Thinking about Populations at a moment in time: Prevalence and Cross-Sectional studies: Infertility COPY Flashcards
Define Epidemiology
basic science of the distribution and determinants of the frequency of disease/ health outcomes in specified populations
Relevance of describing populations and health needs
- … facilitates … and … of health problems – and evaluation of …
- … methods = techniques used to derive … knowledge
- Clinical … = application of … to individual … care
- Epidemiology facilitates prevention and management of health problems – and evaluation of interventions
- Research methods = techniques used to derive epidemiological knowledge
- Clinical epidemiology = application of epidemiology to individual patient care
Clinical epidemiology = application of epidemiology to … … care
Clinical epidemiology = application of epidemiology to individual patient care
What is prevalence?
Prevalence measures the frequency of “cases” of a disease in a given population at a designated time (the numerator). E.g. diagnosed asthma in children aged 5-11 years.
Calculation of prevalence also requires a suitable … (e.g. GP registered patients, schoolchildren) – the number of people who are ‘at …’ of the disease
Calculation of prevalence also requires a suitable denominator (e.g. GP registered patients, schoolchildren) – the number of people who are ‘at risk’ of the disease
Prevalence = number of people … / number of people …
number of people with disease / number of people who could have disease.
Prevalence is expressed as a … (e.g. …), a … of 1 (0.7 is equivalent), or a proportion per … of … (E.g. … of … )
Prevalence is expressed as a percentage (e.g. 70%), a proportion of 1 (0.7 is equivalent), or a proportion per unit of population (700 of every 1000 people)
Types of Prevalence: Point
- This is either A or B
A) Prevalence calculated for a specific purpose
B) Prevalence at a point in time
Give an example
- This is:
A) Prevalence calculated for a specific purpose
B) Prevalence at a point in time
Example: No of women experiencing infertility right now
Types of Prevalence: Period
- This is either A or B
A) Prevalence over a specific period of time
B) Prevalence of an episodic disease/condition
Give an example
- This is either A or B
A) Prevalence over a specific period of time
B) Prevalence of an episodic disease/condition
Example: Women who have experienced infertility in past 12 months
Types of Prevalence: Lifetime
- This is either A or B
A) Prevalence within period of time over which disease typically lasts
B) Prevalence of the disease/condition ever in individual’s lifetime
Give an example
- This is either A or B
A) Prevalence within period of time over which disease typically lasts
B) Prevalence of the disease/condition ever in individual’s lifetime
Example: Women who have experienced infertility ever in their lifetime
Advantages and Disadvantages of Point Prevalence
Advantages Include:
- Identify … in disease/condition frequency and/or intervention …
- If based on survey data, robust to patient … problems
Disadvantages Include:
- Less helpful for diseases/conditions which are …, … in duration or which …
Advantages Include:
- Identify changes in disease/condition frequency and/or intervention effectiveness
- If based on survey data, robust to patient recall problems
Disadvantages Include:
- Less helpful for diseases/conditions which are rare, short in duration or which fluctuate
Advantages and Disadvantages of Period Prevalence
Advantages Include:
- Helpful for diseases/ conditions which … e.g. …
- Helpful in identifying … in disease/ condition frequency and/ or intervention …
Disadvantages Include:
- If based on survey data, problems with … …
Advantages Include:
- Helpful for diseases/ conditions which fluctuate e.g. hay fever
- Helpful in identifying changes in disease/ condition frequency and/ or intervention effectiveness
Disadvantages Include:
- If based on survey data, problems with participant recall
Advantages and Disadvantages of Lifetime Prevalence
Advantages Include:
- Helpful for diseases/ conditions which are … e.g. …
Disadvantages Include:
- Less helpful for knowing how many people … affected by diseases/conditions which are …-limited
- Less helpful in identifying … in disease/condition frequency and/or intervention …
- If based on survey data, problems with … …
Advantages Include:
- Helpful for diseases/ conditions which are episodic e.g. puerperal psychosis
Disadvantages Include:
- Less helpful for knowing how many people currently affected by diseases/conditions which are time-limited
- Less helpful in identifying changes in disease/condition frequency and/or intervention effectiveness
- If based on survey data, problems with participant recall
Exposures - Risk Factors
- Attributes that … or … the … of developing a disease or injury
- May be … - decrease likelihood
- Types of risk factors that might be considered:
- D… risk factors
- B… risk factors
- …-related risk factors
- E… risk factors
- G… risk factors
- Attributes that increase or decrease the likelihood of developing a disease or injury
- May be protective - decrease likelihood
- Types of risk factors that might be considered:
- Demographic risk factors
- Behavioural risk factors
- Health-related risk factors
- Environmental risk factors
- Genetic risk factors
Calculating Prevalence
- We can just calculate basic prevalence within a population
- But we might also want to know about how prevalence is impacted by an …
- So an … here being something that is a … … for prevalence or a cause
- So we have simple prevalence here – so we would add A and C together, this reflects … with the disease
- And then we would divide that by N which is everyone i.e. the whole … at …
- And then if you wanted to, you could separate disease prevalence into numbers of people with a disease who have and have not been … to any particular … factor and compare them
- We can just calculate basic prevalence within a population
- But we might also want to know about how prevalence is impacted by an exposure
- So an exposure here being something that is a risk factor for prevalence or a cause
- So we have simple prevalence here – so we would add A and C together, this reflects everyone with the disease
- And then we would divide that by N which is everyone i.e. the whole population at risk
- And then if you wanted to, you could separate disease prevalence into numbers of people with a disease who have and have not been exposed to any particular risk factor and compare them
Calculating Prevalence
- A or B?
