Data Sets – Nova Scotia Health Atlas

Indicator Definitions

There are four different types of indicators in the Nova Scotia Health Atlas. Scroll down below to learn more about them.

Population Data

Population data play a critical role because they capture the size, growth patterns, and characteristics of communities over time. Governments, researchers, and other organizations rely on this information to build schools, determine where to locate hospitals and clinics, define political boundaries, and allocate funding for public services. Without accurate population data, communities would struggle to anticipate future needs or monitor the social changes taking place around them.

In health research specifically, population data are indispensable. They are needed to calculate disease rates, mortality rates, and other key health indicators. You cannot know how common a health condition is without knowing how many people are at risk. Detailed demographic breakdowns by age, sex, ethnicity, income, and geographic location allow researchers to identify health disparities and pinpoint which groups are most affected by particular illnesses. This information guides the design of public health interventions, helps direct resources to underserved areas, and supports the planning of vaccination campaigns, screening programs, and emergency responses. Population data also form the backbone of epidemiological studies for tracking how diseases spread, evaluating whether health programs are working, and forecasting future healthcare demands as populations age or shift. In short, reliable population data transform raw health statistics into meaningful insights that can save lives and shape sound policy.

The NS Health Atlas includes population counts (total) by sex (female, male) for the following age categories: 0-9; 10-19; 20-34; 35-49; 50-64; 65-74; 65+; 75+. There is also an indicator for median age defined as the age that divides a population into two equal halves: exactly half of the people are younger than this age, and half are older. These data are available for all geographies.

Data source(s): Statistics Canada

Spatial resolution: Counts were provided via request for custom tabulation based on the Community Environs geography. Counts for other geographies are aggregates from the environs within them

Data preparation date: 2024

Start and end date(s): 2021

Sampling frequency: Every five years

Include the following references and acknowledgements from the use of these data: Statistics Canada. 2023. Census Profile. 2021 Census of Population. Statistics Canada Catalogue number 98-316-X2021001. Ottawa. Released November 15, 2023

Determinants of Health

The determinants of health are the many factors that influence the health of a person or the community they live in. They explain why some people stay healthy while others get sick, and why health can vary so much from one group or place to another. Health isn’t just about luck or genetics; it is shaped by a wide mix of conditions working together.

The determinants of health generally fall into a few broad categories:

Biological and genetic factors: These are the traits we inherit from our parents, along with things like age and sex. Some people are born with a higher or lower risk of certain diseases, and our susceptibility to illness changes throughout the lifecourse.

Individual behaviours and lifestyle: These are the behaviours people engage in day to day, such as diet, physical activity, smoking, alcohol use, and sleep. These behaviours can promote health or put it at risk.

Social and economic factors: These include individual, household and community conditions like income, education, employment, and the social support of family and friends. People with steady employment, a good education, and strong relationships tend to be healthier overall.

Physical environment: These include the surroundings people live and work in, including clean air and water, safe housing, neighborhood safety, and access to parks or grocery stores. A healthy environment provides the conditions for health and the ability to practice healthy behaviours.

Health care access and quality: These include indicators of access to and timeliness of medical care, including doctors, medicines, vaccines, and preventive services like checkups and screening.

Why are the determinants of health important?

The determinants of health shape health long before someone ever walks into a doctor’s office. In fact, medical care alone accounts for only a small portion of a person’s overall health. The conditions in which people live, work, and thrive often matter much more to health.

Understanding these conditions helps governments, health organizations, and communities figure out why certain health problems happen and where to focus their efforts. For example, if a neighbourhood has high rates of asthma, looking at the determinants might reveal poor air quality and older housing as the root causes. Treating patients for asthma is critical but would never deal with the reason why some neighbourhoods have higher rates of asthma than others.

By addressing determinants of health, communities (and societies more generally) can prevent disease rather than just treat it, reduce unfair health gaps between different groups, and use their resources more wisely. This bigger-picture view leads to healthier populations and a fairer system where everyone has a better chance to live a long, healthy life.

Determinants of Health in the NS Health Atlas

The NS Health Atlas includes data on several social and environmental determinants of health, including the material security score, social connectivity score, social diversity score, focus populations, air quality, access to greenness, and well water quality.

