Research on body fat distribution illustrates a heterogeneity within obesity and indicates that the pattern in which a person carries their fat could help determine each individual’s cardiometabolic risk profile. The aim of this study was to evaluate the association between balance of different fat compartments (visceral, subcutaneous, and liver) with incident type 2 diabetes (T2D) and cardiovascular disease (CVD) in the UK Biobank imaging study. Magnetic resonance images were collected in 40,174 participants using a 6-minute neck-to-knee protocol and analyzed for visceral adipose tissue (VAT) volume, abdominal subcutaneous adipose tissue (aSAT) volume, and liver proton density fat fraction (LF) using AMRA® Researcher. To assess body fat distribution patterns independent of BMI, personalized body fat z-scores (VATz, aSATz, and LFz) were calculated for each participant using the distribution of least N=150 matched controls with the same sex and similar BMI. Participants without prevalent T2D and CVD (N=35,138), were partitioned in 3 ways: based on the balance between (1) VATz & LFz using z-scores=0 as cut-points (thus creating 4 groups: VATz< 0 & LFz< 0 (reference [lower VAT and LF than predicted by BMI]); VATz< 0 & LFz >0; VATz >0 & LFz< 0; VATz >0 & LFz >0, (2) VATz & aSATz, and (3) LFz & aSATz. Logistic regression and Cox proportional-hazards models were used to investigate the association of the balance between body fat z-scores with incident T2D and CVD respectively. Models were crude and subsequently adjusted for sex, age, and BMI. The strongest association with incident T2D were found for VATz >0 & LFz >0 (crude odds ratio (cOR) 4.31, 95% CI 2.83-6.78, p< 0.001), VATz >0 & aSATz< 0 (cOR 4.43, 95% CI 2.85-7.11, p< 0.001), and LFz >0 & aSATz< 0 (cOR 2.47, 95% CI 1.62-3.83, p< 0.001). When adjusted for sex, age, and BMI, those with VATz >0 and/or LFz >0 remained significant. For incident CVD, the strongest associations were found for VATz >0 & LFz< 0 (crude hazard ratio (cHR) 1.53, 95% CI 1.34-1.76, p< 0.001) and VATz >0 & aSATz< 0 (cHR 1.54, 95% CI 1.34-1.76, p< 0.001). When adjusted for sex, age, and BMI, only VATz >0 & LFz< 0 remained significant. Excessive accumulation of VAT in relation to BMI (VATz >0) was consistently linked to both T2D and CVD. Excessive accumulation of LF in relation to BMI (LFz >0) was linked to T2D only. Groups with skewed fat distribution patterns showed the highest risk for incident CVD (VATz >0 & LFz< 0 and VATz >0 & aSATz< 0) and T2D (VATz >0 & aSATz< 0). Descriptions of body fat distribution pattern could inform diagnosis and treatment strategies for obesity and related conditions.