Exploring the enigma of low prevalence of post-traumatic stress disorder in India

Introduction

Post-traumatic stress disorder (PTSD) is a chronic psychiatric condition associated with significant distress and dysfunction. While worldwide estimates of prevalence range from 3.9% to 24%, little research has been conducted to identify the prevalence of PTSD in the general population of India. This study analyzes data from the National Mental Health Survey 2015-2016, a comprehensive epidemiological study of mental health disorders in India, to explore the unique characteristics and prevalence of PTSD in the Indian population.

Materials and Methods

The National Mental Health Survey 2015-2016 employed a multiple-stage, stratified, cluster-sampling methodology, covering 39,532 individuals in 12 states of India. The Mini-International Neuropsychiatric Interview (MINI) version 6.0.0 was used to diagnose psychiatric disorders, including PTSD. A detailed analysis of sociodemographic profiles, prevalence patterns, comorbidities, economic and social impact, and treatment-seeking behavior was conducted. Firth penalized logistic regression was employed to identify associated sociodemographic factors.

Results

The study revealed a low prevalence of PTSD in India at 0.2%, significantly lower than global averages. Factors associated with PTSD included female gender, middle age (40-49 years), and urban residence. The study also highlighted a high rate of comorbid mood and anxiety disorders, substantial disability, poor treatment-seeking behavior, and significant suicidal risk among individuals with PTSD.

Conclusion

Our findings underscore the need for culturally informed diagnostic and management programs to accurately identify and address PTSD in the Indian population. Cultural nuances, stigma, and the use of Western-derived diagnostic instruments likely contribute to the underidentification and undertreatment of PTSD in India. The study emphasizes the importance of recognizing and addressing these challenges to improve mental health outcomes in India.

Current prevalence and determinants of generalized anxiety disorder from a nationally representative, population-based survey of India

Introduction

Generalized anxiety disorder (GAD) is one of the common anxiety disorders leading to impairment and burden. However, GAD remains the least studied anxiety disorder. There is a need for nationally representative epidemiological data of GAD to understand the current burden and plan the mental health policies and programs to attain their unmet needs. Hence, this study focuses on epidemiology, socio-demographic correlates, disability, and treatment gap of GAD from India's National Mental Health Survey (NMHS) 2016.

Materials and Methods

NMHS 2016 was a nationally representative epidemiological survey of adult respondents from 12 states of India. NMHS is a multi-stage, stratified, random cluster sampling with random selection based on probability proportional to size at each stage. The Mini-International Neuropsychiatric Interview 6.0.0 used to diagnose psychiatric disorders. Sheehan disability scale was used to assess the disability. The current weighted prevalence of GAD was estimated. Association between GAD and socio-demographic factors was done using Firth's penalized logistic regression. The treatment gap and disability in GAD also calculated.

Results

The current weighted prevalence of GAD is 0.57%. The male gender and higher education groups have significantly lesser odds with current GAD. Urban metro and the married group have significantly higher odds with current GAD. The most common comorbid psychiatric disorders are depression (15.8%) followed by agoraphobia (9.4%). Among respondents with current GAD in the past 6 months across three domains, around 2/5th has mild and moderate disability, 1/10th has a severe disability, and 1/20th has an extreme disability. The overall treatment gap of current GAD is 75.7%.

Conclusion

NMHS 2016 has provided valuable insights into the epidemiology and burden of GAD among the general population. The available findings provide a glimpse of the current scenario in GAD to aid policymakers in targeting interventions.

Mental health morbidities in Kerala, India: Insights from National Mental Health Survey, 2015-2016

Background

The National Mental Health Survey was borne out of the felt need for a comprehensive epidemiological survey on mental health to understand the magnitude of psychiatric morbidities in India to aid in mental health policymaking, service planning, and delivery. Kerala was one of the 12 surveyed states, representing southern India.

Aims

To estimate the prevalence and pattern of various mental illnesses and substance use disorders in a representative sample from Kerala state.

Settings and Design

A household survey using a multi-stage, stratified, random cluster sampling technique, with selection based on probability proportionate to size at each stage.

Materials and Methods

The community-based survey was carried out by trained field staff on individuals from systematically selected households from three randomly selected districts of Kerala. The instruments used in the survey included M.I.N.I adult version 6.0, a modified version of the Fagerström Nicotine Dependence Scale and questionnaires to screen for epilepsy, intellectual disability, and autism spectrum disorders.

