Impact of Public Health Interventions on Obesity and Type 2 Diabetes Prevention: A Simulation Study

Complexity in Epidemiology and Public Health. Addressing Complex Health Problems Through a Mix of Epidemiologic Methods and Data

Public health and the underlying disease processes are complex, often involving the interaction of biologic, social, psychologic, economic, and other processes that may be nonlinear and adaptive and have other features of complex systems. There is therefore a need to push the boundaries of public health beyond single-factor data analysis and expand the capacity of research methodology to tackle real-world complexities. This article sets out a way to operationalize complex systems thinking in public health, with a particular focus on how epidemiologic methods and data can contribute towards this end. Our proposed framework comprises three core dimensions-patterns, mechanisms, and dynamics-along which complex systems may be conceptualized. These dimensions cover seven key features of complex systems-emergence, interactions, nonlinearity, interference, feedback loops, adaptation, and evolution. We relate this framework to examples of methods and data traditionally used in epidemiology. We conclude that systematic production of knowledge on complex health issues may benefit from: formulation of research questions and programs in terms of the core dimensions we identify, as a comprehensive way to capture crucial features of complex systems; integration of traditional epidemiologic methods with systems methodology such as computational simulation modeling; interdisciplinary work; and continued investment in a wide range of data types. We believe that the proposed framework can support the systematic production of knowledge on complex health problems, with the use of epidemiology and other disciplines. This will help us understand emergent health phenomena, identify vulnerable population groups, and detect leverage points for promoting public health.

Evaluating the impact of community interventions on childhood obesity in populations living in low-income households in Los Angeles: A simulation study

BACKGROUND

The complex multifactorial nature of childhood obesity makes community interventions difficult to evaluate using traditional approaches; innovative methods are needed.

OBJECTIVE

To evaluate the impact of various interventions targeting childhood obesity-related behaviours, and classified as using a micro-level (e.g., home visitation programs) or macro-level (e.g., business practices) strategy, on obesity among children enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).

METHODS

We simulated a population of 1500 children enrolled in WIC, with specific diet, physical activity, breastfeeding behaviours and body mass index z-scores (BMIz), following them from age 2 to 5 years.

RESULTS

Combined interventions targeting breastfeeding appeared to be moderately effective, reducing BMIz by 0.03 (95% CI -005, -0.01). Two strategy-specific interventions, home visitation programs and business practices targeting obesity-related behaviours, appeared to be moderately effective at reducing BMIz by 0.04 (95% CI -0.06, -0.02) and 0.02 (95% CI -0.04, 0.00), respectively. Contrary to expectation, combining all micro and macro interventions appeared to have no impact or moderately increased the proportion of obesity/overweight among children.

CONCLUSION

Interventions targeting breastfeeding behaviour were most effective when both micro and macro strategies were implemented. Interventions targeting obesity-related behaviours in general were effective for two strategies, home visitation and business practices.

Forecasting Obesity and Type 2 Diabetes Incidence and Burden: The ViLA-Obesity Simulation Model

Background

Obesity is a major public health problem affecting millions of Americans and is considered one of the most potent risk factors for type 2 diabetes. Assessing future disease burden is important for informing policy-decision making for population health and healthcare.

Objective

The aim of this study was to develop a computer model of a cohort of children born in Los Angeles County to study the life course incidence and trends of obesity and its effect on type 2 diabetes mellitus.

Methods

We built the Virtual Los Angeles cohort—ViLA, an agent-based model calibrated to the population of Los Angeles County. In particular, we developed the ViLA-Obesity model, a simulation suite within our ViLA platform that integrated trends in the causes and consequences of obesity, focusing on diabetes as a key obesity consequence during the life course. Each agent within the model exhibited obesity- and diabetes-related healthy and unhealthy behaviors such as sugar-sweetened beverage consumption, physical activity, fast-food consumption, fresh fruits, and vegetable consumption. In addition, agents could gain or lose weight and develop type 2 diabetes mellitus with a certain probability dependent on the agent's socio-demographics, past behaviors and past weight or type 2 diabetes status. We simulated 98,230 inhabitants from birth to age 65 years, living in 235 neighborhoods.

Results

The age-specific incidence of obesity generally increased from 10 to 30% across the life span with two notable peaks at age 6–12 and 30–39 years, while that of type 2 diabetes mellitus generally increased from <2% at age 18–24 to reach a peak of 25% at age 40–49. The 16-year risks of obesity were 32.1% (95% CI: 31.8%, 32.4%) for children aged 2–17 and 81% (95% CI: 80.8%, 81.3%) for adults aged 18–65. The 48-year risk of type 2 diabetes mellitus was 53.4% (95% CI: 53.1%, 53.7%) for adults aged 18–65.

Conclusion

This ViLA-Obesity model provides an insight into the future burden of obesity and type 2 diabetes mellitus in Los Angeles County, one of the most diverse places in the United States. It serves as a platform for conducting experiments for informing evidence-based policy-making.

