Context

In October 2021 the World Health Organization (WHO) published an article about how Mental Health services have been pushed to the limit during the COVID-19 pandemic while stating that the next pandemic will be on mental health encouraging governments to increase their expenditure on Mental Health.

While searching for Mental Health service usage and expenditure in New Zealand we found that the information is spread in several excel spreadsheets from 2002 to 2020 with different sources, formats, and accessibility.

We then proceeded to gather some of the information provided by the New Zealand Ministry of health into 3 datasets that summarise the usage of these services in the last 20 years.

Inspiration

The main inspiration for this dataset was to find a way of building a continuous pipeline for future reference of Mental Health Service usage in New Zealand.

Our first approach was to match Government Expenditure and usage of Mental Health Services in NZ over the last years but finding information about specific government expenditure is hard to come by, So we decided to focus mostly in creating a solid dataframe about mental health service usage over the years.

Data Sources

Ministry of Health New Zealand

This data source was chosen for its ease of access and ability to web scrape.

Datasets were available from three sources: 1) Datasets from 2002 to 2008 2) Dataset of 2010 3) Dataset from 2011 to 2020

3 different crawlers were developed in order to maintain consistency over sources. Datasets from 2011 onwards are displayed in the ministry of health new Aggregated Data Site..

Datasets from 2002 were gathered from legacy sources on the list of reports by the ministry of health

The data provided in this data sets can be classified into 3 groups:

1) NZ Mental Health services usage by gender, age and ethnicity. 2) NZ Mental Health service usage by DHB's (District Health boards) 3) NZ Metal Health service usage by Service provided.

"Data is sourced from the Programme for the Integration of Mental Health Data (PRIMHD). PRIMHD contains Ministry of Health funded mental health and addiction service activity and outcomes data. The data is collected from district health boards (DHBs) and non-governmental organisations (NGOs).

PRIMHD data is used to report on what services are being provided, who is providing the services, and what outcomes are being achieved for health consumers across New Zealand's mental health sector. These reports enable better quality service planning and decision making by mental health and addiction service providers, at local, regional and national levels."

We have combined the data in the excel files provided by the MOH into a single data frame.

Intention of usage.

The idea behind the project is to have an incremental dataset for past and future reference, allow ease of access to timeseries information and better visibility.

Problems while gathering data.

We will divide the problems while gathering information into 2 categories: Downloading and Wrangling.

Downloading

The ministry of health releases an anual report on Mental Health since 2002, this reports are uploaded to the stats page of the Ministry of Health's website.

Reports from 2002 to 2007 have an aggregated site where they can be downlaoded programmatically. Reports from 2008 and 2010 have their individual site and had to be added manually to the download process. Reports from 2011 onwards have their own Mental Health page where they get uploaded every year. This website allows us to make incremental updates to the current dataset.

This 3 types of published papers required individual processes to download programmatically, 2 of them were scrapped from lists, and 1 of them manually added to the dataset.

While developing the download process for reports from 2011 we also find that some links were broken or required manual intervention, this had to be solved with exceptions for different years.

We developed parsers for this matter and expect changes in the future that can be solved by adding simple exceptions to new years given that they change, which at this stage is uncertain.

For the scraping part of the project we used R's rvest library.

Wrangling

The reports published by the Ministry of Health are given in excel format. R's tidiyverse and readxl libraries were used.

These reports are given in multi sheet excel files that have changed considerably over the years and had to be solved with individual parsers.

For this we...

In a survey about wellbeing and wellness issues for organizations in New Zealand conducted in March 2020, ** percent of respondents said that it was an important diversity issue. This represents a decrease from the previous year's result.

NZ: External Health Expenditure Per Capita: Current PPP data was reported at 0.000 Intl $ mn in 2015. This stayed constant from the previous number of 0.000 Intl $ mn for 2014. NZ: External Health Expenditure Per Capita: Current PPP data is updated yearly, averaging 0.000 Intl $ mn from Dec 2000 (Median) to 2015, with 16 observations. NZ: External Health Expenditure Per Capita: Current PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s New Zealand – Table NZ.World Bank: Health Statistics. Current external expenditures on health per capita expressed in international dollars at purchasing power parity (PPP). External sources are composed of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;

Percentage of the population with self-reported mental health outcomes of anxiety, bipolar and depression for Statistical Area 2 (2018) units. Original data sourced from Census 2018 and New Zealand Health Survey 2017/18 and 2018/19. Data provided are synthetic data produced from spatial microsimulation modelling.