Social Determinants of Health

The social determinants of health are the conditions in which people are born, grow, live, work, and age. These conditions include income and wealth, education, employment and working conditions, housing, access to healthcare, social support networks, and exposure to discrimination or social exclusion. These determinants operate along with the wider structural forces (determinants) such as economic policies, social norms, and legal/political systems that shape the distribution of these conditions. They are fundamental to understanding variations in population health because health is powerfully shaped by the circumstances of daily life rather than by biology, healthcare or individual choice alone: the resources and opportunities available to a group determine their access to nutritious food, safe housing, education, and medical care, as well as their exposure to chronic stress and risk. Differences in these social conditions, often patterned along lines of class, race, gender, and geography, help explain the persistent and systematic health inequalities seen between and within populations, frequently accounting for gaps in disease rates and life expectancy more than healthcare access alone. Because these determinants are socially produced and unequally distributed, they reveal how health inequities are ultimately rooted in the organization of society, making social justice and fair distribution of resources central concerns for improving population health.

INDICATOR - Material Security

A summary measure of material disadvantage relative to the Nova Scotia population based on a community-level income, employment rate, education and housing. A lower score indicates a greater amount of material disadvantage. The score incorporates data from several census variables, including: living in households in need of major repair; average value of dwelling; unemployment; average individual income; receiving government transfer payments; low income measure after tax; unaffordable housing; low education level.

Data source(s): Statistics Canada, semi-custom 2021 census profiles, aggregated to Community Environs from dissemination block values.

Spatial resolution: Scores were calculated for the Community Environs geography.

Data preparation date: 2023

Start and end date(s): 2021

Sampling frequency: Every five years

Include the following references and acknowledgements from the use of these data: Saint-Jacques N, Brown P, Purcell J, Rainham DG, Terashima M, Dummer TJB. The Nova Scotia Community Cancer Matrix: A geospatial tool to support cancer prevention. Social Science & Medicine 2023; 330: 116038

INDICATOR - Social Connectivity

A summary measure of social disadvantage relative to the Nova Scotia population largely driven by marital status, single-parent families and proportion of people living alone. A lower score indicates a lesser amount of social connectivity. The score incorporates data from several census variables, including: people separated, divorced or widowed, single parent families, people living alone, but also other variables with less influence on the overall score but contributing to the indicator such as people who have moved over the past year, identify as recent immigrants, identify as a visible minority, or do not speak English or French at home.

Data source(s): Statistics Canada, semi-custom 2021 census profiles, aggregated to Community Environs from dissemination block values.

Spatial resolution: Scores were calculated for the Community Environs geography.

Data preparation date: 2023

Start and end date(s): 2021

Sampling frequency: Every five years

INDICATOR - Social Diversity

A summary measure of social diversity relative to the Nova Scotia population largely driven by factors such as the language(s) spoken at home, the population identifying as a visible minority, recent immigrants, and recent movers. A lower score indicates a lesser amount of social diversity. The score incorporates data from several census variables, including: people who have moved over the past year, people who have immigrated in the past 5-years, identify as a visible minority, do not speak English or French at home but also other variables with less influence on the overall score but contributing to the indicator such as marital status, single-parent families and proportion of people living alone.

Data source(s): Statistics Canada, semi-custom 2021 census profiles, aggregated to Community Environs from dissemination block values.

Spatial resolution: Scores were calculated for the Community Environs geography.

Data preparation date: 2023

Start and end date(s): 2021

Sampling frequency: Every five years

INDICATOR - Material and Social Deprivation

The deprivation index comprises six indicators grouped into two components, material deprivation and social deprivation. These two components point to significant socio-economic inequalities in income, education, employment and family structure. Variations in the deprivation index are closely linked to variations in health behaviours and outcomes. A lower score indicates a lesser amount of material or social deprivation. The material deprivation score incorporates census data on the following indicators: median individual income, unemployment rates, and proportion of adults with less than high school education. The social deprivation score incorporates census data on the following indicators: single parent families, people living alone, and proportion of divorced, separated or widowed adults. Note that deprivation indices are similar to measures of community socioeconomic conditions and provide a relative measure of inequity when comparing communities to the province as a whole.

Data source(s): Nova Scotia Department of Health and Wellness, derived from semi-custom 2021 census profiles, aggregated to Community Clusters from dissemination area values.

Spatial resolution: Scores were calculated for the Community Clusters geography.

Data preparation date: 2020

Start and end date(s): 2021

Sampling frequency: Every five years

Include the following references and acknowledgements from the use of these data: Terashima M, Rainham DG, Levy AR. A small-area analysis of inequalities in chronic disease prevalence across urban and non-urban communities in the Province of Nova Scotia, Canada, 2007–2011. BMJ Open 2014;4:e004459.

