Individual and environmental factors underlying life space of older people - study protocol and design of a cohort study on life-space mobility in old age (LISPE)

This is an electronic reprint of the original article. This reprint may differ from the original in pagination and typographic detail. Author(s): Title: Year: Version: Please cite the original version: All material supplied via JYX is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. Individual and environmental factors underlying life space of older people - study protocol and design of a cohort study on life-space mobility in old age (LISPE) Rantanen, Taina; Portegijs, Erja; Viljanen, Anne; Eronen, Johanna; Saajanaho, Milla; Tsai, Li-Tang; Kauppinen, Markku; Palonen, Eeva-Maija; Sipilä, Sarianna; Iwarsson, Susanne; Rantakokko, Merja Rantanen, T., Portegijs, E., Viljanen, A., Eronen, J., Saajanaho, M., Tsai, L.-T., Kauppinen, M., Palonen, E-M., Sipilä, S., Iwarsson, S. & Rantakokko, M. (2012). Individual and environmental factors underlying life space of older people - study protocol and design of a cohort study on life-space mobility in old age (LISPE). BMC Public Health, 12 (-), 1018. doi:10.1186/1471-2458-12-1018 Retrieved from http://www.biomedcentral.com/1471-2458/12/1018 2012 STUDY PROTOCOL Open Access Individual and environmental factors underlying life space of older people –study protocol and design of a cohort study on life-space mobility in old age (LISPE) Taina Rantanen 1* , Erja Portegijs 1 , Anne Viljanen 1 , Johanna Eronen 1† , Milla Saajanaho 1† , Li-Tang Tsai 1 , Markku Kauppinen 1 , Eeva-Maija Palonen 1 , Sarianna Sipilä 1 , Susanne Iwarsson 2 and Merja Rantakokko 1* Abstract Background: A crucial issue for the sustainability of societies is how to maintain health and functioning in older people. With increasing age, losses in vision, hearing, balance, mobility and cognitive capacity render older people particularly exposed to environmental barriers. A central building block of human functioning is walking. Walking difficulties may start to develop in midlife and become increasingly prevalent with age. Life-space mobility reflects actual mobility performance by taking into account the balance between older adults internal physiologic capacity and the external challenges they encounter in daily life. The aim of the Life-Space Mobility in Old Age (LISPE) project is to examine how home and neighborhood characteristics influence people’s health, functioning, disability, quality of life and life-space mobility in the context of aging. In addition, examine whether a person’s health and function influence life-space mobility. Design: This paper describes the study protocol of the LISPE project, which is a 2-year prospective cohort study of community-dwelling older people aged 75 to 90 (n = 848). The data consists of a baseline survey including face-to-face interviews, objective observation of the home environment and a physical performance test in the participant’s home. All the baseline participants will be interviewed over the phone one and two years after baseline to collect data on life-space mobility, disability and participation restriction. Additional home interviews and environmental evaluations will be conducted for those who relocate during the study period. Data on mortality and health service use will be collected from national registers. In a substudy on walking activity and life space, 358 participants kept a 7-day diary and, in addition, 176 participants also wore an accelerometer. Discussion: Our study, which includes extensive data collection with a large sample, provides a unique opportunity to study topics of importance for aging societies. A novel approach is employed which enables us to study the interactions of environmental features and individual characteristics underlying the life-space of older people. Potentially, the results of this study will contribute to improvements in strategies to postpone or prevent progression to disability and loss of independence. Keywords: Life-space, Mobility, Quality of life, Environment, Participation, Physical activity, Walking, Aging, Cohort studies * Correspondence: [email protected];[email protected] † Equal contributors 1 Gerontology Research Center and Department of Health Sciences, University of Jyväskylä, P.O.Box 35, Jyväskylä FI-40014, Finland Full list of author information is available at the end of the article © 2012 Rantanen et al. licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Rantanen et al. BMC Public Health 2012, 12:1018 http://www.biomedcentral.com/1471-2458/12/1018 Background Walking, driving and using public transport are the leading forms of mobility among older adults in their local neighborhood. Walking is an integral part of mobility and may be considered a prerequisite for the unassisted use of other modes of transportation. Consequently, the different modes of mobility may share similar risk factors. Mobility is optimal when you are able to go where you want to go, when you want to go, and how you want to go, safely and reliably [1]. The proportion of people over 80 years is growing rapidly. The majority of older people lives in private households and, along with increasing age and declining health, tend to spend more and more of their time inside the home or in its immediate surroundings. Eventually, mobility limitations may render them homebound which, in turn, may lead to marginalization from social activities, loneliness and poor quality of life [2]. A better understanding of the factors that hinder or support the independent community mobility of older people is required to optimize opportunities for active aging and to reduce health disparities. The disablement model by Nagi [3], later expanded by Verbrugge and Jette [4], outlines the pathway between pathology and disability. Pathology refers not only to physiological abnormalities, such as chronic diseases or injury, but also to physiological changes with advancing age that affect specific body systems and may result in impairments such as strength, balance or sensory impairments. Impairments may lead to functional limitations such as decreased gait speed, which in turn may cause disability. Disability refers to a situation where individual capabilities are not sufficient to meet the requirements of the living environment. The ecological model of ageing, also known as the “Competence-Press model”[5], describes the person-environment relationship in more detail. Environmental factors influence mobility through interaction with the individual’s capabilities, termed person-environment fit (P-E