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Air Pollution and Multiple Sclerosis Prevalence
in New Brunswick
January 26, 2022
Dr. Sandra Magalhaes
Research Associate
Epidemiologist
BACKGROUND
Multiple Sclerosis
wikimedia.org wikipedia.org
http://www.my-ms.org/
Who Gets MS?
• Peak incidence 30-50 years of age
• Females are two–three times more likely
• Month of birth effect
• Greatest risk in May (northern) and November (southern)
• Latitude gradient
• No consistent association with SES
4
Distribution of MS Globally
5
Distribution of MS across Canada
6
5.6
1994-2001
9.77 (8.00-11.9)
1995-2010
11.4 (10.7–12.0)
1998-2006
13.3 (12.6, 14.0) in 2007
19.4 (18.5, 20.3) in 2010
16.5 (15.8-17.2)
2001-2013
7.8 (7.6-8.1)
1996 - 2008
16.6 (15.7-17.5)
2001-2014
Distribution of MS in NB
14.4
(12.7-16.0)
18.1
(16.1-20.1)
19.7
(17.6-21.8)
19.7
(15.8-23.6)
24.6
(18.6-30.6)
10.9
(8.6-13.2)
12.4
(9.2-15.7)
Incidence
per
100,000
person-years
Environmental Risk Factors
• Latitude/Residential Location
• Infectious Mononucleosis/EBV
• Vitamin D
• Sun Exposure
• Body Size
• Smoking
• Air Pollution?
8
Evidence for Role of Air Pollution
• Urbanization associated with MS
• Air pollution impacts immune system and brain function
• Studies examining various pollutants identify link with higher MS rates and
disease progression, though results are inconsistent
9
RESEARCH OBJECTIVE:
To explore the association
between air pollution and MS in
New Brunswick
METHODS
NB-IRDT
• Conduct objective, rigorous and evidence-based
research and program evaluation to support
GNB planning and policy development
• Host and provide access to person-level
deidentified program data in a highly secure
research network (Fredericton, Moncton, Saint
John sites) as a data custodian
• Receive, link, host and analyze user-provided
personal information from clinical trials,
observational studies, devices etc.
12
Defining Air Pollution Exposure
• Data were available from CANUE (Canadian Urban Environmental Health
Research Consortium; canue.ca)
• Four pollutants were examined
• Particulate matter <2.5µm (PM2.5)
• Nitrogen dioxide (NO2)
• Sulphur dioxide (SO2)
• Ozone (O3)
• Long-term pollutant level obtained for each postal code in NB
• Pollutant levels derived using satellite data and regression models
13
Case Identification
• MS cases were identified using data from the Canadian Chronic Disease
Surveillance System (CCDSS)
• CCDSS uses linked administrative data sources in a consistent and
comparable way across jurisdictions, to allow for timely reporting to support
the planning and evaluation of policies and programs
CCDSS Multiple Sclerosis Case Algorithm
• 1 MS hospitalization or 5 physician visits in 2 years
• Other algorithms have been tested
• Any 3+ MS claims
• Time dependent definition
• Incorporation of prescription data
Sensitivity Specificity PPV NPV
Saskatchewan:
Al-Sakran
(2018)
91%
(81.2-94.6)
99.0%
(96.4-99.9)
98.9%
(96.1-99.9)
91.7%
(87.2-95.0)
Ontario:
Widdfield
(2015)
84.2%
(79.7-88.8)
100%
(99.9-100)
86.0%
(81.6-90.3)
99.9%
(99.9-100)
Geocoding Cases
• Geocoding done using data in the Citizen Database
• Registry of all NB residents who have applied for a Medicare card
• Basic demographic characteristics
• Indicates time eligible and ineligible (and why)
• Address file includes residential history
Study Design
• Ecological study design
• Data was aggregated using the 33 New
Brunswick Health Council Communities
(HCCs)
• Air pollutant levels and MS prevalence in 2011
were mapped using ArcGIS and analyzed
using SAS
• Associations between average air pollutant
levels and MS prevalence at the HCC-level
are reported
17
RESEARCH HYPOTHESIS:
HCCs with higher air pollutant
levels will have higher prevalence
of MS
RESULTS
Variation in Air Pollutants in NB
• Some regional variation observed in pollutant levels
• Average pollutant levels in all regions well below established Canadian air
quality standards
20
Variation in MS Prevalence
• 1532 prevalent MS cases were
identified in NB in 2011
• Prevalence 261 per 100,000
95%CI: 229-301
• Across NB prevalence of MS cases
varied greatly
• Lowest in Bouctouche and Neguac,
but highest in Campbellton and
Perth-Andover
21
Association between Air Pollutants and MS Prevalence
• HCCs with higher PM2.5 have higher prevalence of MS
• When all pollutants were considered together, only PM2.5 was found to be
associated with MS prevalence
• Results remained significant after adjusting for age, sex and income
22
O3
SO2
NO2
PM2.5
Parameter
0.93 (0.86, 1.02)
0.50 (0.16, 1.53)
0.74 (0.62, 0.88)
1.59 (1.31, 1.93)
(95% CI)
Odds Ratio
.15 .5 1 1.5 2
Pollutant Prevalence Ratio
(95%CI)
Summary
• Four pollutants were considered and only PM2.5 was associated with higher
MS prevalence
• PM2.5 exposure is suggested to negatively impact immune function and
impairs integrity of the blood-brain barrier
• Strengths: large population-based data sources, prospectively collected,
detailed pollution data, validated case definition
• Limitations: area level analysis, algorithm not a clinical diagnosis (gold
standard), cannot define disease incidence
• Results warrant closer look using individual-level exposure assignment
employing a population-based cohort study
23
Thank you!
Questions?
Funding Acknowledgements:
sandra.magalhaes@unb.ca

