GIS and Health Geography

GIS and Health Geography
April 17 GIS and Health Geography What is epidemiology? I need to extensively revise these notes. Make them more about GIS analyses, less about the specific methods / terms. Too boring / dry. Brian Klinkenberg

TOC GIS and health geography Epidemiology Major applications for GIS
What is health (and how location matters) What is a disease (and how to identify one) Quantifying disease occurrence Incidence vs prevalence Identifying the population Working with small area data

GIS and health Geography
A GIS can be a useful tool for health researchers and planners because, as expressed by Scholten and Lepper (1991): Health and ill-health are affected by a variety of life-style and environmental factors, including where people live. Characteristics of these locations (including socio-demographic and environmental exposure) offer a valuable source for epidemiological research studies on health and the environment. Health and ill-health always have a spatial dimension, therefore. More than a century ago, epidemiologists and other medical scientists began to explore the potential of maps for understanding the spatial dynamics of disease.

Major applications for GIS
Geog 479 April 17 Spatial epidemiology Environmental hazards Modeling Health Services Identifying health inequalities Spatial epidemiology - understanding health problems Modeling Health Service provision and delivery Investigating environmental hazards / risk factors Identifying health inequalities Data integration Major applications for GIS Brian Klinkenberg

Spatial epidemiology Spatial epidemiology is concerned with describing and understanding spatial variation in disease risk. Individual level data Counts for small areas Recent developments owe much to: Geo-referenced health and population data Computing advances Development of GIS Statistical methodology

Framework for analysis
Geog 479 April 17 Framework for analysis Population is unevenly distributed geographically. People move around (day-to-day movements; longer term movements including migration). People possess relevant individual characteristics (age, sex, genetic make-up, lifestyle, etc). People live in communities (small areas). Brian Klinkenberg

Why small area analyses?
Geog 479 April 17 Why small area analyses? Provides a qualitative answer about the existence of an association (e.g. between environmental variable and health outcome). May provide evidence that can be followed up in other ways. Versus a population health approach (see notes) Brian Klinkenberg

Geographical correlation studies
April 17 These studies typically involve examining geographical variations in exposure to environmental variables (air, water, soil, etc.) and their association with health outcomes while controlling for other relevant factors using regression. Brian Klinkenberg

Issues: Spatial misalignment
Geog 479 April 17 Issues: Spatial misalignment A fundamental issue when performing geographical correlation studies. Brian Klinkenberg

Issues: Uncertainty Frequency and quality of population data (e.g. Census every 5/10 years). Spatial compatibility of different data sets. Availability of data on population movements. Measuring population exposure to the environmental variable. Environmental impacts are often likely to be quite small (relative to, for example, lifestyle effects) and there may be serious confounding effects. Cannot estimate strength of an association. Ecological (or aggregation) bias.

Issues: Best practices
Allow for heterogeneity of exposure. Use well defined population groups. Use survey data to help obtain good exposure data. Allow for latency times. Allow for population movement effects. Issues: Best practices (Richardson 1992)

Geog 479 April 17 Spatial epidemiology Dr. John Snow’s Map of Cholera Deaths in the SOHO District of London, 1854 List some example questions. Identify spatial clustering of the incidence of particular diseases Relate such clustering to clustering of other factors Infer causal relationships Spatial clustering of disease can indicate a localised health issue. By investigating other factors it is sometimes possible to indicate or eliminate possible causes. Examples include: Asthma rates in relation to concentrated sources of dust or exhaust pollution Cancer rates in response to an environmental contaminant such as agricultural spraying or incinerator fallout Investigating clusters of rare disease incidence, E.g. Childhood leukemia Brian Klinkenberg

Geog 479 April 17 Spatial epidemiology Environmental hazards Modeling Health Services Identifying health inequalities Spatial epidemiology - understanding health problems Modeling Health Service provision and delivery Investigating environmental hazards / risk factors Identifying health inequalities Data integration Major applications for GIS Brian Klinkenberg

Environmental hazards
Geog 479 April 17 Environmental hazards Hazard Surveillance Hazardous agent present in the environment Route of exposure exists Exposure Surveillance Host exposed to agent Agent reaches target tissue Agent produces adverse effect Outcome Surveillance Effect clinically apparent GIS and surveillance studies Brian Klinkenberg

Environmental hazards
Geog 479 April 17 GIS: Identify causal and mitigating factors Environmental hazards and spatial epidemiology Environmental hazards Brian Klinkenberg

