Background and objectives: Excess adiposity is a key public health problem; rapidly increasing in prevalence and being a significant predictor of subsequent poor health. Socio-economic inequalities in adiposity are, therefore, of particular interest themselves but also because they may contribute to broader health inequalities. Focusing on income, this is the first study aimed to provide a thorough investigation of inequalities in alternative adiposity measures, going beyond the conventional body mass index (BMI), using concentration indexes and decomposition techniques. Data and Methods: Applying data from Understanding Society (UKHLS) wave 2 (5,459 males; 7,165 females), we estimate concentration indexes for BMI, body composition (percentage body fat, %BF; total body fat index, TBFI; fat-free mass index, FFMI) and central adiposity (waist circumference, WC) in the case of Great Britain. These adiposity measures are treated both as linear and discrete measures. Regression-based decomposition techniques are then implemented to analyse the contribution of a rich set of adiposity covariates to the overall level of income-related inequalities in adiposity. Results and discussion: In males, we found no income-related inequalities using BMI. However, disentangling fat from lean-mass in BMI (TBFI vs FFMI) we show significant pro-rich inequalities (fat-mass is more concentrated among the poor). %BF and WC are associated with similar pro-rich inequalities. Results for females indicate the presence of pro-rich inequalities irrespective of the adiposity measure. Similar patterns are observed when measures of excess adiposity are applied (discrete measures focusing at the right tail of the distribution), although inequalities are higher in magnitude compared to the case of linear adiposity measures. Given BMI’s inability to disentangle body composition, our evidence may reflect the fact that fat-mass accounts for a considerable part of BMI in females, while muscle mass in males. Sex disparities in the association between socio-economic status and body composition may be explained by gender-specific lifestyle and behavioral differences. Decomposition analysis revealed that the pro-rich inequalities in (excess) adiposity are due to correlation between income and other adiposity determinants. Unlike income itself, subjective financial well-being (financial strain and material deprivation measures) is the main contributor of inequalities; this highlights the role of psycho-social processes and/or material pathways (associated with subjective financial well-being) on shaping inequalities in adiposity. Among the remaining covariates, it may worth mentioned that educational attainment also exerts a considerable contribution, while physical activity contributes to less extent on explaining pro-rich adiposity inequalities. Although decomposition analysis does not allow for causal pathways, these evidence may contribute on better understanding inequalities in adiposity, proving useful information to policy-makers aimed to tackle inequalities in adiposity. Conclusion: We explored income-related inequalities in adiposity in Great Britain, using concentration index techniques. BMI-related adiposity measures seem to mask the presence of pro-rich inequalities in males but not in females. Decomposition analysis show that the pertinent adiposity inequalities result from confounding effects, with the major role of subjective financial well-being and education, rather than the “pure” income effect. This indicates that tackling inequalities in adiposity is not simply a case of redistributing income.