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Version: 0.0.2 | Published: 20 Nov 2023 | Updated: 549 days ago
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North-West London Diabetes Risk Scores (NWL DRS)

Dataset

Summary

DOI Name:
Not Available

Documentation

Description:
The North-West London Diabetes Risk Scores (NWL DRS) refers to a dataset that contains information related to diabetes risk assessment and scoring in the North-West London region. Diabetes is a chronic metabolic disorder characterized by high blood sugar levels, and assessing the risk of developing diabetes can help in preventive measures and early intervention. The NWL DRS dataset is designed to capture and analyze data pertaining to diabetes risk factors, screening results, and risk scoring in the North-West London population. It may include information on demographic factors, family history of diabetes, body mass index (BMI), blood pressure levels, fasting glucose levels, lipid profiles, and other relevant clinical and lifestyle factors. The dataset typically includes variables such as age, gender, ethnicity, weight, height, blood pressure measurements, laboratory test results (e.g., fasting glucose, cholesterol levels), and lifestyle information (e.g., smoking status, physical activity level). It may also incorporate specific diabetes risk scoring algorithms or models used to calculate an individual's risk of developing diabetes over a certain period. The NWL DRS dataset serves multiple purposes. It provides a valuable resource for researchers, healthcare professionals, and policymakers to study diabetes risk profiles, understand population-level risk factors, and develop targeted interventions for diabetes prevention and management. Healthcare providers can utilize the NWL DRS dataset to identify individuals at high risk of developing diabetes and implement appropriate preventive measures. It supports the early detection of individuals who may benefit from lifestyle modifications, education, or medical interventions to reduce their risk of developing diabetes and associated complications. Policymakers and public health officials can use the NWL DRS dataset to inform population-level strategies for diabetes prevention and management. By identifying high-risk groups and understanding the distribution of risk factors within the region, targeted interventions and public health campaigns can be designed to promote healthier lifestyles, increase awareness, and facilitate early diagnosis and treatment of diabetes. The NWL DRS dataset may also facilitate research on the effectiveness of different interventions or risk reduction strategies. By tracking diabetes risk scores and outcomes over time, researchers can evaluate the impact of interventions on reducing diabetes incidence and improving population health. It is important to note that access to the NWL DRS dataset and the specific data elements it contains may be subject to privacy regulations and governance frameworks. For more detailed information about the dataset, including its availability, specific variables, and usage guidelines, it is recommended to consult the relevant healthcare authorities or organizations responsible for managing and maintaining the NWL DRS dataset in the North-West London region.
Is Part Of:
WSIC

Coverage

Spatial:
NHS Brent CCG; NHS Central London CCG; NHS Ealing CCG; NHS Hammersmith &Fulham CCG; NHS Harrow CCG; NHS Hillingdon CCG; NHS Hounslow CCG; NHS West London CCG
Typical Age Range:
0-150
Follow Up:
> 10 YEARS
Physical Sample Availability:
NOT AVAILABLE

Provenance

Origin

Purposes:
  • ADMINISTRATIVE
  • CARE
  • OTHER
Sources:
OTHER
Collection Situations:
OTHER

Temporal

Accrual Periodicity:
OTHER
Time Lag:
OTHER

Accessibility

Access

Jurisdictions:
GB
Data Controller:
Joint data controller model across North West London
Data Processor:
NHS BRENT CCG

Usage

Data Use Limitations:
NO RESTRICTION
Data Use Requirements:
  • COLLABORATION REQUIRED
  • GEOGRAPHICAL RESTRICTIONS
  • PROJECT SPECIFIC RESTRICTIONS
  • USER SPECIFIC RESTRICTION
Resource Creators:
  • NHS NWL ICS
  • Discover-NOW

Format and Standards

Vocabulary Encoding Schemes:
OTHER
Conforms To:
OTHER
Languages:
en
Formats:
OTHER