To identify enablers and barriers for scaling up non-communicable disease (NCD) interventions across diverse global contexts and to map these factors to the WHO’s health system building blocks.

A multi-method qualitative study applying the Consolidated Framework for Implementation Research to analyse data from multiple projects nearing or completing scale-up.

Global Alliance for Chronic Diseases-funded implementation research projects conducted across 18 low- and middle-income countries and high-income settings.

Data was derived from documents (n=77) including peer-reviewed publications, policy briefs, and reports and interviews with stakeholders (n=18) (eg, principal investigators, medical professionals, public health workers).

Various context-specific interventions targeting sustainable scale-up of NCD (eg, diabetes, hypertension, cardiovascular disease) interventions at the community, primary care or policy levels.

The primary outcome was identifying contextual enablers and barriers to intervention scale-up. Secondary outcomes included exploring how these factors aligned with health system building blocks (eg, leadership/governance, healthcare workforce).

Twenty enablers (eg, intervention adaptability, strong stakeholder engagement, local empowerment) and 25 barriers (eg, resource limitations, intervention complexity, stakeholder burnout) were identified. Contextual alignment, supportive governance and capacity building were critical for sustainability, while cultural misalignment and socio-political instability frequently hampered scaling efforts.

Tailoring interventions to local health systems, ensuring stakeholder co-ownership and incorporating strategies to mitigate stakeholder burn-out are essential to achieving sustainable, scalable NCD solutions. Future research should focus on integrating systematic cultural adaptation, sustainable financing and workforce capacity building into scale-up planning.

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.