Socio-economic inequalities in and factors associated with minimum dietary diversity among children aged 6–23 months in South Asia: a decomposition analysis - Md Akhtarul Islam; Md Ashfikur Rahman; Satyajit Kundu; Harun Or Rashid; Mortuja Mahamud Tohan (BMJ Open, 2023)
Objective This study aimed to determine the factors associated with minimum dietary diversity (MDD) and estimate the socioeconomic inequalities in MDD among children from five South Asian countries.Design Cross-sectional.Setting The study used the most recent round of secondary databases of Demographic Health Survey data of Bangladesh (2017–2018), India (2019–2021), Maldives (2016–2017), Nepal (2018) and Pakistan (2017–2018).Participants This study used information on MDD and other explanatory variables from a total of 136 980 (weighted) children aged 6–23 months.Methods Multivariable logistic regression was employed to identify the factors associated with MDD and concentration index (CIX) and Lorenz curve were used to measure the socioeconomic inequalities in MDD.Results The overall weighted prevalence of MDD in South Asia was 23.37%. The highest prevalence of MDD was found among children from Maldives (70.7%), while the lowest was in Pakistan (14.2%). Living in affluent versus poor households, having a mother who is employed versus a mother who is unemployed, exposure to various forms of media (newspapers and magazines), seeking antenatal care (ANC) more than four times compared with those who sought ANC less than four times and having children older than 4 years old are the most common significant factors associated with MDD deficiency. This study found the value of the CIX for MDD (MDD: CI=0.0352; p<0.001) among children with a higher socioeconomic status, suggesting inequality in MDD in favour of the more among well-off households.Conclusion Inequality in the prevalence of MDD favours the affluent. Health policy and intervention design should prioritise minimising socioeconomic inequalities concerning the MDD. In addition, policy-makers should prioritise the associated factors of MDD such as education, wealth status, employment, media exposure while designing intervention or policies.