Trajectory of suicide among Indian children and adolescents: a pooled analysis of national data from 1995 to 2021.

BACKGROUND: Suicide is a major public health concern in India especially among children and adolescents. The yearly national statistics show a concerning trend of rising suicide deaths in these age groups. METHODS: The present study, taking 26 years of national data from the National Crime Record Bureau during 1995-2021, examined the trend, patterns, means, and modes of children/adolescent suicides in India. We also undertook a time series analysis by using ARIMA (0,2,1) model to forecast the expected suicide rate for the next one decade. RESULTS: A rising trend of suicide rate among children and adolescents was observed in India over the last 26 years. The forecast indicates a continuance of rising suicide cases for the upcoming decade in India. A substantially different trend of suicide rate was observed among early and late adolescents indicating significantly high vulnerability of late adolescents. Among children /adolescents, the most common causes of suicide were family problems, academic failure, illness, and unemployment. Illness has emerged as one of the leading causes of suicide, with a significant rise over time. Poverty and unemployment were also found as the important contributors with a steadily increasing trend of suicide among children and adolescents facing these problems in recent years. CONCLUSION: The study provides important analysis and information on suicide among children/adolescents in India, by providing useful insights for parents, teachers, policymakers, healthcare practitioners, and stakeholders aiming to prevent and control children and adolescent suicide and boost mental health. The study also provides important leads on risk factors with a forecast of suicide trends for the next 10 years.

Cause Specific survival analysis of Gynaecological Cancers among Non-White Population: A SEER based Study.

Gynaecological cancers are the most prevalent cancers in women, making them a major public health concern for decades. Health disparities and inequalities in access to care among different racial groups have been a major concern in the US healthcare system. This study was aimed at investigating cause-specific survival rates among non-white women with gynaecological cancer and to identify risk factors associated with gynaecological cancer mortality by race. The Kaplan-Meier method was used to calculate 5-year survival estimates and various risk factors for gynaecological cancer among non-white women were analysed using Cox proportional hazard model. The findings of this study highlight the need for targeted interventions to improve access to care and reduce health disparities for non-white women with gynaecological cancer.

Trends in gynecological cancer incidence, mortality, and survival among elderly women: A SEER study.

Objectives: This paper aims to comprehensively analyze trends in gynecological cancers among elderly women in the United States from 1975 to 2020. Methods: Surveillance, Epidemiology, and End Results (SEER) population data were utilized for the analysis. Annual Percentage Change (APC) and Average APC were estimated using join-point regression to assess trends in mortality rates. Results: The study reveals an increasing pattern of incidence and mortality in all gynaecological cancer sites except cervical cancer among elderly. The incidence of cervical cancer decreased from 1975 to 2007 and then increased, whereas cancer-specific mortality decreased from 1977 to 2020, indicating positive advancements in detection and treatment. Conclusions: Despite progress in managing certain gynecological cancers, challenges persist, particularly evidenced by increasing mortality rates for cancers in other female genital organs. This underscores the necessity for sustained research efforts and targeted interventions to address these ongoing challenges effectively.

Changing patterns of cancer burden among elderly across Indian states: Evidence from the global burden of disease study 1990-2019.

Objective: To investigate the trends and patterns of the cancer burden among the elderly in different regions of India at a subnational level. Methods: Data were extracted from the Global Burden of Disease (GBD) Studies India Compare 2019. Prevalence rate, disability-adjusted life years (DALY), and annual percentage change techniques were used to analyze data. Results: The three age groups with the highest prevalence of cancer were those aged 60-64 years, 65-69 years, and 70-74 years. In 2019, The prevalence of cancer among the elderly ranged from 7048.815 in Karnataka to 5743.040 in Jharkhand. Kerala has the most significant annual percentage change in the cancer prevalence rate of 0.291 between 1990 and 2019. The highest DALY rate was observed among individuals aged 80-84 years in 2019. That year, the DALY rate among the elderly was 8112.283 in India. The top five cancers with higher DALY rates among the elderly in India in 2019 were tracheal, bronchus, and lung cancer (908.473), colon and rectum cancer (752.961), stomach cancer (707.464), breast cancer (597.881), and lip and oral cavity cancer (557.637). Conclusion: Elderly individuals demonstrated a higher vulnerable to cancer compared to other age groups. There is a need for state-specific government intervention to minimize the risk of cancer among the elderly due to the heterogeneity in the burden of cancer across Indian states.

Forecasting road accidental deaths in India: an explicit comparison between ARIMA and exponential smoothing method.

The number of deaths due to road accident is increasing day by day and has become an alarming global problem over the decades. India, with her rising motorization is no stranger to this global catastrophe. In this paper two relatively simple yet powerful and versatile techniques for forecasting time series data, autoregressive integrated moving average method (ARIMA) and exponential smoothing method are used to forecast the number of deaths due to road accidents in India from the year 2022-2031. The results based on the two methods are compared and it is found that they are in sync with each other and pre-existing literature. Furthermore, this is a unique attempt to use two time series analysis techniques on the same data and carry out a comparative analysis. The data was collected from the annual report of Ministry of Road Transport and Highways, India (2020) and Accidental Deaths & Suicides in India (ADSI) Report of National Crime Record Bureau (2021). After examining all the probable models, it is observed that ARIMA (2, 2, 2) model and exponential smoothing (M, A, N) model are suitable for the given data. Amongst the two, ARIMA (2, 2, 2) model has a lower AIC and BIC value. Thus, this comes out to be the best model as per our model selection criterion. Further, the study also reveals an upward trend of number of road accidental deaths for the upcoming 10 years in India.

