Global Analysis — Studies and Applications II

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In this way, it was possible to check whether regular use of the application had a positive effect on weight loss. With this model, we could keep track of the BMI trend for each user considering the correlated measures for each subject, since we assumed that each user had his or her own pattern due to intrinsic individual characteristics. Using the coefficients of interaction between the time of login and the climatic predictors, it was possible to determine how BMI changed over time when the climatic variables varied.

Since there were different time spaces between users the number and days of login were heterogeneous in this study , the mixed effects model was the most appropriate method that we could use with this data structure. The entire analysis was performed using SAS software.

This study was conducted in accordance with the guidelines laid down in the Declaration of Helsinki, the privacy policy of Noom Inc. The users of the Noom Coach application were located in different geographic areas with a total of cities [ Fig. A total of people male: , female: were included in this study [ Table 1 ]. The average number of logins for each user was days, which means that each user had a login approximately every 3 days.

Men used the application more often than did women vs. During follow-up, we did not notice a difference regarding the use of the application between males and females when frequent and infrequent users were compared frequent: people who regularly provided information on their meals. People who used the smartphone application to lose body weight achieved their goal after approximately 1 year. The same result was confirmed using a linear mixed-effects model [ Table 3 ]. Therefore, this negative association showed that the BMI decreased over time and subjects who used this app lost their weight.

Using a linear mixed-effects model, it was possible to measure whether the variation in some climatic variables pressure, temperature, dew point, precipitation, and wind speed produces an effect on weight loss. Using the coefficient of the time variable and the coefficients of interaction between climatic variables and time, we noticed that the variation in BMI, varying the time with a single unit, tended to be less negative when temperature increased.

Therefore, low levels of temperature promoted weight loss. The same result was obtained with the dew point variable; the coefficient of interaction was positive, and therefore, low dew points supported weight loss. These results can be also observed in the graphs [ Fig. In these scatterplots, we also noticed that most points for weight loss were less than zero, showing that many users lost weight.

The English in this document has been checked by at least two professional editors, both native speakers of English. These results were corrected by introducing other variables into the model such as initial BMI, area, season, average daily calories for breakfast, lunch, and dinner , age, and gender.

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Be the first to write a review. Studies and Applications II. Subscribe Contact us Submit About Back to top. An Computer Science engineer by education, he has prior experience in software development. Riemannian parallel translation, the ito integral, and stochastic equations on manifolds Pages Gliklikh, Yu.

Using the data from the app and the weather information, it was possible to keep track of the login days for each user and to obtain climatic data for each day of the study considering also the different seasons and location geographical areas of the subjects. The effect of climatic variables on BMI variation was analyzed: low values of temperature and dew point and high levels of precipitation and wind speed were associated with weight loss. We also found that the use of this application helped people to lose weight, people showed a significant decrease of BMI at the end of study period.

Our results agree with similar results obtained in another study One of the variables playing an important role in this analysis was the location of the user, which allowed us to keep track of the different diets, lifestyles, ethnicities and different climatic conditions of the distinct locations.

The amount of variation in BMI depended also on the initial weight: those who start a diet at a higher weight tend to have a higher variation in BMI compared with those with a lower initial weight. Unfortunately, we did not consider all users in this study: subjects who never provided information about their main meals breakfast, lunch, and dinner were discarded to avoid possible biases resulting from improper use of the app. In addition, the lack of information regarding climatic variables on some days led us to remove some users from the analysis, since it was important to have a complete trend for the weather variables to estimate possible associations between variations in the weather and BMI.

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Moreover, it was not easy to estimate missing data using the information at our disposal, since climatic variables have a high variability, particularly during the transition from one season to the next. Even though these choices led us to reduce the size of the sample, they allowed us to have maximal information for users during the follow-up period.

The model we used analyzed the trend for each user and computed an average effect of the evaluated associations, even if the follow-up time for individuals was different: users logged their information on the application during different times of the year different baseline times and with different frequencies. The geographic area structure was useful to allow us to consider various diets and lifestyles that could influence BMI variation and in particular to consider that each area has different climatic conditions in the same season. Even if each user was located in the same place during the study, it was not guaranteed that ethnicity was defined by geographic area since the period of follow-up around one year was not very long, and the current migration rate is high.

