Bioelectrical impedance analysis (BIA) is a relatively simple, inexpensive and non-invasive technique to measure body composition and is therefore suitable in field studies and larger surveys.
We ...performed an overview of BIA-derived body fat percentages (BF%) from 55 published studies of healthy populations aged 6-80 years. In addition, the relationship between body mass index (BMI) and body composition is documented in the context of BIA as a good alternative to closely differentiate which composition of the body better relates to the risk of cardiovascular diseases (CVDs)and all-cause mortality.
BIA-estimated percentage of BF varies greatly with population and age. BIA-estimated BF% is directly and closely related to various health outcomes such as CVDs, which is in contrast to BMI where both high and low BMIs are associated with increased risk of developing chronic diseases. Studies, among others using BIA, suggest that low BMI may reflect low muscle and high BMI fat mass (FM). BIA-derived lean and FM is directly associated with morbidity and mortality. To the contrary, BMI is rather of limited use for measuring BF% in epidemiological studies.
Recent epidemiologic papers are presenting prevalence data suggesting breaks and decreases in obesity rates. However, before concluding that the obesity epidemic is not increasing anymore, the ...validity of the presented data should be discussed more thoroughly. We had a closer look into the literature presented in recent reviews to address the major potential biases and distortions, and to develop insights about how to interpret the presented suggestions for a potential break in the obesity epidemic. Decreasing participation rates, the use of reported rather than measured data and small sample sizes, or lack of representativeness, did not seem to explain presented breaks in the obesity epidemic. Further, available evidence does not suggest that stabilization of obesity rates is seen in higher socioeconomic groups only, or that urbanization could explain a potential break in the obesity epidemic. However, follow-ups of short duration may, in part, explain the apparent break or decrease in the obesity epidemic. On the other hand, a single focus on body mass index (BMI) ⩾25 or ⩾30 kg m(-)(2) is likely to mask a real increase in the obesity epidemic. And, in both children and adults, trends in waist circumferences were generally suggesting an increase, and were stronger than those reported for trends in BMI. Studies concluding that there is a recent break in the obesity epidemic need to be interpreted with caution. Reported studies presenting a break were mostly of short duration. Further, focusing on trends in waist circumference rather than BMI leads to a less optimistic conclusion: the public health problem of obesity is still increasing.
Waist circumference is directly related to all-cause mortality when adjusted for body mass index (BMI). Body fat and fat-free body mass, when mutually adjusted, show with increasing values an ...increasing and decreasing relation to all-cause mortality. We investigated the association of waist circumference and body composition (body fat and fat-free mass), mutually adjusted, to all-cause mortality.
A Danish prospective cohort study with a median follow-up period of 5.8 y.
In all, 27 178 men and 29 875 women, born in Denmark, aged 50-64 y, and without diagnosis of cancer at the time of invitation.
Waist circumference and body composition estimated from impedance measurements. Cox's regression models were used to estimate the mortality rate ratios (RR).
Waist circumference was strongly associated with all-cause mortality after adjustment for body composition; the mortality RR was 1.36 (95% confidence intervals (CI): 1.22-1.52) times higher per 10% larger waist circumference among men and 1.30 (95% CI: 1.17-1.44) times higher among women. Adjustment for waist circumference eliminated the association between high values of the body fat mass index (BFMI) and all-cause mortality. The association between fat-free mass index (FFMI) and mortality remained unaltered.
Waist circumference accounted for the mortality risk associated with excess body fat and not fat-free mass. Waist circumference remained strongly and directly associated with all-cause mortality when adjusted for total body fat in middle-aged men and women, suggesting that the increased mortality risk related to excess body fat is mainly due to abdominal adiposity.
Objective To determine the accuracy of maternal recall of children birthweight (BW) and gestational age (GA), using the Danish Medical Birth Register (DBR) as reference and to examine the ...reliability of recalled BW and its potential correlates.
Design Comparison of data from the DBR and the European Youth Heart Study (EYHS).
Setting Schools in Odense, Denmark.
Population A total of 1271 and 678 mothers of school children participated with information in the accuracy studies of BW and GA, respectively. The reliability sample of BW was composed of 359 women.
Method The agreement between the two sources was evaluated by mean differences (MD), intraclass correlation coefficient (ICC) and Bland–Altman’s plots. The misclassification of the various BW and GA categories were also estimated.
Main outcome measures Differences between recalled and registered BW and GA.