Impact of Policies in Nutrition and Physical Activity on Diabetes and Its Risk Factors in the 28 Member States of the European Union

Since healthy eating and physically active lifestyles can reduce diabetes mellitus (DM) risk, these are often addressed by population-based interventions aiming to prevent DM. Our study examined the impact of nutritional and physical activity policies, national diabetes plans and national diabetes registers contribute to lower prevalence of DM in individuals in the member states of the European Union (EU), taking into account the demographic and socioeconomic status as well as lifestyle choices. Datasets on policy actions, plans and registers were retrieved from the World Cancer Research Fund International's NOURISHING and MOVING policy databases and the European Coalition for Diabetes report. Individual-based data on DM, socioeconomic status and healthy behavior indicators were obtained via the European Health Interview Survey, 2014. Our results showed variation in types and numbers of implemented policies within the member states, additionally, the higher number of these actions were not associated with lower DM prevalence. Only weak correlation between the prevalence of DM and preventive policies was found. Thus, undoubtedly policies have an impact on reducing the prevalence of DM, its increasing burden could not be reversed which underlines the need for applying a network of preventive policies.

Simulation modeling to assess performance of integrated healthcare systems: Literature review to characterize the field and visual aid to guide model selection

BACKGROUND

The guiding principle of many health care reforms is to overcome fragmentation of service delivery and work towards integrated healthcare systems. Even though the value of integration is well recognized, capturing its drivers and its impact as part of health system performance assessment is challenging. The main reason is that current assessment tools only insufficiently capture the complexity of integrated systems, resulting in poor impact estimations of the actions taken towards the 'Triple Aim'. We describe the unique nature of simulation modeling to consider key health reform aspects: system complexity, optimization of actions, and long-term assessments.

RESEARCH QUESTION

How can the use and uptake of simulation models be characterized in the field of performance assessment of integrated healthcare systems?

METHODS

A systematic search was conducted between 2000 and 2018, in 5 academic databases (ACM D. Library, CINAHL, IEEE Xplore, PubMed, Web of Science) complemented with grey literature from Google Scholar. Studies using simulation models with system thinking to assess system performance in topics relevant to integrated healthcare were selected for revision.

RESULTS

After screening 2274 articles, 30 were selected for analysis. Five modeling techniques were characterized, across four application areas in healthcare. Complexity was defined in nine aspects, embedded distinctively in each modeling technique. 'What if?' & 'How to?' scenarios were identified as methods for system optimization. The mean time frame for performance assessments was 18 years.

CONCLUSIONS

Simulation models can evaluate system performance emphasizing the complex relations between components, understanding the system's adaptability to change in short or long-term assessments. These advantages position them as a useful tool for complementing performance assessment of integrated healthcare systems in their pursuit of the 'Triple Aim'. Besides literacy in modeling techniques, accurate model selection is facilitated after identification and prioritization of the complexities that rule system performance. For this purpose, a tool for selecting the most appropriate simulation modeling techniques was developed.

Diabetes Mellitus and Associated Factors in Slovakia: Results from the European Health Interview Survey 2009, 2014, and 2019

Diabetes mellitus (DM) is a high-risk non-communicable disease with an emerging burden for the European Union (EU) member states in the past decades. The unfavorable trend of the burden is striking compared to the declining disease burden due to cardiovascular diseases or stagnation of neoplasms. The goal of this study is to describe the temporal changes of diabetes in the adult population of Slovakia through the three European Health Interview Survey (EHIS) waves and to assess the association between DM and socioeconomic and/or lifestyle characteristics. These cross-sectional studies were carried out using microdata derived from Slovakia’s EHISs conducted in the years 2009 (n = 4972), 2014 (n = 5490), and 2019 (n = 5527). The DM variable was compared to the independent variables such as sociodemographic and lifestyle characteristics including dietary patterns and physical activity. DM prevalence for the EHIS in 2009, 2014, and 2019 were 6.1%, 8.2%, and 9.8%, respectively. In bivariate analysis, the relationship between DM and age, education level, job status, BMI, walking for at least 10 min, and physical activity was significant in the three EHISs. In 2014 and 2019, there was an inverse association between the risk of DM and walking regularly. There was no association between the frequency of eating fruits or vegetables and DM, with the exception of 2009, where a negative association between eating vegetables one to six times a week and DM was observed. Present health policies and activities in Slovakia were unable to reverse the increasing DM burden, indicating that a more systematic approach is needed. Complex policy strategies and legislative measures must be developed and implemented at both the national and EU levels.

Healthy measures: Feasibility study of a moderate carbohydrate weight management intervention

BACKGROUND

People of all weights need to prevent changes that could lead to obesity, a leading public health issue.

OBJECTIVE

To assess the feasibility of Healthy Measures, a moderate carbohydrate (160-300 g/d) nutrition education and behavioral intervention.

