Data_WP5_6 Clinical Biomarkers

This dataset comprises quantifiable clinical measurements related to the cardiometabolic and respiratory health of participants involved in the URBANOME project. Its primary aim is to support the identification of risk factors associated with environmental exposures that may adversely affect human health. The dataset consists of blood and urine biomarkers collected from participants both before and after the interventions (Phase IIa and Phase IIb). These biomarkers provide insights into systemic inflammation, metabolic function, stress levels, hematological parameters, and kidney function. The following blood and urine-based biomarkers are included in the dataset: Blood Sugar (Glucose) – Code: B_Sugar, unit: mg/dL Blood Creatinine – B_Creatinine, mg/dL Blood Cholesterol – B_Cholesterol, mg/dL Blood Triglycerides – B_TGs, mg/dL Ferritin – Ferritin, ng/mL Cortisol – Cortisol, nmol/L Red Blood Cells – RBC, M/μL Hemoglobin – HGB, g/dL Hematocrit – HCT, % Mean Corpuscular Hemoglobin – MCH, pg Mean Corpuscular Hemoglobin Concentration – MCHC, g/dL Red Cell Distribution Width (Coefficient of Variation) – RDW_CV, % White Blood Cells – WBC, K/μL Neutrophils (Percentage) – NEUT_f, % Neutrophils (Absolute Count) – NEUT_a, K/μL Lymphocytes (Percentage) – LYM_f, % Lymphocytes (Absolute Count) – LYM_a, K/μL Monocytes (Percentage) – MONO_f, % Monocytes (Absolute Count) – MONO_a, K/μL Eosinophils (Percentage) – EOS_f, % Eosinophils (Absolute Count) – EOS_a, K/μL Basophils (Percentage) – BASO_f, % Basophils (Absolute Count) – BASO_a, K/μL Platelets – PLT, K/μL Plateletcrit – PCT, unit not specified Mean Platelet Volume – MPV, fL Platelet Distribution Width – PDW, % Mean Corpuscular Volume – MCV, fL Urine-based measurements included: Urine Test Date – U_Date, Date Urine Creatinine – U_Creatinine, g/L Urine Specific Gravity – U_SpecificGravity, unitless In addition to clinical and biomarker data, the dataset incorporates participants’ responses to a comprehensive questionnaire designed to capture diverse information relevant to their environmental and lifestyle contexts. This includes potential sources of pollution and unhealthy living conditions within their immediate surroundings, detailed characteristics of the indoor home environment, dietary habits, recent engagement in specific environmental or occupational activities, and recent use of personal care and cosmetic products. Data are stored by Urban Living Lab, and each file is accompanied by a data dictionary to facilitate the identification and interpretation of variables, measurement units, and data structure.