8 research outputs found

    Primary nocturnal enuresis in children presenting to the outpatient Department of Khartoum ENT Teaching Hospital with adenotonsillar hypertrophy

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    ABSTRACT Background: Primary Nocturnal Enuresis (PNE) is a common health problem seen in childhood. It has many risk factors that can play a role in its etiology including an untreated adenotonsillar hypertrophy (ATH) which is the most common etiology of obstructed sleep apnea (OSA). Objective: This study was undertaken to determine the prevalence of PNE in children with adenotonsillar hypertrophy (ATH) and to reveal the relation of PNE with severity of ATH in Sudanese children. Material and Methods: A total of two hundreds and ninety patients diagnosed with ATH were recruited in this prospective study with age ranging from 5 to 15 years. The study was conducted in Khartoum ENT teaching hospital from Jan. to May 2012. Results: From 290 patients with adenotonsillar hypertrophy, 114 (39.3%) were proved to have primary nocturnal enuresis. From these 114 children, 86 (75.4%) were wetting their beds at least once a week. Almost half of the study population had grade 3 adenotonsillar hypertrophy. However, no statistically significant relationship was found between frequency of primary nocturnal enuresis and grading of adenotonsillar hypertrophy. Conclusion: Prevalence of primary nocturnal enuresis in children with adenotonsillar hypertrophy was high (40%). Children presenting with nocturnal enuresis should be evaluated for adenotonsillar hypertrophy. There is no association between primary nocturnal enuresis and severity of upper airway obstruction caused by adenotonsillar hypertrophy

    Aid on Demand: African Leaders and the Geography of China's Foreign Assistance

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    This article investigates whether China’s foreign aid is particularly prone to political capture by political leaders of aid-receiving countries. Specifically, we examine whether more Chinese aid is allocated to the political leaders’ birth regions and regions populated by the ethnic group to which the leader belongs, controlling for indicators of need and various fixed effects. We have collected data on 117 African leaders’ birthplaces and ethnic groups and geocoded 1,650 Chinese development finance projects across 3,097 physical locations committed to Africa over the 2000-2012 period. Our econometric results show that current political leaders’ birth regions receive substantially larger financial ows from China than other regions. On the contrary, when we replicate the analysis for the World Bank, our regressions with region-fixed effects show no evidence of such favoritism. For Chinese and World Bank aid alike, we also find no evidence that African leaders direct more aid to areas populated by groups who share their ethnicity, when controlling for region-fixed effects

    Telegram, 1937 June 12, to Amelia Earhart

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    Sudan government telegraph to Amelia Earhart, containing wind and weather information, June 12, 193

    Food Security in Sudan: Policies and Strategies

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    2012 Social Accounting Matrix (SAM) for Sudan

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    The 2012 Social Accounting Matrix (SAM) for the Sudan, with a special focus on agriculture, water, and energy, is built using data from domestic sources in the Sudan, including the Central Bureau of Statistics, the Ministry of Agriculture, the Ministry of Finance and Economic Planning, and the Central Bank of Sudan, besides other external sources. Major data sets used include the 2012 National Accounts and Trade Statistics of the CBS, the 53rd Annual Report of the Central Bank of the Sudan, the 2011 Labor Force Survey, the 2009 Household Income and Expenditure Survey, the 2009-2012 Agricultural Production Cost Survey, and the 2005 Industrial Survey. Data from external sources are used to complement national sources. These sources include IMF studies on government finances, FAO reports and data on agriculture, and ILO reports on labor. The SAM distinguishes between agricultural activities based on modes of irrigation, energy based on its major source, and water based on modes of production and types of uses. Land is divided into irrigated and non-irrigated, while natural water resources are added in a separate account. Households are categorized by state, location (rural and urban), and income quintiles. Labor accounts are differentiated based on location (rural and urban), skill level, and gender
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