Introduction

Democratic backsliding refers to the erosion of democratic institutions, processes, and norms. The implications of this decline extend well beyond the political sphere, threatening the potential loss of advancements achieved over decades of democratic governance, including in areas such as National Cancer Control Programs (NCCP).

Democracy has brought peace, development, and economic growth, which has resulted in several downstream benefits [1,2] including more efficient health systems and better population health [3,4]. However, health outcomes are influenced by several factors, such as health financing and infrastructure. Further, health outcomes can be impacted by external shocks, such as armed conflict and natural disasters, air pollution levels, living conditions, and other social determinants of health. Some of these, especially the external shocks, are not under the proximal control of any government. (Figure 1)

In contrast, health policies are linked to governance and serve as crucial political determinants of health, and herein lies the importance of understanding this link. Research indicates that health policies are more effectively formulated and implemented in democratic contexts. This relationship warrants further exploration, as effective governance is essential for policymaking [5,6], and health policies are vital tools for achieving sustained and long-term improvements that can withstand the negative effects of external shocks [3,7].

Health policies are significantly influenced by political dynamics, which can either constrain or enhance public health outcomes. As countries, states, and to a lesser extent, municipalities serve as sites for autonomous official initiatives, their institutional structures play a pivotal role in shaping the political processes that inform social policies, including health policies. These policies are vital for ensuring the delivery of quality and equitable healthcare, and democracy is fundamental to safeguarding the rights of individuals, including the right to health. A literature review indicates that left-leaning and egalitarian political ideologies, as well as advanced liberal democracies, have a positive impact on health outcomes [8].

For example, until the 1970s, Venezuela was considered a well-functioning democracy. Currently, the nation is under authoritarian rule and faces many challenges [9]. This transition has resulted in a fragile healthcare infrastructure [10] and an infant mortality rate (IMR) of 21 per 1,000 live births in 2022, significantly higher than the regional average of 14 per 1,000 live births in Latin America and the Caribbean [11]. The healthcare system has been adversely affected, and outbreaks of infectious diseases, linked to deteriorating public health services, are posing a threat to the nations and regional health [12]. The example of Venezuela is not an isolated one, several other countries, including Hungary, [13] Poland, [14] and Turkey, [15] among others, have witnessed a democratic backsliding characterized by curtailment of judicial independence, media freedom, and civil liberties in recent decades, with implications for policy-making and/or prioritization of investments in health infrastructure [5,16-22].

It is argued that through participative, deliberative, egalitarian, and rights-based approaches and attributes of democracy, normatively public policies, including health policies made under a democratic regime, would address equity, be comprehensive, and be of higher quality [23]. Further, a key mission of WHO’s work in cancer control is to promote NCCPs that are harmonized with strategies for NCDs and other related health concerns. Our study aligns with this mission and is an attempt to study one of the antecedents of NCCPs [24]. Therefore, we aim to study the relationship between the levels of democracy and the quality and comprehensiveness of cancer policies. Since cancer is a leading cause of death worldwide and its burden continues to rise, [25-27] effective policy measures are crucial for improving cancer prevention, screening, treatment, and palliative care. Lastly, the quality of these policies can significantly influence cancer outcomes. With that rationale, this study seeks to test the hypothesis that higher levels of democracy support better quality and comprehensiveness of NCCPs

Materials and Methods

Overview

The relationship between democracy and public policies, including health policies, is not straightforward. It is affected by the influence of several other factors, which are included as controls in this analysis. Democracy is measured using the V-Dem score for the liberal democracy index [28] for the year when the NCCP was last updated. NCCP plans were given a score based on primary research using a pre-designed set of eighty-three items categorized under eleven dimensions which were expertweighted, geometrically aggregated, and log-transformed.

Selection of countries

A purposive sampling technique was used to select 40 countries to ensure an even representation of the various democratic regime types (closed autocracy (CA), electoral autocracy (EA), electoral democracy (ED), and liberal democracy (LD) [29] (Table 1) across four world regions-Americas, Asia and Oceania, Africa and the Middle East, and Europe. We obtained a near-even representation of the World Bank income levels under each regime type, except liberal democracy (LD), where 9 out of 10 countries were high-income countries (HIC) [30]. This was unavoidable given the extant country mix under the LD regime (Appendix C)

Data and measures

Independent variable: Democracy and Governance

VDem dataset provides numerous indicators of regime characteristics, such as multiparty elections, freedom of civil association, et cetera, for 201 countries from 1789 to 2023. This study focuses on the Liberal Democracy Index (D) as the primary independent variable. This index reflects the core principle of ensuring that rulers are responsive to citizens through extensive electoral competition. It considers how free and fair elections are, as well as the ability of political and civil society organizations to operate without restrictions. Additionally, it considers freedom of expression and the media’s independence and capacity to present diverse perspectives on political issues between elections. For more detailed information, refer to the V-Dem 2024 data codebook and report [28].

Democracy is not a moment in time but a way of living and interacting among people and of people with their governments. Similarly, policy formulation or reform can take years and is not an instantaneous or short-term process. Moreover, the resources, expertise, and antecedents of policy choices are shaped over a longer period. To capture the effect of democracy as a factor influencing this long-term policy formulation process, the democratic experience of each country for 5, 10, and 15 years preceding the launch of the latest cancer plan update was calculated using the V-Dem Liberal democracy index (D). We calculated democratic experience by taking the sum of each country’s Liberal democracy index score for the last 5, 10, and 15 years up to the year of plan formulation, giving us another set of independent variables labeled D5, D10, and D15, respectively. Political cycles in most countries are usually 4 to 5 years [31]. Hence, we used 5-year gaps to develop democratic stock indices. D, D5, D10, and D15 were the main independent variables for the regression models. The regime type (R) described above was used

as a categorical variable for descriptive analysis of the data before running regression models. It was done using ANOVA and the Kruskal Wallis test, where the data were normal and not normal in distribution, respectively.

