[INTRODUÇÃO] Empirical evidence suggests that unpaid domestic work (UDW) has a major economic impact which could amount up to 4% of GDP (Alonso et al., 2019). Understanding the determinants of UDW and time usage can help shed light on the economic value of unpaid domestic work and increase its social importance. Gender gaps in the economy are a major reason for the reproduction of stereotypes that diminish the relevance of women’s greater labor market participation. This paper accounts for another step towards the understanding of gender differences as something to be targeted and diminished for the maximization of productivity. By delimiting the drivers of UDW, governments can propose economic and social policies that strive to narrow the gap between women and men and the number of hours that are dedicated to UDW inside households. [METODOLOGIA] We structured an empirical model estimated through Ordinary Least Square regression for outcome variables (UDW) and explanatory variables of interest (such as, but not limited to civil status and age). We also included municipality fixed effects to account for unobserved heterogeneity among different regions in Uganda. Standards errors are robust and clustered at the municipality level to account for potential correlation in the cross-section within each district. We conducted the Seemingly Unrelated Estimation (SUE) test to account for differences in coefficients between both regressions (male vs. female). The null hypothesis that these coefficients are equal amongst each other. [RESULTADOS] The results of the statistical analysis proved the hypothesis to be true, seeing that the coefficient of gender had the biggest effect over the amount of time spent in UDW-related activities. Furthermore, the gender-separated analysis demonstrated the unequal distribution of unpaid domestic work inside the household between husband and wife. Apart from gender and civil status, we found that the age of the individuals and the location of the household are also determinant factors as to the increase or decrease of hours spent weekly for UDW, although the age squared variable demonstrated that the age effect decreases with time. [CONCLUSÃO] The main objective of this study was to investigate how individual characteristics affect hours spent in unpaid domestic work activities. Findings of this research and further analysis shaped the determinants of unpaid domestic work. Our results show that civil status, age, gender and location of the household are determinants of increase or decrease in hours spent on unpaid domestic work. More specifically, the variable for civil status demonstrated a clear difference in the distribution of workload between married women and married men, confirming once again the gender inequality in the distribution of UDW inside the household. The age and age squared variables configured an age range that generates propensity for an increase in the number of hours spent weekly in UDW, broadly defined as the age period after receiving childcare and before eldercare. Also, individuals that live in urban environments experience a decrease in the number of weekly hour load of UDW.  Understanding the primary determinants for an increase or decrease in UDW is paramount to the elaboration of an agenda that strives to understand this reality for different countries and the effect of more or fewer hours engaging in UDW to other aspects of the household.