scholarly journals The Use of Food Images and Crowdsourcing to Capture Real-time Eating Behaviors: Acceptability and Usability Study (Preprint)

2021 ◽  
Author(s):  
Katharine Harrington ◽  
Shannon N Zenk ◽  
Linda Van Horn ◽  
Lauren Giurini ◽  
Nithya Mahakala ◽  
...  
Keyword(s):  
Real Time ◽  
Eating Behavior ◽  
Eating Behaviors ◽  
Significant Risk ◽  
Cost Effective ◽  
Significant Risk Factor ◽  
The United States ◽  
Amazon Mechanical Turk ◽  
Noncommunicable Diseases ◽  
Food Images

BACKGROUND As poor diet quality is a significant risk factor for multiple noncommunicable diseases prevalent in the United States, it is important that methods be developed to accurately capture eating behavior data. There is growing interest in the use of ecological momentary assessments to collect data on health behaviors and their predictors on a micro timescale (at different points within or across days); however, documenting eating behaviors remains a challenge. OBJECTIVE This pilot study (N=48) aims to examine the feasibility—usability and acceptability—of using smartphone-captured and crowdsource-labeled images to document eating behaviors in real time. METHODS Participants completed the Block Fat/Sugar/Fruit/Vegetable Screener to provide a measure of their typical eating behavior, then took pictures of their meals and snacks and answered brief survey questions for 7 consecutive days using a commercially available smartphone app. Participant acceptability was determined through a questionnaire regarding their experiences administered at the end of the study. The images of meals and snacks were uploaded to Amazon Mechanical Turk (MTurk), a crowdsourcing distributed human intelligence platform, where 2 Workers assigned a count of food categories to the images (fruits, vegetables, salty snacks, and sweet snacks). The agreement among MTurk Workers was assessed, and weekly food counts were calculated and compared with the Screener responses. RESULTS Participants reported little difficulty in uploading photographs and remembered to take photographs most of the time. Crowdsource-labeled images (n=1014) showed moderate agreement between the MTurk Worker responses for vegetables (688/1014, 67.85%) and high agreement for all other food categories (871/1014, 85.89% for fruits; 847/1014, 83.53% for salty snacks, and 833/1014, 81.15% for sweet snacks). There were no significant differences in weekly food consumption between the food images and the Block Screener, suggesting that this approach may measure typical eating behaviors as accurately as traditional methods, with lesser burden on participants. CONCLUSIONS Our approach offers a potentially time-efficient and cost-effective strategy for capturing eating events in real time.

scholarly journals The Use of Food Images and Crowdsourcing to Capture Real-time Eating Behaviors: Acceptability and Usability Study

10.2196/27512 ◽  
2021 ◽  
Vol 5 (12) ◽  
pp. e27512
Author(s):  
Katharine Harrington ◽  
Shannon N Zenk ◽  
Linda Van Horn ◽  
Lauren Giurini ◽  
Nithya Mahakala ◽  
...  
Keyword(s):  
Real Time ◽  
Eating Behavior ◽  
Eating Behaviors ◽  
Significant Risk ◽  
Cost Effective ◽  
Significant Risk Factor ◽  
The United States ◽  
Amazon Mechanical Turk ◽  
Noncommunicable Diseases ◽  
Food Images

Background As poor diet quality is a significant risk factor for multiple noncommunicable diseases prevalent in the United States, it is important that methods be developed to accurately capture eating behavior data. There is growing interest in the use of ecological momentary assessments to collect data on health behaviors and their predictors on a micro timescale (at different points within or across days); however, documenting eating behaviors remains a challenge. Objective This pilot study (N=48) aims to examine the feasibility—usability and acceptability—of using smartphone-captured and crowdsource-labeled images to document eating behaviors in real time. Methods Participants completed the Block Fat/Sugar/Fruit/Vegetable Screener to provide a measure of their typical eating behavior, then took pictures of their meals and snacks and answered brief survey questions for 7 consecutive days using a commercially available smartphone app. Participant acceptability was determined through a questionnaire regarding their experiences administered at the end of the study. The images of meals and snacks were uploaded to Amazon Mechanical Turk (MTurk), a crowdsourcing distributed human intelligence platform, where 2 Workers assigned a count of food categories to the images (fruits, vegetables, salty snacks, and sweet snacks). The agreement among MTurk Workers was assessed, and weekly food counts were calculated and compared with the Screener responses. Results Participants reported little difficulty in uploading photographs and remembered to take photographs most of the time. Crowdsource-labeled images (n=1014) showed moderate agreement between the MTurk Worker responses for vegetables (688/1014, 67.85%) and high agreement for all other food categories (871/1014, 85.89% for fruits; 847/1014, 83.53% for salty snacks, and 833/1014, 81.15% for sweet snacks). There were no significant differences in weekly food consumption between the food images and the Block Screener, suggesting that this approach may measure typical eating behaviors as accurately as traditional methods, with lesser burden on participants. Conclusions Our approach offers a potentially time-efficient and cost-effective strategy for capturing eating events in real time.

