11/e005561

Objectives To assess the proportion of the adult obese population in Great Britain who would describe their weight using the terms ‘obese’ and ‘very overweight’ in 2007 and 2012, and identify factors associated with more accurate weight perceptions.

Design Analysis of weight perception data from two population-based surveys.

Setting Population surveys conducted in Great Britain.

Participants Survey respondents (N=657) whose self-reported weight and height placed them in the obese category: body mass index (BMI) ≥30.

Primary outcome measure Self-identification using the terms ‘obese’ and ‘very overweight’.

Results The proportion of obese adults selecting the term ‘obese’ to describe their body size was very low in both women (13% in 2007 and 11% in 2012) and men (4% in 2007 and 7% in 2012) and did not change significantly. Recognition of a substantial degree of overweight (as indexed by endorsement of either of the terms ‘obese’ or ‘very overweight’) declined substantially in women, from 50% in 2007 to 34% in 2012. It was not significantly changed in men (27% in 2007 and 23% in 2012). Having a higher BMI, and being able to identify the BMI threshold for obesity were associated with self-identifying as obese or very overweight.

Conclusions The majority of the adult obese population of Great Britain do not identify themselves as either ‘obese’ or even ‘very overweight’. Public health initiatives to tackle obesity are likely to be hampered by this lack of recognition of weight status. It is important to understand whether moves to increase personal awareness of weight status in the obese population can facilitate beneficial behaviour change, and what role health professionals can play in increasing awareness of weight status in obese patients.

Fast Food Consumption Among Adults in the United States, 2013–2016

https://www.cdc.gov/nchs/data/databriefs/db322-h.pdf

Key findings

  • During 2013–2016, 36.6% of adults consumed fast food on a given day.
  • The percentage of adults who consumed fast food decreased with age: 44.9% aged 20–39, 37.7% aged 40–59, and 24.1% aged 60 and over.
  • The percentage of adults who consumed fast food increased with increasing family income.
  • A higher percentage of non-Hispanic black adults consumed fast food than non-Hispanic white, non-Hispanic Asian, and Hispanic adults.

Impact of weight maintenance and loss on diabetes risk and burden: a population-based study in 33,184 participants

https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-017-4081-6

Background
Weight loss in individuals at high risk of diabetes is an effective prevention method and a major component of the currently prevailing diabetes prevention strategies. The aim of the present study was to investigate the public health potential for diabetes prevention of weight maintenance or moderate weight loss on a population level in an observational cohort with repeated measurements of weight and diabetes status.
Methods
Height, weight and diabetes status were objectively measured at baseline and 10 year follow-up in a population-based cohort of 33,184 participants aged 30–60 years between 1990 and 2013 in Västerbotten County, Sweden. The association between risk of incident diabetes and change in BMI or relative weight was modelled using multivariate logistic regression. Population attributable fractions (PAF) were used to assess population impact of shift in weight.
Results
Mean (SD) BMI at baseline was 25.0 (3.6) kg/m2. Increase in relative weight between baseline and follow-up was linearly associated with incident diabetes risk, odds ratio (OR) 1.05 (95% confidence interval (CI) 1.04–1.06) per 1% change in weight. Compared to weight maintenance (±1.0 kg/m2), weight gain of > +1.0 kg/m2 was associated with an increased risk of incident diabetes, OR 1.52 (95% CI 1.32, 1.74), representing a PAF of 21.9% (95% CI 15.8, 27.6%). For moderate weight loss (−1.0 to −2.0 kg/m2) the OR was 0.72 (95% CI 0.52, 0.99).
Conclusions
Weight maintenance in adulthood is strongly associated with reduced incident diabetes risk and there is considerable potential for diabetes prevention in promoting this as a whole population strategy.

NIH study finds extreme obesity may shorten life expectancy up to 14 years

https://www.nih.gov/news-events/news-releases/nih-study-finds-extreme-obesity-may-shorten-life-expectancy-14-years

Adults with extreme obesity have increased risks of dying at a young age from cancer and many other causes including heart disease, stroke, diabetes, and kidney and liver diseases, according to results of an analysis of data pooled from 20 large studies of people from three countries. The study, led by researchers from the National Cancer Institute (NCI), part of the National Institutes of Health, found that people with class III (or extreme) obesity had a dramatic reduction in life expectancy compared with people of normal weight. The findings appeared July 8, 2014, in PLOS Medicine.

