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Y1 Tp2 Pgh > 1. global determinants of health > Flashcards

1. global determinants of health Flashcards

1
Q

public definition

A

Public = local and population measure to improve health outcomes

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2
Q

global definition

A

Global = global and international response

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3
Q

public and global health definition

A

“The art and science of preventing disease, prolonging life and promoting health through the organized efforts of society.” (Donald Acheson, 1988; WHO)

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4
Q

interdisciplinary

A

Does not just focus on medics

– Epidemiology (disease patterns, distribution across populations)

– Social sciences – psychologists

– Medicine

– Policy – laws and health policies

– Natural sciences – how transmission occurs

– + many more!

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5
Q

Population pyramids

A

—-> graph showing distribution of age groups and gender of a population

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6
Q

low middle income populations

A

LMICs (low middle income countries) have a youthful population due to

High birth rate and death rate

Low life expectancy

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7
Q

3 factors that determine health

A

• Social and economic aspects

– Income status

– Education

– Support networks

• Physical environment

– WASH – water, sanitation and hygiene practics

– Climate change

– Roads – infrastructure, road traffic accidents

• Person’s individual characteristics and behaviours

– Diet

– Smoking

– Gender (e.g. women don’t get testicular cancer)

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8
Q

WASH

A
  • Safe drinking water, sanitation and hygiene
  • 829,000 people each year die from unsafe drinking water, poor sanitation, hand hygiene (WHO, 2019) • Biological and chemical contamination of drinking water
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9
Q

WASH - infectious disease

A

Infectious disease risks

  • Diarrhoeal disease
  • NTDs – neglected tropical diseases
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10
Q

DALY

A
  • DALY = years of life lost + years lived with disability
  • 1 DALY = 1 year of healthy life lost

Years of healthy life lost

Every disease in the world has a disability weighting

(drawback) disability rating is based only on expert opinion

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11
Q

WASH and Trachoma

A

—> World’s leading cause of preventable blindness
Causative organis, = Chlamydia trachomatis

  • ‘Disease of poverty, which goes on to breed poverty’
  • Lack of clean water contributes – poor hand and face washing, transmission on fingers
  • Surgery
  • Antibiotics
  • Face-washing = transmission

Cause inflammation of eyes

Eyelids turn inwards scratch cornea = blindness

• Environmental improvement – toilets, clean water, hygiene education

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12
Q

nutrition transmission definition

A

• Changes in pattern of diet and energy expenditure which accompany changes in economic development, lifestyle and demographics

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13
Q

nutrition transmission patterns 1,2,3

A

Pattern 1: Hunter-gatherer (in the old times)

  • Pattern 2: labour intensive agriculture (interspersed with periods of famine) - pre industrial revolution
  • Pattern 3: ‘receding famine’ – agriculture modernised and industrialised –
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14
Q

nutrition transmission pattern 4

A

• Pattern 4: Degenerative disease = most of the world at the moment

– Multinational control of diet.

– Most of world is here

– Diet related (non-communicable disease prevalent)

High fat, high sugar, high salt

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15
Q

nutrition transmission pattern 5

A

When people realise that pattern 4 affects health some change to pattern 5 behaviour changes = this hasn’t happened on a global or country level yet

  • Pattern 5: Behavioural change -> hypothetical / anecdotal
  • Conscious decision to move away from Pattern 4
  • Keto diet
  • Plant based
  • Paleo
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16
Q

evidence based medicine - what is it

A

EBM –> evidence based medicine

Best scientific evidence

For and against

Combination of 3 factors above, equally weighted

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17
Q

evidence based medicine - 3 factors

A

Individual clinical expertise

Best external evidence

Patient values and expectations

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18
Q

evidence - why is it needed

A
  • From the latter half of the 20th century: lifestyle diseases.
  • Many reports in the media have caused considerable fear, confusion and reduced confidence in research.
  • This appears to have grown exponentially in the SoMe social media age!
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19
Q

types of decision making

A

Driver of pressure to make evidence based decision

Use evidence to make deicsions

Focused and refined

Best used of healthcare resources

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20
Q

alternative to EBM approach

A
  • Evidence
  • Eminence = most qualified opinion is most important
  • Vehemence
  • Eloquence or elegance
  • Providence
  • Diffidence
  • Nervousness
  • Confidence
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21
Q

how research impacts practice

A

Evidence must be used to generate change in behaviour and influence clinical decision making

e.g. use of antibiotics

• Medical professionals need to be skilled in identifying the strongest evidence to support policy in a timely manner

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22
Q

systematic reviews

A

Digesting and reviewing info from lower down, controlled trials and studies

Filtered info used to determine guidelines

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23
Q

filterted information

A

Systematic reviews

Critically appraised topics

Critically appraised individual articles

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24
Q

Unfiltered inforamtion

A

Randomised control trials

Cohort studies

Case controlled studies, case series and reports

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25
Q

evaluating evidence

A

–> Reference resource where experts pool together evidence for a particular topic

  • Peer-reviewed material
  • Conclusion statement
  • Position statement
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26
Q

overview of EBM

A

Get a good question by looking at

Popualtion – who

Intervention - what

Control group – comparison

outcome

Study design (RCT)

Do the study

How well was the study done

What do the results mean

Could they be due to chance

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27
Q

title

A

• Title – does it adequately describe the work, participants, (place), intervention/ exposure and outcome?

