Prevalence and Determinants of Obesity among Primary School Children in Dar es Salaam, Tanzania.

Childhood obesity has increased dramatically and has become a public health concern worldwide. Childhood obesity is likely to persist through adulthood and may lead to early onset of NCDs. However, there is paucity of data on obesity among primary school children in Tanzania. This study assessed the prevalence and determinants of obesity among primary school children in Dar es Salaam. A cross sectional study was conducted among school age children in randomly selected schools in Dar es Salaam. Anthropometric and blood pressure measurements were taken using standard procedures. Body Mass Index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m2). Child obesity was defined as BMI at or above 95th percentile for age and sex. Socio-demographic characteristics of children were determined using a structured questionnaire. Logistic regression was used to determine association between independent variables with obesity among primary school children in Dar es Salaam. A total of 446 children were included in the analysis. The mean age of the participants was 11.1±2.0 years and 53.1% were girls. The mean BMI, SBP and DBP were 16.6±4.0 kg/m2, 103.9±10.3mmHg and 65.6±8.2mmHg respectively. The overall prevalence of child obesity was 5.2% and was higher among girls (6.3%) compared to boys (3.8%). Obese children had significantly higher mean values for age (p=0.042), systolic and diastolic blood pressures (all p<0.001). Most obese children were from households with fewer children (p=0.019) and residing in urban areas (p=0.002). Controlling for other variables, age above 10 years (AOR=3.3, 95% CI=1.5-7.2), female sex (AOR=2.6, 95% CI=1.4-4.9), urban residence (AOR=2.5, 95% CI=1.2-5.3) and having money to spend at school (AOR=2.6, 95% CI=1.4-4.8) were significantly associated with child obesity. The prevalence of childhood obesity in this population was found to be low. However, children from urban schools and girls were proportionately more obese compared to their counterparts. Primary preventive measures for childhood obesity should start early in childhood and address socioeconomic factors of parents contributing to childhood obesity

Mosquito Abundance, Bed net Coverage and Other Factors Associated with Variations in Sporozoite Infectivity Rates in Four Villages of Rural Tanzania.

Entomological surveys are of great importance in decision-making processes regarding malaria control strategies because they help to identify associations between vector abundance both species-specific ecology and disease intervention factors associated with malaria transmission. Sporozoite infectivity rates, mosquito host blood meal source, bed net coverage and mosquito abundance were assessed in this study. A longitudinal survey was conducted in four villages in two regions of Tanzania. Malaria vectors were sampled using the CDC light trap and pyrethrum spray catch methods. In each village, ten paired houses were selected for mosquitoes sampling. Sampling was done in fortnight case and study was undertaken for six months in both Kilimanjaro (Northern Tanzania) and Dodoma (Central Tanzania) regions. A total of 6,883 mosquitoes were collected including: 5,628 (81.8%) Anopheles arabiensis, 1,100 (15.9%) Culex quinquefasciatus, 89 (1.4%) Anopheles funestus, and 66 (0.9%) Anopheles gambiae s.s. Of the total mosquitoes collected 3,861 were captured by CDC light trap and 3,022 by the pyrethrum spray catch method. The overall light trap: spray catch ratio was 1.3:1. Mosquito densities per room were 96.5 and 75.5 for light trap and pyrethrum spray catch respectively. Mosquito infectivity rates between villages that have high proportion of bed net owners and those without bed nets was significant (P < 0.001) and there was a significant difference in sporozoite rates between households with and without bed nets in these four villages (P < 0.001). Malaria remains a major problem in the study areas characterized as low transmission sites. Further studies are required to establish the annual entomological inoculation rates and to observe the annual parasitaemia dynamics in these communities. Outdoor mosquitoes collection should also be considered

The role of cow urine in the oviposition site preference of culicine and Anopheles mosquitoes

<p>Abstract</p> <p>Background</p> <p>Chemical and behavioural ecology of mosquitoes plays an important role in the development of chemical cue based vector control. To date, studies available have focused on evaluating mosquito attractants and repellents of synthetic and human origins. This study, however, was aimed at seasonal evaluation of the efficiency of cow urine in producing oviposition cues to <it>Anopheles gambiae </it>s.l. and <it>Culex quinquefasciatus </it>in both laboratory and field conditions.</p> <p>Methods</p> <p>Oviposition response evaluation in laboratory conditions was carried out in mosquito rearing cages. The oviposition substrates were located in parallel or in diagonal positions inside the cage. Urine evaluation against gravid females of <it>An. arabiensis </it>and <it>Cx. quinquefasciatus </it>was carried out at Day 1, Day 3 and Day 7. Five millilitres (mls) of cow urine was added to oviposition substrate while de-chlorinated water was used as a control. In field experiments, 500 mls of cow urine was added in artificial habitats with 2500 mls of de-chlorinated water and 2 kgs of soil. The experiment was monitored for thirty consecutive days, eggs were collected daily from the habitats at 7.00 hrs. Data analysis was performed using parametric and non-parametric tests for treatments and controls while attraction of the oviposition substrate in each species was presented using Oviposition Activity Index (OAI).</p> <p>Results</p> <p>The OAI was positive with ageing of cattle urine in culicine species in both laboratory and field experiments. The OAI for anopheline species was positive with fresh urine. The OAI during the rainy season was positive for all species tested while in the dry season the OAI for culicine spp and <it>Anopheles gambiae </it>s.l., changed with time from positive to negative values.</p> <p>Based on linear model analysis, seasons and treatments had a significant effect on the number of eggs laid in habitats, even though the number of days had no effect.</p> <p>Conclusion</p> <p>Oviposition substrates treated with cow urine in both laboratory and field conditions have shown that cow urine left to age from 1-7 days has an influence on oviposition behavioural response in mosquitoes. The analysis of microbial colonies for decaying urine should be investigated along with its associated by-products.</p

