233 research outputs found
A Conversation with Monroe Sirken
Born January 11, 1921 in New York City, Monroe Sirken grew up in a suburb of
Pasadena, California. He earned B.A. and M.A. degrees in sociology at UCLA in
1946 and 1947, and a Ph.D. in 1950 in sociology with a minor in mathematics at
the University of Washington in 1950 where Professor Z. W. Birnbaum was his
mentor and thesis advisor. As a Post-Doctoral Fellow of the Social Science
Research Council, Monroe spent 1950--1951 at the Statistics Laboratory,
University of California at Berkeley and the Office of the Assistant Director
for Research, U.S. Bureau of the Census in Suitland, Maryland. Monroe visited
the Census Bureau at a time of great change in the use of sampling and survey
methods, and decided to remain. He began his government career there in 1951 as
a mathematical statistician, and moved to the National Office of Vital
Statistics (NOVS) in 1953 where he was an actuarial mathematician and a
mathematical statistician. He has held a variety of research and administrative
positions at the National Center for Health Statistics (NCHS) and he was the
Associate Director, Research and Methodology and the Director, Office of
Research and Methodology until 1996 when he became a senior research scientist,
the title he currently holds. Aside from administrative responsibilities,
Monroe's major professional interests have been conducting and fostering survey
and statistical research responsive to the needs of federal statistics. His
interest in the design of rare and sensitive population surveys led to the
development of network sampling which improves precision by linking multiple
selection units to the same observation units. His interest in fostering
research on the cognitive aspects of survey methods led to the establishment of
permanent questionnaire design research laboratories, first at NCHS and later
at other federal statistical agencies here and abroad.Comment: Published in at http://dx.doi.org/10.1214/07-STS245 the Statistical
Science (http://www.imstat.org/sts/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Confidence Intervals for Prevalence Estimates from Complex Surveys with Imperfect Assays
We present several related methods for creating confidence intervals to
assess disease prevalence in variety of survey sampling settings. These include
simple random samples with imperfect tests, weighted sampling with perfect
tests, and weighted sampling with imperfect tests, with the first two settings
considered special cases of the third. Our methods use survey results and
measurements of test sensitivity and specificity to construct melded confidence
intervals. We demonstrate that our methods appear to guarantee coverage in
simulated settings, while competing methods are shown to achieve much lower
than nominal coverage. We apply our method to a seroprevalence survey of
SARS-CoV-2 in undiagnosed adults in the United States between May and July
2020.Comment: 45 pages, 35 figure
Data-integration with pseudoweights and survey-calibration: application to developing US-representative lung cancer risk models for use in screening
Accurate cancer risk estimation is crucial to clinical decision-making, such
as identifying high-risk people for screening. However, most existing cancer
risk models incorporate data from epidemiologic studies, which usually cannot
represent the target population. While population-based health surveys are
ideal for making inference to the target population, they typically do not
collect time-to-cancer incidence data. Instead, time-to-cancer specific
mortality is often readily available on surveys via linkage to vital
statistics. We develop calibrated pseudoweighting methods that integrate
individual-level data from a cohort and a survey, and summary statistics of
cancer incidence from national cancer registries. By leveraging
individual-level cancer mortality data in the survey, the proposed methods
impute time-to-cancer incidence for survey sample individuals and use survey
calibration with auxiliary variables of influence functions generated from Cox
regression to improve robustness and efficiency of the inverse-propensity
pseudoweighting method in estimating pure risks. We develop a lung cancer
incidence pure risk model from the Prostate, Lung, Colorectal, and Ovarian
(PLCO) Cancer Screening Trial using our proposed methods by integrating data
from the National Health Interview Survey (NHIS) and cancer registries
Secular Trends in Regional Differences in Nutritional Biomarkers and Self-Reported Dietary Intakes among American Adults: National Health and Nutrition Examination Survey (NHANES) 1988–1994 to 2009–2010
Objective: To understand the contribution of regional differentials in dietary exposures to regional gradients in health, we examined 20-year trends in the association of US census region of residence with nutritional biomarkers and dietary intakes of American adults.
