Twelve-month prevalence and treatment gap for common mental disorders: Findings from a large-scale epidemiological survey in India

Determinants of access to health care for depression in 49 countries: A multilevel analysis

BACKGROUND

The relative importance of individual and country-level factors influencing access to diagnosis and treatment for depression across the world is fairly unknown.

METHODS

We analysed cross-national data from the WHO World Health Surveys. Depression diagnosis and access to health care were ascertained using a structured interview. Logistic Bayesian Multilevel analyses were performed to establish individual and country level factors associated with: (1) receiving a diagnosis and (2) accessing treatment for depression if a diagnosis was ascertained.

RESULTS

The sample included 7870 individuals from 49 countries who met ICD-10 criteria for depressive episode in the past 12 months. A third (32%) of these individuals had ever been diagnosed with depression in their lifetime. Among those diagnosed with depression, 66% reported to have ever received treatment for depression. Although individual factors were more important determinants of access to treatment for depression, country-level factors explained 27.6% of the variance in access to diagnosis and 24.1% in access to treatment. Access to treatment for depression improved with increasing country income. Female gender, better education, the presence of physical co-morbidity, more material assets, and living in urban areas were individual level determinants of better access.

LIMITATIONS

Data on other contextual factors was not available. Unmet need was likely underestimated, since only lifetime treatment data was available.

CONCLUSION

This study highlights major inequalities in access to a diagnosis and treatment of depression. Unlike the prevalence of depression, where contextual factors have shown to have less importance, a significant proportion of the variance in access to depression care was explained by country-level income.

Psychiatric morbidity in the community: A population based-study from Kerala

BACKGROUND

Estimates of psychiatric morbidity in the community will help service development. Participation of trained nonspecialist health-care providers will facilitate scaling up of services in resource-limited settings.

AIMS

This study aimed to estimate the prevalence of priority mental health problems in populations served by the District Mental Health Program (DMHP).

SETTINGS AND DESIGN

This is a population-based cross-sectional survey.

MATERIALS AND METHODS

We did stratified cluster sampling of households in five districts of Kerala. Trained Accredited Social Health Activists (ASHAs) identified people who had symptoms suggestive of schizophrenia or bipolar disorder. Clinicians evaluated the information collected by the ASHAs and designated individuals as probable cases of psychosis or noncases. Screening instruments such as General Health Questionnaire-12, CAGE questionnaire, and Everyday Abilities Scale for India were used for identifying common mental disorders (CMDs), clinically significant alcohol-related problems, and functional impairment.

RESULTS

We found 12.43% of the adult population affected by mental health conditions. We found CMD as most common with a prevalence of 9%. The prevalence of psychosis was 0.71%, clinically significant alcohol-related problems was 1.46%, and dementia and other cognitive impairments was 1.26%. We found informant-based case finding to be useful in the identification of psychosis.

CONCLUSIONS

Mental health problems are common. Nonspecialist health-care providers can be trained to identify psychiatric morbidity in the community. Their participation will help in narrowing the treatment gap. Embedding operational research to DMHP will make scaling up more efficient.