Comparison of bioelectrical impedance and BMI in predicting obesity-related medical conditions

Objective : To determine the relative validity of specific bioelectrical impedance analysis (BIA) prediction equations and BMI as predictors of physiologically relevant general adiposity. Research Methods and Procedures : Subjects were >12, 000 men and women from the Third National Health and Nutrition Examination Survey population. We examined the correlations between BMI and percentage body fat based on 51 different predictive equations, blood pressure, and blood levels of glucose, high‐density lipoprotein cholesterol, and triglycerides, which are known to reflect adiposity, while controlling for other determinants of these physiological measures. Results : BMI consistently had one of the highest correlations across biological markers, and no BIA‐based measure was superior. Percent body fat estimated from BIA was minimally predictive of the physiological markers independent of BMI. Discussion : These results suggest that BIA is not superior to BMI as a predictor of overall adiposity in a general population.     

Is handedness exogenously determined? Counterevidence from South Korea

Establishing whether handedness is exogenously determined can help explain the relationship between handedness and various health and economic outcomes. It can also ensure the use of handedness as an instrument in empirical applications. Using data from the Korean National Health and Nutrition Examination Survey and the National Health and Nutrition Examination Survey in the United States, I investigate the exogeneity of children’s handedness by examining the determinants of mixed-handedness. In the analysis using Korean data, parents’ age, parents’ non-right-handedness, and family income influence the likelihood of children’s mixed-handedness. In the U.S. data analysis, however, none of the child and family characteristics, except being Asian, predict the likelihood of mixed-handedness. These results suggest that mixed-handedness, further handedness cannot be generalized as exogenous and is a race-specific characteristic.     

A cross-sectional survey of cadmium biomarkers and cigarette smoking

Cadmium contamination of tobacco may contribute to the health hazards of cigarette smoking. The 2005–2012 United States National Health and Nutrition Examination Survey data provided a unique opportunity to conduct a cross-sectional survey of cadmium biomarkers and cigarette smoking. Among a sample of 6761 participants, we evaluated mean differences and correlations between cadmium biomarkers in the blood and urine and characteristics of never, former and current smokers. We found statistically significant differences in mean cadmium biomarker levels between never and former smokers as well as between never and current smokers. In current smokers, duration in years had a higher correlation coefficient with urinary than blood cadmium levels. In contrast, number of cigarettes smoked per day had a higher correlation coefficient with blood than urinary cadmium levels. These data suggest that blood and urine cadmium biomarker levels differ by duration and dose. These findings should be considered in evaluating any association between cadmium and smoking related diseases, especially cardiovascular disease.     

The relationships between serum copper levels and overweight/total obesity and central obesity in children and adolescents aged 6-18 years

ObjectiveTo explore the relationships between serum copper levels and overweight/total obesity and central obesity in children and adolescents.MethodsWe included 2,000 children and adolescents from the 2011-2016 US National Health and Nutrition Examination Surveys. The multivariable linear model, logistic model and restricted cubic splines were adopted to assess the relationships. Models were adjusted for data release cycle, age, sex, race/ethnicity, ratio of family income to poverty, and dietary intakes of protein, total sugars, total fat, fiber, energy, calcium, vitamin D, vitamin C, and hours watch television or videos.ResultsThe prevalences of overweight/total obesity and central obesity were 37.38% and 33.40%, respectively. For per-quintile increment in serum copper levels, body mass index increased by 1.06 (0.79-1.33) (kg/m²) and waist circumference increased by 2.43 (1.58-3.27) (cm). The odds ratios (95% confidence intervals) for overweight/total obesity and central obesity among participants with the highest quintile compared with those with the lowest quintile of serum copper levels were 5.46 (3.31-8.98) and 5.64 (3.31-9.58), respectively. The above-mentioned associations were not modified by age (children: 6-12 years, adolescents: 13-18 years) and sex. Dose-response analysis showed that the odds of overweight/total obesity and central obesity increased with increasing serum copper levels to a level of approximate 140 ug/dL where the association seemed to reach a plateau, respectively.ConclusionsSerum copper levels were positively associated with body mass index and waist circumference, and elevated serum copper levels were associated with higher odds of overweight/total obesity and central obesity in children and adolescents.     