“While once a relatively uncommon condition, the prevalence of class III, or extreme, obesity is on the rise. In the United States, for example, six percent of adults are now classified as extremely obese, which, for a person of average height, is more than 100 pounds over the recommended range for normal weight,” said Cari Kitahara, Ph.D., Division of Cancer Epidemiology and Genetics, NCI, and lead author of the study. “Prior to our study, little had been known about the risk of premature death associated with extreme obesity.”

In the study, researchers classified participants according to their body mass index (BMI), which is a measure of total body fat and is calculated by dividing a person’s weight in kilograms by their height in meters squared. BMI classifications (kilogram/meter-squared) are:

  • Normal weight: 18.5-24.9
  • Overweight: 25.0- 29.9
  • Class I obesity: 30.0-34.9
  • Class II obesity: 35.0-39.9
  • Class III obesity: 40.0 or higher

The 20 studies that were analyzed included adults from the United States, Sweden and Australia. These groups form a major part of the NCI Cohort Consortium, which is a large-scale partnership that identifies risk factors for cancer death. After excluding individuals who had ever smoked or had a history of certain diseases, the researchers evaluated the risk of premature death overall and the risk of premature death from specific causes in more than 9,500 individuals who were class III obese and 304,000 others who were classified as normal weight.

The researchers found that the risk of dying overall and from most major health causes rose continuously with increasing BMI within the class III obesity group. Statistical analyses of the pooled data indicated that the excess numbers of deaths in the class III obesity group were mostly due to heart disease, cancer and diabetes. Years of life lost ranged from 6.5 years for participants with a BMI of 40-44.9 to 13.7 years for a BMI of 55-59.9. To provide context, the researchers found that the number of years of life lost for class III obesity was equal or higher than that of current (versus never) cigarette smokers among normal-weight participants in the same study.

The accuracy of the study findings is limited by the use of mostly self-reported height and weight measurements and by the use of BMI as the sole measure of obesity. Nevertheless, the researchers noted, the results highlight the need to develop more effective interventions to combat the growing public health problem of extreme obesity.

“Given our findings, it appears that class III obesity is increasing and may soon emerge as a major cause of early death in this and other countries worldwide,” said Patricia Hartge, Sc.D., Division of Cancer Epidemiology and Genetics, and senior author of the study.

The National Cancer Institute (NCI) leads the National Cancer Program and the NIH effort to dramatically reduce the burden of cancer and improve the lives of cancer patients and their families, through research into prevention and cancer biology, the development of new interventions, and the training and mentoring of new researchers. For more information about cancer, please visit the NCI website at http://www.cancer.gov or call NCI's Cancer Information Service at 1-800-4-CANCER (1-800-422-6237).

About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

Reference

Kitahara CM, et al. Association between Class III Obesity (BMI of 40–59 kg/m) and Mortality: A Pooled Analysis of 20 Prospective Studies. PLOS Medicine. July 8, 2014. DOI: 10.1371/journal.pmed.1001673.

Nonlinear association of BMI with all-cause and cardiovascular mortality in type 2 diabetes mellitus

https://www.ncbi.nlm.nih.gov/pubmed/27888288

Nonlinear association of BMI with all-cause and cardiovascular mortality in type 2 diabetes mellitus: a systematic review and meta-analysis of 414,587 participants in prospective studies.

AIMS/HYPOTHESIS:The relationship between BMI and mortality has been extensively investigated in the general population; however, it is less clear in people with type 2 diabetes. We aimed to assess the association of BMI with all-cause and cardiovascular mortality in individuals with type 2 diabetes mellitus.

METHODS:We searched electronic databases up to 1 March 2016 for prospective studies reporting associations for three or more BMI groups with all-cause and cardiovascular mortality in individuals with type 2 diabetes mellitus. Study-specific associations between BMI and the most-adjusted RR were estimated using restricted cubic splines and a generalised least squares method before pooling study estimates with a multivariate random-effects meta-analysis.