scholarly journals PREVALENCE OF SMOKING IN ADULT POPULATION OF IRKUTSK

2016 ◽  
Vol 1 (6) ◽  
pp. 153-156
Author(s):  
Максикова ◽  
Tatyana Maksikova ◽  
Бабанская ◽  
Evgeniya Babanskaya ◽  
Меньшикова ◽  
...  
Keyword(s):  
Risk Factor ◽  
Adult Population ◽  
Age Groups ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
Noncommunicable Diseases ◽  
Age Difference ◽  
Age Group ◽  
Considerable Problem ◽  
The One

Smoking is a significant risk factor of chronic noncommunicable diseases. Smoking prevalence is variable in different populations. A study of the prevalence of this risk factor allows to estimate its contribution to the development of cardiovascular pathology, to plan the necessary amount of medical care for people using tobacco, and to determine the effectiveness of prevention activities in the region. As a result of the study, smoking frequency in population of the Irkutsk region older 18years of age or over was established as 29.5%. The number of smokers increased with age, reaching maximum value of 38.6% in the group 30–39 years. Male smokers made maximum in the age group 30–39 years, women – in the age group of 18–19 years. The average age of smokers was 34 years, the one of nonsmokers – 43 years. The age difference was 9 years, and it was lower in the group of men than in the group of women (5 and 11 years, respectively). The number of the smoking men were 3 times larger, than women: 50.2% and 13.5%, respectively. Among persons with arterial hypertension, 22.1% were smoking with the maximum frequency of smoking in age groups from 20 to 49 years. These figures point to a considerable problem of smoking in the region.

Determining the Utility of a Laboratory Eating Paradigm to Explore Social Eating

2016 ◽  
Vol 60 (1) ◽  
pp. 1120-1124
Author(s):  
Phillip Jasper ◽  
Adam Hoover ◽  
Eric Muth
Keyword(s):  
Eating Behavior ◽  
Healthy Eating ◽  
Eating Behaviors ◽  
The United States ◽  
Overweight And Obesity ◽  
Subjective Ratings ◽  
Health And Nutrition ◽  
Consumption Rates ◽  
Social Eating ◽  
University Laboratory

According to a recent National Health and Nutrition Examination Survey, overweight and obesity have reached epidemic levels in the United States. Researchers are increasingly engaged in exploring eating behavior with the goals of trying to understand what elements of eating behavior might lead to overweight and obesity and applying knowledge from these studies to encourage people to engage in healthy eating behaviors. The purpose of the current study was to determine the utility of a new laboratory eating paradigm that attempts to create a natural social eating environment while maintaining the control possible within a university laboratory. Known effects of gender on eating behavior (e.g. consumption rates and bite size), positive subjective ratings of the food item used, and subjective ratings of perceived eating behavior were replicated to show the utility of the paradigm.

scholarly journals Decreasing Incidence of Skin and Soft-tissue Infections in 86 US Emergency Departments, 2009–2014

2018 ◽  
Vol 68 (3) ◽  
pp. 453-459 ◽  
Author(s):  
Ethan Morgan ◽  
Sam Hohmann ◽  
Jessica P Ridgway ◽  
Robert S Daum ◽  
Michael Z David
Keyword(s):  
United States ◽  
Soft Tissue ◽  
Hiv Infection ◽  
Emergency Departments ◽  
Medical Center ◽  
Academic Medical Center ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
The United States ◽  
Soft Tissue Infections

Abstract Background The incidence of skin and soft-tissue infections (SSTIs), for which human immunodeficiency virus (HIV) is a significant risk factor, in United States emergency departments (EDs) increased dramatically after 2000 with the emergence of community-associated methicillin-resistant Staphylococcus aureus. Few studies have examined SSTI incidence among HIV-infected and non–HIV-infected patients in the United States after 2010. Methods Data were obtained for patient encounters at all academic medical center EDs affiliated with the Vizient clinical data warehouse assigned an SSTI-associated code based on the International Classification of Diseases, Ninth Revision, between 1 January 2009 and 31 December 2014. The rate was calculated per 1000 ED encounters by year and stratified by SSTI, HIV infection, or both, and by age group, race, payer type, and region of care. Poisson regression was used to assess temporal change over the study period. Results In 2009–2014, a total of 47317 HIV-associated and 820440 SSTI-associated encounters were recorded among 25239781 ED patient encounters. The rate of SSTIs decreased by 8% among all patients and by 14.6%, among those with HIV infection. The SSTI incidence overall decreased from 32.0 to 29.7 per 1000 ED encounters between 2009 and 2014. HIV-infected patients had a significantly higher rate of SSTIs than HIV-uninfected patients (adjusted rate ratio, 1.91; 95% confidence interval, 1.84–1.99). Conclusions The decline in SSTI incidence in US EDs between 2009 and 2014 is a remarkable epidemiologic shift from the increase in SSTIs after 2000, and further research is necessary to assess reasons for this decrease.

