No differences in the body fat after violating core bioelectrical impedance measurement assumptions.

OBJECTIVE: It is unclear to what degree acutely violating bioelectrical impedance analysis (BIA) measurement assumptions will alter the predicted percent fat mass (%FM) and whether this differs by sex or body mass index (BMI). METHODS: %FM was assessed under control, dehydration, exercise, water, food intake and non-voided bladder conditions with three BIA devices (Tanita: BC-418, TBF-314, & Omron HBF-306CN) for men (n = 23, age: 24.0 ± 5.2 years old) and women (n = 17, age: 22.5 ± 3.4 years old) separately. RESULTS: For all BIA devices, there were no differences in the %FM values between the control and the other conditions in men or women (- 1.9 to 0.4%, p > 0.05). Across the three devices and five conditions, 97% of %FM tests returned values within 5% of control (2 tests), and 86% of tests were within 2% of control despite violating an assumption. The errors were greatest with dehydration and women were more likely to have a %FM difference greater than 2% than men with dehydration using the hand-to-foot device (Tanita TBF-314: 59% versus 9%). There were no differences in %FM between control and the conditions when examined by BMI (overweight/obesity: - 2.8 to 0.1% and normal weight: - 1.7 to 0.5%; BMI*trial, p = 0.99). CONCLUSION: %FM estimates were similar despite acutely violating the preliminary measurement BIA assumptions across a range of different BMIs. The minor variations in %FM are smaller than what would be expected with day-to-day variability or weight loss intervention but may be larger in women than men.

Changes in the prevalence of chronic conditions associated with abdominal obesity between 1999 and 2014.

To examine the trends in chronic conditions after accounting for temporal differences in body mass index (BMI) and waist circumference (WC). Pooled cycles (1999-2014) of the U.S. National Health and Nutrition Examination Survey (NHANES) were analysed (n = 36 959). The models were adjusted for caloric intake, smoking, medications use and physical activity. The prevalence of diabetes increased in women with general or abdominal obesity (BMI*time; WC*time, P < .05), but there were no differences in men. For hypertension, independent of BMI, the prevalence was not different over time in both sexes (P > .05), whereas for a given WC, there was a decrease in the prevalence over time in women (WC*time, P = .05). For dyslipidemia, independent of BMI, the prevalence decreased in men, whereas for a given WC, there was a decrease in the prevalence in both sexes (P < .05). Over the same time frame, blood pressure, low-density lipoprotein and triglycerides decreased, while plasma glucose increased independent of general and abdominal obesity (P < .001). The relationship between obesity and chronic conditions has changed over time. There may be other changes that have altered how obesity is related with metabolic health markers over time. Further investigation is needed to better understand the current causes of chronic conditions.

Age- and sex- specific all-cause mortality risk greatest in metabolic syndrome combinations with elevated blood pressure from 7 U.S. cohorts.

BACKGROUND: The association between metabolic syndrome (MetS) and all-cause mortality is well established but it is unclear if there are differences in mortality risk among the 32 possible MetS combinations. Hence, the purpose of this study is to evaluate the associations between different MetS combinations and its individual components with all-cause mortality, and to examine differences in the association by age and sex. METHODS: A merged sample of 82,717 adults from 7 U.S. cohorts was used. RESULTS: In our sample, MetS was present in 32% of men, 34% of women, 28% of younger adults (18-65 years) and 62% of older adults (>65 years) with 14,989 deaths over 14.6 ± 7.4 years of follow-up. Risk of all-cause mortality was higher in younger individuals with a greater number of MetS factors present, but in older adults having all 5 MetS factors was the only combination significantly associated with mortality. Regardless of age or sex, elevated blood pressure was the MetS factor most consistently present in MetS combinations that were significantly and most strongly associated with mortality. In fact, elevated blood pressure in the absence of other risk factors was significantly associated with mortality in men (HR, 95% CI = 1.56, 1.33-1.84), women (HR = 1.62, 1.44-1.81) and younger adults (HR = 1.61, 1.45-1.79). Conversely, waist circumference, glucose and triglycerides in isolation were not associated with mortality (p>0.05). CONCLUSION: In a large U.S. population, different combinations of MetS components vary substantially in their associations with all-cause mortality. Men, women and younger individuals with MetS combinations including elevated blood pressure had stronger associations with greater mortality risk, with minimal associations between MetS and mortality risk in older adults. Thus, we suggest that future algorithms may wish to consider differential weighting of these common metabolic risk factors, particularly in younger populations.

Do moderate- to vigorous-intensity accelerometer count thresholds correspond to relative moderate- to vigorous-intensity physical activity?