fit). If an individual’s competence and the demands of the environment are in balance, then that individual is able to adapt and function optimally. The ecological model of aging has a strong psychological emphasis, while the disablement process model emphasizes physiological changes. Combining the salient aspects of these two models into an analytical approach may provide a good foundation to better understand age-related changes in mobility. In the long term, most of the chronic conditions that accompany aging will have a detrimental influence on mobility through various mechanisms involved in the decline in functioning of the musculoskeletal, neurological or cardio-respiratory systems. The impairments most commonly studied in relation to walking difficulties are those that directly influence walking, namely muscle strength and balance. Impairments in sensory functions, such as vision and hearing, also affect mobility [6]. Hearing loss may hinder the ability to divide attention between traffic, having a conversation, maintaining postural balance and walking, thus potentially increasing risk for falls and other accidents [7]. According to one of our previous studies [8], people with co-existing vision and hearing impairments had over four-fold risk, and people with coexisting impairments in vision, hearing and balance almost 30-fold risk, for falls, compared to people with no vision impairment. Falling and fall-related injuries are common among older people, often leading to a sudden and catastrophic disability. Approximately 20% to 40% of community-dwelling individuals older than 65 years fall every year and about half of those who fall do so repeatedly [9]. Falls may lead to progressive mobility decline, even in the absence of consequent injury. In our previous study, older women with indoor falls were over three times more likely to report new difficulties in walking 2 km by the end of the 3-year follow-up compared to those with no falls [10]. Environmental conditions affect outdoor mobility, especially in older adults [11], either by facilitating or restricting participation in out-of-home activities. Environmental barriers for outdoor mobility subjectively reported by older adults include, for example, poor transportation, discontinuous or uneven side-walks, curbs, noise, heavy traffic, inadequate lighting, lack of resting places, sloping terrain, long distances to services and weather conditions [12,13]. Poor street condition, heavy traffic and excessive noise correlate with onset of mobility limitation while pedestrian-oriented designs and access to recreational facilities are positively associated with physical activity and self-rated health in older adults. Similar evidence exists for the association between barriers in the home and difficulties carrying out important daily activities [14]. However, most of the existing studies are cross-sectional. This makes it impossible to know which comes first, the environmental barrier or the mobility problem, and so draw conclusions on causality (for review, see [15]). Life-space mobility refers to the size of the spatial area (bedroom, home, outside home, neighborhood, town, distant locations) a person purposely moves through in daily life and to the frequency of travel within a specific time and need of assistance for that travel [16]. The first reports on life-space appeared in the aging literature during the 1980s and early 1990s [17,18], but most studies concerned nursing home residents. Life-space mobility reflects the balance between the persons’internal physiologic capacity and the environmental challenges older adults encounter in daily life. Life-space can be used to evaluate transitions in individuals’abilities to live Rantanen et al. BMC Public Health 2012, 12:1018 Page 2 of 17 http://www.biomedcentral.com/1471-2458/12/1018 independently [16]. Only few studies have addressed lifespace mobility in community-living older people [19]. Shrinking life-space probably coincides with giving up valued activities that, maintain the social role of the person, such as visiting friends, participating in out-ofhome hobbies, recreation or work, and in general with giving up accessing community amenities, a situation referred to as participation restriction [20]. However, not all older persons with functional limitations necessarily restrict their life-space, if they can find ways to compensate for their difficulties, e.g. by using mobility devices [21]. Consequently, measuring life-space mobility also needs to incorporate compensatory strategies. Project aims Study aim The aim of the Life-Space Mobility in Old Age (LISPE) project is to examine how home and neighborhood characteristics influence the residents’health, functioning, disability, quality of life and life-space mobility in the context of aging. Specific research questions are: 1. What are the environmental (e.g. distance to services, green spaces, benches by walk ways, heavy traffic, level of urbanization) and individual (e.g. fear of moving outdoors, fear of falling and injury, sensory impairments, walking limitation, personal goals) determinants of life-space mobility, disability and participation restriction? 2. Does life-space mobility correlate with indicators of individual wellbeing (quality of life, depressive symptoms and perceived health)? 3. Do changes (increase, decrease) in life-space mobility lead to parallel changes in indicators of individual wellbeing? 4. What are the environmental and individual predictors of changes in life-space mobility and disability (onset, recovery) and participation restriction? 5. How do facilitating/supporting or encumbering environmental features (perceived and objective) differ according to the extent of life-space mobility or differences in functioning? 6. Do individual and environmental features interact in explaining life-space mobility? 