Development of an action programme tackling obesity-related behaviours in adolescents: a participatory system dynamics approach.

System dynamics approaches are increasingly addressing the complexity of public health problems such as childhood overweight and obesity. These approaches often use system mapping methods, such as the construction of causal loop diagrams, to gain an understanding of the system of interest. However, there is limited practical guidance on how such a system understanding can inform the development of an action programme that can facilitate systems changes. The Lifestyle Innovations Based on Youth Knowledge and Experience (LIKE) programme combines system dynamics and participatory action research to improve obesity-related behaviours, including diet, physical activity, sleep and sedentary behaviour, in 10-14-year-old adolescents in Amsterdam, the Netherlands. This paper illustrates how we used a previously obtained understanding of the system of obesity-related behaviours in adolescents to develop an action programme to facilitate systems changes. A team of evaluation researchers guided interdisciplinary action-groups throughout the process of identifying mechanisms, applying the Intervention Level Framework to identify leverage points and arriving at action ideas with aligning theories of change. The LIKE action programme consisted of 8 mechanisms, 9 leverage points and 14 action ideas which targeted the system's structure and function within multiple subsystems. This illustrates the feasibility of developing actions targeting higher system levels within the confines of a research project timeframe when sufficient and dedicated effort in this process is invested. Furthermore, the system dynamics action programme presented in this study contributes towards the development and implementation of public health programmes that aim to facilitate systems changes in practice.

Healthy ageing in a multi-ethnic population: A descriptive cross-sectional analysis from the HELIUS study.

OBJECTIVE: We investigated ethnic health disparities in the Healthy Life in an Urban Setting multi-ethnic cohort using the multidimensional Healthy Ageing Score. STUDY DESIGN: We conducted a cross-sectional analysis of the study baseline data (2011-2015) collected through questionnaires/physical examinations for 17,091 participants (54.8 % women, mean (SD) age = 44.5 (12.8) years) from South-Asian Surinamese (14.8 %), African Surinamese (20.5 %), Dutch (24.3 %), Moroccan (15.5 %), Turkish (14.9 %), and Ghanaian (10.1 %) origins, living in Amsterdam, the Netherlands. MAIN OUTCOME MEASURES: We computed the Healthy Ageing Score developed in the Rotterdam Study, which has seven biopsychosocial domains: chronic diseases, mental health, cognitive function, physical function, pain, social support, and quality of life. That score was used to discern between healthy, moderate, and poor ageing. We explored differences in healthy ageing by ethnicity, sex, and age group using multinomial logistic regression. RESULTS: The Healthy Ageing Score [overall: poor (69.0 %), moderate (24.8 %), and healthy (6.2 %)] differed between ethnicities and was poorer in women and after midlife (cut-off 45 years) across ethnicities (all p < 0.001). In the fully adjusted models in men and women, poor ageing (vs. healthy ageing) was highest in the South-Asian Surinamese [adjusted odds ratios (95 % confidence intervals)] [2.96 (2.24-3.90) and 6.88 (3.29-14.40), respectively] and Turkish [2.80 (2.11-3.73) and 7.10 (3.31-15.24), respectively] vs. Dutch, in the oldest [5.89 (3.62-9.60) and 13.17 (1.77-98.01), respectively] vs. youngest, and in the divorced [1.48 (1.10-2.01) and 2.83 (1.39-5.77), respectively] vs. married. Poor ageing was inversely associated with educational and occupational levels, mainly in men. CONCLUSIONS: Compared with those of Dutch ethnic origin, ethnic minorities displayed less healthy ageing, which was more pronounced in women, before and after midlife, and was associated with sociodemographic factors.

Why we struggle to make progress in obesity prevention and how we might overcome policy inertia: Lessons from the complexity and political sciences.

Despite evidence for the effectiveness of policies that target obesogenic environments, their adoption remains deficient. Using methods and concepts from complexity and political science (Stock-and-Flow analysis and Punctuated Equilibrium Theory) and a qualitative literature review, we developed system maps to identify feedback loops that hinder policymaking on mitigating obesogenic environments and feedback loops that could trigger and sustain policy change. We found numerous self-reinforcing feedback loops that buttress the assumption that obesity is an individual problem, strengthening the biomedical and commercial weight-loss sectors' claim to "ownership" over solutions. That is, improvements in therapies for individuals with obesity reinforces policymakers' reluctance to target obesogenic environments. Random events that focus attention on obesity (e.g., celebrities dismissing soda) could disrupt this cycle, when actors from outside the medical and weight-loss sector (e.g., anti-weight stigma activists) successfully reframe obesity as a societal problem, which requires robust and politically relevant engagement with affected communities prior to such events taking place. Sustained prioritization of policies targeting obesogenic environments requires shared problem ownership of affected communities and nonhealth government sectors, by emphasizing cobenefits of policies that target obesogenic environments (e.g., ultraprocessed food taxation for raising revenue) and solutions that are meaningful for affected communities.

Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis.

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.

SARS-CoV-2 vaccination uptake in six ethnic groups living in Amsterdam, the Netherlands: A registry-based study within the HELIUS cohort.

OBJECTIVE: Ethnic minority groups have experienced a disproportionate burden of COVID-19, and should therefore be especially encouraged to receive SARS-CoV-2 vaccination. This study compared first-dose uptake of the primary SARS-CoV-2 vaccination series across six ethnic groups in Amsterdam, the Netherlands in 2021. METHODS: We analyzed data from participants of the population-based HELIUS cohort. We linked their data to the SARS-CoV-2 vaccination registry data of the Public Health Service of Amsterdam. We included registry data from January 6, 2021 (the start of the Dutch vaccination campaign) until September 6, 2021 (a date by which all adults in the Netherlands could have received one or two vaccine doses). SARS-CoV-2 vaccination uptake was defined as having received at least one vaccine dose of the primary vaccination series. We examined the association between ethnicity and vaccination uptake using multivariable logistic regression, while accounting for the age and sex distribution of ethnic groups in Amsterdam. RESULTS: We included 19,006 participants (median age 53 years [interquartile range 41-62], 57% female). SARS-CoV-2 vaccination uptake was highest in the South-Asian Surinamese group (60.3%, 95%CI = 58.2-62.3%), followed by the Dutch (59.6%, 95%CI = 58.0-61.1%), Ghanaian (54.1%, 95%CI = 51.7-56.5%), Turkish (47.7%, 95%CI = 45.9-49.6%), African Surinamese (43.0%, 95%CI = 41.2-44.7%), and Moroccan (35.8%, 95%CI = 34.1-37.5%) groups. After adjusting for age, sex, perceived social support, and presence of relevant comorbidities, participants of African Surinamese, Ghanaian, Turkish and Moroccan origin were significantly less likely to be vaccinated than those of Dutch origin. CONCLUSIONS: Prevention strategies should continue tailoring to specific ethnic groups to encourage vaccination uptake and reduce barriers to vaccination.

Ethnic Differences in Carotid Intima Media Thickness and Plaque Presence - The HELIUS study.

Introduction In the Netherlands, the prevalence of cardiovascular diseases (CVD) is higher among South-Asian Surinamese and lower among Moroccans compared to the Dutch. Traditional risk factors for atherosclerotic CVD do not fully explain these disparities. We aim to assess ethnic differences in plaque presence and intima media thickness (cIMT) and explore to which extent these differences are explained by traditional risk factors. Methods We used cross-sectional data from a subgroup of participants enrolled in the multi-ethnic population-based HEalthy Life In an Urban Setting (HELIUS) study who underwent carotid ultrasonography. Logistic and linear regression models were built to assess ethnic differences in plaque presence and cIMT with the Dutch population as reference. Additional models were created to adjust for socioeconomic status, body height and cardiovascular risk factors. Results Of the 3022 participants, 1183, 1051 and 790 individuals were of Dutch, South-Asian Surinamese and Moroccan descent. Mean age was 60.9 years (SD 8.0), 52.8% was female. Compared to the Dutch, we found lower odds for plaque presence in Moroccans (0.77, 95% CI 0.62; 0.95) and no significant differences between the South-Asian Surinamese and Dutch population (0.91, 95% CI 0.76; 1.10). After adjustment for CVD risk factors, we found a lower plaque presence in South-Asian Surinamese (0.63, 95% CI 0.48; 0.82). In both Moroccan and South-Asian Surinamese individuals, adjustment for socioeconomic status did not materially change the results. cIMT was lower in South-Asian Surinamese compared to the Dutch (-17.9 µm, 95% CI -27.9; -7.9) and partly explained by ethnic differences in body height as South-Asian Surinamese individuals were, on average, shorter than the Dutch population. No differences in cIMT between Moroccans and Dutch were found. Conclusions cIMT and plaque prevalence differ between ethnic groups independent of CVD risk. Lower plaque prevalence in Moroccans was partly attributable to a lower prevalence of traditional CVD risk factors, while body height was an important contributor to differences in cIMT in South-Asians. This study emphasizes the need for ethnic-specific cut-off values for plaque presence and cIMT.