Dependent variable: National Cancer Policy score (NCCP score)

A NCCP was identified for each country from sources including but not limited to the International Cancer Control Partnership (ICCP) portal, [32] the WHO Non-communicable Diseases document repository, [33] the Ministry of Health (MoH), and other government websites. A score was assigned for each country’s NCCP by conducting desk research on a pre-designed questionnaire (Appendix A). Each cancer plan was scored using this questionnaire containing 83 items categorized under eleven dimensions (Table 2), which were weighted with expert inputs and combined using geometric aggregation to measure the construct of quality and comprehensiveness of cancer policies. It gave us the primary dependent variable Y_w and its 11 dimensions (Y₁ to Y₁₁). _(a)

These themes have been informed by the following concepts: Cancer care continuum, [34] WHO Health systems building blocks, [35] Key WHO resource documents like Strategizing national health in the 21st century, [36] and the conceptual framework of Health Equity. Weights were assigned to the dimensions using the Budget allocation (BAL) method [37-39] The NCCP score ranged from 0 to 0.087(b) where a higher score indicates a higher quality and comprehensiveness of the cancer policy.

While the NCCP score captured the product of the policy formulation process, primary data was collected on its process to check if it was inclusive and transparent allowing for participation from a range of stakeholders and accountability. A set of eight questions (Appendix A) was used to do this, which provided the secondary dependent variable called Process (P).

Controls

As mentioned earlier, the translation of political intentions, technical capacity, and capability is a complex process and might involve several intermediary factors to arrive at the policy. A methodological choice was made to allow for post-treatment bias by including downstream factors of democracy, such as GDP per capita, as controls.

This was done to ensure that the direct effects of democracy on NCCP quality and comprehensiveness are captured. It is argued that the following variables can impact policy formulation and therefore can function as confounders and hence are included as controls in the regression models

• Health expenditure per capita (current US$) at the time of plan formulation [40]

• Health expenditure (% of GDP) at the time of plan formulation [41]

• Income level [30]

• Domestic autonomy measures if the state is autonomous from the control of other states in the conduct of domestic policy [28].

• World Governance Indicator - Voice and Accountability: it captures the perceptions of the extent to which a country’s citizens can participate in selecting their government, as well as freedom of expression, freedom of association, and free media [42]

• World Governance Indicator (WGI) - Government effectiveness: it captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies [43].

• Gender Inequality Index (GII): It is a composite metric of gender inequality using three dimensions - reproductive health, empowerment, and the labor market. GII measures genderbased disadvantage in three dimensions reproductive health, empowerment (Parliamentary representation of females), and the labor market (Labor force participation for females) [44]

• Gender Development Index (GDI): It measures gender inequalities in achievement in three basic dimensions of human development - health, education, and command over economic resources [45].

Creating the panel data

The panel was created with data from included countries and all variables - independent, control, and dependent variables, listed above. Each data point for the independent and control variables was taken from its source for the year of the last update of the NCCP to capture their proximal effect on the NCCP. For example, the value of the Liberal democracy index (D1) was taken for the year 2011 for Costa Rica, which is when its NCCP was last updated. This can reasonably ensure that the level of democracy (D) reflects the environment under which the plan formulation took place.

Analysis

Statistical analyses were done using R software (version 4.3.3) using packages-gtsummary, ggstatsplot, model summary, pwr, and performance [46]. The panel data used in the analysis are available upon request. A p-value of 0.05 or less indicated a significant difference. Lastly, post hoc power analysis was done using pwr package. The power. f². The test function was utilized, which calculates power for a regression model based on the effect size, denoted as F2. The effect size F² is derived from the coefficient of determination (R2) using the formula:

Where R² represents the proportion of variance explained by the predictors in the model. By providing F², the total sample size, and the number of predictors, the power. f².test function computed the achieved power of the analysis.

Descriptive analysis

The included countries were classified by regime types, region, and income levels, and the mean values of independent and control variables were tabulated.

Bivariate analysis

Analysis of Variance (ANOVA) and Kruskal-Wallis tests were used for bivariate analysis between the independent, control, and dependent variables. In the bivariate analysis, variables were assessed in pairs to identify associations between them. The association of Yw, its dimensions Y¹ to Y¹¹, and the process score (P) were seen with all the independent and control variables then they were analyzed simultaneously in regression models.

Regression

To remove the effect of confounding and arrive at the best-fit model for Yw and some dimension scores, regression was done using the bidirectional stepwise method. It was applied since there were many independent, plausible explanatory variables in our study. The goal was to come up with a parsimonious model and to find the most useful predictor variables. We started with no variables, also called the null model, and evaluated variables for addition or removal at each iterative step, one by one after evaluating them for GVIF (<10), p-value, highest increase in adjusted R-square, and highest reduction in Akaike Information Criterion (AIC). We added variables that improved model fit and removed those that did not. We continued this process until no more variables provided a significant improvement to the model or until all variables under consideration were evaluated. Final models arrived at using this procedure are reported in the results section and Table 7.

Results

Descriptive analysis

Upon cross-tabulating the region and income level (Table 3, Figure 2 and 3); independent and control variables (Table 4); and dependent variables (Table 5) with the regime types, patterns can be seen in the way these variables move across the spectrum of democracy from Closed autocracy (CA), Electoral autocracy (EA), Electoral democracy (ED), to Liberal democracy (LD). For example, health expenditure per capita, and % GDP spent on health show a clear increasing pattern from CA to LD. Health expenditure per capita, and % GDP spent on Health in CA were US Dollars 782.74 (689.210) and 5.66% (3.169), and for LD was US Dollars 4843.72 (3023.547) and 10.91% (2.306) respectively (Table 4). Changes in the control variables may mediate the effects of democracy (or lack thereof) on NCCP.

^ Mean ± (SD); One-way ANOVA

# Median (IQR); Kruskal-Walli’s rank sum test

Bivariate analysis

There is also some association between regime types as a democracy variable and the dimension (Y₁ to Y₁₁), process (P), and overall NCCP scores (Y_w) using one-way ANOVA and Kruskal- Walli’s rank sum tests. The dimension score for Screening and diagnosis, Research, and Equity showed significant differences between the regime types with a p-value of 0.031, 0.012, and 0.024, respectively; the Process score was also significantly different among the regime types (p-value 0.039) (Table 5). These relationships were substantiated when these variables were significantly associated with the other democracy variables. The mean weighted NCCP score (Y_w) was 0.042 (0.015) for countries under CA and 0.054 (0.012) for countries with LD.

