Biomedical subjects

L A Waller

Publications and source records attributed to L A Waller.

13 recordsLinked to original sources

PubMed1999

Work-related assault injuries among nurses.

Work-related violence is a major public health problem; however, there is a serious deficiency in the knowledge of risk factors for this problem. The purpose of this case-control study was to identify risk factors for work-related assault injuries among nurses. We used unconditional logistic regression to model the dependence of work-related assault injuries on each exposure of interest and the respective confounders. We found a decreased rate for the presence of security personnel (RR = 0.40; 95% CI = 0.19-0.82). We found increased rates for the following factors: the perception that administrators considered assault to be part of the job (RR = 8.14; 95% CI = 3.76-17.60); having received assault prevention training in the current workplace (RR = 4.64; 95% CI = 2.33-9.23); a high (>5) vs. low (<2) patient/personnel ratio (RR = 2.54; 95% CI = 1.13-5.70); working predominantly with patients with mental illness (RR = 3.5; 95% CI = 1.41-8.85); and working with patients who had more than 1- to 4-week and more than 4-week lengths of stay in the institution vs. <1 day (RR = 8.85; 95% CI = 1.58-49.52 and 4.25; 95% CI = 1.17-15.39, respectively).

Adult↗

PubMed1998

Clinical detection of depression among community-based elderly people with self-reported symptoms of depression.

BACKGROUND: Depression is under-diagnosed and under-treated in the primary care sector. The purpose of this study was to determine the association between self-reported indications of depression by community-dwelling elderly enrollees in a managed care organization and clinical detection of depression by primary care clinicians. METHODS: This was a 2-year cohort study of elderly people (n = 3410) who responded to the Geriatric Depression Scale (GDS) at the midpoint of the study period. A broad measure of clinical detection was used consisting of one or more of three indicators: diagnosis of depression, visit to a mental health specialist, or antidepressant medication treatment. RESULTS: Approximately half of the community-based elderly people with self-reported indications of depression (GDS > or = 11) did not have documentation of clinical detection of depression by health providers. Physician recognition of depression tended to increase with the severity of enrollees' self-reported feelings of depression. Men 65-74 years old and those > or = 85 years old were at highest risk for under-detection of depression by primary care providers. CONCLUSIONS: Clinical detection of depression of elderly people living in the community continues to be a problem. The implications of failure to recognize the possibility of depression among elderly White men suggest a serious public health problem.

Aged↗

PubMed1998

Discrete distributions for use in twin studies.

We describe several new discrete distributions motivated by the study of longevity in twins. All individuals both living and dead at a given age are randomly paired. The univariate distribution models the number of these pairs where both individuals are alive. If there is a positive association to longevity in twins, then we would expect to see an excessive number of twin pairs both alive at older ages relative to the number of living individuals. We obtain Poisson and normal approximations to the exact distribution. Multivariate distributions are developed to allow for simultaneous and conditional inference at different ages. Odds-ratio parameter models provide a measure of the association of longevity within twin pairs. These models indicate an excessive number of identical twin pairs both alive after age 60 in a cohort of twins born between 1870 and 1880 in Denmark. Monozygotic twins are contrasted with dizygotic twins to separate the genetic and environmental contributions to the similarity in longevity among twins.

Adult↗

PubMed1997

A note on Harold S. Diehl, randomization, and clinical trials.

Harold S. Diehl and coworkers published results from a remarkable trial on the efficacy of vaccines for the common cold in 1938. The original report states that patients were assigned to treatment and control groups "at random." Diehl's study has been referred to as one of the first instances of a randomized, double-blind, placebo-controlled trial. No description of a formal randomization scheme is given in the 1938 report and an unpublished paper of Diehl's suggests the use of alternate assignment in the study.

Common Cold↗

PubMed1997

Log-linear modeling with the negative multinomial distribution.

We develop a negative multinomial sampling plan in which observed cell counts are positively correlated. We show that maximum likelihood estimates of cell means are the same as those found under independent Poisson sampling. There is no maximum likelihood estimate for the shape parameter in general. We propose an estimate of the shape parameter based on the mean and quantiles of Pearson's chi-squared statistic. These techniques are applied to models of cancer incidence for three cities in Ohio and longitudinal health care utilization by a group of senior citizens.

Aged↗

PubMed1996

The analysis of disease clusters, Part I: State of the art.

Public health professionals often are asked to investigate apparent clusters of human health events, or "disease clusters." A cluster is an excess of cases in space (a geographic cluster), in time (a temporal cluster), or in both space and time. This is part I of an introductory-level review of the analysis of disease clusters for physicians and health professionals concerned with infection surveillance in hospitals. It reviews the status of the field with the hope of expanding the use of cluster analysis methods for the routine surveillance of infectious disease in the hospital environment.

