Ten-year health goals put accent on behavior

1989 ◽  
Author(s):  
Susan Landers
Keyword(s):  
Health Goals

Self-set health goals and current health behavior

2004 ◽  
Author(s):  
W. Gebhardt ◽  
G. Pomaki ◽  
K. Joekes ◽  
S. Maes ◽  
S. Boersma ◽  
...  
Keyword(s):  
Health Behavior ◽  
Current Health ◽  
Health Goals

Balancing career and health goals: Shifting goal systems maximizes success

2007 ◽  
Author(s):  
Grainne Fitzsimons ◽  
James Y. Shah ◽  
Arie Kruglanski
Keyword(s):  
Health Goals ◽  
Goal Systems

Flavor halos andconsumer perceptions offood healthfulness

2019 ◽  
Vol 53 (4) ◽  
pp. 685-707
Author(s):  
Nguyen Pham ◽  
Maureen Morrin ◽  
Melissa G. Bublitz
Keyword(s):  
Cognitive Biases ◽  
Underlying Mechanism ◽  
Repeated Exposure ◽  
Future Research ◽  
Medicinal Products ◽  
Dietary Compliance ◽  
Health Goals ◽  
Health Related ◽  
Prevalence Of Obesity ◽  
Cough Syrup

Purpose This paper aims to examine how repeated exposure to health-related products that contain flavors (e.g. cherry-flavored cough syrup) create “flavor halos” that can bias perceptions about the healthfulness of foods that contain the same flavors (e.g. cherry-flavored cheesecake). Design/methodology/approach Six experiments, using both between- and within-subjects designs, explore the effects of flavor halos in hypothetical and actual consumption settings. They test the underlying mechanism, rule out competing explanations and identify an opportunity to correct the cognitive biases created by flavor halos. Findings Flavor halos can be created via repeated exposure to flavored medicinal products in the marketplace. These flavor halos bias dieters’ judgments about the healthfulness of vice foods containing such flavors. Dieters are motivated toward a directional conclusion about food healthfulness to mediate the guilt associated with consuming indulgent products. Providing dieters with corrective information mitigates these effects. Research limitations/implications The authors examine one way flavor halos are created –via repeated exposure to flavored medicinal products. Future research should explore other ways flavor halos are created and other ways to mitigate their effects. Practical implications Considering the prevalence of obesity, organizations striving to help consumers pursue health goals (e.g. weight watchers) can use flavors to improve dietary compliance. Health-care organizations can help consumers understand and correct the cognitive biases associated with flavor halos. Originality/value By identifying flavor halos, this work adds to the literature investigating how flavors influence consumers’ judgments about healthfulness. The results suggest dieters apply flavor halos as they engage in motivated reasoning to license their indulgent desires.

scholarly journals The European Association for the Study of Obesity (EASO) Endorses the Milan Charter on Urban Obesity

Obesity Facts ◽  
2021 ◽  
pp. 1-6
Author(s):  
Michele O. Carruba ◽  
Luca Busetto ◽  
Sheree Bryant ◽  
Antonio Caretto ◽  
Nathalie J. Farpour-Lambert ◽  
...  
Keyword(s):  
Public Health ◽  
Social Stigma ◽  
National Level ◽  
Well Being ◽  
Communicable Diseases ◽  
Urban Environments ◽  
Shared Responsibility ◽  
Access To Treatment ◽  
Non Communicable Diseases ◽  
Health Goals

The Milan Charter on Urban Obesity highlights the challenges of urban environments as a battleground for human health, as cities are often organized to subvert public health goals, and promote rather than prevent the development of obesity and consequent non-communicable diseases. The Charter articulates ten principles which detail actions and strategies through which general practitioners, diverse medical specialists, related healthcare professionals, administrators and healthcare practice managers, policy actors – within health systems and at a national level – along with experts across disciplines, and citizens, can work in cooperation to meet this challenge and improve public health. The Charter urges the adoption of decisions that deliver the following: (i) policies which enable our cities to become healthier and less obesogenic, more supportive of well-being and less health-disruptive in general, and (ii) policies that fully support primary prevention strategies, that address social stigma, and that ensure fair access to treatment for people living with obesity. The Milan Charter on Urban Obesity aims to raise awareness of our shared responsibility for the health of all citizens, and focuses on addressing the health of people living with obesity – not only as a challenge in its own right, but a gateway to other major non-communicable diseases, including cardiovascular diseases, type 2 diabetes, and some cancers.

