No seasonal variation in physical activity of Han Chinese living in Beijing

Objectively measured the impact of ambient air pollution on physical activity for older adults

BACKGROUND

Air pollution poses a significant health risk to the human population, especially for vulnerable groups such as the elderly, potentially discouraging their engagement in physical activity. However, there is a lack of sufficient objective and longitudinal data in current research on how air pollution affects physical activity among older adults. With these gaps, we aimed to explore the relationship between air pollution and objective measurement-based physical activity among older adults by engaging in a longitudinal study design.

METHODS

A total of 184 older adults were recruited from three cities with varying levels of air quality. Mean daily minutes of physical activity were measured with 7 consecutive days of accelerometer monitoring (ActiGraph GT3X-BT). Corresponding air pollution data including daily PM2.5 (µg/m3), PM10 (µg/m3) and air quality index (AQI) were sourced from the China National Environmental Monitoring Centre at monitor locations close to older adults' addresses. Associations between air quality and physical activity were estimated using a fixed effect model, adjusting for average daytime temperature, rain, age and weight.

RESULTS

AQI and PM2.5 were observed to exhibit significant, inverse, and linear associations with mean daily walk steps, minutes of light physical activity (LPA), moderate physical activity (MPA) and moderate-to-vigorous physical activity (MVPA) in the single variable models. A one-level increase in AQI corresponded to a decline in 550.04 steps (95% [CI] = -858.97, -241.10; p < 0.001), 10.43 min (95% [CI] = -17.07, -3.79; p < 0.001), 4.03 min (95% [CI] = -7.48, -0.59; p < 0.001) and 4.16 min (95% [CI] = -7.77, -0.56; p < 0.001) in daily walking steps, LPA, MPA, and MVPA, respectively. A one-level increase in PM2.5 correlated with a decline in daily walk steps, LPA, MPA and MVPA by 361.85 steps (95% [CI] = -516.53, -207.16; p < 0.001), 8.97 min (95% [CI] = -12.28, -5.66; p < 0.001), 3.73 min (95% [CI] = -5.46, -2.01; p < 0.001,) and 3.79 min (95% [CI] = -5.59, -1.98; p < 0.001), respectively. However, PM10 displayed a significant negative association exclusively with LPA, with one-level increase in PM10 resulting in a 3.7-minute reduction in LPA (95% [CI] = -6.81, -0.59, p < 0.05).

CONCLUSION

Air pollution demonstrates an inverse association with physical activity levels among older adults, potentially discouraging their engagement in physical activity. Different air quality indicators may exert varying impacts on physical activity. Future studies are warranted to enhance policy interventions aimed at reducing air pollution and promoting physical activity.

The Impact of Temperature on 24-Hour Movement Behaviors among Chinese Freshmen Students

BACKGROUND

Human populations worldwide have experienced substantial climate change issues. Gaps in scientific literature remain regarding the relationship between temperature and 24-hour movement behavior among people. The purpose of this study is to examine the impact of temperature on 24-hour movement behavior including physical activity (PA), sedentary behavior (SB) and sleep duration among university students living in Beijing, China.

METHODS

We conducted follow-up health surveys on 44,693 freshmen students enrolled at Tsinghua University from 2012 to 2018. PA and SB were measured by using the short version of the International Physical Activity Questionnaire (IPAQ-s); sleep duration was estimated by using The Pittsburgh Sleep Quality Index (CPSQI). Corresponding temperature data measured by the Beijing Meteorological Service were collected to include average daily temperature from the nearest weather station to Tsinghua university. The data were analyzed using linear individual fixed-effect regressions.

RESULTS

An increase in temperature (temperature range 2.29-28.73 °C) by 1 °C was associated with an increase in 0.66 weekly minutes of vigorous physical activity (VPA) (95% confidence interval [CI] = 0.49, 0.82), an increase in 0.56 weekly minutes of moderate physical activity (MPA)(95% CI = 0.32, 0.79), an increase in 1.21 weekly minutes of moderate to vigorous physical activity (MVPA) (95% CI = 0.90, 1.53), an increase in 0.55 weekly minutes of walking (95% CI = 0.31, 0.78), an increase in 1.76 weekly minutes of total PA (95% CI = 1.35, 2.17), and a reduction in 1.60 weekly minutes of sleeping (95% CI = -2.09, -1.11). There was no significant correlation between temperature and sedentary behavior among participants.