DESIGN

An uncontrolled intervention feasibility study including in-person group meetings every 2 weeks for 3 months.

SAMPLE

Fifteen participants of normal and overweight BMI.

MEASUREMENTS

We assessed feasibility of recruitment, attendance, retention and satisfaction as well as anthropometric measures and social cognitive variables with Healthy Measures, a nutrition-focused intervention with moderate carbohydrate portions that also emphasizes self-monitoring of anthropometric measurements. An intent-to-treat analysis was used.

RESULTS

Healthy Measures was feasible, with 13 participants (86.7%) completing pre- and post-intervention assessments. Eight participants lost or maintained weight (53.3%); four gained weight. Healthy eating self-efficacy increased overall (t = -2.54, p = .024). Increased protein and fat intake was associated with weight loss, while reduced protein, carbohydrate, and fat intake resulted in weight gain.

CONCLUSIONS

Healthy Measures shows promise for prevention of weight gain, with evidence of feasibility and positive outcomes. Further research is needed to establish efficacy relative to alternative approaches.

Investigating the Role of Childhood Adiposity in the Development of Adult Type 2 Diabetes in a 64-year Follow-up Cohort: An Application of the Parametric G-formula Within an Agent-based Simulation Study

BACKGROUND

The contribution of childhood obesity to adult type 2 diabetes (T2DM), not through adult adiposity, as well as the causal pathways through which childhood obesity increases adult T2DM risk are not well understood. This study investigated the contribution of childhood obesity to incident T2DM including pathways not through adult adiposity, and explored whether race modified this contribution.

METHODS

We used data from the Virtual Los Angeles Cohort, an agent-based longitudinal birth cohort composed of 98,230 simulated individuals born in 2009 and followed until age 65 years. We applied the parametric mediational g-formula to the causal mediation analysis investigating the impact of childhood obesity on the development of adult T2DM.

RESULTS

The marginal adjusted odds ratio (aOR) for the total effect of childhood obesity on adult T2DM was 1.37 (95% CI = 1.32, 1.46). Nearly all the effect of childhood obesity on adult T2DM was mostly attributable to pathways other than through adult obesity; the aOR for the pure direct effect was 1.36 (95% CI = 1.31, 1.41). In all racial subpopulations, a similar 3% of the total effect of childhood obesity on adult T2DM was attributable to its effect on adult obesity.

CONCLUSIONS

Childhood obesity remains a risk factor for adult T2DM separate from its effects on adult obesity. This study emphasizes the potential benefits of early interventions and illustrates that agent-based simulation models could serve as virtual laboratories for exploring mechanisms in obesity research.

Supplemental Nutrition Assistance Program Education in Los Angeles County: Lessons and observations from the field, 2013-2016

Although the California Department of Public Health has been delivering nutrition education for nearly two decades, the use of Supplemental Nutrition Assistance Program Education (SNAP-Ed) resources to advance policy, systems, and environmental change interventions (PSEs) to prevent obesity has been relatively recent. To date, most efforts to couple PSEs to conventional nutrition education have not been well-studied and as such, their lessons have not been used extensively in local planning. This special issue seeks to close this gap by sharing lessons from the planning and implementation of these efforts in Los Angeles County during the 2013-2016 SNAP-Ed funding cycle. It comprises a collection of six articles that recount key experiences from this work in the field.

Economic evaluation of California prenatal participation in the Special Supplemental Nutrition Program for Women, Infants and Children (WIC) to prevent preterm birth

There is growing evidence that prenatal participation in the Special Supplemental Nutrition Program for Women, Infants and Children (WIC) reduces the risk of adverse birth outcomes. With recent changes in health care, rising health care costs, and increasing rates of prematurity in the U.S., there is urgency to estimate the potential cost savings associated with prenatal WIC participation. A cost-benefit analysis from a societal perspective with a time horizon over the newborn's life course for a hypothetical cohort of 500,000 Californian pregnant women was conducted in 2017. A universal coverage, a status quo ('business as usual') and a reference scenario (absence of WIC) were compared. Total societal costs, incremental cost savings, return on investment, number of preterm births prevented, and incremental net monetary benefits were reported. WIC resulted in cost-savings of about $349 million and the prevention of 7575 preterm births and would save more if it were universal. Spending $1 on prenatal WIC resulted in mean savings of $2.48 (range: $1.24 to $6.83). Decreasing prenatal WIC enrollment by 10% would incur additional costs (i.e. loss) of about $45.3 million to treat the resulting 981 preterm babies. In contrast, a 10% increase in prenatal WIC enrollment would prevent 141 preterm births and achieve additional cost-savings of $6.5 million. The findings confirm evaluations from the early 1990s that prenatal WIC participation is cost-saving and cost-effective. Further savings could be achieved if all eligible women were enrolled in WIC. Substantial preterm birth-related costs would result from reductions in WIC participation.