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K Stronks

Publications and source records attributed to K Stronks.

30 records · Page 2Linked to original sources
PubMed1997

Who should decide? Qualitative analysis of panel data from public, patients, healthcare professionals, and insurers on priorities in health care.

OBJECTIVE: To explore the arguments underlying the choices of patients, the public, general practitioners, specialists, and health insurers regarding priorities in health care. DESIGN: A qualitative analysis of data gathered in a series of panels. Members were asked to economise on the publicly funded healthcare budget, exemplified by 10 services. RESULTS: From a medical point of view, both panels of healthcare professionals thought most services were necessary. The general practitioners tried to achieve the budget cuts by limiting access to services to those most in need of them or those who cannot afford to pay for them. The specialists emphasised the possibilities of reducing costs by increasing the efficiency within services and preventing inappropriate utilisation. The patients mainly economised by limiting universal access to preventive and acute services. The "public" panels excluded services that are relatively inexpensive for individual patients. Moreover, they emphasised the individual's own responsibility for health behaviour and the costs of health care, resulting in the choice for copayments. The health insurers emphasised the importance of including services that relate to a risk only, as well as feasibility aspects. CONCLUSIONS: There were substantial differences in the way the different groups approached the issue of what should be included in the basic package. Healthcare professionals seem to be most aware of the importance of maintaining equal access for everyone in need of health care.

Attitude of Health Personnel↗
PubMed1997

The interrelationship between income, health and employment status.

BACKGROUND: The aim of the study was to test the hypothesis that the relatively strong association between income and health compared to that between education/occupation and health, can partly be interpreted in terms of an association between employment status and health. METHODS: Health indicators used were the prevalence of one or more chronic conditions, and perceived general health. Data were generated from a postal survey, part of the baseline data collection of a Dutch prospective cohort study on socioeconomic inequalities in health. RESULTS: After controlling for differences in other socioeconomic indicators, the association between income and health was found to be stronger than that between occupation or education and health. Most of the difference in strength was found to be due to employment status, especially among men. Controlling for employment status, and controlling for the distribution of those with a long-term work disability in particular, reduced the risks of lower income groups, whereas the risks of lower educational and occupational groups hardly changed. CONCLUSIONS: These results suggest that the relatively strong association between income and health can for a large part be interpreted in terms of an interrelationship between employment status, income and health. More specifically, it is largely due to the concentration of the long-term disabled in lower income groups. This indicates the importance of the selection mechanism, as these groups are excluded from paid employment because of their health status, leading to a lowering of income. However, income was still found to be related to perceived general health after controlling for employment status especially among women. This suggests that an explanation in terms of an effect of material factors on health may also be important.

Adult↗
PubMed1995

Smaller socioeconomic inequalities in health among women: the role of employment status.

BACKGROUND: Socioeconomic inequalities in health are smaller among women than among men. In this paper, it is hypothesized that this is due to a gender difference in employment status. METHODS: We used data from the baseline of a Dutch longitudinal study. The socioeconomic indicators were educational level of the respondent and occupational level of the main breadwinner. Logistic regression was used to assess the size of socioeconomic inequalities in the prevalence of chronic conditions and less than 'good' perceived general health. RESULTS: The smaller socioeconomic inequalities in health among women were partly due to a less pronounced concentration among women than among men of relatively unhealthy employment status categories (unemployed, long-term work-disabled) in lower socioeconomic groups. The smaller inequalities in perceived general health among women could also partly be explained by the smaller overall size of the group of unemployed/long-term disabled/early retired among women than among men, a group which is characterized by relatively large inequalities in health. CONCLUSION: These findings suggest that in the Netherlands the low proportion of women in paid employment, and thereby the low proportion of the unemployed/long-term disabled/early retired, explains part of the smaller socioeconomic inequalities in health among women. The more pronounced concentration of those with a long-term work disability in lower socioeconomic groups among men, also points at the importance of working conditions for the gender difference in the size of socioeconomic inequalities in health.

