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{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003924', 'term': 'Diabetes Mellitus, Type 2'}], 'ancestors': [{'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}]}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2022-04-04', 'size': 562015, 'label': 'Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'SAP_000.pdf', 'typeAbbrev': 'SAP', 'uploadDate': '2022-05-05T05:25', 'hasProtocol': False}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 502682}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2006-03', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-05', 'completionDateStruct': {'date': '2021-10-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-05-15', 'studyFirstSubmitDate': '2022-05-05', 'studyFirstSubmitQcDate': '2022-05-15', 'lastUpdatePostDateStruct': {'date': '2022-05-18', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-05-18', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-10', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'All-cause mortality', 'timeFrame': 'Through longest available follow-up, up to 14.5 years (UK Biobank)', 'description': 'Mortality status optained from registries. The longest available follow-up from baseline examination will be used. Deaths during the first 3 years will be left-censored.'}, {'measure': 'All-cause mortality', 'timeFrame': 'Through longest available follow-up, up to 12.4 years (China Kadoorie Biobank)', 'description': 'Mortality status optained from registries. The longest available follow-up from baseline examination will be used. Deaths during the first 3 years will be left-censored.'}], 'secondaryOutcomes': [{'measure': 'Cardiovascular mortality', 'timeFrame': 'Through longest available follow-up, up to 14.5 (UK Biobank) and 0.4 (China Kadoorie Biobank) years', 'description': 'Cardiovascular mortality status optained from registries (I00 to I-99). The longest available follow-up from baseline examination will be used. Deaths during the first 3 years will be left-censored.'}, {'measure': 'Major adverse cardiovascular events (MACE)', 'timeFrame': 'Through longest available follow-up, up to 14.5 (UK Biobank only)', 'description': 'MACE status optained from registries (I20-I25, I60, I61, I63, or I64 in addition to cardiovascular mortality). The longest available follow-up from baseline examination will be used. Participants with events during the first 3 years will be left-censored.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Diabetes Mellitus, Type 2']}, 'descriptionModule': {'briefSummary': 'The primary aim of study is to study the association between leisure-time physical activity and all-cause mortality among individuals with type 2 diabetes in the UK Biobank cohort and the China Kadoorie Biobank cohort. Secondary outcomes are CVD-mortality (both cohorts) and risk of major adverse cardiovascular events (UK Biobank only). Secondary exposures are physical activity from transportation and occupation.', 'detailedDescription': "AIM To determine dose-response patterns between leisure-time physical activity and all-cause mortality in individuals with type 2 diabetes in the United Kingdom and China. A secondary aim is to study the association between domain-specific physical activity and all-cause mortality and fatal and non-fatal CVD.\n\nStudy design and setting The study is a nested cohort study based on the UK Biobank and China Kadoorie Biobank population-based prospective cohort studies. Both cohorts are designed to study the interrelations between environment, lifestyle, and genes, with the aims of improving the prevention, diagnosis, and treatment of chronic diseases. UK Biobank recruited a total of 502,682 participants (approximately 5.5% of 9.2 million invited) aged 37 to 82 years via 22 assessment centers across England, Wales, and Scotland between 2006 and 2010. At the assessment centers participants completed a touch-screen questionnaire, an interview with a nurse, and a wide variety of physical measurements and biological sampling. A subsample has attended a repeat assessment of all data collected at the baseline examination. Data has been linked with several electronic registries for ongoing follow-up on health status. Ethical approval to establish the UK Biobank cohort was obtained by the North-West Research Ethics Committee and participants gave written informed consent before data collection. China Kadoorie Biobank recruited 515,420 participants aged 30 to 79 years between 2004 and 2008 from 10 regions of mainland China. At the assessment centers participants completed an interviewer-administered questionnaire, physical measurements and provided blood spot tests and non-fasting blood samples. Data has been linked with several electronic registries for ongoing follow-up on health status. China Kadoorie Biobank was approved by the Ethics Committees at Oxford University, the China National Center for Disease Control and from institutional research boards at the local Centers for Disease Control in the 10 included regions.\n\nStudy population The Investigators identified individuals with prevalent type 2 diabetes in the UK Biobank from the baseline assessment (2006-2010) and the 1st repeat assessment (2012-2013), and in China Kadoorie Biobank from the baseline assessment (2004-2008).\n\nUK Biobank: Prevalent type 2 diabetes is determined by the algorithm by Eastwood (PMID: 27631769) or from measured Hba1c ≥48 mmol/mol. The algorithm is based on combining information on self-reported diabetes, insulin use, age of diabetes onset, and ethnicity obtained from a questionnaire in addition to self-reported diabetes, self-reported use of medications (see SAP), and age at diabetes diagnosis obtained from an interview with a trained nurse. Both 'probable' and 'possible' type 2 diabetes from the algorithm are included as type 2 diabetes cases. Type I diabetes is removed from the sample by combining information on insulin use, time from diagnosis to initiation of insulin use, and age of diagnosis. These criteria identify 29,236 individuals with type 2 diabetes.\n\nChina Kadoorie Biobank: prevalent type 2 diabetes is based on self-reported current diabetes with a diagnosis age above 30 years, a random plasma blood glucose ≥11.1 mmol/L, or fasting plasma blood glucose ≥7.0 mmol/L. These criteria identify 30,300 individuals with type 2 diabetes.\n\nFor further detail, please see attached predefined statistical analysis plan (SAP)."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '80 Years', 'minimumAge': '30 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'See statistical analysis plan', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* UK Biobank: Prevalent type 2 diabetes is determined by the algorithm by Eastwood (PMID: 27631769) or from measured Hba1c ≥48 mmol/mol.\n* China Kadoorie Biobank: Self-reported current diabetes with a diagnosis age above 30 years, a random plasma blood glucose ≥11.1 mmol/L, or fasting plasma blood glucose ≥7.0 mmol/L\n\nExclusion Criteria:\n\n* None'}, 'identificationModule': {'nctId': 'NCT05380232', 'briefTitle': 'Physical Activity and Mortality in Type 2 Diabetes', 'organization': {'class': 'OTHER', 'fullName': 'Aarhus University Hospital'}, 'officialTitle': 'Physical Activity and Mortality in Individuals With Type 2 Diabetes: Cross-country Comparison in UK Biobank and China Kadoorie Biobank', 'orgStudyIdInfo': {'id': '29717'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Individuals with type 2 diabetes at the baseline examination', 'description': 'UK Biobank: Prevalent type 2 diabetes is determined by the algorithm of Eastwood et al. (6) or from measured Hba1c ≥48 mmol/mol.\n\nChina Kadoorie Biobank: prevalent type 2 diabetes is based on self-reported current diabetes with a diagnosis age above 30 years, a random plasma blood glucose ≥11.1 mmol/L, or fasting plasma blood glucose ≥7.0 mmol/L.', 'interventionNames': ['Behavioral: Leisure-time physical activity']}], 'interventions': [{'name': 'Leisure-time physical activity', 'type': 'BEHAVIORAL', 'description': 'Self-reported leisure-time physical activity, categorized as; zero (reference), \\>0-7.49 MET-hrs/week, 7.5-14.9 MET-hrs/week, or ≥15 MET-hrs/week.', 'armGroupLabels': ['Individuals with type 2 diabetes at the baseline examination']}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Aarhus University Hospital', 'class': 'OTHER'}, 'collaborators': [{'name': 'University of Aarhus', 'class': 'OTHER'}, {'name': 'The Danish Diabetes Association', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Jakob Tarp', 'investigatorAffiliation': 'Aarhus University Hospital'}}}}