The association of Yw, its dimensions Y₁ to Y₁₁, and the process score (P) were seen with all the independent and control variables, and several significant relationships were discovered (Table 6). Most notably, Yw was significantly associated with WGI Government effectiveness and Gender Inequality Index (GII) with a p-value of 0.023 and 0.02, respectively. Comparable results were obtained upon log and reciprocal transformation of Y_w. Since the Y_w values were normally distributed and comparable results were obtained upon transformations, the need for this was ruled out and was not done in any further analysis.

• Screening and diagnosis score (Y₂) was significantly associated with D5, D10, and D15 (p-value 0.007, 0.032, 0.027), Domestic autonomy, % GDP spent on health, UHC score, WGI Government effectiveness, WGI Voice and accountability, Gender inequality index (p values 0.005, 0.011, 0.004, 0.028, 0.003, 0.002).
• Equity (Y₁₁) dimension was significantly associated with D, D10, D15, GDP per capita, Health expenditure per capita, % GDP spent on health, UHC score, WGI Voice and accountability, WGI Government effectiveness, Gender inequality index (p-value 0.026, 0.022, 0.02, <0.001, <0.001, 0.003, 0.006, 0.005, <0.001, <0.001); and
• Process (P) scores were significantly associated with D, D10, D15, Health expenditure per capita, WGI Voice and accountability, and WGI Government effectiveness (p-value 0.037, 0.046, 0.046, 0.043, 0.011, 0.023).

UHC: Universal Health Coverage; WGI: World Governance Indicators; GII: Gender Inequality Index; GDI: Gender Development Index

Regression

The final model for Y_w (model 7) had an Adjusted R² of 0.424, which means it could explain 42.4% of the variation in the NCCP score with a beta value of 0.01 (p-value of 0.073) and -0.04 (p-value <0.001) for liberal democracy score (D) and GII, respectively. This found a significant albeit small effect of liberal democracy scores (D) on NCCP score in the final model for Y_w where one unit change in D leads to 0.01-unit changes in the geometric NCCP score which is about a 10% increase of quality and comprehensiveness of NCCP, given that the maximum value of Y_w with geometric aggregation was 0.087. Estimates including beta coefficients, log-likelihood ratios, p-values, R-squared, and adjusted R-squared for all the models are reported in Table 7.

The equation of the model for Yw (model 7) is given below -

Y_w = 0.067-0.018* Region Americas-0.018* Region Asia and Oceania-0.016* Region Europe+0.01* D-0.035* GII

Regression Diagnostics and Model Estimation

• Assessment of the model’s assumptions was done using Tests for linearity, normality of residuals, homoscedasticity, and multicollinearity.
• Estimates included beta coefficients, 95% CI, loglikelihood, p-values, and adjusted R-squared.
• The robustness of the results was checked using Q-Q, posterior predictive check, linearity, and homogeneity of variance graphs. (Figure 4)

The model for Process was able to explain 40.7% (adjusted R² 0.407) of variation in P scores with a p-value of <0.001. The beta value for D was 0.38. (Table 7) These results show that higher levels of democracy lead to higher levels of the quality and comprehensiveness of the NCCPs (Y_w) and the transparency and inclusiveness of their formulation (P). Power analysis showed sufficient power for all our models which is mentioned on table 7.

+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001

Discussion

This paper hypothesizes that higher levels of democracy are associated with better quality and more comprehensive cancer policies, hence making a case for supporting democracy in pursuit of better healthcare. The findings of the analysis and their generalizability, considering the methodological choices and existing literature connecting democracy and health, are discussed in this section. It is organized as follows: rising cancer burden and democratic backsliding to set the context; political influences on health and the positive influence of democracy; limitations of the study, new knowledge, and recommendations of the study; and avenues of further research.

Rising cancer burden and the role of health policy

Cancer is a heterogeneous disease group that includes various types, such as breast, cervical, and colon cancers, affecting people from all socio-economic strata. Its global burden has been steadily increasing, causing significant suffering for patients and their families. [25-27] This growing challenge necessitates that governments implement policies that address the full cancer care continuum, are financed sustainably, and create conditions for equitable outcomes. Such policies could help reduce cancer’s morbidity, mortality, and socio-economic impact.

The impact of national health policies is difficult to measure since the outcomes are not only the result of existing policies but of their implementation and a variety of other policies and actions in sectors beyond health (including education, environment, transport, etc.). Nonetheless, effective policies offer a framework and can contribute to the reduction of the cancer burden. Therefore, the quality and comprehensiveness of cancer policies were studied in relation to democracy.

Since early 1980, the World Health Organization (WHO) has been promoting well-conceived and well-managed national cancer control programmes as the best approach to translating evidence into practice [47]. In September 2011, at a High- Level Meeting of the United Nations General Assembly on the Prevention and Control of Non-communicable Diseases (NCDs), Member States committed themselves to integrating noncommunicable diseases, including cancer, into the health planning process [48] Effective policy measures are crucial for improving cancer and the cancer care continuum. However, the quality of these policies can vary across countries, and democracy may play a key role in shaping the quality of cancer policies by affecting the deliberative, participatory, and inclusive aspects of governance and policymaking.

Democracy in danger

There have been multiple reports of democratic backsliding across the world for many years. It is the longest stretch of decline recorded since the 1970s. Reports by Freedom House [49] and International IDEA [50] highlight a worrying trend - nearly half of all countries have seen a weakening of democratic institutions. The 2024 V-Dem report also highlighted a decline in democracy globally. According to their report, the world has been experiencing a shift towards autocracy, with 71% of the world’s population, or 5.7 billion people, currently living in autocracies. This marks a significant increase of 48% compared to a decade ago [51,52].

