A cross ancestry genetic study of psychiatric disorders from India.

Genome-wide association studies across diverse populations may help validate and confirm genetic contributions to risk of disease. We estimated the extent of population stratification as well as the predictive accuracy of polygenic scores (PGS) derived from European samples to a data set from India. We analysed 2685 samples from two data sets, a population neurodevelopmental study (cVEDA) and a hospital-based sample of bipolar affective disorder (BD) and obsessive-compulsive disorder (OCD). Genotyping was conducted using Illumina's Global Screening Array. Population structure was examined with principal component analysis (PCA), uniform manifold approximation and projection (UMAP), support vector machine (SVM) ancestry predictions, and admixture analysis. PGS were calculated from the largest available European discovery GWAS summary statistics for BD, OCD, and externalizing traits using two Bayesian methods that incorporate local linkage disequilibrium structures (PGS-CS-auto) and functional genomic annotations (SBayesRC). Our analyses reveal global and continental PCA overlap with other South Asian populations. Admixture analysis revealed a north-south genetic axis within India (FST 1.6%). The UMAP partially reconstructed the contours of the Indian subcontinent. The Bayesian PGS analyses indicates moderate-to-high predictive power for BD. This was despite the cross-ancestry bias of the discovery GWAS dataset, with the currently available data. However, accuracy for OCD and externalizing traits was much lower. The predictive accuracy was perhaps influenced by the sample size of the discovery GWAS and phenotypic heterogeneity across the syndromes and traits studied. Our study results highlight the accuracy and generalizability of newer PGS models across ancestries. Further research, across diverse populations, would help understand causal mechanisms that contribute to psychiatric syndromes and traits.

Childhood adversities characterize the heterogeneity in the brain pattern of individuals during neurodevelopment.

BACKGROUND: Several factors shape the neurodevelopmental trajectory. A key area of focus in neurodevelopmental research is to estimate the factors that have maximal influence on the brain and can tip the balance from typical to atypical development. METHODS: Utilizing a dissimilarity maximization algorithm on the dynamic mode decomposition (DMD) of the resting state functional MRI data, we classified subjects from the cVEDA neurodevelopmental cohort (n = 987, aged 6-23 years) into homogeneously patterned DMD (representing typical development in 809 subjects) and heterogeneously patterned DMD (indicative of atypical development in 178 subjects). RESULTS: Significant DMD differences were primarily identified in the default mode network (DMN) regions across these groups (p < 0.05, Bonferroni corrected). While the groups were comparable in cognitive performance, the atypical group had more frequent exposure to adversities and faced higher abuses (p < 0.05, Bonferroni corrected). Upon evaluating brain-behavior correlations, we found that correlation patterns between adversity and DMN dynamic modes exhibited age-dependent variations for atypical subjects, hinting at differential utilization of the DMN due to chronic adversities. CONCLUSION: Adversities (particularly abuse) maximally influence the DMN during neurodevelopment and lead to the failure in the development of a coherent DMN system. While DMN's integrity is preserved in typical development, the age-dependent variability in atypically developing individuals is contrasting. The flexibility of DMN might be a compensatory mechanism to protect an individual in an abusive environment. However, such adaptability might deprive the neural system of the faculties of normal functioning and may incur long-term effects on the psyche.

Assessing Adult ADHD: An Updated Review of Rating Scales for Adult Attention Deficit Hyperactivity Disorder (ADHD).

METHOD: Scholarly articles on adult ADHD between 1996 and 2022 were reviewed using the PRISMA guidelines. ADHD rating scales with multiple citations were selected and their psychometric properties and symptom coverage were analyzed. RESULTS: Ten rating scales, with sound psychometric properties, were identified. Out of those reviewed two (BADDS and BAARS-IV) load on the inattentive domain of ADHD, while the rest focus on a comprehensive assessment of ADHD. Only one scale (BARRS-IV) incorporates an assessment of functional impairment. Some scales though widely utilized have not been adequately examined for their sensitivity. CONCLUSIONS: Rating scales are reliable and valid, in the assessment of adult ADHD. We present a review of recent scales, with an expanded focus, to help clinicians make informed decisions on diagnosis, identifying targets and planning interventions accordingly.

A descriptive study of hepatitis C in people who inject drugs.

