1. Environmental Epidemiology in
Small Areas
By Dr Nik Nor Ronaidi bin Nik Mahdi

2. Introduction
Environmental epidemiology studies
environmental risk factors and their impact on
the health of exposed people;
These factors may be natural or anthropogenic
The risk factors derive from the people’s
exposure to chemical, physical or biological
stressors.
The stressors come from point, line or area
sources and reach the population by way of
matrices ( air, water, soil, foods and space for
electomagnetic waves ).

3. Introduction (cont.)
The environmental risk adds or synergically
interacts with the basic risk of contracting an
illness.
The environmental risk is as great as is exposure
and individual physiological and anamnestic
susceptibility.
The exposure to environmental risk factors may
occur in an external environment (outdoor air )
or an internal environment (indoor air ).

4. Introduction (cont.)
• Spatial epidemiology is concerned with describing
and understanding spatial variation in disease
risk.
• Small areas definition:
– no hard-and-fast rules
– Any region containing fewer than 20 cases of disease
– refer to counties and subcounty areas like cities,
census tracts, ZIP code areas, and even individual
blocks
– They range from less than an acre to thousands of
square miles, and from no inhabitants to many
millions

5. Environmental Epidemiology
Objectives
• Environmental Epidemiology assesses the added
risk ( real or potential ) to the population exposed
to environmental pollutants with the purpose of
identifying the sources responsible for the
pollution.

6. Risk factors interaction
The added risk from environmental factors interacts
with non environmental risk factors:
• Behavioural (smoking, drugs, alcohol abuse)
• Socio-health (hygiene, nutrition, stress)
• Genetic (hereditary susceptibility)
• Anamnestic (previous diseases and medication)
• Physiological ( age, sex, pregnancy, weight,
height and respiration)
• Professional exposure

7. Why environmental epidemiology on
small areas?
• The complexity of interaction among risk factors hinders
the risk assessement with conventional statistic tools
used for large populations.
• We have to study the disaggregate non sampled and
territory related data to indentify a clusters of increased
incidence of disease and then filter from them cases with
non environmental risk factors.
• This is only possible for small populations living on small
areas concerned with a small number of risk factors.
• Provides a qualitative answer about the existence of an
association (e.g. between environmental variable and
health outcome)

8. Commonly used data sources
• Censuses:
– Most industrialized countries conduct reliable
censuses of the entire population at regular intervals
(e.g., every five or 10 years).
• Administrative Records:
– records kept by federal, state, and local governments
provide small-area data for years after or between
censuses.
• Sample Surveys:
– The limitation is that sample sizes are generally too
small to provide reliable estimates for small areas.

9. Problems
The small areas considered must be sufficiently
populated for the clusters significance, especially
for stochastic damages.
We have to make use of all computerised
databases : territorial, private, health, and
environmental.
During data transfer and assessement, privacy
must be guaranteed
The health data needs to include family,
physiological, pathological, behavioural
and occupational exposure and mobility data .

10. Problems (cont)
• Latency problems:
– The neoplastic, reproductive and development
diseases begin a long time from exposure.
– therefore the emission sources have to be considered
taking latency time into account.
– The affected subjects have verified for different
exposure for home changes.
– In the course of latency time, the health risks cannnot
be prevented, therefore a risk estimation of possible
exposure and effects is better than the
epidemiological survey of disease cases.

11. Solutions
• In low population density areas, the health
stochastic environmental damages is very little.
• All the institutions have adequate computerized
database systems.
• It is possible to use the private data without
access to subjects names on screen.
• We may obtain the informations on the
environmental risk factors from questionnaires
administered by the family doctor.

12. Necessary resources and
collaborations
Territorial, health and environmental institutions
have to form a coordinated operative team.
The databases have to be to coordinated on
work station capable of building, to managing
and to querying the geodatabases.
The clusters filtering process requires the
elaboration and administration of questionnaires
through family doctors.

13. Operative process
A)Identify the suspicious sources and risk areas
from emissions register, environmental data and
modeling
B) Choose a study area, including risk areas, with a
population of suitable dimensions
C) Build the thematic map of the study area
D) Acquiring and georeference the road, socio-
health and personal databases

14. Operative process ( cont )
E) Identify possible health damage and
environmental diseases
F) Show evidence of the environmental disease
clusters associated with selected factors
G) Filter the clusters from non environmental risk
factor cases
H) Verify the filtered clusters by biochemical
methods on tissue

15. A+B ) Study area identification
Examine the emissions registers and
environmental data in air, soil, foods, water and
space.
Identify the hazardous substances and stressors
carried by matrices.
Fate and diffusion modeling of hazardous
substances and stressors.
Risk areas identification.
Link the risk areas with synergic stressors.
Choose a study area including risk and stressor free
areas.

