Modelling Needs for Mental Healthcare from Epidemiological Surveys with Validation Using Sociodemographic Census Data

Area of Science:

• Public Health
• Epidemiology
• Sociology

Background:

• Mental health needs (MHN) and psychiatric needs (PN) assessment is crucial for resource allocation.
• Sociodemographic factors significantly influence mental health outcomes.
• Understanding variations in needs across different population densities is essential for targeted interventions.

Purpose of the Study:

• To develop and validate a prediction model for MHN and PN.
• To utilize social indicators from census data for prediction.
• To compare prediction accuracy in low-density departments (LDD) and high-density departments (HDD).

Main Methods:

• A population-based study of 20,404 participants in France.
• MHN and PN defined using standardized diagnostic and disability assessments.
• Logistic regression models fitted using sociodemographic data, validated with 2007 census data.

Main Results:

• Prevalence of MHN was 26.6% in LDD and 28.7% in HDD; PN was 9.8% in LDD and 11.3% in HDD.
• Predictors varied by density: LDD included housing type, age, employment, living alone, housing support, and household size.
• HDD predictors included housing type, living alone, household size, marital status, and dwelling duration; predictions were more accurate in HDD.

Conclusions:

• Sociodemographic indicators are valuable for predicting MHN and PN, particularly in high-density settings.
• Census data can be leveraged for predicting mental health needs.
• Further evaluation is needed to determine optimal territorial sizes for mental health resource planning.