RESULTS:We included 21 studies including 24 cohorts, 414,587 participants, 61,889 all-cause and 4470 cardiovascular incident deaths; follow-up ranged from 2.7 to 15.9 years. There was a strong nonlinear relationship between BMI and all-cause mortality in both men and women, with the lowest estimated risk from 31-35 kg/m2 and 28-31 kg/m2 (p value for nonlinearity <0.001) respectively. The risk of mortality at higher BMI values increased significantly only in women, whilst lower values were associated with higher mortality in both sexes. Limited data for cardiovascular mortality were available, with a possible inverse linear association with BMI (higher risk for BMI <27 kg/m2).

CONCLUSIONS/INTERPRETATION:In type 2 diabetes, BMI is nonlinearly associated with all-cause mortality with lowest risk in the overweight group in both men and women. Further research is needed to clarify the relationship with cardiovascular mortality and assess causality and sex differences.

Quantification of the effect of energy imbalance on bodyweight

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3880593/

Obesity interventions can result in weight loss, but accurate prediction of the bodyweight time course requires properly accounting for dynamic energy imbalances. In this report, we describe a mathematical modelling approach to adult human metabolism that simulates energy expenditure adaptations during weight loss. We also present a web-based simulator for prediction of weight change dynamics. We show that the bodyweight response to a change of energy intake is slow, with half times of about 1 year. Furthermore, adults with greater adiposity have a larger expected weight loss for the same change of energy intake, and to reach their steady-state weight will take longer than it would for those with less initial body fat. Using a population-averaged model, we calculated the energy-balance dynamics corresponding to the development of the US adult obesity epidemic. A small persistent average daily energy imbalance gap between intake and expenditure of about 30 kJ per day underlies the observed average weight gain. However, energy intake must have risen to keep pace with increased expenditure associated with increased weight. The average increase of energy intake needed to sustain the increased weight (the maintenance energy gap) has amounted to about 0·9 MJ per day and quantifies the public health challenge to reverse the obesity epidemic.

Test Edit

Relation between BMI and diabetes mellitus and its complications among US older adults.

https://www.ncbi.nlm.nih.gov/pubmed/25580754

OBJECTIVES: This study examined relations between elevated body mass index (BMI) and time to diagnosis with type 2 diabetes mellitus and its complications among older adults in the United States.

METHODS: Data came from the Medicare Current Beneficiary Survey, 1991-2010. A Cox proportional hazard model was used to assess relations between excess BMI at the first Medicare Current Beneficiary Survey interview and time to diabetes mellitus diagnosis, complications, and insulin dependence among Medicare beneficiaries, older than 65 years of age with no prior diabetes mellitus diagnosis, and who were not enrolled in Medicare Advantage (N = 14,657).

RESULTS: Among individuals diagnosed as having diabetes mellitus, elevated BMIs were associated with a progressively higher risk of complications from diabetes mellitus. For women with a BMI ≥40, the risk of insulin dependence (hazard ratio [HR] 3.57; 95% confidence interval [CI] 2.36-5.39) was twice that for women with 25 ≤ BMI < 27.5 (HR 1.77; 95% CI 1.33-2.33). A similar pattern was observed in risk of cardiovascular (25 ≤ BMI < 27.5: HR 1.34; 95% CI 1.15-1.54; BMI ≥40: HR 2.45; 95% CI 1.92-3.11), cerebrovascular (25 ≤ BMI < 27.5: HR 1.30; 95% CI 1.06-1.57; BMI ≥40: HR 2.00; 95% CI 1.42-2.81), renal (25 ≤ BMI < 27.5: HR 1.31; 95% CI 1.04-1.63; BMI ≥40: HR 2.23; 95% CI 1.54-3.22), and lower extremity complications (25 ≤ BMI < 27.5: HR 1.41; 95% CI 1.22-1.61; BMI ≥40: HR 2.95; 95% CI 2.35-3.69).

CONCLUSIONS: Any increase in BMI above normal weight levels is associated with an increased risk of being diagnosed as having complications of diabetes mellitus. For men, the increased risk of these complications occurred at higher BMI levels than in women. Ocular complications occurred at higher BMI levels than other complication types in both men and women.