Using network analysis to identify leverage points based on causal loop diagrams leads to false inference.

Network analysis is gaining momentum as an accepted practice to identify which factors in causal loop diagrams (CLDs)-mental models that graphically represent causal relationships between a system's factors-are most likely to shift system-level behaviour, known as leverage points. This application of network analysis, employed to quantitatively identify leverage points without having to use computational modelling approaches that translate CLDs into sets of mathematical equations, has however not been duly reflected upon. We evaluate whether using commonly applied network analysis metrics to identify leverage points is justified, focusing on betweenness- and closeness centrality. First, we assess whether the metrics identify the same leverage points based on CLDs that represent the same system but differ in inferred causal structure-finding that they provide unreliable results. Second, we consider conflicts between assumptions underlying the metrics and CLDs. We recognise six conflicts suggesting that the metrics are not equipped to take key information captured in CLDs into account. In conclusion, using betweenness- and closeness centrality to identify leverage points based on CLDs is at best premature and at worst incorrect-possibly causing erroneous identification of leverage points. This is problematic as, in current practice, the results can inform policy recommendations. Other quantitative or qualitative approaches that better correspond with the system dynamics perspective must be explored.

A data-driven computational model for obesity-driven diabetes onset and remission through weight loss.

Obesity is a major risk factor for the development of type 2 diabetes (T2D), where a sustained weight loss may result in T2D remission in individuals with obesity. To design effective and feasible intervention strategies to prevent or reverse T2D, it is imperative to study the progression of T2D and remission together. Unfortunately, this is not possible through experimental and observational studies. To address this issue, we introduce a data-driven computational model and use human data to investigate the progression of T2D with obesity and remission through weight loss on the same timeline. We identify thresholds for the emergence of T2D and necessary conditions for remission. We explain why remission is only possible within a window of opportunity and the way that window depends on the progression history of T2D, individual's metabolic state, and calorie restrictions. These findings can help to optimize therapeutic intervention strategies for T2D prevention or treatment.

Socioeconomic Inequalities in Type 2 Diabetes: Mediation Through Status Anxiety?

Objectives: While status anxiety has received attention as a potential mechanism generating health inequalities, empirical evidence is still limited. Studies have been ecological and have largely focused on mental and not physical health outcomes. Methods: We conducted individual-level analyses to assess status anxiety (feelings of inferiority resulting from social comparisons) and resources (financial difficulties) as mediators of the relationship between socioeconomic status (SES) (education/occupation/employment status) and type 2 diabetes (T2D). We used cross-sectional data of 21,150 participants (aged 18-70 years) from the Amsterdam-based HELIUS study. We estimated associations using logistic regression models and estimated mediated proportions using natural effect modelling. Results: Odds of status anxiety were higher among participants with a low SES [e.g., OR = 2.66 (95% CI: 2.06-3.45) for elementary versus academic occupation]. Odds of T2D were 1.49 (95% CI: 1.12-1.97) times higher among participants experiencing status anxiety. Proportion of the SES-T2D relationship mediated was 3.2% (95% CI: 1.5%-7.0%) through status anxiety and 10.9% (95% CI: 6.6%-18.0%) through financial difficulties. Conclusion: Status anxiety and financial difficulties played small but consistent mediating roles. These individual-level analyses underline status anxiety's importance and imply that status anxiety requires attention in efforts to reduce health inequalities.

A Culturally Adapted Diet and Physical Activity Text Message Intervention to Prevent Type 2 Diabetes Mellitus for Women of Pakistani Origin Living in Scotland: Formative Study.