CONCLUSIONS

Temperature was significantly positively correlated with physical activity levels in the Chinese freshmen students, and significantly negatively correlated with sleep duration. Replication of this study is warranted among various populations within China. The evidence of this novel study focused on understanding the relationship between climate change and 24-hour movement behaviors among people for developing effective adaptation strategies to climate change to improve people's health behavior. This study has important implications for future study, as knowledge of the impact of temperature on movement behavior may help in the interpretation of their results and translate into improving people's health behavior.

Impact of ambient air pollution on physical activity and sedentary behavior in children

BACKGROUND

Exposure to air pollution has become a serious environmental issue affecting children's health and health-related behavior in China. Previous studies have focused on the associations between air pollution and physical activity among adults; however, few have examined the relationship between air pollution and health-related behavior among children, which are particularly susceptible population subgroups. The present study aims to examine the impact of air pollution on daily physical activity (PA) and sedentary behavior (SB) among children in China.

METHODS

PA and SB data were collected by actiGraph accelerometers for eight consecutive days. PA and SB data from 206 children were matched to daily air pollution obtained from the Ministry of Environmental Protection of the People's Republic of China, including the average daily air quality index (AQI), PM_2.5 (µg/m³), and PM₁₀ (µg/m³). Associations were estimated using linear individual fixed-effect regressions.

RESULTS

A 10-unit increase in daily AQI was associated with a reduction in daily PA by 5.94 (95% confidence interval [CI] = -8.79, -3.08) minutes of moderate to vigorous physical activity (MVPA) and 229.82 (95% CI = -345.35, -114.28) walking steps and an increase in daily SB by 15.77 (95% CI = 9.01, 22.53) minutes. A 10 µg/m³ increase in air pollution concentration in daily PM_2.5 was associated with a reduction in daily PA by 7.51 (95% CI = -11.04, -3.97) minutes of MVPA, 295.69 (95% CI = -438.46, -152.92) walking steps and an increase in daily SB by 21.12 (95% CI = 12.77, 29.47) minutes. A 10 µg/m³ increase in air pollution concentration in daily PM₁₀ was associated with a reduction in daily PA by 13.18 (95% confidence interval [CI] = -15.98, -10.37) minutes of MVPA, 518.34 (95% CI = -631.77, -404.91) walking steps and an increase in daily SB by 19.87 (95% CI = 13.10, 26.64) minutes.

CONCLUSION

Air pollution may discourage physical activity and increase sedentary behavior among children. Policy interventions are needed to reduce air pollution and develop strategies to decrease risks to children's health.

Working status and seasonal meteorological conditions predict physical activity levels in people living with HIV

Little is known about how demographic, employment and meteorological factors impact physical activity. We conducted an analysis to explore these associations from participants (N = 447) from six cities in the United States and matched their activity data with abstracted local meteorological data from National Oceanic and Atmospheric Administration (NOAA) weather reports. Participants were purposively recruited in 3-month blocks, from December 2015 to October 2017, to reflect physical activity engagement across the seasons. We calculated total physical activity (minutes/week) based on 7-day physical activity recall. Mild correlations were observed between meteorological factors and correlated with lower physical activity. Participants were least active in autumn (Median = 220 min/week) and most active in spring (Median = 375 min/week). In addition to level of education and total hours of work, maximum temperature, relative humidity, heating degree day, precipitation and sunset time together explained 17.6% of variance in total physical activity. Programs assisting in employment for PLHIV and those that promote indoor physical activity during more strenuous seasons are needed. Additional research to better understand the selection, preferences, and impact of indoor environments on physical activity is warranted.

The effect of temperature on physical activity: an aggregated timeseries analysis of smartphone users in five major Chinese cities

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01285-1.

