Environmental & Population Health Statistics

Understanding the complex relationships between environmental factors and population health is essential for protecting communities and informing policy decisions.

As a specialized environmental and population health statistics consultant, I help researchers, public health agencies, and organizations analyze how environmental exposures affect health outcomes across diverse populations.

Whether you’re investigating health disparities, evaluating environmental interventions, or conducting risk assessments, my expertise ensures your findings are methodologically sound and actionable.

Comprehensive Environmental & Population Health Services

Transform complex environmental and health data into clear insights that drive meaningful change.

My specialized statistical services help researchers and public health professionals understand environmental health patterns, identify at-risk populations, and evaluate intervention effectiveness.

Study Design & Environmental Health Planning

Design robust studies that capture true environmental health relationships.

  • Develop environmental epidemiology studies with appropriate exposure assessment
  • Create population health surveillance systems for environmental monitoring
  • Design community-based participatory research frameworks
  • Plan longitudinal studies tracking environmental exposures over time
  • Conduct power analyses for environmental health intervention studies
  • Establish baseline measurements for environmental health disparities research

Environmental Risk Assessment & Analytics

Quantify environmental health risks with precision and transparency.

  • Analyze air pollution impacts on respiratory and cardiovascular health
  • Assess water quality effects on community health outcomes
  • Evaluate occupational health exposures and disease relationships
  • Model environmental mixtures and cumulative exposure effects
  • Conduct spatial analysis of environmental health disparities
  • Perform dose-response modeling for regulatory applications
  • Analyze climate change health impacts and adaptation strategies

Population Health & Health Equity Analysis

Identify and address health disparities through rigorous statistical analysis.

  • Analyze social determinants of health in environmental contexts
  • Assess health equity impacts of environmental policies
  • Evaluate community health intervention effectiveness
  • Model population-level health trends and environmental correlations
  • Conduct health disparities analysis across demographic groups
  • Analyze environmental justice concerns through statistical methods

One Health & Multi-System Analysis

Examine interconnected health relationships across human, animal, and environmental systems.

  • Analyze human-animal-environment health interactions
  • Model zoonotic disease transmission patterns
  • Assess ecosystem health impacts on human populations
  • Evaluate agricultural practices and community health outcomes
  • Analyze environmental contamination effects across species
  • Conduct integrated surveillance system analysis

Advanced Environmental Health Methods

Apply cutting-edge statistical approaches to complex environmental health questions.

  • Implement machine learning methods for environmental health prediction
  • Conduct causal inference analysis for environmental interventions
  • Perform time-series analysis of environmental health data
  • Apply geospatial statistics for environmental health mapping
  • Use Bayesian methods for environmental risk assessment
  • Implement survival analysis for environmental health cohort studies

Regulatory & Policy Support

Provide statistical expertise for environmental health decision-making.

  • Prepare regulatory submissions with robust statistical documentation
  • Develop environmental health impact assessments
  • Create policy briefs with clear statistical summaries
  • Support environmental health litigation with expert analysis
  • Conduct systematic reviews and meta-analyses
  • Provide expert testimony on environmental health statistics
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Why Work With Me For Your Environmental Health Statistics Needs?

Working with a specialized consultant provides distinct advantages for your environmental health research.

Time Efficiency

Focus on your core research objectives while I handle complex statistical analysis requirements.

Reduced Complexity

Navigate challenging environmental health data analysis with confidence and expert guidance.

Accurate Results

Apply appropriate statistical methods designed for environmental health data, including handling of complex exposure patterns, confounding variables, and population heterogeneity.

Actionable Insights

Generate results that directly inform environmental health policy, intervention design, and community protection strategies with clear implications for public health practice.

The Environmental Health Statistics Process

My consulting process ensures thorough analysis and clear communication of environmental health findings.

Discovery Phase

We discuss your environmental health questions, available data sources, study populations, and specific analytical needs to understand your research objectives.

Project Planning & Study Design

Together, we establish the project scope, timeline, and deliverables. I provide a detailed service proposal outlining analytical approaches, expected outcomes, and costs.

Data Analysis & Implementation

I conduct comprehensive statistical analysis using appropriate methods for environmental health data, addressing challenges like exposure measurement error, confounding, and population stratification.

Results & Reporting

I deliver detailed reports with publication-ready tables and figures, methodology documentation, and clear interpretation of findings for your intended audience.

For urgent questions, my on-demand consultation service offers quick, cost-saving solutions.

Book Express Consultation

Case Studies

I worked on large medical datasets to answer causal questions related to epidemiological determinants of disease through complex exposures. Challenges included selection bias, confounding, and missing data. I successfully developed a strategy that gave researchers confidence in their results.
I’ve worked with R&D scientists who were simultaneously running multiple experiments to answer important questions about their cutting-edge products that would have a direct impact on various stakeholders. My role was to help in designing and analyzing the experiments, balancing the conceptual purity of the Design of Experiments theory (DoE) with pragmatic concerns relating to costs and timeline. Most of this work is sealed behind a Non-Disclosure Agreement (NDA) which prevents me from elaborating more.

Don’t Just Take My Word For It…

The positive experiences of my happy collaborators showcased through their glowing testimonials, serve as powerful proof of trustworthiness and the impact of the results I deliver. These testimonials offer real-life examples of how I’ve helped research projects succeed. Here are some of their thoughts:

5/5

"He has a deep understanding of statistics, yet is able to skillfully explain complex concepts to people with little-to-no background in statistics both in French and English."

Elsa Brunet-Ratnasginham

Post-doc, UCSF

5/5

"I had never before worked with a biostatistician who speaks the same language as me! [...] Personally, our collaboration has allowed me to reconcile with statistics."

Manon Nayrac

Post-doc, CRCHUM

5/5

"I highly recommend Justin and his team for your data processing needs in order to have a more robust statistical model than the tests we are accustomed to conducting as biologists!"

Gérémy Sannier

Ph.D candidate, CRCHUM

5/5

"Thanks to him, statistics appeared to me as solutions rather than obstacles."

Mathieu Dubé

Research Associate, CRCHUM

Read Full Collaborator Testimonials
Justin Belair - Causal Inference Expert

My Statistics and Causal Inference Expertise

As a university-level statistics lecturer with a substantial LinkedIn following, scientists from all over the world come to me for my unique combination of academic excellence and practical experience in statistics and causal inference.

I’ve applied causal inference methods in varied settings in both academia and industry: in biomedical sciences such as nephrology, immunology, neuroscience, virology, occupational therapy, epidemiology, dermatology, psychiatry, and oncology; in natural sciences such as agronomy, ecology, and zoology; and social sciences such as communication, and psychology. The list keeps on growing!

I am currently writing an advanced textbook that I hope will give a young generation of academic and industry researches the tools needed to grapple with the complexities of causal inference, and maybe even develop a passion for the subject!

Need expert environmental health statistics support? From study design to complex population health analysis, I provide specialized expertise to advance your research and protect community health.

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Tools and Technologies

Statistical Software & Programming

Using advanced statistical software including R and Python, I implement specialized packages for environmental health analysis, geospatial statistics, and epidemiological modeling.

Environmental Health Analytics

I leverage specialized tools for environmental health data analysis, including GIS software for spatial analysis, time-series modeling packages, and environmental epidemiology-specific statistical methods.

Data Integration Platforms

I work with various environmental health databases and surveillance systems, integrating complex data sources to provide comprehensive population health insights.

Client Industries Served

My statistical consulting expertise extends beyond specific industries, serving clients in fields ranging from R&D in biotechnology and pharmaceuticals to researchers and Principal Investigators (PI) in academia.