Geog 479 April 17 Spatial epidemiology Environmental hazards Modeling Health Services Identifying health inequalities Spatial epidemiology - understanding health problems Modeling Health Service provision and delivery Investigating environmental hazards / risk factors Identifying health inequalities Data integration The bottom map shows the US Organ Transplant regions (United Network Organ Sharing) – because of differential transportation times, people on the east coast are more likely to get an organ transplantation than those on the west coast. (Jet stream can make up to an hour difference in flying times.) Major applications for GIS Brian Klinkenberg

ARIA (Accessibility/Remoteness Index of Australia)
Geog 479 April 17 ARIA (Accessibility/Remoteness Index of Australia) A generic index of accessibility/ remoteness for all populated places in non-metropolitan Australia. A model which allows accessibility to any type of service to be calculated from all populated places in Australia. Modelling health services and health inequalities Brian Klinkenberg

Mortality rate of infants (1980-2001)
Geog 479 April 17 “Where do infants and children die in WA? ” Jane Freemantle, PhD. November 2004 This chart shows the cumulative mortality rate of infant deaths over the twenty year period from 1980 to 2001. The mortality rate per 1000 live births gives the risk of infant death across three geographic areas, and between Aboriginal and NonAboriginal populations. Note that the remote location for both Aboriginal and non-Aboriginal infants carries higher mortality rates than Metro areas. The risk of death for Aboriginal infants is 4 x higher than for non-Aboriginal people in remote locations… ..And three times higher in metro and rural locations. Higher rates of child and infant death in remote and rural locations for all populations. Significantly increased risk for all Aboriginal children, youth and young adults across all locations relative to their Non-Aboriginal peers. Particularly increased risk for Aboriginal children, youth and young adults living in remote locations Mortality rate of infants ( ) Brian Klinkenberg

SES and Heart disease Identifying health inequalities:
Geog 479 April 17 SES and Heart disease Identifying health inequalities: Well-known relationship 25% – 50% of observed gradient due to risk factors like smoking, hypertension and diabetes in lower socio-economic groups (Marmot et al.,1997) Access to healthcare (Bosma et al., 2005) Imbalance between workplace demands and economic reward (Lynch et al.,1997) Poor education, lower levels of health literacy, low birth weight (Marmot, 2000) Relationship may vary with gender, with the association thought to be stronger in males (Thurston, 2005) Social-economic status SES Brian Klinkenberg

Geog 479 April 17 The Data Number of daily hospital discharges (Y) with Ischemic Heart Disease (IHD) where admission had been via emergency room for 591 postcodes in NSW Every day from July 1, 1996 to June 30, 2001 Males and females 5-year age increments Denominator (N) obtained from census Social disadvantage measured at postal area level using the census-derived SEIFA (Socio-Economic Indexes for Areas) index Ischaemic or ischemic heart disease (IHD), or myocardial ischaemia, is a disease characterized by ischaemia (reduced blood supply) to the heart muscle, usually due to coronary artery disease (atherosclerosis of the coronary arteries). Its risk increases with age, smoking, hypercholesterolaemia (high cholesterol levels), diabetes, and hypertension (high blood pressure), and is more common in men and those who have close relatives with ischaemic heart disease. Brian Klinkenberg

SEIFA distribution in NSW
Geog 479 April 17 SEIFA distribution in NSW High values indicate social advantage Socio-Economic Indexes for Areas The higher the SED the less disadvantage compared with other areas SED based on enumerated pops SED generally higher in SE of state, with pockets of high levels in several areas (associated with major settlements) Metro Sydney: high SED on North and South shores and along the harbor Band of lower SED areas tracking major traffic arteries out to the western suburbs (traditional lower to middle working class areas) Brian Klinkenberg

NSW IHD rates Geog 479 April 17 Brian Klinkenberg
Maps show a high degree of variability – especially Sydney IHD rates generally higher in west and lower towards the coast Sydney IHD rates lower in relatively wealthy north shore and eastern suburbs, with a band of high rates extending west along main arteries including with some extreme rates Brian Klinkenberg

Geog 479 April 17 What is epidemiology? The study of the distribution and determinants of health and disease-related states in populations, and the application of this study to control health problems. ‘the product of [epidemiology] is research and information and not public health action and implementation’ (Atwood et al. 1997) ‘epidemiology’s full value is achieved only when its contributions are placed in the context of public health action, resulting in a healthier populace.’ (Koplan et al. 1999) Note how different people have different views of the discipline. This relates to the ‘perspectives’ component that I have highlighted previously. Brian Klinkenberg