Results There was high agreement between recalled and registered BW (MD =−0.2 g; ICC = 0.94) and GA (MD = 0.3 weeks; ICC = 0.76). Only 1.6% of BW would have been misclassified into low, normal or high BW and 16.5% of GA would have been misclassified into preterm, term or post‐term based on maternal recall. The logistic regression revealed that the most important variables in the discordance between recalled and registered BW were ethnicity and parity. Maternal recall of BW was highly reliable (MD =−5.5 g; ICC = 0.93), and reliability remained high across subgroups.
Conclusion Maternal recall of BW and GA seems to be sufficiently accurate for clinical and epidemiological use.
Commercial physical activity monitors have wide utility in the assessment of physical activity in research and clinical settings, however, the removal of devices results in missing data and has the ...potential to bias study conclusions. This study aimed to evaluate methods to address missingness in data collected from commercial activity monitors. This study utilised 1526 days of near complete data from 109 adults participating in a European weight loss maintenance study (NoHoW). We conducted simulation experiments to test a novel scaling methodology (NoHoW method) and alternative imputation strategies (overall/individual mean imputation, overall/individual multiple imputation, Kalman imputation and random forest imputation). Methods were compared for hourly, daily and 14-day physical activity estimates for steps, total daily energy expenditure (TDEE) and time in physical activity categories. In a second simulation study, individual multiple imputation, Kalman imputation and the NoHoW method were tested at different positions and quantities of missingness. Equivalence testing and root mean squared error (RMSE) were used to evaluate the ability of each of the strategies relative to the true data. The NoHoW method, Kalman imputation and multiple imputation methods remained statistically equivalent (p<0.05) for all physical activity metrics at the 14-day level. In the second simulation study, RMSE tended to increase with increased missingness. Multiple imputation showed the smallest RMSE for Steps and TDEE at lower levels of missingness (<19%) and the Kalman and NoHoW methods were generally superior for imputing time in physical activity categories. Individual centred imputation approaches (NoHoW method, Kalman imputation and individual Multiple imputation) offer an effective means to reduce the biases associated with missing data from activity monitors and maximise data retention.
The prevalence of obesity has increased in the past 30 years, and at the same time a steep increase in consumption of soft drinks has been seen. This paper reviews the literature for studies on ...associations between intake of calorically sweetened beverages and obesity, relative to adjustment for energy intake. Conclusions from previous reviews have been inconsistent, but some included many cross-sectional studies or studies supported by sugar industry. A literature search was performed for prospective and experimental studies using Medline and Scirus. Fourteen prospective and five experimental studies were identified. The majority of the prospective studies found positive associations between intake of calorically sweetened beverages and obesity. Three experimental studies found positive effects of calorically sweetened beverages and subsequent changes in body fat. Two experimental studies did not find effects. Eight prospective studies adjusted for energy intake. Seven of these studies reported associations that were essentially similar before and after energy adjustment. In conclusion, a high intake of calorically sweetened beverages can be regarded as a determinant for obesity. However, there seems to be no support that the association between intake of calorically sweetened beverages and obesity is mediated via increased energy intake, and alternative biological explanations should be explored.
Randomised clinical trials find no protection against development of ischaemic heart disease by use of Hormone Therapy (HT) after the age of 50 years. Observational studies suggest that early ...menopause is a risk factor for ischaemic heart disease. Yet, a clinical very relevant question is whether HT reduces this risk associated with early menopause.
To analyse whether early menopause based on various causes are independent risk factors for ischaemic heart disease, and to investigate whether the risks are modified by use of HT.
In a prospective cohort study questionnaires were mailed to Danish female nurses above 44 years of age in 1993. Information on menopause, use of HT and lifestyle was obtained. In total 19,898 (86%) nurses fulfilled the questionnaire, among them 10.533 were postmenopausal with definable menopausal age, free of previous ischaemic heart disease, stroke or cancer. Through individual linkage to national register incident cases of ischaemic heart disease were identified until end of 1998.
Menopause below both age 40 and 45 was associated with an increased risk of ischaemic heart disease, seeming most pronounced for women who had an early ovariectomy but also among spontaneous menopausal women. Generally HT did not reduce the risk except for the early-ovariectomised women, where no increased risk of ischaemic heart disease for HT users was found.
We found an increased risk of ischaemic heart disease associated with early removal of the ovaries that might be reduced with HT. The present study need confirmation from other studies but suggests that early ovariectomised women could benefit from HT.