The Natural Course of Healthy Obesity Over 20 Years

http://www.onlinejacc.org/content/65/1/101

Intense interest surrounds the “healthy” obese phenotype, which is defined as obesity in the absence of metabolic risk factor clustering (1). Efforts to understand the cardiovascular consequences of healthy obesity are ongoing (2); however, its conceptual validity and clinical value rest on the assumption that it is a stable physiological state, rather than a transient phase of obesity-associated metabolic deterioration. Therefore, a fundamental question is whether healthy obese adults maintain this metabolically healthy profile over the long term or naturally transition into unhealthy obesity over time. Few studies have examined this; in those that have, durations of follow-up have been modest, with none exceeding 10 years (3,4). Accordingly, we aimed to describe the natural course of healthy obesity over 2 decades in a large population-based study.

The Whitehall II cohort study of British government workers provided objectively measured anthropometric and metabolic risk factor data. “Obese” was defined as body mass index ≥30 kg/m². “Metabolically healthy” was defined as having <2 of the following: high-density lipoprotein cholesterol level <1.03 mmol/l (men) and <1.29 mmol/l (women); blood pressure ≥130/85 mm Hg or use of antihypertensive medication; fasting plasma glucose level ≥5.6 mmol/l or use of antidiabetic medication; triacylglycerol level ≥1.7 mmol/l; and homeostatic model assessment of insulin resistance >2.87 (baseline 90th percentile value) (1).

Participants with data on obesity and metabolic status at baseline and all follow-up examinations were analyzed. Cross-tabulations were used to describe the proportion of participants according to their baseline (1992/1994) obesity and metabolic status in each category after 5-year (1997/1999), 10-year (2002/2004), 15-year (2007/2009), and 20-year (2012/2014) follow-up examinations. Log binomial models were used to estimate age-, sex-, and ethnicity-adjusted prevalence ratios with 95% confidence intervals for unhealthy obesity at each follow-up, excluding unhealthy obese adults at baseline.

Descriptive analyses were repeated using maximum samples of healthy obese adults on the basis of duration of follow-up, allowing different baseline and follow-up points across the 20-year period. For example, the 15-year healthy obese sample included transitions from 1992/1994, to 2007/2009, or from 1997/1999 to 2012/2014. Analyses were performed using SPSS software version 19.0 (IBM, Armonk, New York), with p < 0.05 indicating statistical significance.

Our primary sample (n = 2,521; 39 to 62 years of age; 75% male) included 66 healthy obese adults at baseline (36.5% of the obese). Of these subjects, 21 (31.8%) were unhealthy obese after 5 years, and 27 (40.9%), 23 (34.8%), and 34 (51.5%) were unhealthy obese after 10, 15, and 20 years, respectively (Table 1). The proportion of healthy obese adults who were healthy nonobese at follow-up was 6.1%, 4.5%, 6.1%, and 10.6% after 5, 10, 15, and 20 years respectively.

The age-, sex-, and ethnicity-adjusted prevalence of unhealthy obesity after 5 years was 11.80 (95% confidence interval [CI]: 7.28 to 19.11) times higher in baseline healthy obese adults compared with healthy nonobese subjects. The corresponding prevalence ratio was 8.09 (95% CI: 5.54 to 11.81) after 10 years, 6.64 (95% CI: 4.43 to 9.96) after 15 years, and 7.74 (95% CI: 5.53 to 10.85) after 20 years.

Subsidiary analyses using maximum samples produced similar results. Of the 389 healthy obese adults with 5-year data, 35.2% were unhealthy obese after 5 years. This proportion was 34.7% after 10 years (sample n = 317), 37.9% after 15 years (sample n = 224), and 48.1% after 20 years (sample n = 106).

After 20 years, approximately one-half of healthy obese adults were unhealthy obese, and only 10% were healthy nonobese. Healthy obese adults were nearly 8 times more likely to progress to an unhealthy obese state after 20 years than healthy nonobese adults, and these subjects were consistently more likely to make this adverse transition than unhealthy nonobese adults. Progressions from healthy to unhealthy obesity also increased steadily with increasing follow-up duration when using maximum samples of healthy obese adults over the follow-up period.

Some evidence suggests that stability is associated with a more favorable fat distribution in the form of lower waist circumference (4), and thus it may be possible to increase stability in healthy obesity over time. However, our results, which were obtained with a longer, more detailed follow-up than any previous study, suggest that long-term stability is the exception, not the norm. The natural course of healthy obesity is progression to metabolic deterioration.