BACKGROUND OBJECTIVES: The seroprevalence of the hepatitis C virus (HCV) in general population is higher than that of human immunodeficiency virus (HIV) in India. People who inject drugs (PWIDs) constitute a high-risk group for all blood-borne infections. Multiple behavioural surveillance surveys have provided a rich typology of HIV-infected PWIDs, but this information is missing for HCV infection. We describe awareness, transmission risk factors and the treatment continuum for HCV infection among PWID. We also report spatial clustering of HCV infection in PWIDs residing in Bengaluru. METHODS: Information from clinical records was collected and telephonic interviews of retrospectively identified PWIDs who received treatment at a tertiary-level addiction treatment facility between 2016 and 2021 were conducted. RESULTS: We identified 391 PWIDs; 220 (56.26%) received an anti-HCV antibody test (4 th Generation HCV-Tridot). Individuals reporting unsafe injection practices were more often tested than those who did not ( χ2 =44.9, df=1, P <0.01). Almost half of the tested and more than a quarter of the whole sample (109/220, 49.9%; 109/391, 27.9%) were seropositive for HCV infection. The projected seropositivity in this group was between 27.9 per cent (best case scenario, all untested assumed negative) and 71.6 per cent (worst case scenario, all untested assumed positive). Only a minority of participants interviewed were aware of HCV (27/183, 14.7%). HCV infection and its associated risk behaviour (PWID) were clustered in certain localities (Diggle and Chetwynd Test; P =0.001) in Bengaluru in the southern district of Karnataka. INTERPRETATION CONCLUSIONS: Undetected HCV infection is common in PWIDs; awareness and treatment uptake is poor in this group. Spatial clustering of infections in a district shows transmission in close networks and provides opportunities for targeted interventions.

Does Propofol Effect Site (Brain) Concentration Predicted by Target-Controlled Infusion Correlate with Propofol Measured in the Brain? An Exploratory Study in Neurosurgical Patients.

BACKGROUND: Total intravenous anesthesia with propofol can be administered by target-controlled infusion pumps, which work on the principles of pharmacokinetic modeling. While designing this model, neurosurgical patients were excluded as the surgical site and drug action site remained the same (brain). Whether the predicted set propofol concentration and the actual brain site concentration correlate, especially in neurosurgical patients with impaired blood-brain barrier (BBB), is still unknown. In this study we compared the set propofol effect-site concentration in the target-controlled infusion pump with actual brain concentration measured by sampling the cerebrospinal fluid (CSF). METHODS: Consecutive adult neurosurgical patients requiring propofol infusion intraoperatively were recruited. Blood and CSF samples were collected simultaneously when patients received propofol infusion at 2 different target effect-site concentrations-2 and 4 ug/mL. To study BBB integrity, CSF-to-blood albumin ratio and imaging findings were compared. The propofol level in the CSF was compared with set concentration using the Wilcoxon signed-rank test. RESULTS: Fifty patients were recruited, and the data were analyzed from 43 patients. There was no correlation between propofol concentration set in TCI and propofol concentration measured in blood and CSF. Though imaging findings were suggestive of BBB disruption in 37/43 patients, the mean (±standard deviation) CSF-to-serum albumin ratio was 0.0028 ± 0.002, suggesting intact BBB integrity (ratio >0.3 was considered as disrupted BBB). CONCLUSIONS: CSF propofol level did not correlate with set concentration in spite of acceptable clinical anesthetic effect. Also, the CSF-to-blood albumin measurement did not provide information on the BBB integrity.

Country-level gender inequality is associated with structural differences in the brains of women and men.

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality.

Cross-continental environmental and genome-wide association study on children and adolescent anxiety and depression.

Anxiety and depression in children and adolescents warrant special attention as a public health issue given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study investigated the impact of environmental factors and genomics on anxiety and depression in children and adolescents across three cohorts: the Adolescent Brain and Cognitive Development Study (US), the Consortium on Vulnerability to Externalizing Disorders and Addictions (India), and IMAGEN (Europe). Linear mixed-effect models, recursive feature elimination regression, and LASSO regression models were used to identify the environmental impact on anxiety/depression. Genome-wide association analyses were then performed for all three cohorts with consideration of significant environmental effects. The most significant and consistent environmental factors were early life stress and school risk. A novel SNP, rs79878474 in chr11p15, was identified as the most promising SNP associated with anxiety and depression. Gene set analysis found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, particularly Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes, respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine and a trend of enrichment in the cerebellum. The study highlights the consistent impact of early life stress and school risk on anxiety and depression during development and suggests the potential role of mutations in potassium channels and the cerebellum region. Further investigation is needed to better understand these findings.