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28
Q

abstract

A

• Abstract – does it give a clear overview of the work, that helps answer your PICOS (other other question)?

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29
Q

introduction

A

• Introduction – remembering this is mostly the opinion of the authors. Only key point from scanning is does this go from the big picture to position the research question and justify why they did what they did?

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30
Q

methods

A

• Methods – Key part, does it make sense, can it answer their question and does it appear transparent and justify the number of participants etc.

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31
Q

results

A

• Results – The other key part, these should be logically laid out, key information in a figure, secondary data in a table. It should only be what was found and no opinions

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32
Q

discussion

A

• Discussion – As with introduction, mostly authors opinion, can be useful for first paragraph which states what the authors think the research found, and then check the conclusion is not overstated and links to the primary outcome, methods and data

33
Q

questions to ask about studies

A
  • Can I now read a paper or a review article and understand why this topic is being investigated?
  • Is this an observation or an experimental study (and is it the best approach to ask this question)?
  • How are the authors testing their hypotheses?
  • Has the trial been registered, did the primary outcomes change? Have the number of participants been justified
  • Do conclusions follow from the data presented in tables and figures?
  • Are the results generalisable?
34
Q

2 types of research

A

observational

experimental

35
Q

observational research

A
  • Establish links/associations
  • Investigator takes measures but does not intervene.
  • Retrospective or prospective
36
Q

observational research - examples

A

• E.g. cross-sectional studies/surveys, case-control studies, cohort studies

Longitudinal period of time – suggest causality

37
Q

experimental research

A
  • Establish cause & effect

* An intervention is performed by the researcher, all else held constant

38
Q

experimental research - examples

A

• E.g. intervention trials, randomised controlled trials (RCTs)reduce confounding and bias

39
Q

Independent (Explanatory) variable

A

the explanatory or predictor variable

– the variable hypothesised to explain the outcome variable.

The cause in cause and effect

40
Q

Outcome (Dependent) variable

A

the variable that is observed as the effect of manipulation of the independent variable.

The variable we expect to change

41
Q

confounding variables

A

—> can’t change, residual things in population

e.g. amount of fat people eat and amount of energy, as people eat more fat = more energy

Gender

Age

Education

Control for confounding variable

• Occurs when it is not possible to disentangle the effects of two or more variables or events

42
Q

accuracy/specificity

A

• Accuracy Closeness to the true value, also called specificity – it measures what is supposed to measure

43
Q

precision/repeatability/reliability

A

• Precision Repeatability, also called reliability – gives same result over repeated trials

44
Q

Sensitivity

A

The likelihood that a test will turn out positive when the result is positive

Example: % of people with clinical depression who score as “depressed” on a scale measuring depression

45
Q

specificity

A

The likelihood that a test will turn out negative when the result is negative

Example: % of people who do not have clinical depression who score as “not depressed” on a scale measuring depression

46
Q

Ideal = high specificity and high sensitivity

A

Can sacrifice a high sensitivity

But don’t sacrifice a high specifity as that means that you get false negatives

47
Q

selection bias

A

Distortion, due to:

a. Methods used to select subjects
b. Factors that influence study participation

Therefore – findings represent factors determining disease AND factors determining participation

48
Q

sample size

A

—> make sure there are enough people in the study

49
Q

sample sixe and power analysis

A

The statistical approach to determining the sample size is a “power calculation” or “power analysis”

Typically involves accepting no more than 5 % level of error, i.e. event occurring by chance

  • Sample size calculations are based on
  • Level of error you will accept
  • Magnitude of the effect under investigation
  • Prevalence of factor you want to measure
  • Relative sizes of the groups being compared
50
Q

p- value

A

A statistical value indicating the probability that your findings are due to a real effect, and not likely to be by chance

51
Q

confidence interval

A

A “95% C.I. (A, B)” means that if we were to repeat our experiment a very large number of times, in 95% of cases, our result would fall always between A and B.

The difference with the p-value is that the C.I. gives you a range or limits, of the lowest and highest values your result can possibly take.

52
Q

Odds Ratio (OR):

A

A measure of how strong an effect is.

• The chance (“odds”) of an event occurring in the “control” group vs. the same event occurring in the “cases group”.

