Bo Cai

Effects of Cardiorespiratory Fitness on Blood Pressure Trajectory With Aging in a Cohort of Healthy Men

BACKGROUNDnAlthough the trajectory of blood pressure (BP) with aging is well known, there is a lack of data on how cardiorespiratory fitness (hereafter referred to as fitness) affects age-associated changes in BP.nnnOBJECTIVESnThe objective of the study was to investigate whether fitness alters the aging-BP trajectory.nnnMETHODSnA cohort from the Aerobics Center Longitudinal Study totaling 13,953 men between 20 and 90 years of age who did not have hypertension, cardiovascular disease, or cancer completed 3 to 28 (mean of 3.8) follow-up medical examinations between 1970 and 2006. Fitness was measured by a maximal treadmill exercise test. Longitudinal data were analyzed using linear mixed models.nnnRESULTSnDiastolic blood pressure (DBP) tended to increase until nearly 60 years of age, when a decrease was observed. Systolic blood pressure (SBP) tended to increase over all age periods. On multivariate analysis, average SBP increased by 0.30 mmxa0Hg (95% confidence interval: 0.29 to 0.31) with 1-year age increment after adjusting for body fat percent, fitness, resting heart rate, glucose level, triglyceride level, cholesterol level, current smoking, heavy alcohol consumption, and parental history of hypertension. DBP had a yearly increase of 0.14 mmxa0Hg (95% confidence interval: 0.13 to 0.15) before age 60 years. Overall, abnormal SBP (>120 mmxa0Hg) began to occur at approximately 50 years of age and abnormal DBP (>80 mmxa0Hg) began to occur at 60 years of age. Men with higher fitness levels experienced abnormal SBP later than those with low fitness levels.nnnCONCLUSIONSnOur findings underscore the potential modifying effect of fitness on BP trajectory with aging over the male adult life span. Improving fitness levels might extend the normal SBP and DBP ranges, delaying the development of hypertension.

Mercury in fish and adverse reproductive outcomes: results from South Carolina

BackgroundMercury is a metal with widespread distribution in aquatic ecosystems and significant neurodevelopmental toxicity in humans. Fish biomonitoring for total mercury has been conducted in South Carolina (SC) since 1976, and consumption advisories have been posted for many SC waterways. However, there is limited information on the potential reproductive impacts of mercury due to recreational or subsistence fish consumption.MethodsTo address this issue, geocoded residential locations for live births from the Vital Statistics Registry (1995–2005, Nu2009=u2009362,625) were linked with spatially interpolated total mercury concentrations in fish to estimate potential mercury exposure from consumption of locally caught fish. Generalized estimating equations were used to test the hypothesis that risk of low birth weight (LBW, <2,500 grams) or preterm birth (PTB, <37xa0weeks clinical gestation) was greater among women living in areas with elevated total mercury in fish, after adjustment for confounding. Separate analyses estimated term LBW and PTB risks using residential proximity to rivers with fish consumption advisories to characterize exposure.ResultsTerm LBW was more likely among women residing in areas in the upper quartile of predicted total mercury in fish (odds ratio [OR]u2009=u20091.04; 95% confidence interval [CI]: 1.00-1.09) or within 8 kilometers of a river with a ‘do not eat’ fish advisory (1.05; 1.00-1.11) compared to the lowest quartile, or rivers without fish consumption restrictions, respectively. When stratified by race, risks for term LBW or PTB were 10-18% more likely among African-American (AA) mothers living in areas with the highest total fish mercury concentrations.ConclusionsTo our knowledge, this is the first study to examine the relationship between fish total mercury concentrations and adverse reproductive outcomes in a large population-based sample that included AA women. The ecologic nature of exposure assessment in this study precludes causal inference. However, the results suggest a need for more detailed investigations to characterize patterns of local fish consumption and potential dose–response relationships between mercury exposure and adverse reproductive outcomes, particularly among AA mothers.

Examination of wrist and hip actigraphy using a novel sleep estimation procedure

Objective Improving and validating sleep scoring algorithms for actigraphs enhances their usefulness in clinical and research applications. The MTI® device (ActiGraph, Pensacola, FL) had not been previously validated for sleep. The aims were to (1) compare the accuracy of sleep metrics obtained via wrist- and hip-mounted MTI® actigraphs with polysomnographic (PSG) recordings in a sample that included both normal sleepers and individuals with presumed sleep disorders; and (2) develop a novel sleep scoring algorithm using spline regression to improve the correspondence between the actigraphs and PSG. Methods Original actigraphy data were amplified and their pattern was estimated using a penalized spline. The magnitude of amplification and the spline were estimated by minimizing the difference in sleep efficiency between wrist- (hip-) actigraphs and PSG recordings. Sleep measures using both the original and spline-modified actigraphy data were compared to PSG using the following: mean sleep summary measures; Spearman rank-order correlations of summary measures; percent of minute-by-minute agreement; sensitivity and specificity; and Bland–Altman plots. Results The original wrist actigraphy data showed modest correspondence with PSG, and much less correspondence was found between hip actigraphy and PSG. The spline-modified wrist actigraphy produced better approximations of interclass correlations, sensitivity, and mean sleep summary measures relative to PSG than the original wrist actigraphy data. The spline-modified hip actigraphy provided improved correspondence, but sleep measures were still not representative of PSG. Discussion The results indicate that with some refinement, the spline regression method has the potential to improve sleep estimates obtained using wrist actigraphy.

Prostate Specific Antigen-Growth Curve Model to Predict High-Risk Prostate Cancer

To investigate if a prostate specific antigen (PSA)‐derived growth curve can predict the occurrence of high‐risk prostate cancer (PrCA).

