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Recent reports of localized areas of increased fat deposition and fat loss in HIV-infected patients, as well as changes in serum levels of metabolites and hormones, have led to the proposal that a lipodystrophy syndrome is occurring. Although the lipodystrophy syndrome is often attributed to the use of HIV protease inhibitor (PI) agents, there is no standard definition of the syndrome, attribution is often by self-report, and prevalence estimates vary widely. In addition, the association of lipodystrophy with use of PI, as well as the interrelationship of body composition changes with metabolic abnormalities, have been challenged. In this review we describe prevalence estimates derived from a review of the English language medical literature with regard to regional increases in fat (lipohypertrophy: 1-56%), regional loss of fat (lipoatrophy; 1-24%), and pooled ‚lipodystrophy‚ syndromes (2-83%). The wide range of prevalence estimates may be due to differing definitions, methods (e.g. self-report versus objective measurements) and patient populations. The relationship of changes in body composition to use of PI is increasingly less clear, and analysis reveals multiple other potential contributing factors such as other classes of antiretroviral agents, duration of antiretroviral therapy, change in viral load, body weight, age, and gender. There are few data on the association of individual changes in fat redistribution with each other. Moreover, the association between fat distribution and metabolic changes such as hyperlipidemia and insulin resistance is also increasingly questioned; PI may play an independent role in metabolic changes. Future studies must examine each localized abnormality in fat distribution discretely, using objective measurements rather than subjective report. Discernment of contributing cofactors is critical and must include, among others, complete medication history, viral load, body weight, age and gender. Because some of the reported changes occur in non-HIV-infected individuals, it is important to calculate the excess prevalence above control populations. The association of individual changes with each other and with contributing factors must be analyzed first, before the definition of a syndrome or of multiple syndromes can be made.