Back

Intrahousehold dynamics in South Asia: understanding the relationships between empowerment, task sharing, decision making, and diets among women

Kumar, N.; Quisumbing, A.; Manohar, S.; Banerjee, A.; Gupta, S.; Chauhan, A.; Patwardhan, S.; Koirala, U.

2025-01-09 nutrition
10.1101/2025.01.08.25320196 medRxiv
Show abstract

Despite the growing evidence on womens roles in agriculture and nutrition, interlinkages between womens empowerment, gendered task allocation, and nutrition are rarely studied together. Using data from the Transforming Agrifood Systems in South Asia (TAFSSA), a household survey that used a "plate to farm" assessment approach in three countries (Bangladesh, India and Nepal), the paper investigates the associations between womens empowerment, gendered task allocation, womens decision-making, and womens diets. Our findings reveal complex and context-specific differences in associations between task allocation, decision-making and womens empowerment. While agency in womens decision-making is positively associated with empowerment in all three country contexts, associations between gendered task allocation and empowerment vary. The share of tasks performed by females, particularly in agriculture and food preparation) is positively associated with womens empowerment, but the proportion of tasks shared equally between males and females does not necessarily empower women. Gendered task allocation and womens empowerment are not significantly associated with womens diets in the three countries, owing to the greater importance of broader socio-economic and context-specific factors such as wealth, education, and regional factors in explaining the variance in dietary outcomes. These findings highlight the need to take a holistic approach that addresses gender norms and household resource constraints to improving womens empowerment, while also addressing local accessibility/availability of nutritious foods to enhance the quality of womens diets.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.