Gambling participation and risk after COVID-19: Analysis of a population representative longitudinal panel of Australians.

BACKGROUND AND AIMS: The impact of the COVID-19 pandemic on gambling participation and levels of gambling harm across populations during the pandemic is now addressed in a well-established body of empirical literature. This study aimed to measure the longer-term implications of COVID-19 on gambling participation and levels of gambling harm. DESIGN: Population-based cohort study using group-based trajectory modelling. SETTING: Australia, using gambling participation, problem gambling risk, sociodemographic and psychosocial data from 2019 (pre COVID-19), 2020, 2021 (during COVID-19) and 2023 (post COVID-19). PARTICIPANTS: A population representative survey of Australian adults, including four waves collected in April 2019 (n = 2054), November 2020 (n = 3029), October 2021 (n = 3474) and January 2023 (n = 3370), with a subset (n = 3160) of the sample having longitudinal data available. MEASUREMENTS: Participants were asked which gambling activities they participated in over the past 12 months for money. Problem gambling risk was measured by the nine-item Problem Gambling Severity Index (PGSI). FINDINGS: There was an overall reduction in gambling participation during COVID-19 and return to pre-pandemic levels for most gambling activities by 2023. The longitudinal analysis yielded four trajectories of gambling participation from 2019 to 2023, including individuals who (1) never gambled (25.0% of the longitudinal sample; n = 789); (2) engaged in non-problematic gambling (59.8%; n = 1888); (3) ceased gambling during COVID-19 and started again post pandemic (10.7%; n = 337); and (4) engaged in high risk gambling (4.6%; n = 146), with particular demographic and psychosocial profiles and patterns of participation in specific gambling activities related to these trajectories. CONCLUSIONS: Although overall gambling participation rates decreased at the population level in Australia during COVID-19, by 2023 participation in gambling appeared to have nearly returned to pre-pandemic levels. Patterns of gambling behavior before, during and after the pandemic appear to be heterogeneous.

Is casual employment in Australia bad for workers' health?

OBJECTIVES: This paper assessed the impact of working in casual employment, compared with permanent employment, on eight health attributes that make up the 36-Item Short Form (SF-36) Health Survey, separately by sex. The mental health impacts of casual jobs with irregular hours over which the worker reports limited control were also investigated. METHODS: Longitudinal data from the Household, Income and Labour Dynamics in Australia Survey, over the period 2001-2018, were used to investigate the relationship between the eight SF-36 subscales and workers' employment contract type. Individual, household and job characteristic confounders were included in dynamic panel data regression models with correlated random effects. RESULTS: For both men and women, health outcomes for casual workers were no worse than for permanent workers for any of the eight SF-36 health attributes. For some health attributes, scores for casual workers were higher (ie, better) than for permanent workers (role physical: men: ß=1.15, 95% CI 0.09 to 2.20, women: ß=1.79, 95% CI 0.79 to 2.80; bodily pain: women: ß=0.90, 95% CI 0.25 to 1.54; vitality: women: ß=0.65, 95% CI 0.13 to 1.18; social functioning: men: ß=1.00, 95% CI 0.28 to 1.73); role emotional: men: ß=1.81, 95% CI 0.73 to 2.89, women: ß=1.24, 95% CI 0.24 to 2.24). Among women (but not men), mental health and role emotional scores were lower for irregular casual workers than for regular permanent workers but not statistically significantly so. CONCLUSIONS: This study found no evidence that casual employment in Australia is detrimental to self-assessed worker health.

Does early-life income inequality predict self-reported health in later life? Evidence from the United States.

We investigate the association between adult health and the income inequality they experienced as children up to 80 years earlier. Our inequality data track shares of national income held by top percentiles from 1913 to 2009. We average those data over the same early-life years and merge them to individual data from the Panel Study of Income Dynamics data for 1984-2009. Controlling for demographic and economic factors, we find both men and women are statistically more likely to report poorer health if income was more unequally distributed during the first years of their lives. The association is robust to alternative specifications of income inequality and time trends and remains significant even when we control for differences in overall childhood health. Our results constitute prima facie evidence that adults' health may be adversely affected by the income inequality they experienced as children.