This report endeavours to use inclusive and appropriate language for all people throughout. Preferred terms are described below. Readers are encouraged to provide feedback for terms that are omitted or incorrect using the report Feedback form.
First Nations peoples
Queensland Health recognises and respects both Aboriginal peoples and Torres Strait Islander peoples, as the First Nations people in Queensland. Queensland Health’s preference is to use ‘First Nations’ peoples and, in respect of both cultural groups, recognises ‘Aboriginal’ and ‘Torres Strait Islander’ peoples as acceptable terms. Queensland Health acknowledges that local environment and operating context will determine preferred choice. More information about Queensland Health’s preferred terminology is available from the Terminology guide for the use of ‘First Nations’ and ‘Aboriginal’ and ‘Torres Strait Islander’.
Refers to people and families who identify as lesbian, gay, bisexual, transgender, intersex and queer. The + reflects that the letters of the acronym do not capture the entire spectrum of sexual orientations, gender identities and intersex variations, and is not intended to be limiting or exclusive of certain groups.
Sex and gender
This report routinely reports health measures by biological sex (male and female). It is acknowledged that this does not capture important variations by gender and sexual orientation. Health assessment by gender and sexual orientation has typically been undertaken in specialist studies.
Recently, the Australian Bureau of Statistics developed Standards for sex, gender, variations of sex characteristics and sexual orientation variables. These standards are anticipated to be increasingly used across health reporting systems. This will enable more routine reporting by gender and will increase comparability across data sources.
Because some health conditions are sex-specific but may be experienced by people who do not identify with that sex (for example, cervical screening), language that is not sex-specific was used in some report sections (for example, ‘cervical screening participants’ or ‘people with a cervix’).
Burden of disease reporting
Burden of disease is expressed as ‘years of healthy life lost’ to distinguish from more general use of the term ‘burden’ which is increasingly being used in other contexts.
Other commonly used terms for reporting formal burden of disease measures are disability adjusted life years (DALYs), years of life lost (YLL) and years lived with disability (YLD).
Years and time periods
Periods of time are explicitly defined in the text and are inclusive of the entire period (example, ‘from 2020 to 2022’ is inclusive of 2020, 2021 and 2022).
The following conventions are used to indicate the period of time used for results based on a:
- financial year yyyy–yy (‘2021–22’; financial year from July 1, 2021 to June 30, 2022)
- calendar year yyyy (‘2022’; calendar year from January 1, 2022 to December 31, 2022)
- combined number of calendar years yyyy–yyyy (‘2020–2022’; calendar years from January 1, 2020 to December 31, 2022)—also referred to as ‘pooled’ data
- combined number of financial years ‘for the x-year period yyyy–yy to yyyy–yy’ (for the 3-year period from 2019–20 to 2021–22)—also referred to as ‘pooled’ data.
An exception to the pooled calendar year format is for the Queensland preventive health survey data which uses yyyy–yy to refer to two years of pooled data in sub-state reporting. This is based on the past precedent for this data source. For example, 2020–21 would indicate pooled data from the 2020 and 2021 surveys.
‘Remoteness’ is determined by Accessibility/Remoteness Index of Australia (ARIA+). Categories of the five categories of remoteness areas are combined for some measures to avoid data cells with small numbers; this information is included in the footnotes of figures where applicable.
Area-based socioeconomic status
‘Socioeconomic status’ may be reported as Index of Relative Socio-economic Disadvantage (IRSD) or Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), depending on primary source information.
Other geographic boundaries
Other geographic boundaries used for reporting are described in the Our People, Regional health section.
This report uses numerous primary and secondary data sources to provide a comprehensive view of the health status of Queenslanders. Providing current methodological and other technical documentation is the responsibility of the relevant data custodians.
This report provides hyperlinks to these primary data source where technical information can be sourced. This may be in individual citations in the Reference section, hyperlinks in footnotes on data dashboard or figures, or in the report data sources table.
Data type differences
Underlying differences in data collection mean that different statistical approaches may be required. A common difference is for data collected as counts (for example hospital episodes of care or notifiable condition counts) or by survey (for example, the Queensland preventive health survey or the National Health Survey).
Because counts are an enumeration of events, calculation of other statistical results is typically more straightforward. Survey data, however, is collected from a sample of the population and requires additional manipulation to ensure that the achieved sample is representative of the wider population. This is because different response rates among different subsets of the population may be bias results. Response rates commonly vary by age and sex, therefore, surveys are benchmarked back to the true population age and sex distribution by generating sample weights. Sample weights are then applied in the majority of analyses so that results are generalisable to the population of interest.
Numerous statistical measures are used in this report. Results at a point in time, for example a calendar year, are typically reported as rates, counts, or prevalence. Rates may be crude rates, age-standardised rates (ASR), or age-specific rates. In text, ASRs are referred to as standardised rates. For survey data, calculations of these measures also include applying the survey weight.
Because many health conditions and behaviours are associated with age, comparing populations with different age structures means that health differences due to age or other factors cannot easily be distinguished. To adjust for the effects of age and assess whether health differences are due to other factors, a statistical technique called age-standardisation is commonly used.
Because this report focuses on long term trends and presents results by geographic areas, adjusting for the effects of differences in age distributions was a priority. When available, age-standardised rates are therefore used.