7. What are the individual and environmental factors and their interactions underlying the association of life-space mobility and quality of life in older people? Substudy aim The aim of the substudy is to investigate the relationship between habitual walking activity and life-space mobility among community-dwelling older people with an emphasis on environmental barriers and facilitators to habitual walking activity. Methods Study design The study is a 2-year prospective cohort study of community-dwelling older people aged 75 to 90 living in the municipalities of Muurame and Jyväskylä, Finland. Over the 2-year period, four personal contacts will be made with the participants, as shown in Figure 1. The initial contact over the phone was followed by a baseline interview at the home of the participant within 1 to 2 weeks. The baseline home visit will be followed up by phone interviews one and two years later. Subsequently, participants who have relocated since the previous assessment will be visited by a research assistant to gain additional information regarding their relocation and new living environment. The study also provides an opportunity to collect data on the use of health services and on the mortality of the participants from national registers. The substudy on walking activity and life-space mobility was conducted immediately following the baseline assessment. Muurame and Jyväskylä are neighboring municipalities located in central Finland with total population of 141 500. At the time of drawing the sample, the total Figure 1 Conduct of the study. The diary as well as the home visit at follow-up 1 (FU1) and 2 (FU2) only concern subgroups of participants and are colored gray. Recr. refers to recruitment and BL to baseline assessment. Rantanen et al. BMC Public Health 2012, 12:1018 Page 3 of 17 http://www.biomedcentral.com/1471-2458/12/1018 population of men and women within that age range was 8 914, of whom 7% lived in sparsely populated areas. For each age group of 75–79, 80–84, and 85–89 years, a random sample of 500 was drawn from the population register on December 12 th , 2011. The sample was supplemented on March 15 th , 2012 with an additional 350 persons for each age group to secure a sufficient number of participants. The resulting sample was thus 2 550. Sample size calculations We calculated that our sample size needed to be at least N = 800 to have sufficient power to also run analyses for subgroups based on age, gender and type of neighborhood. For continuous variables (e.g. life-space mobility variables) a sample size of 800 yields a power of > 99% to show a contribution to the explained variance of 5% in a linear regression model with 10 predictors (including interactions, but not constant) if the probability level (alpha) is set at 0.05. In addition, a sample size of 800 yields even weak correlation coefficients statistically significant. Based on the population characteristics of the recruitment area, 7% of the included population was expected to be living in a sparsely populated area. With a total sample size of at least 800 this would yield a subgroup of about N > 56 persons. In the univariate analyses, correlation coefficients of r > 0.3 would be statistically significant with a two-tailed significance level of 0.05 and a sample size of 56. Recruitment process and data collection Contacting participants A letter containing information about the study including an announcement to expect a phone call the following week was sent to the potential participants. Phone numbers were collected from a nationwide database for all persons in the sample. The research assistant (EMP) called potential participants by phone at the time indicated. When a person could not be contacted, at least 5 repeat phone calls were made on different days and times. When no phone number was available for a person, an information letter was sent including a request to call our research assistant if interested in participating in the study. The initial phone interview During the first phone call potential participants were asked about their willingness to participate in the study and to respond to a short questionnaire with the aim of determining, whether the person was eligible for participation in the study. The inclusion criteria were living independently, able to communicate, residing in the recruitment area and willing to participate. If a person was found eligible, the time for the home visit was set. A letter confirming the time of the home visit was mailed to the participant’s home accompanied by an informed consent form. Persons not interested in participating in the study were asked whether they wished to respond to the same brief phone interview questionnaire as the participants. These data will be used for a non-respondent analysis. The main reason for non-participation (poor health or illness, lack of time, or unwillingness) was recorded if clearly indicated by the person. Baseline face-to-face interview in the participants home The informed consent form was signed by the participant at the start of the face-to-face interview. The interviews were conducted in the participant’s home using computer-assisted personal interviewing (CAPI). That is, interviewers marked the answers on the electronic forms using laptops. The electronic forms were created using SPSS Data Entry Builder (version 4.0) software from SPSS Inc. A hard copy of the questionnaire was available as back-up in case of computer problems. In addition to the self-report questionnaire, the interviewer objectively assessed the physical performance and functional limitations of the participant and physical environmental barriers in entrances and the immediate outdoor environment. The average duration of the interview was 1.5 hours and the environmental evaluation took approximately 15 minutes. Oneand two-year follow-up, phone interview The first follow-up interview will be made via telephone one year from the baseline interview. When, on the first attempt, a person is not contacted, at least 4 further phone calls will be made to this person on different days and times. If the participant is unable to answer the questions over the phone, the possibility of a face-to-face interview will be offered. For those who have relocated, after informed consent an additional home interview will be conducted by a research team member (JE, MS). The second follow-up interview will be conducted in a similar manner. Measures Age and gender were drawn from the population register as part of the sampling procedure. All the other measures and their time of assessment are listed in Table 1. Main outcome measures Life-space mobility The main outcome of the project, life-space mobility, was measured with the University of Alabama at Birmingham Study of Aging Life-Space Assessment (LSA) [16], which was translated into Finnish. The translation was done by a back and forward translation procedure by native-speaking English and Finnish translators. Lifespace mobility reflects actual mobility performance in Rantanen et al. BMC Public Health 2012, 12:1018 Page 4 of 17 http://www.biomedcentral.com/1471-2458/12/1018 Table 1 Measures included in the study and the number of items included in each follow-up Instrument Domains Assessment BL FU1 FU2 Ref. Main outcome measures Life-Space Mobility (LSA) Within home 3 items 3 