A city health profile is a public health report that provides a comprehensive overview of the demographics for a specific city or neighborhood as well as information on a variety of social and health indicators for that particular area.

The 2019 Local Authority Health Profiles have been published.

The Local Authority Health Profiles pull together existing information in one place and contain data on a range of health and wellbeing indicators for local populations. They are intended as ‘conversation starters’ to highlight local issues and priorities for members, and for discussion at Health and Wellbeing Boards.

To find your local 2019 Local Authority Health Profile:

• visit the http://fingertips.phe.org.uk/profile/health-profiles">Local Authority Health Profiles homepage and insert a postcode, town or local authority in the ‘Find your Health Profile’ search box
• alternatively click on the ‘Downloads’ section of the online tool which can be accessed by clicking ‘Start Go to the data’ on the health profiles homepage

2022 School Health Profiles (Profiles) Dataset. Profiles is a system of surveys assessing school health policies and practices in states, school districts, territories, and tribes. Profiles surveys are conducted biennially by education and health agencies among middle and high school principals and lead health education teachers. Profiles monitors the current status of school health education requirements and content, physical education and physical activity, practices related to bullying and sexual harassment, school health policies related to tobacco-use prevention and nutrition, school-based health and mental health services, family engagement and community involvement, and school health coordination.

County Health Status Profiles is an annually published report for the State of California by the California Department of Public Health in collaboration with the California Conference of Local Health Officers. Health indicators are measured for 58 counties and California statewide that can be directly compared to national standards and populations of similar composition. Where available, the measurements are ranked and compared with target rates established for Healthy People National Objectives.

For tables where the health indicator denominator and numerator are derived from the same data source, the denominator excludes records for which the health indicator data is missing and unable to be imputed.

For more information see the County Health Status Profiles report.

The online Health Profiles data has been updated for August 2017.

The online Health Profiles are updated quarterly at the same time as the Public Health Outcomes Framework (PHOF).

The data are presented in an interactive tool that allows users to view them in a user-friendly format. The profiles provide a snapshot overview of health for each local authority in England. These profiles are intended to help local government and health services make plans to improve local people’s health and reduce health inequalities.

This quarterly update contains one new indicator showing the estimated dementia diagnosis rate for people aged 65 and over. We added this indicator following consultation with users and it also appears in PHOF.

http://fingertips.phe.org.uk/profile/health-profiles">View the online Health Profiles.

Provides a collation of national and regional data to provide a baseline against which people can compare data from their own Local Health Profile (LHP). Source agency: Health Designation: Official Statistics not designated as National Statistics Language: English Alternative title: Health Profile of England

Health profiles for all LA areas presenting a range of indicators and a snapshot of the overall health of the local population. Source agency: Health Designation: Official Statistics not designated as National Statistics Language: English Alternative title: Local Health Profiles

This dataset offers a comprehensive collection of various diseases, covering a broad spectrum of health conditions. It includes each disease's common name, scientific name, a detailed description, primary symptoms, known causes, available treatment options (both medical and therapeutic), and suggested lifestyle modifications for managing symptoms. This dataset can serve as a valuable resource for researchers, medical professionals, AI developers, and anyone interested in healthcare-related data science projects

📘 Overview

The Diabetes Health Indicators Dataset provides a rich and realistic representation of patient health data designed for diabetes risk prediction, healthcare analytics, and machine learning experimentation. It is fully preprocessed, consistent, and aligned with medically validated patterns, ensuring reliability for both research and applied modeling.

This dataset integrates multiple health dimensions—demographic, lifestyle, and clinical—to enable robust data-driven insights into diabetes progression and prevention.

🧬 Dataset Description

Each record in this dataset reflects an individual’s health profile, combining demographic attributes, lifestyle behaviors, family medical background, and physiological measurements. The variables simulate realistic medical distributions derived from public health research, maintaining privacy while preserving analytical validity.

The data is suitable for use in:

Predictive modeling (classification or regression)

Exploratory data analysis (EDA)

Hypothesis testing

Health trend visualization

📊 Feature Categories 👨‍👩‍👧 Demographics

Includes age, gender, ethnicity, education level, income category, and employment type — essential for understanding population health disparities.

💪 Lifestyle Indicators

Captures habits such as smoking, alcohol consumption, diet quality, sleep patterns, and physical activity — crucial for preventive health modeling.

🧠 Medical History

Accounts for genetic predisposition and prior conditions such as hypertension or cardiovascular disease, enhancing model interpretability.

❤️ Clinical Measurements

Covers vital and biochemical markers, including body mass index (BMI), blood pressure, cholesterol levels, triglycerides, fasting/post-meal glucose, insulin, and HbA1c metrics.

🎯 Target Variables

Provides both binary and multiclass targets for predicting diabetes diagnosis and stage, supporting diverse modeling approaches.

✅ Data Quality Assurance

Complete & Clean: No missing or duplicate entries.

