wellbeing, society and data

what types of questions can be asked within epidemiology?

descriptive: how many people in the population have a NCD, interested in describing the health of the population, tracking the health of the population for comparison over a time period

analytical/aetiological: what causes and thus can prevent NCDs, looking at association between risk factor and diseases, trying to understand the casuality between the relationship and then improve the health outcomes

predictive: given a set of predictors, can we predict who will get a disease.

what is health?

Health is multidimensional (physical, mental, social) with the positive end of health covered (not just diseased/non-diseased)

• WHO’s definition: a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity

• defined as your ability to adapt and self-manage in the face of social, physical and emotional challenges

• precise universal meaning challenging and strict definition for all conditions not possible

what are the differences between binary and continous measures of health?

a condition is considered as a continuum with arbitrary cut-offs implemented to ensure it is binary

• psycopathy makes it diffcult to place a practical threshold as original axis exists on a continuum.

• binary = yes/no

• continuous = symptoms might exist on a continuum

benefits & disadvantages of self-reported measures of health

cheap and easy to obtain

• able to obtain info on multiple different aspects of health

• difficult to interpret when understanding aetiology

• potential for bias (either random/differential)

what are some examples of measures that are normally used as outcomes in health research?

mental health disorders/symptoms

• self-rated health (e.g very good - very bad scale)

• health records

• vital status

benefits and disadvantages of objective measures of health?

e.g blood pressure, BMI

• can be more accurate than self-reported equivalents

• Hawthorn effect: when people change their behaviour to create more positive results when being measured for some sort of objective measure

what are some examples of derived/calculated measures?

life expectancy (year of birth, sex, age-specific death rates)

• healthy life expectancy (data on health conditions/disability)

what’s the difference between accuracy and precision?

accuracy: how close to the true value the measurement is

precision: how reproducible/consistent the measurement is

features of using health records as a form of measurement

May only be possible to match a proportion of the population

• May only capture those visible to the health service

• Typically, only measure binary disease states

how has the model surrounding disability change over the years?

1800s - medical model (management aimed at curing), directly thought that it is caused by disease

1970s - social model (depends on social environment of person), frames it as a socially created problem, complex collection of conditions

Now - acknowledged combination/interaction, evolving definition

definitions of disability

UK Equality Act 2010: disabled if you have a physical or mental impairment that has a ‘substantial’ and ‘long-term’ negative effect on your ability to do normal daily activities

• WHO: difficulties in any 3 areas of functioning (impairments, activity limitations, participation restrictions) due to physical or mental health conditions.

definition of sensitivity (binary trait)

how good a test is at finding something if it is there - probability that the diseased person is correctly identified as diseased
- e.g the % of the results that will be positive when HIV is present

definition of specificity (binary trait)

accuracy against false positives - probability that non-diseased correctly identified as non-diseased

• e.g the % of the results that will be negative when HIV is not present

what is medicalisation?

the process by which problems traditionally considered nonmedical come to be defined/treated as medical issues

• expansion of medical professional’s influence and authority into the domains of everyday existence

• identifying a personal or social condition (e.g certain medical issue) subject it to medical intervention

what are the underlying factors driving the increase in medicalisation?

appropriate: greater awareness of mental health problems, improved detection by health practitioners

inappropriate: influence of pharma industry to increase profit, medicalisation if previously dealt with by non-medical means

what is screening?

identification of unrecognised disease of defect by rapid tests

what are the key considerations when deciding whether it should be implemented?

sensitivity and specificity example

• potential benefits include: earlier detection of disease, reduced ill health and consequent burden

• potential risks: false positives

definition of surveillance

systematic and continuous collection, analysis and interpretation of data, closely integrated with the timely and coherent dissemination of results to those who take action.

what is surveillance used for?

use learning to improve public health actions

• assess distribution, identify determinants and application of knowledge

• estimating magnitude of a problem, determining geographic distribution, detecting epidemics, stimulating research and evaluating control measures

what are some things to consider when looking at surveillance data?

population size has large impacts on raw data and their presentation

• some people are not at risk for developing a new onset due to pre-existing infection

• denominator important to consider (size of total population at risk needs to be known)

prevalence definition

existing state and number of cases

• often expressed as % (n.o of diseased/total n.o)

incidence definition

number of new cases in a specific period of time, usually expressed per 100,1,000 or 100,000 persons

cumulative incidence calculation

n.o of new cases/total at risk during period of time

how to calculate incidence rate

n.o of new cases/ total at risk person-time

• person-time: when diseased or lost to follow-up, no longer at risk so not counted

• total at risk person time (population size x duration of study)

what is standardisation?

a technique to remove effect of confounding variables when making comparisons

• uses a reference population to standardize the sample to

difference between probability and non-probability sampling

randomly selected particpants vs convenience selection of people

• can have equal or strata weighting

what is generalisability?

