Biomedical subjects

John Staudenmayer

Publications and source records attributed to John Staudenmayer.

7 recordsLinked to original sources

PubMed2006

Modeling observation error and its effects in a random walk/extinction model.

This paper examines the consequences of observation errors for the "random walk with drift", a model that incorporates density independence and is frequently used in population viability analysis. Exact expressions are given for biases in estimates of the mean, variance and growth parameters under very general models for the observation errors. For other quantities, such as the finite rate of increase, and probabilities about population size in the future we provide and evaluate approximate expressions. These expressions explain the biases induced by observation error without relying exclusively on simulations, and also suggest ways to correct for observation error. A secondary contribution is a careful discussion of observation error models, presented in terms of either log-abundance or abundance. This discussion recognizes that the bias and variance in observation errors may change over time, the result of changing sampling effort or dependence on the underlying population being sampled.

Analysis of Variance↗

PubMed2006

Measurement error in a random walk model with applications to population dynamics.

Population abundances are rarely, if ever, known. Instead, they are estimated with some amount of uncertainty. The resulting measurement error has its consequences on subsequent analyses that model population dynamics and estimate probabilities about abundances at future points in time. This article addresses some outstanding questions on the consequences of measurement error in one such dynamic model, the random walk with drift model, and proposes some new ways to correct for measurement error. We present a broad and realistic class of measurement error models that allows both heteroskedasticity and possible correlation in the measurement errors, and we provide analytical results about the biases of estimators that ignore the measurement error. Our new estimators include both method of moments estimators and "pseudo"-estimators that proceed from both observed estimates of population abundance and estimates of parameters in the measurement error model. We derive the asymptotic properties of our methods and existing methods, and we compare their finite-sample performance with a simulation experiment. We also examine the practical implications of the methods by using them to analyze two existing population dynamics data sets.

Animals↗

PubMed2006

Religious service attendance and decline in pulmonary function in a high-functioning elderly cohort.

BACKGROUND: Pulmonary function is an important indicator of respiratory and overall health, yet little is known about the psychosocial factors that predict pulmonary function itself. At the same time, religious activity is emerging as a potential health promoting factor, especially among the elderly. Whether there is a connection between religious activity and pulmonary function is unknown. PURPOSE: In this study, we sought to examine the association between religious attendance and rate of decline in pulmonary function. METHODS: The sample consisted of 1,174 healthy elderly persons enrolled in the MacArthur Study of Successful Aging who were followed for an average of 4.6 years. Information on frequency of religious service attendance and peak expiratory flow rate (PEFR) was collected over 3 waves. A linear mixed model with repeated measures was used to compare rate of decline in PEFR between those who attended religious services regularly and those who did not. RESULTS: Regular religious service attendance was associated with a slower pulmonary function decline among men (by 3.71 L/min per year, p = .02) and women (by 3.27 L/min per year, p = .02), compared to those who never attend services. The findings could not be explained by differences in smoking or physical activity. CONCLUSIONS: Overall findings support the hypothesis that religious activity may play a protective role in maintaining pulmonary health among the elderly.

Aged↗

PubMed2006

Development of novel techniques to classify physical activity mode using accelerometers.

PURPOSE: Use of accelerometers to assess physical activity (PA) is widespread in public health research, but their utility is often limited by the accuracy of data-processing techniques. We hypothesized that more sophisticated approaches to data processing could distinguish between activity types based on accelerometer data, providing a more accurate picture of PA. METHODS: Using data from MTI Actigraphs worn by six subjects during four activities (walking, walking uphill, vacuuming, working at a computer), quadratic discriminant analysis (QDA) was performed, and a hidden Markov model (HMM) was trained to recognize the activities. The ability of the new analytic techniques to accurately classify PA was assessed. RESULTS: The mean (SE) percentage of time points for which the QDA correctly identified activity mode was 70.9% (1.2%). Computer work was correctly recognized most frequently (mean (SE) percent correct = 100% (0.01%)), followed by vacuuming (67.5% (1.5%)), uphill walking (58.2% (3.5%)), and walking (53.6% (3.3%)). The mean (SE) percentage of time points for which the HMM correctly identified activity mode was 80.8% (0.9%). Vacuuming was correctly recognized most frequently (mean (SE) percent correct = 98.8% (0.05%)), followed by computer work (97.3% (0.7%)), walking (62.6% (2.3%)), and uphill walking (62.5% (2.3%)). In contrast to a traditional method of data processing that misidentified the intensity level of 100% of the time spent vacuuming and walking uphill, the QDA and HMM approaches correctly estimated the intensity of activity 99% of the time. CONCLUSION: The novel approach of estimating activity mode, rather than activity level, may allow for more accurate field-based estimates of physical activity using accelerometer data, and this approach warrants more study in a larger and more diverse population of subjects and activities.