Geog 479 April 17 Epidemiologists . . . … are like bookies of disease, stalking the globe to determine point-spreads on which groups of people are most likely to get which diseases. Part detective and part statistician, part anthropologist and part physician, epidemiologists hope to track down the agents of illness by deducing which of the differences between peoples lie at the root of their distinctive disease patterns. (H. Shodell, Science ’82, September, p. 50) Brian Klinkenberg

Epidemiologic approaches
Geog 479 April 17 DESCRIPTIVE Health and disease in the community What? Who? When? Where? What are the health problems of the community? attributes of these illnesses? How many people are affected? What are the attributes of affected persons? Over what period of time? Where do the affected people live, work or spend leisure time? ANALYTIC Etiology, prognosis and program evaluation Why? How? What are the causal agents? What factors affect outcome? By what mechanism do they operate? The etiology of a disease or a problem is the study of its causes. Epidemiologic approaches Brian Klinkenberg

What are ‘health’ and ‘disease’?
Geog 479 April 17 What are ‘health’ and ‘disease’? Dorland's Illustrated Medical Dictionary (28th ed.): Health – "a state of optimal physical, mental, and social well-being, and not merely the absence of disease and infirmity.“ Disease – "any deviation from or interruption of the normal structure or function of any part, organ, or system (or combination thereof) of the body that is manifested by a characteristic set of symptoms and signs . . .". Brian Klinkenberg

What is ‘health’ Health, as defined in the World Health Organization's Constitution, is "a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity." Health is seen as more than just the absence of disease, and depends upon a complex suite of factors, with location taking the lead. A location is more than just a position within a spatial frame (e.g., on the surface of the Earth or within the human body). Different locations on Earth are usually associated with different profiles: physical, biological, environmental, economic, social, cultural and possibly even spiritual profiles, that do affect and are affected by health, disease and healthcare.

Location and health An example of how location matters and carries with it other factors into play: The body weight of infants at birth is one readily available piece of data, and the relationship between low birth-weight and maternal and child health is a continuing line of research. In New York City, Sara McLafferty and Barbara Tempalski have studied the spatial distribution of low birth-weight infants and identified areas in which the number of low birth-weight infants increased sharply during the 1980s. Their results indicated that the rise in low birth-weight was closely linked to women's declining economic status, inadequate insurance coverage and prenatal care, as well as the spread of crack/cocaine.

Location and health

What is ‘disease’ Manifestional criteria:
Geog 479 April 17 What is ‘disease’ Manifestional criteria: Manifestational criteria refer to symptoms, signs, and other manifestations of the condition. Defining a disease in terms of manifestational criteria relies on the proposition that diseases have a characteristic set of manifestations. This defines disease in terms of labeling symptoms. Causal criteria: Causal criteria refer to the etiology of the condition, which must have been identified in order to be employed. This defines disease in terms of underlying pathological etiology. Etiology is the study of causation, or origination. Brian Klinkenberg

Manifestational Criteria
Geog 479 Manifestational Criteria April 17 How do you identify a disease? The Acquired Immunodeficiency Syndrome (AIDS) was initially defined by the CDC in terms of manifestational criteria as a basis for instituting surveillance. The operational definition grouped diverse manifestations – Kaposi's sarcoma outside its usual subpopulation, PCP and other opportunistic infections in people with no known basis for immunodeficiency. This was based on similar epidemiologic observations (similar population affected, similar geographical distribution) and a shared type immunity deficit (elevated ratio of T-suppressor to T-helper lymphocytes). Pneumocystis jiroveci (carinii) (NEW-mo-SIS-tis CA-RIN- nee-eye) pneumonia, or PCP is a severe infection found in people with HIV. It is caused by a fungus called Pneumocystis jiroveci. Brian Klinkenberg

Geog 479 April 17 Causal Criteria Human immunodeficiency virus (HIV, previously called human lymphotrophic virus type III) was discovered and demonstrated to be the causal agent for AIDS. AIDS could then be defined by causal criteria. Brian Klinkenberg

Challenges with Disease Classifications
Geog 479 April 17 Challenges with Disease Classifications A single causal agent may have multiple clinical effects. Multiple etiologic pathways may lead to apparently identical manifestations, so that a manifestationally-defined disease entity may include subgroups with differing etiologies. Multi-causation necessitates a degree of arbitrariness in assigning a causative versus a contributing factor to a disease. Not all persons with the causal agent develop the disease. Etiology is the study of causation, or origination. Brian Klinkenberg

The natural history of disease
Geog 479 April 17 Onset of disease Diagnosis of disease Cause-specific mortality Physiologic Abnormalities Underlying Genetic Susceptibility Sub-clinical disease Clinical disease X Environmental & Behavioral Factors (Spatial dependence) The natural history of disease Brian Klinkenberg