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Air Pollution and Multiple Sclerosis: An Ecological Study

  • 1. Air Pollution and Multiple Sclerosis Prevalence in New Brunswick January 26, 2022 Dr. Sandra Magalhaes Research Associate Epidemiologist
  • 4. Who Gets MS? • Peak incidence 30-50 years of age • Females are two–three times more likely • Month of birth effect • Greatest risk in May (northern) and November (southern) • Latitude gradient • No consistent association with SES 4
  • 5. Distribution of MS Globally 5
  • 6. Distribution of MS across Canada 6 5.6 1994-2001 9.77 (8.00-11.9) 1995-2010 11.4 (10.7–12.0) 1998-2006 13.3 (12.6, 14.0) in 2007 19.4 (18.5, 20.3) in 2010 16.5 (15.8-17.2) 2001-2013 7.8 (7.6-8.1) 1996 - 2008 16.6 (15.7-17.5) 2001-2014
  • 7. Distribution of MS in NB 14.4 (12.7-16.0) 18.1 (16.1-20.1) 19.7 (17.6-21.8) 19.7 (15.8-23.6) 24.6 (18.6-30.6) 10.9 (8.6-13.2) 12.4 (9.2-15.7) Incidence per 100,000 person-years
  • 8. Environmental Risk Factors • Latitude/Residential Location • Infectious Mononucleosis/EBV • Vitamin D • Sun Exposure • Body Size • Smoking • Air Pollution? 8
  • 9. Evidence for Role of Air Pollution • Urbanization associated with MS • Air pollution impacts immune system and brain function • Studies examining various pollutants identify link with higher MS rates and disease progression, though results are inconsistent 9
  • 10. RESEARCH OBJECTIVE: To explore the association between air pollution and MS in New Brunswick
  • 12. NB-IRDT • Conduct objective, rigorous and evidence-based research and program evaluation to support GNB planning and policy development • Host and provide access to person-level deidentified program data in a highly secure research network (Fredericton, Moncton, Saint John sites) as a data custodian • Receive, link, host and analyze user-provided personal information from clinical trials, observational studies, devices etc. 12
  • 13. Defining Air Pollution Exposure • Data were available from CANUE (Canadian Urban Environmental Health Research Consortium; canue.ca) • Four pollutants were examined • Particulate matter <2.5µm (PM2.5) • Nitrogen dioxide (NO2) • Sulphur dioxide (SO2) • Ozone (O3) • Long-term pollutant level obtained for each postal code in NB • Pollutant levels derived using satellite data and regression models 13
  • 14. Case Identification • MS cases were identified using data from the Canadian Chronic Disease Surveillance System (CCDSS) • CCDSS uses linked administrative data sources in a consistent and comparable way across jurisdictions, to allow for timely reporting to support the planning and evaluation of policies and programs
  • 15. CCDSS Multiple Sclerosis Case Algorithm • 1 MS hospitalization or 5 physician visits in 2 years • Other algorithms have been tested • Any 3+ MS claims • Time dependent definition • Incorporation of prescription data Sensitivity Specificity PPV NPV Saskatchewan: Al-Sakran (2018) 91% (81.2-94.6) 99.0% (96.4-99.9) 98.9% (96.1-99.9) 91.7% (87.2-95.0) Ontario: Widdfield (2015) 84.2% (79.7-88.8) 100% (99.9-100) 86.0% (81.6-90.3) 99.9% (99.9-100)
  • 16. Geocoding Cases • Geocoding done using data in the Citizen Database • Registry of all NB residents who have applied for a Medicare card • Basic demographic characteristics • Indicates time eligible and ineligible (and why) • Address file includes residential history
  • 17. Study Design • Ecological study design • Data was aggregated using the 33 New Brunswick Health Council Communities (HCCs) • Air pollutant levels and MS prevalence in 2011 were mapped using ArcGIS and analyzed using SAS • Associations between average air pollutant levels and MS prevalence at the HCC-level are reported 17
  • 18. RESEARCH HYPOTHESIS: HCCs with higher air pollutant levels will have higher prevalence of MS
  • 20. Variation in Air Pollutants in NB • Some regional variation observed in pollutant levels • Average pollutant levels in all regions well below established Canadian air quality standards 20
  • 21. Variation in MS Prevalence • 1532 prevalent MS cases were identified in NB in 2011 • Prevalence 261 per 100,000 95%CI: 229-301 • Across NB prevalence of MS cases varied greatly • Lowest in Bouctouche and Neguac, but highest in Campbellton and Perth-Andover 21
  • 22. Association between Air Pollutants and MS Prevalence • HCCs with higher PM2.5 have higher prevalence of MS • When all pollutants were considered together, only PM2.5 was found to be associated with MS prevalence • Results remained significant after adjusting for age, sex and income 22 O3 SO2 NO2 PM2.5 Parameter 0.93 (0.86, 1.02) 0.50 (0.16, 1.53) 0.74 (0.62, 0.88) 1.59 (1.31, 1.93) (95% CI) Odds Ratio .15 .5 1 1.5 2 Pollutant Prevalence Ratio (95%CI)
  • 23. Summary • Four pollutants were considered and only PM2.5 was associated with higher MS prevalence • PM2.5 exposure is suggested to negatively impact immune function and impairs integrity of the blood-brain barrier • Strengths: large population-based data sources, prospectively collected, detailed pollution data, validated case definition • Limitations: area level analysis, algorithm not a clinical diagnosis (gold standard), cannot define disease incidence • Results warrant closer look using individual-level exposure assignment employing a population-based cohort study 23

Editor's Notes

  1. 8