BackgroundDiabetes is a growing health concern in developing countries, with Cameroon population having an estimated 6% affected. Of note, hospital attendees appear to be increasing all over the country, with fluctuating numbers throughout the annual calendar. The aim of the study was to investigate the relationship between diabete hospitalization admission rates and climate variations in Yaounde.MethodsA retrospectively designed study was conducted in four health facilities of Yaounde (Central Hospital, University teaching hospital, Biyem-Assi and Djoungolo District Hospitals), using medical records from 2000 to 2008. A relationship between diabetes (newly diagnosed diabetes patients or decompensated diabetics) hospitalization admissions and climate variations was determined using the “2000–2008” national meteorological database (precipitation and temperature).ResultsThe monthly medians of precipitation and temperature were 154mm and 25 °C, respectively. The month of October received 239mm of precipitation. The monthly medians of diabetic admissions rates (newly diagnosed or decompensated diabetes patients) were 262 and 72 respectively. October received 366 newly diagnosed diabetics and 99 decompensated diabetics. Interestingly, diabetic hospitalization admissions rates were higher during the rainy (51 %, 1633/3232) than the dry season, though the difference was non-significant. The wettest month (October) reported the highest cases (10 %, 336/3232) corresponding to the month with the highest precipitation level (239mm). Diabetes hospitalization admissions rates varied across health facilities [from 6 % (189/3232) in 2000 to 15 % (474/3232) in 2008].ConclusionDiabetes is an important epidemiological disease in the city of Yaounde. The variation in the prevalence of diabetes is almost superimposed to that of precipitation; and the prevalence seems increasing during raining seasons in Yaoundé.

The objective of the study was to evaluate the spatio-temporal impacts of seasonal rainfall and urban population growth on the variations in normalized difference vegetation index (NDVI) in north Cameroon, which includes climates from south to north, the Sudanese and Sahelian climates. To this end, 48 points of measured rainfall were interpolated based on the kriging method at a spatial resolution of 8 km in accordance with the NOAA-AVHRR NDVI data set. Relationships between rainfall and NDVI, on the one hand, and urban population growth and NDVI, on the other, were analysed considering the 79 administrative units (AUs) in Cameroon. Seasonal (rainy season) variations of the vegetation cover were stud-ied for the period 1987-2002 using the NDVI product at 8 km (NOAA-AVHRR) and 1 km (SPOT-VEGETATION) of spatial resolution. This article emphasizes the importance of the urban signal for the NDVI studies at finer scales, specifically in tropical areas.

No abstract

No abstract

No abstract