The researchers modeled several possible routes connecting these variables simultaneously. Demographic characteristics, socioeconomic circumstances, clinical conditions and behavioral risk factors were treated as predictors of general health and quality of life. Those two measures were then modeled as mediators of happiness. Path analysis was conducted in Stata to estimate direct relationships, indirect relationships through the proposed mediators, and total effects combining both routes. Because the study was cross-sectional, its statistical paths show associations within the analyzed model rather than establishing that one variable caused another or that changes in a factor would produce a corresponding change in happiness.

In the fitted model, higher socioeconomic status, employment and marriage were positively associated with happiness. Female sex and poorer general health had negative direct associations with the happiness score. The model’s broader set of important significant determinants included quality of life, general health status, socioeconomic status, male sex and total high-density lipoprotein cholesterol. The investigators also examined pathways involving common non-communicable diseases and their related risk factors. The findings therefore portray happiness as a construct embedded in a broader biopsychosocial pattern rather than as an outcome associated with health in isolation.

The final path model fit the observed data well. Its comparative fit index was 0.98, while the standardized root mean square residual was 0.017 and the root mean square error of approximation was 0.031. These model-fit statistics indicate that the proposed structure was consistent with the relationships in the dataset. The path analysis also separated direct associations from indirect effects passing through general health and quality of life, allowing the researchers to calculate total effects as the combination of the two. The study did not report longitudinal follow-up, experimental manipulation or evidence that the modeled causal sequence could be reversed.

Taken together, the results support the authors’ view that happiness and health are connected through intertwined clinical, social and behavioral conditions. Quality of life and general health emerged as central features of the network, while socioeconomic position, work and marital status were also associated with happiness scores. The authors suggest that stress reduction, physical activity, chronic disease management and quality-of-life improvement may be relevant domains for future health-promotion efforts, and they argue that measuring happiness could complement existing approaches to non-communicable disease prevention. Those implications remain proposals for intervention and prevention research rather than tested outcomes of this study. The principal evidence is observational and population-specific, so the clearest conclusion is that the fitted model identified meaningful associations among happiness, health, chronic conditions, socioeconomic circumstances and health-related behaviors in the Shahrekord cohort.

Subject of Research: Statistical associations among happiness, health, chronic diseases and socioeconomic factors in an Iranian adult cohort

Article Title: Relationship between common non-communicable diseases (NCDs), risk factors and happiness in Shahrekord PERSIAN Cohort Study: a path analysis model in Iran

Article References: Maarefi, J., Ahmadi, A., Kheiri, S., & Zarean, E. (2026). Relationship between common non-communicable diseases (NCDs), risk factors and happiness in Shahrekord PERSIAN Cohort Study: a path analysis model in Iran. BMC Psychology. https://doi.org/10.1186/s40359-026-05523-0

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05523-0

Keywords: happiness, quality of life, path analysis, noncommunicable diseases, PERSIAN Cohort Study, Shahrekord cohort, socioeconomic status, general health, cholesterol, cross-sectional study, Relationship, between