Adult↗
PubMed1995

Health behaviours explain part of the differences in self reported health associated with partner/marital status in The Netherlands.

STUDY OBJECTIVE: To describe the differences in health behaviours in disparate marital status groups and to estimate the extent to which these can explain differences in health associated with marital status. DESIGN: Baseline data of a prospective cohort study were used. Directly age standardised percentages of each marital group that engaged in each of the following behaviours--smoking, alcohol consumption, coffee consumption, breakfast, leisure exercise, and body mass index--were computed. Multiple logistic regression models were fitted to estimate the health differences associated with marital status with and without control for differences in health behaviours. SETTING: The population of the city of Eindhoven and surrounding municipalities (mixed urban-rural area) in The Netherlands in March 1991. PARTICIPANTS: There were 16,311 men and women, aged 25-74 years, and of Dutch nationality. MAIN RESULTS: There were differences in relation to marital status for each health behaviour. Married people were more likely to practise positive health behaviours (such as exercise and eating breakfast) and less likely to engage in negative ones (such as smoking or drinking heavily) than the other groups. Control for all six health behaviours could explain an average of 20-36% of the differences in perceived and general health and subjective health complaints. CONCLUSIONS: Differences in health behaviours explained a considerable amount, but not all, of the health differences related to marital status. Longitudinal data are necessary to confirm these findings; to determine whether the differences in health behaviours related to marital status are caused by selection effects or social causation effects; and to learn how social control, social support, and stress inter-relate to reinforce negative or to maintain positive health behaviours.

Adult↗
PubMed1994

Validation of cancer prevalence data from a postal survey by comparison with cancer registry records.

Data on self-reported cancer from a health interview survey carried out in 1991 in the southeastern Netherlands by means of a postal questionnaire (n = 17,940) were validated against records from a population-based cancer registry. The sensitivity of the questionnaire was 0.552 (95% confidence interval (CI) 0.507-0.597), and the specificity was 0.995 (95% CI 0.994-0.996). The survey underestimated cancer prevalence in the population by 25%. Of the 212 false negative cases, 46% were registered with non-melanoma skin cancer. After the exclusion of nonmelanoma skin cancer from cancer registry records, cancer prevalence was overestimated by the survey by a negligible 2%. The misclassification of cancer by the postal survey was differential according to age, sex, education, and degree of urbanization. The survey overestimated cancer prevalence ratios for men versus women, old respondents versus young respondents, and urban residents versus rural residents. The prevalence ratios for respondents with a low educational level versus those with a high level were underestimated using survey data. These patterns remained essentially the same after exclusion of nonmelanoma skin cancer from the cancer registry records. This study shows that both overall cancer prevalence and differences in cancer prevalence between subgroups of the population may be biased when health interview survey data are used. If explicit attention is paid to nonmelanoma skin cancer in survey questions, this might improve the validity of overall cancer prevalence estimates, but not that of comparisons between subgroups of the population.

Adolescent↗
PubMed1994

A prospective cohort study investigating the explanation of socio-economic inequalities in health in The Netherlands.

In this paper, the objectives, design, data-collection procedures and enrollment rates of the Longitudinal Study on Socio-Economic Health Differences (LS-SEHD) are described. This study started in 1991, and is the first large-scale longitudinal study of the explanation of socio-economic inequalities in health in the Netherlands. The LS-SEHD aims at making a quantitative assessment of the contribution of different mechanisms and factors to the explanation of socio-economic inequalities in health. It is based on a research model incorporating both 'selection' and 'causation' mechanisms, and a wide range of specific factors possibly involved in these mechanisms: health-related life-style factors, structural/environmental factors, psychosocial stress-related factors, childhood environment, cultural factors, psychological factors, and health in childhood. The design of the LS-SEHD is that of a prospective cohort study. An aselect sample, stratified by age, degree of urbanization and socio-economic status, for approx. 27,000 persons was drawn from the population registers in a region in the Southeastern part of The Netherlands. The persons in this sample received a postal questionnaire. An aselect subsample of approx. 3500 persons from the respondents to the postal questionnaire was, in addition, approached for an oral interview. The follow-up of these samples will use routinely collected data (mortality by cause of death, hospital admissions by diagnosis, cancer incidence), as well as repeated postal questionnaires and oral interviews. The response rate to the base-line postal questionnaire was 70.1% (n = 18,973), and that to the base-line oral interview was 79.4% (n = 2802). If the LS-SEHD is compared to a number of frequently cited longitudinal studies of socio-economic inequalities in health from the United Kingdom, it appears that the differences with the OPCS Longitudinal Study and the birth cohort studies (such as the National Survey of Health and Development) are huge. The LS-SEHD is more akin to the Whitehall(I)-study and the West of Scotland 20-07 study. For example it has the sample size of the former but the open population and emphasis on social factors of the latter. A comparison of the results of various longitudinal studies of socio-economic inequalities in health is recommended.

