Tools and datasets
Cardiovascular disease
A DNA methylation-based blood test to assess lifetime tobacco smoking exposure.
Period of tool development: 2020 – 2024
Contact: Professor Greg Jones, University of Otago,
Available for use by others: Yes
Note: The research team published a comprehensive methods paper which describes the development, validation (with expensive and technically challenging techniques) and utility of this novel smoking-related DNA methylation marker:
Fitzgerald S, Bhat B, Print C & Jones GT 2024. A validated restriction enzyme ddPCR cg05575921 (AHRR) assay to accurately assess smoking exposure. Clinical Epigenetics. 2024;16(1):45 https://doi.org/10.1186/s13148-024-01659-1
Interviews and focus groups with whānau and health provider participants from the Manawataki Fatu Fatu for ACCESS project, a Māori and Pacific-led program of research aiming to achieve equity in CVD care and outcomes.
Period of data collection: 2021 – 2024
Contacts: Dr Corina Grey, Ministry of Pacific Peoples, Associate Professor Matire Harwood, University of Auckland,
|
Ethics approval to share data? |
N |
|
De-identified participant data that could be shared with a third party? |
N |
|
Available in a public repository? |
N |
The DNA methylation values (generated using Illumina EPIC arrays) for 1100 participants of the MENZACS cohort.
Period of data collection: 2018 – 2024
Contact: Professor Robert Doughty, University of Auckland,
|
Ethics approval to share data? |
N |
|
De-identified participant data that could be shared with a third party? |
N |
|
Available in a public repository? |
N |
Diabetes and prediabetes
Data and biological samples from the 6-month Food 4 Health longitudinal intervention and 3-month follow up factorial design randomised controlled trial (total n=152).
Repeated measures (baseline, 3 months, 6 months and 9 months):
- survey data – physical activity (Stanford Leisure-Time activity categorical Item (L-Cat 2.2), smoking, alcohol intake, mental health (Depression Anxiety Stress Scale (DASS-21), Short-form health survey version 2 for New Zealand/Australia (SF36v2) 3 day food diaries
- clinical data – weight, BMI, blood pressure, HbA1c, fasting glucose, HOMA-IR, lipids
- medication use
- blood and faecal samples biobanked for future unspecified research.
Period of data collection: 2017 – 2020
Contact: Professor Jeremy Krebs, University of Otago, Wellington,
|
Ethics approval to share data? |
Yes |
|
De-identified participant data that could be shared with a third party? |
No |
|
Available in a public repository? |
No |
Note: Study interventions, data, sample collections and timelines are specified in the published methods paper:
Barthow, C., Hood, F., McKinlay, E. et al. Food 4 Health - He Oranga Kai: Assessing the efficacy, acceptability and economic implications of Lactobacillus rhamnosus HN001 and β-glucan to improve glycated haemoglobin, metabolic health, and general well-being in adults with pre-diabetes: study protocol for a 2 × 2 factorial design, parallel group, placebo-controlled randomized controlled trial, with embedded qualitative study and economic analysis. Trials 20, 464 (2019). https://doi.org/10.1186/s13063-019-3553-7
An existing dietary multistate lifetable model developed to assess the health, health system and equity impacts of dietary policy in New Zealand, was modified to model interventions and policies in the New Zealand prediabetic population. The model was populated with population numbers, risk factor distributions and disease rates for the NZ prediabetic population. Full methodological details are available in the technical report:
Period of tool development: 2018 – 2019
Contact: Dr Cristina Cleghorn, University of Otago, Wellington,
Available for use by others: A version of this tool will be available to use in future projects, through collaboration with Dr Cleghorn.
Equitable health outcomes
The Framework for Effective and Equitable Implementation in Aotearoa (FrEEIA) is a framework to assist with the development of an equitable implementation plan for a new or existing health intervention.
Period of tool development: 2022 – 2024
Available for use by others: The Implementation Science Aotearoa website will house the framework and user guide (website address TBC).
The FrEEIA readiness assessment tool is designed to help a team planning the implementation of a new intervention. The ‘readiness assessment’ process can help ensure that organisations, teams and individuals are able to implement the intervention effectively and equitably. The tool can also be used again in the evaluation stage after implementation.
Period of tool development: 2022 – 2024
Available for use by others: The Implementation Science Aotearoa website will house the readiness assessment tool and user guides (website address TBC).