Design: Observational. Setting: The biomarker and 24 h dietary recall data were from the National Health and Nutrition Examination Surveys (NHANES) conducted during 1988–1994 and 1999–2010. The US census region was operationalized as Northeast, Midwest, South and West. Nutritional biomarker outcomes were serum folate, vitamins B6, B12, C, D and E, and carotenoids; dietary outcomes were intakes of nutrients, food groups and eating patterns.
Subjects: US adults, n\u3e8000–40 000 for biomarkers and \u3e43 000 for dietary outcomes.
Results: The interactions of survey time period and region were not significant for the examined biomarker and dietary outcomes, indicating similar secular trends among regions. The main effect of region was significant for all nutritional biomarkers except serum vitamin B6, most dietary micronutrients, food groups and eating patterns (P\u3c0·001). The mean serum folate, vitamins B12, C and E, and all carotenoid (except lycopene) biomarker levels, and intakes of dietary fibre, vitamins A, E, C and B6, folate, K, Ca, Mg and Fe, fruits, vegetables and whole grains, were higher in the West and Northeast regions, relative to the South and Midwest regions.
Conclusions: Overall, the regional gradients in dietary exposure, expressed objectively as biomarkers or as self-reported nutrient and food group intakes, paralleled trajectories reported for health outcomes and were remarkably persistent over time
Away from home meals: associations with biomarkers of chronic disease and dietary intake in American adults, NHANES 2005-2010
Background Away from home (AFH) meals are known to be energy-dense and of poor diet quality. Both direct and indirect exposure (e.g., neighborhood restaurant density) to AFH meals have been implicated as contributors to higher body weight and adverse health outcomes. Objective To examine the association of frequency of eating AFH and fast-food meals with biomarkers of chronic disease and dietary intake. Design This cross-sectional study used frequency of AFH and fast-food meal and biomarker data from the NHANES 2005-2010. Information on weekly frequency of AFH and fast-food meals was collected via questionnaire during the household interview. The metabolic biomarkers examined included BMI, serum cholesterol (total, HDL, and LDL), triglycerides, glycohemoglobin, and fasting glucose (n=8314, age ≥20, NHANES 2007-2010). Biomarkers of dietary exposure included serum concentrations of vitamins A, D, E, C, B-6, B-12, folate, and carotenoids (n=4162; 2005-2006). Multiple linear and logistic regression methods adjusted for complex survey methodology and covariates. Results American adults reported a mean of 3.9 (95% CI 3.7, 4.0) AFH and 1.8 (1.6, 1.9) fast-food meals/week. Over 50% of adults reported ≥3 AFH and \u3e35% reported ≥2 fast-food meals/week. Mean BMI of more frequent AFH or fast-food meal reporters was higher (Ptrend≤0.0004). Serum concentrations of total, LDL, and HDL cholesterol were related inversely with frequency of AFH meals (P\u3c0.05). Frequency of fast-food meals and serum HDL-cholesterol were also related inversely (P=0.0001). Serum concentrations of all examined micronutrients (except vitamin A and lycopene) declined with increasing frequency of AFH meals (P\u3c0.05); women and ≥50 y olds were at higher risk. Conclusions Reporters of frequent AFH and fast-food meals had higher BMI and lower concentrations of HDL cholesterol; but profiles of other biomarkers did not indicate higher metabolic risk. However, the serum concentrations of nutrients with mostly plant foods as sources declined with increasing AFH meal frequency
A population-based study of Kaposi Sarcoma-associated herpesvirus seropositivity in Uganda using principal components analysis
BACKGROUND: Kaposi sarcoma-associated herpesvirus (KSHV) seropositivity is associated with sexual, environmental, and socioeconomic exposures. Whether these characteristics are independent risk factors is uncertain because of reliance on selected high-risk or hospital-based populations and incomplete adjustment for confounding. Therefore, we evaluated risk factors for KSHV seropositivity in a population-based study in Uganda using principal components analysis (PCA). METHODS: The study population comprised 2,681 individuals randomly selected from a nationally-representative population-based HIV/AIDS sero-behavioral survey conducted in 2004/05. Questionnaire and laboratory data (97 variables) were transformed into a smaller set of uncorrelated variables using