Neurocognitive Analysis of Low-level Arsenic Exposure and Executive Function Mediated by Brain Anomalies Among Children, Adolescents, and Young Adults in India.

Importance: Arsenic, a contaminant of groundwater and irrigated crops, is a global public health hazard. Exposure to low levels of arsenic through food extends well beyond the areas with high arsenic content in water. Objective: To identify cognitive impairments following commonly prevalent low-level arsenic exposure and characterize their underlying brain mechanisms. Design, Setting, and Participants: This multicenter population-based cohort study analyzed cross-sectional data of the Indian Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA) cohort, recruited between November 4, 2016, and May 4, 2019. Participants aged 6 to 23 years were characterized using deep phenotyping measures of behavior, neuropsychology, psychopathology, brain neuroimaging, and exposure to developmental adversities and environmental neurotoxins. All analyses were performed between June 1, 2020, and December 31, 2021. Exposure: Arsenic levels were measured in urine as an index of exposure. Main Outcomes and Measures: Executive function measured using the cVEDA neuropsychological battery, gray matter volume (GMV) from T1-weighted magnetic resonance imaging, and functional network connectivity measures from resting state functional magnetic resonance imaging. Results: A total of 1014 participants aged 6 to 23 years (589 male [58.1%]; mean [SD] age, 14.86 [4.79] years) were included from 5 geographic locations. Sparse-partial least squares analysis was used to describe a negative association of arsenic exposure with executive function (r = -0.12 [P = 5.4 × 10-4]), brain structure (r = -0.20 [P = 1.8 × 10-8]), and functional connectivity (within network, r = -0.12 [P = 7.5 × 10-4]; between network, r = -0.23 [P = 1.8 × 10-10]). Alterations in executive function were partially mediated by GMV (b = -0.004 [95% CI, -0.007 to -0.002]) and within-network functional connectivity (b = -0.004 [95% CI, -0.008 to -0.002]). Socioeconomic status and body mass index moderated the association between arsenic and GMV, such that the association was strongest in participants with lower socioeconomic status and body mass index. Conclusions and Relevance: The findings of this cross-sectional study suggest that low-level arsenic exposure was associated with alterations in executive functioning and underlying brain correlates. These results indicate potential detrimental consequences of arsenic exposure that are below the currently recommended guidelines and may extend beyond endemic risk areas. Precision medicine approaches to study global mental health vulnerabilities highlight widespread but potentially modifiable risk factors and a mechanistic understanding of the impact of low-level arsenic exposure on brain development.

Cross-continental environmental and genome-wide association study on children and adolescent anxiety and depression.

Anxiety and depression in children and adolescents warrant special attention as a public health issue given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17) and IMAGEN (EUROPE, age of 14). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school risk had the most significant and consistent impact across all three cohorts. Both meta and mega-analysis identified a novel SNP rs79878474 in chr11p15 to be the most promising SNP associated with anxiety and depression. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine and a trend of enrichment in the cerebellum. Our findings provide evidence of consistent environmental impact from early life stress and school risks on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels along with the potential role of the cerebellum region, which are worthy of further investigation.

Growth trajectories for executive and social cognitive abilities in an Indian population sample: Impact of demographic and psychosocial determinants.

Cognitive abilities are markers of brain development and psychopathology. Abilities, across executive, and social domains need better characterization over development, including factors that influence developmental change. This study is based on the cVEDA [Consortium on Vulnerability to Externalizing Disorders and Addictions] study, an Indian population based developmental cohort. Verbal working memory, visuo-spatial working memory, response inhibition, set-shifting, and social cognition (faux pas recognition and emotion recognition) were cross-sectionally assessed in > 8000 individuals over the ages 6-23 years. There was adequate representation across sex, urban-rural background, psychosocial risk (psychopathology, childhood adversity and wealth index, i.e. socio-economic status). Quantile regression was used to model developmental change. Age-based trajectories were generated, along with examination of the impact of determinants (sex, childhood adversity, and wealth index). Development in both executive and social cognitive abilities continued into adulthood. Maturation and stabilization occurred in increasing order of complexity, from working memory to inhibitory control to cognitive flexibility. Age related change was more pronounced for low quantiles in response inhibition (ß∼4 versus  -1 versus -0.25 for lower quantiles). Wealth index had the largest influence on developmental change across cognitive abilities. Sex differences were prominent in response inhibition, set-shifting and emotion recognition. Childhood adversity had a negative influence on cognitive development. These findings add to the limited literature on patterns and determinants of cognitive development. They have implications for understanding developmental vulnerabilities in young persons, and the need for providing conducive socio-economic environments.