The He Pikinga Waiora (Enhancing Wellbeing) Implementation Framework is a tool for funders, health services and community organisations to plan, implement and assess health interventions. The framework is centred on kaupapa Māori (Indigenous knowledge, methods and philosophy) and integrates best practice from international research, particularly emphasising community engagement through participatory co-design approaches.
Period of tool development: 2016 – 2019
Available for use by others: A toolkit of resources to help put the HPW framework into action is available at this website: https://www.hpwcommunity.com/
Healthy food environments
An excel-based optimisation tool, based on the food groups from the 2008/09 adult national nutrition survey which allows optimisation of the average dietary intake for Māori females, Māori males, non-Māori females and non-Māori males based on: GHG emissions, food costs, food based dietary guidelines and 23 nutrient guidelines.
Period of tool development: 2020 – 2021
Available for use by others: This would require collaboration with Dr Cleghorn.
Survey responses from 2526 staff and 261 visitors to New Zealand healthcare facilities to questions about the National Healthy Food and Drink Policy, their food and drink purchasing behaviours, and satisfaction with the food environment.
Period of data collection: 2021 – 2022
Contact: Professor Cliona Ni Mhurchu, University of Auckland,
|
Ethics approval to share data? |
Could be sought |
|
De-identified participant data that could be shared with a third party? |
Could be sought |
|
Available in a public repository? |
No |
Organisation with interest in use of dataset: National Institute for Health Innovation, University of Auckland
A searchable digital database of packaged food and drink products that classifies items as Green, Amber or Red in line with the 2019 version of the National Healthy Food and Drink Policy.
Period of tool development: 2020 – 2024
Available for use by others: Open to requests
Contact: Dr Magda Rosin, University of Auckland,
Organisation with interest in use of tool: National Institute for Health Innovation, University of Auckland
Nutrition information, product size, and promotional information for 8485 food and drinks available in New Zealand healthcare facilities, and their classification as Green, Amber or Red according to the 2019 version of the National Healthy Food and Drink Policy.
Period of data collection: 2021 – 2022
Contact: Professor Cliona Ni Mhurchu, University of Auckland,
|
Ethics approval to share data? |
Could be sought |
|
Available in a public repository? |
No |
Organisation with interest in use of dataset: National Institute for Health Innovation, University of Auckland
A digital tool to collect detailed food and drink data in a range of food settings (vending machines, staff canteens, and other food retail outlets). Contains an algorithm that classifies food and drink items as Green, Amber or Red in line with the 2019 version of the National Healthy Food and Drink Policy.
Period of tool development: 2020
Available for use by others: Open to requests
Contact: Professor Cliona Ni Mhurchu, University of Auckland,
Organisation with interest in use of tool: National Institute for Health Innovation, University of Auckland
A tool to assess organisational food and drink policies across three domains: (1) nutrition standards, (2) promotion of a healthy food and drinks environment, and (3) policy communication, implementation and evaluation.
Period of tool development: 2020
Available for use by others: Open to requests
Contact: Professor Cliona Ni Mhurchu, University of Auckland,
Organisation with interest in use of tool: National Institute for Health Innovation, University of Auckland
Insights from 19 hospital food providers, National DHB Food and Drink Environments Network members, and government representatives who were interviewed regarding the National Healthy Food and Drink Policy.
Period of data collection: 2022 – 2023
Contact: Dr Magda Rosin, University of Auckland,
|
Ethics approval to share data? |
Could be sought |
|
De-identified participant data that could be shared with a third party? |
Could be sought |
|
Available in a public repository? |
No |
Organisation with interest in use of dataset: National Institute for Health Innovation, University of Auckland
Healthy lifestyles
The OL@-OR@ app is a culturally-tailored mHealth tool designed with Māori and Pasifika communities in New Zealand to support healthy lifestyles and reduce risks of heart disease, obesity, and diabetes:
- Information website: https://www.ola-ora.co.nz
- Desktop version: https://olaora.auckland.ac.nz/
- Google Play: https://play.google.com/store/apps/details?id=nz.co.uniservices.olaora&hl=en
Appstore: https://apps.apple.com/nz/app/ol-or/id1278777039
Period of tool development: 2018 – 2019
Contact: Professor Cliona Ni Mhurchu, University of Auckland,
Available for use by others: OL@-OR@ is freely available until June 2025.