Association with Temperature Variability and Physical Activity, Sedentary Behavior, and Sleep in a Free-Living Population

The present study examines the temperature variability in physical activity (PA), sedentary behavior (SB), and sleep in a free-living population. A representative sample of 1235 adults (ages 21–70) from Iowa, U.S.A., wore a SenseWear Mini Armband (SWA) for a randomly assigned day. Koppen’s weather climate classification was used to precisely classify the temperature: cold (−13 to 32 °F), cool (32 to 50 °F), mild (50 to 64 °F), warm (64 to 73 °F), and hot (73 to 95 °F). The main effect of three-way ANOVA (age × gender × temperature) had differences for SB and sleep, with older adults having higher levels than younger adults (p < 0.05). However, moderate to vigorous PA (MVPA) did not vary systematically by age or gender, and contrary to expectations, the main effect of the weather was not significant for MVPA (p > 0.05). Participants spent more time participating in PA at cold than at hot temperatures. The results clarify the impact of temperature on shaping PA and SB patterns in adults. The variable impacts and differential patterns by age suggest that weather should be considered when interpreting differences in PA patterns in research or surveillance applications.

Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach

The increasing ubiquity of smartphone data, with greater spatial and temporal coverage than achieved by traditional study designs, have the potential to provide insight into habitual physical activity patterns. This study implements and evaluates the utility of both K-means clustering and agglomerative hierarchical clustering methods in identifying weekly and yearlong physical activity behaviour trends. Characterising the demographics and choice of activity type within the identified clusters of behaviour. Across all seven clusters of seasonal activity behaviour identified, daylight saving was shown to play a key role in influencing behaviour, with increased activity in summer months. Investigation into weekly behaviours identified six clusters with varied roles, of weekday versus weekend, on the likelihood of meeting physical activity guidelines. Preferred type of physical activity likewise varied between clusters, with gender and age strongly associated with cluster membership. Key relationships are identified between weekly clusters and seasonal activity behaviour clusters, demonstrating how short-term behaviours contribute to longer-term activity patterns. Utilising unsupervised machine learning, this study demonstrates how the volume and richness of secondary app data can allow us to move away from aggregate measures of physical activity to better understand temporal variations in habitual physical activity behaviour.

Ambient air pollution and movement behaviours: A scoping review

This scoping review summarizes the literature about how ambient (outdoor) air pollution impacts movement behaviours (i.e., physical activity, sedentary behaviour, and sleep), or beliefs about movement behaviours. Of 6552 potential documents, 58 documents and 218 findings were included in the final synthesis. Most studies were from the United States and China, involved cross-sectional designs, and included mixed age groups. Overall, unfavourable changes/associations (i.e., decreased/lower physical activity, increased/higher sedentary-related behaviour, and decreased/lower sleep duration and quality) or no change/association in movement behaviours in relation to ambient air pollution were identified. Our findings suggest that more attention should be given to understanding the impact of ambient air pollution on movement behaviours in general and in diverse countries and vulnerable populations such as children or older adults.

Socio-demographic determinants of physical activity and app usage from smartphone data

The increasing ubiquity of smartphones provides a potential new data source to capture physical activity behaviours. Though not designed as a research tool, these secondary data have the potential to capture a large population over a more extensive spatial area and with longer temporality than current methods afford. This paper uses one such secondary data source from a commercial app designed to incentivise activity. We explore the new insights these data provide, alongside the sociodemographic profile of those using physical activity apps, to gain insight into both physical activity behaviour and determinants of app usage in order to evaluate the suitability of the app in providing insights into the physical activity of the population. We find app usage to be higher in females, those aged 25-50, and users more likely to live in areas where a higher proportion of the population are of a lower socioeconomic status. We ascertain longer-term patterns of app usage with increasing age and more male users reaching physical activity guideline recommendations despite longer daily activity duration recorded by female users. Additionally, we identify key weekly and seasonal trends in physical activity. This is one of the first studies to utilise a large volume of secondary physical activity app data to co-investigate usage alongside activity behaviour captured.

Objectively measured association between air pollution and physical activity, sedentary behavior in college students in Beijing