What is health (and how location matters) What is a disease (and how to identify one) Quantifying disease occurrence Incidence versus prevalence Identifying the population Working with small area data

Measures of disease occurrence
Geog 479 April 17 To study disease, we need measures of its occurrence. Some measures of disease occurrence Counts Prevalence Incidence Mortality Measures of disease occurrence Brian Klinkenberg

Epidemiologic approaches
Geog 479 April 17 DESCRIPTIVE Health and disease in the community What? Who? When? Where? What are the health problems of the community? attributes of these illnesses? How many people are affected? What are the attributes of affected persons? Over what period of time? Where do the affected people live, work or spend leisure time? Each of the measures can be calculated for different combinations of What? Who? When? and Where? Each of the W’s needs to be defined carefully to get comparable measures across a province or state, a nation, the world. Epidemiologic approaches Brian Klinkenberg

Geog 479 April 17 The prevalence of a disease is the proportion of individuals in a population with the disease (cases) at a specific point in time: Prevalence is a proportion – range of 0 to 1 Removes the effect of total population size – makes estimates from different populations or over time more comparable. The prevalence of a disease is the proportion of a population that are cases at a point in time. The prevalence of persistent wheeze in a large sample of British primary school children surveyed during 1986 was approximately 3 per cent, the symptom being defined by response to a standard questionnaire completed by the children's parents. Prevalence is an appropriate measure only in such relatively stable conditions, and it is unsuitable for acute disorders. Prevalence Brian Klinkenberg

Prevalence Often expressed as a percent (%) – Prevalence * 100
Geog 479 April 17 Often expressed as a percent (%) – Prevalence * 100 Also often expressed as the prevalence per 1,000 or 10,000 or 100,000. Prevalence * 1,000 = prevalence per 1,000. Prevalence Brian Klinkenberg

Obesity Trends Among U.S. Adults
Geog 479 April 17 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman) 1991 1995 2002 2006 No Data <10% %–14% %–19% %–24% ≥25% Obesity Trends Among U.S. Adults Brian Klinkenberg

Salmonella cases: Infected
Geog 479 Salmonella cases: Infected April 17 Cases infected with the outbreak strain of Salmonella Saintpaul, as of July 15, pm EDT. We would need to know the population in each state in order to determine the prevalence. Brian Klinkenberg

If population size is 3.81 million, then
Geog 479 April 17 If population size is 3.81 million, then It should be noted that once a person is classified as a case, he or she is no longer liable to become a new case, and therefore should not contribute further person years at risk. Sometimes the same pathological event happens more than once to the same individual. In the course of a study, a patient may have several episodes of myocardial infarction. In these circumstances the definition of incidence is usually restricted to the first event, although sometimes (for example in the study of infectious diseases) it is more appropriate to count all episodes. The incidence of a disease is the rate at which new cases occur in a population during a specified period. Incidence Brian Klinkenberg

Salmonella cases: Incidence
Geog 479 April 17 Salmonella cases: Incidence Incidence of cases of infection with the outbreak strain as of July 15, pm EDT Brian Klinkenberg

Cases and Incidence – Salmonella
Geog 479 April 17 Cases infected with the outbreak strain of Salmonella Saintpaul, as of July 15, pm EDT Cases and Incidence – Salmonella Brian Klinkenberg

Incidence and Prevalence
Incidence and prevalence measure different aspects of disease occurrence Prevalence Incidence Numerator: Denominator: Measures: Most useful: All cases, no matter how long diseased Only NEW cases All persons in pop Only persons at risk of disease Presence of disease Risk of disease Resource allocation Risk, etiology Etiology: the study of a disease’s causes.

Mortality Rate – Incidence of death
Geog 479 April 17 Numerator Number of deaths Denominator Number of individuals in population (how defined?) Time interval 1-year: Annual Mortality Rate (typical to use an annual rate) Specifier age, sex, race, etc. Mortality Rate – Incidence of death Brian Klinkenberg

Mortality rates

Importance of defining terms
Geog 479 Importance of defining terms April 17 For any measure, carefully defining both the numerator and denominator is crucial for interpretation. In order for measures to be comparable across studies, need consistent definition and reporting strategies for numerator. Also need consistent approaches for counting (or estimating) the persons or person-time for the denominator. Brian Klinkenberg

Prevalence numerator – case definition
Geog 479 April 17 Prevalence numerator – case definition AIDS cases, United States Result of new definition Relate back to earlier discussion on manifestional criteria versus causal criteria. 1st Quarter of 1993: Expansion of surveillance case definition Brian Klinkenberg

The “demi” in Epidemiology
Geog 479 April 17 The “demi” in Epidemiology Understanding population dynamics is crucial to epidemiology. Demography = the study of population dynamics including fertility, mortality and migration Greek English epi among demos people logy study Brian Klinkenberg

Data considerations Developing multi-level models for spatially-correlated data requires confidence in the dependent data. Data for disease mapping often consists of disease counts and exposure levels in small adjacent geographical areas. The analysis of disease rates or counts for small areas often involves a trade-off between statistical stability of the estimates and geographic precision.

