Search

Introduction Suicide is a major social and health issue in India. Yearly statistics show a concerning increasing pattern of suicidal deaths in India which is higher in comparison to the global trend. There is limited evidence regarding historical analysis of suicide or any forecasting for suicide in India towards predicting the possible risks of death due to suicide. Methods This paper examines the trend of suicide rate and characteristics of suicide victims in India, based on the longitudinal time series data over the last 50 years—collected from the National Crime Record Bureau Reports (1969 to 2018) of the Government of India. In our analysis, we have used the time series model to forecast the suicide rates in India for the next decade. ARIMA (4,1,0) model is found to be the best fit model for forecasting the data. Findings There has been an observable and rising trend of suicide rates in India over the last five decades. The forecast indicates a continuance of rising suicide cases for an upcoming couple of years in India with a limited decline in the following years. The prediction model indicates a future relatively consistent pattern of suicide in India which does not seem to be a very encouraging trend. As we have not included the period staring the year 2020 onwards affected by Covid-19 and which has several disruptions in personal and family spaces, the projected suicide trend during the period of next two to three years (2020–22) may rise far high and then it may show a declining path. Along with this, there is a shift in means of suicide in the last couple of decades. Constituting the second-highest number of cases, Illness associated suicide was visibly a serious concern. Conclusion The present analysis finds that there is no visible substantial relief for suicide deaths during the coming years in India. On the other hand, more extensive exploration of sample cases may provide important information for suicide prevention. Availability of detailed and more inclusive data will be highly useful for analysis and suicide preventive policies. Investment in public health care and other welfare activities like education and employment generation will yield visible positive results in suicide control.

Context: Overweight and obesity has become a major contributor to global burden of chronic diseases and disability. Obesity among rural India is emerging as a major health problem because of change in lifestyle and food habits, thereby increases the risk of multiple morbid conditions among rural population. Aims: This study aims to find out the association of overweight/obesity with different socio-demographic factors and explore the co-morbidities among overweight and obese in a rural setting. Settings and Design: A cross-sectional study was done in a randomly selected primary health centre of Khurda district, Odisha for 4 months. Materials and Methods: This study was done among 183 patients aged >20 years with BMI >25 kg/m2 after taking their consent. Anthropometric measurements were done and data were collected using a semi-structured questionnaire. Statistical Analysis Used: Descriptive statistics such as proportion, mean and standard deviation were calculated and inferential statistics such as Chi-square test, univariate and multivariate regression was done using the SPSS version 20.0. Results: Mean age of participants was 45.7 (±13.8) years. About 93.4% were Grade II obese while 51.9% were at risk according to their waist–hip ratio. Around 53.6% of participants had multi-morbidity. Age, occupation and number of children were significantly associated with obesity. Morbidity was significantly associated with age, occupation, marital status and number of children. Increased grade in obesity the more is the probability of having morbidity. Conclusions: There is an urgent need to screen for obesity at rural health facility and early management for prevention from co-morbidities.

Context: Partograph is a simple, effective and low-cost intrapartum monitoring tool that helps in early identification of complications if any and helps in prompt intervention to save the life of the mother and the newborn. There is limited study about its usage and challenges in plotting from India particularly Odisha. Aim: To determine the usage of partograph and explore the issues/challenges in its plotting at various levels of health facilities Settings and Design: A cross-sectional study was carried out from April to June 2018 in ten different public health facilities from two tribal districts of Odisha, India. Materials and Methods: Quantitative information from 1552 mothers using pre-tested epi-info questionnaire tool and qualitative information through 22 in-depth interviews among health care providers. Statistical Analysis Used: Quantitative data using Ms Excel 10 and IBM SPSS ver. 22 and qualitative data using the inductive content analysis method. Results: Partograph plotting was found in 48.7% (adherence) while its completeness was only 1.03%. Partograph plotting was significantly better at CHCs compared to DHH and SDH (P = 0.000). No significant association of partograph adherence was observed with the birth outcome, complications, referral status and type of delivery. Though majority health care providers knew the importance of the partograph, hardly they use it. The main reasons were increased workload, shortage of staff, cases arriving at a later stage and lack of monitoring from a higher level. Conclusions: On job training on partograph, regular monitoring and strict policy will improve the adherence and completeness in partograph plotting.