Hemoglobin concentration of high-altitude Tibetans and Bolivian Aymara

Elevated hemoglobin concentrations have been reported for high-altitude sojourners and Andean high-altitude natives since early in the 20th century. Thus, reports that have appeared since the 1970s describing relatively low hemoglobin concentration among Tibetan high-altitude natives were unexpected. These suggested a hypothesis of population differences in hematological response to high-altitude hypoxia. A case of quantitatively different responses to one environmental stress would offer an opportunity to study the broad evolutionary question of the origin of adaptations. However, many factors may confound population comparisons. The present study was designed to test the null hypothesis of no difference in mean hemoglobin concentration of Tibetan and Aymara native residents at 3,800–4,065 meters by using healthy samples that were screened for iron deficiency, abnormal hemoglobins, and thalassemias, recruited and assessed using the same techniques. The hypothesis was rejected, because Tibetan males had a significantly lower mean hemoglobin concentration of 15.6 gm/dl compared with 19.2 gm/dl for Aymara males, and Tibetan females had a mean hemoglobin concentration of 14.2 gm/dl compared with 17.8 gm/dl for Aymara females. The Tibetan hemoglobin distribution closely resembled that from a comparable, sea-level sample from the United States, whereas the Aymara distribution was shifted toward 3–4 gm/dl higher values. Genetic factors accounted for a very high proportion of the phenotypic variance in hemoglobin concentration in both samples (0.86 in the Tibetan sample and 0.87 in the Aymara sample). The presence of significant genetic variance means that there is the potential for natural selection and genetic adaptation of hemoglobin concentration in Tibetan and Aymara high-altitude populations. Am J Phys Anthropol 106:385–400, 1998. © 1998 Wiley-Liss, Inc.     

Measures of adiposity and cardiovascular disease risk factors

Objective: To determine which of five measures of adiposity maintains the strongest association with cardiovascular disease risk factors. Research Methods and Procedures: A nationally representative sample of 12,608 adult participants of the third National Health and Nutrition Examination Survey were examined. Waist circumference, total body fat, percent body fat, BMI, and skinfold thickness were measured following a standardized protocol. Results: In multivariable adjusted models including waist circumference and BMI as independent variables, waist circumference was a significantly better predictor. The odds ratios (95% confidence intervals) for each standard deviation higher waist circumference and BMI for men were as follows: 1.88 (1.43, 2.48) and 0.99 (0.76, 1.29), respectively, for hypertension; 1.51 (0.87, 2.59) and 1.23 (0.76, 1.99), respectively, for diabetes; and 1.85 (1.48, 2.32) and 1.00 (0.80, 1.24), respectively, for low high‐density lipoprotein‐cholesterol. The analogous odds ratios (95% confidence intervals) for women were as follows: 2.28 (1.74, 3.00) and 0.91 (0.69, 1.19), respectively, for hypertension; 2.72 (1.85, 4.00) and 0.82 (0.55, 1.23), respectively, for diabetes; and 1.90 (1.47, 2.47) and 1.07 (0.83, 1.38), respectively, for low high‐density lipoprotein‐cholesterol. Results were markedly similar for waist circumference in models adjusting for total body fat, percent body fat, and skinfold thickness separately. In contrast, waist circumference was not a significantly better predictor of elevated C‐reactive protein than the other measures of adiposity. Discussion: Waist circumference maintains a stronger association with cardiovascular disease risk factors than other measures of adiposity.     

The association between iron metabolism with the change of blood pressure and risk of hypertension: A large cross-sectional study

BackgroundThe relationship between iron metabolism and variations in blood pressure and hypertension risk is still not clear. This study aimed to determine whether iron metabolism is associated with changes in blood pressure and hypertension prevalence in the general United States population.MethodsThe National Health and Nutrition Examination Survey (NAHNES) database contains data on 116876 Americans from 1999 to 2020 years. Data from the NHANES database were used to examine the relationships between iron metabolism (serum iron [SI], serum ferritin [SF], and soluble transferrin receptor [sTfR]) and changes in blood pressure and hypertension prevalence. Generalized linear models and restricted cubic spline (RCS) plot curves were used to estimate the relationship between iron metabolism and hypertension. Further, generalized additive models with smooth functions were used to identify the relationship between iron metabolism and blood pressure. Finally, a stratified subgroup analysis was performed.ResultsA total of 6710 participants were included in our analysis. The RCS plot showed a linear relationship between SI, as well as sTfR, and hypertension prevalence. SF and hypertension prevalence were associated in a J-shape. In addition, the relationship between SI and systolic blood pressure (SBP) and diastolic blood pressure (DBP) decreased initially and then increased. A correlation between SF, SBP, and DBP first decreased, then increased, and finally decreased. A positive linear correlation existed between sTfR and SBP, but it increased and then decreased with DBP.ConclusionThe correlation between SF and hypertension prevalence displayed a J-curve. In contrast, the correlation between SI, as well as sTfR, and hypertension risk was negative and positive, respectively.     

