Associations between obesity and health conditions may be overestimated if self-reported body mass index is used

Application of a Web-based Tool for Quantitative Bias Analysis: The Example of Misclassification Due to Self-reported Body Mass Index

BACKGROUND

We describe the use of Apisensr, a web-based application that can be used to implement quantitative bias analysis for misclassification, selection bias, and unmeasured confounding. We apply Apisensr using an example of exposure misclassification bias due to use of self-reported body mass index (BMI) to define obesity status in an analysis of the relationship between obesity and diabetes.

METHODS

We used publicly available data from the National Health and Nutrition Examination Survey. The analysis consisted of: (1) estimating bias parameter values (sensitivity, specificity, negative predictive value, and positive predictive value) for self-reported obesity by sex, age, and race-ethnicity compared to obesity defined by measured BMI, and (2) using Apisensr to adjust for exposure misclassification.

RESULTS

The discrepancy between self-reported and measured obesity varied by demographic group (sensitivity range: 75%-89%; specificity range: 91%-99%). Using Apisensr for quantitative bias analysis, there was a clear pattern in the results: the relationship between obesity and diabetes was underestimated using self-report in all age, sex, and race-ethnicity categories compared to measured obesity. For example, in non-Hispanic White men aged 40-59 years, prevalence odds ratios for diabetes were 3.06 (95% confidence inerval = 1.78, 5.30) using self-reported BMI and 4.11 (95% confidence interval = 2.56, 6.75) after bias analysis adjusting for misclassification.

CONCLUSION

Apisensr is an easy-to-use, web-based Shiny app designed to facilitate quantitative bias analysis. Our results also provide estimates of bias parameter values that can be used by other researchers interested in examining obesity defined by self-reported BMI.

Trajectories of Body Mass Index and Risk for Diabetes Complications and All-Cause Mortality in Finnish Type 2 Diabetes Patients

Objective

We aimed to assess how longitudinal body mass index (BMI) trajectories are associated with diabetes complications and all-cause mortality in Finnish patients with type 2 diabetes (T2D).

Methods

In this cohort study, electronic health records from public primary and specialized healthcare services in all 13 municipalities of North Karelia, Finland, were utilized. This study included a total of 889 adults with newly diagnosed T2D in 2011 or 2012 (mean age at baseline 62.0 years). Individual BMI trajectories from the T2D diagnosis until 2014 were estimated and grouped by growth mixture modeling (GMM). Hazard ratios (HRs) with 95% confidence intervals (CIs) for microvascular complications, macrovascular complications, any diabetes complications, and all-cause mortality from 2015 to 2022 across BMI trajectory groups were estimated using Cox regression models.

Results

Three distinct BMI trajectory groups were identified using GMM and labeled as follows: "stable" (n = 774, 87.1%), "decreasing" (n = 87, 9.8%), and "increasing" (n = 28, 3.1%). During a median follow-up of 8 years, there were 119 (13.3%) patients with microvascular complications, 187 (21.0%) with macrovascular complications, 258 (29.0%) with any diabetes complications, and 180 (20.2%) deaths. Compared with the "stable" BMI, the "increasing" BMI was associated with an increased risk of microvascular complications (HR = 2.88, 95% CI: 1.32 to 6.28), macrovascular complications (HR = 2.52, 95% CI: 1.17 to 5.43), and any diabetes complications (HR = 2.21, 95% CI: 1.16 to 4.20). The "decreasing" BMI was associated with an increased risk of all-cause mortality (HR = 1.90, 95% CI: 1.14 to 3.15), compared to the "stable" BMI.

Conclusion

Our findings underscore the significance of continuous BMI monitoring and weight management in patients with T2D. Tailored treatments are crucial for efficiently preventing weight gain and reducing the risk of diabetes complications.

Asthma and its relationship with anthropometric markers among adults

BACKGROUND

Many studies have examined the association between anthropometric indicators and the likelihood of developing asthma. However, no study has yet examined the link between asthma and anthropometric markers of risk. This study addresses this gap in the literature by evaluating the relationship between asthma, smoking, and anthropometric measurements such as body mass index (BMI), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR) among individuals residing in the United States.

METHODS

This cross-sectional study conducted a secondary analysis of the 2011-2014 National Survey of Midlife Development in the United States, using data from 2,257 participants aged 25-74. We classified the participants into four groups based on self-reported smoking and asthma status: nonsmokers with no asthma, asthma alone, smokers only, and smokers with asthma. The outcomes of interest were BMI, WC, HC, and WHR scores in the latter three groups compared to the nonsmokers with no asthma group.

RESULTS

Linear regression analysis showed that those with asthma alone and smokers with asthma were significantly more likely to have a BMI, WC, or HC score of 1 or higher than people without asthma and smokers only.

CONCLUSION

A higher score on the anthropometric parameters was substantially related to participants who had only asthma and those who had both asthma and smoking.

Reliability of Self-Reported Height and Weight in Children: A School-Based Cross-Sectional Study and a Review

Since anthropometric measurements are not always feasible in large surveys, self-reported values are an alternative. Our objective was to assess the reliability of self-reported weight and height values compared to measured values in children with (1) a cross-sectional study in Switzerland and (2) a comprehensive review with a meta-analysis. We conducted a secondary analysis of data from a school-based study in Switzerland of 2616 children and a review of 63 published studies including 122,629 children. In the cross-sectional study, self-reported and measured values were highly correlated (weight: r = 0.96; height: r = 0.92; body mass index (BMI) r = 0.88), although self-reported values tended to underestimate measured values (weight: -1.4 kg; height: -0.9 cm; BMI: -0.4 kg/m²). Prevalence of underweight was overestimated and prevalence of overweight was underestimated using self-reported values. In the meta-analysis, high correlations were found between self-reported and measured values (weight: r = 0.94; height: r = 0.87; BMI: r = 0.88). Weight (-1.4 kg) and BMI (-0.7 kg/m²) were underestimated, and height was slightly overestimated (+0.1 cm) with self-reported values. Self-reported values tended to be more reliable in children above 11 years old. Self-reported weight and height in children can be a reliable alternative to measurements, but should be used with caution to estimate over- or underweight prevalence.

Anthropometric and adiposity indicators and risk of type 2 diabetes: systematic review and dose-response meta-analysis of cohort studies

OBJECTIVE

To present a comprehensive review of the association between measures of body weight, waist, and fat, and different ratios of these measures, and the risk of type 2 diabetes.

DESIGN

Systematic review and dose-response meta-analysis of cohort studies.

DATA SOURCES

PubMed, Scopus, and Web of Science up to 1 May 2021.

REVIEW METHODS

Cohort studies looking at the association between general or central adiposity and body fat content and the risk of type 2 diabetes in the general adult population were included. Two of the authors extracted the data in duplicate. Random effects dose-response meta-analyses were performed to estimate the degree of the associations. Curvilinear associations were modelled with a one stage weighted mixed effects meta-analysis.

RESULTS

216 cohort studies with 2.3 million individuals with type 2 diabetes among 26 million participants were identified. Relative risks were 1.72 (95% confidence interval 1.65 to 1.81; n=182 studies) for an increase in body mass index of 5 units, 1.61 (1.52 to 1.70; n=78) for a 10 cm larger waist circumference, 1.63 (1.50 to 1.78; n=34) for an increase in waist-to-hip ratio of 0.1 units, 1.73 (1.51 to 1.98; n=25) for an increase in waist-to-height ratio of 0.1 units, 1.42 (1.27 to 1.58; n=9) for an increase in visceral adiposity index of 1 unit, 2.05 (1.41 to 2.98; n=6) for a 10% higher percentage body fat, 1.09 (1.05 to 1.13, n=5) for an increase in body shape index of 0.005 units, 2.55 (1.59 to 4.10, n=4) for a 10% higher body adiposity index, and 1.11 (0.98 to 1.27; n=14) for a 10 cm larger hip circumference. A strong positive linear association was found between body mass index and the risk of type 2 diabetes. Positive linear or monotonic associations were also found in all regions and ethnicities, without marked deviation from linearity at a specific cut-off value. Indices of central fatness, independent of overall adiposity, also had positive linear or monotonic associations with the risk of type 2 diabetes. Positive linear or monotonic associations were also found for total and visceral fat mass, although the number of studies was small.

