Three Decades of Mental Health: Regression Reveals the Story

Suicide Rates Around the World (1985–2016)

Time Series Analysis Global Health Regression R

Executive Summary

This research examines global suicide trends from 1985 to 2016, analyzing patterns across time, gender, geography, and economic factors. The study specifically investigates whether a country's GDP affects its suicide rates, challenging common assumptions about economic prosperity and mental health outcomes.

Key Finding

Statistical analysis found no significant correlation between a country's GDP (both annual and per capita) and its suicide rates, with p-values of 0.846 and 0.460 respectively. This challenges the assumption that economic factors are primary drivers of suicide rates across countries.

Study Period

31 Years

1985–2016

Countries Analyzed

101

Across multiple continents

Gender Disparity

4:1

Male to female suicide ratio

Global Trends & Patterns

Global Suicide Rate Trends 1985-2016

Global suicide rates over time, showing peak in 1995 and subsequent decline

Temporal Trends

The analysis revealed distinct patterns in global suicide rates over the 31-year study period:

  • Global suicide rates increased until 2002 and have since decreased
  • The highest rate occurred in 1995 (15.7 per 100,000 population)
  • By 2015, rates had fallen to 11.1 per 100,000 population
  • The trend shows a clear inverted U-shape pattern over the study period

Gender Disparities

The study found significant differences in suicide rates between males and females:

  • Males have approximately four times higher suicide rates than females (20 vs. 5.4 per 100,000)
  • Male suicide rates fluctuated significantly, peaking in 1995
  • Female rates have steadily decreased since 1985 without major spikes
  • The gender disparity persisted across all regions and time periods

Regional Variations

European and Asian regions show approximately double the suicide rates of North America and Australia, with Lithuania having the highest rate (68.14 per 100,000 for males). This suggests that cultural, social, and healthcare factors may play more significant roles than economic development.

World Map of Suicide Rates

Economic Analysis

A central question of this research was whether economic factors, particularly GDP, correlate with suicide rates across countries. The analysis tested both annual GDP and GDP per capita as potential predictors.

GDP vs Suicide Rate Correlation

Scatter plot showing lack of correlation between GDP per capita and suicide rates

Statistical Findings

The regression analysis found no statistically significant relationship between GDP metrics and suicide rates:

  • Annual GDP correlation: p-value = 0.846 (not significant)
  • GDP per capita correlation: p-value = 0.460 (not significant)
  • R-squared values were extremely low, indicating GDP explains very little variance in suicide rates

Regression Model Specifications

The analysis employed multiple regression models to test the relationship between economic factors and suicide rates:

Model 1: Annual GDP

lm(formula = suicide_rate ~ annual_gdp, data = country_data)

Coefficients:
              Estimate   Std. Error   t value   Pr(>|t|)    
(Intercept)  1.324e+01   5.629e-01    23.52    <2e-16 ***
annual_gdp   3.139e-14   1.607e-13     0.20     0.846    

Residual standard error: 5.63 on 99 degrees of freedom
Multiple R-squared:  0.0003865, Adjusted R-squared:  -0.009707
F-statistic: 0.03825 on 1 and 99 DF,  p-value: 0.8454

Model 2: GDP Per Capita

lm(formula = suicide_rate ~ gdp_per_capita, data = country_data)

Coefficients:
                 Estimate   Std. Error   t value   Pr(>|t|)    
(Intercept)     1.287e+01   6.515e-01    19.76    <2e-16 ***
gdp_per_capita  4.836e-05   6.515e-05     0.74     0.460    

Residual standard error: 5.619 on 99 degrees of freedom
Multiple R-squared:  0.005531, Adjusted R-squared:  -0.004517
F-statistic: 0.5501 on 1 and 99 DF,  p-value: 0.4599

Data Limitations

  • Missing data from many African countries and parts of South America and Southern Asia
  • Potential underreporting in countries with strong religious or cultural taboos around suicide
  • Variations in reporting methods and definitions across countries
  • Limited socioeconomic variables beyond GDP metrics

Research Implications

Mental Health Policy

The findings suggest that mental health interventions should not be based solely on economic development indicators, as GDP appears unrelated to suicide rates.

Regional Approaches

The significant regional variations indicate that culturally specific approaches to suicide prevention may be more effective than universal strategies.

Gender-Specific Programs

The consistent 4:1 male-to-female suicide ratio suggests the need for gender-specific mental health interventions, particularly targeting men.

COVID-19 Context

This research established a baseline understanding for comparison with future data, particularly from the COVID-19 pandemic period. The findings suggest that economic downturns alone may not necessarily lead to increased suicide rates, though more research is needed on this specific relationship.

Conclusion & Future Directions

This analysis challenges common assumptions about the relationship between economic prosperity and suicide rates. The lack of correlation between GDP indicators and suicide rates suggests that mental health outcomes are influenced by a complex interplay of factors beyond economic development.

Key Takeaways

Future Research Directions