- A
- So I would use (A+C) / N as this is total number with the disease over total population at risk
Case definition = criteria for identifying … (case) of …/…
Case definition = criteria for identifying presence (case) of disease/outcome
Defining and operationalising: Case definition (the numerator)
- Case definition = criteria for identifying presence (case) of … / …
- The definition of ‘…’ is crucial – and can be very complex
- Must be clearly defined and specified:
- … within a study
- … to other studies
- r…
- leading to … and … results
- Case definition = criteria for identifying presence (case) of disease/outcome
- The definition of ‘caseness’ is crucial – and can be very complex
- Must be clearly defined and specified:
- consistent within a study
- comparable to other studies
- reproducible
- leading to interpretable and meaningful results
Defining and operationalising: Specified population (the denominator)
- We must then also define the denominator – this can be very complex too
- We need to identify those people truly … to the …/…
- i.e. … people who can’t get it
- And specify further … details e.g. who, where, when
- We must then also define the denominator – this can be very complex too
- We need to identify those people truly susceptible to the disease/condition
- i.e. excluding people who can’t get it
- And specify further population details e.g. who, where, when
Why might we be interested in prevalence of infertility?
- Understanding infertility and its … and …
- Accurate knowledge of …, … differences -> fertility/reproductive care providers, researchers/policy makers
- Implications for
- …- health, happiness
- … – current and future economy, labour workforce
- Informing prevention and public health interventions
- Identifying and prescribing targeted and indicated …
- What, when, how, who
- Service planning and …
- Evaluating … of interventions
- Comparing … before and after/ with and without interventions
- Understanding infertility and its causes and outcomes
- Accurate knowledge of trends, geographical differences -> fertility/reproductive care providers, researchers/policy makers
- Implications for
- Individuals- health, happiness
- Society – current and future economy, labour workforce
- Informing prevention and public health interventions
- Identifying and prescribing targeted and indicated interventions
- What, when, how, who
- Service planning and commissioning
- Evaluating effectiveness of interventions
- Comparing prevalence before and after/ with and without interventions
Defining and operationalising infertility: The numerator
- … perception = a sexually-active non-contracepting female without children / lifetime childlessness
- … perspective = a disease of the reproductive system defined by a failure to achieve clinical pregnancy after 12 months of regular sexual intercourse minus contraception
- after 6 months when female aged 35 years or more
- Consider
- Conception/ Pregnancy / Live birth
- Public perception = a sexually-active non-contracepting female without children / lifetime childlessness
-
Epidemiology = a disease of the reproductive system defined by a failure to achieve clinical pregnancy after 12 months of regular sexual intercourse minus contraception
- after 6 months when female aged 35 years or more
- Consider
- Conception/ Pregnancy / Live birth
Defining and operationalising infertility: The denominator
- Consider
- Sexual activity without … / Regular sexual activity without … / Sexual activity with unsuccessful contraception / … to achieve pregnancy / … to pregnancy
- Females or males / Non-heterosexual couples + Non-couples / People engaging in fertility treatment
- … range
- Consider
- Sexual activity without contraception / Regular sexual activity without contraception / Sexual activity with unsuccessful contraception / Trying to achieve pregnancy / Time to pregnancy
- Females or males / Non-heterosexual couples + Non-couples / People engaging in fertility treatment
- Age range
The way in which we define our numerator and denominator matters because:
- Affects … estimates (fertility estimate ranges e.g. Gurunath et al., 2011; 6.8 – 38.6%)
- … positives and negatives
- Increased/decreased numerator
- Increased/decreased denominator
- Affects … of findings
- Exclude sub-populations of interest from numerator/denominator e.g. non-heterosexual /non-couples
- Affects identification of … factors and outcomes
- Obscure identification/ascertaining impact of exposures
- Obscure identification of temporal or geographical trends
- Affects … planning and …
- Unable to meet demand/wasted resources
- Inappropriate targeting of …
- Affects …
- Under or over-investigation/over-treatment of individuals
- Affects prevalence estimates (fertility estimate ranges e.g. Gurunath et al., 2011; 6.8 – 38.6%)
- False positives and negatives
- Increased/decreased numerator
- Increased/decreased denominator
- Affects coverage of findings
- Exclude sub-populations of interest from numerator/denominator e.g. non-heterosexual /non-couples
- Affects identification of causal factors and outcomes
- Obscure identification/ascertaining impact of exposures
- Obscure identification of temporal or geographical trends
- Affects service planning and commissioning
- Unable to meet demand/wasted resources
- Inappropriate targeting of resources
- Affects treatment
- Under or over-investigation/over-treatment of individuals
How do we find the data we need to establish prevalence?