CONCLUSIONS

A higher body mass index was associated with a greater risk of developing type 2 diabetes. A larger waist circumference, independent of overall adiposity, was strongly and linearly associated with the risk of type 2 diabetes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021255338.

Obesity and weight loss are inversely related to mortality and cardiovascular outcome in prediabetes and type 2 diabetes: data from the ORIGIN trial

AIMS

The association of body weight and weight change with mortality and cardiovascular (CV) outcome in patients with diabetes mellitus (DM) is not clearly established. We assessed the relationship between weight, weight change, and outcomes in patients with established CV risk factors and type 2 DM or pre-diabetes.

METHODS AND RESULTS

A total of 12 521 participants from the ORIGIN trial were grouped in BMI categories of low body weight [body mass index (BMI) < 22 kg/m2] normal (22-24.9), overweight (25-29.9), obesity Grades 1-3 (30-34.9, 35-39.9, ≥40 kg/m2, respectively). Outcome variables included total and CV mortality and composite outcomes of CV death, non-fatal stroke, or myocardial infarction plus revascularization or heart failure hospitalization. Follow-up was 6.2 years (interquartile range 5.8-6.7 years). After multivariable adjustment, lowest risks were seen in patients with overweight and mild obesity for total mortality [overweight: hazard ratio (HR) 0.80 (95% confidence interval (CI) 0.69-0.91); obesity Grade 1: HR 0.82 (0.71-0.95), both P < 0.01)] and CV mortality [overweight: HR 0.79 (0.66-0.94); obesity Grade 1: 0.79 (0.65-0.95), all compared to patients with normal BMI, P < 0.05]. Obesity of any severity was not associated with higher mortality. Low body weight was related to higher mortality [HR 1.28 (1.02-1.61); CV mortality: HR 1.34 (1.01-1.79), P < 0.05]. A continued 2-year weight loss was associated with higher risk of mortality [HR 1.32 (1.18-1.46), P < 0.0001] and CV mortality [HR 1.18 (1.02-1.35), compared to patients without weight loss, P < 0.05]. In turn, weight gain was not related to any adverse outcome.

CONCLUSION

Obesity in patients with DM or pre-diabetes and CV risk profile was not associated with higher mortality or adverse CV outcome. The lowest mortality risk was seen in patients with overweight and moderate obesity (BMI 25-35 kg/m2). Weight loss was an independent risk factor for higher mortality compared to no weight loss.

Validation of Obesity Status Based on Self-Reported Data among Filipina and Indonesian Female Migrant Domestic Workers in Macao (SAR), China

BACKGROUND

Migrant domestic workers are at high risk of overweight and obesity. It is crucial to assess the prevalence of obesity among this migrant population, for surveillance and intervention. Self-reported height and weight are commonly used to derive body mass index (BMI) and assess the prevalence of obesity. The accuracy of BMI from self-reported height and weight in migrant populations remains unknown. The aim of this study was to assess the accuracy of BMI from self-reported measures and identify the optimal adjustment to be made to overweight and obesity cut-off points when using self-reported body mass index among migrant workers.

METHODS

Self-reported and objectively measured height and weight were obtained from 1388 female Filipina domestic workers and 369 female Indonesian domestic workers recruited using respondent-driven sampling between November 2016 and August 2017. Self-reported BMI (based on self-reported height and weight) and measured BMI (based on objectively measured height and weight) were calculated as weight in kilograms divided by the square of height in meters for all participants (kg/m2).

RESULTS

BMI derived from self-reported height and weight was underestimated for both Filipina (z = -27.5, p < 0.001) and Indonesian (z = -9.9, p < 0.001) participants. Applying the gold standard of Asian BMI cut-off points to self-reported BMI, the sensitivity in identifying overweight or obesity was 64.4% for Filipina participants and 78.6% for Indonesian participants and the specificity was 97.9% for Filipina participants and 93.8% for Indonesian participants for overweight or obesity. When self-reported measures were used, the receiver operator characteristic (ROC) curves and the corresponding area under the curve (AUC) indicated optimal cut-off points of 22.0 kg/m2 and 22.3 kg/m2 for Filipina and female Indonesian participants for overweight or obesity.

CONCLUSIONS

Although BMI derived from self-reported height and weight allows for quick and low-cost obesity screening, a considerable underestimation of overweight or obesity prevalence was observed in Filipina and female Indonesian migrant domestic workers in Macao (Special Administrative Region, SAR), China. With the best compromise between sensitivity and specificity, the new cut-off points can be used in future studies to identify overweight or obesity in these two populations using self-reported height and weight.

Nicotine Effects, Body Weight Concerns and Smoking: A Literature Review

How people become addicted to cigarette smoking and remain addicted despite repeated attempts to quit requires piecing together a rather complex puzzle. The present review contextualizes the role of nicotine and smoking sensory stimulation on maintaining smoking, describes nicotine's effects on feeding behavior and body weight, and explores the impact of smoking outcome expectancies, including the belief that nicotine suppresses appetite and body weight, on the decision to smoke or vape (use of e-cigarettes). The analysis concludes with a review of rat models of human nicotine intake that attempt to isolate the effects of nicotine on appetite and weight gain. Animal research replicates with relative closeness phenomena observed in smokers, but the rat model falls short of replicating the long-term weight gain observed post-smoking cessation.

Prevalence of sustained hypertension and obesity among urban and rural adolescents: a school-based, cross-sectional study in North India

OBJECTIVE

Recent data on sustained hypertension and obesity among school-going children and adolescents in India are limited. This study evaluates the prevalence of sustained hypertension and obesity and their risk factors among urban and rural adolescents in northern India.

SETTING

A school-based, cross-sectional survey was conducted in the urban and rural areas of Ludhiana, Punjab, India using standardised measurement tools.

PARTICIPANTS

A total of 1959 participants aged 11-17 years (urban: 849; rural: 1110) were included in this school-based survey.

PRIMARY AND SECONDARY OUTCOME MEASURES

To measure sustained hypertension among school children, two distinct blood pressure (BP) measurements were recorded at an interval of 1 week. High BP was defined and classified into three groups as recommended by international guidelines: (1) normal BP: <90th percentile compared with age, sex and height percentile in each age group; (2) prehypertension: BP=90th-95th percentile; and (3) hypertension: BP >95th percentile. The Indian Academy of Pediatrics classification was used to define underweight, normal, overweight and obesity as per the body mass index (BMI) for specific age groups.

RESULTS

The prevalence of sustained hypertension among rural and urban areas was 5.7% and 8.4%, respectively. The prevalence of obesity in rural and urban school children was 2.7% and 11.0%, respectively. The adjusted multiple regression model found that urban area (relative risk ratio (RRR): 1.7, 95% CI 1.01 to 2.93), hypertension (RRR: 7.4, 95% CI 4.21 to 13.16) and high socioeconomic status (RRR: 38.6, 95% CI 16.54 to 90.22) were significantly associated with an increased risk of obesity. However, self-reported regular physical activity had a protective effect on the risk of obesity among adolescents (RRR: 0.4, 95% CI 0.25 to 0.62). Adolescents who were overweight (RRR: 2.66, 95% CI 1.49 to 4.40) or obese (RRR: 7.21, 95% CI 4.09 to 12.70) and reported added salt intake in their diet (RRR: 4.90, 95% CI 2.83 to 8.48) were at higher risk of hypertension.

CONCLUSION

High prevalence of sustained hypertension and obesity was found among urban school children and adolescents in a northern state in India. Hypertension among adolescents was positively associated with overweight and obesity (high BMI). Prevention and early detection of childhood obesity and high BP should be strengthened to prevent the risk of cardiovascular diseases in adults.

