The association of the neighbourhood built environment with objectively measured physical activity in older adults with and without lower limb osteoarthritis

Abstract

BackgroundThis study examined the associations of objectively measured neighbourhood built environment characteristics with objectively measured physical activity (PA) in older people with and without lower limb osteoarthritis (LLOA), and assessed whether these relationships differ between both groups.MethodsData from the Dutch component of the European Project on OSteoArthritis were used. American College of Rheumatology classification criteria were used to diagnose LLOA (knee and/or hip osteoarthritis). Daily average time spent on total PA and separate PA intensity categories, including light PA, low-light PA, high-light PA, and moderate to vigorous PA, were measured using Actigraph GT3X accelerometers. Geographic Information Systems were used to measure street connectivity (number of street connections per km2) and distances (in km) to resources (health care resources, retail resources, meeting places, and public transport) within neighbourhoods. Multiple Linear Regression Analyses were used to examine the associations between measures of the neighbourhood built environment and PA, adjusted for several confounders.ResultsOf all 247 participants (66–85 years), 41 (16.6 %) had LLOA. The time spent on any PA did not differ significantly between participants with and without LLOA (LLOA: Mean = 268.3, SD = 83.3 versus non-LLOA: Mean = 275.8, SD = 81.2; p = 0.59). In the full sample, no measures of the neighbourhood built environment were statistically significantly associated with total PA. Larger distances to specific health care resources (general practice and physiotherapist) and retail resources (supermarket) were associated with more time spent on PA in older people with LLOA than in those without LLOA. In particular, the associations of light and high-light PA with distances to these specific resources were stronger in participants with LLOA compared to their counterparts without LLOA.ConclusionsSpecific attributes of the neighbourhood built environment are more strongly associated with PA in older people with LLOA than in those without LLOA. Knowledge on the relationship between objectively measured neighbourhood characteristics and PA in older people with and without LLOA could be used to inform policymakers and city planners about adaptation of neighbourhoods and their infrastructures to appropriately facilitate PA in healthy and functionally impaired older adults.

Associations of neighborhood walkability with intensity‐ and bout‐specific physical activity and sedentary behavior of older adults in Japan

“…Some recent studies using accelerometers with older adult participants have focused on associations of environment attributes with overall MVPA and LPA, but they did not examine associations with bout‐specific MVPA, overall SB, and prolonged SB . Hawkesworth et al ., for example, found that population density was unfavorably associated with LPA time, but walkability was not .…”

“…The strengths of the present study include the use of objective measures of both walkability and activity outcomes, and descriptions of detailed activity patterns, which goes beyond previous studies examining associations with overall MVPA and LPA . We provided results from a seldom‐studied Asian population that differed from prior studies of associations of built environment with activity carried out primarily in Western countries.…”

The Longitudinal Aging Study Amsterdam: cohort update 2019 and additional data collections

“…The main environmental data that are currently available in LASA are shown in Table 6 and include: urbanization grade (i.e., number of residents/km 2 ), population demographics (e.g., age-and sex-distribution, marital status and proportions of immigrants and ethnic minority groups), household characteristics (e.g., average household size), educational level (e.g., proportions of individuals who attained high, intermediate or low education), income (e.g., average income and proportion of income recipients), socioeconomic status (e.g., socioeconomic status score), social security (e.g., proportion of social security beneficiaries), air pollution (e.g., concentrations of air pollutants), noise (e.g., road-traffic, rail-traffic and air-traffic noise), crime rates (e.g., number of criminal offenses per 1000 residents), availability of facilities (e.g., in terms of density of/proximity to specific health care facilities and socio-cultural facilities), physical environmental characteristics (e.g., green space and water) and daily average weather parameters (e.g., daily average temperature and humidity). Several of these variables have been used in recent LASA studies [35,[37][38][39][40][41].…”

Habitabilidad urbana en el espacio público, el caso del centro histórico de Toluca, Estado de México

“…(2012), se adapta la evaluación de accesibilidad peatonal del viario (calle) hacia los indicadores de continuidad entre las calles por obstáculos y por ancho de acera. Los indicadores de conectividad contemplados como cualidad de legibilidad que permiten a las personas entender las características espaciales del espacio público relacionado a las rutas (De Schiller y Evans, 2006), se imple-mentan a partir del cálculo de la densidad de intersecciones de calle (intersection density) y el indicador facilidad en el desplazamiento por longitud de manzana o distancia entre intersecciones (block lenght), esto mediante formulaciones estándar de conectividad de las calles usadas para investigación (Witten et al, 2012;Berrigan et al, 2010;Timmermans et al, 2016) en cuenta para la evaluación la distancia mínima de 0.8 m como estándar de paso para una silla de ruedas con acompañante (Seduvi, 2007).…”

“…Se contabilizaron las intersecciones de calles en bloques de 400 x 400 m y se ajustaron a una densidad de 1 km 2 con fines comparativos. El modo de calcular la conectividad = número de intersecciones/ área seleccionada en km 2 (Bourdic et al, 2012), se ha empleado de manera relativa para caracterizar el entorno construido (Witten et al, 2012;Timmermans et al, 2016) y para evaluar la movilidad peatonal y en bicicleta (Dill, 2004). En el proceso de evaluación, se emplearon como guía algunas recomendaciones de diseño urbano consideradas amigables para el peatón (150-160) y se tomaron 150 por km 2 como inicio del intervalo superior; asimismo, para las orientadas a movilidad vehicular (35), nuestro valor mínimo fue de 56, por lo que se tomaron 50 por km 2 como inicio del intervalo inferior (Ewing, 1999;Bourdic et al, 2012), y un punto intermedio de 100.…”