Shiny Dashboard: Reference Values of Physical Performance for Singaporean Adult Population

This post presents a simple dashboard built with R Shiny, which allows users to find out age- and sex-specific reference values of various physical performance tests for older adults.

Nien Xiang Tou


February 3, 2023

Physical function is an important indicator of health. Decline of physical function is inevitable with age, but the rate of decline differs among individuals. Several physical performance tests have been established to monitor changes in physical function as individuals age. This blog post presents a dashboard created using R Shiny to show published age-group specific and sex-specific reference values of various physical performance tests for the Singaporean adult population.

The Reference Values of Physical Performance Dashboard. Source: Author

Importance of Physical Performance Tests

Physical function often deteriorates with age, and such decline is associated with adverse health outcomes, onset of disability as well as mortality. Given the rapidly ageing population globally and locally in Singapore, the burden associated with age-associated functional decline is a key public health concern. Hence, it is imperative for prompt screening of functional decline in the population for targeted interventions to delay functional dependence as best as possible.

Physical performance tests are valid and reliable ways to assess physical function, and several tests have been developed specifically for the older adult population. These physical performance tests have been demonstrated to predict adverse health events. For example,a recent cohort study reported that the ability to balance on one leg for 10 seconds is associated with all-cause mortality (Araujo et al. 2022). Such empirical evidence demonstrates the value of administering physical performance tests.

Importantly, physical performance tests are very economical as they are often easy to administer and do not require specialised equipment. For example, a sit-to-stand test only requires a chair to administer and can be performed independently, yet the test performance has been shown to predict disability in activities of daily living (Zhang et al. 2013). With such tests, individuals are able to easily evaluate their physical function with minimal resources. Therefore, physical performance tests are feasible and valid ways to monitor physical function at a population level.

Evaluation of Physical Performance

Every test is designed to distinguish certain abilities or attributes among different individuals. Clearly, the value of administering a physical performance test is to determine one’s functional ability and interpret that relative to the context of the individual. Akin to the score standards set for Singapore fitness tests such as the National Physical Fitness Award (NAPFA) or Individual Physical Proficiency Test (IPPT), it is necessary for older adults’ physical performance tests to derive normative value scores to stratify performance abilities.

The Yishun Study is a local population-based cross-sectional study that determined normative values of various physical performance tests in a representative sample of community-dwelling younger and older adults. This study employed random sampling methods to recruit over 500 participants from the town of Yishun, filling quotas of 20-40 participants in each sex and age group (i.e., 10-year age groups between 21 and 60 years old and 5-year age groups after 60 years up to 80 years). The age- and sex-specific reference values of various physical performance tests have been published in peer-reviewed journals (Choo et al. 2021; Lee et al. 2021; Pang et al. 2021; Abdul Jabbar et al. 2021; Lau et al. 2020). These values help us to interpret the performance of these tests with respect to each specific age group and gender.

Reference Values of Physical Performance Dashboard

With the aim of helping knowledge users to better interpret these reference values, I created a simple dashboard with R Shiny to present score bands for five physical performance tests based on the Yishun Study data: 1) timed up and go test, 2) five times sit to stand test, 3) six metre walk test, 4) handgrip strength test, and 5) knee extension strength test.

This dashboard assumes a Gaussian or normal distribution. The published mean and standard deviation values are used to estimate the distribution of performance scores for each age and gender group. Performance categories are stratified based on standardised scores, also known as Z-scores, which represent how many standard deviations below or above the mean value. This allows ease of inferring the probability of a certain score. Assuming the mean and standard deviation values are true population parameters, approximately 68% and 95% of scores observed would fall within 1 and 2 standard deviations from the mean, respectively. Using such approach, performance scores can be compared with respect to the mean score determined for each age group.

Physical performance test scores are stratified into a total of seven categories. Please refer to the table below for the standardised scores that correspond to each category.

How to use the dashboard

This dashboard simply requires two inputs from the user: age (in integer) and gender. As the published data was derived from only adults aged 21 years and older, the minimum age input is 21. After, you may toggle between the tabs to access the score bands for each of the five physical performance tests for your age and gender group. The scores are presented in a density plot and table format, with each performance category colour coded. I have also included a short description of each test on the left panel. The video file below presents a quick demonstration of the dashboard.


Abdul Jabbar, Khalid, Wei-Ting Seah, Lay Khoon Lau, Benedict Wei-Jun Pang, Daniella Hui-Min Ng, Queenie Lin-Ling Tan, Kexun Kenneth Chen, Jagadish Mallya Ullal, Tze-Pin Ng, and Shiou-Liang Wee. 2021. “Fast Gait Spatiotemporal Parameters in Adults and Association with Muscle Strength The Yishun Study.” Gait & Posture 85 (March): 217–23.
Araujo, Claudio Gil, Christina Grüne de Souza e Silva, Jari Antero Laukkanen, Maria Fiatarone Singh, Setor Kwadzo Kunutsor, Jonathan Myers, João Felipe Franca, and Claudia Lucia Castro. 2022. “Successful 10-Second One-Legged Stance Performance Predicts Survival in Middle-Aged and Older Individuals.” British Journal of Sports Medicine 56 (17): 975–80.
Choo, Pei Ling, Nien Xiang Tou, Benedict Wei Jun Pang, Lay Khoon Lau, Khalid Abdul Jabbar, Wei Ting Seah, Kenneth Kexun Chen, Tze Pin Ng, and Shiou-Liang Wee. 2021. “Timed Up and Go (TUG) Reference Values and Predictive Cutoffs for Fall Risk and Disability in Singaporean Community-Dwelling Adults: Yishun Cross-Sectional Study and Singapore Longitudinal Aging Study.” Journal of the American Medical Directors Association 22 (8): 1640–45.
Lau, Lay Khoon, Shiou Liang Wee, Wei Jun Benedict Pang, Kexun Kenneth Chen, Khalid Abdul Jabbar, Philip Lin Kiat Yap, Jagadish Ullal Mallya, et al. 2020. “<P>Reference Values of Gait Speed and Gait Spatiotemporal Parameters for a South East Asian Population: The Yishun Study</p>.” Clinical Interventions in Aging Volume 15 (September): 1753–65.
Lee, Shuen Yee, Pei Ling Choo, Benedict Wei Jun Pang, Lay Khoon Lau, Khalid Abdul Jabbar, Wei Ting Seah, Kenneth Kexun Chen, Tze Pin Ng, and Shiou-Liang Wee. 2021. “SPPB Reference Values and Performance in Assessing Sarcopenia in Community-Dwelling Singaporeans Yishun Study.” BMC Geriatrics 21 (1).
Pang, Benedict Wei Jun, Shiou-Liang Wee, Lay Khoon Lau, Khalid Abdul Jabbar, Wei Ting Seah, Daniella Hui Min Ng, Queenie Lin Ling Tan, Kenneth Kexun Chen, Mallya Ullal Jagadish, and Tze Pin Ng. 2021. “Sensorimotor Performance and Reference Values for Fall Risk Assessment in Community-Dwelling Adults: The Yishun Study.” Physical Therapy 101 (7).
Zhang, Fang, Luigi Ferrucci, Elsie Culham, E. Jeffrey Metter, Jack Guralnik, and Nandini Deshpande. 2013. “Performance on Five Times Sit-to-Stand Task as a Predictor of Subsequent Falls and Disability in Older Persons.” Journal of Aging and Health 25 (3): 478–92.