Flawed methods and inappropriate conclusions for health policy on overweight and obesity: the Global BMI Mortality Collaboration meta-analysis

Guideline recommendations and health policy decisions rely on evidence from clinical and epidemiological studies. Adequate methodology and appropriate conclusions are essential to support healthcare and health policy decisions. An analysis of body mass index and mortality by the Global BMI Mortality Collaboration (GBMC) concluded that the association of excess body weight with higher mortality was similar worldwide and that overweight and obesity should be combated everywhere. To reach this conclusion, the GBMC used highly selected data, rather than a systematic approach. The GBMC initially chose individual participant data from 239 prospective studies with approximately 10.6 million participants. The GBMC then excluded over 60% of data and over 75% of fatal events by eliminating all cases with any reported disease at baseline or smoking history and all events within the first 5 years of follow-up. After applying these restrictions, the association of overweight with lower mortality was reversed and the association of obesity with higher mortality was increased. Given the major flaws in the selection process, in the adequacy of the data, in the data analysis, and in the interpretation, the GBMC conclusions should be viewed sceptically as a guide to action, either for clinical decisions or for public health in general. The flawed conclusion that overweight is uniformly associated with substantially increased risk of death and thus should be combated in any circumstances may lead not only to unjustified treatment efforts and potential harm in a wide range of clinical conditions but also to a tremendous waste of resources.

Change in body size and mortality: a systematic review and meta-analysis

Background

: Observational studies have reported that weight loss in later life is associated with an increased risk of mortality. However, the association with weight gain is unclear. We conducted a systematic review and meta-analysis of prospective studies assessing the association of weight gain and loss, and mortality.

Methods

: We searched PubMed, Scopus and Web of Science for articles published before 5 September 2015. We included prospective studies that reported enough information to extract hazard ratios (HRs) with the corresponding 95% confidence intervals (CIs) for the association between weight gain and/or weight loss, and all-cause and cause-specific mortality. The estimates were pooled using a random-effects model. Meta-regression models were fitted to explore sources of potential between-study heterogeneity.

Results

: A total of 25 (providing data from 437 772 participants with 34 038 deaths from all causes) and 24 studies (434 694 participants with 31 978 deaths) presented results for the exposures, weight loss and weight gain. Weight loss compared with a stable weight was associated with an increased risk of all-cause (pooled HR: 1.45; 95% CI: 1.34, 1.58), and cardiovascular disease (CVD) mortality (1.50; 1.32, 1.70) and a slightly increased risk of cancer mortality (1.19; 0.97, 1.46). Weight gain was associated with an increased risk of CVD mortality (1.21; 1.07, 1.36) and a slightly increased risk of all-cause mortality (1.07; 1.01, 1.13) and cancer mortality (1.04; 0.96, 1.13). Considerable heterogeneity was observed; the method used to ascertain body size and the proportion of the baseline sample included in the final analysis explained most of the heterogeneity.

Conclusion

: Weight loss and weight gain in midlife are associated with increased risk of all-cause and CVD mortality.

A comparison of measured versus self-reported anthropometrics for assessing obesity in adults: a literature review

Aims: Up-to-date information on the accuracy between different anthropometric data collection methods is vital for the reliability of anthropometric data. A previous review on this matter was conducted a decade ago. Our aim was to conduct a literature review on the accuracy of self-reported height, weight, and body mass index (BMI) against measured values for assessing obesity in adults. To obtain an overview of the present situation, we included studies published after the previous review. Differences according to sex, BMI groups, and continents were also assessed. Methods: Studies published between January 2006 and April 2017 were identified from a literature search on PubMed. Results: Our search retrieved 62 publications on adult populations that showed a tendency for self-reported height to be overestimated and weight to be underestimated when compared with measured values. The findings were similar for both sexes. BMI derived from self-reported height and weight was underestimated; there was a clear tendency for underestimation of overweight (from 1.8%-points to 9.8%-points) and obesity (from 0.7%-points to 13.4%-points) prevalence by self-report. The bias was greater in overweight and obese participants than those of normal weight. Studies conducted in North America showed a greater bias, whereas the bias in Asian studies seemed to be lower than those from other continents. Conclusions: With globally rising obesity rates, accurate estimation of obesity is essential for effective public health policies to support obesity prevention. As self-report bias tends to be higher among overweight and obese individuals, measured anthropometrics provide a more reliable tool for assessing the prevalence of obesity.

Bias in Hazard Ratios Arising From Misclassification According to Self-Reported Weight and Height in Observational Studies of Body Mass Index and Mortality

Misclassification of body mass index (BMI) categories arising from self-reported weight and height can bias hazard ratios in studies of BMI and mortality. We examined the effects on hazard ratios of such misclassification using national US survey data for 1976 through 2010 that had both measured and self-reported weight and height along with mortality follow-up for 48,763 adults and a subset of 17,405 healthy never-smokers. BMI was categorized as <22.5 (low), 22.5-24.9 (referent), 25.0-29.9 (overweight), 30.0-34.9 (class I obesity), and ≥35.0 (class II-III obesity). Misreporting at higher BMI categories tended to bias hazard ratios upwards for those categories, but that effect was augmented, counterbalanced, or even reversed by misreporting in other BMI categories, in particular those that affected the reference category. For example, among healthy male never-smokers, misclassifications affecting the overweight and the reference categories changed the hazard ratio for overweight from 0.85 with measured data to 1.24 with self-reported data. Both the magnitude and direction of bias varied according to the underlying hazard ratios in measured data, showing that findings on bias from one study should not be extrapolated to a study with different underlying hazard ratios. Because of misclassification effects, self-reported weight and height cannot reliably indicate the lowest-risk BMI category.

Measured versus self-reported body height and body mass in patients after an acute coronary syndrome

The basic anthropometric data describing a person in the broadest context are body weight and height, two of the most frequently analyzed somatometric parameters. The same is true I in relation to clinical patients. The aim of the present study was to compare the self-reported and actual body weight, height and BMI in patients suffering from coronary artery disease and undergoing cardiac rehabilitation. The study sample consisted of 100 patients treated for coronary artery disease. The patients were asked to state their body weight and height. At the same time a three-person study team took measurements, which were later the basis for verification and objective assessment of the data provided by the patients. Statistical analysis was performed with Statistics 11.0 PL software. The analysis of mean results for the assessed group of patients has shown the presence of statistically significant differences between declared and actual data. The differences were observed for both male and female study population. It has been proven that the subjects declare greater body height (mean value 1.697 m vs. 1.666 m) and lower body weight (80.643 kg vs. 82.051 kg). Based on the data from surveys and direct measurements, the body mass index for the self-reported and actual data was calculated. A comparison of these values has shown considerable statistically significant differences. The differences between declared and actual data point to highly subjective self-assessment, which disqualifies the declared data in the context of monitoring of treatment and rehabilitation processes. The authors believe that actual data should be used in direct trial examination of patients suffering from coronary artery disease who presented with acute coronary syndrome.

Comparative effects of the restriction method in two large observational studies of body mass index and mortality among adults

BACKGROUND

A method applied in some large studies of weight and mortality is to begin with a well-defined analytic cohort and use successive restrictions to control for methodologic bias and arrive at final analytic results.

MATERIALS AND METHODS

Two observational studies of body mass index and mortality allow a comparative assessment of these restrictions in very large data sets. One was a meta-analysis of individual participant data with a sample size of 8 million. The second was a study of a South Korean cohort with a sample size of 12 million. Both presented results for participants without pre-existing disease before and after restricting the sample to never-smokers and deleting the first 5 years of follow-up.

RESULTS

Initial results from both studies were generally similar, with hazard ratios (HRs) below 1 for overweight and above 1 for underweight and obesity. The meta-analysis showed higher HRs for overweight and obesity after the restrictions, including a change in the direction of the HR for overweight from 0·99 (95% CI: 0·98-1·01) to 1·11 (95% CI: 1·10, 1·11). The South Korean data showed little effect of the restrictions and the HR for overweight changed from 0·85 (95% CI: 0·84-0·86) to 0·91 (95% CI: 0·90, 0·91). The summary effect size for overweight was 0·90 (95% CI: 0·89-0·91) before restrictions and 1·02 (95% CI: 1·02, 1·03) after restrictions.

CONCLUSIONS

The effect of the restrictions is not consistent across studies, weakening the argument that analyses without such restrictions lack validity.

