Name: National Poll On Healthy Aging (NPHA)
Creator: Kaggle
License: https://creativecommons.org/licenses/by/4.0/

About this Dataset

National Poll On Healthy Aging (NPHA)

Overview

This is a subset of the NPHA dataset filtered down to develop and validate machine learning algorithms for predicting the number of doctors a survey respondent sees in a year. This dataset’s records represent seniors who responded to the NPHA survey.

Dataset Information

For what purpose was the dataset created?
The National Poll on Healthy Aging dataset was created to gather insights on the health, healthcare, and health policy issues affecting Americans aged 50 and older. By focusing on the perspectives of older adults and their caregivers, the University of Michigan aimed to inform the public, healthcare providers, policymakers, and advocates about the various aspects of aging. This includes topics like health insurance, household composition, sleep issues, dental care, prescription medications, and caregiving, thereby providing a comprehensive understanding of the health-related needs and concerns of the older population.

Who funded the creation of the dataset?
The dataset was funded by AARP and Michigan Medicine, the University of Michigan's academic medical centre.

What do the instances in this dataset represent?
Each row represents a survey respondent.

Does the dataset contain data that might be considered sensitive in any way?
Yes. There is information about race/ethnicity, gender, age.

Was there any data preprocessing performed?
For this subset of the original NPHA dataset we chose 14 features related to health and sleep to use for the prediction task. We then removed all survey respondents with missing responses for any of the chosen features.

Has Missing Values?
No

Introductory Paper
National Poll on Healthy Aging (NPHA)
By Malani, Preeti N., Kullgren, Jeffrey, and Solway, Erica. 2017
Published in Inter-university Consortium for Political and Social Research

Additional Variable Information

Class Labels

Number of Doctors Visited: The total count of different doctors the patient has seen = {
1: 0-1 doctors
2: 2-3 doctors
3: 4 or more doctors
}

Age: The patient's age group = {
1: 50-64
2: 65-80
}

Physical Health: A self-assessment of the patient's physical well-being = {
-1: Refused
1: Excellent
2: Very Good
3: Good
4: Fair
5: Poor
}

Mental Health: A self-evaluation of the patient's mental or psychological health = {
-1: Refused
1: Excellent
2: Very Good
3: Good
4: Fair
5: Poor
}

Dental Health: A self-assessment of the patient's oral or dental health= {
-1: Refused
1: Excellent
2: Very Good
3: Good
4: Fair
5: Poor
}

Employment: The patient's employment status or work-related information = {
-1: Refused 6
1: Working full-time
2: Working part-time
3: Retired
4: Not working at this time
}

Stress Keeps Patient from Sleeping: Whether stress affects the patient's ability to sleep = {
0: No
1: Yes
}

Medication Keeps Patient from Sleeping: Whether medication impacts the patient's sleep = {
0: No
1: Yes
}

Pain Keeps Patient from Sleeping: Whether physical pain disturbs the patient's sleep = {
0: No
1: Yes
}

Bathroom Needs Keeps Patient from Sleeping: Whether the need to use the bathroom affects the patient's sleep = {
0: No
1: Yes
}

Unknown Keeps Patient from Sleeping: Unidentified factors affecting the patient's sleep = {
0: No
1: Yes
}

Trouble Sleeping: General issues or difficulties the patient faces with sleeping = {
0: No
1: Yes
}

Prescription Sleep Medication: Information about any sleep medication prescribed to the patient = {
-1: Refused
1: Use regularly
2: Use occasionally
3: Do not use
}

Race: The patient's racial or ethnic background = {
-2: Not asked
-1: REFUSED
1: White, Non-Hispanic
2: Black, Non-Hispanic
3: Other, Non-Hispanic
4: Hispanic
5: 2+ Races, Non-Hispanic
}
Gender: The gender identity of the patient = {
-2: Not asked
-1: REFUSED
1: Male
2: Female
}

Tables

Npha Doctor Visits

@kaggle.joebeachcapital_national_poll_on_healthy_aging_npha.npha_doctor_visits

14.73 KB
714 rows
15 columns


CREATE TABLE npha_doctor_visits (
  "number_of_doctors_visited" BIGINT,
  "age" BIGINT,
  "phyiscal_health" BIGINT,
  "mental_health" BIGINT,
  "dental_health" BIGINT,
  "employment" BIGINT,
  "stress_keeps_patient_from_sleeping" BIGINT,
  "medication_keeps_patient_from_sleeping" BIGINT,
  "pain_keeps_patient_from_sleeping" BIGINT,
  "bathroom_needs_keeps_patient_from_sleeping" BIGINT,
  "uknown_keeps_patient_from_sleeping" BIGINT,
  "trouble_sleeping" BIGINT,
  "prescription_sleep_medication" BIGINT,
  "race" BIGINT,
  "gender" BIGINT
);