South Africa is a middle income country, as defined by the World Bank 
, and it shares with other developing African nations key epidemiological features of the nutritional transition. Thus, the prevalence of obesity is high, particularly in urban areas 
and is more prevalent in females than males 
. Therefore, the current investigation was performed in an urban population of middle-aged, African females residing in the Soweto-Johannesburg conurbation, a group that would be presumed to have a high prevalence of obesity and co-morbid diseases. Our results clearly confirm that this population does have a high prevalence of obesity, metabolic syndrome and related disorders and further emphasises the high burden of disease imparted by obesity-related disorders within low- or middle-income countries 
The high prevalence of metabolic syndrome within this study cohort is largely driven by the high levels of abdominal obesity and the low fasting HDL serum concentrations, as reported in other epidemiological surveys of metabolic syndrome in African populations 
. The very low prevalence of high LDL-cholesterol serum levels in this study population (2.8%) is not unexpected. It has previously been shown that LDL levels are lower in African compared to European and Indian populations within South Africa 
The prevalence of obesity in this population is 50%, which is the highest yet recorded in an indigenous, sub-Saharan African population. Obesity is known to be increasing in the developing world as ‘westernization’ of dietary intakes and urbanisation of former rural populations lead to significant changes in lifestyle 
. Thus, studies in South Africa have shown that dietary fat intake has increased significantly over the preceding 5 decades, and that urbanisation is associated with a higher prevalence of obesity 
. The genetic aetiology of obesity in African populations is currently uncertain, with most genome-wide association studies having been conducted in European cohorts. It is therefore not possible for us to rule out a genetic component to the high BMIs observed within our study population. Type 2 diabetes and impaired fasting glucose were also found to exist at high levels within this population group. This may largely be due to the high prevalence of obesity, particularly abdominal obesity, and the age of the study cohort.
The high frequency at which obesity and co-morbid diseases occur in this study population further confirms the growing problem of diseases of lifestyle in low and middle-income countries 
. Across sub-Saharan Africa the prevalence of diabetes 
, hypertension 
and coronary artery disease 
are known to be increasing and this is mirrored by rising levels of obesity 
. The financial and social burden of non-communicable diseases within resource limited nations is leading to the further deterioration of over-stretched public health services that are already compromised by an epidemic of communicable diseases 
. Intervention at the primary health care level is therefore essential. However, because obesity is not readily acknowledged as a health problem in some African populations 
, lifestyle modification methods, as developed in higher income countries, may not be applicable in this environment without extensive education programs.
The IDF 
and the new harmonised guidelines 
for the diagnosis of the metabolic syndrome both include waist cut-off points for different ethnic groups and recommend that for sub-Saharan African populations the European waist cut-off points are used. However, it is known that for a given waist circumference African females have less visceral fat than European females and it has therefore been suggested that if waist threshold levels are defined by visceral fat mass then they should be different for these 2 population groups 
. Only one other large epidemiological study has been undertaken to determine the optimal waist cut-off points for sub-Saharan African subjects 
. This study was also performed in South Africa, in a rural cohort of 947 male and female subjects and demonstrated that for diagnosis of the metabolic syndrome, a waist circumference cut point of 92 cm for women, was optimal. This figure, obtained using ROC curve analysis, is very similar to that reported in the present study (91.5 cm). However, it is important to note that there are considerable differences between the populations used in these two studies. The present investigation used an urban population of female subjects with a minimum age of 28 years and an obesity prevalence of 50.1%, whereas the study of Motala et al.
analysed female subjects from a rural environment with a minimum age of 16 years and an obesity prevalence of 22.6%. Despite these differences, almost the same waist cut points were obtained for diagnosing the metabolic syndrome. This suggests that, irrespective of differences in lifestyle and obesity prevalence levels, the same cut point for waist circumference can be applied across these population groups. It should also be noted that in a smaller study of urban African male (n
80) and female (n
93) teachers, ROC curve analysis showed that the optimal waist cut point for the diagnosis of the metabolic syndrome in females was 98 cm 
A very important conclusion of this study, which is supported by data from the two investigations discussed above, is that the waist circumference cut-point currently being utilised for the diagnosis of metabolic syndrome in sub-Saharan African females (80 cm) 
is too low and will therefore give an over estimation of prevalence. This is demonstrated in the current study where, using the waist cut point of 91.5 cm incorporated into the new harmonised guidelines 
, the prevalence of metabolic syndrome is 26.2% compared to 42.1% when using the cut point of 80 cm. If one uses the current IDF criteria for diagnosis, then the prevalence of metabolic syndrome is 40.1%. This hypothetical fall in the prevalence of metabolic syndrome may have important implications for any national intervention programs aimed at subjects with an elevated waist circumference, as it would lead to a reduction in the number of subjects requiring therapy. This would be important in low and middle income countries such as South Africa, where financial resources and infrastructure are constrained. It would also ensure that therapies are targeted to those at greatest risk of developing CVD or diabetes.
