{"id":38,"date":"2025-10-20T11:17:29","date_gmt":"2025-10-20T15:17:29","guid":{"rendered":"http:\/\/brukdconsultancy.com\/?p=38"},"modified":"2026-01-02T14:55:14","modified_gmt":"2026-01-02T19:55:14","slug":"are-you-at-risk-of-diabetes","status":"publish","type":"post","link":"https:\/\/brukdconsultancy.com\/blog\/2025\/10\/20\/are-you-at-risk-of-diabetes\/","title":{"rendered":"Discover Key Diabetes Predictors from U.S. and Canadian Health Data"},"content":{"rendered":"

Note to our SMB Partners:<\/strong> This project represents a high-level intervention within the healthcare sector. While the scale and regulatory environment of public health differ from the typical Small-to-Medium Business (SMB) landscape, this case study serves as a clear demonstration of what is possible when organizations move beyond surface-level metrics to leverage high-quality, harmonized data.<\/p>\n

Diabetes is one of the most common chronic health conditions in North America, affecting millions of people every year. At BRUKD Consultancy<\/strong>, we believe that the same predictive analytics used to assess health risks can be applied to business health. By analyzing complex variables, we can move from reacting to problems to predicting outcomes.<\/p>\n

Explore the Interactive Dashboard<\/h2>\n

We invite you to experience this analytical rigor firsthand. Our Diabetes Risk Prediction Dashboard<\/strong> allows you to explore risk factors using real, harmonized health data from both the United States and Canada.<\/p>\n

\n
\n Try the Interactive Dashboard<\/a>\n <\/div>\n<\/div>\n
<\/div>\n

Interested in applying this level of predictive insight to your business?<\/p>\n

\n
\n Book a Strategic Session<\/a>\n <\/div>\n<\/div>\n
<\/div>\n

Key Findings: U.S. vs. Canada<\/h2>\n

By integrating datasets from the U.S. (BRFSS 2015) and Canada (CCHS), we validated risk factors across different healthcare systems. This cross-border harmonization revealed the most consistent predictors of diabetes:<\/p>\n

    \n
  • High Blood Pressure:<\/strong> The strongest predictor in both populations.<\/li>\n
  • High BMI:<\/strong> A universal driver of metabolic risk.<\/li>\n
  • High Cholesterol:<\/strong> Significant correlation regardless of residency.<\/li>\n<\/ul>\n

    Predictive Performance<\/h3>\n
    \n\n\n\n\n\n\n
    Model Type<\/th>\nU.S. BRFSS (AUC)<\/th>\nCanada CCHS (AUC)<\/th>\n<\/tr>\n<\/thead>\n
    Logistic Regression<\/td>\n0.8149<\/td>\n0.7729<\/td>\n<\/tr>\n
    XGBoost<\/td>\n0.8206<\/td>\n0.7315<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

    Note: A higher AUC score represents better predictive accuracy. These models demonstrate how AI can reliably identify high-risk individuals before chronic conditions escalate.<\/em><\/p>\n

    Why This Matters for Your Business<\/h2>\n

    At BRUKD Consultancy<\/strong>, we bridge the gap between academic data science and operational reality. Whether you are managing public health data or SMB customer patterns, the methodology is the same: isolate the variables, review the evidence, and pilot the experiment. By using high-quality data, we move from intuition to certainty.<\/p>\n

    \n

    Disclaimer: This dashboard is for educational and research purposes only. It does not provide medical advice. Always consult a qualified healthcare professional for personal health concerns.<\/em><\/p>\n

    \n Modernizing Canadian Industry through Evidence-Based Practice.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

    The project utilizes an interactive dashboard to assess diabetes risk factors using health data from the U.S. and Canada. It reveals key predictors such as high blood pressure, BMI, and cholesterol, while comparing machine learning models’ effectiveness. The tool offers personalized risk assessments for better public health awareness.<\/p>\n","protected":false},"author":272815509,"featured_media":58,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[784926912],"tags":[12374,1279451,31172306,40978],"class_list":["post-38","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-health-wellness-data-science-ai","tag-artificial-intelligence","tag-diabetes-risk","tag-health-analytics","tag-machine-learning"],"_links":{"self":[{"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/posts\/38","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/users\/272815509"}],"replies":[{"embeddable":true,"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/comments?post=38"}],"version-history":[{"count":14,"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/posts\/38\/revisions"}],"predecessor-version":[{"id":505,"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/posts\/38\/revisions\/505"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/media\/58"}],"wp:attachment":[{"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/media?parent=38"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/categories?post=38"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/brukdconsultancy.com\/blog\/wp-json\/wp\/v2\/tags?post=38"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}