SummaryObjective: This systematic examination and meta-analysis examined the scope and variation of the worldwide double burden of diseases and identified related socio-demographic factors.Design: We searched PubMed for studies published in English from January 1, 2000, through September 28, 2016, that reported on double disease burden. Twenty-nine studies from 18 high-income, middle-income and low-income countries met inclusion criteria and provided 71 obesity-undernutrition ratios, which were included in meta-regression analysis.Results: All high-income countries had a much higher prevalence of obesity than undernutrition (i.e. all the obesity/undernutrition ratios >1); 55% of the ratios in lower middle-income and low-income countries were <1, but only 28% in upper middle-income countries. Meta-analysis showed a pooled obesity-undernutrition ratio of 4.3 (95% CI = 3.1-5.5), which varied by country income level, subjects' age and over time. The average ratio was higher in high-income rather than that in lower middle-income and low-income countries Conclusions: There are considerable differences in the obesity versus undernutrition ratios and in their prevalence by country income level, age groups and over time, which may be a consequence of the cumulative exposure to an obesogenic environment.

Obesity is a complex system problem involving a broad spectrum of policy, social, economic, cultural, environmental, behavioural, and biological factors and the complex interrelated, cross-sector, non-linear, dynamic relationships among them. Systems modelling is an innovative approach with the potential for advancing obesity research. This study examined the applications of systems modelling in obesity research published between 2000 and 2017, examined how the systems models were developed and used in obesity studies and discussed related gaps in current research. We focused on the applications of two main systems modelling approaches: system dynamics modelling and agent-based modelling. The past two decades have seen a growing body of systems modelling in obesity research. The research topics ranged from micro-level to macro-level energy-balance-related behaviours and policies (19 studies), population dynamics (five studies), policy effect simulations (eight studies), environmental (10 studies) and social influences (15 studies) and their effects on obesity rates. Overall, systems analysis in public health research is still in its early stages, with limitations linked to model validity, mixed findings and its actual use in guiding interventions. Challenges in theory and modelling practices need to be addressed to realize the full potential of systems modelling in future obesity research and interventions.