Bioavailability of Iron, Zinc, Phytate and Phytase Activity during Soaking and Germination of White Sorghum Varieties

The changes in phytate, phytase activity and in vitro bioavailability of iron and zinc during soaking and germination of three white sorghum varieties (Sorghum bicolor L. Moench), named Dorado, Shandweel-6, and Giza-15 were investigated. Sorghum varieties were soaked for 20 h and germinated for 72 h after soaking for 20 h to reduce phytate content and increase iron and zinc in vitro bioavailability. The results revealed that iron and zinc content was significantly reduced from 28.16 to 32.16% and 13.78 to 26.69% for soaking treatment and 38.43 to 39.18% and 21.80 to 31.27% for germination treatments, respectively. Phytate content was significantly reduced from 23.59 to 32.40% for soaking treatment and 24.92 to 35.27% for germination treatments, respectively. Phytase enzymes will be activated during drying in equal form in all varieties. The results proved that the main distinct point is the change of phytase activity as well as specific activity during different treatment which showed no significant differences between the varieties used. The in vitro bioavailability of iron and zinc were significantly improved as a result of soaking and germination treatments

Malaria in Africa: Vector Species' Niche Models and Relative Risk Maps

A central theoretical goal of epidemiology is the construction of spatial models of disease prevalence and risk, including maps for the potential spread of infectious disease. We provide three continent-wide maps representing the relative risk of malaria in Africa based on ecological niche models of vector species and risk analysis at a spatial resolution of 1 arc-minute (9 185 275 cells of approximately 4 sq km). Using a maximum entropy method we construct niche models for 10 malaria vector species based on species occurrence records since 1980, 19 climatic variables, altitude, and land cover data (in 14 classes). For seven vectors (Anopheles coustani, A. funestus, A. melas, A. merus, A. moucheti, A. nili, and A. paludis) these are the first published niche models. We predict that Central Africa has poor habitat for both A. arabiensis and A. gambiae, and that A. quadriannulatus and A. arabiensis have restricted habitats in Southern Africa as claimed by field experts in criticism of previous models. The results of the niche models are incorporated into three relative risk models which assume different ecological interactions between vector species. The “additive” model assumes no interaction; the “minimax” model assumes maximum relative risk due to any vector in a cell; and the “competitive exclusion” model assumes the relative risk that arises from the most suitable vector for a cell. All models include variable anthrophilicity of vectors and spatial variation in human population density. Relative risk maps are produced from these models. All models predict that human population density is the critical factor determining malaria risk. Our method of constructing relative risk maps is equally general. We discuss the limits of the relative risk maps reported here, and the additional data that are required for their improvement. The protocol developed here can be used for any other vector-borne disease

The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the <it>An. gambiae </it>complex. <it>Anopheles gambiae </it>is one of four DVS within the <it>An. gambiae </it>complex, the others being <it>An. arabiensis </it>and the coastal <it>An. merus </it>and <it>An. melas</it>. There are a further three, highly anthropophilic DVS in Africa, <it>An. funestus</it>, <it>An. moucheti </it>and <it>An. nili</it>. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed.</p> <p>Results</p> <p>A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method.</p> <p>Conclusions</p> <p>The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: <it>Anopheles </it>(<it>Cellia</it>) <it>arabiensis</it>, <it>An. </it>(<it>Cel.</it>) <it>funestus*</it>, <it>An. </it>(<it>Cel.</it>) <it>gambiae</it>, <it>An. </it>(<it>Cel.</it>) <it>melas</it>, <it>An. </it>(<it>Cel.</it>) <it>merus</it>, <it>An. </it>(<it>Cel.</it>) <it>moucheti </it>and <it>An. </it>(<it>Cel.</it>) <it>nili*</it>, and in the European and Middle Eastern Region: <it>An. </it>(<it>Anopheles</it>) <it>atroparvus</it>, <it>An. </it>(<it>Ano.</it>) <it>labranchiae</it>, <it>An. </it>(<it>Ano.</it>) <it>messeae</it>, <it>An. </it>(<it>Ano.</it>) <it>sacharovi</it>, <it>An. </it>(<it>Cel.</it>) <it>sergentii </it>and <it>An. </it>(<it>Cel.</it>) <it>superpictus*</it>. These maps are presented alongside a bionomics summary for each species relevant to its control.</p