items 3 items [16] Outdoor 3 items 3 items 3 items Neighborhood 3 items 3 items 3 items Town 3 items 3 items 3 items Unlimited 3 items 3 items 3 items Quality of life (WHOQOL-BREF) General 2 items 1 items 1 items [22] Environmental 8 items 8 items 8 items Physical 7 items - 7 items Social relationships 3 items - 3 items Psychological 6 items - 6 items Physical functioning Mobility disability 2 km 1 item 1 item 1 item [23] 500 m 1 item 1 item 1 item Stair climbing 1 item - - Moving indoors 1 item - - Pre-clinical mobility limitation 2 km 6 items 6 items 6 items [23] 500 m 6 items - - Stair climbing 6 items - - Assistive devices 7 items - - [24] Short Physical Performance Battery (SPPB) Standing balance 1 item - - [25,26] Walking 1 item - - Chair rise 1 item - - Physical activities Level of physical activity 1 item 1 item 1 item [27] Barriers to physical activity 17 items - - [28] Avoidance of moving outdoors 2 items - - [29] Unmet physical activity need 2 items 2 items 2 items [30] Environmental factors Perceived environmental barriers Outdoors 15 items - - [13] Entrance 6 items - - Perceived environmental facilitators Outdoors 12 items - - Entrance 7 items - - Exercise facilities 3 items - - Type of housing & neighborhood 2 items - - Objective assessment of environment (HE Screening Tool) Outdoors 17 items - - [31] Entrance 11 items - - Transportation Car driving 2 items 2 items 2 items Public transport 4 items - - Going to store 2 items - - Participation Leisure time activities 5 items - - [32] Impact on Autonomy & Participation (IPA) Autonomy outdoors 5 items - - [33,34] Rantanen et al. BMC Public Health 2012, 12:1018 Page 5 of 17 http://www.biomedcentral.com/1471-2458/12/1018 daily life. The LSA comprises 15 items and assesses mobility through the different life-space levels (distance), which the participant reports having moved through during the 4 weeks preceding the assessment. For each life-space level (bedroom, other rooms, outside home, neighborhood, town, beyond town), participants were asked how many days a week they attained that level and whether they needed help from another person or from assistive devices. Four indicators of life-space mobility will be calculated [16]: 1) Independent life-space, indicating the highest level of life-space attained without help from any devices or persons, 2) Assisted life-space indicating the highest level of life-space attained using the help of assistive devices if needed but not the help of another person, 3) Maximal life-space, indicating the greatest distance attained with the help of devices and/or persons if needed, and 4) a composite score which reflects the distance, frequency and level of independence (range 0–120). For each LSA indicator, higher scores indicate a larger life-space. Of the LSA indicators, the composite score has the strongest correlation with a person’s observed physical performance [16]. At baseline, life-space mobility was assessed during the face-to-face interview whereas during the follow-ups it will be assessed by phone interviews. The test–retest reliability of LSA scores between a face-to-face interview and a phone interview within two weeks of the baseline assessment was reported to be 0.96 [16]. Quality of life The World Health Organization Quality of Life Assessment short version, WHOQOL-BREF, was used for the baseline assessment of quality of life. It measures individuals’perceptions in the context of their culture and value systems, and their personal goals, standards and concerns. The 26-item scale comprises four domains; physical health, psychological health, social relationships and the environment. Scoring is calculated separately for Table 1 Measures included in the study and the number of items included in each follow-up (Continued) Disability in self-care & instrumental activities ADL 5 items - 5 items [35] IADL 9 items - - Additional items 2 items - - Social context Care giver role 2 items - - Social contacts & loneliness Frequency of contacts 3 items - - [36,37] Loneliness 1 item - - Support 1 item - - Marital status & living 2 items - - Socioeconomic status Education 2 items - - [38] Financial situation 1 items - - Profession 1 item - - House ownership 1 item - - General health Self-rated health & chronic diseases Self-rated health 1 item 1 item 1 item [39] Chronic diseases 22 items - - Weight (loss), height 3 items - - [40] Cognitive impairment (MMSE) 30 items - - [41] Depressive symptoms (CES-D) 20 items - - [42] Sensory functions Vision 4 items 2 items 2 items [43] Hearing 11 items 8 items 8 items Perceived postural balance General 1 item - - [44] Fear of falling 1 item - - History of falls 2 items - - Interviewer-rated functional status 8 items - - [45] Personal goals 1 item - - [46] Relocation & major life events - 6 items 6 items Rantanen et al. BMC Public Health 2012, 12:1018 Page 6 of 17 http://www.biomedcentral.com/1471-2458/12/1018 each domain and the composite score in all four domains reflects overall quality of life. For participants with one item missing in a subscale or 1–3 items in the total questionnaire, a sum score was calculated (n = 56). In health research, quality of life refers to the general well-being of individuals and comprises wealth, the built environment, physical and mental health, education, recreation and leisure time and social belonging [22]. Physical functioning Mobility disability and pre-clinical mobility limitation In the initial phone interview, we studied perceived difficulties in outdoor mobility with the following response categories: 1) able without difficulty, 2) able with some difficulty, 3) able with a great deal of difficulty, 4) unable without the help of another person, and 5) unable to manage even with help. Frequency of going outdoors was studied with the response options 1) daily, 2) 4–6 times a week, 3) 1–3 times a week, and 4) less than once a week. These questions were posed for the purpose of the non-respondent analysis. In the face-to-face interview mobility disability was studied for perceived difficulties in walking 2 km and 500 m, climbing up 1 flight of stairs and moving around in the home [23]. The response options were similar to those for outdoor mobility. For the four mobility tasks, those reporting that they were able to manage without difficulty were asked about potential modifications in task performance. The presence of the following modifications was determined (yes/no): resting in the middle of performing the task, using an aid, using the support of handrails, having reduced the frequency of performing the task, having slowed down performance of the