Disability,Arthritis, and Body Weight among Adults 45 Years and Older

Objectives : To examine the association between body weight and disability among persons with and without self‐reported arthritis. Research Methods and Procedures : Data were analyzed for noninstitutionalized adults, 45 years or older, in states that participated in the Behavioral Risk Factor Surveillance System. Self‐reported BMI (kilograms per meter squared) was used to categorize participants into six BMI‐defined groups: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), obese, class 1 (30 to <35), obese, class 2 (35 to <40), and obese, class 3 (≥40). Results : Class 3 obesity (BMI ≥ 40) was significantly associated with disability among participants both with and without self‐reported arthritis. The adjusted odds ratio (AOR) for disability in participants with class 3 obesity was 2.75 [95% confidence interval (CI) = 2.22 to 3.40] among those with self‐reported arthritis and 1.77 (95% CI = 1.20 to 2.62) among those without self‐reported arthritis compared with those of normal weight (BMI 18.5 to <25). Persons with self‐reported arthritis who were obese, class 2 (BMI 35 to <40) and obese, class 1 (BMI 30 to <35) and women with self‐reported arthritis who were overweight (BMI 25 to <30) also had higher odds of disability compared with those of normal weight [AOR = 1.72 (95% CI = 1.47 to 2.00), AOR = 1.30 (95% CI = 1.17 to 1.44), and AOR = 1.18 (95% CI = 1.06 to 1.32), respectively]. Discussion : Our findings reveal that obesity is associated with disability. Preventing and controlling obesity may improve the quality of life for persons with and without self‐reported arthritis.     

Dietary zinc intake,supplemental zinc intake and serum zinc levels and the prevalence of kidney stones in adults

ObjectiveThe association between zinc intake and the risk of kidney stones remains controversial. We examined the associations between dietary zinc intake, supplemental zinc intake and serum zinc levels and the prevalence of kidney stones in adults.MethodsAdult participants from the 2007–2016 NHANES were included. Restricted cubic splines were adopted to assess the dose-response relationships.ResultsDietary zinc intake was linearly associated with the prevalence of kidney stones (P_{for non-linearity} = 0.50), and the odds ratios (95% confidence intervals) of kidney stones were 0.75 (0.51–1.04) for 10 mg/day, 0.65 (0.39-0.97) for 20 mg/day, 0.53 (0.30-0.94) for 30 mg/day and 0.45 (0.22-0.95) for 40 mg/day. The linear relationship was also observed among women and overweight/obese individuals. No association was found between supplemental zinc intake and the prevalence of kidney stones. A non-linear relationship was found between serum zinc levels and the prevalence of kidney stones (P_{for non-linearity} = 0.02), and the odds ratios (95% confidence intervals) of kidney stones were 0.52 (0.33-0.82) for 70 ug/dL, 0.43 (0.24-0.77) for 90 ug/dL, 0.56 (0.32-0.98) for 110 ug/dL and 0.77 (0.37–1.62) for 130 ug/dL. The non-linear relationship was also observed among men and overweight/obese individuals.ConclusionsDietary zinc intake and serum zinc levels were inversely associated with the prevalence of kidney stones in adults, and there may be effect modification by participant sex and body mass index. The present analysis is limited in its ability to establish causality.     