Global Analysis. Studies and Applications I

Regarding the calories intake in the meals, the calories counter in the Noom application was not precise but anyway we considered this characteristic in the model since the variation of weight is conditioned by the total daily calories intake. There are no studies in the literature measuring the direct effect of climatic variables on weight loss. Some studies attempted to analyze the possible association between weather conditions and physical activity which is associated with body weight. For example, walking duration was higher during high temperature periods and longer during daylight hours in a sample of older people A study of urban teenagers in Baltimore showed that an increase in temperature led to more physical activities, whereas precipitation was negatively associated with physical activity Tucker et al.

As reported in Tucker et al. Ridgers et al.

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Global Analysis. Studies and Applications II. Global Analysis. Studies and Applications II. Editors: Borisovich, Yurii G., Gliklikh, Yuri E. (Eds.) Free Preview. Topological theory of fixed points on infinite-dimensional manifolds. Pages Borisovich, Yu. G. (et al.) Preview Buy Chapter 30,19 €. The structure of.

Some studies have analyzed the association between climatic variables and depression, a factor associated with obesity in de Wit et al. The level of rainfall was also analyzed, and high levels of rain led to a greater number of depressive symptoms. Therefore, the studies in the literature analysed only specific geographical areas founding contrasting results.

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They showed that each zone has distinct characteristics such as different climatic conditions in the same season that lead to get contrasting conclusions. Such contrasting conclusions were affected strongly by the fact of being in different geographical areas. Instead our study has been able to recruit subjects located in several zones providing a representative sample of the world. This allowed us to keep into account the differences between areas when we measured the association between weather and weight variation and avoid the possible biases due to the presence of different characteristics in each zone.

In other words, our results are not affected by the fact of being in different areas because we corrected for such a possible bias. How to cite this article : Ustulin, M. Effects of climatic variables on weight loss: a global analysis. Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Ng, M. Global, regional, and national prevalence of overweight and obesity in children and adults during — a systematic analysis for the Global Burden of Disease Study The Lancet , — Ogden, C. Prevalence of childhood and adult obesity in the United States, — JAMA , — Brennan, D. Fifty years of fat: news coverage of trends that predate obesity prevalence. BMC Public Health 15 , Mokdad, A. Prevalence of Obesity, Diabetes, and Obesity-related health risk factors, JAMA , 76—79 Tucker, P.

The effect of season and weather on physical activity: a systematic review. Public Health , — Pagoto, S.

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Evidence-based strategies in weight loss mobile apps. Vershik editor Sign in to write a review. We can order this Usually dispatched within 3 weeks. Quantity Add to basket. This item has been added to your basket View basket Checkout. This volume, a sequel to volumes , and , is a selection of survey or expository articles on recent work in global analysis. These articles centre on methods of global analysis in nonlinear equations and topological and geometrical methods of analysis.

An account by V. Tikhomirov on the life and work of A. Kolmogorov is included as a tribute to his influence on the development of mathematics. Added to basket. Michael Spivak. Maths for Science. Sally Jordan.

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Lara Alcock. Quick Calculus. Daniel Kleppner. Lectures 4 and 5 deal with hydrodynamics and 9 and 10 with general relativity.

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Lecture 6 deals with miscellaneous applications, both mathematical and physical, of the concepts of symmetry groups and conserved quantities. Lecture 7 studies quantum mechanics as a hamiltonian system and discusses, e. Finally lecture 8 studies a general method for obtaining global in time solutions to certain evolution equations. It is a pleasure to thank Professors V. Dlab, D. Dawson and M. Grmela for their kind hospitality at Carleton.

Repository Staff Only: item control page. A Caltech Library Service. Applications of global analysis in mathematical physics. Abstract These notes are based on a series of ten lectures given at Carleton University, Ottawa, from June 21 through July 6, More information and software credits.