Like moving to a city that can be on foot, can add 1100 steps to your day

In the last article in the journal Researchers at the University of Washington, Stanford University and colleagues studied how changes in the walking of built environments affect physical activity, using data from people in the United States.

They discovered that moving to more infantry cities increased the number of steps that people walk every day; These profits lasted at least three months and were demonstrated in most age and sex groups, although the increase was not statistically important for women over 50 years of age.

Background

Physical inaction is widespread around the world. It contributes to serious non-infectious diseases, including cancer, diabetes and cardiovascular diseases. By 2050, fast urbanization will mean that most people live in cities, so urban designing will become even more important to public health.

While earlier studies examined the connections between the built -up environment, in particular in the case and physical activity, the findings were inconsistent. The key uncertainty is whether higher levels of activity are driven by the environment or simply reflect personal preferences regarding active life.

Many previous tests faced restrictions, including small sample sizes, limited geographical cover, the use of the information they reported, which may be biased, cross -sectional tests, which hinder causal inference, and disturbing the self -sufficiency associated with choosing the place of residence.

To overcome these challenges, scientists can now use smartphones for continuous and objective recording of both locations and physical activity, enabling large -scale analysis. Such data may reveal wide patterns of health behavior, city mobility and spreading of diseases, and can also reveal the differences between the measures of physical activity based on devices and reported by themselves.

About the study

The authors used a large set of data from smartphones to separate environmental effects from individual preferences, quantifying, how changes in walking capabilities affect physical activity at both the population and individual level.

The research team analyzed almost 250,000 days of zone data from 5,424 American users of smartphones application (identified from the basic set of data from over 2.1 million US users) who moved at least once in three years, which caused 7447 movements between over 1,600 cities.

The number of steps was recorded continuously via smartphones accelements, which were approved for accuracy in both laboratory and real settings. Physical activity was measured for a period of up to three months before each movement, creating a large -scale natural experiment to assess the impact of changes in a built environment.

Participants represented a number of body weight (BMI), age and sex categories. The transfer due to short -term travels was excluded, and sensitivity tests confirmed that the results were resistant to various definitions of relocation. The combatability was quantitatively determined using the fight result. The analysis included statistical tests (double -sided t) and aggregated results in all transfers.

To solve the potential bias of selection, the study compares with cities with similar walking and did not show significant changes in activity, confirming the view that the observed differences were caused by environmental factors, not personal preferences. The relationship between changes in appropriate walking and physical activity was also a symmetrical point, while reducing the losses of walking activity of similar size to growth growth. The data set also allows subgroup analysis by age, sex, BMI and the level of basic activity.

ANDDuring the observation period, 5,424 participants moved 7447 times between 1609 American cities. The area of the circle is proportional to the square element of the number of transfer to the city of the city. BThe levels of physical activity of participants were followed by the help of smartphone acceleometry within a few months before and after relocation, creating a worldwide study of 7447 Quasi-Experts. C– –FPhysical activity of participants passing from smaller places to go to New York (CINme), compared to participants moving in the opposite direction (DINF). Activity levels change significantly immediately after moving and are symmetrical, but inverted for participants moving in the opposite direction (meINF). All error bars on all numbers correspond to 95% of confidence intervals. Loans: AND– –Dmaps reproduced from the American office of the universal census (https://www.census.gov/geographies/mapping-files/2016/geo/cart-oundary-file.html); BWalking Human Silhouette reproduced with Wikimedia Commons at Creative Commons CC at 1.0 license.

Key arrangements

Transferring to more infantry cities significantly increased daily steps, while moving to smaller areas that can be walked caused equivalent drops. For example, moving from 25 to 75 percentile in walking raised activity by about 1,100 steps a day (about 11 additional minutes of walking), with changes persisting for at least three months.

The effects were consistent among the seasons, climate and levels of income, and the census indicates that most of the movements concerned family, work or housing, not walking, reducing the fears of self -sufficient.

The increase in the steps was largely caused by profits in moderate to the vision of physical activity (MVPA), defined in this study as an activity during the term of office of at least 100 steps per minute, especially fast walking, with a great improvement in walking possibilities (increase by 49-80 points), adding about 1 hour MVPA a week. The equivalent loss of MVPa has occurred for a similar decrease in the possibility of walking. This almost doubled the percentage of participants meeting the guidelines for aerobic activity in the US (from 21.5% to 42.5%), which was lower than typical estimates reported by themselves, reflecting known discrepancies between objective and reported measures.

The effects were observed in the age of sex, BMI and the initial level of activity, although older women showed lower profits and did not achieve statistical significance, which suggests that they may need complementary interventions.

Simulation models have estimated that raising all locations in the US to the level of walking in Chicago/Philadelphia may cause 36 million more Americans to meet the guidelines for activity, while matching the level of New York can increase this by 47 million. These simulations were corrected by age differences between a smartphone’s sample and the general adult population in the USA.

These results emphasize the improvement of the possibility of walking as a scalable strategy to increase physical activity at the population level.

Conclusions

The strengths of this analysis include a large, diverse set of data, longitudinal design, objective step measurement and consistency of results among climates, seasons, income levels and demographic groups.

The results relate to joint restrictions in previous studies, such as small samples, relying on data reported by yourself and the inability to control self -sufficiency. Evidence against housing self -sufficiency is strengthened, but they do not show causal interpretation.

However, the restrictions on this study include potential prejudice towards the higher socio-economic status and conscious health of participants, limiting American cities and relying on the results of the possibilities of foot at the city level, which obscure the variability at the neighborhood level and specific urban features that drive changes.

The method also loses unnecessary actions and requires participants to wear telephones to capture data. However, the growing spread of smartphones and wearing devices should reduce such prejudices over time.

Discoveries have strong political implications, which suggests that improving the possibilities of walking can significantly increase physical activity at the population level, supplementing interventions focused on individual.

While achieving the possibility of walking cities with highly on foot all over the world is unreal, targeted changes in urban design can bring significant health benefits, especially in combination with specific strategies for age and gender for groups such as older women who may encounter additional barriers to activity.