OBJECTIVE: This study aimed to quantify the association between step count and multiple health outcomes in a healthy population.
METHODS: PubMed, Embase, Web of Science, and The Cochrane Library were systematically searched for systematic reviews and meta-analyses from inception to April 1, 2022. Literature screening, data extraction, and data analysis were performed in this umbrella review. The intervention factor was daily step counts measured based on devices. Multiple health outcomes included metabolic diseases, cardiovascular diseases, all-cause mortality, and other outcomes in the healthy population.
RESULTS: Twenty studies with 94 outcomes were identified in this umbrella review. The increase in daily step count contributed to a range of human health outcomes. Furthermore, the special population, different age groups, countries, and cohorts should be carefully considered. Negative correlation between step counts and the following outcomes: metabolic outcomes, cardiovascular diseases, all-cause mortality, postural balance, cognitive function, and mental health. However, there was no association between participation in the outdoor walking group and the improvement of systolic blood pressure and diastolic blood pressure. Analysis of the dose-response association between increasing daily step count and the risk of cardiovascular disease events and all-cause mortality showed a substantially linear relationship.
CONCLUSIONS: A wide range of health outcomes can benefit from the right number of steps.

This study aimed to investigate the relationship between objectively measured step counts, step intensity and FOF in community-dwelling older Chinese women. Cross-sectional analyses were conducted on pooled data (n = 1101) from the baseline survey of the Physical Activity and Health Study (PAHIOWS). Step counts and step intensity were measured using wGT3X-BT accelerometers, and FOF was categorized into two levels (low and high) for logistic regression analysis. Higher step counts were significantly and negatively associated with FOF; however, after adjusting for step intensity, the association was no longer statistically significant. On the contrary, higher step intensity was negatively associated with FOF independent of step counts. This finding may provide new insights into the physical activity management of FOF in older women.

While a higher level of physical activity (PA) is inversely associated with a higher breast cancer (BC) risk, the health benefits of daily steps on obesity-related BC biomarkers remain unclear. We aimed to understand the associations of changes in step counts with levels of five obesity-related BC biomarkers during a two-year follow-up. In total, 144 non-cancer women (47.96 ± 5.72) were observed on both 2019 and 2021. A structured questionnaire, daily steps and fasting blood samples were collected before (t0, 2019) and after (t1, 2021). Levels of biomarkers (IGF-binding proteins 3, adiponectin, soluble leptin receptor, C-reactive protein, and resistin) were assayed by ELISA. Participants were divided into persistent low steps, decreasing steps, increasing steps, and persistent high steps. Associations of categories on proposed biomarkers were estimated using linear regression models, with persistent low steps as reference. Associations between time-varying step counts with biomarkers were quantified using mixed linear models. Compared with persistent low steps, increasing steps is associated with a reduction in C-reactive protein level (β=-0.74, 95%CI=-1.23--0.26, P-value = 2.98 × 10-3). An inverse association between time-varying step counts with C-reactive protein level was identified, consistent across different obesity types and baseline step level categories. No association with daily step counts was observed for other proteins.

Physical activity is an important factor in premature mortality reduction, non-communicable disease prevention, and well-being protection. Climate change will alter temperatures globally, with impacts already found on mortality and morbidity. While uncomfortable temperature is often perceived as a barrier to physical activity, the actual impact of temperature on physical activity has been less well studied, particularly in China. This study examined the associations between temperature and objectively measured physical activity among adult populations in five major Chinese cities.
Aggregated anonymized step count data was obtained between December 2017-2018 for five major Chinese cities: Beijing, Shanghai, Chongqing, Shenzhen, and Hong Kong. The associations of temperature with daily aggregated mean step count were assessed using Generalized Additive Models (GAMs), adjusted for meteorological, air pollution, and time-related variables.
Significant decreases in step counts during periods of high temperatures were found for cold or temperate climate cities (Beijing, Shanghai, and Chongqing), with maximum physical activity occurring between 16 and 19.3 °C. High temperatures were associated with decreases of 800-1500 daily steps compared to optimal temperatures. For cities in subtropical climates (Shenzhen and Hong Kong), non-significant declines were found with high temperatures. Overall, females and the elderly demonstrated lower optimal temperatures for physical activity and larger decreases of step count in warmer temperatures.
As minor reductions in physical activity could consequentially affect health, an increased awareness of temperature\'s impact on physical activity is necessary. City-wide adaptations and physical activity interventions should seek ways to sustain physical activity levels in the face of shifting temperatures from climate change.