INDICATOR - Focus Populations

Specific demographic groups defined by shared characteristics or unique vulnerabilities to ensure that equity-seeking, at-risk, or heavily impacted communities receive tailored, effective support. Focus populations include data on several groups, including: people who lived in a different city, province, or country 1 or 5 years ago, no high school diploma, no high school diploma and greater than 65 years of age, people ages 25-64 years with no post-secondary education, median individual income, living on low income cut-off after tax, living on low income measure after tax, people ages 18-64 years living on low income measure after tax, people aged 65+ years living on low income measure after tax, employment rate among those participating in the labour force, living in subsidized housing, and renters.

Data source(s): Statistics Canada semi-custom 2021 census profiles, aggregated to Community Environs from dissemination block values.

Spatial resolution: Scores were calculated for the Community Environs geography. Values for other geographies represent averages from the Community Environs within them.

Data preparation date: 2023

Start and end date(s): 2021

Sampling frequency: Every five years

Environmental Determinants of Health

The environmental or ecological determinants of health are the physical, chemical, biological, and broader ecosystem (even planetary) conditions in which people live that shape their health and wellbeing. These determinants include air and water quality, sanitation, housing, food systems, climate, exposure to toxins or pathogens, and the stability of the natural systems (such as clean water cycles, fertile soils, and a stable climate) that human life ultimately depends on. They are fundamental to understanding variations in population health because health is not produced in isolation from the environment: the conditions surrounding a population set the baseline exposures, risks, and resources that influence who gets sick, how often, and from what. Differences in these ecological conditions help explain persistent inequalities in rates of disease, life expectancy, and wellbeing, often more powerfully than individual behaviour or medical care alone. Because these determinants operate at the collective and systemic level, often without respect to political borders, they reveal how the health of populations is bound up with the health of the ecosystems that sustain them, making environmental sustainability and health inseparable concerns.

INDICATOR - AIR QUALITY: Concentrations of fine particulate matter air pollution (PM_2.5)

The quality of the air in a particular area, specifically the degree to which it is free from pollutants and contaminants that can negatively impact human health and the environment. The data are averages of annual and monthly ground-level fine particulate matter (PM_2.5) for 2024 that combine Aerosol Optical Depth (AOD) retrievals (Dark Target, Deep Blue, MAIAC) and make use of observations from satellite-based NASA instruments (MODIS/Terra, MODIS/Aqua, MISR/Terra, SeaWiFS/SeaStar, VIIRS/SNPP, and VIIRS/NOAA20) with the GEOS-Chem chemical transport model. Values represent annual average concentrations in micrograms per cubic metre of air.

Data source(s): Atmospheric Composition Analysis Group

Spatial resolution: Annual average values were calculated for each geography from a spatial grid (0.1°x0.1°) approximately 11 km² in resolution

Data preparation date: 2024

Start and end date(s): 2024

Sampling frequency: Annual estimates

Include the following references and acknowledgements from the use of these data: Shen, S. Li, C. van Donkelaar, A. Jacobs, N. Wang, C. Martin, R. V.: Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning. (2024) ACS ES&T Air. DOI: 10.1021/acsestair.3c00054

INDICATOR - AIR QUALITY: Annual mean nitrogen oxide emissions (NO_x)

The quality of the air in a particular area, specifically the degree to which it is free from pollutants and contaminants that can negatively impact human health and the environment. The TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite measures tropospheric nitrogen dioxide vertical column densities (VCDs) daily. Researchers use annual mean NO₂ columns to track urban NO_x emission trends, identify industrial or agricultural hotspots, and evaluate bottom-up emission inventories.Values represent annual average flow rate of nitrogen oxides emitted per second.

Data source(s): Atmospheric Composition Analysis Group

Spatial resolution: Annual average values were calculated for each geography

Data preparation date: 2024

Start and end date(s): 2024

Sampling frequency: Annual estimates

Include the following references and acknowledgements from the use of these data: Rey-Pommier A, Héraud A, Chevallier F, Ciais P, Christoudias T, Kushta J, and Sciare J. Global gridded NOx emissions using TROPOMI observations. Earth System Science Data 2025; 17(7): 3329–3351. https://doi.org/10.5194/essd-17-3329-2025

INDICATOR - AIR QUALITY: Annual mean nitrogen dioxide concentrations (NO₂)

The quality of the air in a particular area, specifically the degree to which it is free from pollutants and contaminants that can negatively impact human health and the environment. Vertical column density NO₂ measurements from the Aura Ozone Monitoring Instrument (OMI) were employed to develop a land-use regression model and single-year gridded estimates of NO₂ at a resolution of 0.1°x0.1°.

