The Use of Measures of Influence in Epidemiology

Helfenstein U (Biostatistical Centre for the Medical Department, University of Zurich, Plattenstrasse 54, CH-8032, Zurich, Switzerland) and Minder C. International Journal of Epidemiology 1990, 19: 197-204. In epidemiological studies the units of observation often consist of political entities such as countries, each of which has its own specific inner structure. When a multiple regression is performed it is therefore of particular interest to ana-lyse not only the overall behaviour of the dataset, but in addition, to investigate how each individual country contributes to, and deviates from, this overall behaviour. By means of the example ‘relation between infant mortality and structural data of countries' several ways are discussed of how each individual country can influence the regression model. Firstly the potential influonco which each country might exhibit due to the explanatory variables alone is analysed. Then the actual influence of each country is analysed by taking the explanatory variables and the target variable into account simultaneously. This is done by means of statistical measures not generally familiar to epidemiologists, which have been developed in recent years (leverage values, Cook's distances). These measures also point to deviations of countries from the model, and suggest directions in which to search for explanation. Finally the influence of the ‘size' of the countries is investigate

Beeinflusst die medizinische Versorgungsstruktur den Anteil Todesfälle im Spital?: Eine ökologische Analyse in den MS-Regionen der Schweiz

Summary: Objectives: With the discussion about measures to reduce over-capacities in the health services in mind, we examined the influence of medical supply structures and services on hospital utillisation directly before death. Methods: Based on the specification of the place of dying from the death certificates, we determined the proportions of deaths in hospitals in an ecological study. We analysed deaths of persons above age 65 in each of the 106 mobility regions of Switzerland in the years 1979 to 1980. Results: The proportion of deaths occuring in hospitals varied between 27% and 81%. Despite missing data regarding stationary and ambulatory care services, more than half of the variance could be explained by means of a multivariate regression analysis. Our results imply an inverse relation between the proportion of deaths in the hospital and the number of consultations provided by primary care physicians, as well as the number of nursing home beds. Further, we observe a direct relation to the number of hospital beds in a region. All indicators are calculated per inhabitant. Conclusions: In health care supply planning, such systematic associations should be taken into account. We recommend to analyse regularly interregional differences in supply and outcome of medical performances with the best available dat

Drogenkonsumenten als benachteiligte Gruppe: die Entwicklung ihrer sozialen und gesundheitlichen Situation in der Schweiz

In der Schweiz sind schätzungsweise 30'000 Personen von Heroin abhängig. Viele von ihnen leben in prekären gesundheitlichen, sozialen und wirtschaftlichen Verhältnissen, gehören also einer benachteiligten Gruppe an. Krankheiten, aber auch soziale Probleme sind in dieser Gruppe gehäuft. Ihre wichtigsten Gesundheitsprobleme betreffen HIV/AIDS, Hepatitis und eine allgemein stark erhöhte Sterblichkeit. Ziel dieser Arbeit ist es, die Veränderungen der gesundheitlichen und sozialen Situation der Drogenkonsumenten zu beschreiben, wie sie durch die Entwicklungen auf den Ebenen der Politik, des Rechts und des Gesundheitswesens in der Schweiz in den letzten Jahren beeinflussi wurden. Ein Schwerpunkt sind die Ergebnisse der Studien mit ärztlich kontrollierter Heroinverschreibung. Die Arbeit fasst die aktuelle Literatur und Information zum Thema zusamme

Mortality by education in German speaking Switzerland, 1990-1997: results from the Swiss National Cohort

Background The aim of this paper is to show for the first time mortality differentials by level of education for Swiss men and women. This work is of interest to public health efforts in Switzerland as well as for co-operative international research into the determinants of socioeconomic differentials in health and mortality. Methods This study is based on a longitudinal data set from the Swiss National Cohort, currently incorporating a probabilistic record linkage of the 1990 Swiss census, and all subsequent deaths until the end of 1997. The study population covers all Swiss nationals aged ≥25 years living in German speaking Switzerland, with 19.7 million person-years and 296 929 deaths observed. Educational gradients were analysed using standardized mortality ratios, multiple logistic regression, and the Relative Index of Inequality (RII). Results There were sizeable gradients in mortality by education for all age groups and both sexes. The mortality odds ratio decreased by 7.2% (95% CI: 7.0-7.5%) per additional year of education for men, and by 6.0% (95% CI: 5.6-6.3%) for women. In men, we found a steady decrease of the gradient from 13.1% (95% CI: 11.9-14.4%) in the age group 25-39 to 4.5% (95% CI: 4.0-5.0%) in the age group ≥75 years. For women in the age groups under 65 the gradients were smaller; over the age of 40 there was no decrease with increasing age. These results were fairly insensitive to variations in the parameters of record linkage. Conclusions Despite a comparatively low overall mortality, Swiss men in the 1990s show larger relative gradients in mortality by education than men in other European countries in the 1980s, with the possible exception of younger men in Italy. In Switzerland there is a sizeable potential for further increasing overall life expectancy by reducing the mortality of those with a lower educational level. The results presented contribute to a reliable assessment of socioeconomic mortality differentials in Europ