The purpose of this study is to examine the association between hourly air pollution on hourly physical activity (PA) and sedentary behavior (SB) among college students in Beijing, China. The secondary aim was to examine such associations varied at specific time. A total of 340 participants were recruited from the Tsinghua University, in Beijing, China. Accelerometers provided PA measures, including moderate-to-vigorous physical activity (MVPA), walking steps, energy expenditure and sedentary time for 7 consecutive days. Corresponding air pollution data by the Beijing Municipal Ecological Environment Bureau in the closed site (Wan Liu site) in Tsinghua University were collected including average hourly air quality index (AQI) and PM_2.5 (μg/m³). Associations were estimated using linear individual fixed-effect regressions. We also conducted an air pollution risk perception survey among 2307 freshmen (76.6% males) who were enrolled in Tsinghua in 2016, and the survey was done in May 22-26, 2017. A one level increase in hourly air quality index (AQI) was associated with a reduction in 1-h PA by 0.083 (95% confidence interval [CI] = -0.137, -0.029) minutes of MVPA, 8.8 (95% CI = -15.0, -2.6) walking steps, 0.65 (95% CI = -1.03, -0.27) kcals of energy expenditure. A 10 μg/m³ increase in air pollution concentration in hourly PM_2.5 was associated with a reduction in 1-h PA by 0.021 (95% confidence interval [CI] = -0.033, -0.010) minutes of MVPA, 2.2 (95% CI = -3.5, -0.9) walking steps, 0.170 (95% CI = -0.250, -0.089) kcals of energy expenditure an increase in 1-h sedentary behavior 0.045 (0.005, 0.0845). At specific time, stronger negative associations of AQI and PM_2.5 air pollution with PA at 8 a.m., 4 p.m., 5 p.m. and 7 p.m. Similarly, stronger positive associations of 1 h AQI and PM_2.5 air pollution with SB at 8 a.m., 9 a.m., 11 a.m., and 7 p.m. A total of 94.9% participants (n = 2235) responded "yes" to air pollution change activities in the survey, which may partially explain PA change. Air pollution may discourage physical activity and increases sedentary behavior among freshman students living in Beijing, China. This is preliminary study. The impact of air pollution on physical activity and sedentary behavior at a specific time may be different.

Seasons, weather, and device-measured movement behaviors: a scoping review from 2006 to 2020

BACKGROUND

This scoping review summarized research on (a) seasonal differences in physical activity and sedentary behavior, and (b) specific weather indices associated with those behaviors.

METHODS

PubMed, CINAHL, and SPORTDiscus were searched to identify relevant studies. After identifying and screening 1459 articles, data were extracted from 110 articles with 118,189 participants from 30 countries (almost exclusively high-income countries) on five continents.

RESULTS

Both physical activity volume and moderate-to-vigorous physical activity (MVPA) were greater in summer than winter. Sedentary behavior was greater in winter than either spring or summer, and insufficient evidence existed to draw conclusions about seasonal differences in light physical activity. Physical activity volume and MVPA duration were positively associated with both the photoperiod and temperature, and negatively associated with precipitation. Sedentary behavior was negatively associated with photoperiod and positively associated with precipitation. Insufficient evidence existed to draw conclusions about light physical activity and specific weather indices. Many weather indices have been neglected in this literature (e.g., air quality, barometric pressure, cloud coverage, humidity, snow, visibility, windchill).

CONCLUSIONS

The natural environment can influence health by facilitating or inhibiting physical activity. Behavioral interventions should be sensitive to potential weather impacts. Extreme weather conditions brought about by climate change may compromise health-enhancing physical activity in the short term and, over longer periods of time, stimulate human migration in search of more suitable environmental niches.

Changes in Season Affect Body Weight, Physical Activity, Food Intake, and Sleep in Female College Students: A Preliminary Study

The current study examined how body weight and lifestyle fluctuate between spring, autumn, and winter in Japanese female college students and whether weight gain is associated with changes in physical activity, food intake, and sleep. We measured body weight and lifestyle factors in 31 participants from May 2017 to January 2018. Weight was measured daily in participants’ homes. Physical activity and sleep were measured for three weeks in three seasons using two accelerometers. Food intake was assessed using a validated food frequency questionnaire. Body weight significantly decreased in autumn compared with spring (p < 0.001). Body weight in winter tended to increase compared with autumn (p = 0.052). Step counts and energy intake were significantly different between seasons (p < 0.05). Total time in bed was not significantly different between seasons. In comparisons of changes in lifestyle patterns from autumn to winter between the weight gain (≥0.5 kg) and weight maintenance groups, seasonal changes in lifestyle factors were not significantly different between groups (p > 0.05). The results indicated that body weight and lifestyle were affected by seasonal variability in female college students, but no significant relationships existed between seasonal weight gain and changes in lifestyle patterns.