Self-administered nicotine differentially impacts body weight gain in obesity-prone and obesity-resistant rats

Obesity and tobacco smoking represent the largest challenges to public health, but the causal relationship between nicotine and obesity is poorly understood. Nicotine suppresses body weight gain, a factor impacting smoking initiation and the failure to quit, particularly among obese smokers. The impact of nicotine on body weight regulation in obesity-prone and obesity-resistant populations consuming densely caloric diets is unknown. In the current experiment, body weight gain of adult male rats maintained on a high energy diet (31.8% kcal from fat) distributed into obesity-prone (OP), obesity-resistant (OR) and an intermediate group, which was placed on standard rodent chow (Chow). These rats were surgically implanted with intravenous catheters and allowed to self-administer nicotine (0 or 60μg/kg/infusion, a standard self-administration dose) in 1-h sessions for 20 consecutive days. Self-administered nicotine significantly suppressed body weight gain but not food intake in OP and Chow rats. Self-administered nicotine had no effect on body weight gain in OR rats. These data suggest that: 1) OR rats are also resistant to nicotine-induced suppression of body weight gain; and 2) nicotine may reduce levels of obesity in a subset of smokers prone to obesity.

The effect of tobacco cessation on weight gain, obesity, and diabetes risk

OBJECTIVE

Most smokers gain weight after quitting, and some develop new onset obesity and type 2 diabetes. The purpose of this paper is to synthesize the current science investigating the consequences of tobacco cessation on body weight and diabetes, as well as intervention strategies that minimize or prevent weight gain while still allowing for successful tobacco cessation.

METHODS

Systematic reviews and relevant studies that were published since prior reviews were selected.

RESULTS

Smoking cessation can cause excessive weight gain in some individuals and can be associated with clinically significant outcomes such as diabetes or obesity onset. Interventions that combine smoking cessation and weight control can be effective for improving cessation and minimizing weight gain but need to be tested in specific populations.

CONCLUSIONS

Despite the health benefits of quitting tobacco, post-cessation weight gain and new onset obesity and diabetes are a significant concern. Promising interventions may need to be more widely applied to reduce the consequences of both obesity and tobacco use.

[Validity of anthropometric measurements and weight perceptions reported by relatives of children under 4 years old]

OBJECTIVE

To assess the validity of weight and height measurements reported by parents and the perception of their children's weight status in order to assess the prevalence of overweight children under 4 years old.

METHODS

Cross-sectional study. Anthropometric data was collected by self-report questionnaires completed by parents of children 3-45 months old: 1) information from paediatric check-ups (gold standard); 2) information reported from the home environment; and 3) data from individual perceptions. WHO standards were used.

RESULTS

Reported height was underestimated, thus reported weight/height and BMI/age were overestimated. Overweight prevalence according to paediatric check-ups was 18.6%, compared to 26.5% reported prevalence, showing a moderate concordance (Kappa: 0.47 [0.34-0.60]), 70% sensitivity and 84% specificity. Subjective perception was 11.2%, representing 30% sensitivity and 93% specificity.

CONCLUSIONS

The reported information has little validity for population-based studies, as height is underestimated and overweight status is not correctly perceived due to distortion of individual perception. Questionnaires must be validated and awareness raised among families.

Body Mass Index and Cancer Mortality Among Korean Older Middle-Aged Men: A Prospective Cohort Study

The association of body mass index (BMI; kg/m) with overall and site-specific cancer mortality in Asians is not well understood. A total of 113,478 men from the Korean Veterans Health Study who returned a postal survey in 2004 were followed up until 2010. The adjusted hazard ratios (HRs) of cancer mortality were calculated using a Cox model. During 6.4 years of follow-up, 3478 men died from cancer. A reverse J-curve association with a nadir at 25.0 to 27.4 kg/m was observed. Below 25 kg/m, the HRs of death for each 5 kg/m decrease in BMI were 1.72 (95% confidence interval = 1.57-1.90) for overall cancer; 3.63 (2.57-5.12) for upper aerodigestive tract (UADT) cancers, including oral cavity and larynx [HR = 4.21 (2.18-8.12)] and esophagus [HR = 2.96 (1.82-4.81)] cancers; 1.52 (1.35-1.71) for non-UADT and non-lung cancers, including stomach [HR = 2.72 (2.13-3.48)] and large intestine [HR = 1.68 (1.20-2.36)] cancers; and 1.93 (1.59-2.34) for lung cancer. In the range of 25 to 47 kg/m, the HRs for each 5 kg/m increase in BMI were 1.27 (1.03-1.56) for overall cancer mortality and 1.57 (1.02-2.43) for lung cancer mortality. In individuals <25 kg/m, inverse associations with mortality from overall cancer and non-UADT and non-lung cancer were stronger in never-smokers than in current smokers. Both low and high BMI were strong predictors of mortality from overall and several site-specific cancers in Korean men. Further research is needed to evaluate whether interventions involving weight change (loss or gain) reduce the risk of cancer or improve the survival.

Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts

BACKGROUND

In Switzerland, as in other developed countries, the prevalence of overweight and obesity has increased substantially since the early 1990s. Most of the analyses so far have been based on sporadic surveys or self-reported data and did not offer potential for small-area analyses. The goal of this study was to investigate spatial variation and determinants of obesity among young Swiss men using recent conscription data.

METHODS

A complete, anonymized dataset of conscription records for the 2010-2012 period were provided by Swiss Armed Forces. We used a series of Bayesian hierarchical logistic regression models to investigate the spatial pattern of obesity across 3,187 postcodes, varying them by type of random effects (spatially unstructured and structured), level of adjustment by individual (age and professional status) and area-based [urbanicity and index of socio-economic position (SEP)] characteristics.

RESULTS

The analysed dataset consisted of 100,919 conscripts, out of which 5,892 (5.8 %) were obese. Crude obesity prevalence increased with age among conscripts of lower individual and area-based SEP and varied greatly over postcodes. Best model's estimates of adjusted odds ratios of obesity on postcode level ranged from 0.61 to 1.93 and showed a strong spatial pattern of obesity risk across the country. Odds ratios above 1 concentrated in central and north Switzerland. Smaller pockets of elevated obesity risk also emerged around cities of Geneva, Fribourg and Lausanne. Lower estimates were observed in North-East and East as well as south of the Alps. Importantly, small regional outliers were observed and patterning did not follow administrative boundaries. Similarly as with crude obesity prevalence, the best fitting model confirmed increasing risk of obesity with age and among conscripts of lower professional status. The risk decreased with higher area-based SEP and, to a lesser degree - in rural areas.

CONCLUSION

In Switzerland, there is a substantial spatial variation in obesity risk among young Swiss men. Small-area estimates of obesity risk derived from conscripts records contribute to its understanding and could be used to design further studies and interventions.

Body mass index and mortality among Korean elderly in rural communities: Kangwha Cohort Study

Background

The relationship between body mass index (BMI) and mortality may differ by ethnicity, but its exact nature remains unclear among Koreans. The study aim was to prospectively examine the association between BMI and mortality in Korean.

Methods

6166 residents (2636 men; 3530 women) of rural communities (Kangwha County, Republic of Korea) aged 55 and above were followed up for deaths from 1985–2008. The multivariable-adjusted hazard ratios were calculated using the Cox proportional hazards model.

Results

During the 23.8 years of follow-up (an average of 12.5 years in men and 15.7 years in women), 2174 men and 2372 women died. Men with BMI of 21.0–27.4 and women with BMI of 20.0–27.4 had a minimal risk for all-cause mortality. A lower BMI as well as a higher BMI increased the hazard ratio of death. For example, multivariable-adjusted hazard ratios associated with BMI below 16, and with BMI of 27.5 and above, were 2.4 (95% CI = 1.6–3.5) and 1.5 (95% CI = 1.1–1.9) respectively, in men, compared to those with BMI of 23.0–24.9. This reverse J-curve association was maintained among never smokers, and among people with no known chronic diseases. Higher BMI increased vascular mortality, while lower BMI increased deaths from vascular diseases, cancers, and, especially, respiratory diseases. Except for cancers, these associations were generally weaker in women than in men.

Conclusions

A reverse J-curve association between BMI and all-cause mortality may exist. BMI of 21–27.4 (rather than the range suggested by WHO of 18.5–23 for Asians) may be considered a normal range with acceptable risk in Koreans aged 55 and above, and may be used as cut points for interventions. More concern should be given to people with BMI above and below a BMI range with acceptable risk. Further studies are needed to determine ethnicity-specific associations.

The impact of obesity and weight gain on development of sleep problems in a population-based sample

OBJECTIVES

The objective of this study was to investigate the role of obesity and weight gain in the development of sleep problems in a population-based cohort.

