This document discusses factors that increase cardiovascular disease risk such as genetics, age, and gender. It also discusses important considerations for study design including having a large enough sample size, investigating one variable while controlling for others, and conducting longitudinal studies over a long period of time. Examples provided are the Munster Heart Study and Framingham Study. Metadata analysis is described as analyzing data from all available studies in a particular area.

1. Chapter 1C

2.  Be able to evaluate the design of studies
used to determine health risk factors,
including sample selection and sample size
used to collect data that are both valid and
reliable.
 Know how factors such as genetics, age and
gender increase the risk of CVDs

3.  Sample size must be bigger (number of
people involved)
 Investigate one variable, keep other variable
constant(control).
 Some are carried out over a long time
(longitudinal study)
 Ex. Munster Heart Study – 10856 men, 36-65
ages, Europe; Framingham Study – many
similar American citizens.

4.  Metadata analysis - When data from all the
available studies in a particular area are
analysed

8.  These studies are excellent resource when
investigating whether there is a genetic factor at
work, any differences between them is
environmental.