Data source(s): Canadian Urban Environmental Health Research Consortium (CANUE)

Spatial resolution: Annual average values gridded values (0.1°x0.1°) were calculated for each geography OR approximateLY 11 km2 in spatial resolution.

Data preparation date: 2025

Start and end date(s): 2018

Sampling frequency: Annual estimates

Include the following references and acknowledgements from the use of these data: Larkin A, Anenberg S, Goldberg D, Mohegh A, Brauer M, Hystad P. A global spatial-temporal land use regression model for nitrogen dioxide air pollution. Frontiers in Environmental Science 2025; 11: https://doi.org/10.3389/fenvs.2023.1125979.

INDICATOR - AIR QUALITY: Potential for radon in indoor air or risk of radon exposure

Radon (Rn) is a naturally occurring, colourless and odourless gas that is radioactive and known to cause lung cancer. It is the second leading cause of lung cancer after smoking and the leading cause of the disease among nonsmokers. Radon is generated naturally from the radioactive decay of uranium. Radon potential is determined using airborne gamma-ray spectrometric data, data on bedrock geology layer show the distribution rock units and potential to produce Rn, and estimates of the permeability of the surface material to incorporate Rn mobility characteristics, a factor deemed very important in allowing Rn to travel through the soil to reach a building’s foundation. Collectively these unweighted datasets produce data depicting Rn potential score (Rn Score). Scores are classified into tertiles where 1 = lower potential, 2 = moderate potential, and 3 = higher potential.

Data source(s): Nova Scotia Department of Natural Resources

Spatial resolution: Original data, 250 m x 250 m resolution; values averaged to health atlas geographies and categorized into radon potential scores

Data preparation date: 2025

Start and end date(s): 2025

Sampling frequency: Unknown

Include the following references and acknowledgements from the use of these data: O’Reilly GA, Goodwin TA, McKinnon JS, Fisher BE. Potential for Radon in Indoor Air in Nova Scotia. Nova Scotia Department of Natural Resources, Mineral Resources Branch, Halifax, Nova Scotia. https://novascotia.ca/natr/meb/download/dp486.asp

INDICATOR - GREENNESS: Population-weighted value of normalized difference vegetation index (NDVI)

Values range from 0 (least green) to 1 (most green). The NDVI is the difference between near-infrared (NIR) and red reflectance from the Earth’s surface, divided by their sum and reflects chlorophyll production in healthy photosynthesizing plants and trees. Values range from between -1 to 1 with values below 0 associated with water and values above 0 reflecting increasing amounts of greenness.

Data source(s): Landsat 8 and 9 via Google Earth Engine (GEE) platform

Spatial resolution: Original data, 30 m x 30 m resolution; values averaged to health atlas geographies and weighted according to dissemination block face population data

Data preparation date: 2025

Start and end date(s): May 1 – September 30, 2025

Sampling frequency: To be determined.

Include the following references and acknowledgements from the use of these data: Fendereski F, Rainham DG. Developing Heat Vulnerability Index for Nova Scotia. Report for the Department of Health and Wellness and the NS HeatADAPT project. 2026.

INDICATOR - Well Water Indicators

The well water indicators include the number of private wells or wells that are privately owned and supplying domestic potable water to a household. Included are values that provide a count of wells by area and the count as a proportion of the number of households. Indicators of private well water quality include estimated high-hazard areas for manganese, arsenic, and uranium. These are naturally occurring contaminants that are picked up by groundwater flow through rock and sediment and can occur in private well drinking water. Higher values indicate greater community exposure to these contaminants in drinking water from private wells. More information on well water testing.

Data source(s):
Arsenic in well water
Uranium in well water
Manganese in well water
Civic points using well water

Spatial resolution: 1:500 K (higher resolution sampling and bedrock geology in some areas but defaulting to lowest resolution).

Data preparation date: 2021

Start and end date(s): Arsenic: 1954 to 2016, Uranium: 1954 – 2020.

Sampling frequency: N/A. Where time series were available, the most recent sample from each unique sampling location (i.e., well) were used in the risk mapping approach.

Include the following references and acknowledgements from the use of these data: Kennedy G, Department of Natural Resources and Renewables, January, 2021.