This study reviewed the literature on the relations between exposure to chemicals with endocrine-disrupting abilities and obesity in humans. The studies generally indicated that exposure to some of ...the endocrine-disrupting chemicals was associated with an increase in body size in humans. The results depended on the type of chemical, exposure level, timing of exposure and gender. Nearly all the studies investigating dichlorodiphenyldichloroethylene (DDE) found that exposure was associated with an increase in body size, whereas the results of the studies investigating polychlorinated biphenyl (PCB) exposure were depending on dose, timing and gender. Hexachlorobenzene, polybrominated biphenyls, beta-hexachlorocyclohexane, oxychlordane and phthalates were likewise generally associated with an increase in body size. Studies investigating polychlorinated dibenzodioxins and polychlorinated dibenzofurans found either associations with weight gain or an increase in waist circumference, or no association. The one study investigating relations with bisphenol A found no association. Studies investigating prenatal exposure indicated that exposure in utero may cause permanent physiological changes predisposing to later weight gain. The study findings suggest that some endocrine disruptors may play a role for the development of the obesity epidemic, in addition to the more commonly perceived putative contributors.
Objective: Obesity-related under-reporting of usual dietary intake is one of the most persistent sources of bias in nutrition research. The aim of this paper is to characterize obese and non-obese ...individuals with respect to reporting errors observed with two common dietary instruments, using energy and protein recovery biomarkers as reference measures. Population and methods: This report employs data from the Observing Protein and Energy Nutrition (OPEN) study. Analyses are based on stratified samples of 211 (57 obese) men and 179 (50 obese) women who completed 24-h recalls (24HR), food frequency questionnaires (FFQ), doubly labelled water (DLW) and urinary nitrogen (UN) assessments. Results: In obese and non-obese subgroups, FFQ yielded lower energy and protein intake estimates than 24HR, although biomarker-based information indicated under-reporting with both dietary instruments. Gender differences in obesity-related bias were noted. Among women, the DLW-based energy requirement was 378 kcal greater in obese than in non-obese groups; the FFQ was able to detect a statistically significant portion of this extra energy, while the 24HR was not. Among men, the DLW-based energy requirement was 485 kcal greater in the obese group; however, neither FFQ nor 24HR detected this difference in energy requirement. Combining protein and energy estimates, obese men significantly over-reported the proportion of energy from protein using the 24HR, but not with the FFQ. In obese women, no significant reporting error for energy percent protein was observed by either method. At the individual level, correlations between energy expenditure and reported energy intake tended to be weaker in obese than non-obese groups, particularly with the 24HR. Correlations between true and reported protein density were consistently higher than for protein or energy alone, and did not vary significantly with obesity. Conclusion: This work adds to existing evidence that neither of these commonly used dietary reporting methods adequately measures energy or protein intake in obese groups. The 24HR, while capturing more realistic energy distributions for usual intake, may be particularly problematic in the obese.
To review studies of patterns of food intake, as assessed by diet index, factor analysis or cluster analysis, and their associations with body mass index or obesity (BMI/Ob).
Systematic literature ...review MEDLINE search with crosscheck of references.
Thirty observational studies relating food intake patterns to anthropometric information were identified and reviewed. Food intake patterns were defined using a diet index, factor or cluster analysis in 12, nine and nine studies, respectively. Measures of body mass were made concurrently with the diet assessment in all studies, and only in a few cases were the primary outcomes related to BMI/Ob.
The food intake patterns identified could, in most factor or cluster analysis studies, be categorised as: (a) meat, fatty, sweet or energy dense foods; (b) vegetables, fruit, whole grain and low-fat foods; or (c) by high alcohol consumption. The diet indexes were designed to capture a high diversity and/or food combinations matching the recommendations. The relationships with BMI/Ob were inconsistent-ten studies found that intake patterns, which we categorised as fatty, sweet or energy dense were positively associated with BMI/Ob, while similar patterns in four other studies were negatively associated with BMI. The significant associations between diet index score and BMI/Ob were consistently negative, while the associations between factor scores or cluster membership and BMI/Ob were less clear in terms of food intake pattern. Men and women had similar food intake patterns, but food intake patterns were less often positively associated with BMI/Ob in women. In 11 studies, there were no significant associations between food intake pattern and BMI/Ob.
This review showed that no consistent associations could be identified between BMI or Ob and food intake patterns, derived from diet index, factor analysis or cluster analysis. However, the heterogeneity of food intake patterns identified by such analyses and the lack of gold standards for the application of these techniques hampers consistent analysis of a relation between food intake patterns and health.
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