Heart rate variability in response to pain stimulus in VLBW infants followed longitudinally during NICU stay.

The objective of this longitudinal study, conducted in a neonatal intensive care unit, was to characterize the response to pain of high-risk very low birth weight infants (<1,500 g) from 23 to 38 weeks post-menstrual age (PMA) by measuring heart rate variability (HRV). Heart period data were recorded before, during, and after a heel lanced or wrist venipunctured blood draw for routine clinical evaluation. Pain response to the blood draw procedure and age-related changes of HRV in low-frequency and high-frequency bands were modeled with linear mixed-effects models. HRV in both bands decreased during pain, followed by a recovery to near-baseline levels. Venipuncture and mechanical ventilation were factors that attenuated the HRV response to pain. HRV at the baseline increased with post-menstrual age but the growth rate of high-frequency power was reduced in mechanically ventilated infants. There was some evidence that low-frequency HRV response to pain improved with advancing PMA.

Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

Mixed effects model in negative exponential curve

Despite many researches on development in education and psychology, not often is the methodology tested with real data. A major barrier to test the growth model is that the design of study includes repeated observations and the nature of the growth is nonlinear. The repeat measurements on a nonlinear model require sophisticated statistical methods. In this study, we present mixed effects model in a negative exponential curve to describe the development of children's reading skills. This model can describe the nature of the growth on children's reading skills and account for intra-individual and inter-individual variation. We also apply simple techniques including cross-validation, regression, and graphical methods to determine the most appropriate curve for data, to find efficient initial values of parameters, and to select potential covariates. We illustrate with an example that motivated this research: a longitudinal study of academic skills from grade 1 to grade 12 in Connecticut public schools. ^

Statistical issues on studies of mixed longitudinal design

Mixed longitudinal designs are important study designs for many areas of medical research. Mixed longitudinal studies have several advantages over cross-sectional or pure longitudinal studies, including shorter study completion time and ability to separate time and age effects, thus are an attractive choice. Statistical methodology used in general longitudinal studies has been rapidly developing within the last few decades. Common approaches for statistical modeling in studies with mixed longitudinal designs have been the linear mixed-effects model incorporating an age or time effect. The general linear mixed-effects model is considered an appropriate choice to analyze repeated measurements data in longitudinal studies. However, common use of linear mixed-effects model on mixed longitudinal studies often incorporates age as the only random-effect but fails to take into consideration the cohort effect in conducting statistical inferences on age-related trajectories of outcome measurements. We believe special attention should be paid to cohort effects when analyzing data in mixed longitudinal designs with multiple overlapping cohorts. Thus, this has become an important statistical issue to address. ^ This research aims to address statistical issues related to mixed longitudinal studies. The proposed study examined the existing statistical analysis methods for the mixed longitudinal designs and developed an alternative analytic method to incorporate effects from multiple overlapping cohorts as well as from different aged subjects. The proposed study used simulation to evaluate the performance of the proposed analytic method by comparing it with the commonly-used model. Finally, the study applied the proposed analytic method to the data collected by an existing study Project HeartBeat!, which had been evaluated using traditional analytic techniques. Project HeartBeat! is a longitudinal study of cardiovascular disease (CVD) risk factors in childhood and adolescence using a mixed longitudinal design. The proposed model was used to evaluate four blood lipids adjusting for age, gender, race/ethnicity, and endocrine hormones. The result of this dissertation suggest the proposed analytic model could be a more flexible and reliable choice than the traditional model in terms of fitting data to provide more accurate estimates in mixed longitudinal studies. Conceptually, the proposed model described in this study has useful features, including consideration of effects from multiple overlapping cohorts, and is an attractive approach for analyzing data in mixed longitudinal design studies.^

Analysis of life expectancy using linear and nonlinear models

Life expectancy has consistently increased over the last 150 years due to improvements in nutrition, medicine, and public health. Several studies found that in many developed countries, life expectancy continued to rise following a nearly linear trend, which was contrary to a common belief that the rate of improvement in life expectancy would decelerate and was fit with an S-shaped curve. Using samples of countries that exhibited a wide range of economic development levels, we explored the change in life expectancy over time by employing both nonlinear and linear models. We then observed if there were any significant differences in estimates between linear models, assuming an auto-correlated error structure. When data did not have a sigmoidal shape, nonlinear growth models sometimes failed to provide meaningful parameter estimates. The existence of an inflection point and asymptotes in the growth models made them inflexible with life expectancy data. In linear models, there was no significant difference in the life expectancy growth rate and future estimates between ordinary least squares (OLS) and generalized least squares (GLS). However, the generalized least squares model was more robust because the data involved time-series variables and residuals were positively correlated. ^

Assessing homogeneity in workplace exposure under stationary and non-stationary scenarios