16. C+D) Geodatabase building
Acquire raster map of study area
Map vectorialization for residential, production
and service structure and sensitive sites
Acquire personal and health databases on the
map layers for geodatabase building

17. E) Possible environmental diseases
Reduced fertility, spontaneous abortion
Lower birth weight, malformations
Respiratory, gastroenteric and kidney diseases
Immune, endocrine and neoplastic diseases
Nervous and mental diseases
Dermatological and sense organ diseases
Infectious and parasitic diseases
Cardiocirculatory and muscle-skeleton diseases

18. F) clusters identification
• Health data layer may show clusters with a
greater incidence of disease caused by the
environment causes
G) clusters purification
•Patients ( or at relatives in case of death ) of
these clusters have to be given a questionnaire
to identify and exclude non prevalent
environmental cases

19. G) Anamnestic questionnaire for
cluster filtering
Family anamnesis ( disease cases in relatives not
living in the cluster )
Work and behavioural anamnesis ( exposure to
professional and behavioural risk factors )
socioeconomic, pathologic and pharmacological
anamnesis ( factors modifying exposure,
susceptibility or prognosis )

20. H) Clusters biochemical check
Even the most careful cluster purification not
confirm the relationship between environmental
factors and diseases
Therefore we must research metabolic markers,
i.e.matabolites of pollutants, in tissues ( hairs or
nails ) or biological fluids ( blood, urine, saliva
and mother’s milk ) in affected people or in
random sample for comparison with subjects
outside the cluster.

21. Environmental risk communication
• The communication should be able to
disseminate risk information in a timely, reliable
and targeted manner
• Communication should include: method
description, uncertainty factors and scientific
bibliography.
• The assessement receivers who manage the
environmental risk take responsability for using
the assessement in environmental protection
and health prevention decisions.

22. • Objective:
– To assess environmental causes of outdoor falls using
a small urban community in Hong Kong as an
example.
• Data collection by collaboration with A&E
Department of the Kwong Wah Hospital (94% of
HK population seek medical care from public
hospitals)

23. • ‘geocoding’ or ‘address matching’ is a process
that involves assigning a geographic coordinate
to position a fall location and linking its
descriptive attributes
• Using Centamap—a free web map service in
Hong Kong

24. • Data analysis:
2.Incident mapping
– uses points as the smallest representation of a fall
incident
– Each point location is associated with a number of
attributes about the faller
– enables a better understanding of incidental factors
and their spatial patterns
3.Cluster analysis
– involves the detection of hot spots
– These hot spots are speculated as the correct
targets for implementing improvement or
preventive measures.

25. 1. Associative study
– to explain relationships between geographical
phenomena
– enable the identification of potential hot spots of falls
and their likely causes
• On-site inspection at target locations to identify
specific circumstances surrounding the falls.

28. Problems
• Confounding factors:
– demographic characteristics, personal traits (including
gait and balance, visual condition), past medical history
and long term use of medication, as well as activities
engaged at the time can increase or decrease the risk of
falls.
• No official data about the location of falls
available→ collaboration with the A&E Department
of the Kwong Wah Hospital

29. Problems (cont)
• fall injuries either treated in other hospitals or by
other means (e.g. traditional therapy) or not
treated will not be included.
• Research conducted with consent from the
patients and on a voluntary basis
– it would be wise for the government, to integrate
data on fall injuries into the medical records of all
hospitals under the mandate of the Hospital Authority

30. THANK YOU

31. REFERENCES
• Alessandro Menegozzo (2010), slide presentation: Environmental
Epidemiology on small areas. Agenzia Regionale Prevenzione
Protezione Ambientale Veneto ( Italy ).
• P. Elliott, J. Cuzick, D. English, R.Stern (1992). Geographical and
Environmental Epidemiology: Methods for Small-Area Studies.
Oxford University Press Inc., New York.
• Paul Elliott and David A. Savitz (2008). Design Issues in Small-Area
Studies of Environment and Health. Environmental Health
Perspectives, 116, 1098-1104.
• Poh-Chin Lai, Wing-Cheung Wong, Chien-Tat Low, Martin Wong,
Ming-Houng Chan (2010). A Small-Area Study of Environmental
Risk Assessment of Outdoor Falls. J Med Syst
• Stanley K. Smith (2003). Small-area Analysis. Encyclopedia of
Population. Farmington Hills, MI: Macmillan Reference, 898-901.