Analysis Group Researchers Identify Neighborhood Characteristics That May Predict Psoriasis in Quebec, Canada

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Jun 18, 2024, 09:00 ET

BOSTON, June 18, 2024 /PRNewswire/ -- Researchers from Analysis Group, a global leader in health economics and outcomes research (HEOR), have coauthored a study connecting how the environments in which people live, work, and play may predict the incidence of psoriasis across Quebec. Published in the American Journal of Clinical Dermatology, this first study of its kind identified factors such as bright nighttime light and restricted access to green spaces with higher incidences of psoriasis.

Although the impact of individual-level health behaviors (e.g., diet, alcohol consumption, smoking, and exercise) on psoriasis is well understood, the impact of larger social, cultural, economic, and environmental conditions where patients live has not been studied. To fill this gap, investigators analyzed the relationship between the incidence of psoriasis in different areas of Quebec and more than 400 neighborhood covariates available from the Canadian Urban Environmental Health Research Consortium, including air, noise, and light pollution measures; greenness indicators; "blue spaces," or outdoor spaces with water; climate metrics; socioeconomic neighborhood characteristics; urbanization; and active living environments, in which points of interest and public transportation are within walking distance.

Using advanced tree-based machine learning to model the complex, multivariable datasets, investigators identified 46 neighborhood factors that had an impact on predicting the probability of high incidence of psoriasis. Top predictors, including higher ultraviolet radiation, maximum daily temperature, soil moisture, and urbanization, all had a negative association with incidence of psoriasis, meaning that higher predictor values were associated with lower incidence of psoriasis in a given area. However, higher levels of nighttime light brightness had a positive association, and middle-class socioeconomic factors in a neighborhood also suggested higher incidence of psoriasis.

The study, "Tree–Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada," was published in March by the American Journal of Clinical Dermatology. Analysis Group services were provided pro bono.

Investigators included Analysis Group Principal Jimmy Royer, Vice President Irina Pivneva, Director of Data Science Maxime Leroux, and Data Scientist Kathleen Chen; Drs. Anastasiya Muntyanu, Raymond Milan, Mohammed Kaouache, Ivan V. Litvinov, Elham Rahme, and Elena Netchiporouk of McGill University; Dr. Julien Ringuet of Centre de Recherche Dermatologique de Quebec; Dr. Wayne Gulliver of Memorial University of Newfoundland; Qiuyan Yu of Exponent Inc; and Christopher E. M. Griffiths and Darren M. Ashcroft of the University of Manchester.

To learn more about Analysis Group's HEOR capabilities, visit www.analysisgroup.com/healthoutcomes

About Analysis Group's HEOR, Epidemiology & Market Access Practice
Founded in 1981, Analysis Group is one of the largest international economics consulting firms, with more than 1,200 professionals across 14 offices. Analysis Group's health care experts apply analytical expertise to health economics and outcomes research (HEOR), clinical research, market access and commercial strategy, and health care policy engagements, as well as drug safety-related engagements in epidemiology. Analysis Group's internal experts, together with our network of affiliated experts from academia, industry, and government, provide our clients with exceptional breadth and depth of expertise and end-to-end consulting services globally.

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SOURCE Analysis Group