Background: Addressing non-communicable disease (NCDs) is a global priority in the Sustainable Development Goals, especially for adolescents. However, existing literature on NCD burden, risk factors and determinants, and effective interventions and policies for targeting these diseases in adolescents, is limited. This study develops an evidence-based conceptual framework, and highlights pathways between risk factors and interventions to NCD development during adolescence (ages 10–19 years) and continuing into adulthood. Additionally, the epidemiologic profile of key NCD risk factors and outcomes among adolescents and preventative NCD policies/laws/legislations are examined, and a multivariable analysis is conducted to explore the determinants of NCDs among adolescents and adults. Methods: We reviewed literature to develop an adolescent-specific conceptual framework for NCDs. Global data repositories were searched from Jan-July 2018 for data on NCD-related risk factors, outcomes, and policy data for 194 countries from 1990 to 2016. Disability-Adjusted Life Years were used to assess disease burden. A hierarchical modeling approach and ordinary least squares regression was used to explore the basic and underlying causes of NCD burden. Results: Mental health disorders are the most common NCDs found in adolescents. Adverse behaviours and lifestyle factors, specifically smoking, alcohol and drug use, poor diet and metabolic syndrome, are key risk factors for NCD development in adolescence. Across countries, laws and policies for preventing NCD-related risk factors exist, however those targeting contraceptive use, drug harm reduction, mental health and nutrition are generally limited. Many effective interventions for NCD prevention exist but must be implemented at scale through multisectoral action utilizing diverse delivery mechanisms. Multivariable analyses showed that structural/macro, community and household factors have significant associations with NCD burden among adolescents and adults. Conclusions: Multi-sectoral efforts are needed to target NCD risk factors among adolescents to mitigate disease burden and adverse outcomes in adulthood. Findings could guide policy and programming to reduce NCD burden in the sustainable development era.

Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term “context”; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the “messiness” that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By embracing uncertainty and adapting innovatively, complexity thinking enables system actors to engage meaningfully and comfortably in healthcare system transformation.

Despite increasing global attention to adolescent health in low- and middle-income countries (LMICs), limited literature exists on the timing of pubertal development in these settings. This study aimed to determine the age at menarche (AAM) and age of puberty onset [female Tanner Stage Breast 2 (B2) and male Tanner Stage Genital 2 (G2)] among healthy adolescents living in LMICs. It also aimed to explore the impact of nutritional status on pubertal timing in this population. MEDLINE, Embase, Cochrane CENTRAL, Web of Science, Scopus, and grey literature databases were searched. Observational studies and control arms of randomized controlled trials (RCTs) with healthy participants from LMICs born in or after 1998 were included. Pooled estimates with 95% CIs were calculated by random-effects meta-analyses using the DerSimonian and Laird inverse variance method for each pubertal milestone and by BMI category subgroups. Twenty-seven studies were included in the meta-analysis, representing 90,188 adolescents (78.3% female). Pooled mean estimates for AAM for normal, thin, and overweight BMI groupings were 12.3 y (95% CI: 12.1, 12.5), 12.4 y (95% CI: 12.2, 12.6), and 12.1 y (95% CI: 11.7, 12.5), respectively. For Tanner Stage B2, pooled mean age estimates for normal, thin, and overweight BMI groupings were 10.4 y (95% CI: 9.2, 11.6), 10.2 y (95% CI: 9.3, 11.4), and 8.4 y (95% CI: 6.8, 10.0), respectively. Finally, for Tanner Stage G2, pooled mean estimates for normal, thin, and overweight BMI groupings were 11.0 y (95% CI: 10.3, 11.7), 11.3 y (95% CI: 9.8, 12.9), and 10.3 y (95% CI: 10.0, 10.6), respectively. Data on the timing of pubertal milestones has traditionally come from high-income settings. In this systematic review of contemporary data from adolescents in LMICs, AAM, as well as age at pubertal onset, were similar to those reported from high-income settings.