This paper describes the development of a physical activity questionnaire (PAQ) designed for Chinese adolescents and their mothers in urban and rural settings, and reports on results of the PAQ, pedometry, and hand grip dynamometry from the Chinese Children and Families Cohort Study pilot investigation (CFCS).
As part of a pilot investigation to evaluate the feasibility to follow-up and obtain detailed nutrition, dietary, physical activity, and ultraviolet radiation (UVR) data from CFCS participants, data were collected in 2013 for 93 adolescent/mother pairs from a rural (n = 41) and an urban site (n = 52) in two provinces. Respondents were asked to wear a pedometer for seven days (Omron HJ-151), use a Takei Digital Grip Strength Dynamometer on (each hand; three trials; two separate days), and complete a 39 item, eight domain PAQ covering the past year. Self-reported physical activity (PA) was linked to metabolic equivalent of task (MET) scores in kcal/kg/hr and used to calculate METs for different domains of PA and intensity categories.
Compliance was high (95%) in this measurement protocol administered by health staff during a series of data collection efforts at home and local clinics or health centers. Step counts were highly variable, averaging between 5000 and 10000 per day with somewhat higher step counts in rural adolescent boys. Maximum grip strength (Kgs) was greater in children (Mean = 36.5, SE = 0.8) than mothers (Mean = 28.8, SE = 0.8) and similar in the urban (Mean = 29.6, SE = 0.6) compared to the rural (Mean = 29.6, SE = 0.5) communities overall. Grip strength, step counts, and measures of time spent in different activities or activity intensities were uncorrelated.
Device and question-based measurement of PA and strength were readily accepted in these Chinese urban and rural populations. The PAQ on physical activity in the past year produced some plausible population averages, but individual responses suggested recall challenges. If data about specific activities are required, future studies should explore use of standardized survey questions concerning such fewer specific activities or instruments examining shorter time periods such as one, three, or seven day recalls.

BACKGROUND: The objectives of this review paper were to synthesize the data from randomized controlled trials in the literature to come to a conclusion on the effects of e-health interventions on promoting physical activity in older people.
METHODS: The Medline, CINAHL, Embase, PsycINFO, and SportDiscus databases were searched for articles about studies that 1) recruited subjects with a mean age of > 50 years, 2) tested e-health interventions, 3) employed control groups with no or less advanced e-health strategies, 4) measured physical activity as an outcome, 5) were published between 1st January 2008 and 31st May 2019, and 6) employed randomized controlled trials. The risk of bias in individual studies was assessed using the Physiotherapy Evidence Database scale. To examine the effects of the interventions, variables quantifying the amount of physical activity were extracted. The within-group effects of individual studies were summarized using Hedges g and 95% confidence intervals. Between-group effects were summarized by meta-analyses using RevMan 5.0 with a random effect model.
RESULTS: Of the 2810 identified studies, 38 were eligible, 25 were included in the meta-analyses. The within-group effect sizes (Hedges g) of physical activity in the intervention group at T1 ranged from small to large: physical activity time (0.12 to 0.84), step counts (- 0.01 to 11.19), energy expenditure (- 0.05 to 0.86), walking time (0.13 to 3.33), and sedentary time (- 0.12 to - 0.28). The delayed effects as observed in T2 and T3 also ranged from small to large: physical activity time (0.24 to 1.24) and energy expenditure (0.15 to 1.32). In the meta-analysis, the between-group effect of the e-health intervention on physical activity time measured by questionnaires, physical activity time measured by objective wearable devices, energy expenditure, and step counts were all significant with minimal heterogeneity.
CONCLUSIONS: E-health interventions are effective at increasing the time spent on physical activity, energy expenditure in physical activity, and the number of walking steps. It is recommended that e-health interventions be included in guidelines to enhance physical activity in older people. Further studies should be conducted to determine the most effective e-health strategies.