Health Behaviours in the NS Health Atlas

The NS Health Atlas includes data on health behaviours, specifically currently smoking behaviours. While other health behaviours are of interest, developing estimates of health behaviours at small-area scales requires investment in research, time, and related expertise. Estimates of smoking behaviours for Nova Scotia were generated as part of a research project supported by the Lung Association of Nova Scotia and PEI using data from the Canadian Community Health Survey.

Understanding smoking and smoking-related behaviours is essential for protecting and improving public health, since smoking remains one of the leading causes of preventable illness and death worldwide. Looking at how smoking rates differ across small local areas, rather than just at the national or regional level, helps reveal pockets where people are most at risk and where the harms of smoking are concentrated. This kind of detailed, local information allows health officials to design interventions that are tailored to the specific needs of each community, such as targeted quit-smoking programs or education campaigns. It also supports smarter use of limited healthcare resources by directing funding, staff, and services to the communities that need them most. Paying attention to small-area variations in smoking behaviour helps ensure that public health efforts reach the right people in the right places, leading to better outcomes for the whole population.

INDICATOR - Smoking behaviours

The percentage of the population aged 12 and older who report being current smokers on either a daily or occasional basis, former smokers, or exposed to second-hand (environmental) smoke. Second-hand smoke is a toxic mixture of two forms of smoke from burning tobacco products: sidestream smoke (smoke released directly into the air from the burning end) and mainstream smoke (the smoke exhaled by the smoker); former smokers include individuals who have smoked at least 100 cigarettes in their lifetime (includes former and occasional smokers) but report not smoking at all at the time of the survey; current smokers include Individuals aged 12 and older who have smoked at least 100 cigarettes in their lifetime and who currently smoke on either a daily or occasional (non-daily) basis. Values are estimates of prevalence and include credible intervals. Areas with higher-than-average prevalence are identified using a measure of exceedance probability and displayed with hatching patterns. Exceedance probabilities provide a measure of confidence that the estimated prevalent rate is higher or lower than that of the provincial average as measured over the period of 2011 to 2020. Areas with an exceedance probability of 80% or higher (i.e., 0.8) are considered to have a significantly higher-than-average prevalence; areas with an exceedance probability of 20% or lower (i.e., 0.2) are considered to have significantly lower-than-average prevalence of smoking.

Data source(s): Canadian Community Health Survey, Statistics Canada

Spatial resolution: Rates calculated for community environs.

Data preparation date: 2025

Start and end date(s): 2011-2020

Sampling frequency: To be determined.

Include the following references and acknowledgements from the use of these data: Rainham DG & Saint-Jacques N. Community-level estimation of smoking behaviour prevalence in Nova Scotia. Unpublished manuscript. August 2026.

Health Outcomes in the NS Health Atlas

The NS Health Atlas includes data on health outcomes, specifically on cancer types where prevention efforts can make a difference in Nova Scotia . While other health outcomes are of interest (e.g., chronic diseases), developing estimates of health outcomes at small-area scales requires investment in research, time and related expertise. Estimates of high-cost healthcare use were generated as part of a research project supported by the Province of Nova Scotia. Estimates of cancer rates for Nova Scotia were generated as part of a research project supported by Research Nova Scotia through the former Establishment Grants program.

High-cost Healthcare in Nova Scotia

Most of what we spend on public healthcare in Nova Scotia is on the treatment of a small percentage of patients living with several serious, long-term health problems at once. These patients have many complex chronic health conditions. When the healthcare system does not effectively meet their needs, it results in poor health outcomes and expensive contact with the healthcare system. Healthcare costs are a function of access to, and coordination of, alternate levels of care services to support discharge from hospitals. Poor access to alternate levels of care services may delay discharge, resulting in higher costs. Poor outcomes following discharge may also lead to repeat hospitalizations.

One useful way to tackle this issue is to compare different communities to see where these high rates of costly care show up most. Spotting these differences helps us focus our efforts where they’ll do the most good. Targeting the right places with the right solutions will help to lower costs and help patients stay healthier. Finding better ways to care for this group of patients would go a long way toward keeping the province’s healthcare system financially sustainable.

INDICATOR - High-cost healthcare use

This indicator represents the top 5% of health (physician + inpatient hospital) costs. Estimates are based on average annual cost for Nova Scotian residents aged 30 years and older between 2015-17. % Difference vs. Provincial Average is the percentage difference in healthcare costs compared to the provincial average; the % Difference Accounting for Age is the percentage difference in healthcare costs compared to the provincial average accounting for age and gender of the population; the % Difference Accounting for Age and Condition is the percentage difference in healthcare costs compared to the provincial average accounting for age, gender, and the underlying health conditions of the population.