New Zealand NZ: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data was reported at 100.000 % in 2015. This stayed constant from the previous number of 100.000 % for 2014. New Zealand NZ: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data is updated yearly, averaging 100.000 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 100.000 % in 2015 and a record low of 100.000 % in 2015. New Zealand NZ: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s New Zealand – Table NZ.World Bank: Health Statistics. The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households. This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; Weighted average;

These datasets are concordance files that link the Geographic Classification for Health (GCH) to statistical geographies and geographic units commonly used in health research and analysis in Aotearoa New Zealand (NZ). More information about the develppment of the GCH is available in our Open Access publication. Our long-term aim is the comprehensive and accurate understanding of urban-rural variation in health outcomes and healthcare utilization at both national and regional levels. This is best achieved by the widespread uptake of the GCH by health researchers and health policy makers. The GCH is straightforward to use and most users will only need the relevant concordance file.
Statistical Area 1s (SA1s, small statistical areas which are the output geography for population data) were used as the building blocks for the Geographic Classification for Health (GCH) and are the preferred small areas when undertaking the analysis of health data using the GCH. It is however appreciated that a lot of health data is not available at the SA1 level and GCH concordance files are also available for Domicile (Census Area Units, CAU) and Statistical Area 2s (SA2) and Meshblock. The following concordance files are available in excel format:

SA12018_to_GCH2018.csv This concordance file applies a GCH category to each SA1 in NZ SA22018_to_GCH2018.csv This concordance file applies a GCH category to each SA2 in NZ MoH_HDOM_to_GCH2018.csv This concordance file applies a GCH category to each Domicile in NZ. Please read the additional information below if you plan to use this concordance file. MoH_MB_to_GCH2018.csv This concordance file applies a GCH category to each Meshblock in NZ. Please read the additional information below if you plan to use this concordance file.

Additional information relating to geographic units used by the Ministry of Health:

MoH_HDOM_to_GCH2018.csv This file has been designed specifically to add GCH to the Ministry of Health (MoH) datasets containing Domicile codes. Use this file if your dataset contains only Domicile codes. If your dataset also contains Meshblock codes, then use the MoH Meshblock to GCH concordance file. This file includes 2006 and 2013 domicile codes. The 2013 domiciles are still current as of 2022, and this file will still work well with data outside those years. Domicile boundaries do not align well with SA1 boundaries, and longitudinal health data usually contains some older Domiciles which have been phased out and replaced with multiple smaller Domiciles. These deprecated Domiciles may overlap multiple SA1s. Usually, all such SA1s belong to the same GCH category. Occasionally, a Domicile will overlap more than one GCH category. When this happens, we have assigned the GCH category to which the majority of people living in that Domicile belong. By necessity, this will allocate a minority of people in those Domiciles to a GCH category to which they do not belong.
MoH_MB_to_GCH2018.csv This file has been designed specifically to add GCH to Ministry of Health (MoH) datasets containing Meshblock codes. This file includes 2018, 2013, 2006, and 2001 Meshblock codes, but will still work well with data outside those years. Meshblock boundaries from census 2018 fit perfectly and completely within the Statistics New Zealand Statistical Area 1s (SA1) boundaries on which GCH is based. However, longitudinal health data usually contains some older Meshblocks which have been phased out and replaced by multiple smaller Meshblocks. These deprecated Meshblocks may overlap multiple SA1s. Usually, all such SA1s belong to the same GCH category. Occasionally, a Meshblock will overlap more than one GCH category. When this happens, we have assigned the GCH category to which the majority of people living in that Meshblock belong. By necessity, this will allocate a minority of people in those Meshblocks to a GCH category to which they do not belong.

Te mauri o te rakau, te mauri o te ngahere, te mauri o te tangata: Mātauranga Māori based solutions for kauri dieback and myrtle rust

Māori worldviews are essential for establishing priorities and allowing the co-production of knowledge in response to threats to taonga rākau (treasured tree) species.

In the fight against kauri dieback and myrtle rust, Māori have been seeking solutions that call on their knowledge systems and understandings of the physical and meta-physical elements of the universe. This includes solutions embedded in the spiritual dimensions of this knowledge, that are vital to the protection and enhancement of the natural environment. These are often overlooked, or at worst subjugated, by conventional environmental management practices and the science knowledge that underpins its decision-making.

This is a suite of kaupapa Māori projects that aim to restore the collective health of trees, forests and people. The team will do this by connecting to, and resourcing, Māori communities and their environmental knowledge holders to explore solutions embedded in mātauranga Māori (Māori knowledge).

These projects are unashamedly indigenous and will collectively show how mātauranga-led research can contribute to contemporary biosecurity issues, while addressing the aspirations of Māori and their communities.

Theme Co-leads:

• Melanie Mark-Shadbolt, Te Tira Whakamātaki

• Valance Smith, Auckland University of Technology

Dataset for the maps accompanying the Housing in Aotearoa New Zealand: 2025 report. This dataset contains data for severe housing deprivation from the 2018 and 2023 Censuses.

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Data is available by health district.

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Severe housing deprivation has data for the census usually resident population from the 2018 and 2023 Censuses, including:

• estimated prevalence rate of severe housing deprivation (per 10,000 people)
• estimated rate for those; without shelter, in temporary accommodation, sharing someone else’s private dwelling, in uninhabitable housing, for whom it could not be determined whether they were severely housing deprived or not.

