Estimating the population exposed to a risk factor over a time window: A microsimulation modelling approach from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

Abstract

Objectives Burden of disease estimation commonly requires estimates of the population exposed to a risk factor over a time window (yeart to yeart+n). We present a microsimulation modelling approach for producing such estimates and apply it to calculate the population exposed to long working hours for one country (Italy). Methods We developed a three-model approach: Model 1, a multilevel model, estimates exposure to the risk factor at the first year of the time window (yeart). Model 2, a regression model, estimates transition probabilities between exposure categories during the time window (yeart to yeart+n). Model 3, a microsimulation model, estimates the exposed population over the time window, using the Monte Carlo method. The microsimulation is carried out in three steps: (a) a representative synthetic population is initiated in the first year of the time window using prevalence estimates from Model 1, (b) the exposed population is simulated over the time window using the transition probabilities from Model 2; and (c) the population is censored for deaths during the time window. Results We estimated the population exposed to long working hours (i.e. 41–48, 49–54 and ≥55 hours/week) over a 10-year time window (2002–11) in Italy. We populated all three models with official data from Labour Force Surveys, United Nations population estimates and World Health Organization life tables. Estimates were produced of populations exposed over the time window, disaggregated by sex and 5-year age group. Conclusions Our modelling approach for estimating the population exposed to a risk factor over a time window is simple, versatile, and flexible. It however requires longitudinal exposure data and Model 3 (the microsimulation model) is stochastic. The approach can improve accuracy and transparency in exposure and burden of disease estimations. To improve the approach, a logical next step is changing Model 3 to a deterministic microsimulation method, such as modelling of microflows.

New global indicator for workers’ health: mortality rate from diseases attributable to selected occupational risk factors

“…9 All estimates adjust for occupational turnover using WHO-approved methods: for example, estimates for recently added pairs 12 model workers moving between employment and unemployment or retirement using longitudinal occupation data. 21 Briefly, for the 19 established exposure–disease pairs (pairs number 1–19 in Table 1 ) WHO and the ILO derived population-attributable fractions from the 2017 Global Burden of Disease Study. 16 These fractions quantify the proportion of deaths from a particular disease attributable to a specific risk factor.…”

How can Ministries of Health and Labour add the new indicator on work-related diseases to the monitoring system for the United Nations global goals?

“…In 2016 and in the spirits of the SDGs 1 ) and the OneUN approach 5 ) , WHO and the International Labour Organization (ILO) partnered to improve global workers’ health monitoring by regularly producing the first interagency estimates of occupational burden of disease: the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates) 6 , 7 , 8 , 9 ) . Between 2016 and 2021, WHO and the ILO harmonized their methods for estimating health loss from established pairs of occupational risk factor and health outcome 8 , 10 ) and, supported by over 250 individual experts in 35 countries, conducted pre-registered 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ) systematic reviews and meta-analyses 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ) of prioritized additional pairs 31 ) . The produced estimates have revolutionized global understanding of occupational burden of disease, establishing exposure to long working hours as the occupational risk factor with the largest attributable disease burden (745,194 deaths/year) 32 ) and occupational exposure to solar ultraviolet radiation as the third largest occupational carcinogen (18,960 deaths/year) 33 ) .…”