BACKGROUND: Individuals of South Asian origin are at an increased risk of developing type 2 diabetes mellitus (T2DM) compared with other ethnic minority groups. Therefore, there is a need to develop interventions to address, and reduce, this heightened risk. OBJECTIVE: We undertook formative work to develop a culturally adapted diet and physical activity text message intervention to prevent T2DM for women of Pakistani origin living in Scotland. METHODS: We used a stepwise approach that was informed by the Six Steps in Quality Intervention Development framework, which consisted of gathering evidence through literature review and focus groups (step 1), developing a program theory for the intervention (step 2), and finally developing the content of the text messages and an accompanying delivery plan (step 3). RESULTS: In step 1, we reviewed 12 articles and identified 3 key themes describing factors impacting on diet and physical activity in the context of T2DM prevention: knowledge on ways to prevent T2DM through diet and physical activity; cultural, social, and gender norms; and perceived level of control and sense of inevitability over developing T2DM. The key themes that emerged from the 3 focus groups with a total of 25 women were the need for interventions to provide "friendly encouragement," "companionship," and a "focus on the individual" and also for the text messages to "set achievable goals" and include "information on cooking healthy meals." We combined the findings of the focus groups and literature review to create 13 guiding principles for culturally adapting the text messages. In step 2, we developed a program theory, which specified the main determinants of change that our text messages should aim to enhance: knowledge and skills, sense of control, goal setting and planning behavior, peer support, and norms and beliefs guiding behavior. In step 3, we used both the intervention program theory and guiding principles to develop a set of 73 text messages aimed at supporting a healthy diet and 65 text messages supporting increasing physical activity. CONCLUSIONS: We present a theory-based approach to develop a culturally adapted diet and physical activity text message intervention to prevent T2DM for women of Pakistani origin living in Scotland. This study outlines an approach that may also be applicable to the development of interventions for other ethnic minority populations in diverse settings. There is now a need to build on this formative work and undertake a feasibility trial of a text message-based diet and physical activity intervention to prevent T2DM for women of Pakistani origin living in Scotland.

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis.

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.

Digital health for all: How digital health could reduce inequality and increase universal health coverage.

Digital transformation in health care has a lot of opportunities to improve access and quality of care. However, in reality not all individuals and communities are benefiting equally from these innovations. People in vulnerable conditions, already in need of more care and support, are often not participating in digital health programs. Fortunately, numerous initiatives worldwide are committed to make digital health accessible to all citizens, stimulating the long-cherished global pursuit of universal health coverage. Unfortunately initiatives are not always familiar with each other and miss connection to jointly make a significant positive impact. To reach universal health coverage via digital health it is necessary to facilitate mutual knowledge exchange, both globally and locally, to link initiatives and apply academic knowledge into practice. This will support policymakers, health care providers and other stakeholders to ensure that digital innovations can increase access to care for everyone, leading towards Digital health for all.

Relative contributions of pre-pandemic factors and intra-pandemic activities to differential COVID-19 risk among migrant and non-migrant populations in the Netherlands: lessons for future pandemic preparedness.

BACKGROUND: Although risk factors for differences in SARS-CoV-2 infections between migrant and non-migrant populations in high income countries have been identified, their relative contributions to these SARS-CoV-2 infections, which could aid in the preparation for future viral pandemics, remain unknown. We investigated the relative contributions of pre-pandemic factors and intra-pandemic activities to differential SARS-CoV-2 infections in the Netherlands by migration background (Dutch, African Surinamese, South-Asian Surinamese, Ghanaians, Turkish, and Moroccan origin). METHODS: We utilized pre-pandemic (2011-2015) and intra-pandemic (2020-2021) data from the HELIUS cohort, linked to SARS-CoV-2 PCR test results from Public Health Service of Amsterdam (GGD Amsterdam). Pre-pandemic factors included socio-demographic, medical, and lifestyle factors. Intra-pandemic activities included COVID-19 risk aggravating and mitigating activities such as physical distancing, use of face masks, and other similar activities. We calculated prevalence ratios (PRs) in the HELIUS population that was merged with GGD Amsterdam PCR test data using robust Poisson regression (SARS-CoV-2 PCR test result as outcome, migration background as predictor). We then obtained the distribution of migrant and non-migrant populations in Amsterdam as of January 2021 from Statistics Netherlands. The migrant populations included people who have migrated themselves as well as their offspring. We used PRs and the population distributions to calculate population attributable fractions (PAFs) using the standard formula. We used age and sex adjusted models to introduce pre-pandemic factors and intra-pandemic activities, noting the relative changes in PAFs. RESULTS: From 20,359 eligible HELIUS participants, 8,595 were linked to GGD Amsterdam PCR test data and included in the study. Pre-pandemic socio-demographic factors (especially education, occupation, and household size) resulted in the largest changes in PAFs when introduced in age and sex adjusted models (up to 45%), followed by pre-pandemic lifestyle factors (up to 23%, especially alcohol consumption). Intra-pandemic activities resulted in the least changes in PAFs when introduced in age and sex adjusted models (up to 16%). CONCLUSION: Interventions that target pre-pandemic socio-economic status and other drivers of health inequalities between migrant and non-migrant populations are urgently needed at present to better prevent infection disparities in future viral pandemics.