task, experiencing tiredness when performing the task, or some other change in carrying out the task. These questions identify individuals at an early stage of mobility limitation, that is, preclinical mobility limitation. Preclinical mobility limitation is a state between intact mobility and manifest mobility limitation. Individuals who report task modification have an increased risk of future mobility limitation. However, at the same time they may postpone manifest mobility limitation by making the task performance less taxing by modifying the way they do the task [23]. Use of assistive devices for mobility The use of an assistive device for mobility was rated for seven listed assistive devices with the response options: 1) no, 2) yes, only indoors, 3) yes, only outdoors, and 4) yes, both indoors and outdoors. This list was used previously in the SCAMOB (Screening and Counseling for Physical Activity and Mobility project, ISRCTN07330512) project [24]. Short physical performance battery Lower-extremity physical performance was objectively assessed by the Short Physical Performance Battery (SPPB) [25], which was translated into Finnish [26]. The tests were performed in the participant’s home. The battery comprises three tests that assess standing balance (indicator of balance function), walking speed over a distance of 2.44 meters (general indicator of mobility), and the ability to rise from a chair (indicator of muscle power and strength). Each task is rated from 0 to 4 points according to established ageand gender-specific cut-off points [25]. Participants unable to perform the testing procedure due to mobility-related limitations were assigned a score of 0 for each respective test. Participants unable (e.g. temporary medical condition, wheel chair use, severely impaired sight, lack of suitable a chair) or unwilling to do the tests were assigned a missing score for the respective tests (n = 9 for all tests, n = 3 for one test only). A SPPB sum score was calculated (range 0–12) when at least two tests were completed. When one test was not completed, the maximal score was lowered accordingly. Higher scores indicate better performance. The SPPB is a validated and frequently used tool in older people, with low SPPB sum scores predicting falls, loss of independence and mortality [25]. Physical activities Level of physical activity Present level of physical activity was assessed with a self-report scale by Grimby [27] with slight modifications. Both the lowest and the highest category of the initial scale were divided into two categories. The resulting 7-point scale depicted their level of physical activity over the last year: 0) mostly resting, or lying down, 1) hardly any activity, mostly sitting, 2) light physical activity, such as light household tasks, 3) moderate physical activity for about 3 h a week: walking longer distances, cycling and domestic work, 4) moderate physical activity for at least 4 h a week or heavier physical activity 1–2h a week, 5) heavier physical activity or moderate exercise for at least 3 h a week, and 6) competitive sports. This scale is feasible in older independent populations as it is easy and quick to use and it also rates domestic activities [24]. Barriers to physical activity The questionnaire on barriers to physical activity was developed by an expert panel for our previous study (SCAMOB) and further developed for the present study. The scale includes 17 items under the themes of poor health, fear and negative experiences, lack of knowledge, lack of time and interest, lack of company and unsuitable environment [28]. Each item is rated as yes or no. Rantanen et al. BMC Public Health 2012, 12:1018 Page 7 of 17 http://www.biomedcentral.com/1471-2458/12/1018 Avoidance of moving outdoors Avoidance of moving outdoors was assessed with two questions: “Do you avoid moving outdoors during day time?”,“Do you avoid moving outdoors in the evening?” with response options yes and no. Those responding “yes”were asked the reasons for avoidance. These questions identify persons with fear of moving outdoors [29]. Unmet physical activity need Unmet physical activity need is the feeling that one’s level of physical activity is inadequate, and thus distinct from the recommended amount of physical activity. Unmet physical activity need was studied by the questions “Do you feel that you would have the opportunity to increase your level of physical activity level if someone recommended you do so?”and “Would you like to increase your level of physical activity?”The response options were yes and no. Participants who felt that they had no opportunity to increase their physical activity even though they were willing to do so, were defined as experiencing unmet physical activity need [30]. Environmental factors Perceived environmental barriers and facilitators for mobility Barriers and facilitators to mobility in the outdoor and entrance environments of the home were examined as perceived by the participants using standardized questionnaires. The questions on environmental barriers and facilitators were developed by an expert panel for an earlier study (SCAMOB)[13]. For this study, new items were added to this list by an expert group (gerontology, occupational and physical therapy, human geography) with extensive experience in research on environmental effects and health outcomes. Participants were asked whether certain environmental features hindered or facilitated their possibilities for moving outdoors, with the response options yes and no. Altogether, the questionnaire comprised 15 environmental barriers and 12 facilitators for outdoor mobility and six barriers and seven facilitators for mobility in home entrance areas. In addition, three questions about the availability of suitable exercise facilities (outdoor facilities for physical activity, such as walking routes or ski tracks; a park or other green area; and indoor exercise facilities, such as a gym or public swimming pool) within walking distance from the home were asked (yes/no). Type of housing and neighborhood In the initial phone interview the type of dwelling (apartment block, row house, semi-detached or detached house) was self-reported. At baseline, the interviewer registered the type of dwelling as well as the type of neighborhood (urban, suburban, rural). The neighborhood areas were later confirmed by a researcher from the location on amap. Objective physical environmental barriers Physical environmental barriers in the home and its immediate surroundings constitute an objectively observable factor that can be rated in terms of current standards and