MATERIAL AND METHODS

A population-based sample of men (n = 1896, aged 40-79 years) and women (n = 5116, age ≥20 years) responded to questionnaires at baseline and follow-up after 10-13 years. Sleep problems were assessed through questions about difficulties initiating sleep (DIS), difficulties maintaining sleep (DMS), excessive daytime sleepiness (EDS), and insomnia. Body mass index (BMI) was calculated from self-reported weight and height at both baseline and follow-up, while confounding factors (physical activity, tobacco and alcohol use, somatic disease, and snoring) were based on responses at baseline.

RESULTS

Although overweight and obese subjects reported more sleep problems at baseline, there was no independent association between BMI level at baseline and development of new sleep problems. Subjects in the quartile with the highest rise in BMI with a weight gain exceeding 2.06 kg/m2 had a higher risk of developing DMS [adjusted odds ratio (OR) 1.58; 95% confidence interval (CI) 1.25-2.01), EDS (2.25; 1.65-3.06], and insomnia (2.78; 1.60-4.82). Weight gain was not associated with the development of DIS.

CONCLUSIONS

Weight gain is an independent risk factor for developing several sleep problems and daytime sleepiness. The presence of overweight and weight gain should be considered when treating patients with sleep problems.

Estimating population attributable fractions to quantify the health burden of obesity

PURPOSE

Obesity is a highly prevalent condition in the United States and elsewhere and is associated with increased mortality and morbidity. Here, we discuss some issues involved in quantifying the health burden of obesity using population attributable fraction (PAF) estimates and provide examples.

METHODS

We searched PubMed for articles reporting attributable fraction estimates for obesity. We reviewed eligible articles to identify methodological concerns and tabulated illustrative examples of PAF estimates for obesity relative to cancer, diabetes, cardiovascular disease, and all-cause mortality.

RESULTS

There is considerable variability among studies regarding the methods used for PAF calculation and the selection of appropriate counterfactuals. The reported estimates ranged from 5% to 15% for all-cause mortality, -0.2% to 8% for all-cancer incidence, 7% to 44% for cardiovascular disease incidence, and 3% to 83% for diabetes incidence.

CONCLUSIONS

To evaluate a given estimate, it is important to consider whether the exposure and outcome were defined similarly for the PAF and for the relative risks, whether the relative risks were suitable for the population at hand, and whether PAF was calculated using correct methods. Strong causal assumptions are not necessarily warranted. In general, PAFs for obesity may be best considered as indicators of association.

Body mass index categories in observational studies of weight and risk of death

The World Health Organization (Geneva, Switzerland) and the National Heart, Lung, and Blood Institute (Bethesda, Maryland) have developed standard categories of body mass index (BMI) (calculated as weight (kg)/height (m)(2)) of less than 18.5 (underweight), 18.5-24.9 (normal weight), 25.0-29.9 (overweight), and 30.0 or more (obesity). Nevertheless, studies of BMI and the risk of death sometimes use nonstandard BMI categories that vary across studies. In a meta-analysis of 8 large studies that used nonstandard BMI categories and were published between 1999 and 2014 and included 5.8 million participants, hazard ratios tended to be small throughout the range of overweight and normal weight. Risks were similar between subjects of high-normal weight (BMI of approximately 23.0-24.9) and those of low overweight (BMI of approximately 25.0-27.4). In an example using national survey data, minor variations in the reference category affected hazard ratios. For example, choosing high-normal weight (BMI of 23.0-24.9) instead of standard normal weight (BMI of 18.5-24.9) as the reference category produced higher nonsignificant hazard ratios (1.05 vs. 0.97 for men and 1.06 vs. 1.02 for women) for the standard overweight category (BMI of 25.0-29.9). Use of the standard BMI groupings avoids problems of ad hoc and post hoc category selection and facilitates between-study comparisons. The ways in which BMI data are categorized and reported may shape inferences about the degree of risk for various BMI categories.

High frequency body mass measurement, feedback, and health behaviors

We analyze weight and fat percentage measurements of respondents in an online general population panel in the Netherlands, collected using wireless scales, with an average frequency of 1.6 measurements per week. First, we document the existence of a weekly cycle; body mass is lowest on Fridays and highest on Mondays, showing significant (p<0.01) differences of, on average, 0.2 kilogram in weight, 0.06 in BMI value, and 0.03 in fat percentage. Second, we find that in the general population fat-based measures of obesity point at a three times larger prevalence of obesity (53%) than BMI-based measures (17%). Third, we find that feedback that includes a recommended weight range increases the temporal variation in individual body mass by almost ten percent (sd for weight increases from 1.13 to 1.22; sd for BMI increases from 0.37 to 0.41; sd for fat percentage increases from 0.55 to 0.61.

Socioeconomic, temporal and regional variation in body mass index among 188,537 Swiss male conscripts born between 1986 and 1992

Background

Rising levels of overweight and obesity are important public-health concerns worldwide. The purpose of this study is to elucidate their prevalence and trends in Switzerland by analyzing variations in Body Mass Index (BMI) of Swiss conscripts.

Methods

The conscription records were provided by the Swiss Army. This study focussed on conscripts 18.5–20.5 years of age from the seven one-year birth cohorts spanning the period 1986–1992. BMI across professional status, area-based socioeconomic position (abSEP), urbanicity and regions was analyzed. Two piecewise quantile regression models with linear splines for three birth-cohort groups were used to examine the association of median BMI with explanatory variables and to determine the extent to which BMI has varied over time.

Results

The study population consisted of 188,537 individuals. Median BMI was 22.51 kg/m² (22.45–22.57 95% confidence interval (CI)). BMI was lower among conscripts of high professional status (−0.46 kg/m²; 95% CI: −0.50, −0.42, compared with low), living in areas of high abSEP (−0.11 kg/m²; 95% CI: −0.16, −0.07 compared to medium) and from urban communities (−0.07 kg/m²; 95% CI: −0.11, −0.03, compared with peri-urban). Comparing with Midland, median BMI was highest in the North-West (0.25 kg/m²; 95% CI: 0.19–0.30) and Central regions (0.11 kg/m²; 95% CI: 0.05–0.16) and lowest in the East (−0.19 kg/m²; 95% CI: −0.24, −0.14) and Lake Geneva regions (−0.15 kg/m²; 95% CI: −0.20, −0.09). Trajectories of regional BMI growth varied across birth cohorts, with median BMI remaining high in the Central and North-West regions, whereas stabilization and in some cases a decline were observed elsewhere.

Conclusions

BMI of Swiss conscripts is associated with individual and abSEP and urbanicity. Results show regional variation in the levels and temporal trajectories of BMI growth and signal their possible slowdown among recent birth cohorts.

Mortality risk associated with underweight: a census-linked cohort of 31,578 individuals with up to 32 years of follow-up

Background

In contrast to obesity, information on the health risks of underweight is sparse. We examined the long-term association between underweight and mortality by considering factors possibly influencing this relationship.

Methods

We included 31,578 individuals aged 25–74 years, who participated in population based health studies between 1977 and 1993 and were followed-up for survival until 2008 by record linkage with the Swiss National Cohort (SNC). Body Mass Index (BMI) was calculated from measured (53% of study population) or self-reported height and weight. Underweight was defined as BMI < 18.5 kg/m². Cox regression models were used to determine mortality Hazard Ratios (HR) of underweight vs. normal weight (BMI 18.5- < 25.0 kg/m²). Covariates were study, sex, smoking, healthy eating proxy, sports frequency, and educational level.

Results

Underweight individuals represented 3.0% of the total study population (n = 945), and were mostly women (89.9%). Compared to normal weight, underweight was associated with increased all-cause mortality (HR: 1.37; 95% CI: 1.14-1.65). Increased risk was apparent in both sexes, regardless of smoking status, and mainly driven by excess death from external causes (HR: 3.18; 1.96-5.17), but not cancer, cardiovascular or respiratory diseases. The HR were 1.16 (0.88-1.53) in studies with measured BMI and 1.59 (1.24-2.05) with self-reported BMI.

Conclusions

The increased risk of dying of underweight people was mainly due to an increased mortality risk from external causes. Using self-reported BMI may lead to an overestimation of mortality risk associated with underweight.