Since governance affects social policymaking, [53,54] how policy shaping will be approached will also be different based on the existing regime types. Health policy advocates need to be aware of this and the fact that democratic backsliding can have negative consequences for population health [5]. First, there is a normative argument that public health is committed to supporting human rights and balancing population health needs with respect for individual autonomy, both of which are incompatible with authoritarianism [55]. Second, there is an empirical argument that backsliding increases the probability of worse public health systems and the potential for poor population health outcomes [5].

Political influences on health

Institutional structures shape the political processes from which policies emerge [56]. A literature review reported that leftleaning and egalitarian politics positively impact health, as do advanced and liberal democracies [8].

When governments adopt a participatory and representative approach to policymaking, the resulting policies are more likely to address people’s needs, be more effectively implemented, and promote equity. Under favorable external conditions, such policies can lead to positive health outcomes, with factors like economic development often shaped by democratic governance impacting the social determinants of health [57]. Conversely, political interference can disrupt the policy-making process and hinder effective implementation [6].

Given this background, the analysis found that higher levels of democracy lead to better quality and comprehensiveness of NCCPs. A one-unit change in democracy leads to a 10% increment in the NCCP score. It is worth noting that a 10% increase in the quality and comprehensiveness of NCCP is substantial, given that it is a policy with several other contributory factors and inputs. This suggests that higher levels of democracy do support better quality and comprehensiveness of NCCPs, and yet democracy is often ignored as a lever of policy change. If leveraged, advocacy for democracy can lead to several benefits already discussed, like better policies, economic development, and better health outcomes.

The formulation of NCCPs was more inclusive and transparent in countries with higher levels of democracy. This approach facilitated the involvement of various stakeholders and incorporated public input, ensuring that the voices of end users were considered in health-related matters. As a result, the policies were more responsive and people-centered, leading to more effective implementation and long-term, sustainable improvements. [23,58] Additionally, nearly all dimensions of the NCCP, including key aspects of the cancer care continuum such as prevention, treatment, and financing (Table 5) scored higher in liberal democracies (LD) compared to closed autocracies (CA), except for Y8 Monitoring and Evaluation. Notably, the scores for screening and diagnosis, research, and equity were significantly higher in countries with higher levels of democracy.

Better quality health policies alone are not a primary outcome of interest; rather, the concern is on improving population health. To that end, existing literature suggests that effective and equitable health policies have had a positive influence on population health and other co-benefits, such as poverty reduction by contributing to goals outside the health domain [59-61].

Since the results indicate that the quality and comprehensiveness of NCCPs were higher in countries with greater levels of democracy, it can be expected that democracy contributes to better cancer outcomes. This occurs not only through the enhancement of NCCPs, which provide a strong blueprint for action, but also through other pathways such as economic development and improved public service delivery. The WHO supports this view, stating that national health policies provide a framework for improving health outcomes and addressing national health priorities. A study by Thomas Fujiwara reinforces this, suggesting that public service delivery is the key channel through which democracy influences health outcomes, as observed in Brazil. [62] Similarly, Burgess et al. have found that electoral competition enhances social outcomes, including health, by reducing biases in public service delivery [63]. This is crucial because democracy is often associated with improved governance, such as better control of corruption, greater administrative efficiency, and stronger state capacity [64]. Therefore, the actual impact of democracy on health outcomes may be even greater than captured by this analysis.

The transferability of the findings to underserved populations warrants careful consideration. While purposive sampling allowed for the inclusion of countries across income levels and regions. Despite that it must be acknowledged that liberal democracies in the sample were predominantly high-income countries (9/10), potentially limiting generalizability to low-resource democratic settings.

Health policies play a critical role in balancing competing priorities and promoting targeted approaches to healthcare based on need, evidence, and feasibility. The results demonstrate that, in democratic settings, people benefit from policies that are of higher quality and developed through inclusive and transparent processes. These findings, along with existing literature, highlight the often-overlooked connection between political determinants of health such as democracy and the formulation of health policies.

In summary: (i) there is a significant correlation between levels of democracy and both NCCP and Process scores; (ii) there is evidence that these correlations persist even after controlling for other variables; and (iii) while the correlations appear to be causal, further empirical investigation is required to confirm this.

Limitations

It is acknowledged that this study has potential limitations.
1. Omitted Variables: There could be other variables that might influence NCCP scores but were not included as covariates despite attempts to account for all possible covariates and including them, based on the existing literature.
2. Ecological Fallacy: the analysis focuses on countrylevel data, and findings may not translate to individual-level relationships in terms of democratic, policy, and health system experiences. However, it is acceptable since the study aimed to explore country level effects of democracy on NCCPs.
3. In alignment with the aim of the study we focused on assessing the relationship between level of democracy and the quality and comprehensiveness of NCCPs. Hence, this study did not study the health outcomes as result of democracy or cancer policies.
4. Point estimates for correlation do not imply causation, and therefore, this study does not claim causal inferences.
5. Residual confounding in the final model cannot be eliminated despite attempts to control it using regression models
6. Limited sample size and possibility of bias due to non-random selection of countries. As explained in section 2.1 Selection of countries, purposive sampling was done to ensure even representation of countries from various regions and regime types. Sample size may be considered limited, but it included 20% of all countries.
7. Major occurrences in the global health policy landscape could influence national policies and these changes are agnostic to the levels of democracy at the country level. Regional diffusion of policies is also a possibility that can alter the NCCP scores without affecting the levels of democracy. This choice was made in alignment with the scope of this study and hence recommendations for further research in this direction is made.
8. A consolidated index of democracy was used, rather than disaggregating parameters, to simplify the analysis. However, this approach may obscure potential relationships between specific aspects of democracy and health policies. This choice was made in alignment with the scope of this study, and hence recommendations for further research in this direction are made.
9. Principal Component Analysis (PCA) and Factor Analysis (FA) were not used for dimension reduction in creating the questionnaire for the NCCP score. This decision was made because the dimensions represented a continuum of care, each of which was essential to retain and had been validated by public health experts.

