Non-linear multivariate decomposition modelling of the predictors of menstrual product use among reproductive-aged women: evidence from the 2022 Ghanaian demographic and health survey - Summary - MDSpire
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Non-linear multivariate decomposition modelling of the predictors of menstrual product use among reproductive-aged women: evidence from the 2022 Ghanaian demographic and health survey
To examine the determinants of menstrual product use and quantify the contributions of compositional and structural factors to residence-related disparities in Ghana.
Approach:
Data Source: Data were derived from the 2022 Ghana Demographic and Health Survey among a weighted sample of 12,497 women aged 15–49 years.
Statistical Analysis: Single-and multilevel logistic and ordered logistic regression models were fitted, and non-linear multivariate decomposition analysis was conducted.
Key Findings:
Higher individual educational attainment, household wealth, urban residence, younger age, self-reported good health, and greater media exposure were associated with the use of modern menstrual products.
13%-15% of the variance in product use was attributable to between-cluster differences.
Compositional factors, particularly household wealth and education, accounted for 63% of rural–urban inequalities in menstrual product use.
Interpretation:
Structural inequities in wealth, education, and community resources are major determinants of menstrual product use in Ghana.
Limitations:
The study may not capture all contextual factors influencing menstrual product use.
Findings are based on cross-sectional data, limiting causal inferences.
Conclusion:
Disparities in menstrual product use are influenced by various factors, including wealth and education.