In most epidemiological studies, historical monitoring data are scant and must be pooled to identify occupational groups with homogeneous exposures. Homogeneity of exposure is generally assessed in a group of workers who share a common job title or work in a common area. While published results suggest that the degree of homogeneity varies widely across job groups, less is known whether such variation differs across industrial sectors, classes of contaminants, or in the methods used to group workers. Relying upon a compilation of results presented in the literature, patterns of homogeneity among nearly 500 occupational groups of workers were evaluated on the basis of type of industry and agent. Additionally, effects of the characteristics of the sampling strategy on estimated indicators of homogeneity of exposure were assessed. ^ Exposure profiles for occupational groups of workers have typically been assessed under the assumption of stationarity, i.e., the mean exposure level and variance of the distribution that describes the underlying population of exposures are constant over time. Yet, the literature has shown that occupational exposures have declined in the last decades. This renders traditional methods for the description of exposure profiles inadequate. Thus, work was needed to develop appropriate methods to assess homogeneity for groups of workers whose exposures have changed over time. A study was carried out applying mixed effects models with a term for temporal trend to appropriately describe exposure profiles of groups of workers in the nickel-producing industry over a 20-year period. Using a sub-set of groups of nickel-exposed workers, another study was conducted to develop and apply a framework to evaluate the assumption of stationarity of the variances in the presence of systematic changes in exposure levels over time. ^

Understanding disparities in emergency department visits for asthma

Asthma is the most common chronic disorder in childhood, affecting an estimated 6.2 million children under 18 years (1). The purpose of this study was to look at individual- and community-level characteristics simultaneously to examine and explain the factors that contribute to the use of emergency department services by children 18 years old or less and to determine if there was an association between air quality and ED visits in the same population, from 2005-2007 in Houston/Harris County. Data were collected from the Houston Safety Net Hospital Emergency Department Use Study and the 2000 US Census. Bivariate and multivariate logistic regression models and mixed effects models were used to analyze data that was collected during the study period.^ There were 704,902 ED visits made by children 18 and younger, who were living in Houston from January 1, 2005 to December 31, 2007. Of those, 19,098 had a primary discharge diagnosis of asthma. Asthma ED visits varied by season, with proportions of ED visits for asthma highest from September-December. African-American children were 2.6 (95% CI, 2.43-2.66) times more likely to have an ED visit for asthma compared to White children. Poverty, single parent headed households, and younger age all a greater likelihood of having gone to the ED for asthma treatment. Compared to Whites living in lightly-monitored pollution areas, African-Americans and Hispanics living in heavily monitored areas were 1.15 (95% CI, 1.04-1.28) times more likely to have an ED visit for asthma.^ Race and poverty seem to account for a large portion of the disparities in ED use found among children. This was true even after accounting for multiple individual- and community-level variables. These results suggest that racial disparities in asthma continue to pose risks for African American children, and they point to the need for additional research into potential explanations and remedies. Programs to reduce inappropriate ED use must be sensitive to an array of complex socioeconomic issues within minority and income populations. ^

The role of cardiorespiratory fitness and weight status on 24-hr ambulatory blood pressure among adolescents

BACKGROUND: This observational research study investigated the association of cardiorespiratory fitness and weight status with repeated measures of 24-hr ambulatory blood pressure (24-hr ABP). Little is known about these associations and few data exist examining the interaction between cardiorespiratory fitness and weight status and the contributions of each on 24-hr ABP in youth. ^ METHODS: This research study used secondary analysis data from the "Adolescent Blood Pressure and Anger: Ethnic Differences" study. This current study sample included 374 African-American, Anglo-American, and Mexican-American adolescents 11-16 years of age. Mixed-effects models were used for testing the relationship between weight status and cardiorespiratory fitness and repeated measures of ambulatory blood pressure over 24 hours (24-hr ABP). Weight status was categorized into "normal weight" (BMI<85th percentile), "overweight" (85th≤BMI<95th), and "obese" (BMI≥95th). Cardiorespiratory fitness, determined by heart rate recovery (HRR), was defined as the difference between heart rate at peak exercise and heart rate at two minutes post-exercise, as measured by a height-adjusted step test and stratified into two groups: low and high fitness, using a median split. Ambulatory blood pressure (ABP) was monitored for a 24-hr period on a school day using the Spacelabs ambulatory monitor (Model 90207). Blood pressure and heart rate were recorded at 30 minute intervals throughout the day of recording and at 60 minute intervals during sleep. ^ RESULTS: No significant associations were found between weight status and mean 24-hr systolic blood pressure (SBP) or mean arterial pressure (MAP). A significant and inverse association between weight status and mean 24-hr diastolic blood pressure (DBP) was revealed. Cardiorespiratory fitness was significantly and inversely associated with mean 24-hr ABP. High fitness adolescents had significantly lower mean 24-hr SPB, DBP, and MAP measurements than low fitness adolescents. Compared to low fitness adolescents, high fitness adolescents had 1.90 mmHg, 1.16 mmHg, and 1.68 mmHg lower mean 24-hr SBP, DBP, and MAP, respectively. Additionally, high fitness appeared to afford protection from higher mean 24-hr SBP and MAP, irrespective of weight status. Among normal weight adolescents, low fitness resulted in higher mean 24-hr SBP and MAP, compared to their fit counterparts. Among adolescents categorized as high fitness, increasing weight status did not appear to result in higher mean 24-hr SBP or MAP. Cardiorespiratory fitness, rather than weight status, appeared to be a more dominant predictor of mean 24-hr SBP and MAP. ^ CONCLUSIONS: To our knowledge, this research is the first study to investigate the independent and combined contributions of cardiorespiratory fitness and weight status on 24-hr ABP, all objectively measured. The results of this study may potentially guide and inform future research. It appears that early cardiovascular disease (CVD) prevention should focus on improving cardiorespiratory fitness levels among all adolescents, particularly those adolescents least fit, regardless of their weight status, while obesity prevention efforts continue.^

