Diabetes Metab J.  2018 Aug;42(4):320-329. 10.4093/dmj.2017.0104.

Air Pollution Has a Significant Negative Impact on Intentional Efforts to Lose Weight: A Global Scale Analysis

• Ustulin M
• Park SY
• Chin SO
• Chon S
• Woo JT
• Rhee SY

• KMID: 2418720
• DOI: http://doi.org/10.4093/dmj.2017.0104

Abstract

BACKGROUND
Air pollution causes many diseases and deaths. It is important to see how air pollution affects obesity, which is common worldwide. Therefore, we analyzed data from a smartphone application for intentional weight loss, and then we validated them.
METHODS
Our analysis was structured in two parts. We analyzed data from a cohort registered to a smartphone application in 10 large cities of the world and matched it with the annual pollution values. We validated these results using daily pollution data in United States and matching them with user information. Body mass index (BMI) variation between final and initial login time was considered as outcome in the first part, and daily BMI in the validation. We analyzed: daily calories intake, daily weight, daily physical activity, geographical coordinates, seasons, age, gender. Weather Underground application programming interface provided daily climatic values. Annual and daily values of particulate matter PM10 and PM2.5 were extracted. In the first part of the analysis, we used 2,608 users and then 995 users located in United States.
RESULTS
Air pollution was highest in Seoul and lowest in Detroit. Users decreased BMI by 2.14 kg/m2 in average (95% confidence interval, −2.26 to −2.04). From a multilevel model, PM10 (β=0.04, P=0.002) and PM2.5 (β=0.08, P < 0.001) had a significant negative effect on weight loss when collected per year. The results were confirmed with the validation (βAQI*time=1.5×10-5; P < 0.001) by mixed effects model.
CONCLUSION
This is the first study that shows how air pollution affects intentional weight loss applied on wider area of the world.

Keyword

Air pollution; Mobile applications; Obesity; Smartphone; Weight loss

MeSH Terms

Air Pollution*
Body Mass Index
Cohort Studies
Mobile Applications
Motor Activity
Obesity
Particulate Matter
Seasons
Seoul
Smartphone
United States
Weather
Weight Loss
Particulate Matter

Figure

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  Fig. 1 Distribution of the initial body mass index per town. Darker colors define increasing levels of weight (“normal,” “overweight,” “obesity”). Pie charts and map were realized with SAS software.

• 

  Fig. 2 Distribution of the initial body mass index per area in United States (northeast, west, and midwest). The cities were grouped per area for the small size. Pie charts and map were realized with SAS software.

• 

  Fig. 3 Scatter plot of the weight loss and intensity of air pollution. aDiff. BMI=final BMI–initial body mass index per user, bPollution=mean of the air quality index computed on the entire observation period per user.

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