Factors Related to Coronary Heart Disease Risk Among Men: Validation of the Framingham Risk Score

Introduction Coronary heart disease (CHD) remains a leading cause of death in the United States. The Framingham Risk Score (FRS) was developed to help clinicians in determining their patients’ CHD risk. We hypothesize that the FRS will be significantly predictive of CHD events among men in the Aerobics Center Longitudinal Study (ACLS) population. Methods Our study consisted of 34,557 men who attended the Cooper Clinic in Dallas, Texas, for a baseline clinical examination from 1972 through 2002. CHD events included self-reported myocardial infarction or revascularization or death due to CHD. During the 12-year follow-up 587 CHD events occurred. Multivariable-adjusted hazard ratios generated from ACLS analysis were compared with the application of FRS to the Framingham Heart Study (FHS). Results The ACLS cohort produced similar hazard ratios to the FHS. The adjusted Cox proportional hazard model revealed that men with total cholesterol of 280 mg/dL or greater were 2.21 (95% confidence interval (CI), 1.59–3.09) times more likely to have a CHD event than men with total cholesterol from 160 through 199mg/dL; men with diabetes were 1.63 (95% CI, 1.35–1.98) times more likely to experience a CHD event than men without diabetes. Conclusion The FRS significantly predicts CHD events in the ACLS cohort. To the best of our knowledge, this is the first report of a large, single-center cohort study to validate the FRS by using extensive laboratory and clinical measurements.

The use of multiphase nonlinear mixed models to define and quantify long-term changes in serum prostate-specific antigen: data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial

PURPOSEnTo test the hypothesis that the pattern of prostate-specific antigen (PSA) change in men diagnosed with high-risk prostate cancer (PrCA) differs from the pattern evident in men diagnosed with low-risk PrCA or those with no evidence of PrCA.nnnMETHODSnA retrospective cohort study from which PSA measures were taken before PrCA diagnosis from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Data were fitted using a nonlinear regression model to estimate the adjusted absolute and relative (%) change of PSA.nnnRESULTSnData on 20,888 men with an average age of 61.61 years were included in the analysis. Of these, the 324 (1.55%) diagnosed with high-risk PrCA had a steeper and earlier transition into an exponential pattern of PSA change than the 1368 men diagnosed with low-risk cancer. At 1 year before diagnosis and/or exit, the average absolute PSA rates were 0.05 ng/mL/year (0.05-0.05), 0.59 (0.52-0.66), and 2.60 (2.11-3.09) for men with no evidence of PrCA, men with low-risk PrCA and those with high-risk PrCA, respectively.nnnCONCLUSIONSnThe pattern of PSA change with time was significantly different for men who develop high-risk PrCA from those diagnosed with low-risk PrCA. Further research is required to validate this method and its utilization in PrCA screening.

Addition of estimated cardiorespiratory fitness to the clinical assessment of 10-year coronary heart disease risk in asymptomatic men

The Framingham Risk Score (FRS) was developed to quantify a patients coronary heart disease (CHD) risk. Non-exercise estimated CRF (e-CRF) may provide a clinically practical method for describing cardiorespiratory fitness. We computed e-CRF and tested its association with the FRS and CHD. Male participants (n = 29,854) in the Aerobics Center Longitudinal Study (ACLS) who completed a baseline examination between 1979–2002 were followed for 12 years to determine incident CHD defined by self-report of myocardial infarction, revascularization, or CHD mortality. e-CRF was defined from a 7-item scale and categorized using age-specific tertiles. Multivariable survival analysis determined associations between FRS, e-CRF, and CHD. Interaction between e-CRF and FRS was tested by stratified analysis by ‘low’ and ‘moderate or high’ 10-year CHD risk. Men with high e-CRF were significantly (p-value < 0.0001) younger, and less likely to be smokers, compared to men with low e-CRF. Multivariable survival analysis reported men with high e-CRF were 29% (HR = 0.71; 95% 0.56, 0.88) less likely to experience a CHD event compared to men with low e-CRF. Stratified analyses showed men with ‘low’ 10-year FRS predicted CHD risk and high e-CRF had a 28% (HR = 0.72; 95% CI 0.57, 0.91) lower CHD-mortality risk compared to men with low e-CRF, no association was found in this group and men with moderate e-CRF. Men who were more fit had a decreased risk for CHD compared to men in the lowest third of fitness. Estimated CRF may add clinical value to the FRS and help clinicians better predict long-term CHD risk.

Body mass index trajectories during infancy and pediatric obesity at 6 years

PURPOSEnThe purpose of the article was to examine the relationship between body mass index (BMI) trajectories during infancy and risk of obesity at the age of 6 years.nnnMETHODSnWe used data on 1169 children with at least two BMI measures during their first year of life from the Infant Feeding Practices Survey II and its Year 6 Follow-Up. Latent class growth analysis was used to identify distinct trajectories of BMI, and multiple logistic regression analyses were used to assess the association of the identified trajectories with obesity at the age of 6 years.nnnRESULTSnThree trajectories of BMI were identified during the first year of life: low stable (80.2%), high stable (16.9%), and rising (2.8%). Obesity at the age of 6 years was highest among children with a high-stable trajectory (17.2%), followed by the low-stable (9.6%) and rising (9.1%) groups. Compared with those in the low-stable trajectory, the adjusted odds ratio for obesity at the age of 6 years was 1.79 (95% confidence interval 1.13-2.84) in children with the high-stable growth trajectory and 0.84 (0.26-2.72) in children with the rising growth trajectory.nnnCONCLUSIONSnHigh-stable BMI trajectory in infancy resulted in a higher risk for obesity at the age of 6 years, but had low accuracy for identifying obese children at the age of 6 years.