Recommendation

This study provides an empirical basis for defending democracy in pursuit of public health. Maintaining higher levels of democracy is expected to result in better quality and more comprehensive cancer policies that are formulated in an inclusive and participatory manner. Since policies are typically formulated for long timescales, it is reasonable to expect that these benefits will be sustained in the long term. Willison et al recommended some practices for public health institutions, including reinvigorating alliances and multilateral institutions, developing civil society organizations, and combating misinformation to support democracy. In turn, healthier people are more likely to vote and less likely to support authoritarianism [5,65,66].

Avenues of further research

• Correlation of NCCP scores with cancer outcome (mortality) and to explore which dimension of the cancer plan (screening, diagnosis, or treatment) is more strongly associated with positive health outcomes?
• Using disaggregated scores of democracies could help understand which aspects of democracy lead to better health policies.
• Since social policies can transform politics once enacted and implemented. It could be worthwhile to study this “policy feedback” over time [56].
• Study of the relationship between other national health policies (environmental or social welfare/security policies) and levels of democracy.
• Study to explore the effect of regional diffusion of policies and their interplay with levels of democracy. For example, a national health insurance or family planning policies which have the potential to spread or influence policies in the neighboring countries because of a similar geopolitical climate or shared challenges [67].
• Examination of how democratic processes can be leveraged to improve cancer policy development in resourceconstrained settings and ensure equitable policy implementation for marginalized communities.

Conclusion

The findings of this study have implications for health policy making related to cancer and deepen understanding of the political determinants of health. Democratic systems, with their emphasis on public participation and responsiveness to citizen needs, are more likely to prioritize public health and implement effective cancer control policies that are evidence-based, comprehensive, and equity-focused. This study underscores the importance of defending and promoting democracy to create environments where comprehensive and effective cancer policies are made.

Beyond contributing to academic discourse, these findings offer insights for policymakers aiming to improve cancer care and guidance for advocates seeking effective strategies to shape health policies. However, navigating this advocacy is complex; strategies that spur positive change in liberal democracies might be perceived as regime challenges in closed autocracies. The challenge lies in identifying appropriate strategies tailored to the specific context, considering factors like regime type, resource availability, and the presence of networks and coalitions [68].

The global decline in democracy alerts us to the need for concerted efforts to safeguard and promote national cancer policies that prioritize equity. Organizations like the WHO play a pivotal role in advocating for policies prioritizing equity and public education on the connection between democracy and health outcomes. This paper serves as one such effort, arguing that democracies could potentially contribute to better cancer policies and improved health outcomes.

Author Contributions: Conceptualization, A.R.G.; methodology, A.R.G. and A.K.M.; software, A.K.M.; validation, A.R.G.; formal analysis, A.R.G., and A.K.M.; investigation, A.R.G., and A.K.M.; resources, A.R.G.; data curation, A.K.M.; writing original draft preparation, A.R.G., and A.K.M.; writing review and editing, A.R.G. and A.K.M.; visualization, A.R.G. and A.K.M.; supervision, A.R.G.; project administration, A.R.G. All authors have read and agreed to the published version of the manuscript

Data Availability Statement: The raw data supporting the conclusions of this article will be made available by the authors on request.

Appendix A -Questionnaire

The questionnaire was divided into two sections
(1) Structure which had 82 items categorized in 11 dimensions.
(2) Process which had 8 items. (Table A1, A2, A3)

Additionally, underlying issues such as digestive disorders, gastritis, mineral imbalances, and excessive physical or sexual activity were found to exacerbate symptoms by influencing the body’s overall acid-base balance. Addressing these root factors not only improved urinary health but also supported general well-being. The findings suggest that frequent urination may, in many cases, be a symptom of systemic pH imbalance and can be effectively managed through natural, non-invasive strategies. This perspective offers a promising direction for individuals who have not responded to conventional treatments, emphasizing the importance of holistic approaches that restore internal balance and support long-term urinary health.

^(b) Geometric and not arithmetic aggregation was used to allow for non-compensation of dimension score upon aggregation; the highest dimension
score of each dimension when geometrically aggregated will produce a score of 0.087. ^(c) Scale (also called a questionnaire or an instrument) is defined as a set of items designed to measure a construct, also called latent variable or domain which cannot be measured directly but is composed of measurable domains. (Fabrigar & Ebel-Lam, 2017).

^(d) Definition of NCCP given by Gorgojo et al (2019) was used - A national cancer control plan (NCCP) is a government document aiming to meet the strategic goals and support implementation of national cancer control activities in the country.

^(e) As per World Health Organization (WHO) NCCP are defined as ‘public health programmes designed to reduce cancer incidence and mortality and improve quality of life of cancer patients, through the systematic and equitable implementation of evidence- based strategies for the prevention, early detection, diagnosis, treatment and palliation, making the best use of available resources.
^(f) According to the model, information about quality of care can be drawn from three categories: “structure,” “process,” and “outcomes.”

Appendix B -Scale Development

We developed the scale(c) to score the National Cancer Control Plan (NCCP) [69] ^{(d, e)} of the countries included in our research using a combination of literature review and expert-informed iterative procedure which is described below.

The construct that we wanted to measure using our scale was the quality and comprehensiveness of NCCPs. To measure and score a complicated concept such as the quality of health policy we could not rely on proxy measures such as health outcomes since they are impacted by several other elements such as the health systems, social determinants of health etc. Hence, we needed to develop a set of specific questions or items to measure our construct-Quality and comprehensiveness of NCCP. All items or questions were included or excluded with this construct in mind and were grouped under 11 dimensions (Table B1).

As a starting point, we defined our construct - A NCCP can be called high quality and comprehensive when it is resource-appropriate, has outlined programmes to achieve its goals, recognizes innovative care and detailed the necessary funding and monitoring required to ensure successful and equitable implementation across the cancer care-continuum to address the disease burden in the country.

Scale development

Generation of items

After identifying the construct and its operational definition we identified key items that should be a part of a NCCP from the existing literature. Some additional aspects like the use of innovative medicine and newer technologies like telemedicine, and finally concepts like health equity were added. The question format was kept mostly dichotomous with a Yes or No answer to lend objectivity to the scoring.