53
Q

Odds Ratio (OR): values

A

OR = 1 means no difference between groups

OR > 1 the event is more likely in the cases = “induces” disease

OR < 1 the event is more likely in the control group = “protects

54
Q

Cross sectional studies

A

Think of “surveys”

  • Measure disease & exposure at the same time in a population
  • Useful for assessing prevalence, exploring relationships & generating hypotheses
  • Do not give evidence of cause & effect or change over time
  • Key issues in critical appraisal include sampling, confounding & validity/reliability of methods/data
55
Q

case control studies

A

Think of “rare diseases”

  • Select “subjects” and “patients” (i.e. on basis of outcome variable, with or without disease).
  • CCS look back to behaviour in the past
  • Case-control studies are best for rare disease, assessment of multiple exposures
  • When evaluating a case-control study consider suitability of control group and sources of bias
56
Q

cohort studies

A

Think of “large groups” being followed over time

  • Group 1 - people exposed to variable of interest
  • Group 2 - people not exposed to variable of interest
  • All subjects are healthy at the start of the trial except in “inception” cohorts (Greenhalgh, ch.3)
57
Q

retrospective cohort

A

Prospective cohort – exposure measured now and in the future

58
Q

retrospective cohort

A

Retrospective cohort - based on measurements of exposure taken in the past

59
Q

Cohort studies – relative risk

A

All measure the risk of future outcome on the exposed group vs. on the non-exposed group

60
Q

Cohort studies – relative risk values

A

risk if exposed/ risk if not exposed

– RR = 1 no effect of exposure

– RR > 1 the exposure increases risk

– RR <1 the exposure decreases risk

61
Q

odds ratio and relative risk

A

• Note that the OR is a related measure to RR, it approximates to the RR

– The OR gives an estimate based on number of existing events (“cases”) now; the RR esimates a risk based on diseaese development over time

62
Q

relative risk and absolute risk

A

RR is not absolute risk, needs changing to absolute risk, e.g. recent stories about processed meat and cancer risk (RR 17% absolute risk 1 extra case per 1000)

Effect absolute risk is different

63
Q

key aspects of experimental studies

A

randomisation,

blinding, - do researchers know who is getting what intervention

placebo

ITT (intention to treat, do people that start the study end the study – problem with intervention may cause dropout)

• Experimental studies provide the best evidence of cause and effect – results can be used to perform meta-analyses

64
Q

RCT - classic design

A

Study population

Define selction criteria for participsnts

Select and invite partticipants

Randomisation of participants into control and treatment groups

Complete or drop out

65
Q

Experimental studies limitations

A

• Limitations include ethical considerations, cost and factors leading to bias

66
Q

systematic reviews

A

• Systematic reviews are a type of Secondary Research

– Overviews primary (original) research

– Conducted following of a pre-defined, reproducible, and non-biased method (follows agreed standards)

• Systematic reviews allow a quick evaluation of the cumulative evidence behind a particular intervention

67
Q

• When appraising a SR you should consider:

A

– Was the research question relevant and specific?

– Was the literature search conducted thorough and accurate?

– Was the quality of the studies assessed (and weighed)?

– Are conclusions reasonably deduced from the numerical results?

68
Q

qualitative research

A

Why

Interviews, observations

Get opinions, views

Non numerical, qualitative, descriptive ?

Unrepresentative

Non statistical

69
Q

quantitative research

A

How many, what, how

Quantified observations; interventions; laboratory

Associations; causeeffect relationships

Testing hypotheses; numerical or quantifiable

Representative

Statistical

70
Q

Critical appraisal - what is it

A
  • A process of review necessary to be able to judge the evidence
  • Involves identifying both positive and negative aspects of research or evidence
  • Allows to identify relevant information to enhance practice
71
Q

Research process

A

Identify problem

Review literature

Develop testable hypothesis

Design intervention

Alect recruit subjects

Obtain and analyse data

Interpret results

Diseeminate results

72
Q

What influences the quality of research

A
  • Relevance of topic chosen when research will be finished
  • Practical issues (resources, funding, staff)
  • Ethical considerations
  • Study design and methodology
  • The play of chance (statistical analysis)
  • Relevance to practice
73
Q

critical analysis definition

A

“To weigh up the evidence critically to assess its validity (closeness to the truth) and usefulness (applicability)”. (Sackett and Haynes, 1995)

“A technique for increasing the effectiveness of your reading”

74
Q

Critical analysis is not

A
  • A description
  • Making assumptions
  • Making unsupported generalisation
  • Not questioning the information you have
  • Giving inaccurate or misleading information
  • Quoting what the author’s say without giving your own views and stating the difference between the author’s opinions
75
Q

why do we need to critically analyse research papers

A
  • Information overload
  • “ Science is just one of many truths”. Professor Robert Winston
  • Variable quality of research
  • Need for evidence-based practice
  • Supports the decision-making process in clinical practice
76
Q

First questions in critical analysis

A
  • What was the research question / hypothesis?
  • Why is the research needed, is it original?
  • What was the study design?
  • Was the study design appropriate for the question?
77
Q

Methodology

A

• The sample

– Sample size, power of the study

– Inclusion/exclusion criteria

– Randomised, differences between groups

– Recruitment

  • Intervention
  • Outcome measures and measurement tools
  • Duration / follow up (loss to follow up)
  • Bias
78
Q

Results

A
  • Comprehensive, precision
  • Bias in representation
  • Presentation
  • Descriptive
  • Analysis

– Quantitative statistics

– Qualitative

79
Q

what do you do in a critical analysis

A

Analyse and evaluate

– Question the information you have.

• Argue

– What is in favour of authors arguments, what is against?

  • Conclude and summarise your understanding of the main points
  • Develop your own view with justification

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