Transient pain and discomfort when wearing high-heeled shoes.

In the dynamic world of fashion, high-heeled footwear is revered as a symbol of style, luxury and sophistication. Yet, beneath the facade of elegance of classy footwear lies the harsh reality of discomfort and pain. Thus, this study aims to investigate the influence of wearing high-heeled shoes on the sensation of pain across different body regions over a period of 6 h. It involved fifty female participants, all habitual wearers of high-heeled shoes, aged between 20 and 30 years. Each participant kept a record of their perceptions of pain and discomfort every hour for a total of 6 h using a 0-10 pain scale with 0 indicating no pain and 10 indicating severe pain. The findings reveal a progressive rise in pain throughout wear, with the most intense pain reported in the back, calcaneus, and metatarsals. The analysis shows that after approximately 3.5 h, participants experience significant increases in pain levels. However, the relationship between heel height and pain is not linear. It appears that a heel height of 7.5 cm is the threshold where overall body pain becomes significant. The study suggests that a duration of 3.5 h of wear and a heel height of 7.5 cm serve as critical points to decrease overall body pain. Moreover, beyond this heel height, knee pain diminishes compared to other body areas possibly due to the shift towards a more neutral posture. The study findings, coupled with the recommendations, can assist footwear designers in crafting not only stylish but also comfortable shoes.

Efficacy of information extraction from bar, line, circular, bubble and radar graphs.

With the emergence of enormous amounts of data, numerous ways to visualize such data have been used. Bar, circular, line, radar and bubble graphs that are ubiquitous were investigated for their effectiveness. Fourteen participants performed four types of evaluations: between categories (cities), within categories (transport modes within a city), all categories, and a direct reading within a category from a graph. The representations were presented in random order and participants were asked to respond to sixteen questions to the best of their ability after visually scanning the related graph. There were two trials on two separate days for each participant. Eye movements were recorded using an eye tracker. Bar and line graphs show superiority over circular and radial graphs in effectiveness, efficiency, and perceived ease of use primarily due to eye saccades. The radar graph had the worst performance. "Vibration-type" fill pattern could be improved by adding colors and symbolic fills. Design guidelines are proposed for the effective representation of data so that the presentation and communication of information are effective.

Lifestyle and socioeconomic determinants of diabetes: Evidence from country-level data.

OBJECTIVE: The objectives of the study is to investigate the global socioeconomic risk factors associated with diabetes prevalence using evidence from available country-level data. DESIGN: A cross-sectional study based on (2010 & 2019) countrywide Health Nutrition and Population Statistics data. POPULATION: People ages 20-79 who have diabetes. SETTING: One hundred and thirty-two countries or territories in the world. PRIMARY OUTCOME MEASURE: Diabetes prevalence rates were determined from (2010 & 2019) countrywide Health Nutrition and Population Statistics (Health Stats, World Bank Group). RESULTS: In 2010, a 1% increase in per capita income and total tobacco consumption is associated with a 0.92% (95% CI 0.64% to 1.19%) and 0.02% (95% CI 0.006% to 0.047%) increase in diabetes prevalence respectively; and a 1% increase in alcohol consumption is associated with a -0.85% (95% CI -1.17% to -0.53%) decrease in diabetes prevalence. Statistically significant socioeconomic and lifestyle indices positively associated with diabetes prevalence included gross national income; overweight prevalence (BMI>25 kg/m2); and tobacco consumption. Statistically significant inverse associations with global diabetes prevalence included total population size; unemployment and alcohol consumption. The 2019 data was removed due to sparsity of data. CONCLUSION: Statistically significant global lifestyle and socioeconomic determinants of diabetes prevalence include alcohol consumption; tobacco consumption; overweight prevalence; per capita income; total population and unemployment rates. Determinants of diabetes include modifiable risk factors which are consistent at both the micro and macro level and include tobacco consumption and overweight prevalence. Factors which are non-modifiable and warrant further investigation include total population and unemployment rates, which were inversely associated with diabetes prevalence and are a product of other underlying factors. Other determinants such as alcohol consumption was also inversely associated with diabetes prevalence, but has been observed to have both negative and positive associations with diabetes at the micro-level. These associations were dependent upon the amount of alcohol consumed. Global cut-off point of alcohol consumption is critical to establish global policies to reduce diabetes prevalence. Overall, the use of cross-sectional based study for country level aggregate data is a critical tool that should be considered when making global joint strategies or policies against diabetes in both data analysis and decision making.