Smart Wearables: The Impact of Age & Income on Activity & What We Track


    Nov 14, 2022

    The use of health and fitness tech saw a significant uptick as the lockdown closed many gyms and curbed people’s mobility during the pandemic.

    To investigate the usage patterns and effects of wearables and apps, we teamed up with Anna Schneider, professor of business psychology at Fresenius University, and the global public opinion and data company YouGov.

    Our recently published report Getting a move on features the results from an online survey of 18,358 respondents across six countries: China, France, Germany, Italy, the UK, and the US.

    In the first post of this series, we reported that – unsurprisingly – many respondents felt their physical activity and exercise intensity drop due to pandemic-imposed lockdowns and restrictions.

    However, we also found the following trends with people who started using a new app or device to track their physical activity or take part in online fitness sessions:

    • They were twice as likely to increase their physical activity than other people.
    • Respondents who track either general metrics (e.g., heart rate, blood pressure, and sleep) or exercise-specific metrics exercise for about 50% longer than those who do not track either.
    • Respondents who track both types of metrics exercise for 100% longer than non-trackers.

    As well as general trends, we also looked at how income and age respectively impacted health and fitness habits during the pandemic, as well as the differences between men and women in perception of satisfaction with life and body image based on the usage of wearables and fitness apps.

    Here are our findings:

    Income: Technology is a self-tracking equalizer

    Legend: n=18,358, exercise time was collected in great detail in the questionnaire encompassing mild, moderate, and strenuous exercise during paid work, unpaid work, and leisure separately for weekdays and weekends; for data analysis, exercise was defined as at least moderate exercise. Definitions used in the questionnaire:  mild exercise (e.g., stretching, casual walking, fishing, golf using cart), moderate exercise e.g., yoga, hiking, jumping on a trampoline), strenuous exercise (e.g., martial arts, competitive soccer, football, hockey, high impact aerobics) *very small sample size in this cell (average change excl. this cell = +80). For an overview previous studies see: Western, M.J. et al. (2021):The effectiveness of digital interventions for increasing physical activity in individuals of low socioeconomic status: a systematic review and meta-analysis. International Journal of Behavioral Nutrition and Physical Activity – 09-November-2021.

    Similarities: In contrast to previous studies, the report finds similar changes in exercise duration on people on low-, medium-, and high-incomes when using tracking features. On average, respondents in the low-income bracket exercised for 48% longer when they tracked one of either general or exercise-specific metrics and 112% when tracking both. The corresponding increases were 49% and 95% for the medium income bracket.

    Differences: High earners changed their exercise habits less, showing average increases in exercise duration of 31% (tracking general or exercise metrics) and 49% (tracking both) on average. However, those in the highest income bracket started at a higher duration before they started using wearables and tracking metrics, exercising 10 minutes more on average than the low-income group each day. This is likely to explain the decreased effect of tracking in high earners. For respondents who track both general and exercise-specific metrics, the average exercise duration gap between high- and low-income groups shrinks to 4 minutes.

    Age is no barrier

    The 55+ age group of health and fitness tech adopters track more metrics than younger self-trackers. Promoting health and fitness technology for the elderly can go a long way to alleviate the challenges of aging populations.

    In France, Germany, and Italy, they track more metrics than younger respondents using similar functions. The study also found that tracking physical activity was more likely to push users in the 55+ age group to increase their exercise intensity than younger ones.

    One possible explanation is that the older demographic is likely to be more concerned with tracking both general health-related and exercise-based metrics to help monitor, anticipate, prevent, or alleviate existing or potential health concerns.

    The study concluded that the increased adoption of health and fitness technologies can go a long way to improving physical activity in older populations.

    User friendliness is a big advantage

    Our results suggest that the user friendliness of devices and apps may be as important as price when it comes to broad technology adoption and reaping the benefits from increased exercise. Newer health and fitness technologies produce smart content and recommendations that are significantly easier for users to interpret and use to improve their fitness routines. Older generations of devices and apps forced users to interpret raw data on their own.

    Body image

    The benefits of exercise go beyond improvements in health. The survey found that respondents who exercise also showed higher satisfaction with their life and bodies. Notably, women tended to see greater increases associated with exercise across these two measures than men (see figure below).

    Legend: The average refers to the specific gender within each country respectively; n(female no exercise)=4,474; n(female with exercise)=4,814; n(male no exercise)=3,957; n(male with exercise)=5,113. *p<.10; **p<.05; ***p<.01 (t-test)

    Key Takeaways

    We found that wearables and tracking metrics:

    • Increased physical activity in all demographics surveyed, which in turn increased satisfaction with life and body image, particularly among women.
    • Increased exercise duration across income groups and narrowed the gap between how long people exercised for in the low- and high-income brackets.
    • Increased the likelihood of users in the 55+ age group stepping up exercise intensity to a greater extent than younger users. Older people also track more metrics than young people and user-friendly technology that interprets data more fully can encourage adoption of wearables and tracking apps.

    Further reading

    About the study

    The report is based on a CAWI (computer-assisted web interview) survey of 18,358 respondents in China, Germany, France, Italy, UK, and the US. The survey was administered by YouGov, a global market research company. The survey was in the field from 2022/04/26 to 2022/05/09.

    The data collection adhered to YouGov’s privacy policy. The data set received by Huawei contained anonymized data only. Huawei is neither a data controller nor data processor of respondents’ personal data.

    Disclaimer: Any views and/or opinions expressed in this post by individual authors or contributors are their personal views and/or opinions and do not necessarily reflect the views and/or opinions of Huawei Technologies.


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