Based on this initial list of items generated, we conducted a literature review to add more items deductively by studying existing scales, questionnaires, frameworks, or guidance documents from a variety of sources including the World Health Organization (WHO), International Atomic Energy Agency (IAEA), European Union (EU), Center for Disease Control (CDC), International Cancer Control Partnerships (ICCP), Association of European Cancer Leagues, Union for International Cancer Control (UICC) and others including academic articles [36,47,48,69-78]. For a complete list of tools and frameworks, please see (Table B2).

Donabedian’s Structure, Process, and Outcome framework(f) of examining health services and evaluating the quality of health care [79] was adapted to develop a framework for policy evaluation with health outcomes being the result of the policy structure and process. (see figure B1) We argue that the process by which a NCCP was formulated is just as important as the structure of the plan. Hence, a set of items under the heading ‘process’ was added in the NCCP evaluation which looked at the inclusiveness and transparency of the plan formulation process.

We adapted the Donabedian’s framework in the policy evaluation space as a framework where-
• The structure includes the contents of the policy documents, what they focus on and plan to address. For example, the Cancer care continuum, equity, monitoring and evaluation etc. Although their mere inclusion does not ensure effective implementation, it does establish accountability and creates systems for action, for example, the inclusion of an M&E section in the plan would mean that there are personnel and mechanisms in place to carry it out.
• The process includes ‘How’ the policy or the plan was arrived at. It is just as important as the structure since policies that are inclusive and are made in consultations with the end users, patients and healthcare providers tend to be grounded in lived experiences and have a higher acceptability [80,81]. Furthermore, A key strategy employed by democratic governments to enhance their legitimacy and reputation has been the adoption of measures aimed at fostering public participation in policymaking, thereby increasing procedural transparency while embedding decisions in sound scientific evidence [82,83]. The evidence-based nature of the NCCPs is also assessed under the process head.
• Outcomes include the health outcomes for the disease area that the plan or policy in question addresses. In this case where we are concerned with the evaluation of NCCPs the health outcomes of relevance will be cancer mortality and other parameters related to cancer, for example, survival rates, incidence rates etc. Outcomes were not included in the analysis of this study since our focus was on exploring the relationship between democracy and health policies.

Refinements

Refinements were made iteratively in discussion with health policy experts, researchers and end-users of the NCCP scale (see figure B2 for more details). A preliminary review of resources yielded 113 potential items for structure and 12 items for process. Following the removal of overlapping items to reduce redundancy, merging some items to achieve harmonization and with the addition of some items suggested by experts, we arrived at 83 items for structure and 8 items for process which were included in the questionnaire. Finally, experts advised the categorization of the finalized list of items under dimensions which built upon the pre-defined evidenceinformed domains given by Oar et al 2019. For the final list of items and dimensions see Appendix A.

Validation

Since, the country selection was not done randomly and the main objective of this study was not to develop a scale, partly because several scales have been proposed by others most notably by Oar et al [75]. Therefore, exploratory and confirmatory factor analyses were not carried out and the item reduction and assignment of dimensions were done solely based on expert consultations and validation.

Pre-testing

The scale was tested on a set of 5 countries and researcher feedback was incorporated in adjusting the language and order of some

^(a) For a detailed description of the methods adopted to choose the items and design the questionnaire; finalize the items and its dimensions; and methodologies for weighting and aggregation please see Appendix B.question items before beginning research on all forty countries included in the sample. Before commencing research, consensus was achieved between the authors and health policy experts involved in the refinement and validation of the scale that it is optimum in length, and the included items measure the construct of quality and comprehensiveness of NCCPs.

Weighting

Weights were assigned to the dimensions using Budget allocation (BAL) which is a participatory method including experts who are given a “budget” of N points (100 in our case), to be distributed over several sub-indicators or dimensions, “paying” more for those indicators whose importance they want to stress. This was done in three phases (1) selection of experts from a wide spectrum of knowledge, and experience including in the field of global health policy, patient advocacy, and governance. The panel of experts also included Healthcare providers and policymakers. (2) Budget allocation by experts; (3) calculation of weights [37,39,84].

The following process was followed -
• Identify the Dimensions: The first step was to identify the dimensions that made up the composite indicator-NCCP score. The scale items have been classified under these dimensions. Table B1 describes the dimensions of our scale.
• Collect Expert Input: We gathered a diverse panel of experts-Healthcare providers, policymakers, global health experts, academicians, patients and patient advocates. These experts were responsible for assigning weights to the dimensions. They were reached out via email with a brief overview of the study, description of the dimensions as per table B1, and the instruction for weighting using Budget Allocation method.
• Budget Allocation Process [39]: In the budget allocation process, each expert is given a hypothetical budget (100 points) that they can allocate across the different dimensions. The idea is that the more important a dimension is, the more of their budget an expert would allocate to it.
• Normalize the Weights: After all experts had allocated their budgets, we normalized the weights for each dimension. This was done by dividing the total points allocated to each dimension by all experts by the total points allocated across all dimensions (number of experts multiplied by 100). This gave us a weight between 0 and 1 for each dimension. (Table B3)
• Calculate the Composite Indicator: We multiply each dimension score by its weight and then geometrically aggregated these values to get the composite score for NCCP. We chose geometric aggregation over linear aggregation because when different dimensions are equally legitimate and important, then a non-compensatory logic is better suited (geometric mean). This is usually the case when very different dimensions are involved in the composite, like in our case for example, equity, financing and continuum of care are included.