Association of obesity with cardiovascular disease mortality in the PLCO trial

OBJECTIVE

Obesity is a risk factor for cardiovascular disease (CVD) mortality, but the association between obesity and specific causes of CVD mortality is still under investigation.

METHOD

We prospectively examined body-mass index (BMI) in relation to CVD-specific causes of death in approximately 86,000 US men and women in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, followed for up to 13 years. BMI was calculated from self-reported weight and height at baseline. Hazard ratios (HRs) were calculated overall and stratified by sex, smoking status, and educational level.

RESULT

Overweight non-obese participants (BMI: 25.0-29.9) were not at excess risk for CVD mortality (HR and CIs are 1.02 [0.92-1.13]), compared to participants of normal BMI (18.5-24.9). Excess CVD mortality was observed for participants of BMI 30.0-34.9 (HR and CIs: 1.29 [1.13-1.48]), BMI 35.0-39.9 (HR and CIs: 1.87 [1.51-2.32]) and BMI 40.0+ (HR and CIs: 2.21 [1.57-3.21]) (p<0.001 for trend). BMI was unrelated to mortality due to stroke. The observed association of BMI with CVD was independent of gender, smoking status and educational level.

CONCLUSION

Obesity is associated with increased mortality due to CVD.

Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis

IMPORTANCE

Estimates of the relative mortality risks associated with normal weight, overweight, and obesity may help to inform decision making in the clinical setting.

OBJECTIVE

To perform a systematic review of reported hazard ratios (HRs) of all-cause mortality for overweight and obesity relative to normal weight in the general population.

DATA SOURCES

PubMed and EMBASE electronic databases were searched through September 30, 2012, without language restrictions.

STUDY SELECTION

Articles that reported HRs for all-cause mortality using standard body mass index (BMI) categories from prospective studies of general populations of adults were selected by consensus among multiple reviewers. Studies were excluded that used nonstandard categories or that were limited to adolescents or to those with specific medical conditions or to those undergoing specific procedures. PubMed searches yielded 7034 articles, of which 141 (2.0%) were eligible. An EMBASE search yielded 2 additional articles. After eliminating overlap, 97 studies were retained for analysis, providing a combined sample size of more than 2.88 million individuals and more than 270,000 deaths.

DATA EXTRACTION

Data were extracted by 1 reviewer and then reviewed by 3 independent reviewers. We selected the most complex model available for the full sample and used a variety of sensitivity analyses to address issues of possible overadjustment (adjusted for factors in causal pathway) or underadjustment (not adjusted for at least age, sex, and smoking).

RESULTS

Random-effects summary all-cause mortality HRs for overweight (BMI of 25-<30), obesity (BMI of ≥30), grade 1 obesity (BMI of 30-<35), and grades 2 and 3 obesity (BMI of ≥35) were calculated relative to normal weight (BMI of 18.5-<25). The summary HRs were 0.94 (95% CI, 0.91-0.96) for overweight, 1.18 (95% CI, 1.12-1.25) for obesity (all grades combined), 0.95 (95% CI, 0.88-1.01) for grade 1 obesity, and 1.29 (95% CI, 1.18-1.41) for grades 2 and 3 obesity. These findings persisted when limited to studies with measured weight and height that were considered to be adequately adjusted. The HRs tended to be higher when weight and height were self-reported rather than measured.

CONCLUSIONS AND RELEVANCE

Relative to normal weight, both obesity (all grades) and grades 2 and 3 obesity were associated with significantly higher all-cause mortality. Grade 1 obesity overall was not associated with higher mortality, and overweight was associated with significantly lower all-cause mortality. The use of predefined standard BMI groupings can facilitate between-study comparisons.

Cardiovascular risk factors attributable to obesity and overweight in Switzerland

BACKGROUND AND AIMS

Obesity increases the risk for cardiovascular risk factors (CVRFs), including hypertension, dyslipidaemia and type 2 diabetes. In this study, we assessed the burden of overweight and obesity on CVRFs in Switzerland, using Swiss-specific population attributable fractions (PAFs).

METHODS AND RESULTS

The number of cases of CVRFs that could have been prevented if the increase in overweight and obesity in Switzerland had been contained was estimated using gender-specific, age- and smoking-adjusted PAFs for overweight and obesity. PAFs were estimated from the Swiss Health Survey 2007 (self-reported) and the CoLaus study (measured) data. PAFs from self-reported were lower than from measured data. Using measured data, overweight and obesity contributed to 38% of hypertension cases in men (32% in women). In men, overweight had a larger impact than obesity (22.2% and 15.6%, respectively), while the opposite was observed for women (13.6% and 18.1%, respectively). In men, 37% of dyslipidaemia (30% in women) could be attributed to overweight and obesity; overweight had a higher contribution than obesity in both sexes. In men, 57% of type 2 diabetes (62% in women) was attributable to overweight and obesity; obesity had a larger impact than overweight in both sexes. Overall, approximately 27,000 cases of type 2 diabetes, 63,000 cases of high blood pressure and 37,000 cases of dyslipidaemia could have been avoided if overweight and obesity levels were maintained at 1992 levels.

CONCLUSION

A large proportion of CVRFs is attributable to overweight and/or obesity and could have been prevented by containing the overweight/obesity epidemic.

Childhood and family influences on body mass index in early adulthood: findings from the Ontario Child Health Study

BACKGROUND

Overweight and obesity are steadily increasing worldwide with the greatest prevalence occurring in high-income countries. Many factors influence body mass index (BMI); however multiple influences assessed in families and individuals are rarely studied together in a prospective design. Our objective was to model the impact of multiple influences at the child (low birth weight, history of maltreatment, a history of childhood mental and physical conditions, and school difficulties) and family level (parental income and education, parental mental and physical health, and family functioning) on BMI in early adulthood.

METHODS

We used data from the Ontario Child Health Study, a prospective, population-based study of 3,294 children (ages 4-16 years) enrolled in 1983 and followed up in 2001 (N = 1,928; ages 21-35 years). Using multilevel models, we tested the association between family and child-level variables and adult BMI after controlling for sociodemographic variables and health status in early adulthood.

RESULTS

At the child level, presence of psychiatric disorder and school difficulties were related to higher BMI in early adulthood. At the family level, receipt of social assistance was associated with higher BMI, whereas family functioning, having immigrant parents and higher levels of parental education were associated with lower BMI. We found that gender moderated the effect of two risk factors on BMI: receipt of social assistance and presence of a medical condition in childhood. In females, but not in males, the presence of these risk factors was associated with higher BMI in early adulthood.

CONCLUSION

Overall, these findings indicate that childhood risk factors associated with higher BMI in early adulthood are multi-faceted and long-lasting. These findings highlight the need for preventive interventions to be implemented at the family level in childhood.

Can self-reported height and weight be used among people living with HIV/AIDS?

To assess the reliability and validity of self-reported height and weight in adults living with HIV/AIDS (ALWHA) we assessed 508 ALWHA of both genders on antiretroviral therapy. Height and weight were directly measured in a subsample. Sensitivity and specificity analysis were performed to determine the validity of self-reported measures. Bland-Altman's method was used to calculate the limits of agreement between values while reliability was assessed using intraclass coefficients. Regression equations were devised to determine actual measures from self-reported values. Mean differences among measured and self-reported weight were -0.96 kg for men and -0.54 kg for women. Mean height differences were less than 2 cm, yielding good reliability for body mass index (BMI). Overweight (BMI ≥ 25 kg/m(2)) diagnosis sensitivity was 90.6% and specificity was 81.2%. Corrected measures determined by regression equations had stronger correlation with self-reported values (r > 0.980). Self-reported height and weight showed good reliability and validity compared with directly measured height and weight. However, measures should be corrected whenever possible to achieve higher accuracy.

Health status, hospitalizations, day procedures, and physician costs associated with body mass index (BMI) levels in Ontario, Canada

Background

Obesity is today’s principal neglected public health problem, as a rising proportion of adults will succumb to the medical complications of obesity. However, little is known about the burden of obesity in adults living in Ontario.

Objectives

To present an overview of the human and economic burden associated with BMI categories in Ontario, Canada, in terms of socio-demographics, comorbidities, health-related quality of life (HRQoL) and costs associated with hospitalization, same day procedures and physician visits.

