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L J Gunning-Schepers

Publications and source records attributed to L J Gunning-Schepers.

45 records · Page 3Linked to original sources
PubMed1994

Age, socioeconomic status, and mortality at the aggregate level.

STUDY OBJECTIVE: Indicators of socioeconomic status are associated with age. This study aimed to analyse the influence of the age distribution on the ranking of small areas by socioeconomic status and on the association between their socioeconomic status and standardised mortality. DESIGN: The ranking of small areas by socioeconomic status indicators (educational level, income, and unemployment) was compared with crude values and after correction for their age structure. The age and gender standardised mortality ratios (SMRs) of these areas for the age group 1-64 years was then rank correlated with both crude and age standardised measures of socioeconomic status. SETTING: This study used data for all (n = 22) boroughs of Amsterdam for the period 1986-91. MAIN RESULTS: Correction of indicators of socioeconomic status for the age structure of the population hardly affects the ranking of Amsterdam boroughs by socioeconomic status. All rank correlations between crude and age standardised socioeconomic status measures are above 0.95. Rank correlations between SMR and these socioeconomic status measures also hardly change after correction for the age structure of boroughs except for education. Mean income per earner is the socioeconomic status indicator most strongly associated with the SMR. CONCLUSIONS: This study shows that the age structure of Amsterdam boroughs has almost no influence on their ranking by socioeconomic status and a limited influence on the association between their socioeconomic status and SMR, except for educational level. The latter indicator has the strongest association with age. This result and theoretical considerations indicate that a correction for the age structure of the population will be more important if small areas differ little with regard to socioeconomic status, if they vary considerably in age structure, or if a given indicator of socioeconomic status shows a strong cohort effect or age association.

Adolescent↗
PubMed1992

Timeless epidemiology or history cannot be ignored.

Epidemiology has produced some useful effect measures, the etiologic fraction and the potential impact fraction, with which the effects of changes in risk factor prevalence on disease specific incidence can be estimated. However to be able to use them for decisions in health policy, adjustments need to be made, in order to incorporate elements that can be avoided in carefully designed epidemiologic studies but cannot be ignored if the results are applied to the "real world". Such necessary adjustments include an approach in which the multi factorial aspects of chronic disease epidemiology and time dimensions can be taken into account. In this article we show the effect of including a time dimension in epidemiologic effect measures. Such a time dimension is important, e.g. to be able to incorporate the effect of a gradual reduction in excess risk following cessation of exposure to a risk factor such as cigarette smoking.

Chronic Disease↗
PubMed1987

Avoidable burden of illness: how much can prevention contribute to health?

The WHO campaign for health for all by the year 2000 brought health back into the centre of attention in health policy making. Different authors have analysed the determinants of health in different models. One of these is the well-known model of Lalonde, in which health is seen as the result of four determinants: human biology, life style, environment and health care. Dever, in the U.S., has tried to quantify this model in order to compare the percentages of mortality attributable to each of the four determinants with the percentage of resources from the health care budget, allocated to them. The authors have, individually, tried to replicate these estimates, through a survey of Dutch experts. The results of these surveys are presented and discussed. The authors conclude that, although a quantification of the relative importance of the determinants of health would be extremely useful in health policy making, the methodology proposed by Dever does not yield suitable results. An alternative approach suggested, would be to subdivide the broad determinants into known risk factors and to arrive at a quantification through the utilization of known epidemiologic relationships between risk factors and disease.

Health Policy↗
PubMed1986

"Health for all by the year 2000": a mere slogan or a workable formula?

In the last decade WHO launched its world-wide Health for All by the Year 2000 (HFA 2000) campaign. This has also been picked up by the WHO European Region and by individual countries within that region. In this context The Netherlands has started up work on a Health 2000 Report. In this article, the work on this report and its underlying model are carefully reviewed in the light of the HFA 2000 strategy, and the HFA 2000 goal is evaluated in the light of the health problems Western European countries are controlled with. The conclusion is that all three main elements of the HFA 2000 strategy are useful for long term health planning efforts in the European Region. Health for All by the Year 2000 is not a mere slogan but has proved to be a workable formula.

Health Planning↗
PubMedDate not supplied

Differences between studies in reported relative risks associated with smoking: an overview.

Reported Relative Risks associated with smoking differ between studies; these differences may reflect true biological differences between populations or may be research artifacts introduced by differences in factors such as amount smoked or smoking duration. The authors reviewed the literature published before June 1992 on relative risks associated with smoking for heart disease, stroke, lung cancer, and chronic obstructive lung disease. They quantified the effect of variables such as age, amount smoked, and smoking duration on reported relative risks. The main reasons for the variation in reported relative risks were: misclassification of former smokers as never smokers, the use of mortality rate ratios rather than incidence rate ratios, a possible period effect suggesting increasing relative risks over time, and differences in the amounts smoked. It is far more likely that these factors are responsible for the observed variation between studies than that the variations reflect true biological differences between populations. Using relative risks from other studies is therefore justified in calculating a population attributable risk if the studies are carefully selected and address factors such as amount smoked and period effects.

Cardiovascular Diseases↗