This study aims to investigate the associations between childhood health, childhood socioeconomic status and dementia risk in later life, and to assess the potential modifying effects of their interaction. The study also accounted for key confounders to better clarify these relationships within the Indonesian population.

Cross-sectional study.

Indonesia.

6693 aged 50+.

Individuals in the ‘unhealthy’ childhood health cluster had 1.17 times higher odds of dementia risk compared with the ‘healthy’ cluster (95% CI: 1.00 to 1.38), a borderline association, while those in the ‘poor socioeconomic status’ cluster had 1.39 times higher odds compared with the ‘non-poor’ cluster (95% CI: 1.15 to 1.68). No significant interaction was found between childhood health and socioeconomic status on either the multiplicative (OR=0.88, 95% CI: 0.30 to 2.57) or additive scale (all relative excess risk due to interaction, attributable proportion and synergy index measures non-significant). Older age, lower education, lower wealth, lower social capital and higher depression scores are significantly associated with increased dementia risk.

This study finds that both childhood health and socioeconomic status independently influence dementia risk in later life. No significant interaction between these two early-life factors was found, suggesting that their effects on dementia risk operate independently rather than synergistically. Using nationally representative Indonesian data, the findings highlight the importance of addressing early-life adversity in dementia prevention and call for standardised definitions to improve research comparability, particularly in low-income and middle-income countries contexts.

While childhood circumstances predict mental health outcomes in high-income countries, evidence from low-income and middle-income countries (LMICs) like Indonesia remains scarce. This study examines the long-term association between childhood socioeconomic status (SES), health and depressive symptoms in adulthood, testing the hypothesis that early-life disadvantages increase the odds of depressive symptoms later in life.

Cross-sectional analysis using latent class analysis to cluster childhood SES/health and logistic regression to assess associations with depressive symptoms.

A nationally representative household survey was conducted across 13 provinces in urban and rural areas of Indonesia.

32 085 adults aged 18 years and older from the 2014–2015 Indonesia Family Life Survey. Participants with missing data on childhood circumstances or depressive symptoms were excluded, resulting in a final analytic sample of 29 140 individuals.

The primary outcome was depressive symptoms measured using the 10-item Centre for Epidemiologic Studies Depression Scale, with scores ≥10 indicating clinically significant symptoms. Secondary exposures included latent classes of childhood SES and health (high, moderate and low disadvantage). Analyses adjusted for adult SES, health behaviours, social capital and demographic characteristics.

Three latent classes emerged: low (64.85%), moderate (5.73%) and high (29.42%) early-life disadvantage. Adjusted logistic regression showed higher odds of depressive symptoms for high (OR 1.39, 95% CI 1.28 to 1.50) and moderate disadvantage (OR 1.66, 95% CI 1.48 to 1.87) versus low. Significant covariates included age, education, wealth and social capital (all p

Early-life disadvantages predict depressive symptoms in adulthood in Indonesia, underscoring the need for child-focused interventions (health, education and poverty reduction) to mitigate long-term mental health risks in LMICs. Further research should explore longitudinal mechanisms.

The current diagnostic pathway for patients with a suspected inherited bleeding disorder is long, costly, resource intensive, emotionally draining for patients and often futile, as half of patients will remain without a diagnosis and be labelled ‘bleeding disorder of unknown cause’. Advances in understanding the genetic basis of the inherited bleeding disorders, coupled with both increasing infrastructure for genetic/genomic testing and decreasing costs, have increased the feasibility of introducing genomic testing into the clinical diagnostic pathway as a potential solution to improve the care of these patients. Yet, there remain evidence gaps on the optimal integration of genomic analysis into the diagnostic pathway.

Using a multicentre randomised-controlled trial design, we will evaluate an early genomic testing strategy for the diagnosis of newly referred patients with a suspected inherited bleeding disorder. Eligible participants will be randomised to early genomic testing diagnostic pathway (intervention) or standard diagnostic pathway (control) and will be followed for a 12-month period. Patients in the control group who remain undiagnosed at study end will be offered identical early genomic testing to ensure equitable access to the intervention. The study will follow a parallel fixed design with waitlist control group and a 1:1 allocation ratio. The study will be conducted at three tertiary care centres in Ontario, Canada, with a target sample size of 212 participants. Clinical utility will be evaluated via the primary outcome of diagnostic yield, as well as the secondary outcome of time to diagnosis. Additional secondary outcomes will allow for assessment of patient impact via health-related quality of life and patient burden measures, as well as evaluation of economic impact through a cost-effectiveness analysis and budget impact analysis.

This investigator-initiated study was approved by the Queen’s University Health Sciences and Affiliated Teaching Hospitals Research Ethics Board through Clinical Trials Ontario (CTO-4909). Participant informed consent/assent is required. Findings will be disseminated through academic publications.

ClinicalTrials.gov, NCT06736158.