PLoS One. 2025 Jul 31;20(7):e0328413. doi: 10.1371/journal.pone.0328413. eCollection 2025.
ABSTRACT
OBJECTIVES: To investigate patterns and correlates of depression among Norwegian older adults (age 70+), 1995-2019, and estimate the number of older adults with depression by 2050.
DESIGN: Population-based cross-sectional study.
SETTING AND PARTICIPANTS: Three surveys of the Trøndelag Health Study (Norway): HUNT2 (1995-96), HUNT3 (2007-08), and HUNT4 (2017-19). 22,822 home dwellers aged 70 + who participated in at least one of the three surveys.
METHODS: Depression was defined as scores ≥8 on the depression subscale of the Hospital Anxiety and Depression Scale. Covariates included sex, age, education, marital status, and reported loneliness. Depression prevalence (%) was standardized to the Norwegian population by age, sex, and education for years close to the initial HUNT survey year (1995, 2006, and 2016). Projection of the total number of individuals with depression in the coming decades were estimated. Predictors of depression were analyzed with logistic regression and the potential reduction in depression prevalence by reducing the prevalence of loneliness was estimated.
RESULTS: Standardized depression prevalence decreased from 16.7% (HUNT2) to 14.9% (HUNT3), and 11.5% (HUNT4), and was highest among men, the oldest (85+), the lower-educated, and in earlier surveys (all p < 0.001). Living alone was also associated with higher depression prevalence, but only if loneliness was present. While depression rates are falling, we expect the number of depressed individuals to double by 2050 as the population ages.
CONCLUSION AND IMPLICATIONS: Depression rates among adults aged 70 + decreased by 50% from 1995 to 2019, but less so among the oldest old. The rates were highest among single older men. Despite decreasing prevalence, the number of depressed older adults will increase significantly in the future. Given the major individual and societal costs of depression, this trend is alarming for societies preparing for the challenges posed by population aging. This can, however, be addressed by addressing predictors of depression.
PMID:40743243 | DOI:10.1371/journal.pone.0328413
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