A multivariate decomposition analysis of drivers of overweight and obesity among Ghanaian women

Journal article

Background

Overweight and obesity are rising globally, with Ghana experiencing significant increases among women over the past two decades, raising public health concerns. This study aimed to identify and quantify the key drivers of overweight and obesity among women of reproductive age in Ghana, analysing how these factors have contributed to prevalence changes over time.

Methods

Data from the 2003, 2008, 2014, and 2022 Ghana Demographic and Health Surveys were analysed using binary logistic regression to assess associations with factors such as age, wealth, and education. Multivariate decomposition analysis quantified the contributions of these factors to the observed increases in overweight and obesity prevalence over time.

Results

Here we show overweight and obesity among Ghanaian women rise significantly, reaching 43% in 2022. Key drivers of change in overweight and obesity include wealth, education, urban residence, age, and region. Women in the wealthiest quintile have three times the odds of overweight (aOR: 3.07 [2.02-4.67]) and over six times the odds of obesity (aOR: 6.73 [3.80-11.91]) compared to the poorest quintile. Decomposition analysis shows that 22.5% of the increase in prevalence was due to changes in population characteristics, such as marital and educational status.

Conclusions

Our findings reveal that socio-demographic changes in society, beyond individual behavioural factors, drive the rising overweight and obesity prevalence among Ghanaian women of childbearing age. These findings highlight the dynamic factors influencing weight outcomes and the need for tailored strategies addressing the diverse and evolving determinants of overweight and obesity in Ghanaian women.

Authors: Mensah, JP; Akparibo, R; Atuobi-Yeboah, A; Anaba, E; Gray, LA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: communications medicine
• Publication date: 2026-01-15
• DOI: 10.1038/s43856-026-01391-2
• EISSN: 2730-664X
• ISSN: 2730-664X
• Language: English
• Keywords: Obesity; Logistic regression; Marital status; Overweight; Multivariate analysis; Population; Odds; Public health