guidelines for good housing design in the national context concerned. The environment is described on the basis of standards and guidelines [47] and assessed by professionals. The Housing Enabler methodology rests on 20 years of methodological development, empirical research and practice application [48]. Since a complete Housing Enabler assessment [49] is complex and time-consuming, we used selected portions of a reduced version; the Housing Enabler Screening Tool [50]. To develop this tool, based on statistical analyses with data from three comprehensive datasets with personal and environmental component data as well as expert panels, the core items of the environmental component of the complete Housing Enabler instrument were identified [31,50]. That is, the physical environmental barriers that are most crucial in relation to the occurrence of functional limitations and the generation of accessibility problems were identified. Whereas the environmental component of an earlier version of the complete instrument [51] contained 188 items, the reduced set had 61. In a subsequent study, this item pool was used as a starting point for creating the Screening Tool. A pilot version was tested for feasibility and inter-rater reliability [50], and after further revisions, the Housing Enabler Screening Tool was established [48,49]. In the LISPE Project, major parts of two of the three sections were used, namely 17 items of the section exterior surroundings and 11 items of the section entrances. The screening involves visiting a dwelling to observe and document the environmental barriers that exist. For three participants the environmental evaluation was not performed since the interview was held in a different location than their home. Transportation The participants were asked how often they drove a car, travelled by car as a passenger, used public transport such as a bus or a train, and used a taxi or Special Transportation Services. The response options were 1) daily or almost daily, 2) a few times a week, 3) a few times a month, 4) a few times a year, 5) less than once a year, or 6) never. Participants who answered that they never drove a car were asked about their driving history: 1) has never driven a car, or 2) had stopped driving a car. All participants were asked whether they were able to use public transport for daily travelling, and if not, why not. Rantanen et al. BMC Public Health 2012, 12:1018 Page 8 of 17 http://www.biomedcentral.com/1471-2458/12/1018 We have collected data over a period of six months, starting in winter and ending in summer. The climate in central Finland is characterized by cold winters with ice and snow, and moderately warm summers. Consequently, the extended data collection period may have introduced additional variability in life-space mobility. Although the outdoor temperatures may not affect the lives of the Finnish people too much, people are more likely to stay indoors in winter to avoid walking on slippery surfaces. In this study, it is possible to take outdoor temperature into account. It should also be borne in mind that a wide range of weather conditions are a fact of life in our study area. Consequently, the six-month data collection period may increase the face-validity of the data. Our participants were rather old at baseline and therefore we tried to restrict the length of the interview so as not to burden them too much. Consequently, some aspects relevant for life-space mobility have possibly been left out of the study. For example, we were able objectively to assess physical fitness only for lower extremity performance. Conclusions A specific strength of this study is that we have collected data on a topic important for aging societies. We have used a novel approach which enables us to study the interactions between environmental features and individual characteristics that underlie the life-space of older people. The results of this study have the potential to contribute to improvements in strategies to postpone or prevent progression to disability and loss of independence. Abbreviations ADL: Activities of Daily Living; CAPI: Computer-Assisted Personal Interviewing; CES-D: Centre for Epidemiologic Studies Depression Scale; HE: Housing Enabler; IADL: Instrumental Activities of Daily Living; IPA: Impact on Participation and Autonomy; LISPE: Life-Space Mobility in Old Age; LSA: LifeSpace Assessment; MMSE: Mini-Mental State Examination; SCAMOB: Screening and Counseling for Physical Activity and Mobility; SPPB: Short Physical Performance Battery; WHOQOL-BREF: World Health Organization Quality of Life Scale Short Version. Competing interests Together with dr. B. Slaug, SI is the copyright holder and owner of the Housing Enabler (HE) methodology, provided as a commercial product (see www.enabler.nu). The remaining authors declare that they do not have competing interests. Authors’contributions This manuscript was drafted by all authors. Each author was responsible for writing part of the manuscript and critically revising the complete manuscript. Additional, author contributions were: TR contributed to the concept and design of the study, acquisition of data, and analyses and interpretation of data as the Principal Investigator. EP contributed to the concept and design of the study with specific focus on physical function and activity, acquisition of data and quality assurance, and analyses and interpretation of data. AV contributed to the concept and design of the study with specific focus on sensory function and falls. JE contributed to the design of the study with specific focus on disparity in physical activity, and acquisition of data as interviewer. MS contributed to the design of the study with specific focus on personal goals, and acquisition of data as interviewer. LTT contributed to the design of the study with specific focus on the walking activity, and acquisition of data for the substudy. MK contributed to the design of the study, statistical and methodological support, acquisition of data and quality assurance, and analyses and interpretation of data. EMP contributed to the design and coordination of the study, participant recruitment, and acquisition of data and quality assurance. SS contributed to the concept and design of the study with specific focus on physical and mobility function. SI contributed to the concept and design of the study with specific focus on the environmental assessment, and acquisition of environmental data. MR contributed to the concept and design of the study with specific focus on mobility function, life space and environmental gerontology, acquisition of data and quality assurance, and analyses and interpretation of data. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank Dr. Tiina-Mari Lyyra for her help in planning the project and all the interviewers for their valuable work with the data collection. The LISPE project is funded by the Academy of Finland, the Future of Living and Housing (ASU-LIVE; grant number 255403) program and Finnish Ministry of Education and Culture. Additionally Anne Viljanen is Figure 3 Flow chart of the substudy. Rantanen et al. BMC Public Health 2012, 12:1018 Page 15 of 17 http://www.biomedcentral.com/1471-2458/12/1018 funded by a personal grant from the Academy of Finland (grant number 251723) and Susanne Iwarsson by the Ribbing Foundation, Lund, Sweden. The funding agencies played no role in the design, conduct, data management, analysis or manuscript preparation related to this article. Author details 1 Gerontology Research Center and Department of Health Sciences, University of Jyväskylä, P.O.Box 35, Jyväskylä FI-40014, Finland. 2 Department of Health Sciences, Lund University, Lund, Sweden. Received: 14 November 2012 Accepted: 19 November 2012 Published: 22 November 2012 References 1. Satariano WA, Guralnik JM, Jackson RJ, Marottoli RA, Phelan EA, Prohaska TR: Mobility and aging: New directions for public health action. Am J Public Health 2012, 102:1508–1515. 2. Cohen-Mansfield J, Shmotkin D, Hazan H: Homebound older persons: prevalence, characteristics, and longitudinal predictors. Arch Gerontol Geriatr 2012, 54:55–60. 3. Nagi SZ: An epidemiology of disability among adults in the United States. Milbank Mem Fund Q Health Soc 1976, 54:439–467. 4. Verbrugge LM, Jette AM: The disablement process. Soc Sci Med 1994, 38:1–14. 5. Lawton MP, Nahemow L: Ecology and aging process.InThe psychology of adult development and aging. Edited by Eisdorfer C, Lawton MP. Washington DC: American Psychological Association; 1973:619–674. 6. Viljanen A, Kaprio J, Pyykko I, Sorri M, Koskenvuo M, Rantanen T: Hearing acuity as a predictor of walking difficulties in older women. J Am Geriatr Soc 2009, 57:2282–2286. 7. Viljanen A, Kaprio J, Pyykko I, Sorri M, Pajala S, Kauppinen M, Koskenvuo M, Rantanen T: Hearing as a predictor of falls and postural balance in older female twins. J Gerontol A Biol Sci Med Sci 2009, 64:312–317. 8. Kulmala J, Viljanen A, Sipila S, Pajala S, Parssinen O, Kauppinen M, Koskenvuo M, Kaprio J, Rantanen T: Poor vision accompanied with other sensory impairments as a predictor of falls in older women. Age Ageing 2009, 38:162–167. 9. Peel NM: Epidemiology of falls in older age. Can J Aging 2011, 15:1–13. 10. Mänty M, Heinonen A, Viljanen A, Pajala S, Koskenvuo M, Kaprio J, Rantanen T: Outdoor and indoor falls as predictors of mobility limitation in older women. Age Ageing 2009, 38:757–761. 11. Shumway-Cook A, Patla A, Stewart A, Ferrucci L, Ciol MA, Guralnik JM: Environmental components of mobility disability in community-living older persons. J Am Geriatr Soc 2003, 51:393–398. 12. Balfour JL, Kaplan GA: Neighborhood environment and loss of physical function in older adults: evidence from the alameda county study. Am J Epidemiol 2002, 155:507–515. 13. Rantakokko M, Iwarsson S, Mänty M, Leinonen R, Rantanen T: Perceived barriers in the outdoor environment and development of walking difficulties in older people. Age Ageing 2012, 41:118–121. 14. Wahl HW, Fange A, Oswald F, Gitlin LN, Iwarsson S: The home environment and disability-related outcomes in aging individuals: what is the empirical evidence? Gerontologist 2009, 49:355–367. 15. Clarke P, Nieuwenhuijsen ER: Environments for healthy ageing: a critical review. Maturitas 2009, 64:14–19. 16. Baker PS, Bodner EV, Allman RM: Measuring life-space mobility in community-dwelling older adults. J Am Geriatr Soc 2003, 51:1610–1614. 17. Ward RA, Kilburn H: Community access and satisfaction: racial differences in later life. Int J Aging Hum Dev 1983, 16:209–219. 18. Tinetti ME, Ginter SF: The nursing home life-space diameter. A measure of extent and frequency of mobility among nursing home residents. J Am Geriatr Soc 1990, 38:1311–1315. 19. Peel C, Sawyer Baker P, Roth DL, Brown CJ, Brodner EV, Allman RM: Assessing mobility in older adults: the UAB study of aging life-space assessment. Phys Ther 2005, 85:1008–1119. 20. World Health Organization: ICF: international classification of functioning, disability and health. Geneva: World Health Organization; 2002. 21. Auger C, Demers L, Gelinas I, Miller WC, Jutai JW, Noreau L: Life-space mobility of middle-aged and older adults at various stages of usage of power mobility devices. Arch Phys Med Rehabil 2010, 91:765–773. 22. The WHOQOL Group: Development of the world health organization WHOQOL-BREF quality of life assessment. Psychol Med 1998, 28:551–558. 23. Mänty M, Heinonen A, Leinonen R, Törmakangas T, Sakari-Rantala R, Hirvensalo M, von Bonsdorff MB, Rantanen T: Construct and predictive validity of a self-reported measure of preclinical mobility limitation. Arch Phys Med Rehabil 2007, 88:1108–1113. 24. Leinonen R, Heikkinen E, Hirvensalo M, Lintunen T, Rasinaho M, Sakari-Rantala R, Kallinen M, Koski J, Mottonen S, Kannas S, Huovinen P, Rantanen T: Customer-oriented counseling for physical activity in older people: study protocol and selected baseline results of a randomizedcontrolled trial (ISRCTN 07330512). Scand J Med Sci Sports 2007, 17:156–164. 25. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB: A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 1994, 49:M85–M94. 26. Mänty M, Sihvonen S, Hulkko T, Lounamaa A: Iäkkäiden henkilöiden kaatumistapaturmat. Opas kaatumisten ja murtumien ehkäisyyn. Helsinki: Publications of the National Public Health Institute B; 2007:29. 27. Grimby G: Physical activity and muscle training in the elderly. Acta Med Scand Suppl 1986, 711:233–237. 28. Rasinaho M, Hirvensalo M, Leinonen R, Lintunen T, Rantanen T: Motives for and barriers to physical activity among older adults with mobility limitations. J Aging Phys Act 2007, 15:90–102. 29. Rantakokko M, Mänty M, Iwarsson S, Törmakangas T, Leinonen R, Heikkinen E, Rantanen T: Fear of moving outdoors and development of outdoor walking difficulty in older people. J Am Geriatr Soc 2009, 57:634–640. 30. Rantakokko M, Iwarsson S, Hirvensalo M, Leinonen R, Heikkinen E, Rantanen T: Unmet physical activity need in old age. J Am Geriatr Soc 2010, 58:707–712. 31. Carlsson G, Schilling O, Slaug B, Fänge A, Ståhl A, Nygren C, Iwarsson S: Towards a screening tool for housing accessibility problems: a reduced version of the housing enabler. J Appl Gerontol 2009, 28:59–80. 