Epidemiology Flashcards
• Lind w first experient and had to do with nutrition
was a Scottish doctor, a pioneer of naval
hygiene and expert on the treatment of scurvy.
• Selected 12 men from the ship, all suffering from
scurvy,
– divided them into six pairs,
– giving each group different additions to their
basic diet.
• Cider, Seawater, A mixture of garlic,
mustard & horseradish, Spoonfuls
of vinegar, Oranges, Lemons
• Those fed citrus fruits experienced a
remarkable recovery.
critical trial
Goldberger
second landmark study- also nutrition
Physician & epidemiologist discovered the cause for pellagra,
known as infectious disease, resulting from a diet deficient in
vitamin B3 (niacin), that killed many poor Southerners in the
early part of the 20th century.
• Observation (poor neighborhood, institutions, dietary status)
• Requested fresh foods containing fruits, vegetables &meat
from Washington were provided to children in two
Mississippi orphanages & to inmates. Results were dramatic;
• Those fed a diet of fresh meat, milk & vegetables
instead of a corn-based diet recovered from
pellagra. Those without the disease who ate the new diet did
not contract pellagra.
Joseph Goldberger (1874 - 1929)
Observation, Hypothesis, Test, Conclusion
requested 20 ppl on death row
was unique as it had a control study
• What is epidemiology?
Originates from the Greek words, epi (upon) +
demos (people) + logy (study of)
study of ppl
“The study of the distribution & determinants of health related states & events in populations, • & the application of this study to control health problems” John M. Last, Dictionary of Epidemiology
Distribution?
how are different regions affected and others are not
Affected population • Place • Time • Age • Sex (can also be gender) • Race • Occupation • Income • Education • Exposure to agents
Determinants?
host factors
enviro factors
• Host factors: – Age – Sex – Ethnicity – Genetic make up – Diet – Physical activity – Physiologic state (example age - uni students have bad diet- lowers immune system) • Environmental factors – Living conditions – Occupation – Location – Lifestyle
What is epidemiology, really?
• Study of the health and disease of the population. • Basic science of public health •What causes disease? •How does disease spread ? •What prevents disease? what works .in controlling disease?
what is epidimiology used for
- Provide the scientific basis to prevent disease &
injury & promote health. - Determine relative importance to establish
priorities for research & action. - Identify sections of the population at greatest
risk to target interventions. - the effectiveness of programs in improving
the health of the population - Study natural history of disease from precursor
states through clinical course - Conduct surveillance of disease and injury
occurrence in populations
• 22 health surveillance centers in Canada - Investigate disease outbreaks
Basic epidemiologic concepts
• Rate:
a magnitude or frequency of event in population relative to
total population at a given time unit;
Vital stats
• Neonatal Mortality Rate= number of deaths to infants <28 days during yr x 1000
Number of live births in same year
• Infant mortality rate= number of deaths to infants <1 yr during yr x 1000
Number of live births in same year
• Maternal mortality rate= number of Pregnancy–related deaths during yr x 100,000
Number of live births in same year
• Cause specific death rate= number of deaths due to a particular cause during yr x 1000
Average mid-year population
• Crude birth rate = number of live births during yr x 1000
Average mid-year population
• Crude death rate= number of death during yr x 1000
Average mid-year population
number of deaths Pregnancy–related death= 1
• Number of live births= 1000
• Maternal mortality rate= ?
100/100,000
Neonatal Mortality Rate= number of deaths to infants <28 days during yr x 1000 Number of live births in same year Number of deaths =20 Number of live births= 400 Rate: ?
50/1000
number of deaths due to cardiovascular diseases=800
• Average mid-year population=200000
• Cardiovascular mortality rate=?
Cause specific death rate= number of deaths due to a particular cause during yr x 1000
Average mid-year population
4/1000
• Incidence:
how to calculate
The number of new cases!!!! of a disease during a
specific time period in a defined population
• Identifying the susceptible people free of the disease
• Periodical examination over time and count the new cases
• How to calculate:
– The number of new cases of a disease or condition in a
specified time period (usually a year) divided by the size
of the population under consideration who are initially
disease free.
– If the incidence rate is very small, it is presented as
number of cases per 100,000 (multiply the ratio by
100,000)
How to calculate incidence?
• Example:
– new cases of neural tubal defect in year 1990 in
Nova Scotia: 4
– Total population (number of live births in 1990):
2000
– What is the incidence ?
4/2000 x 100,000 = 200
10 out of 200 have the desease
10 new cases this year
200-10=190
10/190 x 100000= 5263
Prevalence:
the number of existing cases of a disease or
other condition in a given population.
– how commonly a disease or condition occurs in a population.
• How to calculate
– The number of individuals with the disease or condition at
a particular time point divided by the number of
individuals examined
– Usually expressed as a percentage (multiply the ratio by
100)
– In rare cases, usually expressed in 100,000 (multiply the
ratio by 100,000)
• Example:
– In a national nutrition survey in Canada in 2004,
900 of adults were severely food insecure.
– Total population of adults under the study: 12,000
– What is the prevalence of food insecurity in this
sample of Canadian adults?
