G. A. M. van den Bos

Burden of informal caregiving for stroke patients: Identification of caregivers at risk of adverse health effects

Background: We assessed the objective and subjective burden of caregiving for stroke patients and investigated which characteristics of the patient, the informal caregiver and the objective burden contribute most to subjective burden and to the condition of feeling substantially burdened. Methods: We studied a sample of 151 stroke survivors and their primary informal caregivers. We collected data through patient and caregiver interviews 6 months after stroke. Results: Both the level of subjective burden and the condition of feeling substantially burdened were associated with both caregiver’s and patient’s health-related quality of life, patient’s age, and the number of caregiving tasks performed. Conclusions: These conditions can be used in clinical practice to identify potentially vulnerable caregivers in need of support and at risk of adverse health effects. Monitoring stroke survivors as well as their family caregivers at discharge may help to prevent or alleviate caregiver burden.

AGEING AND THE RELATIONSHIP BETWEEN FUNCTIONAL STATUS AND SELF-RATED HEALTH IN ELDERLY MEN

Functional status (measured as functional limitations or disabilities) is an important determinant of self-rated health in the elderly. Several issues which are not yet clear in this association are addressed in this study: (i) the modifying effect of age on the association; (ii) the effect of recent changes in disability level on the current level of self-rated health, and (iii) the effect of functional limitations on self-rated health, independent of disabilities. Data were derived from the 1990, 1993 and 1995 surveys of the Zutphen Elderly Study, a longitudinal health study in men born between 1900 and 1920. Analyses of repeated measurements were performed with self-rated health as dependent variable and disabilities, functional limitations, age, survey year, and interaction terms as independent variables. Odds ratios were calculated from these models. Men with disabilities in instrumental activities of daily living had no different health ratings than men without disabilities. Those with disabilities in mobility and basic activities of daily living, however, had an odds ratio on poor self-rated health of 4.7 (95% confidence interval: 2.7-7.9) and 8.9 (4.6-17.1) respectively. This association became weaker with increasing age, leading to an absence of a significant association in the oldest group. The current level of self-rated health was only associated with the current level of disabilities. Information on previous levels of disabilities did not contribute to current self-rated health. Functional limitations had a small, but significant, effect on self-rated health when disabilities were taken into account. This study helps in enhancing insight in the complex relationship between functional status and self-rated health in the elderly.

Socioeconomic Status and Stroke Incidence in the US Elderly The Role of Risk Factors in the EPESE Study

Background and Purpose— This study assesses the effect of socioeconomic status on stroke incidence in the elderly, and the contribution of risk factors to stroke disparities. Methods— Data comprised a sample of 2812 men and women aged 65 years and over from the New Haven cohort of the Established Populations for the Epidemiologic Studies of the Elderly. Individuals provided baseline information on demographics, functioning, cardiovascular and psychosocial risk factors in 1982 and were followed for 12 years. Proportional hazard models were used to model survival from initial interview to first fatal or nonfatal stroke. Results— Two hundred and seventy subjects developed incident stroke. At ages 65 to 74, lower socioeconomic status was associated with higher stroke incidence for both education (HRlowest/highest=2.07, 95% CI, 1.04 to 4.13) and income (HRlowest/highest=2.08, 95% CI, 1.01 to 4.27). Adjustment for race, diabetes, depression, social networks and functioning attenuated hazard ratios to a nonsignificant level, whereas other risk factors did not change associations significantly. Beyond age 75, however, stroke rates were higher among those with the highest education (HRlowest/highest=0.42, 95% CI, 0.22 to 0.79) and income (HRlowest/highest=0.43, 95% CI, 0.22 to 0.86), which remained largely unchanged after adjustment for risk factors. Conclusions— We observed substantial socioeconomic disparities in stroke at ages 65 to 74, whereas a crossover of the association occurred beyond age 75. Policies to improve social and economic resources at early old age, and interventions to improve diabetes management, depression, social networks and functioning in the disadvantaged elderly can contribute to reduce stroke disparities.