Data source(s): Discharge Abstract Database; National Household Survey Database; Statistics Canada Population Census Data

Spatial resolution: Rates calculated for Community Clusters and Health Networks

Data preparation date: 2022

Start and end date(s): 2015-2017

Sampling frequency: To be determined.

Include the following references and acknowledgements from the use of these data: Kephart G, Asada Y, Atherton F, Burge F, Campbell LA, Campbell M, Dowling L, Dyer J, Lawson B, Lethbridge L, Levy A, Terashima M. 2016. Small area variation in rates of high-cost healthcare use across Nova Scotia. Maritime SPOR SUPPORT Unit. Halifax, Nova Scotia.

Relative Risk of Cancer in Nova Scotia

Understanding small-area variations in cancer outcomes is essential for protecting and improving public health. This is because up to 50% of all cancers diagnosed are thought to be preventable because they are often caused by risk factors that can be changed or avoided– with the right support. Some of these factors are things that we eat, drink, whether we are physically active, maintain a healthy body weight, can access and afford healthy food or even, are able access and participate in cancer screening programs. When we look at how the rates of cancer differ across small local areas, rather than solely relying on national or provincial levels, we can uncover important differences in rates that would otherwise be ‘averaged out’ over the larger areas. This detailed, ‘community-level’ information helps health officials understand not only how the risk of cancer varies across the province, but who is being affected and possibly, why–which is often tied to differences in income, environment, and access to care. With this knowledge, health decision-makers, clinicians and health promoters can design targeted interventions like local screening drives or awareness campaigns and direct limited healthcare resources to the communities that need them most. In short, paying close attention to small-area variations in cancer risk helps ensure that prevention efforts and treatment efforts reach the right people in the right places, leading to fairer and better health outcomes for everyone.

INDICATOR(S) - Relative risk of cancer

The posterior predictions and associated 95% credible intervals of the median relative risk (RR) estimates at the Community Environs level, using cancers diagnosed between 2014-2017 (most recent data available at time of analyses). Here, RR measures how the rate of cancer in an area compares to that of the average provincial rate measured over 2001-2017. The Exceedance probabilities provide a measure of confidence that the estimated community-specific risk is higher or lower than that of the provincial average. Areas with a RR greater than 1 and an exceedance probability of 80% or higher (i.e., 0.8) are considered to have a significantly higher-than-average cancer rate; areas with RR smaller than 1 and an exceedance probability of 20% or lower (i.e. 0.2) are considered to have significantly lower-than-average cancer rate.

Cancer types reported: all cancers were invasive first primary diagnosed in Nova Scotia residents including with: bladder– including in situ (bladder; C67), female breast (breast; C50), cervix uteri (cervix; C53), colorectal (C18–C20, C26.0), head and neck (C00–C14, C30-C32.9), liver (C22.0, C22.1), lung and bronchus (lung; C34), melanoma of the skin (melanoma; C44 (type 8720–8790)), pancreas (C25), and stomach (C16). Case selection followed the multiple primary rules established by the International Agency for Research on Cancer (IARC),and disease coding followed the standards of the World Health Organization International Classification of Disease for Oncology (ICD-O). Cases diagnosed between 2014 and 2017 were aggregated over the 2016 census period. Rates for Nova Scotia (i.e. referent population) were derived from cases diagnosed between 2001-2017. Data, including, sex at birth, age at diagnosis and spatial location at time of diagnosis, were accessed from the NS Cancer Registry for research purposes following an application to the NS Health (NSH) Data Access Committee and Research Ethics Board (REB # 1023913).

Geroreferencing: 90% of cases were assigned to one of 301 Community Environs using residential civic addresses at the time of diagnosis; 10% were assigned using postal codes.

Population at risk: Population counts from semi-custom files aggregating population from dissemination-block to COMe were obtained from Statistics Canada census 2001, 2006, 2011 and 2016. The data were used to determine population at risk by sex and age and over time.

Data source(s): Nova Scotia Cancer Registry, Nova Scotia Health Cancer Care Program.

Spatial resolution: Rates calculated for Community Environs

Data preparation date: 2025

Start and end date(s): 2001-2017

Sampling frequency: To be determined.

Include the following references and acknowledgements from the use of these data: Saint-Jacques N, Purcell J, Brown PE, Rainham DG, Dummer TJB. Small-area spatio-temporal analysis of cancer risk to support effective and equitable cancer prevention. PLOS One 2025; https://doi.org/10.1371/journal.pone.0325523