Types of Corruption in Small and Micro Enterprises (SMEs) in Ibadan, Nigeria

Corruption is a phenomenon that manifests in various types and forms especially among operators of Small and Micro Enterprises (SMEs). Many actions of the operators which constitute corrupt practices often tend to be overlooked in spite of their grave consequences for the success SMEs in Nigeria. The fight against corruption in Nigeria is more concentrated in the formal sector. This study was, therefore, designed to investigate various forms in which corrupt practices are carried out among Small and Micro Enterprises in Ibadan, Nigeria. Business owners, their employees, apprentices and consumers constituted the study population. Primary data were collected using questionnaire administered on 200 business owners, 150 employees and 150 apprentices randomly chosen in five business districts in Ibadan; and the conduct of 10 in-depth interviews with purposively selected participants. Quantitative data were analysed at uni-variate level using simple percentages and frequencies while qualitative data were content analysed. Findings from the study revealed that corrupt practices were rampant among actors in SMEs and the common types of corrupt practices included stealing (60%), deception of customers (78.4%), tax evasion (62%), sale of fake products (76%), sale of expired products (65.2%), tampering with measurement scales (69.6%), bribery (82.4%), and poor service delivery (73%). The study concludes that the level of corruption in SMEs calls for concern and government should extend the fight against corruption to the informal sector in Nigeria

Health impact assessment of particulate pollution in Tallinn using fine spatial resolution and modeling techniques

<p>Abstract</p> <p>Background</p> <p>Health impact assessments (HIA) use information on exposure, baseline mortality/morbidity and exposure-response functions from epidemiological studies in order to quantify the health impacts of existing situations and/or alternative scenarios. The aim of this study was to improve HIA methods for air pollution studies in situations where exposures can be estimated using GIS with high spatial resolution and dispersion modeling approaches.</p> <p>Methods</p> <p>Tallinn was divided into 84 sections according to neighborhoods, with a total population of approx. 390 000 persons. Actual baseline rates for total mortality and hospitalization with cardiovascular and respiratory diagnosis were identified. The exposure to fine particles (PM_2.5) from local emissions was defined as the modeled annual levels. The model validation and morbidity assessment were based on 2006 PM₁₀or PM_2.5levels at 3 monitoring stations. The exposure-response coefficients used were for total mortality 6.2% (95% CI 1.6–11%) per 10 μg/m³increase of annual mean PM_2.5concentration and for the assessment of respiratory and cardiovascular hospitalizations 1.14% (95% CI 0.62–1.67%) and 0.73% (95% CI 0.47–0.93%) per 10 μg/m³increase of PM₁₀. The direct costs related to morbidity were calculated according to hospital treatment expenses in 2005 and the cost of premature deaths using the concept of Value of Life Year (VOLY).</p> <p>Results</p> <p>The annual population-weighted-modeled exposure to locally emitted PM_2.5in Tallinn was 11.6 μg/m³. Our analysis showed that it corresponds to 296 (95% CI 76528) premature deaths resulting in 3859 (95% CI 10236636) Years of Life Lost (YLL) per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.64 (95% CI 0.17–1.10) years. While in the polluted city centre this may reach 1.17 years, in the least polluted neighborhoods it remains between 0.1 and 0.3 years. When dividing the YLL by the number of premature deaths, the decrease in life expectancy among the actual cases is around 13 years. As for the morbidity, the short-term effects of air pollution were estimated to result in an additional 71 (95% CI 43–104) respiratory and 204 (95% CI 131–260) cardiovascular hospitalizations per year. The biggest external costs are related to the long-term effects on mortality: this is on average €150 (95% CI 40–260) million annually. In comparison, the costs of short-term air-pollution driven hospitalizations are small €0.3 (95% CI 0.2–0.4) million.</p> <p>Conclusion</p> <p>Sectioning the city for analysis and using GIS systems can help to improve the accuracy of air pollution health impact estimations, especially in study areas with poor air pollution monitoring data but available dispersion models.</p

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Genetic studies of body mass index yield new insights for obesity biology

Note: A full list of authors and affiliations appears at the end of the article. Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.</p