No abstract

Municipal street sweepers are exposed to large amount of dusts, microorganisms, toxins and automobile exhaust pollution. Chronic inhalation of such particulate matter has the potential to impair their pulmonary functions. The strict adherence to the standards and norms for the management of municipal solid wastes to reduce occupational health hazards in developing countries India is still a matter of concern. This study conducted among the municipal sweepers of Chitradurga district, compared the effects of chronic exposure to dust on the pulmonary function using spirometry test. This study also assessed the effects of smoking and irregular usage of protection masks, and compared the results with the healthy controls. Respiratory symptoms of cough (30%), chest pain (17.5%), catarrah and sneezing (21.5%) were found to be in higher percentage among the municipal street sweepers than the controls. Only 20% of participants municipal street sweepers used personal protective measures, wearing protective masks, regularly in the past 1 year, during sweeping streets. It was found that FEV1, FEV1/FVC, PEFR and FEF 25%-75% were significantly lesser among non-smoker street sweepers, when compared with that of non-smoking controls. Similarly these PFT values were significantly reduced among the smoker street sweepers and among the sweepers who didn't use protective masks while sweeping. This study highlights the occupational hazard faced by municipal sweepers and attempts to emphasize on importance of usage of protective masks.

Hypertension (HTN) is a major risk factor for cardiovascular diseases. At least 45% of deaths due to heart disease and 51% of deaths due to stroke are the result of hypertension. According to research on the prevalence and absolute burden of HTN in India, HTN positively correlated with age and was present in 20.6% of men and 20.9% of women. It was estimated that this trend will increase to 22.9% and 23.6% for men and women, respectively, by 2025. Controlling blood pressure is therefore important to lower both morbidity and mortality. Computer-aided diagnosis (CAD) is a noninvasive technique which can determine subtle myocardial structural changes at an early stage. In this work, we show how a multi-resolution analysis-based CAD system can be utilized for the detection of early HTN-induced left ventricular heart muscle changes with the help of ultrasound imaging. Firstly, features were extracted from the ultrasound imagery, and then the feature dimensions were reduced using a locality sensitive discriminant analysis (LSDA). The decision tree classifier with contourlet and shearlet transform features was later employed for improved performance and maximized accuracy using only two features. The developed model is applicable for the evaluation of cardiac structural alteration in HTN and can be used as a standalone tool in hospitals and polyclinics.