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Map shows the estimated prevalence rate of severe housing deprivation (per 10,000 people) for the census usually resident population for the 2023 Census.

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Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. 

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. 

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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Severe housing deprivation time series

The 2018 estimates of severe housing deprivation have been updated using the 2023 methodology for estimating severe housing deprivation. Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information.

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Severe housing deprivation

Figures in this map and geospatial file exclude Women’s refuge data, as well as estimates for children living in non-private dwellings. Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information.

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About the 2023 Census dataset

For information on the 2023 Census dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Census usually resident population count concept quality rating

The census usually resident population count is rated as very high quality.

Census usually resident population count – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Quality of severe housing deprivation data

Severe housing deprivation (homelessness) estimates – updated methodology: 2023 Census has more information on the data quality of this variable.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

In a survey conducted in 2021 in New Zealand, regarding the level of trust respondents had in the health system in New Zealand, below ** percent of female respondents stated that they completely trusted the health system, whereas around ** percent of male respondents stated that they completely trusted the health system. The public health system in New Zealand enables residents to have free or subsidized healthcare. A private health system is also available, in which users can still access public healthcare services.

New Zealand NZ: Current Health Expenditure: % of GDP data was reported at 9.340 % in 2015. This records a decrease from the previous number of 9.403 % for 2014. New Zealand NZ: Current Health Expenditure: % of GDP data is updated yearly, averaging 8.888 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 9.699 % in 2012 and a record low of 7.470 % in 2000. New Zealand NZ: Current Health Expenditure: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s New Zealand – Table NZ.World Bank: Health Statistics. Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;

Geospatial data about NZIMD A new set of indicators for social health. Export to CAD, GIS, PDF, CSV and access via API.

In a 2019 survey into the main reasons small business or sole employers perceive as barriers to providing staff wellbeing in New Zealand, ** percent of respondents with ** to ** employees said running a business affected mental and or or physical health. Elsewhere, ** percent of respondents with one employees said running a business affects physical and / or mental health.

New Zealand: Health spending as percent of GDP: The latest value from 2021 is 10.05 percent, a decline from 10.07 percent in 2020. In comparison, the world average is 7.21 percent, based on data from 181 countries. Historically, the average for New Zealand from 2000 to 2021 is 8.92 percent. The minimum value, 7.47 percent, was reached in 2000 while the maximum of 10.07 percent was recorded in 2020.

Contains data from World Health Organization's data portal covering various indicators (one per resource).

Methods of data collection are in the published paper and its parent (both open-access, see related works below). Briefly: Respondents were survey participants from an internet Panel survey firm. Data have been cleaned and processed: this was mostly simplifying/collapsing response options to fewer options for reporting.

ObjectivesRacism is an important health determinant that contributes to ethnic health inequities. This study sought to describe New Zealand adults’ reported recent experiences of racism over a 10 year period. It also sought to examine the association between recent experience of racism and a range of negative health and wellbeing measures.MethodsThe study utilised previously collected data from multiple cross-sectional national surveys (New Zealand Health Surveys 2002/03, 2006/07, 2011/12; and General Social Surveys 2008, 2010, 2012) to provide prevalence estimates of reported experience of racism (in the last 12 months) by major ethnic groupings in New Zealand. Meta-analytical techniques were used to provide improved estimates of the association between recent experience of racism and negative health from multivariable models, for the total cohorts and stratified by ethnicity.ResultsReported recent experience of racism was highest among Asian participants followed by Māori and Pacific peoples, with Europeans reporting the lowest experience of racism. Among Asian participants, reported experience of racism was higher for those born overseas compared to those born in New Zealand. Recent experience of racism appeared to be declining for most groups over the time period examined. Experience of racism in the last 12 months was consistently associated with negative measures of health and wellbeing (SF-12 physical and mental health component scores, self-rated health, overall life satisfaction). While exposure to racism was more common in the non-European ethnic groups, the impact of recent exposure to racism on health was similar across ethnic groups, with the exception of SF-12 physical health.ConclusionsThe higher experience of racism among non-European groups remains an issue in New Zealand and its potential effects on health may contribute to ethnic health inequities. Ongoing focus and monitoring of racism as a determinant of health is required to inform and improve interventions.

In New Zealand in 2020, the health & beauty sector saw a ** percent increase in the number of domestic online transactions compared to the previous year. The domestic online consumer spend within this sector also increased, with a *** percent rise compared to 2019.

Meta-analysis of surveys showing association between experience of racial discrimination (last 12 months) and health and wellbeing measures, stratified by ethnicity and adjusted for age, gender, nativity, NZDep, education qualification.

Wellbeing statistics: 2021 (supplementary) presents supplementary data from the 2021 General Social Survey (GSS), adding to the data released in Wellbeing statistics: 2021 in July 2022.

This statistic depicts the results of a survey conducted in December 2018 about the level of concern for the health system in New Zealand. During the survey period, around ** percent of respondents stated they were very concerned about the health system in the country.