Abbreviations: NCCP: National Cancer Control Plan; CA: Closed Autocracy; EA: Electoral Autocracy; LD: Liberal Democracy; ED: Electoral Democracy; IMR: Infant Mortality Rate; ICCP: International Cancer Control Partnership: MoH: Ministry of Health; WHO: World Health Organization; GDP: Gross domestic product; BAL: Budget Allocation; WGI: World Governance Indicator; GII: Gender Inequality Index; GDI: Gender Development Index; NCDs: Non-communicable Diseases; PCA: Principal Component Analysis; FA: Factor Analysis;

AIC: Akaike Information Criterion

References

1. Reiter D (2017) Is Democracy a Cause of Peace? Oxford Research Encyclopedia of Politics.
2. Williamson V (2024) Democracy is good for the economy. Can business defend it? Brookings.
3. Mc Cartney G, Hearty W, Arnot J, Popham F, Cumbers A, et al. (2019) Impact of political economy on population health: A systematic review of reviews. American Journal of Public Health 109(6): 1-12.
4. Roessler M, Schmitt J (2021) Health system efficiency and democracy: A public choice perspective. PLoS ONE 16(9): 1-22.
5. Willison CE, Falkenbach M, Greer SL, Singer PM (2023) Backsliding among indicators of democratic stability relevant to public health: Risks in OECD nations. World Medical & Health Policy 15(4): 455-475.
6. Greer SL, Vasev N, Jarman H, Wismar M, Figueras J (2019) It’s the governance, stupid! TAPIC: a governance framework to strengthen decision making and implementation. Health Systems and Policy Analysis.
7. Lee S (2022) Does Democracy Matter for Public Health? International Journal of Social Determinants of Health and Health Services 53(1): 15-29.
8. Muntaner C, Borrell C, Ng E, Chung H, Espelt A, et al. (2011) Politics, welfare regimes, and population health: controversies and evidence. Sociology of Health & Illness 33(6): 946-964.
9. IREF (Institute for Research in Economic and Fiscal Issues) (2017) Democracy: Impossible without economic freedom-IREF Europe EN.
10. Broner TT, Page K (2020) Venezuela’s Health Care Crisis Now Poses a Global Threat. Human Rights Watch.
11. WBG (World Bank Group) (n.d.). Mortality rate, infant (per 1,000 live births)-Venezuela, RB, Latin America & Caribbean.
12. Page KR, Doocy S, Reyna Ganteaume F, Castro JS, Spiegel P, et al. (2019) Venezuela’s public health crisis: a regional emergency. The Lancet 393(10177): 1254-1260.
13. Meyer Sahling JH, Toth F (2020) Governing illiberal democracies: Democratic backsliding and the political appointment of top officials in Hungary. NISPAcee Journal of Public Administration and Policy 13(2): 93-113.
14. Adamska Gallant A (2022) Backsliding of the Rule of Law in Poland-a Systemic Problem with the Independence of Courts. International Journal for Court Administration 13(3): 1-8.
15. Bayer R, Kemahlıoğlu Ö (2023) Democratic Backsliding, Conflict, and Partisan Mobilization of Ethnic Groups: Local Government Control and Electoral Participation in Turkey. South European Society and Politics 28(1): 19-46.
16. Dean J (2024) Democratic decline a global phenomenon, even in wealthy nations. Cornell Chronicle.
17. Little AT, Meng A (2024) Measuring Democratic Backsliding. PS: Political Science & Politics 57(2): 149-161.
18. WEF (World Economic Forum) (2017) The Global Risks Report 2017.
19. OECD (Organization for Economic Co-operation and Development) (n.d.) (2021) State of Health in the EU: Poland Pp: 1-24.
20. OECD (Organization for Economic Co-operation and Development) (n.d.) (2021) State of Health in the EU The Country Health Profile series: Hungary Pp: 1-24.
21. OECD (Organization for Economic Co-operation and Development) (n.d.) (2024) Health at a Glance: Europe 2022.
22. CSEP (Centre for Social and Economic Progress) (2022) Health System in Turkey: Reforms, Transformations and Challenges Pp: 1-39.
23. WHO (World Health Organization) (n.d.) Supporting national health policies, strategies, plans.
24. WHO (World Health Organization) (n.d.) Controlling cancer.
25. Siegel RL, Giaquinto AN, Ahmedin J (2024) Cancer statistics 2024. CA: A Cancer Journal for Clinicians 74(1): 12-49.
26. UICC (Union for International Cancer Control) (2024) GLOBOCAN 2022: Latest global cancer data shows rising incidence and stark inequities.
27. IARC (International Agency for Research on Cancer) (n.d.) Global Cancer Observatory (GCO).
28. V-Dem (n.d.) The V-Dem Dataset.
29. V-Dem Institute (n.d.) Democracy Reports.
30. World Bank (n.d.) The World by Income and Region.
31. Shi M, Svensson J (2006) Political budget cycles: Do they differ across countries and why? Journal of Public Economics 90(8-9): 1367-1389.
32. ICCP (International Cancer Control Partnership) (n.d.) National Plans.
33. WHO (World Health Organization) (n.d.) Noncommunicable Disease Document Repository.
34. Chan RJ, Milch VE, Crawford Williams F, Agbejule OA, Joseph R, et al. (2023) Patient navigation across the cancer care continuum: An overview of systematic reviews and emerging literature. CA: A Cancer Journal for Clinicians 73(6): 565-589.
35. WHO (World Health Organization) (2010) Monitoring the Building Blocks of Health Systems: A Handbook of Indicators and their Measurement Strategies Pp: 1-110.
36. WHO (World Health Organization) (2016) Strategizing national health in the 21st century: a handbook.
37. Gan X, Fernandez IC, Guo J, Wilson M, Zhao Y, et al. (2017) When to use what: Methods for weighting and aggregating sustainability indicators. Ecological Indicators 81: 491-502.
38. EU (European Union) (2009) State-of-the-art report on current methodologies and practices for composite indicator development.
39. EU (European Union) (2005) Tools for Composite Indicators Building.
40. The World Bank (n.d.) Current health expenditure per capita (current US$).
41. The World Bank (n.d.) Current health expenditure (% of GDP).
42. The World Bank (n.d.) World Governance Indicator: Voice and Accountability Pp: 1-2.
43. The World Bank (n.d.) World Governance Indicator: Government Effectiveness Pp: 1-2.