A Stroke-Adapted 30-Item Version of the Sickness Impact Profile to Assess Quality of Life (SA-SIP30)

BACKGROUND AND PURPOSE In view of the growing therapeutic options in stroke, measurement of quality of life has become increasingly relevant as an outcome parameters. The Sickness Impact Profile (SIP) is one of the most widely used measures to assess quality of life. To overcome the major disadvantage of the SIP, its length, we constructed a short stroke adapted 30-item SIP version (SA-SIP30). METHODS Data on the original SIP version were collected for 319 communicative patients at 6 months after stroke. The 12 subscales and the 136 items of the original SIP were reduced to 8 subscales with 30 items in a three step procedure, on the basis of relevancy and homogeneity. Reliability of the SA-SIP30 was evaluated by means of an analysis of homogeneity (Cronbachs alpha coefficient). Different types of validity were assessed: construct, clinical, and external validities. RESULTS Homogeneity of the SA-SIP30 was demonstrated by a high Cronbachs alpha (0.85). Principal component analyses revealed the same two dimensions as in the original SIP (a physical and a psychosocial dimension). The SA-SIP30 could explain 91% of the variation in scores of the original SIP in the same cohort of patients, and 89% in a different cohort. Furthermore, the SA-SIP30 was related to other functional health measures similar to how the original SIP was. We could demonstrate that the SA-SIP30 was able to distinguish patients with lacunar infarctions from patients with cortical or subcortical lesions. CONCLUSIONS We conclude that the SA-SIP30 is a feasible and clinimetrically sound measure to assess quality of life after stroke.

Socioeconomic variations in the course of stroke: unequal health outcomes, equal care?

Study objective: The aim of this paper is to quantify the socioeconomic gap in long term health outcomes after stroke and related health care utilisation, in order to evaluate whether those in need of care do actually receive appropriate levels of care. Design: Stroke patients from the lower socioeconomic group were compared with stroke patients from the higher socioeconomic group with respect to sociodemographic and clinical characteristics, health outcomes, and related health care utilisation. Setting: Patients were recruited from admissions to 23 randomly selected hospitals in the Netherlands. Patients: 465 patients were included who had had a stroke six months earlier and were followed up three years and five years after stroke. Main results: The observed odds ratios suggest that patients from the lower socioeconomic group experienced more disabilities up to three years after stroke and more handicaps up to five years after stroke. After adjusting for health care needs there were no significant associations between socioeconomic status and health care utilisation. The observed figures, however, suggest that a lower socioeconomic status tended to increase admission to nursing homes and to decrease receiving care in non-institutional settings. Conclusions: Overall, inequalities in long term health outcomes were observed but solid indications for large inequalities in health care utilisation were not found. More investments in coordinated stroke services are needed to alleviate the unfavourable health situation of disadvantaged groups and to ensure that health care services respond appropriately to the health care needs of different socioeconomic groups.

Clinical Meaning of the Stroke-Adapted Sickness Impact Profile–30 and the Sickness Impact Profile–136

Background and Purpose Handicap or health-related quality of life (HRQL) measures are seldom used in stroke trials, although the importance of these measures has been stressed frequently. We studied the clinical meaning of the Stroke-Adapted Sickness Impact Profile–30 (SA-SIP30) and the original SIP136 for use in stroke research. Methods We included 418 patients who had had a stroke 6 months earlier. We studied the associations between the SA-SIP30 and SIP136 scores versus other frequently used outcome measures from the International Classification of Impairments, Disabilities, and Handicaps (ICIDH) (Barthel Index, Rankin Scale) and the HRQL model (health perception items, Euroqol). To interpret the continuous SA-SIP30 and SIP136 scores, we used receiver operating characteristic curve analysis with the aforementioned measures as external criteria. Results The psychosocial dimension scores of both SIP versions remained largely unexplained. The physical dimension and total scores of both SIP versions were mainly associated with the disability measures derived from the ICIDH model, as well as with the physical HRQL domains. Most patients with an SA-SIP30 total score >33 or an SIP136 total score >22 had poor health profiles. There were no major differences between the SA-SIP30 and the SIP136, although the SA-SIP30 scores were less skewed toward the healthier outcomes than the SIP136. Conclusions Our study showed that (1) both SIP total scores primarily represent aspects of physical functioning and not HRQL; (2) both SIP versions provide more clinical information than the frequently used disability measures; and (3) the SA-SIP30 should be preferred over the SIP136.

Quality of life as an instrument for need assessment and outcome assessment of health care in chronic patients.