“external validity” - can the findings of this study then be generalised to the wider population?

what are some factors that need to be considered within generalising findings to the general population?

Representativeness of general population - WEIRD populations

• detailed knowledge of causal processes & factors which could modify risk

• characteristics of source and population (e.g socioeconomic determinants)

what are the differences between observational and experimental study designs?

observational (cross-sectional surveys, cohort, case-control studies) and experimental (RCT, quasi-experiments)

• Changes are made within experimental studies to determine the effect on the participants, whereas in observational studies, there is no change done towards the population. 

• Quasi-experimental - looking for natural opportunities where the researcher can implement changes

what’s the definition of a cross-sectional study?

Study of health and potential determinant as measured at one point in time, exposure and health measured at same time 

benefits and disadvantages of using cross-sectional studies?

• Cheap and easy to carry out, if only one cross-section is being taken - good to see if you want to demonstrate basic associations

• can’t rule out reverse causation, nor can you demonstrate temporality between two factors = causal inference challenging

• Usually provides prevalence but not incidence - can’t distinguish risk factors for occurrence of disease (incidence) from risk factors for survival with the disease

how would you carry out a cohort study?

Take everyone at a baseline timepoint, and then again at another time for everyone to measure the health outcome 

how would you define a cohort?

•  group of individuals with shared characteristic - birth cohort/occupational cohort that are followed up over time creating a longitudinal approach and can be prospective/retrospective. 

how would you conduct a case-control study?

Retrospective study that identifies individuals with a specific outcome (cases) and similar individuals without it (controls) to compare their prior exposure to risk factors

• Study moves backward in time, from effect (disease) to cause (exposure).

• Researchers compare the frequency of exposure in the cases to the frequency of exposure in the controls.

benefits and limitations of case-control study

• comparatively quick & easy to conduct, useful in particular when disease is rare

• choosing comparison (control) group is difficult - hard to match (so findings could be confounded, even after matching or adjustment), concerns about accuracy of recalling past events (exposures)

what would you measure at the first and second time for a cohort study?

First time: exposure measured, and confounders, when isolating the variable we can then see the control and impact the actual variable has on the health outcome if all other variables are controlled for. 

• Second time: health outcome measured 

what’s a kappa statistic?

evaluating the agreement between the 2 rates, ranging from -1 to 1, a score of 1 indicates perfect agreement whilst 0 indicates agreement no better than chance and negative values indicate disagreement.

benefits and disadvantages of ecological study designs?

Unit of observation in a group of people, not individuals (e.g country/city)

• Data is often readily/cheaply available

• Causal inference difficult given confounding (ecological fallacy) and it is based off drawing individual inferences from grouped data. 

benefits and disadvantages of experimental study designs?

Compare treatment with placebo or other treatment which can be randomised (unblinded, single or double-blind) 

• Potentially robust in terms of causal influence since confounding can be minimised (randomisation) 

• Concerns about: ethics, practicality, wider generalisability (who takes part voluntarily in trials?), usually limited to short-term follow-up

benefits and disadvantages of study reviews?

Narrative - broad but possibly biased with the main concern being that the author might be biased in picking (cherry pick) studies for inclusion, thus conclusion 

• Systematic: usually narrower, less bias and with optional meta-analysis

•  Combines results, where they can be combined/compared leading to precise estimates (tight confidence interval) but this could still be non-causal = misleading

• Useful to test heterogeneity

definition of risk

probability that something will occur, and probabilities can range from 0 to 1, or converted to %

• The closer to 1 = greater risk 

how would you compare risks?

• Subtract to get risk difference  (risk in exposed - risk in unexposed)

• Divide to get risk ratio (risk in exposed/ risk in unexposed)

how do you interpret the results in risks?

Ratios > 1.0 indicate rate is higher among exposed then unexposed,

• =1.0 indicate no association,

• <1.0 = rate is lower among exposed than unexposed 

how to calculate odds ratio

example: Calculate odds of exposure among those with ADHD (300/500) divided by 1 - (300/500) = 1.5

1. Calculate odds of exposure among those without ADHD (503/1000) - exposed/total n.o of individuals - (503/1000) = 1.012

2. Odds ratio in the case control study: 1.5/1.012 = 1.48

what is the difference in utilising difference and ratio measures within studies?

