Comparing Waist Circumference, Sagittal Abdominal Diameter, and BMI As Predictors of Cardiovascular Disease in 11,449 U.S. Adults

Although the body mass index (BMI) is a good indicator of weight for height and cardiometabolic risk, indices of abdominal adiposity may be better screening tools for cardiovascular disease (CVD) risk. PURPOSE: This study compared the sagittal abdominal diameter, with correction for height (SADHtR), and waist circumference, with correction for height (WHtR), and BMI, which includes a height correction, as predictors of CVD. METHODS: A total of 11,449 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. SADHtR and WHtR were measured by trained technicians. For SADHtR, the subject was in the supine position and a sliding-beam abdominal caliper with a built-in bubble was used to ensure a vertical measurement. WHtR was assessed by extending a measuring tape around the waist in a horizontal plane at the upper level of the iliac crest. For both SADHtR and WHtR, the measured values were divided by height. Additionally, subjects were asked to report if a doctor or other health care professional had ever told them that they had congestive heart failure, coronary heart disease, angina, heart attack, and/or stroke. Subjects were divided into quartiles based on their separate SADHtR, WHtR, and BMI values and logistic regression was employed to analyze the data. RESULTS: With age, sex, and race controlled, odds ratios for having or not having CVD were: Q1 vs Q2: SADHtR: 1.31 (95% CI: 1.00-1.73); WHtR: 1.05 (0.72-1.53) and BMI: 1.07 (0.81-1.41). Q1 vs Q3: SADHtR: 1.81 (95% CI: 1.44-2.28); WHtR: 1.38 (1.01-1.88) and BMI: 1.26 (0.95-1.67). Q1 vs Q4: SADHtR: 2.65 (95% CI: 2.07-3.38); WHtR: 2.11 (1.53-2.92) and BMI: 1.86 (1.34-2.58). Overall, SADHtR was the best predictor of CVD, followed by WHtR, and BMI was the weakest of the three, for each quartile comparison. Effect modification was evaluated with BMI divided into sex-specific quartiles and SADHtR was a strong predictor of CVD within each quartile. WHtR was a significant predictor of CVD within each BMI quartile except the first. CONCLUSION: Clinicians and epidemiologists should seriously consider including WHtR or SADHtR, particularly the latter, as a screening tool within their programs

10-year Weight Change and Biological Aging in a Random Sample of 3,059 U.S. Adults

Telomeres play a key role in the protection of chromosomes. A good index of biological aging is the length of telomeres. Telomeres gradually shorten over time. Hence, they are strongly related to chronological age. Lifestyle is also an important factor influencing telomere length. PURPOSE: This investigation was designed to study the relationship between 10-yr weight change and leukocyte telomere length (LTL) in a large sample of 3,059 randomly selected U.S. adults, 35-70 years old. METHODS: NHANES (National Health and Nutrition Examination Survey) data were used with a cross-sectional design to determine the relationship between percent weight change and LTL. Percent weight change was calculated by subtracting baseline body weight 10-yrs earlier from current body weight and then dividing by the individual’s baseline body weight. The quantitative polymerase chain reaction method was used to measure LTL relative to standard reference DNA (T/S ratio). Covariates included age, sex, race/ethnicity, year of assessment, economic status, intent to lose weight, BMI, smoking, total physical activity, and disease status, (i.e., having or not having diabetes, cardiovascular disease, and/or cancer). Multiple regression was used to determine the linear relationship between percent weight change and LTL. Potential mediating variables were controlled using partial correlation. Because women and men differed significantly in percent 10-yr weight change and also telomere length, the data were analyzed separately by sex. RESULTS: After adjusting for age, race, year of assessment, and economic status, the association between percent 10-yr weight change and LTL was significant in women (F=8.0, P=0.0085). Controlling for all the covariates weakened the relationship slightly (F=6.5, P=0.0163). With all the covariates controlled, for each 1 percentage point increase in weight over the 10-yrs, telomeres were 3.96 base pairs (bp) shorter, on average. Given each 1-yr increase in age was associated with telomeres that were 14.2 bp shorter in women, each 3.6 percentage point increase in weight over the 10-yrs was predictive of 1 yr greater biological aging. 10-yr weight change was not associated with LTL in men. CONCLUSION: 10-yr weight change is a significant predictor of biological aging in U.S. women, but not in men

Abdominal Adiposity Indexed by the Sagittal Abdominal Diameter and Risk of Mortality in 14,119 U.S. Adults

