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How does educational level correlate with the risk of Alzheimer's?

Bashir Gulistani

Last edited Oct 23, 2024
Created on Oct 23, 2024

Demographic Information:

  • Age: Patients' ages range from 60 to 90 years, offering insights into how Alzheimer's disease manifests across different age groups.
  • Gender: Gender is recorded with 0 representing Male and 1 representing Female.
  • Ethnicity: Patients' ethnic backgrounds are categorized as Caucasian, African American, Asian, or Other, allowing for analysis of Alzheimer's impact across various ethnic groups.
  • Education Level: The dataset includes the educational background of each patient, from no formal education to higher education, which may influence cognitive resilience.

Lifestyle Factors:

  • Body Mass Index (BMI): BMI values, ranging from 15 to 40, are provided for each patient to explore the connection between physical health and Alzheimer's.
  • Smoking Status: Indicates whether the patient is a smoker (1 for Yes, 0 for No), given that smoking is a risk factor for various health conditions, including cognitive decline.
  • Alcohol Consumption: The number of alcohol units consumed per week is recorded, ranging from 0 to 20, to assess its effect on cognitive health.
  • Physical Activity: Hours of weekly physical activity are listed, with values ranging from 0 to 10, to examine its relationship with cognitive function.
  • Diet Quality: Patients receive a diet quality score from 0 to 10, which might be linked to overall health and cognitive performance.
  • Sleep Quality: Sleep quality is rated on a scale of 4 to 10, considering the connection between poor sleep and cognitive issues, including Alzheimer's.

Medical History:

  • Family History of Alzheimer's: Records whether the patient has a family history of Alzheimer's disease (1 for Yes, 0 for No), a key factor in genetic predisposition.
  • Cardiovascular Disease: Notes the presence of cardiovascular disease, important due to the link between heart and brain health.
  • Diabetes: Indicates whether the patient has diabetes, as it increases the risk of Alzheimer's.
  • Depression: Records if the patient has a history of depression, a known risk factor for cognitive decline.
  • Head Injury: Includes data on whether the patient has suffered a head injury, as traumatic brain injuries can elevate Alzheimer's risk.
  • Hypertension: The presence of high blood pressure is recorded, another significant factor in overall health and Alzheimer's risk.

Clinical Measurements:

  • Blood Pressure (Systolic and Diastolic): Blood pressure readings are included, with systolic ranging from 90 to 180 mmHg and diastolic from 60 to 120 mmHg, to assess cardiovascular health.
  • Cholesterol Levels: The dataset provides total cholesterol levels (150-300 mg/dL), as well as LDL (50-200 mg/dL), HDL (20-100 mg/dL), and triglycerides (50-400 mg/dL), which are crucial for understanding heart health in relation to Alzheimer's.

Cognitive and Functional Assessments:

  • Mini-Mental State Examination (MMSE) Score: Scores range from 0 to 30, with lower scores indicating more severe cognitive impairment, providing a snapshot of cognitive status.
  • Functional Assessment: Functional impairment is scored from 0 to 10, with lower scores indicating greater difficulty in daily living, highlighting the impact of Alzheimer's.
  • Memory Complaints: Notes whether the patient has reported memory issues (1 for Yes, 0 for No), often an early indicator of Alzheimer's.
  • Behavioral Problems: Records the presence of behavioral issues, which are significant in Alzheimer's progression and management.
  • Activities of Daily Living (ADL) Score: Scores range from 0 to 10, with lower scores indicating more difficulty in performing daily activities, essential for gauging disease severity.

Symptoms:

  • Confusion and Disorientation: Records whether the patient experiences confusion or disorientation, common symptoms in Alzheimer's.
  • Personality Changes: Includes information on any personality changes, a notable aspect of Alzheimer's disease.
  • Difficulty Completing Tasks: Indicates whether the patient has trouble completing tasks, a key sign of cognitive decline.
  • Forgetfulness: Tracks the presence of forgetfulness, one of the primary symptoms of Alzheimer's.

Diagnosis Information:

  • Alzheimer's Diagnosis Status: Clearly indicates whether each patient has been diagnosed with Alzheimer's disease (1 for Yes, 0 for No), allowing for data analysis in the context of confirmed diagnoses. Confidential Information:

Doctor in Charge: To protect privacy, the dataset uses a placeholder ("XXXConfid") for the name of the doctor overseeing each patient, ensuring compliance with confidentiality standards.

Identify Tasks for your Datasets:

  • I want to summarize the distribution of MMSE (Mini-Mental State Examination) scores across all patients.
  • I want to compare the correlation between Age and Memory Complaints.
  • I want to explore unexpected patterns in Physical Activity and Diagnosis (whether the patient has Alzheimer’s).
  • I want to identify patients with high CholesterolTotal who also suffer from Cardiovascular Disease.
  • I want to present the trend of Systolic Blood Pressure over age groups.

Link to the original dataset:

https://www.kaggle.com/datasets/rabieelkharoua/alzheimers-disease-dataset

MIT Licensed