Changes in the PQRST intervals and heart rate variability associated with rewarming in two newborns undergoing hypothermia therapy.

BACKGROUND: Little is known about the effects of hypothermia therapy and subsequent rewarming on the PQRST intervals and heart rate variability (HRV) in term newborns with hypoxic-ischemic encephalopathy (HIE). OBJECTIVES: This study describes the changes in the PQRST intervals and HRV during rewarming to normal core body temperature of 2 newborns with HIE after hypothermia therapy. METHODS: Within 6 h after birth, 2 newborns with HIE were cooled to a core body temperature of 33.5 degrees C for 72 h using a cooling blanket, followed by gradual rewarming (0.5 degrees C per hour) until the body temperature reached 36.5 degrees C. Custom instrumentation recorded the electrocardiogram from the leads used for clinical monitoring of vital signs. Generalized linear mixed models were calculated to estimate temperature-related changes in PQRST intervals and HRV. Results: For every 1 degrees C increase in body temperature, the heart rate increased by 9.2 bpm (95% CI 6.8-11.6), the QTc interval decreased by 21.6 ms (95% CI 17.3-25.9), and low and high frequency HRV decreased by 0.480 dB (95% CI 0.052-0.907) and 0.938 dB (95% CI 0.460-1.416), respectively. CONCLUSIONS: Hypothermia-induced changes in the electrocardiogram should be monitored carefully in future studies.

Genes to blood pressure: The effects of variation in genes of the renin-angiotensin system on the hormonal and renal control of blood pressure

Objective. Essential hypertension affects 25% of the US adult population and is a leading contributor to morbidity and mortality. Because BP is a multifactorial phenotype that resists simple genetic analysis, intermediate phenotypes within the complex network of BP regulatory systems may be more accessible to genetic dissection. The Renin-Angiotensin System (RAS) is known to influence intermediate and long-term blood pressure regulation through alterations in vascular tone and renal sodium and fluid resorption. This dissertation examines associations between renin (REN), angiotensinogen (AGT), angiotensin-converting enzyme (ACE) and angiotensin II type 1 receptor (AT1) gene variation and interindividual differences in plasma hormone levels, renal hemodynamics, and BP homeostasis.^ Methods. A total of 150 unrelated men and 150 unrelated women, between 20.0 and 49.9 years of age and free of acute or chronic illness except for a history of hypertension (11 men and 7 women, all off medications), were studied after one week on a controlled sodium diet. RAS plasma hormone levels, renal hemodynamics and BP were determined prior to and during angiotensin II (Ang II) infusion. Individuals were genotyped by PCR for a variable number tandem repeat (VNTR) polymorphism in REN, and for the following restriction fragment length polymorphisms (RFLP): AGT M235T, ACE I/D, and AT1 A1166C. Associations between clinical measurements and allelic variation were examined using multiple linear regression statistical models.^ Results. Women homozygous for the AT1 1166C allele demonstrated higher intracellular levels of sodium (p = 0.044). Men homozygous for the AGT T235 allele demonstrated a blunted decrement in renal plasma flow in response to Ang II infusion (p = 0.0002). There were no significant associations between RAS gene variation and interindividual variation in RAS plasma hormone levels or BP.^ Conclusions. Rather than identifying new BP controlling genes or alleles, the study paradigm employed in this thesis (i.e., measured genes, controlled environments and interventions) may provide mechanistic insight into how candidate genes affect BP homeostasis. ^

Health outcomes, quality improvement and cost-effectiveness of the Community Diabetes Education (CoDE) program: Results of a randomized controlled trial