The body mass index (BMI) is frequently used as a general measure of overweight and obesity. It is a good predictor of disease and premature death. However, research shows that indices of abdominal adiposity tend to be better predictors of disease risk and mortality than BMI. To date, the sagittal abdominal diameter (SAD), an index of abdominal adiposity, has never been evaluated as a predictor of mortality. PURPOSE: The present study was conducted to determine the extent that adults with different levels of SAD vary in their risk of all-cause mortality over an average follow-up of 6 years. METHODS: A total of 14,119 randomly selected adults, ages 20-79, from the National Health and Nutrition Examination Survey (NHANES), were included. SAD was measured by trained technicians during the years 2011-2016. The abdominal height of subjects was assessed in the supine position and a sliding-beam abdominal caliper with a built-in bubble was used to ensure a vertical measurement. Mortality data were acquired from the U.S. public-use linked mortality files (LMF), which are available for NHANES participants through 2018. Adjustments were made for 9 baseline potential confounding variables, including age, sex, race, BMI, cardiovascular disease, cancer, liver disease, smoking, and alcohol use. Subjects were divided into sex-specific quartiles based on their SAD values, and Cox proportional hazard ratios were calculated to determine risk of mortality over the follow-up period using SAS 9.4. RESULTS: With all the covariates controlled, hazard ratios showed a dose response relationship with all-cause mortality. Specifically, adults in Quartile 1 (Q1), those with the lowest sex-specific abdominal adiposity, had 0.45 (95% CI: 0.28-0.73) times the risk of mortality compared to those in Quartile 4 (Q4). Additionally, risk of mortality was 0.63 (95% CI: 0.42-0.95) for adults in Q2 vs Q4, and 0.67 (95% CI: 0.48-0.93) for Q3 vs Q4, each statistically significant. In the Q1 vs Q4 comparison, risk of mortality was 55% lower for those with the leanest SAD values. Overall, SAD was related to risk of all-cause mortality in a dose-response pattern. CONCLUSION: Epidemiologists and health care providers should seriously consider utilizing SAD as a screening tool within their programs. It is an excellent predictor of all-cause mortality

Dietary Fiber Intake Predicts 10-Yr Weight Change in 7,804 U.S. Adults

Although the relationship between dietary fiber intake and obesity has been examined many times, studies evaluating the association between fiber consumption and long-term weight gain are rare. This is unfortunate because it is weight gain over time that drives the development of obesity. PURPOSE: This study was conducted to determine the relationship between dietary fiber intake and weight change over a 10-yr period in 7,804 U.S. men and women, 36-70 years old. METHODS: Data from the National Health and Nutrition Examination Survey (NHANES) were used to answer the research question. Because subjects were randomly selected, the results are generalizable to the U.S. adult population within the same age-range. Weight change (kg) over the previous 10 years was measured by subtracting self-reported, baseline body weight 10-yrs earlier from current measured body weight. Percent weight change was calculated by dividing 10-yr weight change (kg) by baseline body weight. Dietary fiber intake was assessed by taking the average of two 24-hr dietary recall interview results (midnight to midnight) administered by trained technicians, the first in-person and the second via telephone. Fiber consumption was expressed as grams consumed per 1000 kcal. Multiple regression was used to determine the linear relationship between fiber intake and percent weight change. Demographic covariates included age, sex, and race/ethnicity. Lifestyle covariates included total physical activity, smoking, alcohol use, and whether the participant was on a special diet. Potential mediating variables were controlled using partial correlation. RESULTS: After controlling for the demographic covariates, the association between fiber intake and percent 10-yr weight change was linear and inverse (F=19.2, PCONCLUSION: The more dietary fiber U.S. men and women consume, the less weight they tend to gain over 10 years

Strength Training and Waist Circumference: Evidence Based on 5,581 Randomly Selected U.S. Men and Women

Abdominal obesity is a risk factor for many serious diseases. Waist circumference is a good measure of abdominal adiposity. A number of investigations show that regular exercise reduces abdominal obesity. However, few studies have focused on strength training and abdominal fat. PURPOSE: This study evaluated the association between time spent strength training (ST) and abdominal adiposity, indexed by waist circumference (WC), in a random sample of 5,581 U.S adults. METHODS: Data collected as part of the National Health and Nutrition Examination Survey (NHANES) was used to answer the research question using a cross-sectional design. The findings are applicable to the general U.S adult population because the sample was randomly selected. Time spent strength training (ST) per week was calculated by multiplying the number of days of ST per week by the number of minutes per session. Total MET-minutes of participation in other types of physical activity (PA) was calculated based on self-reported involvement in 47 other activities. ANOVA and partial correlation were used to determine differences in mean waist circumferences across 3 categories of weekly ST: None, 10-50 minutes/week (Moderate), and 60+ minutes/week (Frequent). Partial correlation and the LSmeans procedure were used to adjust means for differences in potential confounders, including age, race, income, smoking pack years, BMI, and MET-minutes of activity other than ST. Data from U.S. men and women were analyzed separately. RESULTS: In U.S. women (n=2,950), (Mean ± SE) Frequent (88.8 ± 1.2 cm) and Moderate lifters (89.5 ± 1.2 cm) each had significantly smaller waists than non-lifters (91.3 ± 0.9), F=5.1, P=0.0126 (denominator df=29). The relationship was stronger in men (n=2,631) given Frequent (91.0 ± 1.1 cm) and Moderate lifters (92.5 ± 1.0 cm) each had significantly smaller waists than non-lifters (94.9 ± 0.8 cm), F=43.5, PCONCLUSION: Strength training accounts for lower levels of abdominal fat in U.S. men and women