Difference measures quantify the potential direct public health benefit of an intervention. 

• Ratio measures provide an intuitive summary of the magnitude of differences in 2 exposures

what is a confidence interval?

ndicates where we are 95% certain that the true population measure (e.g risk ratio, or other measure of effect, or prevalence estimate) is likely to be - not completely certain since data used from sample which is not the population

how are difference/ratio measures used in relation to confidence intervals?

• Difference measure: does the confidence interval contain 0?

• Ratio measure: does the confidence interval contain 1?

what is the population attributable risk proportion?

measure of the proportion of the total disease burden associated with exposure

• PARP = (a/a+b) - (c/c+d)   divided by a/a+b

what is the attributable proporiton?

risk for exposed group - risk for unexposed group/ risk for exposed group x 100 

how can you interpret linear regression?

outcome - continuous (e.g BMI), exposure - continuous or categorical

difference between continuous and categorical exposure?

• Continuous exposure: mean difference in outcome per 1 unit increase in exposure

• Categorical exposure: mean difference in outcome in group 1 compared with group 0 (e.g men vs women)

what is the difference between deterministic and probabilistic?

• Deterministic:   occurrences are causally determined by preceding events or natural laws

• Probabilistic: of, relating to, or based on probability - considering multiple component causes, but often have not identified all of the possible causal components

how can we understand disease causation?

Causes can be shared and for each individual struggling with a condition, no single exposure is sufficient by itself. 

• People can accumulate “causes” across life (at one point and/or slow cumulation) 

  • E.g tobacco smoke in utero, chronic poverty, cigarette smoking starts in adolescence

  • Disease manifestation takes time, and understanding etiology across life can inform when to intervene (more cost-effective to intervene earlier in life) 

what is the difference between sufficient and necessary component causes?

• Sufficient:  set of different factors which result in disease: multiple sets

• Necessary:  if all cases of disease require the cause (e.g alcoholism - alcohol consumption necessary) 

what is reverse causality?

• Reverse causality: X-> Y but in reverse causality Y-> X, a pertinent issue in cross-sectional studies, less likely in longitudinal studies

what is the difference between a confounder and mediation factor when thinking about causal inference?

• To understand if 1 exposure causes disease or ill health, need to try to rule out other potential causes (confounding)

• Interested in mechanism or pathway (mediation) - helps scientific understanding, can lead to identification of new targets for intervention

what is a confounder?

bias of estimated effect due to common cause of exposure and outcome

• Common to present unadjusted and confounder-adjusted results

how can confounding be used within bias studies?

Confounding bias can lead to incorrect conclusions and costly consequences

• Comparisons can help us understand importance of confounding bias

• Comparing unadjusted and confounder-adjusted estimates of association

• Comparing results from different study designs (e.g observational vs experimental studies)

• Comparing results from contexts with different confounding structures

what is a mediator?

 variable on part of causal pathway from exposure to outcome

• Common in epidemiology to see unadjusted and mediator-adjusted results 

how can results be explained by a mediator?

• Results similar - suggests not explained by mediator

• Results differ - suggested explained by mediator

• Can’t distinguish mediation and confounding statistically - need knowledge of topic 

how can results be explained by a confounder?

• Results similar: suggests little bias due to confounding

• Results differ: suggests confounding bias (often confounders measured poorly, bias due to confounding can remain when adjusted (residual) or remain as the confounders are unobserved

• Hard to measure all the confounders - can be confounded by unobserved confounders

definition of AI

computational systems that can perform cognitive tasks

definition of agents

LLMs which execute tasks

• need to undergo prompt engineering

what is agi?

artificial general intelligence

• AI that can do all/most human cognitive work as well as/better than humans

what is gpt?

General Purpose Technology  - can be used for anything and does not need to take away human autonomy when utilising these tools for research

• Could be used very much for admin tasks

• Emerging evidence shows that AI can be quite good in demonstrating and summarising abstracts of papers which could help utilise efficiency within systematic reviews

what are the pitfalls of utilising ai?

hallucinations - could be improved through training/optimisation, can modify temperature setting (lower value = more deterministic)

• sycophancy (tend to agree with you and runs with errors in prompts)

• inconsistency

• bias

• reproductibility issues/reliance on closed source tech

what are the ethical concerns surrounding the use of ai?

ethical concerns surrounding training data - are they exploiting human activity?