32. Pynnönen K, Törmakangas T, Heikkinen RL, Rantanen T, Lyyra TM: Does social activity decrease risk for institutionalization and mortality in older people? J Gerontol B Psychol Sci Soc Sci 2012, 67:765–774. 33. Cardol M, de Haan RJ, de Jong BA, van den Bos GA, de Groot IJ: Psychometric properties of the impact on participation and autonomy questionnaire. Arch Phys Med Rehabil 2001, 82:210–216. 34. Kanelisto K, Salminen A: IPA-kyselylomake valinnoista ja osallistumisesta jokapäiväisessä elämässä: toimintakyvyn itsearviointimenetelmä aikuisille, joilla on fyysisiä toimintarajoitteita. Helsinki: Kelan tutkimusosasto; 2011. 35. Laukkanen P, Karppi P, Heikkinen E, Kauppinen M: Coping with activities of daily living in different care settings. Age Ageing 2001, 30:489–494. 36. Lyyra TM, Lyyra AL, Lumme-Sandt K, Tiikkainen P, Heikkinen RL: Social relations in older adults: secular trends and longitudinal changes over a 16-year follow-up. Arch Gerontol Geriatr 2010, 51:133–138. 37. Tiikkainen P, Heikkinen RL: Associations between loneliness, depressive symptoms and perceived togetherness in older people. Aging Ment Health 2005, 9:526–534. 38. Pohjolainen P, Heikkinen E, Lyyra AL, Helin S, Tyrkkö K: Socio-economic status, health and life-style in two elderly cohorts in jyväskylä. Scand J Soc Med Suppl 1997, 52:1–65. 39. Subramanian SV, Huijts T, Avendano M: Self-reported health assessments in the 2002 world health survey: How do they correlate with education? Bull World Health Organ 2010, 88:131–138. 40. Ritchie CS, Locher JL, Roth DL, McVie T, Sawyer P, Allman R: Unintentional weight loss predicts decline in activities of daily living function and life-space mobility over 4 years among community-dwelling older adults. J Gerontol A Biol Sci Med Sci 2008, 63:67–75. 41. Folstein MF, Folstein SE, McHugh PR: Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975, 12:189–198. 42. Radloff LS: The CES-D scale: a self-reported scale for research in the general population. Applied Psychol Measurement 1977, 1:385–401. 43. Laitinen A, Koskinen S, Härkänen T, Reunanen A, Laatikainen L, Aromaa A: A nationwide population-based survey on visual acuity, near vision, and self-reported visual function in the adult population in Finland. Ophthalmology 2005, 112:2227–2237. 44. Viljanen A, Kulmala J, Rantakokko M, Koskenvuo M, Kaprio J, Rantanen T: Fear of falling and coexisting sensory difficulties as predictors of Rantanen et al. BMC Public Health 2012, 12:1018 Page 16 of 17 http://www.biomedcentral.com/1471-2458/12/1018 mobility decline in older women. J Gerontol A Biol Sci Med Sci 2012, 67:1230–1237. 45. Heistaro S: Methodology report: health 2000 survey. Helsinki: National Public Health Institute; 2008. 46. Little BR: Personal projects. A rationale and method for investigation. Environ Behav 1983, 15:273–309. 47. Preiser WFE, Ostroff E: Universal design handbook. New York: McGraw-Hill; 2001. 48. Iwarsson S, Slaug B, Haak M: Current developments of the housing enabler methodology. Br J Occup Ther 2012, in press. 49. Iwarsson S, Slaug B: Housing enabler –A method for rating/screening and analysing accessibility problems in housing. Manual for the complete instrument and screening tool. Lund & Staffanstorp, Sweden: Veten & Skapen HB och Slaug Enabling Development; 2010. 50. Iwarsson S, Slaug B, Malmgren Fänge A: The housing enabler screening tool: feasibility and inter-rater reliability in a real-estate company practice context. J Appl Gerontol 2011, 31:641–660. 51. Iwarsson S, Slaug B: The housing enabler. An instrument for assessing and analysing accessibility problems in housing. Nävlinge and Staffanstorp: Veten & Skapen HB & Slaug Data Management; 2001. 52. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW: Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA 1963, 185:914–919. 53. Lawton MP, Brody EM: Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 1969, 9:179–186. 54. Nosikov A, Gudex G: EUROHIS. Developing common instruments for health surveys. Amsterdam: WHO Regional Office for Europe, IOS Press; 2003. 55. Beekman ATF, Deeg DJ, van Limbeek J, Braam AW, de Vries MZ, van Tilburg W: Criterion validity of the center for epidemiologic studies depression scale (CES-D): results from a community-based sample of older subjects in the Netherlands. Psychol Med 1997, 27:231–235. 56. Radloff LS, Teri L: Use of the center for epidemiologic studies depression scale with older adults. Clinical Gerontologist: The J of Aging and Mental Health 1986, 5:119–136. 57. Hétu R, Getty L, Philibert L, Desilets F, Noble W, Stephens D: Mise au point d'un outil Clinique pour la mesure d'incapacités auditives et de handicaps. J Speech-Lang Path Audiol 1994, 18:83–95. 58. Noble W, Atherley G: The hearing measurement scale: a questionnaire for the assessment of auditory disability. J Audit Res 1970, 10:229–250. 59. Aromaa A, Koskinen S, and Kansanterveyslaitos: Health and functional capacity in Finland: baseline results of the health 2000 health examination survey. Helsinki: National Public Health Institute; 2004. 60. Hietanen A, Era P, Henrichsen J, Rosenhall U, Sorri M, Heikkinen E: Hearing among 75-year-old people in three Nordic localities: a comparative study. Int J Audiol 2005, 44:500–508. 61. Salmela-Aro K, Read S, Nurmi J, Koskenvuo M, Kaprio J, Rantanen T: Personal goals of older female twins.Genetic and environmental effects. Eur Psychol 2009, 14:160–167. 62. Lawton MP, Moss MS, Winter L, Hoffman C: Motivation in later life: personal projects and well-being. Psychol Aging 2002, 17:539–547. 63. Davis MG, Fox KR: Physical activity patterns assessed by accelerometry in older people. Eur J Appl Physiol 2007, 100:581–589. 64. United Nations, Economic and Social Commission for Asia and the Pacific: Guidelines on the application of new technology to population data collection and capture. http://www.unescap.org/stat/pop-it/pop-guide/index.asp. 65. von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP: STROBE initiative: the strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 2007, 370:1453–1457. 66. Hardy SE, Allore H, Studenski SA: Missing data: a special challenge in aging research. J Am Geriatr Soc 2009, 57:722–729. doi:10.1186/1471-2458-12-1018 Cite this article as: Rantanen et al.:Individual and environmental factors underlying life space of older people –study protocol and design of a cohort study on life-space mobility in old age (LISPE). BMC Public Health 2012 12:1018. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit Rantanen et al. BMC Public Health 2012, 12:1018 Page 17 of 17 http://www.biomedcentral.com/1471-2458/12/1018