Adolescent↗
PubMed1994

Differences in self-reported morbidity by marital status and by living arrangement.

It has frequently been shown that the never married, divorced and widowed have higher rates of self-reported morbidity than married people. The purpose of this study was to assess to what extent morbidity differences by marital status can be explained by differences in living arrangement (i.e. living with a partner or not). If living arrangement plays a major role, one expects to find that: 1. people who live with a partner have lower morbidity rates than those who live alone; 2. morbidity differences by marital status decrease substantially after controlling for living arrangement. Data from the GLOBE study, a large prospective cohort in the Netherlands, on 18,973 people from Eindhoven and its surroundings, aged 15-74, were used to test the hypotheses. The measures for morbidity were perceived general health, subjective health complaints, chronic conditions and work disability. Multiple logistic regression models were used to calculate odds ratios for morbidity by living arrangement (question 1) and for morbidity by marital status, firstly without control and subsequently with control for living arrangement (question 2). In all models we controlled for other sociodemographic variables (age, sex, educational level, degree of urbanization, religion and country of birth). Our analyses showed that people who live with a partner have lower morbidity rates than those who live alone. They further showed that the excess risks of the never married, widowed and divorced decreased by 40-70% for all health measures (except subjective health complaints) after controlling for living arrangement.(ABSTRACT TRUNCATED AT 250 WORDS)

Adolescent↗
PubMed1994

The determinants of excellent health: different from the determinants of ill-health?

BACKGROUND: In the famous definition of the World Health Organization, health is 'a state of complete physical, mental and social well-being, not merely the absence of disease or infirmity'. Until now, the distribution and determinants of the positive end of the health spectrum have not been studied extensively. In an exploratory analysis, we have compared the determinants of excellent health and of ill-health using data from a postal survey among 18,973 people in a region in the southeastern Netherlands. METHODS: Excellent health was defined as the presence of a very good self-assessment of health in the absence of any self-reported chronic condition or health complaint, and was present in 8.2% of the survey population. Ill-health was defined as the presence of two or more self-reported chronic conditions, four or more health complaints and a less-than-good self-assessment of health, and was present in 10.5% of the survey population. The remainder of the survey population was used as a reference group. Two sets of explanatory variables were available: a set of seven socio-demographic variables and a set of nine specific risk factors. Logistic regression analysis was used to assess the strengths and patterns of the associations between the determinants and the two outcome variables, excellent health and ill-health, controlling for age and gender. RESULTS: Both the socio-demographic variables and the specific risk factors had largely similar (but mirrored) patterns of association with excellent health and with ill-health. Important socio-demographic determinants of excellent health (and of ill-health) were education, employment status and urbanization (as well as age and gender). Important specific risk factors were leisure exercise, housing problems, smoking, negative life events, obesity and alcohol intake. The percentage of deviance accounted for by each of these sets of determinants was two to three times as large in the case of ill-health as in the case of excellent health. CONCLUSION: The processes by which excellent health is generated probably have much in common with those which generate ill-health. At the same time it is obvious that our understanding of the determinants of ill-health is better than that of the determinants of excellent health, and further study of the latter is recommended.

