DATA: Body Mass Index and Waist to Hip Ratio

Here is the link to the data.

Please check you data for completeness make changes - you have editing power.

By next week you need to post a comment on how you would analyse this data.

Look at Chapters 1 and 2 of this blog for help.

https://docs.google.com/spreadsheet/ccc?key=0Ao5VdKkjuh89dFlFNXJNUjh6OWJIQVJQMkpVWTh4Z3c

PowerPoints can be downloaded from:

http://planet.uwc.ac.za/nisl/ESS_2012/ESS132/

PowerPoint 2: Measures of location

When conducting an experiment, we collect data, usually in the form of quantitative variables that are measured or observed. These values we refer to as response variables.

Data will be either discrete or continuous. Discrete variables are obtained by counting. There are a finite, or countable number of choices available with discrete data. You can’t have 2.36 people present in the room for example.

Continuous variables are usually obtained by measuring. Length, mass, time – these are all examples of continuous variables. Since continuous variables are real numbers, we usually round them in other words, we put a boundary on the number of decimal places.

Learn more by opening up the following Google Slide Show
https://docs.google.com/open?id=0B45VdKkjuh89aGYxV2tIeW1kNVU

PowerPoint 1: Data types and representation

When conducting an experiment, we collect data, usually in the form of quantitative variables that are measured or observed. These values we refer to as response variables.

Data will be either discrete or continuous. Discrete variables are obtained by counting. There are a finite, or countable number of choices available with discrete data. You can’t have 2.36 people present in the room for example.

Continuous variables are usually obtained by measuring. Length, mass, time – these are all examples of continuous variables. Since continuous variables are real numbers, we usually round them in other words, we put a boundary on the number of decimal places.

Learn more by opening up the following Google Slide Show

https://docs.google.com/open?id=0B45VdKkjuh89c1IzbDdqX0NzVEk

Capetonians SA's fattest by Janice Keogh (Beeld 2010-09-08)

Johannesburg - About two-thirds of women in South Africa are overweight. This is just one of the findings in a survey done in July among 500 adults in the country's four biggest cities, on behalf of the pharmaceutical company GlaxoSmithKline (GSK). Altogether 72% of Cape Town's residents are overweight. Pretoria comes second at 68%, followed by Johannesburg at 59% and Durban at 52%. The study also showed that, with 61% of adults in these four cities being overweight, South Africa is the country with the third-most overweight citizens, with America coming first and Britain second. Australia is in fourth place. 

Dr Jeff King, a Johannesburg cardiologist who was involved in the study, attributes this tendency to South Africans becoming more westernised and increasingly likely to eat junk food. According to Andrea Ellens, who was also involved in the survey, the world reached a turning point a few years ago.

There are currently more overweight than malnourished people worldwide.Jonathan Girling, deputy president of consumer healthcare at GSK, said the purpose of the survey was "to determine how healthy South Africans are". According to Celynn Erasmus, a dietician, many people sacrifice their health for money. "Being overweight, obese or morbidly obese combined with stress in the workplace is a recipe for disaster."

Besides work stress, things like cold temperatures, boredom and depression also tend to make people eat more, according to the study.
Ellens says the cost of healthy food has a significant impact on people's weight. About 40% of respondents' food shopping is driven by price, and 59% feel the government should do more to prevent citizens from becoming obese, for instance by making healthier food more affordable.

Ellens also said that overweight parents have an impact on how their children eat. Children were not included in the sample, but previous studies by the World Health Organisation showed that 17% of children in South Africa are overweight.

Please complete the following information collected in class today – use the link below to determine ratios and risks

Measurements to be done in class

	Scale A	Scale B	Scale C Digital (+ 0.2kg)
Weight (Mass) kg
Height (cm)		Body Mass Index BMI		Risk
Waist (cm)	Hip (cm)	WHR (Waist to Hip ratio)		Risk
Age		Exercise (30 min or more) Circle the most appropriate	1-3 times a month	1-2 day a week
Gender (M/F)			2-4 days a week	More than 4 days a week

 Please use the link below to calculate BMI and WHR and then condition (risk)

http://www.scars1.com/CareTools/Calculators/Advanced_BMI/

Course website: http://ESS132.blogspot.com (Part of our new Carbon Campus site http://carboncampus.blogspot.com)