Understanding the system dynamics of obesity-related behaviours in 10- to 14-year-old adolescents in Amsterdam from a multi-actor perspective.

Introduction and Methods: To develop an understanding of the dynamics driving obesity-related behaviours in adolescents, we conducted systems-based analysis on a causal loop diagram (CLD) created from a multi-actor perspective, including academic researchers, adolescents and local stakeholders. Results: The CLD contained 121 factors and 31 feedback loops. We identified six subsystems with their goals: (1) interaction between adolescents and the food environment, with profit maximisation as goal, (2) interaction between adolescents and the physical activity environment, with utility maximisation of outdoor spaces as goal, (3) interaction between adolescents and the online environment, with profit maximisation from technology use as goal, (4) interaction between adolescents, parenting and the wider socioeconomic environment, with a goal focused on individual parental responsibility, (5) interaction between healthcare professionals and families, with the goal resulting in treating obesity as an isolated problem, and (6) transition from childhood to adolescence, with the goal centring around adolescents' susceptibility to an environment that stimulates obesity-related behaviours. Discussion: Analysis showed that inclusion of the researchers' and stakeholders' perspectives contributed to an understanding of how the system structure of an environment works. Integration of the adolescents' perspective enriched insights on how adolescents interact with that environment. The analysis further showed that the dynamics driving obesity-related behaviours are geared towards further reinforcing such behaviours.

Differences in incidence, nature of symptoms, and duration of long COVID among hospitalised migrant and non-migrant patients in the Netherlands: a retrospective cohort study.

Background: Comprehensive data on long COVID across ethnic and migrant groups are lacking. We investigated incidence, nature of symptoms, clinical predictors, and duration of long COVID among COVID-19 hospitalised patients in the Netherlands by migration background (Dutch, Turkish, Moroccan, and Surinamese origin, Others). Methods: We used COVID-19 admissions and follow up data (January 2021-July 2022) from Amsterdam University Medical Centers. We calculated long COVID incidence proportions per NICE guidelines by migration background and assessed for clinical predictors via robust Poisson regressions. We then examined associations between migration background and long COVID using robust Poisson regressions and adjusted for derived clinical predictors, and other biologically relevant factors. We also assessed long COVID symptom persistence at one-year post-discharge. Findings: 1886 patients were included. 483 patients had long COVID (26%, 95% CI 24-28%) at 12 weeks post-discharge. Symptoms like dizziness, joint pain, insomnia, and headache varied by migration background. Clinical predictors of long COVID were female sex, hospital admission duration, intensive care unit admission, and receiving oxygen, or corticosteroid therapy. Long COVID risk was higher among patients with migration background than Dutch origin patients after adjustments for derived clinical predictors, age, smoking, vaccination status, comorbidities and remdesivir treatment. Only 14% of long COVID symptoms persisted at one-year post-discharge. Interpretation: There are significant differences in occurrence, nature of symptoms, and duration of long COVID by migration background. Studies assessing the spectrum of functional limitation and access to post-COVID healthcare are needed to help plan for appropriate and accessible healthcare interventions. Funding: The Amsterdam UMC COVID-19 biobank is supported by the Amsterdam UMC Corona Research Fund and the Talud Foundation (Stichting Talud). The current analyses were supported by the Novo Nordisk Foundation [NNF21OC0067528].

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.

Lifestyle versus social determinants of health in the Dutch parliament: An automated analysis of debate transcripts.

Although public health scholars increasingly recognize the importance of the social determinants of health (SDOH), health policy outputs tend to emphasize downstream lifestyle factors instead. We use an automated corpus research approach to analyse fourteen years of health policy debate in the Dutch House of Representatives' Health Committee, testing three potential causes of the lack of attention for SDOH: political ideology, by which members of parliament (MPs) from some political orientations may prioritize lifestyle factors over SDOH; lifestyle drift, by which early attention for SDOH during problem analysis is replaced by a lifestyle focus in the development of solutions as the challenges in addressing SDOH become clear; and focusing events, by which political or societal chance events, known to the public and political elites simultaneously, bolster the lifestyle perspective on health. Our analysis shows that overall, the committee spent most of its time discussing neither SDOH nor lifestyle: healthcare financing and service delivery dominated instead. When SDOH or lifestyle were referenced, left-leaning MPs referred significantly more to SDOH and right-leaning MPs significantly more to lifestyle. Temporal effects related to election cycles yielded inconsistent evidence. Finally, peak attention for both lifestyle and SDOH coincided with ongoing political debate instead of exogenous, unforeseen focusing events, and these peaks were rendered relatively insignificant by the larger and more consistent attention for health care. This paper provides a first step toward automated analysis of policy debates at scale, opening up new avenues for the empirical study of health political discourse.