Statistical modeling and estimating number of healthy life years lost and healthy life expectancy in India, 2000-2019.

Objective: In this study, our objective is to propose various models to estimate healthy life year lost (HLYL) and healthy life expectancy (HLE) in India. Methods: The HLYL and HLE were estimated and further these estimates were compared with the direct life table method and the World Health Organization (WHO) method. From the mortality perspective, we have developed a log-logistic model for estimating the parameter (bx), which is characterized by HLYL. The results were compared with other models, such as the Gompertz and Weibull model. Here, we have also obtained the HLE by subtracting HLYL from the total life expectancy. Results: The result shows an increasing trend of HLYL among the male, female, and the total population in India. Conclusion: From the log-logistic model, the HLYL was estimated as 8.79 years, 8.36 years, and 9.38 years for the total, male, and female populations, respectively, in India during 2019.

Forecasting suicide rates in India: An empirical exposition.

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.

Novel predictive risk factor for Erectile Dysfunction: Serum folic acid.

The purpose of this study was to compare the serum Folic Acid (FA) levels in patients with Erectile Dysfunction (ED) and healthy controls and whether levels vary with its severity. The study was carried out on 77 sexually active individuals, out of which 41 complained of ED and 36 were apparently normal. Patients were excluded if they had any diseases known to cause ED. The severity was further categorised based on IIEF-5 scores. Blood serum levels of testosterone, lipid profile, random blood sugar, liver function test, renal function test and FA levels were obtained in each patient. Independent-samples t test of significance was used when comparing between two means. Pearson's correlation coefficient (r) test was used for correlating data. All clinical and biochemical parameters except FA were comparable in both the groups. FA levels were significantly decreased in ED group (5.29 vs. 10.8; p value = .004). Smoking habits were comparable between the groups, and FA levels did not vary among smokers and nonsmokers (p value = .46). Serum FA levels significantly declined with increasing severity of ED (8.28 vs. 5.56 vs. 4.37 vs. 3.5; p value < .001). Thus, decreased FA might possibly be one of the novel risk factors for ED.

Determinants of home deliveries - Findings from India DLHS 4 analysis.

BACKGROUND: Place of delivery has major implication on decreasing maternal morbidity and mortality. India has adopted various policies to encourage institutional births, still there are large numbers of deliveries which occur at home. Thus, it is imperative to understand the risk factors associated with home deliveries among women in India. METHODS: The national representative district level household data-4 (2012-13) have been used for this analysis. A multiple logistic regression model has been used to determine the significant factors associated with home deliveries. RESULTS: A total of 22,363 live births were selected for analysis for the year 2012. Out of which 3,602 (15.4%) are found to be home delivery births, remaining are either private or government institutional births. North-east states are found to be high prevalence of home deliveries. The potential factors viz., age of women, educational level of both husband and wife, age at first birth, higher order parity and not registered for ANC check-up, etc., are significantly associated with home delivery birth preferences among women in India. CONCLUSION: Our analysis demonstrates that targeting the significant predictors particularly education of family members and compulsory registration for ANC check-up will significantly reduce the preference for home delivery.

Count data regression modeling: an application to spontaneous abortion.

BACKGROUND: In India, around 20,000 women die every year due to abortion-related complications. In count data modeling, there is sometimes a prevalence of zero counts. This article is concerned with the estimation of various count regression models to predict the average number of spontaneous abortions among women in Punjab and few northern states in India. The study also assesses the factors associated with the number of spontaneous abortions. METHODS: This study includes 27,173 married women of Punjab obtained from the DLHS-4 survey (2012-13) to train the count models. The study predicts the average number of spontaneous abortions using various count regression models, and also identifies the determinants affecting the spontaneous abortions. Further, the best model is validated with other northern states of India using the latest data (NFHS-4, 2015-16). RESULTS: Statistical comparisons among four estimation methods reveals that the ZINB model provides the best prediction for the number of spontaneous abortions. The study suggests total children born to a woman, antenatal care (ANC) place, place of residence, woman's education, and economic status are the most significant factors affecting the instance of spontaneous abortion. CONCLUSIONS: This article offers a practical demonstration of techniques designed to handle count outcome variables. The statistical comparisons among four estimation models revealed that the ZINB model provides the best prediction for the number of spontaneous abortions, and it suggests policymakers to use this model to predict the number of spontaneous abortions. The study recommends promoting higher education among women in Punjab and other northern states of India. It also suggests that women must receive institutional antenatal care and have a limited number of children.

Statistical models for longitudinal zero-inflated count data: application to seizure attacks.