Direct age-standardisation converts the crude overall rate estimate to the rate that would have occurred if the age structure was that of the standard population. In this report, the 2001 Australian population was used as the standard population, unless otherwise stated. Age-standardised rates calculated using different standard populations cannot be directly compared.
In some instances, crude rates may be more appropriate or be the only available information. For example, crude rates are reported in this report for intentional self-harm hospitalisations in Our health, for mortality rate in Our regional health, and in Our lifestyle for results from the Queensland preventive health survey. Crude rates are calculated by dividing the total number of events by the total population, multiplied by a constant, such as 100,000, to give crude rate for 100,000 persons.
In some instances, both crude and age-standardised rates are included. For example, Supplemental data under Additional information may include options to select crude rates and/or event count information.
Crude rates will differ from standardised rates, often to a considerable degree. In the Our regional health section, the crude rate of all cause mortality in Wide Bay Hospital and Health Service was higher than the standardised rate (977.5 and 567.9 per 100,000 persons, respectively). The difference is caused by a large age effect due to over-representation of older age groups. Age-standardisation adjusts for the age effect meaning that the differences in standardised rates mortality between regions are due to factors other than age.
Age-specific rates are limited to a particular age group. They are calculated by dividing the number of health events in the age group by the total number of target population in that age group, multiplied by a constant, such as 100,000, to give age-specific rate for 100,000 persons. Refer to the methods for reporting population health status for more details.
Comparison of Queensland or Australia with other jurisdictions, is reported as ‘rank’. To apply ranks, the health event is ordered from best (ranked first) to worst (ranked last). A ranking of 1 is therefore consistently the best outcome. Ranks greater than 1 mean progressively worse health outcomes relative the group ranked first.
Ranks do not imply a statistical difference, however. It is common for health outcomes for groups, such as states and territories, to be so closely similar that there is not statistical difference. In text, this may be noted, for example, by stating that the Queensland result is similar to the national result.
Statistical significance helps quantify whether a result is likely due to chance or to some factor of interest. Results that are statistically significant are reported in the text. Results that do not reach statistical significance, or are missing a measure of statistical significance, are omitted or reported as ‘similar’.
The confidence interval (CI) is a range of values that is expected to contain the true population value 95% of the time data were collected on multiple samples. Thus, a large interval reflects less certainty in the precision of the estimate. A conservative approach to assessing statistical difference is to compare CIs. When CIs do not overlap, the differences are unlikely to be due to chance. Comparison of CIs is the predominant approached to assessing statistical significance due to the large number of comparisons that occur across this report.
The relative standard error (RSE) is calculated by dividing the standard error of the estimate by the estimate itself and is expressed as a percentage. It is particularly useful when assessing the reliability of estimates with large CIs. Estimates with an RSE less than 25% are reliable and are reported. Estimates with an RSE between 25% and 50% should be interpreted with caution. Estimates with an RSE greater than 50% are not considered sufficiently reliable and are not reported.
Reporting statistical difference
Differences between results are reported as a percentage increase/higher or ‘times higher’.
Percentage increase is the percentage of the lower value that is the difference between the two values. For example, the injury hospitalisation rate was 73.9% higher in remote and very remote areas than major cities (6,344.9 and 3,647.7 per 100,000 persons, respectively). Difference: 6,344.9-3,647.7 = 2,697.2. Ratio: 2,697.2/3,647.7 = 0.739 (73.9%).
Times higher is calculated by dividing the larger value by the smaller value. For example, injury mortality was 2.8 times higher in males than females (57.1 and 20.7 per 100,000 persons, respectively). This is: 57.1/20.7 = 2.8 times higher.
These calculations are typically applied only when the results for the compared groups are significantly different. In a limited number of cases, this approach may be used for more general descriptive purposes.
This report contains trend analysis that may be either descriptive or be based on statistical trend analysis. The intention is to increase statistical trend analysis over time.
Caution should be used in comparing data over time as there have been changes in coding standards and between the International Statistical Classification of Diseases and Related Health Problems, Australian Modification (ICD-10-AM) editions. For example: the coding standard for viral hepatitis in the 8th edition of ICD-10-AM introduced in 2013–14 may account for a proportion of the increase in the rate of vaccine preventable conditions. See Appendix A - Admitted patient care 2013–14: Australian hospital statistics, AIHW, for more details.
Statistical trends analysis
Trends results from the Queensland preventive health survey are reported primarily in the Our lifestyle chapter. Poisson regression was used to analyse statistical changes in health status over time as the annual percentage change (APC). Interaction effects between subgroups are also assessed to determine whether the rate of change over time differed, for example between males and females. In the course of analysis, whether the trend is linear or better described by another shaped function is also assessed.
Methodological information is available in the report Trends in preventive health risk factors 2002–2013 (Appendix 1).
Trends reported descriptively
Trends for count data are descriptively reported. Typically, the change is described as the difference between the first and last data point of the series. In cases where there was a clear underlying data coding change, the trend may be described starting with the data point following the coding change. A similar approach was used where a change in trend was visible but could not be attributed to a change in coding practices.
Descriptive assessment of trends was applied conservatively, and the intention is to increase the amount of statistical trend analysis over time.