Development of Health‐Related Waist Circumference Thresholds Within BMI Categories

Objective: To develop and cross‐validate waist circumference (WC) thresholds within BMI categories. The utility of the derived values was compared with the single WC thresholds (women, 88 cm; men, 102 cm) recommended by NIH and Health Canada. Research Methods and Procedures: The sample included adults classified as normal weight (BMI = 18.5 to 24.9), overweight (BMI = 25 to 29.9), obese I (BMI = 30 to 34.9), and obese II+ (BMI ≥ 35) from the Third U.S. National Health and Nutrition Examination Survey (NHANES III; n = 11, 968) and the Canadian Heart Health Surveys (CHHS; n = 6286). Receiver operating characteristic curves were used to determine the optimal WC thresholds that predicted high risk of coronary events (top quintile of Framingham scores) within BMI categories using the NHANES III. The BMI‐specific WC thresholds were cross‐validated using the CHHS. Results: The optimal WC thresholds increased across BMI categories from 87 to 124 cm in men and from 79 to 115 cm in women. The validation study indicated improved sensitivity and specificity with the BMI‐specific WC thresholds compared with the single thresholds. Discussion: Compared with the recommended WC thresholds, the BMI‐specific values improved the identification of health risk. In normal weight, overweight, obese I, and obese II+ patients, WC cut‐offs of 90, 100, 110, and 125 cm in men and 80, 90, 105, and 115 cm in women, respectively, can be used to identify those at increased risk.     

Zinc status is independently related to the bone mineral density,fracture risk assessment tool result,and bone fracture history: Results from a U.S. nationally representative survey

PurposePrevious reports have identified the important role of zinc in bone health. Although the risk of zinc deficiency is still a concern in the U.S., there has never been an in-depth study of the association between zinc status and bone health in a sample representing the country.MethodsWe included 2,895 subjects (aged ≥ 40 years) from National Health and Nutrition Examination Survey (NHANES) 2013–2014 to explore the relationship among three biomarkers of zinc (serum, food, and total intake), the bone mineral density (BMD) of the total spine and femur, the FRAX® scores, and the previous history of bone fractures.ResultsWe showed a one-unit increase in the ln-serum zinc level was associated with an increase in the total spine BMD (ß = 0.068; S.E. = 0.028; P = 0.030) and total femur BMD (ß = 0.061; S.E. = 0.017; P = 0.003), while a one-unit increase in the ln-food zinc intake amount was correlated with an increase in the total femur BMD in the participants (ß = 0.023; S.E. = 0.009; P = 0.021). The ln-total zinc intake amount was correlated with an increase in the total femur BMD in women (ß = 0.016; S.E. = 0.007; P = 0.041). We also found food zinc intake was negatively correlated with the FRAX® score, while increased levels of all three zinc biomarkers were associated with a decreased incidence of previous bone fractures.ConclusionsIn this representative survey of American adults above 40 years old, higher zinc status was associated with higher total spine and femoral BMD, lower FRAX® scores, and lower incidence of previous fractures. If this finding is causal, increased zinc intake remains an important issue for Americans.     

Correcting biases in estimates of mortality attributable to obesity

Objective: To assess whether a recent study that found a relatively small number of excess deaths attributable to obesity may have underestimated by not correcting for statistical biases. Research Methods and Procedures: This prospective cohort study used data from the First National Health and Nutrition Examination Survey Epidemiologic Follow‐Up Study. Survival analyses were conducted using 9690 individuals 32 to 87 years of age and 1886 all‐cause deaths during a 9.1‐year follow‐up. Corrections were made for the reputed regression‐dilution bias by using the average BMI during the decade before follow‐up as predictor. Corrections for the reputed reverse‐causation bias were made by excluding participants with a history of serious illness. Attributable fractions were calculated and used to estimate excess deaths. Results: The uncorrected estimate of excess deaths attributable to obesity (BMI ≥30) was 41.9, using 18.5 to 25 kg/m² as ideal‐weight category. Using average BMI as predictor increased the estimate to 93.3. Correcting for reverse‐causation effects increased the estimate further to 131.1 (range, 93.3 to 169.0). The uncorrected hazard ratio, 1.25, was increased to 1.41 by using average BMI as predictor, and then to 2.40 by correcting for reverse causation. Using BMI 21 to 25 kg/m² and 23 to 25 kg/m² as ideal‐weight categories increased the corrected estimates to 144.6 (range, 80.5 to 177.2) and 164.1 (range, 103.8 to 194.9), respectively. Larger increases were found for overweight and Grade 2 to 4 obesity (BMI ≥35 kg/m²). For overweight, the uncorrected estimate using 18.5 to 25 kg/m² as ideal‐weight category was ?88.3 and the corrected estimate using 23 to 25 kg/m² as ideal‐weight category was 205.4 (range, 114.5 to 296.3). Discussion: Correcting for statistical biases and using higher ideal‐weight categories increased the estimate of excess deaths attributable to obesity by ～400% and changed the negative estimate for overweight to a large positive estimate.     