BACKGROUND: Chronic non-communicable diseases:- such as epilepsy, are increasingly recognized as public health problems in developing and African countries. This study aimed at finding determinants of the number of epileptic seizure attacks using different count data modeling techniques. METHODS: Four common fixed-effects Poisson family models were reviewed to analyze the count data with a high proportion of zeros in longitudinal outcome, i.e., the number of seizure attacks in epilepsy patients. This is because, in addition to the problem of extra zeros, the correlation between measurements upon the same patient at different occasions needs to be taken into consideration. RESULTS: The investigation remarkably identified some important factors associated with epileptic seizure attacks. As people grow old, the number of seizure attacks increased and male patients had more seizures than their female counterparts. In general, a patient's age, sex, monthly income, family history of epilepsy andservice satisfaction were some of the significant factors responsible for the frequency of seizure attacks (P value<0.05). CONCLUSION: This study suggests that zero-inflated negative binomial is the best model for predicting and describing the number of seizure attacks as well as identifying the potential risk factors. Addressing these risk factors will definitely contain the progression of seizure attack.

High prevalence of cesarean section births in private sector health facilities- analysis of district level household survey-4 (DLHS-4) of India.

BACKGROUND: Worldwide rising cesarean section (CS) births is an issue of concern. In India, with increase in institutional deliveries there has also been an increase in cesarean section births. Aim of the study is to quantify the prevalence of cesarean section births in public and private health facility, and also to determine the factors associated with cesarean section births. METHODS: We analyzed data from district level household survey data 4 (DLHS-4) combined individual level dataset for 19 states/UTs of India comprising 24,398 deliveries resulting in 22,111 live births for year 2011. The percentages and Chi-square has been computed for the select variables viz. Socio demographic, maternal, antenatal care and delivery related based on type of births (CS Vs normal births). The multiple logistic regression model has been used to identify the potential risk factors associated with CS births. RESULTS: Of 22,111 live birth analyzed 49.2% were delivered at public sector, 31.9% at private sector and 18.9% were home deliveries. Prevalence of CS births were 13.7% (95% CI; 13.0- 14.3%) and 37.9% (95% CI; 36.7- 39.0%) in the public and private sectors, respectively. Higher odds of CS births were observed with- delivery at private health facility (OR 3.79; 95% C.I 3.06-4.72), urban residence (OR 1.15; 95% C.I 1.00- 1.35), first delivery after 35 years of maternal age (OR 5.5; 95% C.I 1.85- 16.4), hypertension in pregnancy (OR 1.32; 95% C.I 1.06- 1.65) and breach presentation (OR 2.37; 95% C.I. 1.63- 3.43). CONCLUSIONS: Our findings shows that CS births are nearly three times more in private as compared to public sector health facilities.The higher rates of CS births, especially in private sector, not only increase the cost of care but may pose unnecessary risks to women (when there is no indications for CS). The government of India need to take measures to strengthen existing public health facilities as well as ensure that cesarean sections are performed based upon medical indications in both public and private sector health facilities.

Antimicrobial drug prescribing patterns for community-acquired pneumonia in hospitalized patients: A retrospective pilot study from New Delhi, India.

OBJECTIVE: The objective of this study was to determine patterns and frequency of antimicrobial drug use among hospitalized patients with community-acquired pneumonia (CAP). METHODOLOGY: A retrospective 5 years (April 2007-March 2012) detailed medical record review of patients diagnosed with CAP and discharged to home from Non-Intensive Care Unit respiratory medicine wards of two public hospitals in Delhi. RESULTS: A total of 261 medical records were analyzed. Over the 5 years, 82.0% (2007-08), 78.6% (2008-09), 59.5% (2009-10), 64.7% (2010-11), and 67.8% (2011-12) patients were prescribed two antimicrobials. In the last two study years, the proportion of patients receiving three antimicrobials increased (from 2.0% to 26.5% and 28.8%), while the proportion receiving monotherapy decreased (from 16.0% to 8.8% and 3.4%). In accordance with guidelines, beta-lactams and macrolides were the two most frequently prescribed antimicrobials (34.1%). However, newer generation beta-lactams were prescribed. A total of 37 patients were prescribed beta-lactam-tazobactam combination preparations. Overall, beta-lactams constituted more than 40% of prescriptions while macrolides were the second most prescribed class. Cephalosporin prescriptions significantly increased (P < 0.01) and penicillin prescriptions significantly decreased over study periods. The prescription of fluoroquinolones also decreased (21.5-6.0%, P < 0.01) and aminoglycoside prescription ranged from 9.7% to 16.4%, over 5 years. Reasons for prescribing three antimicrobials, use of aminoglycosides, or higher-end/reserve antibiotics were not mentioned in the medical records. There were no hospital-specific guidelines for doctors to follow in the treatment of CAP. CONCLUSIONS: These findings suggest the need for implementing antimicrobial treatment guidelines. Adequate documentation and monitoring of antibiotic use for feedback are also lacking. An antimicrobial stewardship program may offer the most comprehensive solution for appropriate use of antimicrobials.