44. UNDP (United Nations Development Report) (n.d.) Gender Inequality Index (GII).
45. Human Development Reports (n.d.) Gender Development Index.
46. R Project (n.d.) R: The R Project for Statistical Computing.
47. World Health Organization (2007) Cancer Control: Knowledge into Action: WHO Guide for Effective Programmes.
48. UICC (Union for International Cancer Control) (n.d.) Supporting national cancer control planning: a toolkit for Civil Society organizations (CSOS) Pp: 1-120.
49. Freedom House (2024) The Mounting Damage of Flawed Elections and Armed Conflict.
50. International Idea (2023) Bedrocks of democracy under threat across the globe.
51. Lima R (2024) Democracy declined in 42 countries in 2023, new V-Dem report says.
52. V-Dem Institute (2024) Democracy Winning and Losing at the Ballot-Democracy Report PP: 1-64.
53. Ahrens L (2024) The impact of public opinion on voting and policymaking. Zeitschrift Für Politikwissenschaft 34(1): 77-100.
54. Harvard Kennedy School (2024) Public policy, values, and politics: Why so much depends on getting them right.
55. Abbasi M, Majdzadeh R, Zali A, Karimi A, Akrami F (2018) The evolution of public health ethics frameworks: systematic review of moral values and norms in public health policy. Medicine, Health Care and Philosophy 21(3): 387-402.
56. Skocpol T, Amenta E (1986) States and social policies. Annual Review of Sociology 12: 131-157.
57. Pelke L (2023) Reanalyzing the link between democracy and economic development. International Area Studies Review 26(4): 361-383.
58. WHO (World Health Organization) (n.d.) Promoting participatory governance, social participation and accountability.
59. Joynt Maddox KE, Louis ST (2024) The Role of Health Policy in Improving Health Outcomes and Health Equity. Transactions of the American Clinical and Climatological Association 134: 200-213.
60. Allen P, Pilar M, Walsh Bailey C, Hooley C, Mazzucca S, et al. (2020) Quantitative measures of health policy implementation determinants and outcomes: A systematic review. Implementation Science 15(1): 1-17.
61. Greer SL, Falkenbach M, Siciliani L, McKee M, Wismar M, et al. (2022) From Health in All Policies to Health for All Policies. The Lancet Public Health 7(8): 718-720.
62. Fujiwara T (2015) Voting Technology, Political Responsiveness, and Infant Health: Evidence from Brazil. Econometrica 83(2): 423-464.
63. Robin Burgess B, Jedwab R, Miguel E, Morjaria A, Padró Miquel G, et al. (2015) The Value of Democracy: Evidence from Road Building in Kenya. American Economic Review 105(6): 1817-1851.
64. Halleröd B, Rothstein B, Daoud A, Nandy S (2013) Bad Governance and Poor Children: A Comparative Analysis of Government Efficiency and Severe Child Deprivation in 68 Low- and Middle-income Countries. World Development 48: 19-31.
65. McCabe K, Zhu Y, Bajaj SS, Martin AF (2024) Increasing Voter Participation Through Health Care-Based Voter Registration. JAMA Health Forum 5(6): 1-7.
66. Brown CL, Raza D, Pinto AD (2020) Voting, health and interventions in healthcare settings: a scoping review. Public Health Reviews 41(1): 1-21.
67. Sabourin E, Grisa C, Lopes Filho M (n.d.) (2018) Regional diffusion of Brazilian public policies for the strengthening of family farming in Latin America and the Caribbean.
68. Freedom House (n.d.) Freedom in the World 2020: Recommendations for Strengthening Democracy.
69. WHO (World Health Organization) (2002) National cancer control programmes: policies and managerial guidelines 2^nd
70. WHO (World Health Organization) (2011) National cancer control programmes core capacity self-assessment tool (n.d.) Pp: 1-22.
71. Albreht T, Martin Moreno JM, Jelenc M, Gorgojo L, Harris M (n.d.) European Guide for Quality National Cancer Control Programmes Pp: 1-113.
72. CDC (n.d.) Comprehensive Cancer Control Branch Program Evaluation Toolkit.
73. Jelenc M, Weiderpass E, Fitzpatrick P, Albreht T (2021) Developments in National Cancer Control Programmes in Europe-Results from the Analysis of a Pan-European Survey. Cancer Control 28.
74. Romero Y, Trapani D, Johnson S, Tittenbrun Z, Given L, et al. (2018) National cancer control plans: a global analysis. The Lancet. Oncology 19(10): 546-555.
75. Oar A, Moraes FY, Romero Y, Ilbawi A, Yap ML (2019) Core elements of national cancer control plans: a tool to support plan development and review. The Lancet Oncology 20(11): 645-652.
76. ICCP Portal (n.d.) (2016) National Cancer Control Plan Development and Implementation Assessment Tool.
77. Thrift Perry M, Cabanes A, Cardoso F, Hunt KM, Cruz TA, et al. (2018) Global analysis of metastatic breast cancer policy gaps and advocacy efforts across the patient journey. Breast 41: 93-106.
78. WHO (World Health Organization) (2023) Assessing national capacity for the prevention and control of noncommunicable diseases: report of the 2021 global survey.
79. Berwick D, Fox DM (2016) “Evaluating the Quality of Medical Care”: Donabedian’s Classic Article 50 Years Later. The Milbank Quarterly 94(2): 237-241.
80. Bua A, Escobar O (2018) Participatory-deliberative processes and public policy agendas: lessons for policy and practice. Policy Design and Practice 1(2): 126-140.
81. Weatherill S (2017) A Responsive Technocracy? EU Politicization and the Consumer Policies of the European Commission by Chr. Rauh (Colchester: ECPR Press, 2016, ISBN 9781785521270), xiii+ 310pp., £50.00 hb. JCMS: Journal of Common Market Studies 55(6): 1451-1452.
82. Meier K, O toole L (2006) Bureaucracy in a Democratic State: A Governance Perspective. Choice Reviews Online 45(01): 1-22.
83. Braun C, Busuioc M (2020) Stakeholder engagement as a conduit for regulatory legitimacy? Journal of European Public Policy 27(11): 1599-1611.
84. Saisana Michaela, Tarantola Stefano (2002) State-of-the-art report on current methodologies and practices for composite indicator development. Publications Office of the EU Pp: 1-80.