Clarifying gender interactions in multivariate analysis

Summary: Objectives: To examine a linear regression model to predict physical fitness using an alternative concept to analyse gender interactions. Methods: Data were obtained from the Berne Lifestyle Panel, a survey on health and lifestyles of 56-66 years old Bernese citizens. A measure of physical fitness was regressed on gender, education and their interaction as central explanatory variables and age as confounding factor. For ease of interpretation, two dummy variables of education are introduced, one for female, the other for male education. The model with education dummy variables is compared to a linear regression model without interaction stratified by gender, and with a model with the multiplicative gender-education interaction term without stratification. Results: The use of dummy variables ensures an accurate description of both women's and men's associations of education with the dependant variable, without losing any explanatory power due to stratification. Conclusion: The results show that the use of dummy variables is a rewarding alternative to stratification and conventional gender interaction analysis, providing both sufficient statistical information and a basis for straightforward interpretatio

A simple approach to fairer hospital benchmarking using patient experience data

Objective To determine the factors contributing most to variability in patient experience in order to present approaches for fairer benchmarking of hospitals and for quality improvement. Design Secondary analysis of data from a widely used survey on patient experience. Setting Inpatients from all 24 acute hospitals in the Canton of Bern in Switzerland. Data collection followed the standardized and validated Picker Institute methodology for a period of 13 weeks in the fall/winter of 2005. Participants Inpatients age 18 years and older (n = 14 089), discharged within the sampling period. Main outcome measures ‘Patient experience', measured by the total Picker Problem Score (PPS) and by six domain scores (care, communication, respect, cooperation, organization, discharge management). Results In regression analysis, the patient factors self-reported health, age and education explained the highest proportion of variability in the PPS (4.8, 2.2 and 0.7%, respectively). Multiple linear adjustment for factors associated with patients removed between 29 and 33% of variability between hospital categories. The domain score means varied from under 5% for ‘respect towards the patient' to 34% for ‘discharge management'. Ranking of hospitals by domain scores differed from the ranking based on the total PPS. Conclusions Statistical adjustment for patient mix and additional stratification for some hospital factors make benchmarking using patient survey data fairer and more transparent. Use of our approach for presenting quality data may make interpretation easier for the different target groups and may enhance the relevance of such information for decision-makin

The use of measures of influence in epidemiology

In epidemiological studies the units of observation often consist of political entities such as countries, each of which has its own specific inner structure. When a multiple regression is performed it is therefore of particular interest to analyse not only the overall behaviour of the dataset, but in addition, to investigate how each individual country contributes to, and deviates from, this overall behaviour. By means of the example 'relation between infant mortality and structural data of countries' several ways are discussed of how each individual country can influence the regression model. Firstly the potential influence which each country might exhibit due to the explanatory variables alone is analysed. Then the actual influence of each country is analysed by taking the explanatory variables and the target variable into account simultaneously. This is done by means of statistical measures not generally familiar to epidemiologists, which have been developed in recent years (leverage values, Cook's distances). These measures also point to deviations of countries from the model, and suggest directions in which to search for explanation. Finally the influence of the 'size' of the countries is investigated

Risk of Infectious Complications in Patients Taking Glucocorticosteroids

The association between corticosteroid therapy and subsequent infections was calculated by pooling data from 71 controlled clinical trials. The overall rate of infectious complications was 12.7% in the 2,111 patients randomly allocated to systemic corticosteroids and 8.0% in the 2,087 controls (relative risk [RR], 1.6; 95% confidence interval [CI], 1.3-1.9; P 1; P = .03) diseases. The rate was not increased in patients given a daily dose of <10 mg or a cumulative dose of <700 mg of prednisone. With increasing doses the rate of occurrence of infectious complications increased in patients given corticosteroids as well as in patients given placebo, a finding suggesting that not only the corticosteroid but also the underlying disease state account for the steroid-associated infectious complications observed in clinical practic