An example: Pellagra in the US
Geog 479 April 17 An example: Pellagra in the US Disease caused by a deficient diet or failure of the body to absorb B complex vitamins or an amino acid. Common in certain parts of the world (in people consuming large quantities of corn), the disease is characterized by scaly skin sores, diarrhea, mucosal changes, and mental symptoms (especially a schizophrenia-like dementia). It may develop after gastrointestinal diseases or alcoholism. Brian Klinkenberg

Multi-level data in spatial epidemiology
A case study: They considered approximately 800 counties clustered within 9 states in southern US For each county, data consisted of observed and expected number of pellagra deaths For each county, they also had several county-specific socio-economic characteristics and dietary factors % acres in cotton % farms under 20 acres Dairy cows per capita Access to mental hospital % Afro-American % single women Multi-level data in spatial epidemiology

Scientific Questions Which social, economical, behavioral, or dietary factors best explain spatial distribution of pellagra in southern US? Which of the above factors is more important for explaining the history of pellagra incidence in the US? To what extent have state-laws affected the incidence of pellagra?

Definition of Standardized Mortality Ratio

Definition of the expected number of deaths

Crude Standardized Mortality Ratio (Observed/Expected) of Pellagra Deaths in Southern USA in (Courtesy of Dr Harry Marks)

Statistical Challenges
For small areas, the Standardized Mortality Ratio (SMR) can be very instable and maps of SMR can be misleading Spatial smoothing can improve stability SMR are spatially correlated Spatially correlated random effects Covariates available at different level of spatial aggregation (county, State) Multi-level regression structure

Geog 479 April 17 Spatial Smoothing Spatial smoothing can reduce the random noise in maps of observable data (or disease rates) Trade-off between geographic resolution and the variability of the mapped estimates Spatial smoothing as method for reducing random noise and highlight meaningful geographic patterns in the underlying risk Brian Klinkenberg

Shrinkage Estimation Shrinkage methods can be used to take into account instable SMR for the small areas Idea is that: smoothed estimates for each area “borrow strength” (precision) from data in other areas, by an amount dependent on the precision of the raw estimate of each area

Shrinkage Estimation When population in area A is large
Statistical error associated with observed rate is small High credibility (weight) is given to observed estimate Smoothed rate is close to observed rate When population in area A is small Statistical error associated with observed rate is large Little credibility (low weight) is given to observed estimate Smoothed rate is “shrunk” towards mean rate of surrounding areas Shrinkage Estimation

Raw and smoothed SMR

SMR of pellagra deaths for 800 southern US counties in 1930
Crude SMR Smoothed SMR SMR of pellagra deaths for 800 southern US counties in 1930

Ensuring comparability
Geog 479 April 17 Ensuring comparability In epidemiology and demography, most rates, such as incidence, prevalence, mortality, are strongly age-dependent, with risks rising (e.g. chronic diseases) or declining (e.g. measles) with age. In part this is biological (e.g. immunity acquisition), and in part it reflects the hazards of cumulative exposure, as is the case for many forms of cancer. For many purposes, age-specific comparisons may be the most useful. Brian Klinkenberg

Ensuring comparability
However, comparisons of crude age-specific rates over time and between populations may be very misleading if the underlying age composition differs in the populations being compared. Hence, for a variety of purposes, a single age-independent index, representing a set of age-specific rates, may be more appropriate. This is achieved by a process of age standardization or age adjustment.

Geog 479 April 17 Standardizing The age-standardized mortality rate is a weighted average of the age-specific mortality rates per persons, where the weights are the proportions of persons in the corresponding age groups of the standard population. Brian Klinkenberg

Methodological toolboxes
Spatial Analytic Techniques for Medical Geographers (Albert et al., 2000)

Summary GIS and health geography Epidemiology
Major applications for GIS Epidemiology What is health (and how location matters) What is a disease (and how to identify one) Quantifying disease occurrence Incidence versus prevalence Identifying the population Working with small area data

GIS and Health Geography

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