Methods

The records of all Ontarians who participated in the Canadian Community Health Survey (CCHS), cycle 1.1 and provided consent to data linkage were linked to three administrative databases. Socio-demographic variables, medical characteristics, HRQoL, one year hospitalization, day procedure and physician costs were described per BMI category. Regression analyses were conducted to identify predictors of medical characteristics, HRQoL and costs.

Results

More than 50% of adult participants were either overweight or obese in 2000/2001. Obese adults, and to a lesser extent overweight adults, were more likely to report physician-diagnosed comorbid conditions, to use medications, and to have a lower HRQoL. After covariate adjustment, the hospitalization and physician costs were respectively 40% and 22% higher among obese and overweight adults than among normal-weight adults. No statistical cost differences were observed between normal and underweight individuals or between normal and overweight individuals. HRQoL was significantly lower in underweight and obese adults when compared to normal-weight individuals.

Conclusions

Due to the large human and economic burden associated with under- or excess-weight, policies promoting healthy weight should remain a priority for governments and employers.

A comparison between Atlantic Canadian and national correction equations to improve the accuracy of self-reported obesity estimates in Atlantic Canada

OBJECTIVES

To determine whether obesity correction equations for the Canadian general population, which are dependent on the prevalence of obesity, are appropriate for use in Atlantic Canada, which has the highest obesity rates in the country. Also, to compare the accuracy of the national equations to equations developed specifically for the Atlantic Canadian population.

METHODS

The dataset consisted of Canadian Community Health Survey (CCHS) 2007-2008 data collected on 17,126 Atlantic Canadians and a subsample of adults, who provided measured height and weight (MHW) data. Atlantic correction equations were developed in the MHW subsample. Using separate multiple regression models for men and women, self-reported body mass index (BMI) was corrected by multiplying the self-reported estimate by its corresponding model coefficient and adding the model intercept. Paired t-tests were used to determine whether corrected mean BMI values were significantly more accurate (i.e., closer to measured data) than the equivalent means based on self-reported data. The analyses were repeated using the national equations.

RESULTS

Both the Atlantic and the national equations yielded corrected obesity estimates that were significantly more accurate than those based on self-report.

CONCLUSION

The results provide some evidence of the generalizability of the national equations to atypical regions of Canada.

Dose-dependent positive association between cigarette smoking, abdominal obesity and body fat: cross-sectional data from a population-based survey

Background

Although smokers tend to have a lower body-mass index than non-smokers, smoking may favour abdominal body fat accumulation. To our knowledge, no population-based studies have assessed the relationship between smoking and body fat composition. We assessed the association between cigarette smoking and waist circumference, body fat, and body-mass index.

Methods

Height, weight, and waist circumference were measured among 6,123 Caucasians (ages 35-75) from a cross-sectional population-based study in Switzerland. Abdominal obesity was defined as waist circumference ≥102 cm for men and ≥88 cm for women. Body fat (percent total body weight) was measured by electrical bioimpedance. Age- and sex-specific body fat cut-offs were used to define excess body fat. Cigarettes smoked per day were assessed by self-administered questionnaire. Age-adjusted means and odds ratios were calculated using linear and logistic regression.

Results

Current smokers (29% of men and 24% of women) had lower mean waist circumference, body fat percentage, and body-mass index compared with non-smokers. Age-adjusted mean waist circumference and body fat increased with cigarettes smoked per day among smokers. The association between cigarettes smoked per day and body-mass index was non-significant. Compared with light smokers, the adjusted odds ratio (OR) for abdominal obesity in men was 1.28 (0.78-2.10) for moderate smokers and 1.94 (1.15-3.27) for heavy smokers (P = 0.03 for trend), and 1.07 (0.72-1.58) and 2.15 (1.26-3.64) in female moderate and heavy smokers, respectively (P < 0.01 for trend). Compared with light smokers, the OR for excess body fat in men was 1.05 (95% CI: 0.58-1.92) for moderate smokers and 1.15 (0.60-2.20) for heavy smokers (P = 0.75 for trend) and 1.34 (0.89-2.00) and 2.11 (1.25-3.57), respectively in women (P = 0.07 for trend).

Conclusion

Among smokers, cigarettes smoked per day were positively associated with central fat accumulation, particularly in women.

Reverse causation and illness-related weight loss in observational studies of body weight and mortality

In studies of weight and mortality, the construct of reverse causation has come to be used to imply that the exposure-outcome relation is biased by weight loss due to preexisting illness. Observed weight-mortality associations are sometimes thought to result from this bias. Evidence for the occurrence of such bias is weak and inconsistent, suggesting that either the analytical methods used have been inadequate or else illness-related weight loss is not an important source of bias. Deleting participants has been the most frequent approach to control possible bias. As implemented, this can lead to deletion of almost 90% of all deaths in a sample and to deletion of more overweight and obese participants than participants with normal or below normal weight. Because it has not been demonstrated that the procedures used to adjust for reverse causation increase validity or have large or systematic effects on relative risks, it is premature to consider reverse causation as an important cause of bias. Further research would be useful to elucidate the potential effects and importance of reverse causation or illness-related weight loss as a source of bias in the observed associations between weight and mortality in cohort studies.

Temporal trends in misclassification patterns of measured and self-report based body mass index categories--findings from three population surveys in Ireland

BACKGROUND

As the use of self-reported data to classify obesity continues, the temporal change in the accuracy of self-report measurement when compared to clinical measurement remains unclear. The objective of this study was to examine temporal trends in misclassification patterns, as well as sensitivity and specificity, of clinically measured versus self-report based body mass index (BMI) from three national lifestyle surveys over a 10-year period.

METHODS

The Surveys of Lifestyle Attitudes and Nutrition (SLÁN) were interview based cross-sectional survey/measurements involving nationally representative samples in 1998, 2002 and 2007. Data from a subsample of both self-reported and measured height and weight were available from 66 men and 142 women in 1998, 147 men and 184 women in 2002 and 909 men and 1128 women in 2007. Respondents were classified into the BMI categories normal (< 25 kg m⁻²), overweight (25- < 30 kg m⁻²) and obese (≥ 30 kg m⁻²).

RESULTS

Underreporting of BMI increased across the three surveys (14%→21%→24%; p = 0.002). Sensitivity scores for the normal category exceeded 94% in all three surveys but decreased for the overweight (75%→68%→66%) and obese categories (80%→64%→53%). Simultaneously, specificity levels remained high.

CONCLUSIONS

BMI values based on self-reported determinations of height and weight in population samples are underestimating the true prevalence of the obesity epidemic and this underestimation is increasing with time. The decreased sensitivity and consistently high specificity scores in the obese category across time, highlights the limitation of self-report based BMI classifications and the need for simple, readily comprehensible indicators of obesity.

Variations in BMI and prevalence of health risks in diverse racial and ethnic populations

When examining health risks associated with the BMI, investigators often rely on the customary BMI thresholds of the 1995 World Health Organization report. However, within-interval variations in morbidity and mortality can be substantial, and the thresholds do not necessarily correspond to identifiable risk increases. Comparing the prevalence of hypertension, diabetes, coronary heart disease (CHD), asthma, and arthritis among non-Hispanic whites, blacks, East Asians and Hispanics, we examine differences in the BMI-health-risk relationships for small BMI increments. The analysis is based on 11 years of data of the National Health Interview Survey (NHIS), with a sample size of 337,375 for the combined 1997-2007 Sample Adult. The analysis uses multivariate logistic regression models, employing a nonparametric approach to modeling the BMI-health-risk relationship, while relying on narrowly defined BMI categories. Rising BMI levels are associated with higher levels of chronic disease burdens in four major racial and ethnic groups, even after adjusting for many socio-demographic characteristics and three important health-related behaviors (smoking, physical activity, alcohol consumption). For all population groups, except East Asians, a modestly higher disease risk was noted for persons with a BMI <20 compared with persons with BMI in the range of 20-21. Using five chronic conditions as risk criteria, a categorization of the BMI into normal weight, overweight, or obesity appears arbitrary. Although the prevalence of disease risks differs among racial and ethnic groups regardless of BMI levels, the evidence presented here does not support the notion that the BMI-health-risk profile of East Asians and others warrants race-specific BMI cutoff points.

