This report presents the 2012/13 results from the New Zealand Health Survey, for both adults and children. The report includes information on health behaviours and risk factors, health conditions and access to health services. These findings update those published in 2011/12, from what is now a continuous New Zealand Health Survey.

This report provides a snapshot of the health of New Zealanders through the publication of key indicators on health behaviours, health status and access to health care for both adults and children. This report presents the 2014/15 results from the continuous New Zealand Health Survey, with comparisons to the 2011/12 and 2006/07 surveys.

Objective: The COVID-19 pandemic and associated restrictions are associated with adverse psychological impacts but an assessment of positive wellbeing is required to understand the overall impacts of the pandemic.

Methods: The NZ Lockdown Psychological Distress Survey measured excellent wellbeing categorised by a WHO-Five Well-being Index (WHO-5) score ≥22. The survey also contained demographic and pre-lockdown questions, subjective and objective lockdown experiences, and questions on alcohol use. The proportion of participants with excellent wellbeing is reported with multivariate analysis examining the relative importance of individual factors associated with excellent wellbeing.

Results: Approximately 9% of the overall sample reported excellent wellbeing during the New Zealand lockdown. Excellent wellbeing status was associated with older age, male gender, Māori and Asian ethnicity, and lower levels of education. Excellent wellbeing was negatively associated with smoking, poor physical and mental health, and previous trauma.

Conclusion: A substantial minority of New Zealanders reported excellent wellbeing during severe COVID-19 pandemic restrictions. Demographic and broader health factors predicted excellent wellbeing status. An understanding of these factors may help to enhance wellbeing during any future lockdowns.

This report presents information and key results from the mental health and problematic substance use module of the New Zealand Health Survey (NZHS).

New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Out-Patient Services: Medical data was reported at 15.200 NZD in 2016. This records an increase from the previous number of 12.200 NZD for 2013. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Out-Patient Services: Medical data is updated yearly, averaging 11.350 NZD from Jun 2007 (Median) to 2016, with 4 observations. The data reached an all-time high of 15.200 NZD in 2016 and a record low of 10.000 NZD in 2007. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Out-Patient Services: Medical data remains active status in CEIC and is reported by Statistics New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.H010: Household Economic Survey: Average Weekly Household Expenditure.

The report 'The Health of New Zealand Adults 2011/12' presents key findings about adults' health and access to health services in 2011/12. These statistics come from the New Zealand Health Survey. Results are available by sex, age group, ethnic group and neighbourhood deprivation.

In a survey conducted in 2021 in New Zealand, regarding the level of trust respondents had in the health system in New Zealand, below 20 percent of female respondents stated that they completely trusted the health system, whereas around 23 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.

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 53 percent of respondents stated they were very concerned about the health system in the country.

New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Medical Product, Appliances and Equipment: Pharmaceutical data was reported at 9.000 NZD in 2016. This records an increase from the previous number of 6.900 NZD for 2013. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Medical Product, Appliances and Equipment: Pharmaceutical data is updated yearly, averaging 6.450 NZD from Jun 2007 (Median) to 2016, with 4 observations. The data reached an all-time high of 9.000 NZD in 2016 and a record low of 5.800 NZD in 2007. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Medical Product, Appliances and Equipment: Pharmaceutical data remains active status in CEIC and is reported by Statistics New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.H010: Household Economic Survey: Average Weekly Household Expenditure.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

Five thousand four hundred and fifty-five (5450) names were randomly selected from the New Zealand electoral rolls, where 90% of eligible voters are registered. In addition, an over sample of 549 was made from the Maori Rolls in order to ensure that the Maori were adequately represented in the national sample. This resulted in a total sample of 6004.

Mode of data collection

Mail Questionnaire [mail]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

This data presents the 2017–20 regional results from the New Zealand Health Survey, for both adults and children.

Association of sociodemographic factors and experience of racism (last 12 months), from meta-analysis of multivariable logistic regression across all six surveys (NZHS and GSS).

aB-WMH, The Beijing World Mental Health Survey; CMDPSD, Comorbid Mental Disorders during Periods of Social Disruption; ESEMeD, The European Study Of The Epidemiology Of Mental Disorders; LEBANON, Lebanese Evaluation of the Burden of Ailments and Needs of the Nation; M-NCS, The Mexico National Comorbidity Survey; NCS-R, The US National Comorbidity Survey Replication; NHS, Israel National Health Survey; NSHS, Bulgaria National Survey of Health and Stress; NSMH, The Colombian National Study of Mental Health; NSMHW, The Nigerian Survey of Mental Health and Wellbeing; NZMHS, New Zealand Mental Health Survey; RMHS, Romania Mental Health Survey; SASH, South Africa Stress and Health Study; S-WMH, The Shanghai World Mental Health Survey; WMHI, World Mental Health India; WMHJ2002–2006, World Mental Health Japan Survey.bMost WMH surveys are based on stratified multistage clustered area probability household samples in which samples of areas equivalent to counties or municipalities in the US were selected in the first stage followed by one or more subsequent stages of geographic sampling (e.g., towns within counties, blocks within towns, households within blocks) to arrive at a sample of households, in each of which a listing of household members was created and one or two people were selected from this listing to be interviewed. No substitution was allowed when the originally sampled household resident could not be interviewed. These household samples were selected from census area data in all countries other than France (where telephone directories were used to select households) and the Netherlands (where postal registries were used to select households). Several WMH surveys (Belgium, Germany, Italy) used municipal resident registries to select respondents without listing households. The Japanese sample is the only totally unclustered sample, with households randomly selected in each of the four sample areas and one random respondent selected in each sample household. 16 of the 22 surveys are based on nationally representative (NR) household samples, while two others are based on NR household samples in urbanized areas (Colombia, Mexico).cBrazil, Israel, New Zealand, Romania, and South Africa did not have an age restricted part II sample. All other countries, with the exception of India, Nigeria, the People's Republic of China, and Ukraine (which were age restricted to ≤39 y) were age restricted to ≤44 y.dThe response rate is calculated as the ratio of the number of households in which an interview was completed to the number of households originally sampled, excluding from the denominator households known not to be eligible either because of being vacant at the time of initial contact or because the residents were unable to speak the designated languages of the survey.eThe weighted average response rate is 73%.

This data presents the 2017–20 regional results from the New Zealand Health Survey, for both adults and children.

Summary of surveys.

This report analyses the level of obesity in New Zealand's adult population. For the purpose of this report, obesity includes people that are overweight and obese, which is defined as having a Body Mass Index of 25.0 and over. The data for this report is sourced from the New Zealand Health Survey conducted by the Ministry of Health (Manatu Hauora). The level of obesity is expressed as a percentage of the population aged 15 and over that is considered overweight or obese for the year ending June.

This dataset presents findings from the New Zealand Health Survey (NZHS) about the private health insurance (PHI) of adults and children across different population groups (age, sex, ethnicity, neighbourhood deprivation, household income, district health board) in New Zealand.

New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Out-Patient Services data was reported at 24.000 NZD in 2016. This records an increase from the previous number of 17.800 NZD for 2013. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Out-Patient Services data is updated yearly, averaging 16.850 NZD from Jun 2007 (Median) to 2016, with 4 observations. The data reached an all-time high of 24.000 NZD in 2016 and a record low of 14.700 NZD in 2007. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Health: Out-Patient Services data remains active status in CEIC and is reported by Statistics New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.H010: Household Economic Survey: Average Weekly Household Expenditure.

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.

In a survey conducted in New Zealand in 2022, over one third of respondents reported that the cost of healthcare serves as a leading barrier to healthcare access in the country. Approximately one third of respondents reported that waiting periods are too long.