Summer Learning Institute in Interdisciplinary HIV Research MaRS Centre, Toronto, July 13-17, 2009

Population Health and Cohort Research

Robert Hogg, PhD

Simon Fraser University, Faculty of Health SciencesBC Centre for Excellence in HIV/AIDS

OverviewObjectiveReadingsPopulation HealthEpidemiologyStudy Design

Descriptive, analytical, experimental and observational

Measures of Association

ObjectiveTo review the basic concepts of population health,

epidemiology and study design

ReadingsNational Center for Chronic Disease Prevention and

Health Promotion, US Centres for Disease Control and Prevention, EXCITE, Epidemiology in the Classroom. An introduction to epidemiology.www.cdc.gov/excite/classroom/intro_epi.htm)

Definition Population health is an approach to health that aims

to improve the health of the entire population and to reduce health inequities among population groups. In order to reach these objectives, it looks at and acts upon the broad range of factors and conditions that have a strong influence on our health.

- Public Health Agency of Canada

Canada versus United StatesLife expectancy at birth (years, both sexes)

Canada versus United StatesLife expectancy at birth (years, both sexes)

Explanation?Why does Canada have a higher life

expectancy than the United States?

Variation in life expectancy by US county

Income

It took the poorest fifth of urban Canadians until the mid-1990s to reach the life expectancy experienced by the richest fifth 25 years earlier.

Key elements of a Population Health approach

Address the determinants of health: The range of individual and collective factors and conditions (and their interactions) that have been shown to correlate with health status.

Determinants of healthIncome and Social Status Social Support Networks Education Employment/Working Conditions Social Environments Physical Environments Personal Health Practices and Coping Skills Healthy Child Development Biology and Genetic Endowment Health Services Gender Culture

Population and those affectedPopulation Affected Proportion

affected

Male 814 655 .805

Female 440 118 .268

Married 350 161 .460

Single 845 595 .704

Anglo Saxon 564 340 .602

Non-Anglo Saxon

634 416 .656

Tier one 324 126 .389

Tier two 271 153 .565

Tier three 712 526 .739

Total population = 1,307, total affected = 805, and proportion affected = .620

Create a theoryClass time 5 minutesDescribe the data (best way you can)Note variations between groupsWhy did they occur?What is the event?

The TitanicWhat is the event?

Sinking of the TitanicWhy did it occur?

Ship hit an ice berg and there were not enough life boats

Variations in those affected• Men more than women

Women and children were generally put on life boats first.

• Variation by class

First class had better access to life boats

What is epidemiology? “The study of epidemics”

Concise Oxford Dictionary, 1964

“The study of the distribution and determinants of disease in humans”MacMahon and Pugh, 1970

“The science of the occurrence of illness”Miettinen, 1978

“The study of the distribution and determinants of health related states and events in specified populations and the application of this study to control the health problems”John Last, Dictionary of Epidemiology, 2001

Simply: Who gets disease? Why do they get it? And what can we do about it?

What is epidemiology? Considered a cornerstone methodology of public health research.

Highly regarding in evidence-based medicine for determining optimal treatment approaches.

Each disease condition has its own “culture” of application of epidemiological tools, but all rest on the same foundation of epidemiological principles and methods.

Examples: Infectious disease epidemiology Environmental epidemiology Chronic disease epidemiology Injury epidemiology Molecular epidemiology Genetic epidemiology

Purposes of epidemiology Determine the extent of disease in a population.

e.g., What is the prevalence of Hepatitis C among injection drug users in the Downtown Eastside of Vancouver?

Assess risks of exposure on developing disease. e.g., What is the risk of exposure to Baby Tylenol in infancy on

the likelihood of developing childhood asthma?

Identify the cause of new syndromes (e.g., HIV causes AIDS) e.g., What was the cause of the unusually high incidence of

Kaposi’s sarcoma among homosexual men in San Francisco in the early 1980s?

Study the natural history and prognosis of disease e.g., In the absence of chemotherapy, how long do people

survive after a diagnosis of lung cancer?

Purposes of epidemiology Determine whether treatment “x” is effective

e.g., Is the herbal remedy Echinacea an effective treatment against the common cold?