Where to make your measurements Male/Female

 Body Mass Index

The body mass index (BMI), or Quetelet index, is a heuristic proxy for human body fat based on an individual's weight and height. BMI does not actually measure the percentage of body fat. It was devised between 1830 and 1850 by the Belgian polymath Adolphe Quetelet during the course of developing "social physics".Body mass index is defined as the individual's body mass divided by the square of his or her height. The formulae universally used in medicine produce a unit of measure of kg/m². BMI can also be determined using a BMI chart, which displays BMI as a function of weight (horizontal axis) and height (vertical axis) using contour lines for different values of BMI or colors for different BMI categories.

Source: http://en.wikipedia.org/wiki/Body_mass_index

Waist to Hip Ratio

The WHR has been used as an indicator or measure of the health of a person, and the risk of developing serious health conditions. Research shows that people with "apple-shaped" bodies (with more weight around the waist) face more health risks than those with "pear-shaped" bodies who carry more weight around the hips.

WHR is used as a measurement of obesity, which in turn is a possible indicator of other more serious health conditions.
WHO STEPS states that abdominal obesity is defined as a waist–hip ratio above 0.90 for males and above 0.85 for females, or a body mass index (BMI) above 30.0. The National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) states that women with waist–hip ratios of more than 0.8, and men with more than 1.0, are at increased health risk because of their fat distribution. 

WHR has been found to be a more efficient predictor of mortality in older people than waist circumference or BMI. If obesity is redefined using WHR instead of BMI, the proportion of people categorized as at risk of heart attack worldwide increases threefold. The body fat percentage is considered to be an even more accurate measure of relative weight. Of these three measurements, only the waist–hip ratio takes account of the differences in body structure. Hence, it is possible for two women to have vastly different body mass indices but the same waist–hip ratio, or to have the same body mass index but vastly different waist–hip ratios.

Even in ancient civilizations globally, female representations are most often in the 0.6-0.7 range for WHR, suggesting a preference towards lower WHR.

Other studies have found that waist circumference, not WHR, to be a good indicator of cardiovascular risk factors, body fat distribution and hypertension in type 2 diabetes.

Source: http://en.wikipedia.org/wiki/Waist%E2%80%93hip_ratio

ESS132 Overview of Course and listing of assignment details) 2012

Meetings (Lectures Practicals)

THIRD TERM

First week, (Monday 3^rd period CH1, Wednesday  2^nd period SC9, Thursday 5^th-7^th Collaborative Learning Lab and Friday 4^th period  SC9)

Rest of term 3 meet Thursday 5^th-7^th Collaborative Learning Lab

FOURTH TERM

Meet Thursday 5^th-7^th Collaborative Learning Lab

Last week of term (venues to be announce, Thursday 5^th-7^th Collaborative Learning Lab)

Availability

Dr Richard Knight (General correspondence knight.rich@gmail.com submissions knight.rich@ymail.com)

Mondays 2am until 5pm (3D GIS lab ,BCB 5^th floor New Life Science Building)

Fridays 9am until 11:30am (3D GIS lab ,BCB 5^th floor New Life Science Building)

Mr Martin Cocks (Correspondence mcocks@uwc.ac.za – only after 23 August)

Thursdays ONLY (10am until 1pm – only after 23 August)

Course Outcome

The student will have demonstrated the ability to: Analyse a case study and combine content and skills that have been learnt in other modules and apply them to a particular case study.

The content to be applied will be gained from any of the other five first year Environmental and Sustainability Studies modules as well as facts pertaining to the particular case as discussed with the lecturer concerned.

Course Assessment

Introduction to Measurement and Statistics (Cape Town Student Health Survey) 25% (Due Date: 10/08/2012)

Concept Map (Hand Prepared) Globalisation Cartograms 25% (Due Date 24/08/2012)

Preliminary Research Report 25% (Dute Date09/10/2012)(This and final report = EXAM Mark)

Preliminary Research Report 25% (Dute Date30/10/2012) NOTE WE CANNOT ACCEPT LATE REPORTS

Course Website

Material will be put up at the following URL http://ess132.blogspot.com

Detailed content will be posted at this site including full descriptions of each assignment.