Health and Lifestyles Survey

Impacts of Covid

Interviewing for the 2020 Health and Lifestyles Survey was delayed for five months due to the COVID-19 lockdown. Interviewing was then suspended twice in the Auckland region in response to the alert level being raised to level 3. At all other times, interviewing took place at alert levels 1 and 2 with additional COVID-19 precautions in place. It is unclear what impact the delays to the survey and the pandemic response have had on the data. No adjustments have been made to account for the impacts of these delays and the pandemic response.

Changes in response rates

Lower response rates in 2018 than in 2016 and 2020 among young (15 to 24 years) male Māori, young male NZ European/Other, young female Asian, and older (55+ years) male Asian respondents mean that comparisons of 2018 data with 2016 and 2020 should be made with caution. We recommend focusing on longer-term trends where possible.

Overview of analysis in Kupe

Ethnicity

Both total response and prioritised ethnicity have been used in Kupe:

• Prioritised ethnicity means that a respondent is allocated to a single ethnicity even when they reported belonging to more than one ethnic group. The prioritised order is Māori, Pacific peoples, Asian peoples, then NZ European/MELAA/Other.
• Total response ethnicity means that people who reported belonging to more than one ethnic group are counted once in each group they reported.
• Equity-based ethnicity is another form of prioritised ethnicity. We use this for comparison purposes, and you will only see this in the 'Subgroups comparison' tab. For Māori equity, respondents were allocated in the priority of Māori, Pacific peoples, and then everyone else (non-Māori non-Pacific). For Pacific peoples, respondents were allocated in the priority of Pacific peoples, Māori, and then everyone else. For each equity variable, non-Māori non-Pacific is the comparison group, ie Māori versus non-Māori non-Pacific

Further details of these output options are in the Health Information Standards Organisation (HISO) Ethnicity Data Protocols (Ministry of Health, 2017).

Deprivation

NZDep is a small-area-based index. It provides a measure of neighbourhood deprivation. This is done by looking at the comparative socioeconomic positions of small areas and assigning them decile numbers, from least deprived (1) to most deprived (10). The index is based on nine socioeconomic variables from the Census. Deciles were grouped for analysis into least deprived (deciles 1-3) mid deprived (4-7) and most deprived (8-10). Click here for more information.

Subgroups comparison for binary indicators

These analyses aimed to understand how the risk by each indicator varied across demographic subgroups (such as sex) while adjusting for other factors such as age. We used a quasi-Poisson regression model with a logarithm link function (Lumley, 2011) to estimate relative risks (RRs) and related 95% confidence intervals (CIs) for binary indicators. We replaced estimates with dashes when we had any of the following indications of unreliability:

• The sample size of fewer than 10 events of interest per parameter in the model. This follows the guideline for logistic regression outlined in Hosmer et al. (2013), pp 407-408.
• The CIs that were unusually wide, which was defined as the width of the CI is greater than or equal to 4 times the ratio estimate.
• We applied a conservative approach to ratio estimates and suppressed those that were greater than 7 or less than 1/7.

Changes over time

The proportion or prevalence of each indicator was compared with the most recent available survey year if at least two data points were available. We suppressed all values that contain a small sample size ( n< 30) to maintain the reliability of results and minimise the margin of error. Some of the variation of estimated proportion or prevalence between survey years could potentially be from changes in the questionnaire and/or methodology.

Weighting adjustment

Statistical selection weighting adjustments were applied to each dataset to compensate for selection bias. Post-stratification weight was used to ensure that findings from the survey are representative of the New Zealand population with respect to major demographic characteristics such as sex, age, and ethnicity.

Reliability of survey results - sampling error

We present 95% CIs to indicate the uncertainty in an estimate due to collecting data from only a sample of the population. For survey data, 95% CI gives the range that if we select 100 different samples, we would expect the proportion value to fall within the range 95% of the time.

Reliability of survey results - non sampling error

Findings are likely to under- or overestimate some indicators due to the nature of self-reported information. For instance, when a question was asked 'thinking about the last 12 months, how often have you felt that you might have a problem with gambling?' the respondents then responded with either never, sometimes, most of the time, or almost always. Depending on what the respondent considers to be socially desirable, this can lead to over-reporting of good behaviours or under-reporting of risk behaviours. Also asking for the last 12 months assumes respondents can accurately recall previous events over the time period which may not be the case.

Survey results show associations rather than cause-and-effect relationships

Kupe provides a snapshot of data at one point in time. Results can be used to look at associations between different factors, such as gambling harm and neighbourhood deprivation. It does not look at cause-and-effect relationships.

For example, if we find out that a problem with gambling is more common in people living in deprived areas, it does not mean that problem gambling is caused by living in deprived areas.

Revisions to previously published data

Findings obtained from Kupe may differ from previous Health New Zealand reports and between Kupe releases for the following reasons:

• Subgroups comparison: We have started to apply quasi-Poisson models to calculate risk ratios in 2018. The technique has not been used in previous HNZ reports before 2018.
• Benchmarking: Each survey year is now benchmarked to the estimated resident population of New Zealand at the time of the survey year, whereas, in reports before 2016 the survey data was benchmarked to the most recent New Zealand census population.
• Extreme weights: As part of an on-going data quality assurance, in 2018, we trimmed extreme weights of all survey years. This was to reduce the overall variation in weights and to increase the reported precision of the estimates. The total amount trimmed values are then divided among the observations that were not trimmed, so that the total weight remains the same.
• Confidence Intervals: A modified version of the binomial intervals as described in Korn and Graubard (1998) is used in Kupe.
• Prior to November 2020, totals used a different method (the Woolf logit interval method). In November 2020, a change was made so totals used the above method. This has led to slight changes (up to the first decimal) for confidence intervals and p values for prevalences and changes over time.
• Indicators: The following indicators have been removed for the 2020 Health and Lifestyles Survey (version 5.3).
  • No interaction between pokie players with staff at gambling venues
  • Help services advertised at pokie venues
  • Spent more than $25 on playing gaming machines / pokies

References

Lumley, T. (2011). Complex surveys: a guide to analysis using R(Vol. 565). Hoboken, New Jersey: John Wiley & Sons.

Ministry of Health. (2017).HISO 10001:2017 Ethnicity data protocols. Wellington: Ministry of Health. www.health.govt.nz/publication/hiso-100012017-ethnicity-data-protocols

Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (Third edition). Hoboken, New Jersey: Wiley.

Korn, E. L., & Graubard, B. I. (1998). Confidence intervals for proportions with small expected number of positive counts estimated from survey data. Survey Methodology 24(2): 193-201.