• Did we/others consent? Will revenue be shared with authors/artists?

• AI slop: increase in low quality scientific publications - overwhelming an already stretched publication system

how is ai currently being used within academia ?

• Increases accesses to millions of papers and reduces hallucinations 

• Bandwidth freed for higher level tasks for humans

• Can help to create more ambitious reviews (e.g across disciplines/designs), continual, more informed papers 

• AI can be done through unlocking historic (new) data, and with collected data - manual variable work (AI assisted) and then can use one research question to address all studies.

definition of epidemiology

•  scientific study of distribution, pattern and causes of health and disease

definition of social epidemiology

• branch of epidemiology interested in how social structures and institutions impact health and disease risk in a population

definition of socioeconomic position

umbrella term, that captures lots of different measures of social standing, and how advantaged or disadvantaged individuals are based on their social or economic circumstances

• E.g income, education, wealth, housing tenure, occupational class 

what are some arguments around SEP?

Class traditionally been defined by occupation, wealth and education. But research argues that this is too simplistic, suggesting that class has 3 dimensions (economic, social and cultural). 

• SEP is multidimensional, which manifest across life and measures of SEP typically overlap despite potential for independent effects on health 

what are some considerations when looking at functional measures of health?

• Multi-cohort studies are often popular, looking at various different measures to culminate in an evidence-based research surrounding health inequalities. 

• Environmental decisions might limit individual’s personal autonomy to make their own personal health decisions, but evidence is ample when considering health inequalities within “health behaviours”

what is the physical activity paradox?

• occupational physical activity is often repetitive, prolonged and without recovery with additional workplace hazards attached to manual occupations 

• Higher stress in jobs characterised by high demand and low control - greater purchasing power supports healthier behaviours. 

• Gradients within healthcare differs in direction/size across time and place, across the entire distribution of SES 

what are the 3 causal processes that create associations between SEP and health?

1. A causal relationship that SEP directly relates to health from some mediators

2. Confounded relationship by e.g intelligence, social factors, personal characteristics, genetics 

3. Reverse causality where health affects the individual’s SEP (e.g poor health affects capacity to work, and earn more = if true, the focus of intervention changes) 

what are some explanations that can be used to explain mediation of SEP?

• material - e.g work conditions, cost of buying goods

• Behavioural & cultural: exercise, smoking, alcohol habits

• Psychosocial: e.g stress (work/home), social isolation

what is the fundamental cause theory?

Socioeconomic position is a “fundamental cause” of health inequalities

• Advantaged SEP is related to key resources such as money, knowledge, power, social connections and these resources can be used to avoid health risks or minimise the consequences of disease

• SEP influences multiple diseases through multiple pathways, as health inequalities persist over time, even when specific diseases/risk factors change because advantaged groups are better able to benefit from new knowledge and treatments

• When evidence appears of something being health-damaging, those of highest SES quickest to avoid it. 

what is the ecosocial theory?

Explains how social inequalities become biologically embodied

• Health produced through interactions between social, political, economic and ecological systems rather than solely by individual behaviour or biology

• Power, discrimination, and social structures (e.g racism, sexism, class inequality) influence who is exposed to risks and who has access to protective resources

• Health patterns reflect cumulative exposures over time (intergenerational effects and life course processes). 

what are some examples of disruptive behaviour disorders (ODD)?

oppositional defiant disorder (ODD) -> developmentally inappropriate level of irritable, argumentative, and defiant behaviours requiring 4 out of 8 symptoms present for at least 6 months

what are some examples of disruptive behaviour disorders (CD?)

Conduct disorder (CD): behaviour that violates the rights of others or major age-appropriate societal norms 

what are some characteristics of anxiety disorders?

dysregulation of anxiety response system which is manifested by intense fear reaction (e.g social anxiety)

what are some characteristics of depressive disorders?

persistent depressed or irritable mood, or loss of interest in pleasure in daily activities, with symptoms must impair functioning such as impact on social relationships 

what are the demographic features of child mental health disorders?

can vary by age, with 12.8% of 9000 children in England meeting the criteria for a mental health disorder. 

• It can also vary by gender when considering emotional disorders, most prevalent in females 17 to 19

• When behavioural disorders, more prevalent in boys 11 to 16

• 20.2% of adults meet criteria for a common mental health disorder in a past week

what are some risk factors for child mental health disorders?

