Kia ora. In this video, we’ll explore the New Zealand Health Survey Regional Data Release: what it is, what’s available, and how to find and use a statistic. We’ll walk through an example in four simple steps: choosing the statistic type, locating the indicator, filtering the data, and interpreting the result.
The regional data release provides New Zealand Health Survey data broken down by geographic areas and demographics. The data is available as downloadable data tables, allowing you to explore health and wellbeing indicators for different regions and population groups across New Zealand. On the regional release page, you’ll find the data itself alongside some other useful information.
First, the indicator reference guide. This is your starting point. An indicator is something that is measured in the survey and indicators are grouped together under topics. For example, the mental health topic includes indicators on loneliness and psychological distress. The guide explains: what each indicator measures, who it’s for, what topic it relates to, and what years it’s available for.
Next, the statistics themselves. Statistics are provided separately for Adults and Children and in two types: “Crude or unadjusted statistic”, which show the results as they’re observed in the population. These reflect the actual burden of health conditions or behaviors and are best used to describe health outcomes within a region. Then there are “Age-standardised statistics” which are intended for comparing populations with different age structures rather than estimating actual rates. They help us understand whether the differences we can see are due to real health patterns, rather than one group being older or younger than another. Because they are age standardised, they should not be interpreted as the actual burden in the population, so if you want to see that, then use the unadjusted statistics.
All the statistics are available across five different geographies: Health region, District health board, Regional council, Iwi Māori partnership board, and Geographic Classification for health. They can also be broken down by demographics such as: gender, age group, ethnic group, neighbourhood deprivation, and disability status.
Let’s go through an example together. Suppose I’m interested in adults’ self-rated health in the Central Te Ikaroa health region, around 2018. I want to find out what proportion of adults consider their health to be good to excellent.
Here’s how I’d find the information: First, I decide what type of statistic I need. Because I’m not comparing populations with different age structures, I’ll use crude or unadjusted statistics rather than age-standardised statistics. If I wanted to compare an indicator across ethnic groups, I might use the age-standardised statistics to account for differences in age structure. In our example, I’ll select “Adult statistics”.
Next, I’ll check the Indicator Reference Guide to see where self-rated health is located. The guide shows that self-rated health sits under the topic also called “Self-rated health”. The indicator I’m interested in is called ‘health_goodvgexc’. This indicator measures adults reporting good, very good, or excellent health. The guide tells me that this indicator is available for all survey years.
Now I’ll open the self-rated health topic file and filter the data to match what I’m looking for. I’ve already identified the indicator I’m interested in, which is the ‘health_goodvgexc’ indicator. I’m interested in data around 2018, so let’s select the 2017/18 to 2019/20 three-year pool, because it’s around 2018. I’m interested in the Central Te Ikaroa health region, so I will select health region under geography type. And Central Te Ikaroa under geography value. I’ll select All under demographics, since I’m not focusing on any particular subgroup. If I were interested in, for example, self-rated health among adults aged 45 to 54, I could select that demographic group here. Lastly, the value type I’m looking for is a proportion, as I want to know what proportion of adults reported good, very good, or excellent health. If I wanted to know the number of adults who have good, very good, or excellent self-rated health, I can select total here.
The table shows a value of 86.0%. Using the indicator description from the reference guide, I can interpret this as: “An estimated 86.0% of adults in the Central Te Ikaroa health region between 2017/18 and 2019/20 reported being in good, very good, or excellent self-rated health.” The web page also includes guidance on how to cite the data correctly.
Thank you for watching. We encourage you to explore the Regional Data Release and make use of the resources provided to better understand the health and wellbeing of New Zealanders across different regions and communities. If you have any queries, please email healthsurvey@health.govt.nz