Adolescent↗
PubMed1989

The contribution of medical care to inequalities in health: differences between socio-economic groups in decline of mortality from conditions amenable to medical intervention.

In order to investigate the contribution of medical care to the widening of mortality differences between socio-economic groups, we studied differences in the decline of mortality from conditions which have become amenable to medical intervention. For England and Wales, data on occupational mortality from the Decennial Supplements of the years around 1931, 1961 and 1981 were used. For the Netherlands, a more indirect approach had to be followed, using data on geographical variation in mortality for the years around 1952, 1962, 1972 and 1982. In England and Wales during the period 1931-1961 mortality from conditions which became amenable to medical intervention generally declined more in relative terms among the higher occupational classes, both for men and for married women. During the period 1961-1981 the picture was less consistent, although for about half of the conditions mortality declines were again larger in the higher occupational classes. The findings for the Netherlands suggest a similar pattern of differential mortality decline for a small number of conditions only. Possible explanations for these findings are discussed. We conclude that: the widening of the mortality differences between socio-economic groups in England and Wales was partly due to differences in decline of mortality from conditions amenable to medical intervention; the same may be true to some extent for the Netherlands, but the evidence is not striking; differences in decline of mortality from 'amenable' conditions were probably due, at least in part and at least up to 1960, to differences between socio-economic groups in accessibility, utilization or quality of medical care.(ABSTRACT TRUNCATED AT 250 WORDS)

Delivery of Health Care↗
PubMedDate not supplied

Cultural, material, and psychosocial correlates of the socioeconomic gradient in smoking behavior among adults.

BACKGROUND: The aim was to identify the correlates of educational differences in smoking among adults. METHODS: We used data from the baseline of a Dutch longitudinal study, relating to a population of 2,462 respondents, ages 25-74. Logistic regression was used to assess the educational gradient in smoking. Current smokers were compared with former and never smokers, respectively. RESULTS: The risk of being a current smoker compared with being a former/never smoker was higher among lower educational groups. For example, the odds of being a current smoker compared with never smoker among persons in the lowest level was more than five times as high as that for persons in the highest level. A substantial part (20-40%) of the increased risk of being a smoker among lower groups appeared to be associated with adverse material conditions. The financial situation especially accounted for that effect. One of the cultural factors, i.e., locus of control, was found to account for approximately 30% of the educational gradient in the case in which smokers were compared with former smokers. Psychosocial factors, i.e., neuroticism and coping styles, accounted for less of the gradient in smoking than cultural and material factors. CONCLUSIONS: On the basis of the results, we hypothesize that both cultural and material factors contribute to the higher smoking rates among lower socioeconomic groups. Psychosocial factors seem to be less important. If our results are confirmed in more powerful studies, this would indicate, first, that possibilities for a reduction of smoking differences may be found in tailoring smoking cessation programs to the more externally oriented locus of control and the coping styles that are common among lower educational groups, and second, that a reduction of smoking differences may follow from an improvement of the material living conditions of lower socioeconomic groups.

Adaptation, Psychological↗
PubMedDate not supplied

The importance of psychosocial stressors for socio-economic inequalities in perceived health.

The uneven distribution of psychosocial stressors as well as their differential health impact have been suggested as a possible explanation for socio-economic inequalities in health. We assessed the importance of both explanations, using data from the baseline of a Dutch longitudinal study. The outcome measure was the prevalence of perceived health problems. Educational level was used as an indicator of socio-economic status, whilst both life-events and long-term difficulties were included as stressors. We controlled for educational differences in neuroticism in order to eliminate any bias which might arise from the fact that people in lower educational groups are more inclined to report both stressors and health problems. The higher exposure to stressors was found to contribute to the increased risk of perceived health problems, even after differences in neuroticism were taken into account. Long-term difficulties, especially those related to material conditions, account for most of the effect. The impact of stress on health was hardly found to be moderated by educational level. The implications for future research are discussed.

Adolescent↗