The finding that the waist cut-point currently recommended for the diagnosis of the metabolic syndrome is not applicable to sub-Saharan African populations highlights the inappropriate use of guidelines derived from non-African study cohorts for the diagnosis of diseases within Africa. This is further exemplified by a study showing that an HbA1c cut point of 6.5% for the diagnosis of diabetes, as derived from studies in which no sub-Saharan populations were included 
, was not applicable within a mixed ancestry group from South Africa 
The rising prevalence of obesity 
and co-morbid diseases 
within sub-Saharan Africa suggests that an inevitable rise in the prevalence of the metabolic syndrome must also be occurring. Furthermore, the HIV epidemic within these nations may also be contributing to the high prevalence of metabolic diseases since African-based studies have shown that HIV and anti-retroviral therapy are both linked to metabolic dysfunction 
. Given these circumstances, the determination of the appropriate waist cut-point for diagnosing metabolic syndrome in sub-Saharan populations becomes vitally important as it will allow for a more accurate estimation of the changing prevalence levels of the syndrome over time and in response to interventions.
An interesting and important feature of our study is that the prevalence and the risk of a number of different metabolic disorders increase at a very similar waist circumference cut-point. This may be related to visceral adiposity because in previous studies this body fat depot has been linked to all the metabolic variables analysed in the current investigation 
. Furthermore, it has been suggested that there is a level of visceral fat above which there is increased cardiovascular risk 
, and it is therefore possible that in African females a waist circumference of 87.6–91.5 cm equates to this visceral fat level. There is an alternative hypothesis which suggests that the insulin sensitivity of the subcutaneous fat depot determines the threshold of triglyceride deposition within that tissue 
. Once this threshold is exceeded (equivalent to a waist circumference of 87.6–91.5 cm?), triglycerides will be deposited at other sites including the visceral adipose depot, skeletal muscle and liver, and it is this ectopic fat deposition that leads to an increased risk of metabolic disease.
Waist circumference has a relatively poor sensitivity and specificity for diagnosing metabolic disorders, as shown in this and other investigations 
. Waist circumference is a proxy indictor of visceral fat mass 
and it has been shown that the latter anthropometric variable is a better diagnostic criterion for identifying metabolic syndrome than the former 
. However, the measurement of waist circumference is far simpler and less expensive than that of visceral fat and is therefore the preferred anthropometric component in all diagnostic guidelines for metabolic syndrome.
There are some limitations to this study. Lipid, glucose and insulin levels were not obtained in all subjects, however there were no differences in anthropometric variables between subjects who did or did not have these analytes measured. Despite metabolic data not being obtained for all subjects, the study was still sufficiently powered to demonstrate that the area under the ROC curve for metabolic syndrome, insulin resistance, hypertension, hypo-high density lipoproteinaemia and dysglycaemia were statistically significantly greater than 0.5. It has been suggested that the ability to statistically demonstrate that the area under the ROC curve is greater than 0.5 is the most appropriate way to determine the correct sample size for a ROC curve analysis 
. Another limitation of the study is that the population investigated was a stable, urban group and therefore may not be comparable to rural populations. However, as previously noted, a study performed in a rural South African population did obtain a very similar optimal waist cut point for the diagnosis of metabolic syndrome to that obtained in the current study 
. Our study only included females and therefore further investigations must be performed in male subjects.
In conclusion, urban, middle-aged African females have very high prevalence levels of abdominal obesity, type 2 diabetes and metabolic syndrome. The reason for the high prevalence of these diseases is not known however, lifestyle factors may play a major role but a genetic aetiology cannot be ruled out. The determination, by ROC curve analysis, of optimal waist circumference cut points for the diagnosis of the metabolic syndrome demonstrated that a value of 91.5 cm would be more appropriate than the currently recommended level of 80 cm. Further investigations are necessary to determine whether this cut point can also be used in other sub-Saharan African populations.