Identifying practical disease prevention strategies and determining whether they are effective e.g., What is the effect of municipal smoking bylaws on the

prevalence of smoking and incidence of lung cancer?

Identifying health service use needs and trends e.g., What is the prevalence and incidence of HIV/AIDS in

British Columbia and what proportion of infected individuals will require antiretroviral therapy by 2015?

Descriptive studiesResearch that describes the occurrence of disease

and/or exposureRemember: Person, place and timeAsk: Who?, what?, when?, where?Example: National Population Health Survey

PersonCharacteristics of the individuals affected by the

disease. May vary by disease.age, gender, marital status, race/ethnicity, health

status, religion, occupation, socio-economic status, sexual orientation, travel history, education, health status, genetic predisposition, etc.

PlaceWhere did the events take place? Standard place characteristics include:

Location where the disease was acquired (e.g. country, province, city, postal code)

Description of the location (e.g. type housing, crowded living conditions, proximity to animals)

Surrounding characteristics of the environment (e.g industrial areas, farms)

TimeWhen did the events occur?When did symptoms first appearDate of event (day, week, month, year), clock time of

event, day versus night, seasonal variation, annual variation, etc.

Descriptive studiesCase reports / case series Detailed descriptions usually by a doctor or group of

doctors identifying diseases that are unusual/interesting; may be related to unusual exposure

Ecological studiesCompare the prevalence of exposures and disease

occurrence in populationsNote: observations collected/displayed at the group

level may not apply at the individual level

South AfricaWood et al. The Lancet, 2000

Antiretroviral use has a substantial impact on life expectancy

Analytic studiesTo evaluate the association between an exposure or

characteristic and the development of a particular diseaseThree essential characteristics that are examined to study

causes of disease: HostAgentEnvironment

Host

EnvironmentAgent

Epidemiologic Homeostasis

Intrinsic traits that influence the risk of exposure, susceptibility once exposed, and the responses to causal factors.

Host

EnvironmentAgent

Epidemiologic Homeostasis

Biological, physical, or chemical factors that

are necessary for disease occurrence.

Host

EnvironmentAgent

Epidemiologic Homeostasis

Extrinsic Factors that determine the level of exposure, likelihood of exposure, and susceptibility to disease once exposed.

Host

EnvironmentAgent

Epidemiologic HomeostasisAgent, host, and environmental factors interact to determine the distribution of disease in human populations. These factors may to form a steady state (epidemiologic homeostasis) or may readjust to lead to the elimination of disease or epidemics, depending on whether factors favor the host or the agent

Host

EnvironmentAgent

Epidemiologic HomeostasisPaul Farmer: “First you cure the family of TB. Then you start changing the conditions that made them especially vulnerable to TB in the first place.” (p293)

TB

Haitian family

Haiti

Overview of Analytic Study DesignsStudy Design Temporal Nature Characterization of

Subjects at Enrollment

Cross-sectional study Point in Time (snapshot). Exposure and disease status collected at same time.

Case-control study Point in Time or may collect retrospective data.

Disease and non-diseased. Look retrospectively to collect info on exposure.

Cohort Follow subjects over time (prospectively or retrospectively).

Exposed and not exposed. Follow over time to determine disease status.

Clinical Trial Follow subjects over time (prospectively).

Similar disease status but randomly assigned an exposure. Followed over time to determine outcome.

Epidemiological Study Designs

Experimental studies – researcher tries to change something and measure the effect on disease outcome – clinical trials, preventive trials

Observational studies – researcher does not intervene in any way

Randomized control trial

The North American Opiate Medication Initiative (NAOMI) A clinical trial that examined whether

medically prescribed heroin could successfully attract and retain street-heroin users who have not benefited from previous repeated attempts at methadone maintenance and abstinence programs

The trial showed remarkable retention rates and significant improvements in illicit heroin use, illegal activity and health for participants receiving heroin, as well as those assigned to optimized methadone maintenance.

Create a trialWhat is the outcome?What is the exposure?Who is at risk?What is the intervention/ treatment?What are the advantages and disadvantages?