The objectives of this dissertation were to evaluate health outcomes, quality improvement measures, and the long-term cost-effectiveness and impact on diabetes-related microvascular and macrovascular complications of a community health worker-led culturally tailored diabetes education and management intervention provided to uninsured Mexican Americans in an urban faith-based clinic. A prospective, randomized controlled repeated measures design was employed to compare the intervention effects between: (1) an intervention group (n=90) that participated in the Community Diabetes Education (CoDE) program along with usual medical care; and (2) a wait-listed comparison group (n=90) that received only usual medical care. Changes in hemoglobin A1c (HbA1c) and secondary outcomes (lipid status, blood pressure and body mass index) were assessed using linear mixed-models and an intention-to-treat approach. The CoDE group experienced greater reduction in HbA1c (-1.6%, p<.001) than the control group (-.9%, p<.001) over the 12 month study period. After adjusting for group-by-time interaction, antidiabetic medication use at baseline, changes made to the antidiabetic regime over the study period, duration of diabetes and baseline HbA1c, a statistically significant intervention effect on HbA1c (-.7%, p=.02) was observed for CoDE participants. Process and outcome quality measures were evaluated using multiple mixed-effects logistic regression models. Assessment of quality indicators revealed that the CoDE intervention group was significantly more likely to have received a dilated retinal examination than the control group, and 53% achieved a HbA1c below 7% compared with 38% of control group subjects. Long-term cost-effectiveness and impact on diabetes-related health outcomes were estimated through simulation modeling using the rigorously validated Archimedes Model. Over a 20 year time horizon, CoDE participants were forecasted to have less proliferative diabetic retinopathy, fewer foot ulcers, and reduced numbers of foot amputations than control group subjects who received usual medical care. An incremental cost-effectiveness ratio of $355 per quality-adjusted life-year gained was estimated for CoDE intervention participants over the same time period. The results from the three areas of program evaluation: impact on short-term health outcomes, quantification of improvement in quality of diabetes care, and projection of long-term cost-effectiveness and impact on diabetes-related health outcomes provide evidence that a community health worker can be a valuable resource to reduce diabetes disparities for uninsured Mexican Americans. This evidence supports formal integration of community health workers as members of the diabetes care team.^

Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

Preclinical modeling of multi-drug cancer therapies

Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

Determinants of CD4 cell count decline after treatment interruption

Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

Whence a healthy mind: Correlation of physical fitness and academic performance among schoolchildren

Background. Public schools are a key forum in the fight for child health because of the opportunities they present for physical activity and fitness surveillance. However, because schools are evaluated and funded on the basis of standardized academic performance rather than physical activity, empirical research evaluating the connections between fitness and academic performance is needed to justify curriculum allocations to physical activity. ^ Methods. Analyses were based on a convenience sample of 315,092 individually-matched standardized academic (TAKS™) and fitness (FITNESSGRAM®) test records collected by 13 Texas school districts under state mandates. We categorized each fitness result in quintiles by age and gender and used a mixed effects regression model to compare the academic performance of the top and bottom fitness groups for each fitness test and grade level combination. ^ Results. All fitness variables except BMI showed significant, positive associations with academic performance after sociodemographic covariate adjustments, with effect sizes ranging from 0.07 (95% CI: 0.05,0.08) in girls trunklift-TAKS reading to 0.34 (0.32,0.35) in boys cardiovascular-TAKS math. Cardiovascular fitness showed the largest inter-quintile difference in TAKS score (32-75 points), followed by curl-ups. After an additional adjustment for BMI and curl-ups, cardiovascular associations peaked in 8th-9 th grades (maximum inter-quintile difference 142 TAKS points; effect size 0.75 (0.69,0.82) for 8th grade girls math) and showed dose-response characteristics across quintiles (p<0.001 for both genders and outcomes). BMI analysis demonstrated limited, non-linear association with academic performance after adjustment for sociodemographic, cardiovascular fitness and curl-up variables. Low-BMI Hispanic high school boys showed significantly lower TAKS scores than the moderate (but not high) BMI group. High-BMI non-Hispanic white high school girls showed significantly lower scores than the moderate (but not low) BMI group. ^ Conclusions. In this study, fitness was strongly and significantly related to academic performance. Cardiovascular fitness showed a distinct dose-response association with academic performance independent of other sociodemographic and fitness variables. The association peaked in late middle to early high school. The independent association of BMI to academic performance was only found in two sub-groups and was non-linear, with both low and high BMI posing risk relative to moderate BMI but not to each other. In light of our findings, we recommend that policymakers consider PE mandates in middle-high school and require linkage of academic and fitness records to facilitate longitudinal surveillance. School administrators should consider increasing PE time in pursuit of higher academic test scores, and PE practitioners should emphasize cardiovascular fitness over BMI reduction.^