2 datasets found
  1. Life expectancy in New Zealand, 1870-2020

    • statista.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista, Life expectancy in New Zealand, 1870-2020 [Dataset]. https://www.statista.com/statistics/1041182/life-expectancy-new-zealand-all-time/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1870 - 2020
    Area covered
    New Zealand
    Description

    Life expectancy in New Zealand was just over 34 in the year 1870, and over the course of the next 150 years, it is expected to have increased to just over 82 by the year 2020. Although life expectancy has generally increased along a gradual curve throughout New Zealand's history, there was a slight dip in the late 1910s, as a result of the First World War and following influenza epidemic. Apart from this, there were no anomalies that reduced life expectancy throughout this 150 year period.

  2. Multi Country Study Survey 2000-2001 - New Zealand

    • datacatalog.ihsn.org
    • apps.who.int
    Updated Mar 29, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    World Health Organization (WHO) (2019). Multi Country Study Survey 2000-2001 - New Zealand [Dataset]. https://datacatalog.ihsn.org/catalog/study/NZL_2000_MCSS_v01_M
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset provided by
    World Health Organizationhttps://who.int/
    Authors
    World Health Organization (WHO)
    Time period covered
    2000 - 2001
    Area covered
    New Zealand
    Description

    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.

  3. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista, Life expectancy in New Zealand, 1870-2020 [Dataset]. https://www.statista.com/statistics/1041182/life-expectancy-new-zealand-all-time/
Organization logo

Life expectancy in New Zealand, 1870-2020

Explore at:
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
1870 - 2020
Area covered
New Zealand
Description

Life expectancy in New Zealand was just over 34 in the year 1870, and over the course of the next 150 years, it is expected to have increased to just over 82 by the year 2020. Although life expectancy has generally increased along a gradual curve throughout New Zealand's history, there was a slight dip in the late 1910s, as a result of the First World War and following influenza epidemic. Apart from this, there were no anomalies that reduced life expectancy throughout this 150 year period.

Search
Clear search
Close search
Google apps
Main menu