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

Niue, World Health Organization. 2013. Niue NCD risk factors STEPS report. [Suva, Fiji]: World health Organization Western pacific Region. 121 p.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.

The 2010 Niue Global school-based student health survey (GSHS) was a school-based survey of students in Forms 1-7.

The purpose of the GSHS is to provide data on health behaviors and protective factors among students to: - Help countries develop priorities, establish programs, and advocate for resources for school health and youth health programs and policies; - Allow international agencies, countries, and others to make comparisons across countries regarding the prevalence of health behaviors and protective factors; and - Establish trends in the prevalence of health behaviors and protective factors by country for use in evaluation of school health and youth health promotion.

• v01: Edited, anonymous datasets for public distribution.

The 2010 Niue GSHS measured alcohol use; dietary behaviors; hygiene; mental health; physical activity; protective factors; tobacco use; and violence and unintentional injury.

• Collection start: 2010
• Collection end: 2010

This is a subset of Sustainable Development Goals (all)

Contains available data on Pacific Sustainable Development Indicators selected by the region and endorsed by Forum Leaders in the Pacific Roadmap for Sustainable Development. Data is collated from a number of sources, including national household collections, civil registry data, education management information systems, health information systems, treasury papers, and published reports from countries and development partners.

The 2015 Lancet Commission’s conclusion – that ‘tackling climate change could be the greatest global health opportunity of the 21st century’ highlighted the need for a global monitoring system with the ability to engage policymakers and support health professionals.In 2016 the Lancet Countdown: Tracking Progress on Health and Climate Change was formed to address this gap, beginning with a public consultation to identify key areas to track and monitor. The collaboration recognises that health should be at the centre of how governments and decision makers understand and respond to climate change, to maximise the human benefits of a robust response.Publishing annually in The Lancet, with strategic and financial support from the Wellcome Trust, The Lancet Countdown is hosted by University College London, and works with almost 300 leading researchers from around the world to track and understand the evolving links between climate change and people’s health.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format.

Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datasets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of acquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.

Depending on the intended use of a dataset, we recommend a few data processing steps before analysis: - Analyze missing data: Project Tycho datasets do not include time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported. - Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

HIES collects a wealth of information on HH income and expenditure, such as source of income by industry, HH expenditure on goods and services, and income and expenditure associated with subsistence production and consumption. In addition to this, HIES collects information on sectoral and thematic areas, such as education, health, labour force, primary activities, transport, information and communication, transfers and remittances, food expenditure (acquisition) and gender. The Pacific Islands regionally standardized HIES instruments and procedures were adopted by NSO for the 2015/2016 HIES. These standards, were designed to feed high-quality data to HIES data end users for: • deriving expenditure weights and other useful data for the revision of the CPI; • supplementing the data available for use in compiling official estimates of various components in the System of NA; • supplementing the data available for production of the balance of payments; and • gathering information on poverty lines and the incidence of poverty in Niue.

The data allow for the production of useful indicators and information on the industries covered in the survey, including providing data to inform indicators under the United Nations Sustainable Development Goals (SDGs). This report, the above listed outputs, and additional thematic analyses, collectively provide information to assist with multisector planning and policy formation. The 2015/2016 HIES was conducted to update the 2002 HIES data and aimed to estimate the total amount HH spent and earnt over the past 12 months at the national level (total expenditure and income).

V01: Cleaned, labelled and anonymized version of the Master file.

HOUSEHOLD: Housing characteristics, tenure characteristics, utilities and communication, goods and assets, vehicles and accessories, loans, expenditure, income.

INDIVIDUAL: Demographic profile, economic activities, health, communication.

• Collection start: 2015
• Collection end: 2016

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format.

Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datasets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of acquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.

Depending on the intended use of a dataset, we recommend a few data processing steps before analysis: - Analyze missing data: Project Tycho datasets do not include time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported. - Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

Abstract

STEPS is a household-based survey to obtain core data on the established risk factors that determine the major burden of NCDs.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Adults aged 15+ years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Census

Mode of data collection

Face-to-face [f2f]

Response rate

Of the total population aged 15 years and over (n=1071), 913 were surveyed at Step 1 and Step 2 giving a response rate of 85.2%. Of these, 863 people undertook biochemical measures at Step 3 (response rate 80.6%).

WHO Activity File - Niue-2018-19

WHO Activity File - Niue-2016-17

Statistics illustrates consumption, production, prices, and trade of Medical Ultraviolet or Infrared Apparatus in Niue from 2007 to 2024.

Abstract

The GSHS is a school-based survey which uses a self-administered questionnaire to obtain data on young people's health behaviour and protective factors related to the leading causes of morbidity and mortality among children and adults worldwide.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

School-going adolescents aged 13-15 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Niue GSHS was a school-based survey of students in Forms 1-7. A census was used to produce data representative of all students in Forms 1-7 in Niue.

Sampling deviation

The school response rate was 100%, the student response rate was 81%, and the overall response rate was 81%.

Mode of data collection

self-administered

Research instrument

The following core modules were included in the survey: alcohol use dietary behaviours hygiene mental health physical activity protective factors tobacco use violence and unintentional injury

Cleaning operations

All data processing (scanning, cleaning, editing, and weighting) was conducted at the US Centers for Disease Control.

Statistics illustrates the export volume of Rubber; vulcanised (other than hard rubber), gloves, of a kind used for medical, surgical, dental or veterinary purposes in Niue from 2007 to 2024 by trade partner.

Abstract

The GYTS is a school-based survey which uses a self-administered questionnaire to monitor tobacco use among youth and to guide the implementation and evaluation of tobacco prevention and control programmes.

Geographic coverage

National

Analysis unit

Individuals

Universe

School-going adolescents aged 13-15 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

GYTS uses a global standardized methodology that includes a two-stage sample design with schools selected with a probability proportional to enrollment size. The classes within selected schools are chosen randomly and all students in selected classes are eligible to participate in the survey.

A total of 36 students aged 13-15 in sections 3, 4 and 5 completed the survey.

Mode of data collection

self-administered

Cleaning operations

All data processing (scanning, cleaning, editing, and weighting) was conducted at the US Centers for Disease Control.

Response rate

The overall response rate was 46.9%.

Arrora Deiye (Nauru Bureau of Statistics), Marilyn Deireragea (Chief Secretary Department), Fanuma Sioneholo (Statistics Niue) and Asnath Bam (Department of Health) with guidance from Gloria Mathenge (SPC) and Lauren Moran of the Australian Bureau of Statistics (ABS) - 2019.

The sites at Sandfly in Gela, Central Province were established over a three year period (three sites in 2004, two sites in 2005 and one site in 2007) after a series of workshops on good governance and marine resource awareness raising under the coral gardens project which was implemented by SIDT, ECANSI and Fisheries Division of the Solomon Islands government with funding from SPREP through FSPI. The sites are all community owned although two of them are owned and operated by resort owners who are indigenous residents of Gela Available online Call Number: 25389 Physical Description: 28 p.