We aimed to predict % maximal oxygen consumption at absolute accelerometer thresholds and to estimate and compare durations of objective physical activity (PA) among body mass index (BMI) categories using thresholds that account for cardiorespiratory fitness. Eight hundred twenty-eight adults (53.5% male; age, 33.9 ± 0.3 years) from the National Health and Nutrition Examination Survey 2003-2004 were analyzed. Metabolic equivalent values at absolute thresholds were converted to percentage of maximal oxygen consumption, and accelerometer counts corresponding to 40% or 60% maximal oxygen consumption were determined using 4 energy expenditure prediction equations. Absolute thresholds underestimated PA intensity for all adults; however, because of lower fitness, individuals with overweight and obesity work at significantly higher percentage of maximal oxygen consumption at the absolute thresholds and require significantly lower accelerometer counts to reach relative moderate and vigorous PA intensities compared with those with normal weight (P < 0.05). However, moderate-to-vigorous physical activity (MVPA) durations were shorter when using relative thresholds compared with absolute thresholds (in all BMI groups, P < 0.05), and they were shorter among individuals with obesity compared with those with normal weight when using relative thresholds (P < 0.05). Regardless of the thresholds used, a greater proportion of individuals with normal weight met the PA guideline of 150 min·week-1 of MVPA compared with individuals with obesity (absolute: 21.3% vs 6.7%; Yngve: 4.0% vs 0.2%; Swartz: 10.7% vs 3.9%; Hendelman: 4.7% vs 0.2%; Freedson: 6.4% vs 0.5%; P < 0.05). Current absolute thresholds of accelerometry-derived PA may overestimate MVPA for all BMI categories when compared with relative thresholds that account for cardiorespiratory fitness. Given the large variability in our results, more work is needed to better understand how to use accelerometers for evaluating PA at the population level.

The Association between Antihypertensive Medication Use and Blood Pressure Is Influenced by Obesity.

Introduction: One in three US adults is living with obesity or hypertension, and more than 75% of hypertensive individuals are using antihypertensive medications. Therefore, it is important to examine blood pressure (BP) differences in populations that are using these medications with differing obesity status. Aim: We examined whether BP attained when using various antihypertensive medications varies amongst different body mass index (BMI) categories and whether antihypertensive medication use is associated with differences in other metabolic risk factors, independent of BMI. Methods: Adults with hypertension from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014 were used (n=15,285). Linear regression analyses were used to examine the main effects and interaction between antihypertensive use and BMI. Results: In general, users of antihypertensive medications had lower BP than those not taking BP medications (NoBPMed) (P < 0.05), whereby in women, the differences in systolic BP between angiotensin-converting-enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) users and NoBPMed were greater in those with obesity (ACE inhibitors: -14 ± 1 mmHg; ARB: -16 ± 1 mmHg) compared to normal weight individuals (ACE inhibitors: -9 ± 1 mmHg; ARB: -11 ± 1 mmHg) (P < 0.05). Diastolic BP differences between women ARB users and NoBPMed were also greatest in obesity (-5 ± 1 mmHg) (P < 0.05) whilst there were no differences in normal weight individuals (-1 ± 1 mmHg) (P>0.05). Furthermore, glucose levels and waist circumference in women were higher in those using ACE inhibitors compared to diuretics (P < 0.05). Conclusion: ACE inhibitors and ARBs may be associated with more beneficial BP profiles in women with obesity, with no obesity-related BP differences for antihypertensive medication in men. However, there could be potential cardiometabolic effects for some antihypertensive medications that should be explored further.

Trends in medication use by body mass index and age between 1988 and 2012 in the United States.

OBJECTIVE: Whether the increase in prescription medication use over time differs by age and obesity status is unclear. METHOD: National Health and Nutrition Examination Survey (NHANES) between 1988 and 2012 was analyzed (n = 57,543). FINDINGS: Increased medication use over time was seen in older individuals of all body mass index (BMI) classes, with the most prominent increase in those with obesity (p<0.001). For example, older men (≥65y) with obesity took 3.1 more medications between 1988 and 2012 versus 1.5 for normal weight older men. There were minimal differences in medication use over time in younger individuals. In men, the odds of taking antihypertensives, lipid-lowering medication, antidiabetics, and antidepressants increased with age, time and BMI wherein the association between age and medication use was magnified over time (age*time, p<0.05). In women, older women with overweight or obesity had a greater increase in the likelihood of antihypertensives and antidiabetics medication over time (BMI*time, p>0.05). CONCLUSION: Older individuals of all BMI classes may be driving the increase in medication use over time. However, the rise in the likelihood of taking cardiometabolic medications over time was generally not different between those with or without obesity in men with some increases seen in older women. Further research may be required to assess accessibility and barriers to medication use among certain demographics.