Vigorous Physical Activity and the Length of Telomeres Across Levels of BMI in 4,458 U.S. Adults

Telomere length is an index of cellular aging. Longer telomeres are predictive of longer life. Healthy lifestyles are associated with longer telomeres. PURPOSE: This study focused on the relationship between time spent in vigorous physical activity (PA) and leukocyte telomere length (LTL) in 4,458 randomly selected U.S. adults, 20-69 years old. METHODS: The association was studied using data collected as part of the National Health and Nutrition Examination Survey (NHANES) and a cross-sectional design. Vigorous physical activity was indexed by calculating total time spent jogging or running per week (Jog/Run/Wk). Weekly jog/run time was calculated by multiplying days of jog/run per week by minutes per session. From the total, 3 categories were formed: None, Some, and Met Guidelines. Adults who jogged or ran more than 10 min/wk but less than 75 min/wk fit into the Some category. Adults who jog/ran 75 min/wk or more, and therefore met or exceeded the U.S. PA guidelines, were labeled, Met Guidelines. Participation in 47 other forms of PA was also calculated based on time spent in other PAs. Data were analyzed using one-way ANOVA. Partial correlation was used to adjust for differences in potential mediating factors, including demographic (age, sex, race, and economic status) and lifestyle factors (smoking pack years, BMI, participation in PA other than jog/run/wk, diabetes status, and cardiovascular disease status. RESULTS: In the total sample, after adjusting for all the potential covariates, mean LTL differed across the 3 jog/run/wk categories (F=4.1, P=0.0272). Specifically, adults who met the guidelines via jogging or running had longer telomeres than those who did not perform regular PA (None). With the sample delimited to normal weight adults only, there was no relationship between jog/run/wk and LTL (F=1.0, P=0.3774). However, focusing on adults with overweight only, the association was significant (F=3.9, P=0.0327). Adults who met the guidelines via jog/run had longer telomeres than sedentary adults. With the sample delimited to adults with obesity only, there were no differences in LTL across the 3 levels of jog/run/wk (F=0.8, P=0.4529). CONCLUSION: Jogging/running is predictive of adults with longer telomeres, but only among overweight adults, not in adults with normal weight or obesity

Strength Training and Biological Aging: Telomere Evidence from a National Sample of 4,813 U.S. Adults

Telomere length is an index of biological aging. As humans age, their telomeres become progressively shorter. Additionally, healthy lifestyle practices are associated with longer telomeres and unhealthy habits predict shorter telomeres. PURPOSE: This study evaluated the association between weekly time spent strength training (ST) and leukocyte telomere length (LTL) in 4,813 randomly selected U.S. adults, 20-69 years old. METHODS: Data collected as part of the National Health and Nutrition Examination Survey (NHANES) was employed to answer the research question using a cross-sectional design. The findings are generalizable to the U.S. adult population. Time spent ST per wk was calculated by multiplying the number of days of ST per wk by min. per session. Participation in other forms of physical activity (PA) was also calculated based on reported involvement in 47 other PAs. Data were analyzed using multiple regression. Partial correlation was used to adjust for differences in potential confounders, including demographic (age, sex, race, and economic status) and lifestyle factors (smoking, BMI, diabetes status, and participation in PA other than ST). RESULTS: In the total sample, with all the covariates controlled, ST and LTL were linearly related (F=12.1, P=0.0016). With men and women studied separately, LTL was not related to ST time in women (F=3.3, P=0.0813), probably because relatively few U.S. women (n=2483) engaged in regular ST (4.9%). Of the 2,330 men in the sample, 9% reported some ST. The association was significant and positive in men. After adjusting for the demographic covariates (F=10.3, P=0.0032) and the demographic and lifestyle covariates combined (F=9.1, P=0.0053), results showed that as time spent ST increased, telomere length increased, meaning biologic aging decreased. In men, for each min. spent in ST per week, telomeres were 0.57 base pairs (bp) longer, on average. Therefore, men with the same age, race, economic status, smoking, BMI, diabetes status, and other PA habits, who ST 90 min. per week, had telomeres that were 51 bp longer than non-lifters, on average. In this national sample, the difference in bp associated with 90 min. of ST per wk was equivalent to about 3 yrs less biological aging. CONCLUSION: Regular ST is predictive of longer telomeres and less biological aging, especially in men

St. Louis Area Earthquake Hazards Mapping Project: Seismic and Liquefaction Hazard Maps