Results

A total of 2479 respondents aged >18 years were interviewed. The lifetime and current prevalence of mental morbidity (excluding tobacco use disorders) was 14.14% and 11.36%, respectively. Neurotic/stress-related disorders and depressive disorders were 5.43% and 2.49%, respectively, while severe mental disorders were prevalent in 0.44% of the sample. The prevalence of high risk for suicide was 2.23%.

Conclusions

The survey revealed high rates of common mental illnesses and suicide risk in the state when compared to national estimates.

Nationally representative epidemiological study of social anxiety disorder from India

Background

Social anxiety disorder (SAD), also termed as social phobia, is a disabling psychiatric condition with limited epidemiological research on it in India. This study, using data from the National Mental Health Survey (NMHS), 2016, is the first to explore its current prevalence and associated factors in India.

Materials and Methods

The NMHS in India used a comprehensive population-based study with subjects selected through a multistage stratified random cluster sampling technique across 12 states. The study included 34,802 adults interviewed with the Mini-International Psychiatric Interview 6.0.0. Firth penalized logistic regression (FPLR) was used to estimate covariate odds ratios (ORs), and the treatment gap for SAD and disability measured using Sheehan's disability scale was calculated.

Results

The study found a 0.47% prevalence of SAD, with an average age of 35.68 years (standard deviation (SD) = 15.23) among those affected. Factors, such as male gender, unemployment, and living in urban areas, were associated with higher odds of SAD, while the elderly had lower odds. A significant proportion of individuals with SAD experienced disability in work (63%), social life (77%), and family life (68%). They spent a median of ₹ 2500 per month on treatment and had a high rate of comorbid psychiatric disorders (58%). The treatment gap was substantial at 82%.

Conclusions

A considerable portion of India's population (approximately >65 lakhs) is affected by SAD. Surprisingly, the NMHS 2016 report indicates a higher risk of SAD among males compared with females, a trend that warrants further investigation. SAD in India is linked to significant disability and a considerable treatment gap, emphasizing the need for innovative approaches to address this large, affected population, especially in light of the scarcity of mental health professionals.

Firth's penalized logistic regression: A superior approach for analysis of data from India's National Mental Health Survey, 2016

The National Mental Health Survey of India (NMHS) was a ground-breaking nationwide study that harnessed a uniform, standardized methodology blending quantitative and qualitative approaches. Covering data from 12 states across diverse regions, its mission was to gauge the prevalence of psychiatric disorders, bridge treatment gaps, explore service utilization, and gauge the socioeconomic repercussions of these conditions. This initiative provided pivotal insights into the intricate landscape of mental health in India. One of the analyses planned for NMHS data was to undertake a logistic regression analysis with an aim to unravel how various sociodemographic factors influence the presence or absence of specific psychiatric disorders. Within this pursuit, two substantial challenges loomed. The first pertained to data separation, a complication that could perturb parameter estimation. The second challenge stemmed from the existence of disorders with lower prevalence rates, which resulted in datasets of limited density, potentially undermining the statistical reliability of our analysis. In response to these data-driven hurdles, NMHS recognized the critical necessity for an alternative to conventional logistic regression, one that could adeptly navigate these complexities, ensuring robust and dependable insights from the collected data. Traditional logistic regression, a widely prevalent method for modeling binary outcomes, has its limitations, especially when faced with limited datasets and rare outcomes. Here, the problem of "complete separation" can lead to convergence failure in traditional logistic regression estimations, a conundrum frequently encountered when handling binary variables. Firth's penalized logistic regression emerges as a potent solution to these challenges, effectively mitigating analytical biases rooted in small sample sizes, rare events, and complete separation. This article endeavors to illuminate the superior efficacy of Firth's method in managing small datasets within scientific research and advocates for its more widespread application. We provide a succinct introduction to Firth's method, emphasizing its distinct advantages over alternative analytical approaches and underscoring its application to data from the NMHS 2015-2016, particularly for disorders with lower prevalence.

A close critical look of India's National Mental Health Survey 2016

The National Mental Health Survey 2016 (NMHS 2016) was a large epidemiological study, one of its kind, conducted by the National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru to overcome the shortcomings of the previous surveys. The detailed report of the study is available in two parts- 'mental health systems' and 'prevalence, pattern and outcomes'. Though done comprehensively, there are some inevitable limitations. The private sector, a substantial health care provider in the country was not a participant in the survey. Though MINI version 6.0 is a standard and structured instrument, it does not cover many commonly encountered mental illnesses like somatoform disorders. Further, the methodology of the survey makes it difficult for an accurate calculation of the prevalence of individual major psychiatric disorders. The survey has been appraised using a standard checklist for prevalence studies. The detailed qualitative data has not been shared in the report. The contribution of the traditional indigenous systems of healthcare and accessibility of services in rural areas have not been elaborated. Thus, the need for a comprehensive and culturally sensitive assessment tool, involvement of the private sector, and enhancing funding provision to improve the infrastructure are emphasized as future directions for the subsequent phases of the survey.

