Objectives:To study the difference in the prevalence of hypertension and associated risk factors in urban and rural populations and the association of hypertension with various determinants.Materials and Methods:A community-based cross-sectional study was conducted in 48 villages and 15 urban wards of Jabalpur District of Central India. Nine hundred and thirty-nine individuals aged 20 years and above (624 from rural areas and 315 from urban areas) were included in the study. The prevalence of hypertension and associated cardiovascular risk factors was assessed in the urban and rural populations. A pretested questionnaire was used to collect data on socio-demographic, behavioral, and dietary factors. Anthropometric measurements of weight, height, waist and hip circumference, and blood pressure measurements were taken using the standard methodology. The glucose oxidase–peroxidase and cholesterol oxidase–cholesterol peroxidase methods were used to measure plasma glucose and serum cholesterol, respectively. Bivariate analysis was followed by multivariate analysis to detect the odds of getting hypertension with various risk factors for the urban and rural populations separately. Hypertension was defined as per Joint National Committee (JNC) - VII criteria.Results:The response rate was 97%. Overall prevalence of hypertension was 17%, with 21.4% in the urban population and 14.8% in the rural population. Significantly higher mean values of weight, height, body mass index (BMI), hip circumference (HC), waist circumference (WC), waist hip ratio (WHR), systolic blood pressure (SBP), fasting blood sugar (FBS), and serum cholesterol levels were mapped in the urban population in comparison with the rural population. Multivariate logistic regression analysis identified increasing age, parental history of hypertension, tobacco smoking, tobacco chewing, physical inactivity, high estimated per capita salt consumption, and BMI ≥27.5 kg/m2 as independent predictors for hypertension in the urban population, while in the rural population, increasing age, physical inactivity, central obesity, tobacco chewing and tobacco smoking were independent predictors for hypertension.Conclusion:The prevalence of hypertension and other cardiovascular risk factors was high in both urban and rural communities. Therefore, there is a need for comprehensive health promotion programs to encourage lifestyle modification.

Background: Hypertension is the most recognized modifiable risk factor of CVD, stroke and end stage renal disease and it is directly responsible for 57% of all stroke and 24% of all coronary heart disease related deaths in India. There is paucity of data on hypertension among tribal population. Addiction of Nicotine and some cultural practices like alcohol intake is common in tribal, which are the known risk factor for NCDs. Therefore, the study of health status of tribal communities related to hypertension, is highly desirable and essential. The objectives of the study were to determine the prevalence of hypertension and associate risk factors among non migratory tribal population. Methods: A cross sectional study was conducted from March 2015 to February 2016 among 762 adults aged 20-65 years who were non migratory residents of Mawai block of Mandla districts, and they were selected through multi stage random sampling method. Results: Hypertension prevalence was 27.1% among study population. 82.2% study subjects had never undergone for blood pressure check-up. Prevalence was significantly associated with high age group. It was slightly more among the study subjects taking mixed diet than to pure vegetarian. Smoking and alcohol intake was found to be significantly associated with hypertension. It was more prevalent among mild and sedentary workers and association was significant with BMI ≥25. Conclusions: In the study every fourth study individual is Hypertensive, where smoking (in any form) and obesity was found as commonest risk factor for it.

Background: “Malnutrition is a silent emergency”. Malnutrition is not only an important cause of childhood mortality and morbidity, but also leads to permanent impairment of both physical and mental growth of those who survive. Methods: Cross sectional study was conducted among 720 children of age group 06-59 months in randomly selected eight wards of Jabalpur District. Multistage random sampling technique was used for the selection of study subjects. Predesigned questionnaire was used to collect data and anthropometric measurements were done. Data entry and analysis was done using Epi Info™ 7.1.5 and SPSS 20.0 (free trial version). Results: The prevalence of underweight, stunting and wasting were found to be 34.3%, 41.5% and 18.9% respectively while the prevalence of obese and overweight was 3.1% and 7.4% respectively. Malnutrition was found to be higher among the children born with low birth weight, having higher birth order, more number of siblings, those with incomplete immunization status and inappropriate feeding practices i.e. lack of exclusive breast feeding and improper weaning. Conclusions: The present study demonstrates the multiple risk factors for childhood malnutrition, encompassing sectors other than health alone like social and economic sectors, requiring multisectoral approach to fight against the silent killer of childhood malnutrition.

Globally the increasing prevalence of diabetes mellitus (DM) is major public health concern. International Diabetes Federation has stated that in India alone, the number of people with DM is estimated to be 40.9 million and is expected to rise to 69.9 million by 2025.[1] The Indian Diabetes Risk Score (IDRS) was developed by Madras Diabetes Research Foundation (MDRF) as a simple tool to help detect undiagnosed type 2 DM (T2DM) in the community.[2] We conducted a study among 911 adults of Jabalpur District to detect the prevalence of hypertension in the year 2011-2012, which has been published earlier. [3] We further analyzed the data to validate the IDRS score against increased fasting blood sugar levels in diagnosing T2DM. T2DM was confirmed either by history of previously known disease or fasting plasma glucose ≥ 126 mg/dl on two occasions. Sensitivity, specificity, positive predictive value, negative predictive value, Youden index (sensitivity + specificity −1), likelihood ratio for positive test, and likelihood ratio for negative test were calculated for IDRS cut-offs of ≥20, ≥40, ≥60, and ≥80 against the presence of T2DM (either known diabetic or fasting plasma glucose >126 mg/dl on two occasions). The overall prevalence of T2DM was 9.99% (95% confidence interval, 8.04-11.94%). In the Receiver Operating Characteristic analysis, IDRS had an area under the curve of 0.736 and a p < 0.001. The best cut-off was IDRS ≥ 40 with a sensitivity, specificity, and Youden index of 60.4%, 70.7%, and 0.31, respectively [ Table 1]. The MDRF-IDRS was also validated in the Boloor Diabetes study in Karnataka state where using IDRS, screening of nearly one-third of the population of Boloor locality in Mangalore was done. In that study, using an IDRS score ≥ 60, 62.2% of people living with undiagnosed diabetes in that population could CorrespondenceGlobally the increasing prevalence of diabetes mellitus (DM) is major public health concern. The Indian Diabetes Risk Score (IDRS) was developed by Madras Diabetes Research Foundation (MDRF) as a simple tool to help detect undiagnosed type 2 DM (T2DM) in the community. We conducted a study among 911 adults of Jabalpur District to validate the IDRS score against increased fasting blood sugar levels in diagnosing T2DM. T2DM was confirmed either by history of previously known disease or fasting plasma glucose ≥126 mg/dl on two occasions. Sensitivity, specificity, positive predictive value, negative predictive value, Youden index (sensitivity + specificity −1), likelihood ratio for positive test, and likelihood ratio for negative test were calculated for IDRS cut-offs of ≥20, ≥40, ≥60, and ≥80 against the presence of T2DM (either known diabetic or fasting plasma glucose >126 mg/dl on two occasions). The overall prevalence of T2DM was 9.99% (95% confidence interval, 8.04-11.94%). In the Receiver operating characteristic analysis, IDRS had an area under the curve of 0.736 (P < 0.001). The best cut-off was IDRS 40 with a sensitivity, specificity, and Youden index of 60.4%, 70.7%, and 0.31, ...

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