scholarly journals Causal Analysis of Health Interventions and Environments for Influencing the Spread of COVID-19 in the United States of America

2020 ◽  
Author(s):  
zhouxuan Li ◽  
Tao Xu ◽  
Kai Zhang ◽  
Hong-Wen Deng ◽  
Eric Boerwinkle ◽  
...  
Keyword(s):  
Risk Factor ◽  
Unemployment Rate ◽  
Additive Model ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
The United States ◽  
Health Interventions ◽  
Health Crisis ◽  
The Us ◽  
Pharmaceutical Interventions

As of August 27, 2020, the number of cumulative cases of COVID-19 in the US exceeded 5,863,363 and included 180,595 deaths, thus causing a serious public health crisis. Curbing the spread of Covid-19 is still urgently needed. Given the lack of potential vaccines and effective medications, non-pharmaceutical interventions are the major option to curtail the spread of COVID-19. An accurate estimate of the potential impact of different non-pharmaceutical measures on containing, and identify risk factors influencing the spread of COVID-19 is crucial for planning the most effective interventions to curb the spread of COVID-19 and to reduce the deaths. Additive model-based bivariate causal discovery for scalar factors and multivariate Granger causality tests for time series factors are applied to the surveillance data of lab-confirmed Covid-19 cases in the US, University of Maryland Data (UMD) data, and Google mobility data from March 5, 2020 to August 25, 2020 in order to evaluate the contributions of social-biological factors, economics, the Google mobility indexes, and the rate of the virus test to the number of the new cases and number of deaths from COVID-19. We found that active cases/1000 people, workplaces, tests done/1000 people, imported COVID-19 cases, unemployment rate and unemployment claims/1000 people, mobility trends for places of residence (residential), retail and test capacity were the most significant risk factor for the new cases of COVID-19 in 23, 7, 6, 5, 4, 2, 1 and 1 states, respectively, and that active cases/1000 people, workplaces, residential, unemployment rate, imported COVID cases, unemployment claims/1000 people, transit stations, mobility trends (transit) , tests done/1000 people, grocery, testing capacity, retail, percentage of change in consumption, percentage of working from home were the most significant risk factor for the deaths of COVID-19 in 17, 10, 4, 4, 3, 2, 2, 2, 1, 1, 1, 1 states, respectively. We observed that no metrics showed significant evidence in mitigating the COVID-19 epidemic in FL and only a few metrics showed evidence in reducing the number of new cases of COVID-19 in AZ, NY and TX. Our results showed that the majority of non-pharmaceutical interventions had a large effect on slowing the transmission and reducing deaths, and that health interventions were still needed to contain COVID-19.

Perinatal Experiences of Low-Income and Incarcerated Women

2014 ◽  
Author(s):  
Julie Poehlmann ◽  
Rebecca Shlafer
Keyword(s):  
Pregnant Women ◽  
Low Income ◽  
Significant Risk ◽  
Perinatal Outcomes ◽  
Psychosocial Interventions ◽  
Significant Risk Factor ◽  
The United States ◽  
Incarcerated Women ◽  
Negative Effects ◽  
Pregnancy And Postpartum

Poverty is a significant risk factor for suboptimal pregnancy and infant outcomes. Because of widespread recognition of the negative effects of poverty during pregnancy, federal programs in the United States and other health and psychosocial interventions are available to improve pregnancy and postpartum outcomes, with some success. Incarceration is increasingly recognized as a significant risk for pregnant women and their children. When they enter jail or prison, 6–10% of incarcerated women are pregnant, and more than 1,400 women per year give birth while incarcerated. Pregnant prisoners are more likely to experience risk factors associated with poor perinatal outcomes and are likely to receive inadequate prenatal care, and many states still allow shackling of incarcerated women during labor and birth. Although few interventions are available for incarcerated pregnant women, several progressive programs, such as those involving doulas or nursery programs, are available for a minority of affected women.