Intent to vaccinate against SARS-CoV-2 and its determinants across six ethnic groups living in Amsterdam, the Netherlands: A cross-sectional analysis of the HELIUS study.

BACKGROUND: Ethnic minority groups experience a disproportionately high burden of infections, hospitalizations and mortality due to COVID-19, and therefore should be especially encouraged to receive SARS-CoV-2 vaccination. This study aimed to investigate the intent to vaccinate against SARS-CoV-2, along with its determinants, in six ethnic groups residing in Amsterdam, the Netherlands. METHODS: We analyzed data of participants enrolled in the population-based multi-ethnic HELIUS cohort, aged 24 to 79 years, who were tested for SARS-CoV-2 antibodies and answered questions on vaccination intent from November 23, 2020 to March 31, 2021. During the study period, SARS-CoV-2 vaccination in the Netherlands became available to individuals working in healthcare or > 75 years old. Vaccination intent was measured by two statements on a 7-point Likert scale and categorized into low, medium, and high. Using ordinal logistic regression, we examined the association between ethnicity and lower vaccination intent. We also assessed determinants of lower vaccination intent per ethnic group. RESULTS: A total of 2,068 participants were included (median age 56 years, interquartile range 46-63). High intent to vaccinate was most common in the Dutch ethnic origin group (369/466, 79.2%), followed by the Ghanaian (111/213, 52.1%), South-Asian Surinamese (186/391, 47.6%), Turkish (153/325, 47.1%), African Surinamese (156/362, 43.1%), and Moroccan ethnic groups (92/311, 29.6%). Lower intent to vaccinate was more common in all groups other than the Dutch group (P < 0.001). Being female, believing that COVID-19 is exaggerated in the media, and being < 45 years of age were common determinants of lower SARS-CoV-2 vaccination intent across most ethnic groups. Other identified determinants were specific to certain ethnic groups. CONCLUSIONS: Lower intent to vaccinate against SARS-CoV-2 in the largest ethnic minority groups of Amsterdam is a major public health concern. The ethnic-specific and general determinants of lower vaccination intent observed in this study could help shape vaccination interventions and campaigns.

The contribution of smoking to differences in cardiovascular disease incidence between men and women across six ethnic groups in Amsterdam, the Netherlands: The HELIUS study.

It is unclear to what extent differences in cardiovascular disease (CVD) risk between men and women are explained by differences in smoking, and whether this contribution to risk is consistent across ethnic groups. In this prospective study, we determined the contribution of smoking to differences in CVD incidence between men and women, also in various ethnic groups. We linked baseline data of 18,058 participants of six ethnic groups from the HELIUS study (Amsterdam, the Netherlands) to CVD incidence data, based on hospital admission and death records from Statistics Netherlands (2013-2019). The contribution of smoking to CVD incidence, as estimated by the population attributable fraction, was higher in men than in women, overall (24.1% versus 15.6%) and across most ethnic groups. Among Dutch participants, however, the contribution of smoking was higher among women (21.0%) than men (16.2%). Using Cox regression analyses, we observed that differences in smoking prevalence explained 22.0% of the overall lower hazard for CVD in women compared to men. Smoking contributed minimally to the lower hazards for CVD in women among participants of Dutch (0%), Ghanaian (4.9%) and Moroccan origin (0%), but explained 28.6% and 48.6% of the lower hazards in women in South-Asian Surinamese and African Surinamese groups, respectively. While smoking prevention and cessation may lead to lower CVD incidence in most groups of men and women, it may not substantially reduce disparities in CVD risk between men and women in most ethnic groups.

Promoting the health of vulnerable populations: Three steps towards a systems-based re-orientation of public health intervention research.

This paper proposes a novel framework for the development of interventions in vulnerable populations. The framework combines a complex systems lens with syndemic theory. Whereas funding bodies, research organizations and reporting guidelines tend to encourage intervention research that (i) focuses on singular and predefined health outcomes, (ii) searches for generalizable cause-effect relationships, and (iii) aims to identify universally effective interventions, the paper suggests that a different direction is needed for addressing health inequities: We need to (i) start with exploratory analysis of population-level data, and (ii) invest in contextualized in-depth knowledge of the complex dynamics that produce health inequities in specific populations and settings, while we (iii) work with stakeholders at multiple levels to create change within systems.