A Bayesian functional data model for surveys collected under informative sampling with application to mortality estimation using NHANES

Functional data are often extremely high-dimensional and exhibit strong dependence structures but can often prove valuable for both prediction and inference. The literature on functional data analysis is well developed; however, there has been very little work involving functional data in complex survey settings. Motivated by physical activity monitor data from the National Health and Nutrition Examination Survey (NHANES), we develop a Bayesian model for functional covariates that can properly account for the survey design. Our approach is intended for non-Gaussian data and can be applied in multivariate settings. In addition, we make use of a variety of Bayesian modeling techniques to ensure that the model is fit in a computationally efficient manner. We illustrate the value of our approach through two simulation studies as well as an example of mortality estimation using NHANES data.     

Relationship between Number of Eggs,Brood Weight,and Female Body Weight in Crustacea

Relationships between number of eggs (N_g), brood weight (W_g), and body length (L) and weight (W) of females were studied for 16 orders and suborders of Crustacea. The study was based on the authors' observations in the inland waters of the European USSR, in the coastal regions of the fareastern and northern seas and data from V. V. KUZNETSOV (preserved in archives). An extensive literature was also used. The equations describing the relationships (N_g=f(L) and W_g=f(W) are calculated for some species and high taxons. On the average for the superclass (excluding the order Notostraca) the W_g/W ratio appeared to be 0.16. This ratio is markedly different for species of Notostraca. It is supposed that this difference is due to the high metabolic rate of Notostraca.     

Relationship of BMI,Waist Circumference,and Weight Change with Use of Health Services by Older Adults

Objective: To examine the relationship of BMI, waist circumference (WC), and weight change with use of health care services by older adults. Research Methods and Procedures: This was a prospective cohort study conducted from 2001 to 2003 among 2919 persons representative of the non‐institutionalized Spanish population ≥60 years of age. Analyses were performed using logistic regression, with adjustment for age, educational level, size of place of residence, tobacco use, alcohol consumption, and presence of chronic disease. Results: Obesity (BMI ≥ 30 kg/m²) and abdominal obesity (WC >102 cm in men and >88 cm in women) in 2001 were associated with greater use of certain health care services among men and women in the period 2001–2003. Compared with women with WC ≤ 88 cm, women with abdominal obesity were more likely to visit primary care physicians [odds ratio (OR): 1.36; 95% confidence limit (CL): 1.06–1.73] and receive influenza vaccination (OR: 1.30; 95% CL: 1.03–1.63). Weight gain was not associated with greater health service use by either sex, regardless of baseline BMI. Weight loss was associated with greater health service use by obese and non‐obese subjects of both sexes. In comparison with those who reported no important weight change, non‐obese women who lost weight were more likely to visit hospital specialists (OR: 1.45; 95% CL: 1.02–2.06), receive home medical visits (OR: 1.61; 95% CL: 1.06–2.45), be hospitalized (OR: 1.88; 95% CL: 1.29–2.74), and have more than one hospital admission (OR: 2.31; 95% CL: 1.19–4.47). Discussion: Obesity and weight loss are associated with greater health service use among the elderly.     

Comparison of self-reported and measured BMI as correlates of disease markers in US adults