Predicted impact of increasing average ambient temperature over the coming century on mortality from cardiovascular disease and stroke in the USA

BACKGROUND AND AIMS

Future climate change may adversely impact human health. The direct effects of extreme hot temperatures on mortality are well established, and their future impact well modelled. However, less extreme changes in ambient temperature (Ta) have been previously associated with increased mortality from circulatory and metabolic diseases, but their future impact is less clear.

METHODS

We evaluated the spatial association between cardiovascular diseases (CVD) and stroke mortality with average Ta across the US mainland, and then used this relationship to model future temporal trends in mortality from CVD and stroke until the end of the century (2099), using different warming scenarios for each US county.

RESULTS

Ta was significantly associated with crude levels of CVD mortality (R² = 0.269) and stroke mortality (R² = 0.264). Moreover, there was a strong positive link between Ta and physical inactivity (PIA) (R² = 0.215). Once adjusted for PIA the associations between Ta and CVD and stroke mortality were much reduced (R² = 0.054 and R² = 0.091 respectively) but still highly significant.

CONCLUSIONS

By 2099 modelling suggests between 8844 and 25,486 extra deaths each year from CVD, and between 2,063 and 13,039 extra deaths for stroke, beyond the increases expected from population expansion. Mortality due to changes in the mean Ta may be as, or more, significant than the impacts of extreme hot weather events.

Genetic Factors Associated With Human Physical Activity: Are Your Genes Too Tight To Prevent You Exercising?

The benefits of physical activity (PA) on health and fitness are well known. It has become apparent from studies of heritability that there is a considerable genetic component to PA. However, PA is such a complex phenotype that the measurement and quantification of it provide a challenge to a clearer understanding of its genetic basis. In this review, we assessed available evidence from family and twin studies that have estimated the heritability of PA. Heritability is greater when evaluated by accelerometry compared with questionnaires, and for questionnaires higher in twin than family studies. Accelerometry studies suggest heritability of PA is 51% to 56%. There have been many genome-wide linkage studies, candidate gene studies, and four genome-wide association studies that have highlighted specific genetic factors linked to different PA levels. These studies have generally failed to replicate identified loci, with the exception of the melanocortin 4 receptor, and this may be because of the variability in the measurement techniques used to characterize the behavior. Future work should aim to standardize the procedures used to measure PA in the context of trying to identify genetic causes. The link of genetics to physical exercise is not so tight that it prevents voluntary interventions.

Seasonal variation in body mass, body composition and activity-induced energy expenditure: a long-term study

BACKGROUND/OBJECTIVES

Seasonal variation in body mass is a model for the study of body mass regulation. Here a long-term study is presented on body mass, body composition, and activity-induced energy expenditure in a subject with a large seasonal variation in body mass of about 3.0 kg.

SUBJECT/METHODS

Body mass was assessed daily over >20 consecutive years. Daily assessment of activity-induced energy expenditure was performed over the last 10 years. Body composition was assessed monthly for 1 year in the middle and at the end of the observation interval. Additionally, data were compared with data on body composition, resting energy expenditure, and total daily energy expenditure of the same subject as a participant in published studies.

RESULTS

Body mass showed a pronounced seasonal variation, associated with a synchronous variation in physical activity. Body mass peaked in the cold winter months when physical activity reached the lowest annual value and decreased to the lowest value in mid-summer when daily physical activity peaked. The seasonal variation in body mass consisted mainly of body fat. Longitudinally, over the past 8 years of the observation interval, average fat-free mass showed a decrease of 1.0 kg and fat mass increased 0.8 kg.

CONCLUSIONS

In a subject with a pronounced seasonal variation in physical activity, activity-induced variation in energy requirement was covered by an annual variation in body mass, mainly as fat. Maintenance of activity-induced energy expenditure did not protect against loss of fat-free body mass with advancing age.