Use of self-reported height and weight biases the body mass index-mortality association

Background

Many large-scale epidemiologic data sources used to evaluate the body mass index (BMI: kg/m²) mortality association have relied on BMI derived from self-reported height and weight. Although measured BMI (BMI_M) and self-reported BMI (BMI_SR) correlate highly, self-reports are systematically biased.

Objective

To rigorously examine how self-reporting bias influences the association between BMI and mortality rate.

Subjects

Samples representing the US non-institutionalized civilian population.

Design and Methods

National Health and Nutrition Examination Survey data (NHANES II: 1976-80; NHANES III: 1988-94) contain BMI_M and BMI_SR. We applied Cox regression to estimate mortality hazard ratios (HRs) for BMI_M and BMI_SR categories, respectively, and compared results. We similarly analyzed subgroups of ostensibly healthy never-smokers.

Results

Misclassification by BMI_SR among the underweight and obesity ranged from 30–40% despite high correlations between BMI_M and BMI_SR (r>0.9). The reporting bias was moderately correlated with BMI_M (r>0.35), but not BMI_SR (r<0.15). Analyses using BMI_SR failed to detect six of eight significant mortality HRs detected by BMI_M. Significantly biased HRs were detected in the NHANES II full dataset (χ² = 12.49; p = 0.01) and healthy subgroup (χ² = 9.93; p = 0.04), but not in the NHANES III full dataset (χ² = 5.63; p = 0.23) or healthy subgroup (χ² = 1.52; p = 0.82).

Conclusions

BMI_SR should not be treated as interchangeable with BMI_M in BMI-mortality analyses. Bias and inconsistency introduced by using BMI_SR in place of BMI_M in BMI-mortality estimation and hypothesis tests may account for important discrepancies in published findings.

Accuracy of self-reported height and weight in a community-based sample of older African Americans and whites

BACKGROUND

To ascertain accuracy of self-reported height, weight (and hence body mass index) in African American and white women and men older than 70 years of age.

METHOD

The sample consisted of cognitively intact participants at the third in-person wave (1992-1993) of the Duke Established Populations for Epidemiologic Studies of the Elderly (age 71 and older, N = 1761; residents of five adjacent counties, one urban, four rural). During in-person, in-home interviews using trained interviewers, height and weight were self-reported (and measured later in the same visit using a standardized protocol), and information were obtained on race, sex, and age.

RESULTS

Accuracy of self-reported height and weight was high (intraclass correlation coefficient 0.85 and 0.97, respectively) but differed as a function of race and age. On average, all groups overestimated their height; whereas (non-Hispanic) white men and women underestimated their weight, African Americans overestimated their weight. Overestimation of height and weight was more marked in persons 85 years and older. Specificity for overweight (body mass index [kg/m(2)] ≥ 25) and obesity (body mass index ≥ 30) ranged from 0.90 to 0.99 for African Americans and whites, but sensitivity was better for African Americans (overweight: 0.81, obesity: 0.89), than for whites (0.66 and 0.57, respectively).

CONCLUSIONS

Height and weight self-reported by African Americans and whites over the age of 70 can be used in epidemiological studies, with greater caution needed for self-reports of whites, and of persons 85 years of age or older.

Overweight and obesity among adults in Serbia: results from the National Health Survey

INTRODUCTION

The purpose of the study was to evaluate the prevalence of overweight and obesity in Serbian adults. The impact of socioeconomic and lifestyle factors on weight was explored.

MATERIALS AND METHODS

A cross-sectional study representative of the adult population in Serbia was carried out in 2006. The study involved 13,796 people aged 20 years and over (6551 men and 7245 women). Individuals were interviewed and underwent anthropometric examination (overweight and obesity defined by body mass index--BMI).

RESULTS

In 2006 in Serbia, 55.7% of adult population was overweight (19.0% of examinees were obese). Among men (body mass index ≥ 25 kg/m²) 26.4% considered themselves as above ideal weight (overweight and obese), while 70.9% classified themselves in an ideal body weight (normal weight). Among women (body mass index ≥ 25 kg/m²) 41.7% classified themselves as above ideal body weight while 56.0% as ideal body weight. Lower educational status, marriage status, rural area of settlement, third and fourth level of household income and irregular main meals were all strongly associated with overweight and obesity.

CONCLUSIONS

High prevalence of overweight and obesity is a significant public health problem among Serbian adults. Efforts are needed to effectively promote daily physical activity and healthy eating through progressive modifications in lifestyle and the creation of supportive environments.

The association between body mass index and patients' experiences with inpatient care

OBJECTIVE

To explore the association between patients' body mass index (BMI) and their experiences with inpatient care.

DESIGN

Cross-sectional. Mail survey.

SETTING

University Hospital of Geneva.

PARTICIPANTS

Questionnaires were mailed to 2385 eligible adult patients, 6 weeks after discharge (response rate = 69%).

MAIN OUTCOME MEASURES

Patients' experiences with care were measured using the Picker inpatient survey questionnaire. BMI was calculated using self-reported height and weight. Main dependent variables were the global Picker patient experience (PPE-15) score and nine dimension-specific problem scores, scored from 0 (no reported problems) to 1 (all items coded as problems). We used linear regressions, adjusting for age, gender, education, subjective health, smoking and hospitalization, to assess the association between patients' BMI and their experiences with inpatient care.

RESULTS

Of the patients, 4.8% were underweight, 50.8% had normal weight, 30.3% were overweight and 14.1% were obese. Adjusted analysis shows that compared with normal weight, obesity was significantly associated with fewer problematic items in the surgery-related information domain, and being underweight or overweight was associated with more problematic items in the involvement of family/friends domain. The global PPE-15 score was significantly higher (more problems) for underweight patients.

CONCLUSIONS

Underweight patients, but not obese patients, reported more problems during hospitalization.

The bias in self-reported obesity from 1976 to 2005: a Canada-US comparison

The objective of this study was to determine whether the bias in self-reported estimates of obesity has changed over time and followed different patterns in Canada and the United States. Using age-standardized data from three waves of the National Health and Nutrition Examination Survey (NHANES) in the United States and the Canadian Community Health Survey (CCHS) and the Canadian Heart Health Survey (CHHS) in Canada, discrepancies were compared between reported and measured estimates of height, weight, and obesity (based on the BMI) from 1976 to 2005. Results indicated that obesity increased in both countries, but rates were higher in the United States. The discrepancy between self-reported and measured obesity was small in the United States with reported data underestimating measured prevalence by about 3%; this stayed relatively constant over time. In Canada, the discrepancy was large and doubled in the past decade (from 4 to 8%). In the United States, self-reported data may be more accurate in monitoring changes in obesity over time, as the estimates have consistently remained about 3% below the measured estimates, whereas in Canada, monitoring obesity based solely on self-reported height and weight may produce inaccurate estimates because of the increasing discrepancy between self-reported and measured data.

Food-related lifestyles and their association to obesity in five European countries

This paper's objective is to investigate the associations between obesity and Food-Related Lifestyles (FRL) in five European countries. A cross-sectional web-based survey was carried out in Belgium, Denmark, Germany, Greece and Poland, January 2008, with quota samples on gender (male, female), age categories (20-44 and 45-70 years), and locality of residence (urban, rural). A total of 2437 respondents (51% women, 49% men; mean age 41.4 years, SD 13.1) participated. Obtained data included socio-demographic information, measure of the food-related lifestyle scale and self-reported weights and heights. Body Mass Index (in kg/m(2)) was calculated as weight (in kg) divided by the squared height (in m(2)). Individuals were classified as obese if BMI > or = 30. Logistic regressions were fitted for the aggregated sample and then by country with obese as dependent and socio-demographics and FRL were included as independents. The prevalence of obesity in the five countries is 22%. Europeans giving more importance to 'self-fulfilment' (odds = 1.18), 'planning of meals' (odds = 1.15), and preferring 'snacks vs. meals' (odds = 1.24) are more likely to be obese. Respondents were less likely to be obese if they attached lower levels of importance to the use of 'shopping lists' (odds = 0.87). The overall picture is that a stronger interest in health, organic products and freshness, within the FLR domain of quality aspects, is associated with 'not being obese'. This study has identified specific FRL dimensions as potential predictors of obesity. The resulting consumers' profiling can be used for targeted interventions for weight management in Europe.