A Nationwide Prevalence of Common Mental Disorders and Suicidality in Nepal: Evidence from National Mental Health Survey, 2019-2020

BACKGROUND

Mental disorders account for a large portion of burden of disease. In Nepal, the prevalence of mental disorders has been rising steadily, but national and province level prevalence is not available. This study aims to assess the prevalence of common mental disorders and suicidality in Nepal.

METHODS

We conducted nationwide descriptive cross-sectional community-based prevalence study of mental disorders and suicidality among adults (aged 18 years and above) and adolescents (aged 13 to 17 years) in Nepal. We included a total of 9200 adults and 5888 adolescents from seven provinces of Nepal by using a multistage Probability Proportionate to Size sampling technique. Mental disorders and suicidality were assessed using translated and adapted Nepalese version of Mini International Neuropsychiatric Interview (MINI) for disorders, English version 7.0.2 for Diagnostic and Statistical Manual of Mental disorders,5th Edition (DSM-5). Data were entered in CSPro v7.2. Weighted estimates for different mental disorders were calculated.

RESULTS

The overall weighted lifetime prevalence of any mental disorder among adults and adolescents was estimated at 10% and 5.2%, respectively. Suicidality was present among 7.2% of the adult and 4.1% of the adolescent participants. Among adult participants, the current prevalence of suicidal thoughts and lifetime suicidal attempts were found to be 6.5% and 1.1%, respectively.

CONCLUSIONS

This survey indicated that mental health problems are major public health concerns in Nepal that should not be overlooked. Hence, a multisectoral approach is needed to address the burden of mental health problems among adults and adolescents in Nepal.

Prevalence and its correlates of anxiety disorders from India's National Mental Health Survey 2016

INTRODUCTION

Anxiety disorders (ADs) impact the quality of life and productivity at an individual level and result in substantial loss of national income. Representative epidemiological studies estimating the burden of ADs are limited in India. National Mental Health Survey (NMHS) 2016 of India aimed to strengthen mental health services across India assessed the prevalence and pattern of public health priority mental disorders for mental health-care policy and implementation. This article focuses on the current prevalence, sociodemographic correlates, disability, and treatment gap in ADs in the adult population of NMHS 2016.

MATERIALS AND METHODS

NMHS 2016 was a nationally representative, multicentered study across 12 Indian states during 2014-2016. Diagnosis of ADs (generalized AD, panic disorder, agoraphobia, and social AD) was based on Mini-International Neuropsychiatric Interview 6.0.0. Disability was by Sheehan's Disability Scale.

RESULTS

The current weighted prevalence of ADs was 2.57% (95% confidence interval: 2.54-2.60). Risk factors identified were female gender, 40-59 age group, and urban metro dwellers. Around 60% suffered from the disability of varying severity. The overall treatment gap for ADs was 82.9%.

CONCLUSIONS

The burden of AD is similar to Depressive disorders, and this article calls for the immediate attention of policymakers to institute effective management plans in existing public health programs.

The National Mental Health Survey of India (2016): Prevalence, socio-demographic correlates and treatment gap of mental morbidity

BACKGROUND

Recognizing the need for good quality, scientific and reliable information for strengthening mental health policies and programmes, the National Mental Health Survey (NMHS) of India was implemented by National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, in the year 2015-2016.

AIM

To estimate the prevalence, socio-demographic correlates and treatment gap of mental morbidity in a representative population of India.

METHODS

NMHS was conducted across 12 Indian states where trained field investigators completed 34,802 interviews using tablet-assisted personal interviews. Eligible study subjects (18+ years) in households were selected by a multi-stage, stratified, random cluster sampling technique. Mental morbidity was assessed using MINI 6. Three-tier data monitoring system was adopted for quality assurance. Weighted and specific prevalence estimates were derived (current and lifetime) for different mental disorders. Mental morbidity was defined as those disorders as per the International Statistical Classification of Diseases, Tenth Revision Diagnostic Criteria for Research (ICD-10 DCR). Multivariate logistic regression was conducted to examine risk for mental morbidity by different socio-demographic factors. Survey was approved by central and state-level institutional ethical committees.