Medically Realistic: Values fall within validated clinical ranges.

Balanced Distribution: Reflects realistic yet model-friendly patterns.

ML Ready: Ideal for direct integration into predictive workflows.

💡 Potential Use Cases

🩹 Binary Classification: Predict whether a patient has diabetes.

⚕️ Multiclass Prediction: Determine diabetes stage (e.g., Pre-Diabetes, Type 1, Type 2).

📈 Regression Modeling: Estimate glucose, HbA1c, or overall risk scores.

🧩 Exploratory Analysis: Discover relationships between lifestyle and clinical indicators.

🤖 Machine Learning Research: Develop, benchmark, and validate healthcare prediction models.

📉 Statistical Testing: Analyze the significance of lifestyle or demographic risk factors.

📂 File Information

Format: CSV (comma-separated)

Structure: One record per patient

Content: Demographic, lifestyle, medical, and target variables

🔍 Attribution

This dataset was generated using statistically inspired methods based on clinical and public health literature. All entries are synthetic, ensuring privacy protection while maintaining realistic distributions suitable for healthcare AI applications.

For more information see here

Child Health Profiles provide a snapshot of child health and well-being for each local authority in England using key health indicators, which enable comparison locally, regionally and nationally Source agency: Health Designation: Official Statistics not designated as National Statistics Language: English Alternative title: Local Authority Child Health Profiles

This dataset, titled "Federated Health Records for Privacy-Preserving AI Research," is a healthcare dataset designed to support research and experimentation in Federated Learning (FL) and Homomorphic Encryption (HE) for secure artificial intelligence applications.

Each record represents a simulated patient's health profile, including key features such as age, BMI, blood pressure, glucose and insulin levels, physical activity, and diet quality. The dataset is partitioned by client_id, simulating data distributed across multiple hospitals or mobile devices, where direct data sharing is restricted due to privacy concerns.

The target variable, risk_of_diabetes, is a binary indicator derived from a logistic function applied to health metrics, helping researchers model classification tasks in a privacy-aware environment.

💡 Key Features Federated-ready: Labeled by client_id to simulate decentralized data sources.

Privacy-focused: Supports homomorphic encryption-based model updates.

Flexible use: Suitable for classification, secure model aggregation, and robustness testing.

Health Profile of Kurrum

Statistics Canada's Health Profile features community-level data from a number of sources including Statistics Canada's health surveys, administrative data, and the census of population.

The virtual R/Pharma Conference is happening this week! To celebrate, we're exploring Patient Risk Profiles. Thank you to Jenna Reps for preparing this data!

This dataset contains 100 simulated patient's medical history features and the predicted 1-year risk of 14 outcomes based on each patient's medical history features. The predictions used real logistic regression models developed on a large real world healthcare dataset.

Data Dictionary

patient_risk_profiles.csv

Indicators in the Sexual and reproductive health profiles have been updated with the latest data. The annual update to reproductive health indicators gives national and local data to inform planning for sexual health and contraceptive services for local populations. This includes information about inequalities such as deprivation, age and sex where this is available. These data are intended for use by local government and health service professionals. 

This release updates indicators relating to: 

• contraceptive prescribing for 2023
• hospital admissions related to fertility for the year ending March 2024

The data for contraceptive prescribing and hospital admissions related to fertility have also been revised for the previous year to account for updates to population estimates.

Characteristics include: well-being, health conditions, health behaviours, health system, accessibility, environmental factors, deaths by cause, life expectancy, personal resources, living and working conditions, community characteristics. Includes counts and rates, high and low 95% confidence intervals, coefficient of variation, significance vis-a-vis Canada, province, peer group rate, and previous reference period.

This app has one page for each geography type, navigated using an "Other geographies" menu.For more information about the Community Health Profiles data initiative, please see the initiative homepage.

This table contains 93984 series, with data for years 2002 - 2002 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Prince Edward Island; Newfoundland and Labrador; Nova Scotia ...), Age group (4 items: 65 years and over;25 to 64 years;15 to 24 years; Total; 15 years and over ...), Sex (3 items: Both sexes; Females; Males ...), Mental health and well-being profile (89 items: Total population for the variable major depressive episode; Major depressive episode; all measured criteria are met; Major depressive episode; measured criteria not met; Major depressive episode; not stated ...), Characteristics (8 items: Number of persons; Coefficient of variation for number of persons; Low 95% confidence interval; number of persons; High 95% confidence interval; number of persons ...).

Find Massachusetts health data by community, county, and region, including population demographics. Build custom data reports with over 100 health and social determinants of health data indicators and explore over 28,000 current and historical data layers in the map room.

Health profiles for all LA areas presenting a range of indicators and a snapshot of the overall health of the local population. The Department of Health was previously responsible for the publication of Local Health Profiles. Source agency: Public Health England Designation: Official Statistics not designated as National Statistics Language: English Alternative title: Local Health Profiles