Risk clustering and psychopathology from a multi-center cohort of Indian children, adolescents, and young adults.

Developmental adversities early in life are associated with later psychopathology. Clustering may be a useful approach to group multiple diverse risks together and study their relation with psychopathology. To generate risk clusters of children, adolescents, and young adults, based on adverse environmental exposure and developmental characteristics, and to examine the association of risk clusters with manifest psychopathology. Participants (n = 8300) between 6 and 23 years were recruited from seven sites in India. We administered questionnaires to elicit history of previous exposure to adverse childhood environments, family history of psychiatric disorders in first-degree relatives, and a range of antenatal and postnatal adversities. We used these variables to generate risk clusters. Mini-International Neuropsychiatric Interview-5 was administered to evaluate manifest psychopathology. Two-step cluster analysis revealed two clusters designated as high-risk cluster (HRC) and low-risk cluster (LRC), comprising 4197 (50.5%) and 4103 (49.5%) participants, respectively. HRC had higher frequencies of family history of mental illness, antenatal and neonatal risk factors, developmental delays, history of migration, and exposure to adverse childhood experiences than LRC. There were significantly higher risks of any psychiatric disorder [Relative Risk (RR) = 2.0, 95% CI 1.8-2.3], externalizing (RR = 4.8, 95% CI 3.6-6.4) and internalizing disorders (RR = 2.6, 95% CI 2.2-2.9), and suicidality (2.3, 95% CI 1.8-2.8) in HRC. Social-environmental and developmental factors could classify Indian children, adolescents and young adults into homogeneous clusters at high or low risk of psychopathology. These biopsychosocial determinants of mental health may have practice, policy and research implications for people in low- and middle-income countries.

District-level differences in the distribution of mental and substance use disorders in Assam.

Background: The lifetime prevalence of mental morbidity in Assam is estimated at 8% (NMHS 2015-16). Understanding the distribution patterns of different types of mental disorders among persons with mental morbidity in different districts would facilitate evidence-driven district mental health programming in Assam. Given the varied socio-geopolitical situation across districts in Assam, significant variations in the distribution of mental disorders are expected. Aims: To assess interdistrict differentials in common mental disorders (CMDs), severe mental disorders (SMDs), socioeconomic impact, healthcare utilization, and mental disability across three districts sampled in NMHS in Assam. Materials and Methods: This cross-sectional study used stratified random cluster sampling to identify and study eligible adult participants in Dibrugarh, Barpeta, and Cachar districts. Standardized scales and validated questionnaires were used to assess mental morbidity, disability, socioeconomic impact, and healthcare utilization. The distribution of different mental disorders among persons with mental disorders and their interdistrict differentials were tested using the Chi-square test of significance. Results: Among persons with mental morbidity, the most common disorder was CMDs (79%). The proportional distribution of CMDs among persons with mental morbidity was significantly higher in the Dibrugarh district (79%), whereas the distribution of SMDs was higher in the Cachar district (55%). The distribution of alcohol use disorder was the highest in the Dibrugarh district (71.6%). Significant differences in disability and healthcare utilization were observed between the districts. Conclusions: NMHS 2015-16 Assam indicates significant differentials in the distribution of CMDs and SMDs, healthcare utilization, and associated disability between the three districts. The differentials necessitate further research to understand socio-ethnocultural, religious, geopolitical, and other factors influencing the distribution. These differences need to be accounted for during the implementation of mental health programs in the state.

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.

Bipolar affective disorder in India: A multi-site population-based cross-sectional study.