(900/12000) x 100=7.5
200 ppl, 10 old cases, 10 new cases
20/200 x 100 = 10%
Basic epidemiologic concepts
risk?
risk factor
relative risk
? The probability of an event occurring
• Risk factors: Clinically important signs associated
with an increased likelihood of acquiring a disease
– Inherited
– Environment
• Physical
• Social
• Relative Risk= Risk of disease or death in exposed group
Risk of disease, death in unexposed group
• 1
• > 1.0
• <1.0 29
B
Risk of disease, death in unexposed group
• Example 1
– Two equal groups of 100 adults over 50, G1
exposed to trans fats for 6 months, G2, regular
diet
• G1, 20 new cases of CVDs
• G2, 10 new cases of CVDs
– What is the relative risk for G1 and what it means?
relative risk is 2 - twice as likely to die
• Relative Risk= Risk of disease or death in exposed group
Risk of disease, death in unexposed group
• Example 2
– Two equal groups of 200 individuals, G1 had high
intake Carbonated soft drink as their beverage
choice, G2 had fruit drink as their beverage of
choice. Followed over one year
• G1, 25% had BMI higher than 30
• G2, 25% had BMI higher than 30
– What is relative risk for G1 and what it means?
- you are likely likely to have a high bmi compared to soft drinks
Example 3
– Two equal groups of 50 cases of Rheumatoid
Arthritis with active disease, G1 exposed to
vitamin D 1000 IU/d for 6 months, G2, no
supplement
• G1, 4 had high CRP levels
• G2, 16 had high CRP levels
– What is relative risk for G2 and what it means?
0.25 - these guys have a lower risk lowers your risk by 4 times
flip it around the other was
4 times more likely to have high crp levels
Basic epidemiologic concepts
What public Health officials do: – Observing (surveillance) – Counting the cases or events – Relating cases or events to the population at risk – Making some types of comparisons what else:
nutritional epidemiology
look at relationship btw nutritional determinants and disease/ health outcomes
The study of the nutritional determinants of diseases in
human populations
• Function: Identify & study associations between diet &
disease in defined population
• Original focus in nutrition epidemiology: nutrient deficiency
diseases
• What about now? what are the major areas of focus in
nutritional epidemiology?
– Case-control studies:
observational
comparing cases (with
health outcomes) with controls (with no evidence
of health outcome)
– Cohort studies:
observational
two groups free of the health
outcome, one group exposed to the risk factor of
interest, the other not. Followed prospectively .
Analytical experimental studies
Controlled trials
• Non-random controlled trials (examples)
• Randomized Controlled Double-Blind clinical Trials
(gold standard)
• Field trials
• Community interventions
• Meta-Analyses (support the evidence)
Randomized Trial Methodology
• Random allocation - Each subject has an equal
chance of being assigned to any group in the study,
so that all groups in a study are similar in all
characteristics not controlled by other methods, such
as subject selection.
• Random allocation can be used with matching to
ensure the study groups are comparable
Case studies:
non-experimental descriptive
individual cases diseases
• Case series:
non-experimental descriptive
description of similar cases of diseases
• Ecological studies:
non-experimental descriptive
studies of risk factors & health outcomes at population level
• Cross-sectional surveys:
non-experimental descriptive
snapshots of risk factors, health outcomes, & other relevant factors in a population
Case-control studies disadvantages
Incomplete data(retrospective) Biased recall in exposure Issues with selecting controls Change in methods over time
limited results (retrospective)
Case-control studies advantages
Less expensive(smaller #, shorter period)
Suitable for rare diseases
Prospective Cohort
disadvantages
Needs large # of subjects
More expensive/longer period
Change in methods over time
Loss of subjects
prospective cohort
advantages
Multiple outcome, less bias, more
reliable, more comprehensive
results
More efficient for rare disease
Nested case-control study design?
A case-control study embedded within a longitudinal prospective cohort study
Prospective vs. retrospective studies? Bias & confounding are more common
Bias & confounding (example another stimulus that is causing the result- drinking beer AND smoking(could just be the soking)) are more common in retrospective
in the gold standard there are four possibilities
The treatments do not differ & we correctly conclude
they do not differ
• The treatments do not differ but we conclude they do
differ
• The treatments differ but we conclude they do not
differ
• The treatments do differ & we correctly conclude
that they do differ
in the gold standard
advantages
Helpful in assessing the value of food/nutrient to
improve health/control disease
• Can evaluate a single variable in a precisely defined
patient/at risk group
•
• Prospective design
• Eliminates bias by comparing two otherwise identical
groups
• Allows for meta-analysis
Disadvantages?
Expensive and time consuming
• Not always properly conducted – too few subjects, too
short a time period
• Influence of sponsorship
• Failure to randomize all eligible subjects
• Failure to blind assessors to randomized status of
subjects
Community Trials
• Communities rather than individuals comprise
the treatment groups
• Appropriate for diseases that have their origins
in social conditions that can be influenced by
intervention directed at group behavior as well
as individuals
Limitations of Community Trials?
Random allocation of communities is not practical
• Only a small number of communities can be
included
• Other methods are needed to ensure any
difference found can be attributed to the
intervention rather than to any inherent
differences between the communities studied
Field Trials
• Involve people who are disease-free but
presumed to be at risk
• Data collection – “in the field” – among noninstitutionalized
people in the general population
• Used to evaluate interventions that reduce
exposure without measuring the occurrence of
health effects.
Limitations of Field Trials?
Huge undertaking
• Major logistic considerations
• Major financial considerations
• Think of how much work is required to randomize
and allocate participants to various treatment
groups!
Interpretation of data in nutritional epidemiology
Considering the nature of nutrition data, all necessary measures
need to be taken in data collection, cleaning, and analyses
• It is concerned whether an association represents a true causeeffect
relationship when it is observed
– strength of association: not likely to be strong in nutritional
epidemiology
– consistency of a finding in various studies & populations
– null findings should sometimes be expected in nutritional
epidemiology