Organisation with interest in use of tool: National Institute for Health Innovation, University of Auckland
Healthy physical activity environments
The Getting Around Survey was undertaken with two case study communities (a social housing community and a private retirement village) and ‘control’ locations (social housing residents and older people living in the community) in 2021, 2022 and 2023.
The data includes responses to questions about travel patterns, getting around, wellbeing, financial constraints, access and use of shared modes of trsnsport, as well as demographic data.
This dataset is a repeated cross section with a nested longitudinal sample. 2021 (n=532); 2022 (n=368); 2023 (n=387).
Period of data collection: 2021 – 2023
Contact: Dr Angela Curl, University of Otago,
|
Ethics approval to share data? |
Could be sought – see note |
|
De-identified participant data that could be shared with a third party? |
Data is de-identified at the individual level but the small communities involved are likely to be identifiable. |
|
Available in a public repository? |
No |
Note: Researchers interested in working with the research team to analyse the data could be added to the ethics application, but the data cannot be freely shared with external researchers.
Te Ara Mua–Future Streets is a controlled intervention study of a neighbourhood street retrofit designed to make walking and cycling easier for Māngere residents and reflecting local cultural identity.
The Māngere Residents’ Survey was conducted face-to-face with adults and children living in Māngere Central (intervention area) and Māngere East (controlled area), in 2014, 2017, 2021 and 2023. Across the two localities approximately 2000 individuals were recruited in 2014, 2017 and 2023. In 2021 the survey was disrupted by COVID and abandoned after 687 interviews had been completed.
Survey questions include demographic variables, physical activity, mode use to different destinations, perceptions of neighbourhood safety and social cohesion. In addition, respondents were asked to wear a pedometer for 7 days to measure physical activity and in 2021 and 2023 adults were also asked to wear an accelerometer.
The ethnic composition of Māngere in 2023 was as follows: 59.4% identifying with a Pacific Island ethnic group, 19.1% European, 19% Asian, and 16.4% Māori. The ethnicities of survey respondents is consistent with population levels.
Period of data collection: 2014 – 2023
Contact: Professor Alex Macmillan, University of Otago,
|
Ethics approval to share data? |
Could be sought – see note |
|
De-identified participant data that could be shared with a third party? |
Data is de-identified at the individual level but the Māngere community is not de-identified. |
|
Available in a public repository? |
No |
Group with interest in use of dataset: the wider Māngere community
Note: Ownership of the data resides with the research team and the wider Māngere community. While the research team would welcome interest, particularly from Māori and Pasifika scholars, analyses would need to be conducted in partnership with the research team who retain a governance role with respect to the data. The dataset would not be handed over to a third party organisation.
Non-communicable diseases (general)
Code used in IDI data analysis:
A. Statistical code for manuscript: ‘What protects against pre-diabetes progressing to diabetes? observational study of integrated health and social data’. (2019)
B. Shared statistical code from the study: ‘Living in areas with different levels of earthquake damage and risk of cardiovascular disease: a cohort-linkage study’. (2017)
Disclaimer: This code is not official statistics. It has been created for research purposes in the IDI which is carefully managed by Stats NZ. For more information about the IDI please visit https://www.stats.govt.nz/integrated-data/.
Contributors: Data was provided by Statistics New Zealand.
Links to code:
A. https://hdl.handle.net/10523/9726
B. https://vhin.co.nz/guides/shared-code/
Period of code development: 2016 – 2019
Contact: Dr Andrea Teng, University of Otago,
Note: Data is restricted but code is freely available online at links above.
This dataset contains the SAS statistical code used in the manuscript: ‘How does the level of functional impairment vary in individuals with non-communicable disease and comorbidity? Cross-sectional analysis of linked census and administrative data’.
It includes one SAS program written by Andrea Teng for use in the Statistics New Zealand Integrated Data Infrastructure (IDI). The code was run on a historic refresh and may need to be updated to run in subsequent IDI refresh. All records have been checked via output checking process.
Disclaimer: This code is not official statistics. It has been created for research purposes in the IDI which is carefully managed by Stats NZ. For more information about the IDI please visit https://www.stats.govt.nz/integrated-data/.
Contributors: Data was provided by Statistics New Zealand.
Period of code development: 2022 – 2023