Acceleration↗

PubMed2004

Chronic caregiver stress and IgE expression, allergen-induced proliferation, and cytokine profiles in a birth cohort predisposed to atopy.

BACKGROUND: Psychologic stress modifies immune function and cytokine production. OBJECTIVE: We examined relationships between caregiver stress on the following markers of early childhood immune response: (1) IgE expression (n=215); (2) mitogen-induced and allergen-specific (Dermatophagoides farinae [Der f 1] and cockroach [Bla g 2]) proliferative response (n=114); and (3) subsequent cytokine expression (INF-gamma, TNF-alpha, IL-10, and IL-13) in a prospective birth cohort predisposed to atopy. METHODS: Caregiver stress was measured at 2-month intervals for the first 2 years of life and yearly thereafter by using the Perceived Stress Scale. A subsequent blood sample obtained from the children (median age, 2.1 years; range, 18-32 months) was analyzed for total serum IgE level and allergen-induced proliferation quantified as the stimulation index (SI; mean thymidine incorporation of the stimulated sample divided by that of the unstimulated sample). The relationship between stress and the proliferative response (SI >3 vs SI < or =3), and total IgE level (< or =100 IU/mL vs >100 IU/mL) was examined by using logistic regression. The relationship between cytokine levels and stress was analyzed by using linear regression. RESULTS: In adjusted analyses higher caregiver stress in the first 6 months after birth was associated with a Der f 1 SI of greater than 3 (odds ratio [OR], 1.5; 95% CI, 1.0-2.3) and nominally associated with a Bla g 2 SI of greater than 3 (OR, 1.13; 95% CI, 0.7-1.8). Higher stress between ages 6 and 18 months was associated with a high total IgE level (OR, 2.03; 95% CI, 1.1-3.6). Higher stress was significantly associated with increased production of TNF-alpha, with a suggested trend between higher stress and reduced INF-gamma production. CONCLUSION: Increased stress in early childhood was associated with an atopic immune profile in these children predisposed to atopy-asthma.

Allergens↗

PubMed2002

A study of indoor carbon dioxide levels and sick leave among office workers.

BACKGROUND: A previous observational study detected a strong positive relationship between sick leave absences and carbon dioxide (CO2) concentrations in office buildings in the Boston area. The authors speculated that the observed association was due to a causal effect associated with low dilution ventilation, perhaps increased airborne transmission of respiratory infections. This study was undertaken to explore this association. METHODS: We conducted an intervention study of indoor CO2 levels and sick leave among hourly office workers employed by a large corporation. Outdoor air supply rates were adjusted periodically to increase the range of CO2 concentrations. We recorded indoor CO2 concentrations every 10 minutes and calculated a CO2 concentration differential as a measure of outdoor air supply per person by subtracting the 1-3 a.m. average CO2 concentration from the same-day 9 a.m. - 5 a.m. average concentration. The metric of CO2 differential was used as a surrogate for the concentration of exhaled breath and for potential exposure to human source airborne respiratory pathogens. RESULTS: The weekly mean, workday, CO2 concentration differential ranged from 37 to 250 ppm with a peak CO2 concentration above background of 312 ppm as compared with the American Society of Heating, Refrigeration and Air-conditioning Engineers (ASHRAE) recommended maximum differential of 700 ppm. We determined the frequency of sick leave among 294 hourly workers scheduled to work approximately 49,804.2 days in the study areas using company records. We found no association between sick leave and CO2 differential CONCLUSIONS: The CO2 differential was in the range of very low values, as compared with the ASHRAE recommended maximum differential of 700 ppm. Although no effect was found, this study was unable to test whether higher CO2 differentials may be associated with increased sick leave.

Adult↗

PubMed2002

Segmented regression in the presence of covariate measurement error in main study/validation study designs.

This article considers the problem of segmented regression in the presence of covariate measurement error in main study/validation study designs. First, we derive a closed and interpretable form for the full likelihood. After that, we use the likelihood results to compute the bias of the estimated changepoint in the case when the measurement error is ignored. We find the direction of the bias in the estimated changepoint to be determined by the design distribution of the observed covariates, and the bias can be in either direction. We apply the methodology to data from a nutritional study that investigates the relation between dietary folate and blood serum homocysteine levels and find that the analysis that ignores covariate measurement error would have indicated a much higher minimum daily dietary folate intake requirement than is obtained in the analysis that takes covariate measurement error into account.

Bias↗