Background Physical fitness is a key component of independent living and healthy ageing. For the measurement of physical fitness in older adults, the Senior Fitness Test is a commonly used tool. The objective of this study is to calculate sex- and age-specific normative values for handgrip strength and components of the Senior Fitness Test for older adults (65–75 years) in Germany. Methods Cross-sectional data of 1657 community-dwelling older adults residing in Bremen, Germany (53% female) were included in this study. Physical fitness was assessed using the following measurements of the Senior Fitness Test battery: 30s-chair stand test, 2 min-step test, sit-and-reach test, and back scratch test. In addition, handgrip strength was measured using a Saehan DHD-3 digital hand dynamometer SH1003. Sex- and age specific normative values were calculated for the 1st, 3rd, 10th, 25th, 50th, 75th, 90th, 97th, and 99th percentile using the GAMLSS method. Results The normative values show differences dependent on sex and age. For handgrip strength, the 30s-chair stand test and the 2 min-step test, normative values were higher for men, while women reached higher values in the sit-and-reach test and the back scratch test. For both, men and women, normative values declined with age. Conclusions This study provides sex- and age-specific normative values for handgrip strength and components of the Senior Fitness Test for older adults in Germany. They might be useful for future research and for the application in practice.

Purpose: The PRECEDE-PROCEED model (PPM) is a community-based participatory research (CBPR) framework for health promotion, yet the direct application of the PPM into practice is unclear. This paper describes how the PPM was adapted for the development and application of a pilot intervention study to promote outdoor physical activity (PA) in older adults (OUTDOOR ACTIVE). We illustrate the steps and adaptations we applied to put the PPM into practice and present the developed interventions. Design: The PPM was adapted by incorporating a socio-ecological model. This ensured the design of any resultant intervention would explicitly address multi-level determinants of physical activity. The list of possible program components to select from for the design of an intervention was also extended. Setting: Bremen, Germany. Participants: Participants in the intervention development were 924 noninstitutionalized older adults, aged 65-75 years (response: 25.2%), living in Bremen-Hemelingen, Germany. For implementation of the intervention and to ensure sustainability, several groups of stakeholders were involved throughout the process. Methods: A mixed method design was employed (e.g., focus groups, quantitative survey) to identify determinants. A round table and participatory workshops were held to involve the target group and community stakeholders in the design of an intervention using the adapted PPM model. Results: A conceptual model was developed illustrating the integration of a socio-ecological model into the PPM. The model received ecological validity, as it was affirmed by community stakeholders as an appropriate method for designing a community-level PA intervention. Target goals to address PA determinants were selected by target group members. An intervention to meet the goals was developed and implemented with target group input. Conclusion: The adapted PPM is a promising starting point for developing multi-level interventions. Steps should be taken to ensure all social groups are participating in the process and all levels of determinants are addressed.

Background Regular physical activity (PA) is an important strategy for healthy ageing. Socioeconomic status was found to be a key determinant of PA, however, evidence on associations between socioeconomic status and PA among older adults is limited. The aim of this study was to contribute to research on the associations of socioeconomic status and PA among older adults by including self-reported and objectively measured PA data. Furthermore, we examined the self-reported PA data more closely by looking at the activities separately. Methods Cross-sectional data of 1507 participants (52.5% female) of the OUTDOOR ACTIVE study between 65 and 75 years, residing in Bremen, Germany, were included in the analyses. Self-reported PA was assessed via questionnaire and comprised all organised and non-organised activities. For analyses, mean hours per week of total and moderate to vigorous PA, and mean metabolic equivalents per week were used. Objectively measured PA was assessed using accelerometers over seven consecutive days. Socioeconomic status was included as an additive social class index containing education, income, and occupation. To test for associations between PA and socioeconomic status, linear regressions were carried out. Results Self-reported PA showed significant negative associations with socioeconomic status for both men and women. Objectively measured PA was positively associated with socioeconomic status, which was significant in men but not in women. When examining physical activities separately, time spent on housework, gardening, biking, and walking decreased with increasing socioeconomic status. Women in the second SES quintile and men in the third quintile reported the most, and women in the first quintile and men in the fifth quintile the least hours per week spent on exercise. Conclusions The results of this study contributed to the existing research gap on the associations of socioeconomic status and PA among older adults. Moreover, we provided information on both self-reported and objectively measured PA, and showed the discrepancies in the two methods’ results. These findings can help to develop PA promotion interventions targeting specific socioeconomic status groups and to develop accurate, valid, and reliable self-reported and objective measurements of PA for older adults.