RESULTS

The weighted lifetime prevalence of 'any mental morbidity' was estimated at 13.67% (95% confidence interval (CI) = 13.61, 13.73) and current prevalence was 10.56% (95% CI = 10.51, 10.61). Mental and behavioural problems due to psychoactive substance use (F10-F19; 22.44%), mood disorders (F30-F39; 5.61%) and neurotic and stress-related disorders (F40-F48; 3.70%) were the most commonly prevalent mental morbidity in India. The overall prevalence was estimated to be higher among males, middle-aged individuals, in urban-metros, among less educated and in households with lower income. Treatment gap for overall mental morbidity was 84.5%.

CONCLUSION

NMHS is the largest reported survey of mental morbidity in India. Survey estimated that nearly 150 million individuals suffer from one or the other mental morbidity in India. This information is to be used for planning, delivery and evaluating mental health programming in the country.

Prevalence and pattern of mental illnesses in Uttar Pradesh, India: Findings from the National Mental Health Survey 2015-16

AIM

To estimate the prevalence and distribution of psychiatric morbidity, and study pattern of help-seeking in a community representative sample from the state of Uttar Pradesh in northern India.

METHOD

A multi-stage, stratified, random cluster sampling was used. The survey was conducted on 3508 adults during 2015-16 using M.I.N.I 6.0.0, modified Fagerström Nicotine Dependence Scale for all forms of tobacco, questionnaires for epilepsy and intellectual disability. The WHO Pathway Interview Schedule was used to study pattern of help-seeking behaviour. Focused group discussions (FGDs) and key informant interviews (KIIs) were also carried out.

RESULT

Current and lifetime prevalence of 'any mental morbidity' (excluding tobacco use disorders) was 6.08% and 7.97%, respectively. The prevalence of substance use disorders, was 16.36%, of which tobacco use disorders alone contributed 16.06%. Neurotic and depressive disorders were the next most common morbidity. Schizophrenia and other psychotic disorders had a current prevalence of 0.09%. High-risk for suicide was reported to be 0.93%. Treatment gap varied between 75 and 100% for different disorders. FGDs and KIIs reflected a higher burden of substance use, including prescription drug abuse, substantial prevalence of cultural mental morbidity, deep rooted stigma, low help-seeking behaviour, and issues surrounding homeless mentally ill persons in the community.

CONCLUSION

The survey revealed high mental morbidity and alarming treatment gap. FGDs and KIIs also highlight the burden of morbidity that probably goes un-noticed, due to socio-cultural systems and stigma. Findings from this survey are intended to be the groundwork for the (re)planning of mental healthcare infrastructure in the state.

Gambling disorders, gambling type preferences, and psychiatric comorbidity among the Thai general population: Results of the 2013 National Mental Health Survey

Background and aims To estimate the prevalence of problem and pathological gambling, gender and age-group differences in gambling types, and comorbidities with other psychiatric disorders among the Thai general population. Methods Analysis was conducted on 4,727 participants of Thailand's 2013 National Mental Health Survey, a multistage stratified cluster survey, using the Composite International Diagnostic Interview. Diagnoses of problem and pathological gambling and other psychiatric disorders were based on the DSM-IV-TR criteria with the following additional criteria for gamblers: more than 10 lifetime gambling episodes and a single year loss of at least 365 USD from gambling. Results The estimated lifetime prevalence rates of pathological and problem gambling were 0.90% [95% confidence interval (CI): 0.51-1.29] and 1.14% (95% CI: 0.58-1.70), respectively. The most popular type of gambling was playing lotteries [69.5%, standard error (SE) = 1.9], the prevalence of which was significantly higher among females and older age groups. The most common psychiatric disorders seen among pathological gamblers were alcohol abuse (57.4%), nicotine dependence (49.5%), and any drug use disorder (16.2%). Pathological gambling was highly prevalent among those who ever experienced major depressive episodes (5.5%), any drug dependence (5.1%), and intermittent explosive disorder (4.8%). The association between pathological gambling was strongest with a history of major depressive episode [adjusted odds ratio (AOR) = 10.4, 95% CI: 2.80-38.4]. Conclusion The study confirms the recognition of gambling disorders as a public health concern in Thailand and suggests a need for culturally specific preventive measures for pathological gamblers and those with a history of substance use disorders or major depression.