Hypothesis testing is an important activity of empirical research and evidence-based medicine. A well worked up hypothesis is half the answer to the research question. For this, both knowledge of the subject derived from extensive review of the literature and working knowledge of basic statistical concepts are desirable. The present paper discusses the methods of working up a good hypothesis and statistical concepts of hypothesis testing.

Context:The biggest challenge in implementing the primary health care principles is of equitable distribution of health care to all. The rural masses and urban slum dwellers are most vulnerable to lack of access to health care.Aim:To study access to health services among slum dwellers and rural population.Setting and Design:A cross-sectional survey in an urban slum and surrounding rural areas in field practice area of a medical college.Materials and Methods:Structured instrument along with qualitative techniques such as focus group discussions, were used to collect information on access and utilization of health services from 865 individuals of both sexes and all ages selected from urban slums, villages, and indoor and outdoor patients. Access to basic determinants of good health such as housing, water, and sanitation was also elicited. Besides, health needs based on self-reported disease conditions were compiled.Results:More than 50% of respondents were living in poor housing and insanitary conditions. Besides the burden of communicable diseases and malnutrition (especially in children), risk of lifestyle diseases as evidenced by high Body mass index in 25% of adults surveyed was found. Private medical practitioners were more accessible than government facilities. More than 60% sought treatment from private medical facilities for their own ailments (for sickness in children this proportion was 74%). People who visited government facilities were more dissatisfied with the services (30.88%) than those who visited private facilities (18.31%). This difference was significant (OR=1.99, 95% confidence interval 1.40 to 2.88; χ2 =15.95, df=1, P=0.007). The main barriers to health care identified were waiting time long, affordability, poor quality of care, distance, and attitude of health workers.Conclusion:The underprivileged in India continue to have poor access to basic determinants of good health as well as to curative services from government sources during illness.

Background:The nutritional status of under fi ve children in urban slums is an important health indicator for assessing the health status of entire population and one of the major predictors of child survival. Objective: A nutritional survey was carried out in September-October 2012 in the fi eld practice area of a medical college in Pimpri, Pune area with an objective to assess the nutritional status of under-fi ve children. Materials and Methods: All the under fi ve students in the fi eld practice area of the medical college were examined. A total of 658 children were examined. Results and Conclusion: It was observed that the prevalence of under weight 34.3% (226/654) (30.7 to 38.0 C.I.), stunting 58.7% (386/654) (54.9 to 62.4 C.I.) and wasting was 16.9%(109/654) (14.0 to 19.7 95% C.I.). The prevalence of under weight 37.6% (114/303) and stunting 61.4% (186/303) was more in girls whereas wasting was more in boys 18%. (64/355)

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Background: Recent studies in India indicate rising trends of diabetes even in rural areas. Continuous monitoring of the diabetes situation is required by repeated cross sectional studies in different parts of the country both urban rural to plan control measures. Aim: To estimate the prevalence of Type 2 diabetes in a sample of rural population and explore associations between diabetes and known risk factors. Materials and Methods: A cross sectional study was carried out in 3 villages in the rural field practice area of a medical college in Pune, India. All eligible adults of both genders were included and screened for diabetes by house to house survey. A total of 1000 subjects were examined. Physical examination included measuring height, weight, and waist hip ratio. Blood glucose was estimated using glucometer. Family history of diabetes was also elicited. Data was analysed by descriptive statistics using proportions with 95% confidence intervals. Various associations were explored using using Odds Ratio with 95% confidence intervals as applicable. Results: The prevalence of diabetes mellitus was 9.1% (91/1000; 95% CI 7.4, 11). Most cases of newly detected diabetics were in the age group 36 - 40 years. There was no association between gender and diabetes (OR = 1.38, 95% CI 0.88, 2.17). Overweight status was associated with diabetes: 38.5% (35/91) of diabetics were overweight compared to 18.6% (169/909) of non-diabetics (OR = 2.74, 95% CI 1.69, 4.41). Similarly abnormal waist hip ratio was associated with diabetes: 47.25% (43/91) of diabetics had high waist hip ratio compared with 29.59% (269/909) of non-diabetics (OR = 2.13, 95% CI 1.35, 3.37). Also family history was strongly associated with diabetes: 27.5% (25/91) of diabetics gave positive family history compared with 9.4% (85/909) of non-diabetics (OR = 3.67, 95% CI = 2.13, 6.30). Conclusion: The burden of diabetes was present in the rural population studied. The associated known risk factors were also prevalent and showed strong relationship with diabetes. Diabetes mellitus erstwhile thought to be a disease of urban life appears to be equally prevalent in the rural setting.