- We use a … study = identifies e../o.. within people
- An observational study
- A defined … is surveyed to simultaneously measure
- …/ condition status (e.g. infertility)
- … (e.g. sedentary lifestyle, alcohol intake)
- Sample selected using inclusion and exclusion criteria
- Could be general population or clinic-based
- Prevalence is reported for the population as a whole, and often for subgroups
- We use a cross-sectional study = exposures/outcomes within people
- An observational study
- A defined population is surveyed to simultaneously measure
- Disease/ condition status (e.g. infertility)
- Exposure (e.g. sedentary lifestyle, alcohol intake)
- Sample selected using inclusion and exclusion criteria
- Could be general population or clinic-based
- Prevalence is reported for the population as a whole, and often for subgroups
Sources of cross-sectional study data
-
Primary or secondary data
- Primary data = … data
- Secondary data = … registers, …/…. records, … data
- Primary or secondary data
- Primary data = survey data
- Secondary data = mortality registers, hospital/medical records, census data
Strengths and Weaknesses of Cross-Sectional Studies
-
Strengths:__
- Measure … and thus … burden in whole population and subpopulations
- Can compare prevalence in … and ..-… to risk factors
- Quick and …
- Can be used to inform …
- Can be used to initially … a hypothesis, prior to another type of study
-
Weaknesses:
- Not suitable for … diseases
- Not suitable for diseases of … duration
- Cannot measure rate of … cases arising and any … thereof
- Vulnerable to …, including …
-
Strengths:__
- Measure prevalence and thus disease burden in whole population and subpopulations
- Can compare prevalence in exposed and non-exposed to risk factors
- Quick and inexpensive
- Can be used to inform hypotheses
- Can be used to initially explore a hypothesis, prior to another type of study
-
Weaknesses:
- Not suitable for rare diseases
- Not suitable for diseases of short duration
- Cannot measure rate of new cases arising and any changes thereof
- Vulnerable to bias, including confounding
A … is a variable that influences both the dependent variable and independent variable causing a spurious association.
A confounder is a variable that influences both the dependent variable and independent variable causing a spurious association.
Cross-sectional studies - the problem of confounding
- A confounder is a … that influences both the dependent variable and independent variable causing a spurious ….
- Cross-sectional studies do not provide any protection against confounding because
- … and … are measured at the same time
- exposure status is … occurring and not random/manipulated
- A confounder is a variable that influences both the dependent variable and independent variable causing a spurious association.
- Cross-sectional studies do not provide any protection against confounding because
- exposures and outcomes are measured at the same time
- exposure status is naturally occurring and not random/manipulated
Strengths and Weaknesses of Secondary Data
- It is …
- If anonymous, minimal ethical/governance … needed
- -Limited by what … already gathered
- –Poor … and missing …
- It is Cheap
- If anonymous, minimal ethical/governance approval needed
- -Limited by what data already gathered
- –Poor accuracy and missing data
Strengths and Weaknesses of Primary Data
- Gather … data
- -Difficult to achieve … sample
- -More …
*
- Gather additional data
- -Difficult to achieve representative sample
- -More expensive
Majority of studies on infertility appear to be … (Direkvand-Moghadam A, et al. 2014)
Majority of studies on infertility appear to be cross-sectional (Direkvand-Moghadam A, et al. 2014)
How do we find the data we need to establish prevalence? (other option)
- An … study = exposures/outcomes within populations
- Data collected at the community/population (not …) level
- Data often existing … e.g. government figures
- Can be used to …
- Disease/outcome
- Exposures
- Exposures are those relating to the … (not individuals) e.g.
- Comparing between … area (exposure = area)
- Comparing across … (exposure = time)
- Data collected at the community/population (not …) level
- An ecological study = exposures/outcomes within populations
- Data collected at the community/population (not individual) level
- Data often existing standard e.g. government figures
- Can be used to quantify
- Disease/outcome
- Exposures
- Exposures are those relating to the population (not individuals) e.g.
- Comparing between geographic area (exposure = area)
- Comparing across time (exposure = time)
- Data collected at the community/population (not individual) level
… is a basic science focused on understanding disease/health needs of populations
Epidemiology is a basic science focused on understanding disease/health needs of populations
… is a way of quantifying health needs of populations at a moment in time
Prevalence is a way of quantifying health needs of populations at a moment in time
… = number of people with disease/condition in a given population at a given time
Prevalence = number of people with disease/condition in a given population at a given time
Prevalence calculation = … with disease / … disease
Prevalence calculation = number of people with disease / number of people who could have disease
… studies can be used to capture a ‘snap shot’ of prevalence (of exposures/outcomes) within a population (/subpopulations) at a moment in time
Cross-sectional studies can be used to capture a ‘snap shot’ of prevalence (of exposures/outcomes) within a population (/subpopulations) at a moment in time
Ecological studies are very similar (to cross-sectional studies), but collect data on … not …
Ecological studies are very similar, but collect data on populations not individuals
Cross-sectional studies cannot demonstrate cause and effect and are vulnerable to …
Cross-sectional studies cannot demonstrate cause and effect and are vulnerable to confounding
