Australian population norms for paid work productivity and exploratory estimates for unpaid work productivity

The productivity-adjusted life years metric was developed to quantify the impact of disease on work productivity. To establish baseline distributions for comparing disease burdens across health conditions and populations, this study estimated Australian population norms for the paid work productivity index and productivity-adjusted life expectancy (PALE) including exploratory estimates for unpaid work. This study primarily used data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey Wave 22, conducted between 2022 and 2023 (n = 12,819) to estimate paid work time, unpaid work time, and absenteeism. Data on presenteeism were obtained from the Australian Workplace Barometer (AWB) Survey. The productivity index was estimated by dividing actual number of working hours by typical number of working hours, ranging from 0 (completely unproductive) to 1 (completely productive). Due to limited data, unpaid work productivity loss was estimated exploratorily based on paid work productivity loss, and sensitivity analyses were conducted. The sex-specific productivity index by five-year age groups was combined with the Australian life table, using data from the Australian Bureau of Statistics (ABS), to estimate PALE. PALEs were calculated using no discounting, and 3 % and 5 % discount rates. The population productivity index was 0.831 (0.847 for male; 0.815 for female). At age 15, PALE for male was 51.2 years (undiscounted), 24.0 years (discounted at 3 %), and 16.7 years (discounted at 5 %). For female, PALE was 53.0 years (undiscounted), 23.7 years (discounted at 3 %), and 16.3 years (discounted at 5 %). The estimated population norms for the productivity index and PALE provide a baseline for assessing the productivity-related burden of specific diseases and identifying variations across subpopulations. Additional empirical research, particularly on the measurement of unpaid work productivity, is needed to further refine the underlying assumptions. • Work productivity is essential to individual wellbeing and the societal economy. • Measuring health-related productivity loss is important. • This study provides norms for the productivity index and productivity-adjusted life expectancy. • Population norms help quantify productivity burden across diseases and groups. • Findings can further inform health technology assessments and resource allocation.