Introduction Quality of life is generally acknowledged as a central concept in health care, but its full application in healthcare research and clinical practice are still being debated. With an increasing prevalence of chronic diseases and the focus of health care expanding from “adding years to life” to “adding life to years”, there is a growing interest in assessments of quality of life in health care. Measures of quality of life have been used almost exclusively in health services research to assess outcomes of care—that is, eVectiveness of care. Arguments in favour of this “outcome approach” are based upon the growth of the healthcare system, the need for cost containment, and the ensuing call for evidence-based health care. Less attention has been given to the use of quality of life for monitoring health needs as an index of the relative appropriateness of health care. Although the “outcome approach” is already widely established, the “need approach” has only recently gained attention. Chronically ill patients are particularly likely to benefit from need assessment and the routine use of patient derived data in making decisions about the distribution, access, and content of long term care. Comprehensive evaluations of health care must involve assessments of outcomes and needs. It is only by including both these assessments that the process of care for patients with a chronic disease can be improved. This article aims to clarify the interrelation between quality of life and quality of care. To elucidate this association we will use examples from our research on patients with stroke. The objectives are (a) to describe the necessity and use of measures of quality of life in health services research; (b) to examine the use of measures of quality of life to study outcomes of care and to illustrate how these measures can be used to assess the need for care; and (c) to discuss problems in quality assurance that are related to the comprehensiveness of chronic care.

Impact of Stroke Type on Survival and Functional Health

In a cohort 760 consecutive stroke patients (23 hospitals in the Netherlands), we studied prognosis in relation to stroke type and focused on (a) short-term and long-term mortality, and (b) long-term functional health. Based on clinical and CT data, we distinguished infratentorial strokes from supratentorial strokes (lacunar infarctions, (sub)cortical infarctions and intracerebral hemorrhages). Cumulative mortality for all stroke patients was 34% at 6 months, 51% at 3 years, and 62% at 5 years. Short-term mortality could be explained by stroke type, whereas long-term mortality could not. Of all survivors, 55% were in poor functional health at 6 months, 49% at 3 years and 42% at 5 years. Long-term functional health outcomes were associated with stroke type. We conclude that the impact of stroke type on mortality is limited to the first 6 months, whereas the type of stroke influences the long-term functional health.

Socioeconomic status of very small areas and stroke incidence in the Netherlands

Objective: To examine whether characteristics of very small living areas can be used to predict disease incidence and to use these characteristics to assess socioeconomic differences in stroke incidence in the Netherlands. Design: Characteristics of postcode areas of stroke patients are compared with characteristics of postcode areas of all individual people in the study region, using Poisson regression analysis. Setting: Six provinces of the Netherlands, covering about half of the country. Patients: 760 patients who in 1991 or 1992 were consecutively admitted because of stroke to 23 Dutch hospitals. Main results: Stroke incidence is significantly higher among people living in postcode areas with below average socioeconomic status (relative risk=1.27; 95% confidence intervals 1.08 to 1.51) and among people living in postcode areas with predominantly older inhabitants (RR=3.17; 95% CI=2.29 to 4.39). It is also significantly increased in more urbanised areas compared with the countryside, the highest incidence being found in the large cities (RR=1.78; 95% CI=1.31 to 2.44). Conclusions: A clear socioeconomic gradient in stroke incidence in the Netherlands is observed, with people living in detailed postcode areas with below average socioeconomic status experiencing a significantly higher risk of stroke. The analysis also confirms that characteristics of detailed postcode areas can effectively be used to differentiate between areas with and areas without stroke patients.

Identification of risk factors related to perceived unmet demands in patients with chronic stroke

Purpose. To investigate the prevalence of unmet demands concerning autonomy and participation and to identify risk factors related to these unmet demands in patients with chronic stroke. Method. A cross-sectional study of 147 patients three years after stroke. We assessed perceived unmet care demands in relation to problems of participation and autonomy measured by the Impact on Participation and Autonomy Questionnaire (IPAQ). Socio-demographic and health characteristics were analysed as potential risk factors for the prevalence of unmet demands, using multivariate regression analysis. Results. A total of 33% of the patients perceived at least one unmet demand in one of the IPAQ subdomains. Risk factors significantly related to the presence of unmet demands were younger age, motor impairment, fatigue and depressive symptoms. Findings indicate that the model including these factors was fairly accurate in identifying patients having unmet demands and those not having unmet demands. Conclusions. Unmet care demands were present in a substantial proportion of the stroke patients. The risk factors identified are helpful for clinicians and health care providers to recognize patients who are at risk of perceiving unmet care demands and to optimize care to patients with chronic stroke.