We present probabilistic and deterministic seismic and liquefaction hazard maps for the densely populated St. Louis metropolitan area that account for the expected effects of surficial geology on earthquake ground shaking. Hazard calculations were based on a map grid of 0.005°, or about every 500 m, and are thus higher in resolution than any earlier studies. To estimate ground motions at the surface of the model (e.g., site amplification), we used a new detailed near-surface shear-wave velocity model in a 1D equivalent- linear response analysis. When compared with the 2014 U.S. Geological Survey (USGS) National Seismic Hazard Model, which uses a uniform firm-rock-site condition, the new probabilistic seismic-hazard estimates document much more variability. Hazard levels for upland sites (consisting of bedrock and weathered bedrock overlain by loess-covered till and drift deposits), show up to twice the ground-motion values for peak ground acceleration (PGA), and similar ground-motion values for 1.0 s spectral acceleration (SA). Probabilistic ground-motion levels for lowland alluvial floodplain sites (generally the 20-40-m-thick modern Mississippi and Missouri River floodplain deposits overlying bedrock) exhibit up to twice the ground-motion levels for PGA, and up to three times the ground-motion levels for 1.0 s SA. Liquefaction probability curves were developed from available standard penetration test data assuming typical lowland and upland water table levels. A simplified liquefaction hazard map was created from the 5%-in-50-year probabilistic ground-shaking model. The liquefaction hazard ranges from low (\u3c40% of area expected to liquefy) in the uplands to severe (\u3e60% of area expected to liquefy) in the lowlands. Because many transportation routes, power and gas transmission lines, and population centers exist in or on the highly susceptible lowland alluvium, these areas in the St. Louis region are at significant potential risk from seismically induced liquefaction and associated ground deformation

Galaxy Clustering in Early SDSS Redshift Data

We present the first measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our sample consists of 29,300 galaxies with redshifts 5,700 km/s < cz < 39,000 km/s, distributed in several long but narrow (2.5-5 degree) segments, covering 690 square degrees. For the full, flux-limited sample, the redshift-space correlation length is approximately 8 Mpc/h. The two-dimensional correlation function \xi(r_p,\pi) shows clear signatures of both the small-scale, ``fingers-of-God'' distortion caused by velocity dispersions in collapsed objects and the large-scale compression caused by coherent flows, though the latter cannot be measured with high precision in the present sample. The inferred real-space correlation function is well described by a power law, \xi(r)=(r/6.1+/-0.2 Mpc/h)^{-1.75+/-0.03}, for 0.1 Mpc/h < r < 16 Mpc/h. The galaxy pairwise velocity dispersion is \sigma_{12} ~ 600+/-100 km/s for projected separations 0.15 Mpc/h < r_p < 5 Mpc/h. When we divide the sample by color, the red galaxies exhibit a stronger and steeper real-space correlation function and a higher pairwise velocity dispersion than do the blue galaxies. The relative behavior of subsamples defined by high/low profile concentration or high/low surface brightness is qualitatively similar to that of the red/blue subsamples. Our most striking result is a clear measurement of scale-independent luminosity bias at r < 10 Mpc/h: subsamples with absolute magnitude ranges centered on M_*-1.5, M_*, and M_*+1.5 have real-space correlation functions that are parallel power laws of slope ~ -1.8 with correlation lengths of approximately 7.4 Mpc/h, 6.3 Mpc/h, and 4.7 Mpc/h, respectively.Comment: 51 pages, 18 figures. Replaced to match accepted ApJ versio

The Seventh Data Release of the Sloan Digital Sky Survey

This paper describes the Seventh Data Release of the Sloan Digital Sky Survey (SDSS), marking the completion of the original goals of the SDSS and the end of the phase known as SDSS-II. It includes 11663 deg^2 of imaging data, with most of the roughly 2000 deg^2 increment over the previous data release lying in regions of low Galactic latitude. The catalog contains five-band photometry for 357 million distinct objects. The survey also includes repeat photometry over 250 deg^2 along the Celestial Equator in the Southern Galactic Cap. A coaddition of these data goes roughly two magnitudes fainter than the main survey. The spectroscopy is now complete over a contiguous area of 7500 deg^2 in the Northern Galactic Cap, closing the gap that was present in previous data releases. There are over 1.6 million spectra in total, including 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data release includes improved stellar photometry at low Galactic latitude. The astrometry has all been recalibrated with the second version of the USNO CCD Astrograph Catalog (UCAC-2), reducing the rms statistical errors at the bright end to 45 milli-arcseconds per coordinate. A systematic error in bright galaxy photometr is less severe than previously reported for the majority of galaxies. Finally, we describe a series of improvements to the spectroscopic reductions, including better flat-fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities. (Abridged)Comment: 20 pages, 10 embedded figures. Accepted to ApJS after minor correction