Algorithms↗

PubMed1996

The analysis of disease clusters, Part II: Introduction to techniques.

Public health professionals often are asked to investigate apparent clusters of human health events or "disease clusters." A cluster is an excess of cases in space (a geographic cluster), in time (a temporal cluster), or in both space and time. This is the second part of an introductory-level review of the analysis of disease clusters for physicians and health professionals concerned with infection surveillance in hospitals. It reviews the status of the field with the hope of expanding the use of cluster analysis methods for the routine surveillance of infectious diseases in the hospital environment.

Cluster Analysis↗

PubMed1995

Detection and assessment of clusters of disease: an application to nuclear power plant facilities and childhood leukaemia in Sweden.

We review some recent statistical methods for examining geographic patterns of disease incidence for the presence of clusters. General methods search for clusters throughout the study area and then assess the statistical significance of any clusters detected. Focused methods check for elevated incidence rates close to prespecified locations of putative sources of hazard. We apply the methods to leukaemia incidence data for children aged 0-15 years in Sweden (1980-1990), particularly in reference to locations of nuclear power facilities. Unlike some other studies, notably in the United Kingdom, we do not find any significant clusters.

Adolescent↗

PubMed1995

Disease models implicit in statistical tests of disease clustering.

State and local health departments investigate an increasing number of cluster allegations, for which the selection of appropriate statistical methods is an important problem. Many of the methods for the spatial analysis of health data assume, either implicitly or explicitly, some model of disease occurrence, and comparisons of methods can be difficult when their underlying disease models differ. We review some of the issues involved in the statistical analysis of spatial disease patterns and describe several methods recently proposed to detect areas of increased disease rates. The disease models upon which the methods are based are explicitly described, and they provide a useful basis for comparing alternative clustering methods.

Cluster Analysis↗

PubMed1993

The effects of scale on tests for disease clustering.

Surveillance of a large geographic region for 'clusters' of adverse health events, particularly cancers, often involves searching for raised incidence in the vicinity of prespecified putative sources of hazard. For reasons of practicality or of confidentiality, incidence and population data are usually only available aggregated over subregions or 'cells'. The performance of statistical procedures designed to detect the presence of clusters can be highly sensitive to the level of aggregation, that is to the choice of partition of the region into the cells. We investigate this sensitivity in the cases of three recently proposed procedures, namely those of Besag and Newell, Stone, and Waller et al. For illustration, we use leukaemia incidence data for 1978-82 in a region of upstate New York, with inactive hazardous waste sites containing trichloroethylene acting as suspected sources.

Cluster Analysis↗

PubMedDate not supplied

Statistical power and design of focused clustering studies.

Focused clustering studies investigate raised incidence of disease in the vicinity of prespecified putative sources of increased risk. The analytic power functions of three focused tests of disease clustering are defined and used to address two design issues related to focused cluster studies. The power functions provide sample sizes required to detect a given increase in relative risk and allow measurement of the effects of aggregating data when a fixed underlying cluster model is assumed. Results are illustrated on hypothetical data as well as leukaemia data from upstate New York.

Cluster Analysis↗

PubMedDate not supplied

The power of focused tests to detect disease clustering.

Statistical tests have been proposed for determining whether incident cases of adverse health effects are 'clustered' together. Several procedures, termed 'focused', specifically analyse disease surveillance data around pre-specified putative sources of environmental hazard. Little has been done to compare the performance of various proposed methods on actual models of clustering. Analytic power functions are derived for three tests of focused clustering. These functions are based on the probabilistic structure of the clustering tests and do not require simulation. The three tests are compared with respect to statistical power on hypothetical data where monotone multiplicative increases in disease risk near a putative hazard define disease clusters of varying intensity.

Cluster Analysis↗

PubMedDate not supplied

Environmental justice and statistical summaries of differences in exposure distributions.

Recent regulatory action requires the assessment of environmental justice (equitable protection from the burdens of environmental hazards across sociodemographic subpopulations) in the siting of hazardous waste sites, and prioritization of environmental remediation efforts. Assessments of environmental justice require linking exposure, demographic, and health data. The geographic nature of the data makes the use of geographic information systems attractive for environmental justice assessments. Typical geographic assessments compare the composition of 'exposed' populations, while typical statistical assessments focus on differences in health outcomes between population subgroups, possibly adjusted for exposure. We outline an alternate approach based on summarized differences between exposure distributions within each population subgroup. We illustrate how such summaries provide a tool for site evaluation (e.g., defining exposure inequities resulting from locating a new potential hazard at any of a number of possible sites). In addition, we describe summaries, based on dose-response relationships, to describe risk differences imposed by the observed exposure differences. Reported toxic emissions from Allegheny County, Pennsylvania illustrate the approach.

Bayes Theorem↗