Trends in risk factors and management strategies used by people with type 2 diabetes in New South Wales, Australia

Health behaviour and wellbeing trends among Australian adults before and during the COVID-19 pandemic (2017-2022): An interrupted time-series analysis

Objective

To explore population-level trends in health behaviours and wellbeing indicators from before (2017-2019) to during (2020-2022) the COVID-19 pandemic in Australia.

Methods

Using cross-sectional data from New South Wales Adult Population Health Surveys (2017-2022, n = 73,680 responses), we calculated weighted prevalence estimates and interrupted time-series logit models to investigate trends in health behavioural risk factors (vegetable and fruit intake, physical activity, alcohol consumption, smoking, e-cigarette use), Body Mass Index (BMI) (overweight and obesity), and wellbeing indicators (psychological distress, self-rated health) among adults aged ≥ 16 years before and during the pandemic.

Results

From 2017 to 2022, the behavioural risk factors and BMI trends were mostly unchanged. Similarly, wellbeing indicator trends showed only minor variations according to age. The interrupted time-series models found marked changes from before to during the COVID-19 pandemic for e-cigarette use and self-rated health. E-cigarette use showed an overall increasing trend, with significant increases from 2017 to 2022 (OR 8.25, 95 %CI 6.10-11.16). Poor self-rated health showed a stable trend before COVID-19, but decreased in 2020 (OR 0.68, 95 %CI 0.58-0.80) and 2021 (OR 0.70, 95 %CI 0.60-0.81), returning to pre-COVID levels in 2022 (OR 1.23, 95 %CI 1.07-1.41). During the pandemic (2020-2022), there were few statistically significant observed changes in prevalence trends according to SES indicators.

Conclusion

Among Australian adults, relatively small population-level impacts of the COVID-19 pandemic on health behaviours and wellbeing trends were observed. Continued surveillance and sub-group analyses are essential for investigating potential time-lagged effects and regional or sociodemographic differences in health behaviours and wellbeing.