Household income impacts emotional disorder in 5 to 19 years old most in 4th lowest income range

• Most prevalent in White British children

• 2.51 or more family dysfunction scores manifests greater risk of mental disorder 

• Parents with severe psychological distress impact likelihood of children adopting mental disorders. 

• Other risk factors include: parent employment, parenting practices, neighbourhood deprivation

what does the family stress model show in prevalence of mental disorders within children?

shows that structural factors (e.g family income, social class) -> psychosocial factors (e.g parenting practices, family functioning) which act as mediators of structural factors then culminates in the prevalence of mental disorders within children.

what are the arguements made for the genetic influences within mental health?

Galton:  argues that social success is strongly influenced by heritability, establishment of eugenics

• Hernstein & Murray: IQ plays major role in shaping social outcomes & IQ is determined partly by genetics. 

• Heritability less well studied than environmental risks when explaining human behaviour

• Standard Social Science Model: critique of bias in social science towards social explanations 

• Neglect of evolutionary and biological influences on human behaviour

• Need for an integrative approach drawing of both social and biological explanations.

definition of behavioural genetics

study of the role of heritability (genes) in behaviour

definition of genetic epidemiology

study of the role of genetic factors in determining health and disease

how does a twin study design work

takes advantage of known shared genetics between identical twins (100%, monozygotic) vs non-identical twins (50%, dizygotic)

• Assumption that both sets of twins share 100% of their family environment

• Comparing the resemblance of identical and non-identical twins on a phenotype (e.g observable characteristics which can be a trait, behaviour or disease)

• Other genetically informative designs include adoption and IVF studies where children are genetically unrelated to parents. 

what are the assumptions that fall within a twin study?

The bigger the difference is between the correlation between MZ compared to DZ twins, the higher the heritability of the trait or phenotype. 

• Heritability of behavioural phenotype tends to increase with age 

• Over time, genetic influence become bigger and bigger as individuals progress through life. 

what are the limitations of twin and adoption studies?

• Assumption of twin studies that identical and non-identical twins share the same environments

• Although adoptive parents genetically unrelated, selective process in matching children and adoptive parents (e.g temperamental similarities) 

• Twin studies and other traditional heritability design only estimate the overall genetic influence on a given trait, not which specific genes are involved. 

what are candidate gene studies?

heritability studied at the molecular level, identifying specific genes influencing behaviour and disease

• Genes selected for study based on theory on neurological and biological mechanisms 

• E.g genes involved in dopamine reception (reward-motivated behaviour) 

what are genome-wide association studies?

not driven by theoretical assumptions, millions of gene types examined for their association with a given trait (e.g depression) 

• Identification of multiple genes (polygenic) associated with a specific trait/disorder, with polygenic risk scores developed from GWAS studies which can be used in further research. 

• Fairly common variations in specific sites of the genome can only be observed.

what is the differential susceptibility thesis?

more children are more genetically more sensitive to their environment than others

• Can be good or bad, children with vulnerable genes suffer in bad rearing environments but flourish in good environments and children with less sensitive genes less affected by bad environment but also less influenced by nurturing environment

• Often appears as a binary approach, but more likely that children fall on a continuum

• Could have been through genetic and natural resilience within the child to deal with the environment they’ve been put in 

how does the mechanisms of passive rGE work?

 parents pass on their genes to their children and genes also influence parental behaviours and child rearing practices (genetic nurture)

• Other examples include home learning environment (books, stimulation etc) and child educational achievement 

• May be confounded (or partially mediated) by parent genes related to intelligence and cognitive functioning 

how does the mechanisms of active rGE work?

individuals self select their environments according to their characteristics and personality traits, which are genetically influenced (e.g antisocial child may be attracted to antisocial peers) 

how does the mechanisms of reactive rGE work?

child’s genetically driven characteristics and behaviours influence how environment responds to child (parenting practices, peer relationships)

what is genetic epidemiology used for?

 establish whether a disorder is genetically influenced, size of genetics influence, identify genes associated with the disorder. 

• Although a trait is highly genetically influenced, environmental influences can still be very powerful (e.g height found to be 95% explained by heritability) 

• But environmental factors (nutrition, healthcare) can now explain the increase in average height in the last century

what is epigenetics?

 involve the study of change in gene expression rather than the alteration of the genetic code itself

• Changes to gene expression can be due to environmental influences (E.g our lifestyle) with the expression of genes being able to influence our health and behaviour

what is the definition of cognitive epidemiology?

The study of contributions and measurements of the associations between intelligence test scores or cognitive ability can influence health outcomes.