Objective: The purpose of this study is to evaluate the validity of BMI based on self‐reported data by comparison with technician‐measured BMI and biomarkers of adiposity. Research Methods and Procedures: We analyzed data from 10,639 National Health and Nutrition Education Study III participants ≥20 years of age to compare BMI calculated from self‐reported weight and height with BMI from technician‐measured values and body fatness estimated from bioelectrical impedance analysis in relation to systolic blood pressure, fasting blood levels of glucose, high‐density lipoprotein‐cholesterol, triglycerides, C‐reactive protein, and leptin. Results: BMI based on self‐reported data (25.07 kg/m²) was lower than BMI based on technician measurements (25.52 kg/m²) because of underreporting weight (?0.56 kg; 95% confidence interval, ?0.71, ?0.41) and overreporting height (0.76 cm; 95% confidence interval, 0.64, 0.88). However, the correlations between self‐reported and measured BMI values were very high (0.95 for whites, 0.93 for blacks, and 0.90 for Mexican Americans). In terms of biomarkers, self‐reported and measured BMI values were equally correlated with fasting blood glucose (r = 0.43), high‐density lipoprotein‐cholesterol (r = ?0.53), and systolic blood pressure (r = 0.54). Similar correlations were observed for both measures of BMI with plasma concentrations of triglycerides and leptin. These correlations did not differ appreciably by age, sex, ethnicity, or obesity status. Correlations for percentage body fat estimated through bioelectrical impedance analysis with these biomarkers were similar to those for BMI. Discussion: The accuracy of self‐reported BMI is sufficient for epidemiological studies using disease biomarkers, although inappropriate for precise measures of obesity prevalence.     

膝骨关节炎患者关节疼痛与软骨下骨髓水肿的相关性研究

目的:探讨膝骨关节炎(KOA)患者关节疼痛与软骨下骨髓水肿(BME)的相关性。方法:选取2012年12月到2016年1月在我院接受治疗的KOA患者70例,所有患者均行MRI检查,并根据有无BME将其分为对照组和观察组,其中有BME的患者均纳入观察组,共56例,无BME的患者纳入对照组,共14例,对观察组的BME情况进行评分,并进一步根据BME得分情况将观察组分为1分组、2分组和3分组。采用主诉疼痛分级法(VRS)、视觉模糊评分(VAS)对所有患者进行疼痛评分。比较对照组和观察组的VRS分级、VAS评分,比较1分组、2分组和3分组的VRS分级、VAS评分,分析BME得分和VRS分级、VAS评分的相关性。结果:观察组的VRS分级的Ⅰ级比例为17.86%,显著低于对照组的50.00%,Ⅱ级比例为64.29%,显著高于对照组的28.57%,差异均有统计学意义(P0.05);观察组的VAS评分显著高于对照组,差异有统计学意义(P0.05);观察组三个分组的VRS分级Ⅰ级、Ⅱ级、Ⅲ级比例整体比较差异有统计学意义(P0.05),1分组的VRS分级Ⅰ级比例显著高于2分组和3分组,2分组的VRS分级Ⅱ级比例显著高于1分组和3分组,3分组的VRS分级Ⅲ级比例显著高于1分组和2分组,差异均有统计学意义(P0.05);观察组三个分组的VAS评分整体比较差异有统计学意义(P0.05),3分组的VAS评分显著高于1分组和2分组,2分组的VAS评分显著高于1分组,差异均有统计学意义(P0.05);经Spearman统计分析显示BME得分和VRS分级、VAS评分呈正相关(P0.05)。结论:大部分KOA患者存在BME,而有BME的KOA患者关节疼痛更加明显,且BME越严重疼痛感越强。     

The Relationship between Body Mass Index and Post-Cessation Weight Gain in the Year after Quitting Smoking: A Cross-Sectional Study

Introduction

There is wide variability in the amount of weight gained when quitting smoking, but little is known about key predictors of weight gain. We examined the impact of body mass index (BMI) category and sociodemographic variables on post-cessation weight gain.

Materials and Methods

We utilized National Health and Nutrition Examination Survey data from five consecutive cycles of data collection from 2003–2004 to 2011–2012 to estimate post-cessation weight gain by BMI category among recent quitters (n = 654). We analyzed data on their “current weight” and their “past year weight”. We also compared the recent quitters with current smokers, in order to estimate the amount of weight that could be attributed to quitting smoking.

Results

Recent quitters gained 1.4 kg (95% CI: 0.8 to 2.0), while current smokers had a non-significant weight change (-0.01 kg (95% CI: -0.3 to 0.2). Weight gain was significant for those in the normal weight (3.1 kg, 95% CI: 2.3 to 3.9) and overweight BMI categories (2.2 kg, 95% CI: 1.1 to 3.2).

Conclusions

BMI category is a key factor in the extent of post-cessation weight gain, with normal and overweight recent quitters gaining significant amounts of weight.