How well does performance predict self-reported functioning in - PDF document

How well does performance predict self-reported functioning in Europe? A cross-country comparison among 14 European countries using SHARE data. Maria Bilo 1 , Eileen Crimmins 2 1 Dipartimento di Scienze Statistiche, Sapienza Università di Roma, Italy 2 Davis School of Gerontology, University of Southern California, USA Introduction Measurement of physical capability can be based on either performance or self-reports. Both approaches have advantages and disadvantages when measuring functioning among older adults [Angel et al. 2000, Gill 2010]. Self-reported functioning is often used because it is low cost and easy to administer; there is no need for equipment or special training of interviewers. However, respondents may evaluate their functioning relative to their own environment, including their personal adaptations, and relative to their reference population, resulting in measures which are not comparable across members of the population or across populations [Coman & Richardson 2006]. Performance-based measurement of functioning is more expensive given the need for special equipment and training and the time required for administration. However , results may depend on the respondent’s motivation and reflect maximal performance in an artificial environment rather than every day or normal ability. Comparison of the two approaches indicates that they can provide disparate results [Roedersheimer et al. 2016, Sager et al. 1992] because they indicate different aspects of functioning [Bean et al. 2011]. For example, performance-based measures seem to express strength or velocity related functioning better than self-reported measures. On the other hand, self-reports appear to be a better measure functioning that relies on aerobic capacity, disease burden or self-efficacy. Furthermore, Bean et al. point out that performance-based measures primarily reflect abilities of the lower limbs; whereas self-reported measures indicate abilities in tasks that require both the upper and lower limbs. A general conclusion is that both types of 1

measures capture information on the functional ability of older people but in different dimensions [Seidel et al. 2011]. Comparison of functioning across national populations show different results depending on the method of measurement. For example, differences in performance based functioning across Europe indicate that older persons in the Northern-continental countries have higher grip strength than those in Southern European countries [Andersen-Ranberg et al. 2009]. Furthermore, it was shown that grip strength indeed strongly predicts disability, morbidity and death among older Europeans [Hairi et al. 2009] but that socio-economic drivers (wealth, education, occupation and income) of grip strength do not consistently predict grip strength in Europeans. The aim of this paper is to examine cross-national differences in self-reported physical functioning and performance-based functioning. The questions addressed include: 1) Are there statistically significant differences in self-reported functionality among European countries? 2) Do differences in functioning ability as evidenced by performance-based measurement explain the differences in self-reports of functioning differences across European countries? Background As mentioned, there are several studies that compare either performance-based or self-reported measurements between countries with or within Europe. The US, e.g. shows higher self- reported disability than the Netherlands [Kapteyn et al. 2007]. Another study of disability in three European countries illustrated cross-cultural variation in the association of self-reports and performance-based disability measurement [Van den Brink 2003]. Data from 1990 were used to compare men from Italy, the Netherlands and Finland. The initial North-South gradient in self-reported disabilities as well as performance abilities was explained by adjusting by age, socioeconomic status, household composition and chronic diseases. Furthermore, it could be shown that performance score was positively associated with self-reported disability score in 2

those three countries and that the strength of this association did not differ between the countries. The study concludes that those differences among European countries may result from different sociocultural and physically environmental backgrounds of the participants. [Andersen-Ranberg 2009, Brothers et al. 2014, Verropoulou 2009] We expect national levels of both observed and reported functioning ability to be affected by sociodemographic composition of populations. Educational level has been shown to be a strong predictor of functioning [ d’Uva et al. 2008 , Verropoulou 2009]. Gender has also been shown to be related to functioning ability [Crimmins et al. 2011, Verropoulou 2009]. It has also been shown that performance-based tests explain most variance in self-reported health, even though there was no strong association between self-reported and performance-based health [Kempen et al. 1996]. Nevertheless, it is unclear how and to what extend those performance-based measures influence self-reported health in different countries. Comparative studies are essential to understand circumstances that are associated with health differences among different countries. To understand how certain factors have a possibly different impact among countries provides a great potential to expand the knowledge around health differences and the approaches to minimize them. Comparative studies improve the understanding of the limits of the generalization of health issues in different countries. Consequently, we reckon that performance-based test results play a part in contributing to predict self-reported health but that those influences vary by countries. Methods Data The data used is drawn from the Survey of Health, Ageing and Retirement in Europe (SHARE) [Börsch-Supan 2016]. SHARE is a cross-national panel survey producing individual level data on health, socio-economic status, and social and family networks for a number of European countries. This paper uses data from SHARE Wave 2 (2006/2007) (DOI: 3

10.6103/SHARE.w2.500). All data were collected by interviewers in a face-to-face computer- aided personal interviews (CAPI), supplemented by self-completion paper and pencil questionnaires [Börsch-Supan et al. 2008]. See Börsch-Supan et al. [2013] for methodological details. The second wave of SHARE (2006/2007) interviews people aged 50 and older from 14 European countries: Austria, Belgium, Switzerland, Germany, Denmark, Spain, France, Greece, Italy, Netherlands, Sweden, Czech Republic, Ireland and Poland. For our analysis, we select first people aged 50 and older from those countries with reliable information about their age and sex (N = 33,697). Furthermore, we excluded respondents who did not perform at least 1 out of 3 performance-based tests (grip strength, peak flow, chair stand) from our analysis (2,106 cases). SHARE also has a fourth performance-based test of walking speed. This test was not used in our analysis because only respondents age 75 and higher were asked to do this test. Therefore, we start our analysis with 31,591 observations. Measures Self-reported functioning ability is reflected by an additive index, based on responses to questions on 6 activities of daily living (dressing, walking across a room, bathing or showering, eating, getting in or out of bed, using the toilet), 7 instrumental activities of daily living (using a map for orientation, preparing a hot meal, grocery shopping, making telephone calls, taking medications, house/garden work, managing money), and 10 Nagi indicators of mobility, arm function and fine motor limitations (walking 100 meters, sitting for about 2 hours, getting up from a chair after sitting for long periods, climbing several flights of stairs without resting, climbing one flight of stairs without resting, stooping/kneeling/crouching, reaching or extending arms above shoulder level, pulling or pushing large objects like a living rooms chair, lifting or carrying weights over 10 pounds/5 kilos, picking up a small coin from a table). People who respond that they are limited in an activity are scored a 1. Therefore, the ADL variable has a value range from 0 to 6, whereas the range of the IADL variable spans 0 to 7. The NAGI 4