scholarly journals Comparison of Recreational Fish Consumption Advisories Across the USA

2021 ◽  
Author(s):  
Brittany M. Cleary ◽  
Megan E. Romano ◽  
Celia Y. Chen ◽  
Wendy Heiger-Bernays ◽  
Kathryn A. Crawford
Keyword(s):  
Mississippi River ◽  
Fish Consumption ◽  
Lake Michigan ◽  
Acute Tolerance ◽  
Health Goals ◽  
Fish Consumption Advisories ◽  
Regional Collaboration ◽  
Slope Factor ◽  
The Usa ◽  
Lower Mississippi River

Abstract Purpose of Review Our comparative analysis sought to understand the factors which drive differences in fish consumption advisories across the USA — including exposure scenarios (acute and chronic health risk, non-cancer and cancer health endpoints), toxicity values (reference dose, cancer slope factor, acute tolerance level), and meal size and bodyweight assumptions. Recent Findings Fish consumption provides essential nutrients but also results in exposure to contaminants such as PCBs and methylmercury. To protect consumers from the risks of fish contaminants, fish consumption advisories are established, most often by state jurisdictions, to estimate the amount of a certain fish species a person could consume throughout their lifetime without harm. However, inconsistencies in advisories across the USA confuse consumers and undermine the public health goals of fish advisory programs. To date, no rigorous comparison of state and national fish consumption advisories has been reported. Summary Our work identifies discrepancies in key assumptions used to derive risk-based advisories between US states, reflecting differences in the interpretation of toxicity science. We also address the implications for these differences by reviewing advisories issued by contiguous states bordering two waterbodies: Lake Michigan and the Lower Mississippi River. Our findings highlight the importance of regional collaboration when issuing advisories, so that consumers of self-caught fish are equipped with clear knowledge to make decisions to protect their health.

scholarly journals Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data

2021 ◽  
Vol 6 (5) ◽  
pp. e005387
Author(s):  
Tim Adair ◽  
Sonja Firth ◽  
Tint Pa Pa Phyo ◽  
Khin Sandar Bo ◽  
Alan D Lopez
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Integration Method ◽  
Mortality Rates ◽  
Vital Statistics ◽  
Death Registration ◽  
Chronic Respiratory Diseases ◽  
Health Goals ◽  
Specific Mortality ◽  
Four Causes

IntroductionThe measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.MethodsThe integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.ResultsIn Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.ConclusionThis integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

scholarly journals Machine Learning and Sensor Fusion for Estimating Continuous Energy Expenditure

AI Magazine ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 55 ◽  
Author(s):  
Nisarg Vyas ◽  
Jonathan Farringdon ◽  
David Andre ◽  
John Ivo Stivoric
Keyword(s):  
Machine Learning ◽  
Energy Expenditure ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Sensor Technology ◽  
Health Goals ◽  
System A ◽  
Multi Sensor Data Fusion ◽  
Learning Techniques ◽  
Insight Into

In this article we provide insight into the BodyMedia FIT armband system — a wearable multi-sensor technology that continuously monitors physiological events related to energy expenditure for weight management using machine learning and data modeling methods. Since becoming commercially available in 2001, more than half a million users have used the system to track their physiological parameters and to achieve their individual health goals including weight-loss. We describe several challenges that arise in applying machine learning techniques to the health care domain and present various solutions utilized in the armband system. We demonstrate how machine learning and multi-sensor data fusion techniques are critical to the system’s success.

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