Introduction: Bipolar Affective Disorder (BPAD) merits careful consideration within the medical and healthcare communities, researchers, and policymakers. This is due to its substantial disability burden, elevated prevalence of co-morbidities, heightened lifetime risk of suicidality, and a significant treatment gap. This article focuses on the lifetime and current prevalence, correlates, co-morbidities, associated disabilities, socio-economic impact, and treatment gap for BPAD in the adult population of the National Mental Health Survey (NMHS) 2016. Materials and Methods: The NMHS 2016 was a nationally representative study conducted across 12 Indian states between 2014 and 2016. A multi-stage, stratified, random cluster sampling technique based on probability proportionate to size at each stage was used. The diagnosis of BPAD was based on Mini-International Neuropsychiatric Interview 6.0.0. Sheehan's Disability Scale was used to assess the disability. Results: A total of 34,802 adults were interviewed. The overall weighted prevalence of BPAD was 0.3% [95% confidence interval (CI): 0.29-0.31] for current and 0.5% (95% CI: 0.49-0.51) for lifetime diagnosis. Male gender [odds ratio (OR) 1.56] and residence in urban metropolitans (OR 2.43) had a significantly higher risk of a lifetime diagnosis of BPAD. Substantial cross-sectional co-morbidities were noted as per MINI 6.0.0 with the diagnosis of current BPAD such as tobacco use disorder (33.3%), other substance use disorders (14.6%), and anxiety disorders (10.4%). Two-thirds of persons with current BPAD reported disability of varying severity at work (63%), social (59.3%), and family life (63%). The treatment gap for current BPAD was 70.4%. Conclusion: Most individuals with current BPAD reported moderate-severe disability. There were substantial co-morbidities and a large treatment gap. These warrant concentrated efforts from policymakers in devising effective strategies.

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.

Epidemiological analysis of mental health morbidity in Tamil Nadu.

Background: Existing psychiatric epidemiological studies from Tamil Nadu with methodological limitations and variations had under-reported the prevalence of mental morbidity. Robust data from a representative population-based epidemiological study are not readily available to guide mental health programs in Tamil Nadu. Aim: This study aimed to estimate the prevalence, correlates, and treatment gap of mental morbidity in the state of Tamil Nadu using data from National Mental Health Survey (NMHS) of India, 2015-2016. Materials and Methods: NMHS in Tamil Nadu was conducted in 60 clusters of 4 districts (Trichy, Tirunelveli, Thoothukudi, and Namakkal) using a door-to-door survey and multistage sampling proportionate to rural, urban nonmetro, and urban metro population. Mini-International Neuropsychiatric Interview (M.I.N.I version 6) and Fagerstrom nicotine dependence scale were administered on a representative adult (aged ≥18 years) sample to assess the mental morbidity. Prevalence and 95% confidence intervals (CIs) were estimated after weighing the sample for survey design. Results: A total of 3059 adults from 1069 households were interviewed. The overall weighted prevalence of lifetime and current mental morbidity was 19.3% (95% CI: 19.0%-19.6%) and 11.8% (95% CI: 11.6%-12.0%) respectively. Participants who were men (largely contributed by substance-use disorders), aged 40-49 years, from rural areas, and from lower income quintile had higher prevalence of mental morbidity. The treatment gap was 94.2% for any mental health problem. Common mental disorders (depression, anxiety, and substance-use) accounted for most of the morbidity. Conclusion: The burden and treatment gap for mental health morbidity is high in Tamil Nadu. The findings call for urgent policy level and systemic action to strengthen mental health program in Tamil Nadu.

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.

Prevalence and pattern of mental disorders in the state of West Bengal: Findings from the National Mental Health Survey of India 2016.

Background: West Bengal, situated in eastern India, comprising 19 districts as of 2016 and consisting of 9.13 crore population, had been one of the participating states in the National Mental Health Survey, 2015-16. Aim: To estimate the prevalence and pattern of mental disorders in a representative population in West Bengal. Materials and Methods: Based upon a multi-stage stratified random cluster sampling with probability proportionate to each stage, 2646 eligible individuals were interviewed. Standard validated instruments in Bengali like socio-demographic profiles and Mini International Neuropsychiatric Interview (MINI) version 6 were used by trained data collectors with quality monitoring as per a standardized protocol. Results: The current prevalence of mental illness in the state of West Bengal is 13.07% (12.9-13.24 95% CI), which is more than the current national average of 10.56% (10.51-10.61 95% CI). The prevalence of severe mental illness of 2.32% and suicide risk of 1.75% (1.68-1.81 95% CI) is higher than the national average. The common mental illness prevalence is 11.29 (11.13-11.45 95% CI), which is similar to the national weighted average. In West Bengal, severe mental illness is more concentrated in the rural areas in contrast to the national trend. Also, the prevalence of alcohol use disorder is 3.04 (2.96-3.13 95% CI) and epilepsy is 0.03 (0.27-0.29 95% CI), which is less than the national average. Conclusion: The prevalence of mental disorders in the state of West Bengal is higher than the national average, and for severe mental illness, the prevalence is the highest as compared to the national average.