Background Physical activity (PA) is one of the key determinants of healthy ageing. Research showed that time allocation plays an important role in PA. Therefore, an understanding of the time use of older adults is crucial for developing PA programs. The aim of this study was to examine the associations of time allocation and objectively measured PA, and several health indicators in older adults. Methods In this cross-sectional study all 915 participants of the OUTDOOR ACTIVE study were included. The participants were 65 to 75 years old and resided in a subdistrict of Bremen, Germany (50.9% female). The active domains were derived from the SLOTH model (leisure activities, occupation, active transport, home-based activities). PA was objectively measured with accelerometers over seven consecutive days. Binary logistic regressions were used to test the associations of total PA and time spent in the domains with several health indicators (self-rated health, overweight, obesity, activities of daily living (ADL)). Results Participants over the age of 70 years were significantly less physically active than those under 70 years and women were significantly more physically active than men. Regardless of age and sex, most time was spent on home-based activities (women: 118.5 ± 87.8 min/day; men: 80.2 ± 69.4 min/day). Both PA and time spent on leisure activities were associated with a lower risk of bad self-rated health (0.36; 95%-CL: 0.20, 0.65 for PA; 0.93; 95%-CL: 0.87, 0.99 for leisure activities) and less limitations in ADL. PA and active transport seemed to lower the risk of overweight (0.39; 95%-CL: 0.25, 0.62 for PA; 0.80; 95%-CL: 0.69, 0.93 for active transport) and obesity (0.36; 95%-CL: 0.21, 0.60 for PA; 0.77; 95%-CL: 0.64, 0.92 for active transport). Having an occupation was associated with a lower risk of bad self-rated health (0.60; 95%-CL: 0.40, 0.92). Conclusions The results of this study provide insights in the time allocation to active domains and total PA of older adults, as well as the associations with health indicators. These findings have important implications for the development of PA programs and guidelines. Future research should examine the associations further in longitudinal studies.

The study of physical activity in older adults is becoming more and more relevant. For evaluation of physical activity recommendations, intensity-specific accelerometer cut-points are utilized. However, research on accelerometer cut-points for older adults is still scarce. The aim of the study was to generate placement-specific cut-points of ActiGraph GT3X+ activity counts and raw measures of acceleration to determine physical activity intensity in older adults. A further aim was to compare the validity of the generated cut-points for a range of different physical activities. The study was a single experimental trial using a convenience sample. Study participants were 20 adults aged 59 to 73 years. Accelerometers were worn at six different placements (one on each wrist, one on each ankle, and two at the hip) and breath-by-breath indirect calorimetry was used as the reference for energy. The experiment comprised of two parts; a) The first required participants to walk on a treadmill at incremental speeds (3.0–5.0 km·h-1), and b) Five different everyday activities (reading, cleaning, shopping, cycling, aerobics) were staged in the laboratory setting. Accelerometer cut-points (activity counts, raw data) were derived for each of the investigated placements by linear regression using the treadmill part. Performance of the cut-points was assessed by applying the cut-points to the everyday activities. We provide cut-points for six placements and two accelerometer metrics in the specific age group. However, the derived cut-points did not outperform published ones. More research and innovative approaches are needed for improving internal and external validity of research results across populations and age groups.