Impact of Air Pollution on Sedentary Behavior: A Cohort Study of Freshmen at a University in Beijing, China

Human populations worldwide have experienced substantial environmental issues in part due to air pollution, notably in China. Gaps in the scientific literature remain regarding the relationship between air pollution and sedentary behavior among young adults in China. The purpose of this study is to examine the effect of air pollution on sedentary behavior among college students living in Beijing, China. We conducted follow-up health surveys on 12,174 freshman students enrolled at Tsinghua University from 2013 to 2017. Sedentary behavior was measured using the short version of the International Physical Activity Questionnaire (IPAQ). Corresponding air pollution data measured by the Ministry of Environmental Protection of the People's Republic of China were collected to include the average hourly air quality index (AQI), PM_2.5, PM₁₀, and NO₂ (µg/m³). The data were analyzed using linear individual fixed-effect regressions. An increase in air pollution concentration of one standard deviation in AQI, PM_2.5, PM₁₀, and NO₂ was associated with an increase in weekly total hours of sedentary behavior by 7.35 (95% confidence interval (CI) = 5.89, 8.80), 6.24 (95% CI = 5.00, 7.49), 6.80 (95% CI = 5.46, 8.15), and 7.06 (95% CI = 5.65, 8.47), respectively. In the presence of air pollution, women students tended to increase their sedentary behavior more than men. Air pollution increases sedentary behavior among freshman students living in Beijing, China. Replication of this study is warranted among various populations within China.

Impact of Obesity and Ozone on the Association Between Particulate Air Pollution and Cardiovascular Disease and Stroke Mortality Among US Adults

Background

Cardiovascular diseases (CVDs) and stroke are the highest and third highest causes of death, respectively, in the whole United States. It is well established that both long‐ and short‐term exposure to particulate air pollution (particulate matter with diameters <2.5 μm [PM_2.5]) increases the risks of both CVD and stroke mortality.

Methods and Results

We combined county‐level data for CVD and stroke mortality, and prevalence of hypertension and obesity, with spatial patterns of PM_2.5 and ozone in a cross‐sectional ecological study. We found significant positive associations between both CVD (β=15.4, P<0.001) and stroke (β=2.7, P<0.001) mortality with PM_2.5. Ozone had significant link with just CVD (β=1372.1, P<0.001). Once poverty, ethnicity, and education were taken into account, there were still significant positive associations between PM_2.5 and both CVD (β=1.2, P<0.001) and stroke (β=1.1, P<0.001) mortality. Moreover, the association between CVD and ozone remained after adjustment for these factors (β=21.8, P<0.001). PM_2.5 and ozone were independent risk factors. The impact of PM_2.5 on CVD and stroke mortality was strongly dependent on the prevalence of obesity. Hypertension partially mediated the associations of PM_2.5 and mortality from CVD and stroke.

Conclusions

There was a spatial association between PM_2.5 exposure and the leading causes of death and disability in United States. The effect of PM_2.5 was considerably greater in areas where obesity is more prevalent. Hypertension is a possible mediator of the association of PM_2.5 and both CVD and stroke.

The association between ambient fine particulate air pollution and physical activity: a cohort study of university students living in Beijing

Background

Air pollution has become a substantial environmental issue affecting human health and health-related behavior in China. Physical activity is widely accepted as a method to promote health and well-being and is potentially influenced by air pollution. Previous population-based studies have focused on the impact of air pollution on physical activity in the U.S. using a cross-sectional survey method; however, few have examined the impact on middle income countries such as China using follow-up data. The purpose of this study is to examine the impact of ambient fine particulate matter (PM_2.5) air pollution on physical activity among freshmen students living in Beijing by use of follow-up data.

Methods

We conducted 4 follow-up health surveys on 3445 freshmen students from Tsinghua University from 2012 to 2013 and 2480 freshmen completed all 4 surveys. Linear individual fixed-effect regressions were performed based on repeated-measure physical activity-related health behaviors and ambient PM_2.5 concentrations among the follow-up participants.

Results

An increase in ambient PM_2.5 concentration by one standard deviation (44.72 μg/m³) was associated with a reduction in 22.32 weekly minutes of vigorous physical activity (95% confidence interval [CI] = 24.88–19.77), a reduction in 10.63 weekly minutes of moderate physical activity (95% CI = 14.61–6.64), a reduction in 32.45 weekly minutes of moderate to vigorous physical activity (MVPA) (95% CI = 37.63–27.28), and a reduction in 226.14 weekly physical activity MET-minute scores (95% CI = 256.06–196.21). The impact of ambient PM_2.5 concentration on weekly total minutes of moderate physical activity tended to be greater among males than among females.

Conclusions

Ambient PM_2.5 air pollution significantly discouraged physical activity among Chinese freshmen students living in Beijing. Future studies are warranted to replicate study findings in other Chinese cities and universities, and policy interventions are urgently needed to reduce air pollution levels in China.