Observational studiesMeasurement of disease occurrence or health

outcomeComparing patterns of exposure and disease

outcomesIdentifying risk factors associated with

health/disease

Observational studiesMeasurement of disease occurrence or health

outcomeComparing patterns of exposure and disease

outcomesIdentifying risk factors associated with

health/disease

Can be either descriptive or analytical

Cohort Studies• Cohort: any designated group or persons who are

followed or traced over a period of time, as in a prospective cohort study

• Cohort studies: compare rates of occurrence of disease or death in people with or without a particular exposure

CIHR Team in HIV treatment outcomes: The Canadian Observational Cohort (CANOC) Collaboration This emerging team collaboration is an essential first step to

evaluating the impact of antiretroviral care on the health and well being of persons infected with HIV/AIDS across various regions of Canada.

Participating cohorts

•BC Centre for Excellence in HIV/AIDS

•Clinique Medicale L’Actuel

•Canadian Co-infection Cohort Study

•EARTH

•Maple Leaf Medical Clinic

•Montreal Chest Institute IDS

•Ontario HIV Treatment Network

•Toronto General Hospital

•University of Ottawa

Inclusion criteriaCurrent criteria for inclusion:

First HAART therapy date ≥ Jan 1st, 2000Must have a baseline CD4 and baseline viral

load Baselines must be from within the six months

prior to therapy

Current ProjectClinical and socio-demographic characteristics associated with time to virological suppression among individuals on HAART in Canada.

Lead Investigator: Dr. Curtis Cooper

Background: What constitutes an adequate immunological response has been described variously as increases in CD4 cell counts of > 25 cells, 50 cells, or 100 cells from baseline or absolute CD4 cell count > 200 cells at 6 months after initiating therapy. Patients who achieve virologic suppression but do not achieve adequate immunologic responses have been shown to be at increased risk for disease progression. However, some of these patients may eventually reach immunological targets later in the course of their treatment.

Objective(s): To determine the length of time to virological suppression among individuals in the CANOC collaboration.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 12 24 36 48 60 72 84 96

Follow Up Time (Months)

PI single

NNRTI

PI boosted

Probability of not Achieving Viral Suppression

Initial Drug Regimen

Log-rank test: p-value < 0.0001

PI single

NNRTI

PI boosted

Month 0 12 24 36 48 60 72 84 96

PI single n=281 103 65 43 26 18 9 5 0

NNRTIn=110

3 260 159 102 72 34 15 0 0

PI boosted

n=1013 237 84 39 19 5 0 0 0

Viral load suppressionby initial HAART regimen

Measures of AssociationMeasures of association cannot tell you

whether an exposure causes a disease.Just how strongly the two are associated.

Measures of Association: 2x2 tableDisease Status

Diseased Not diseased

Total

Exposure Status

Exposed a b a+b

Not exposed

c d c+d

Total a+c b+d a+b+c+d

Measures of Association: 2x2 table

Cohort Study or Clinical Trial:Relative Risk (RR) = Proportion of people with

disease among the exposed / Proportion of people with the disease among the unexposed

RR = [a/(a+b)]/[c/(c+d)]

Explanations for Association

Real Cause and EffectChanceBiasConfoundingReverse Causation

Bradford-Hill criteria of causation (1965) Temporality: The effect has to occur after the cause.

Strength of Association: The stronger the association, the more likely it is that the relationship between an exposure and a disease is causal. However, a small association does not mean that there is not a causal effect.

Consistency: Consistent findings observed by different studies in different places with different populations strengthens the likelihood of a causal relationship.

Dose-Response Relationship: Greater exposure should generally lead to greater incidence of disease. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.

Biological Plausibility: A plausible biological mechanism between exposure and disease is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge).

Specificity: Causation is likely if an exposure influences a very specific outcome or population, with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.

Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that "... lack of such [laboratory] evidence cannot nullify the epidemiological associations" .

Experiment: Causation is more likely if evidence is based on randomised experiments

Analogy: Causation may be more likely if it has already been shown in an analogous exposure and outcome.

Create a studyWhat is the outcome?What is the exposure?Is it descriptive or analyticalIs it observational or experimentalWhat are the advantages and disadvantages?

5 minutes to design

CANOC Trainee awards• Application deadline: August 31st, 2009• One year funding up to $20,000• According to CIHR scales• Only those with scores above 3.5 will be considered• Visit:

http://www.ohtn.on.ca/Pages/Funding/Salary-Awards.aspx