Ultrasound in radiology —state of the art

2011 ◽  
Author(s):  
David O. Cosgrove
Keyword(s):  
Real Time ◽  
Far East ◽  
Major Change ◽  
Cost Effective ◽  
The United States ◽  
Technical Developments ◽  
The People ◽  
Picture Archiving And Communication ◽  
Magnetic Resonance Imaging Mri ◽  
Time Systems

The practice of ultrasound in radiology has continued to develop and shows no signs of slowing down. The changes affect the systems themselves, with important technical developments, as well as the ways they are used, and to some extent these are interlinked. The earliest static scanners were so difficult to use that only dedicated personnel could find the time and make the effort required to use them. This led to a small cohort of enthusiasts offering a limited and expensive service. Strangely, they were a mixture of doctors (many of whom were not radiologists) and physicists, perhaps reflecting the complexity of the scanners. with the development of real-time systems and increasingly as they have become easier to operate, ultrasound found its place within radiology departments and, in parallel, in cardiology and obstetric units as well as in vascular labs. Here the role of physicists faded and most of the people performing the scans were medical, a situation that still obtains in many parts of the world, notably in the Far East (in China, the doctors are ultrasound specialists) and in many European countries. In others, especially in the United States, technologists or radiographers took over the actual scanning, leaving radiologists or their equivalent (cardiologists, obstetricians) to read and report the studies by analogy with other scanning modalities such as computed tomography (CT) and magnetic resonance imaging (MRI). The driver for this major change has mainly been financial: medics are expensive and sharing the workload with technologists is cost-effective. However, this shift comes with a penalty: as ultrasound is a real-time method and the techniques required to make the studies are very interactive, simply reading a set of images on a PACS (picture archiving and communication system) workstation deprives the radiologist of dynamic information that can be critical to making the diagnosis. In some places the response to this has been to train the technicians or radiographers to interpret and report their own cases. Though often disapproved of by the regulatory authorities and exposing practitioners to risks of litigation, this approach has been popular amongst radiographers only partly because their extended role is rewarded by additional pay.

scholarly journals Quantification of toxic metallic elements using machine learning techniques and spark emission spectroscopy

2019 ◽  
Author(s):  
Seyyed Ali Davari ◽  
Anthony S. Wexler
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Emission Spectroscopy ◽  
Cost Effective ◽  
The United States ◽  
Machine Learning Techniques ◽  
Metallic Elements ◽  
Learning Techniques ◽  
Single Feature ◽  
Us Epa

Abstract. The United States Environmental Protection Agency (US EPA) list of Hazardous Air Pollutants (HAPs) includes metal elements suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metallic elements in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost effective technique that can be used for analyzing toxic metallic elements in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metallic elements targeted by US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. Least Absolute Shrinkage and Selection Operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metallic elements from the observed spectra. The limits of detections (LOD) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however for some elements the single-feature LOD marginally outperforms LASSO LOD. The combination of low cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data driven solutions to costly measurements.

scholarly journals Quantification of toxic metals using machine learning techniques and spark emission spectroscopy

2020 ◽  
Vol 13 (10) ◽  
pp. 5369-5377
Author(s):  
Seyyed Ali Davari ◽  
Anthony S. Wexler
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Toxic Metals ◽  
Emission Spectroscopy ◽  
Cost Effective ◽  
The United States ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Single Feature ◽  
Us Epa

Abstract. The United States Environmental Protection Agency (US EPA) list of hazardous air pollutants (HAPs) includes toxic metal suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metals in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost-effective technique that can be used for analyzing toxic metals in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metals targeted by the US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. The least absolute shrinkage and selection operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metals from the observed spectra. The limits of detections (LODs) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however, for some toxic metals the single-feature LOD marginally outperforms LASSO LOD. The combination of low-cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data-driven solutions to costly measurements.

Recent changes in the treatment of hypertension

2014 ◽  
Vol 4 (3) ◽  
pp. 143-145
Author(s):  
Bridget Bradley ◽  
Lisa Janssen Carlson
Keyword(s):  
European Society ◽  
Treatment Guidelines ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
The United States ◽  
Joint National Committee ◽  
National Committee ◽  
Treatment Of Hypertension ◽  
European Society Of Cardiology ◽  
Detection Evaluation

Hypertension affects a large portion of the United States' population and is a significant risk factor for cardiovascular events. A variety of treatment guidelines exist including the American Diabetes Association, European Society of Hypertension/European Society of Cardiology and the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure guidelines. The following is a summary of these guidelines regarding the effective treatment of hypertension.

Sign in / Sign up

Export Citation Format

Share Document