Major sociodemographic changes have occurred in Egypt to promote the development of noncommunicable diseases. We have performed a cross-sectional, population-based survey of persons > or = 20 years of age in Cairo and surrounding rural villages to describe the prevalence of diabetes risk factors, diagnosed diabetes, previously undiagnosed diabetes, and impaired glucose tolerance by age, sex, rural and urban residence, and socioeconomic status (SES). In the survey, we identified 6052 eligible households: 76% of household respondents completed a household examination and 72% of selected household respondents subsequently completed a medical examination. Exercise was assessed by questionnaire; adiposity by measurement of height, weight, and girths; and diabetes by history and 2-h 75 g oral glucose tolerance test. In rural areas, 52% of persons > or = 20 years of age were sedentary, 16% were obese, and 4.9% had diabetes. In lower SES urban areas, 73% were sedentary, 37% were obese, and 13.5% had diabetes. In higher SES urban areas, 89% were sedentary, 49% were obese, and 20% had diabetes. The combined prevalence of diagnosed and undiagnosed diabetes in the Egyptian population > or = 20 years of age was estimated to be 9.3%. Approximately half the diabetes was diagnosed and the other half was previously undiagnosed. The prevalence of diabetes in Egypt is high, and the gradient in risk factors and disease from rural to urban areas and in urban areas from lower to higher SES suggest that diabetes is a major, emerging clinical and public health problem in Egypt.

We performed a cross-sectional, population-based survey of persons 20 years of age and older living in Cairo and surrounding rural villages. The purpose was to describe glycaemic control and the prevalence of microvascular and neuropathic complications among Egyptians with diagnosed diabetes, previously undiagnosed diabetes, impaired glucose tolerance, and normal glucose tolerance. A total of 6052 households were surveyed. The response rate was 76% for the household survey and 72% for the medical examination. Among people with previously diagnosed diabetes, mean haemoglobin A1c, was 9.0%. Forty-two per cent had retinopathy, 21% albuminuria, and 22% neuropathy. Legal blindness was prevalent (5%) but clinical nephropathy (7%) and foot ulcers (1%) were uncommon in persons with diagnosed diabetes. Among people with diagnosed diabetes, microvascular and neuropathic complications were associated with hyperglycaemia. Retinopathy was also associated with duration of diabetes; albuminuria with hypertension and hypercholesterolaemia; and neuropathy with age, female sex, and hypercholesterolaemia. Albuminuria was as common in people with previously undiagnosed diabetes (22%) as those with diagnosed disease (21%). Mean haemoglobin A1c was lower (7.8%) and retinopathy (16%) and neuropathy (14%) were less prevalent in people with previously undiagnosed disease. Ocular conditions, blindness, and neuropathy were prevalent in the non-diabetic population. The microvascular and neuropathic complications of diabetes are a major clinical and public health problem in Egypt.

The onset of diabetes relative to clinical diagnosis was estimated in Egyptians with noninsulindependent diabetes mellitus (NIDDM) based on the relationship between retinopathy and duration of diabetes. Between July 1992 and October 1993 the Diabetes in Egypt (DIE) Project performed a cross-sectional, population-based survey with clinical and laboratory follow-up to describe the prevalence of microvascular, neuropathic, and macrovascular complications among Egyptians a 20 years of age with diagnosed diabetes, previously undiagnosed diabetes, impaired glucose tolerance, and normal glucose tolerance. The sample of persons with diabetes diagnosed prior to the survey had medical examinations which included a dilated eye examination and retinal photographs. Generalized linear models were used to relate the probability of retinopathy to duration of diabetes. Among 218 persons with diabetes diagnosed prior to the DIE project, 87 (40 %) had diabetic retinopathy. The onset of retinopathy was estimated to occur 2.6 years (p = 0.04) prior to clinical diagnosis. The estimated annual incidence of retinopathy was 5 % and the estimated prevalence at the time of clinical diagnosis of diabetes was 12 %. On the basis of reports that retinopathy does not occur until approximately 5 years after the development of diabetes, the onset of NlDDM was estimated to occur 7.6 years prior to its clinical diagnosis. This estimate of the onset of NIDDM in Egyptians is comparable to other estimates reported for US and Australian populations. KEY WORDS Non-insulindependent diabetes mellitus Diagnosis Retinopathy Epidemiology Egypt Patients and Methods The method of identification and description of the study Population has been reported elsewhere.' Between July 1992 and October 1993, the Diabetes in Egypt (DIE)

Software effort estimation accuracy is a key factor in effective planning, controlling, and delivering a successful software project within budget and schedule.The overestimation and underestimation both are the key challenges for future software development, henceforth there is a continuous need for accuracy in software effort estimation. The researchers and practitioners are striving to identify which machine learning estimation technique gives more accurate results based on evaluation measures, datasets and other relevant attributes. The authors of related research are generally not aware of previously published results of machine learning effort estimation techniques. The main aim of this study is to assist the researchers to know which machine learning technique yields the promising effort estimation accuracy prediction in software development. In this article, the performance of the machine learning ensemble and solo techniques are investigated on publicly and non-publicly domain datasets based on the two most commonly used accuracy evaluation metrics. We used the systematic literature review methodology proposed by Kitchenham and Charters. This includes searching for the most relevant papers, applying quality assessment (QA) criteria, extracting data, and drawing results. We have evaluated a state-of-the-art accuracy performance of 35 selected studies (17 ensemble, 18 solo) using mean magnitude of relative error and PRED (25) as a set of reliable accuracy metrics for performance evaluation of accuracy among two techniques to report the research questions stated in this study. We found that machine learning techniques are the most frequently implemented in the construction of ensemble effort estimation (EEE) techniques. The results of this study revealed that the EEE techniques usually yield a promising estimation accuracy than the solo techniques.