PCA. Multivariable logistic regression models were fitted to estimate odds ratios and 95% confidence intervals for the association between components and KSHV seropositivity. RESULTS: Data were reduced to three principal components (PCs) labeled as Sexual behavioral, Socioeconomic, and Knowledge PCs. In crude analysis, KSHV seropositivity was associated with the Knowledge (p(trend) = 0.012) and Socioeconomic components (p(trend) = 0.0001), but not with the Sexual-behavioral component (p(trend) = 0.066). KSHV seropositivity was associated with the Socioeconomic PC (p(trend) = 0.037), but not with the Sexual-behavioral and Knowledge PCs, in the models including PCs, age, gender and geographic region. CONCLUSIONS: Our results fit with the view that in Uganda socioeconomic characteristic may influence KSHV seropositivity. Conversely, the results fit with the interpretation that in Uganda sexual-behavioral characteristics, if relevant, contribute minimally
A population-based study of Kaposi Sarcoma-associated herpesvirus seropositivity in Uganda using principal components analysis
Abstract
Background
Kaposi sarcoma-associated herpesvirus (KSHV) seropositivity is associated with sexual, environmental, and socioeconomic exposures. Whether these characteristics are independent risk factors is uncertain because of reliance on selected high-risk or hospital-based populations and incomplete adjustment for confounding. Therefore, we evaluated risk factors for KSHV seropositivity in a population-based study in Uganda using principal components analysis (PCA).
Methods
The study population comprised 2,681 individuals randomly selected from a nationally-representative population-based HIV/AIDS sero-behavioral survey conducted in 2004/05. Questionnaire and laboratory data (97 variables) were transformed into a smaller set of uncorrelated variables using PCA. Multivariable logistic regression models were fitted to estimate odds ratios and 95% confidence intervals for the association between components and KSHV seropositivity.
Results
Data were reduced to three principal components (PCs) labeled as Sexual behavioral, Socioeconomic, and Knowledge PCs. In crude analysis, KSHV seropositivity was associated with the Knowledge (p
trend
 = 0.012) and Socioeconomic components (p
trend
 = 0.0001), but not with the Sexual-behavioral component (p
trend
 = 0.066). KSHV seropositivity was associated with the Socioeconomic PC (p
trend
 = 0.037), but not with the Sexual-behavioral and Knowledge PCs, in the models including PCs, age, gender and geographic region.
Conclusions
Our results fit with the view that in Uganda socioeconomic characteristic may influence KSHV seropositivity. Conversely, the results fit with the interpretation that in Uganda sexual-behavioral characteristics, if relevant, contribute minimally.http://deepblue.lib.umich.edu/bitstream/2027.42/112399/1/13027_2012_Article_423.pd
Male Pattern Baldness in Relation to Prostate Cancer–Specific Mortality: A Prospective Analysis in the NHANES I Epidemiologic Follow-up Study
We used male pattern baldness as a proxy for long-term androgen exposure and investigated the association of dermatologist-assessed hair loss with prostate cancer–specific mortality in the first National Health and Nutrition Examination Survey Epidemiologic Follow-up Study. From the baseline survey (1971–1974), we included 4,316 men who were 25–74 years of age and had no prior cancer diagnosis. We estimated hazard ratios and used Cox proportional hazards regressions with age as the time metric and baseline hazard stratified by baseline age. A hybrid framework was used to account for stratification and clustering of the sample design, with adjustment for the variables used to calculate sample weights. During follow-up (median, 21 years), 3,284 deaths occurred; prostate cancer was the underlying cause of 107. In multivariable models, compared with no balding, any baldness was associated with a 56% higher risk of fatal prostate cancer (hazard ratio = 1.56; 95% confidence interval: 1.02, 2.37), and moderate balding specifically was associated with an 83% higher risk (hazard ratio = 1.83; 95% confidence interval: 1.15, 2.92). Conversely, patterned hair loss was not statistically significantly associated with all-cause mortality. Our analysis suggests that patterned hair loss is associated with a higher risk of fatal prostate cancer and supports the hypothesis of overlapping pathophysiological mechanisms
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