Publication Trends,Thematic Clusters and Governance in Ageing–Insurance Research: A Bibliometric and Systematic Review

Abstract

Population ageing is intensifying demands on insurance systems to deliver financial protection, equity and sustainability. Yet research at the ageing–insurance interface remains fragmented across behavioural, institutional and policy levels, with governance mechanisms rarely specified. A mixed-method review combined bibliometric mapping with structured systematic synthesis. A title-restricted Scopus search (June 2025) yielded 134 peer-reviewed articles. Author-keyword co-word analysis (VOSviewer; minimum frequency = 2) identified thematic structure, which guided in-depth synthesis of 31 empirical studies coded for theory, context, insurance type, design and analysis. Three clusters emerged: Health and Active Ageing, Systemic Policy Challenges, and Financial Insurance Models. The literature is regionally concentrated, particularly in East Asia. Most studies prioritise behavioural outcomes, institutional design or fiscal modelling separately; only a minority explicitly connects individual-, scheme- and system-level dynamics through governance and implementation pathways. Cluster patterns include inconsistent measurement and population segmentation (red), solvency models treating ageing as exogenous (green), and persistent equity gaps alongside divergence between formal coverage and realised protection (blue). Linking bibliometric themes to mechanism-oriented synthesis, the review advances a multilevel lens and a focussed agenda for comparative, governance-aware research on resilient and inclusive insurance in ageing societies.

Keywords

ageing long-term care insurance universal health coverage insurance governance bibliometric analysis systematic review

Introduction

Global population ageing is accelerating, with 1 in 6 people projected to be aged 65 or older by 2050.¹ This demographic shift places growing pressure on healthcare, social protection, and long-term financial systems. Insurance mechanisms—including public health, pension schemes, long-term care, and private coverage—play a pivotal role in safeguarding older adults and buffering households against later-life uncertainties.² Yet how ageing transforms insurance needs, policy design, and consumer uptake remains insufficiently understood, particularly as demographic change intersects with rising inequality, health system fragmentation, and fiscal stress. In practice, these pressures translate into recurrent policy dilemmas—how to expand coverage without deepening inequities, how to finance longer lives without shifting excessive risk to households, and how to align scheme rules with the realities of later-life care and health needs.

Empirical research on the ageing-insurance nexus is growing but remains fragmented and uneven. Many studies concentrate on specific insurance types—such as long-term care,^3,4 public health insurance,^5,6 or private health coverage^7,8—often focussing on defined settings or programme-specific evaluations. While these contributions offer valuable insights into consumer behaviour or policy outcomes, they rarely interrogate how broader institutional environments shape the experience and governance of ageing-related risks. Moreover, few studies explicitly theorise ageing as a multidimensional construct—socially framed, behaviourally enacted, and institutionally mediated—leaving gaps in understanding how ageing influences both the demand for and design of insurance systems.⁹ The result is not simply a diverse literature, but a literature that is difficult to use: findings on utilisation, enrolment, or benefit effects are often tied to one scheme or setting, with limited clarity about which outcomes are driven by population needs, which by institutional design, and which by governance capacity. Without such distinctions, it remains hard to derive transferable insights—whether for scholarship that seeks explanation, or for policy that must make choices under fiscal and equity constraints.

Review studies have begun to organise this emerging literature, but most remain siloed by topic or methodology. Bibliometric analyses chart publication trends or citation dynamics without engaging theoretical integration,^10,11 while systematic reviews focus on targeted domains such as long-term care,^12,13 health insurance,¹⁴ ageing workers,¹⁵ or policy design.¹⁶ Others explore geriatric health burdens¹⁷ but do not address insurance systems as sites of collective risk-sharing or institutional negotiation. As a result, the ageing-insurance research landscape remains theoretically underdeveloped and methodologically dispersed. Accordingly, what is still missing is an integrative account that explains how evidence from different strands fits together: how ageing-related risks are defined and measured, how schemes allocate and manage those risks through design features, and how governance arrangements shape implementation, accountability, and distributional outcomes. This gap is particularly consequential as governments face intensifying pressures to build sustainable, inclusive insurance systems that can adapt to changing demographic and socioeconomic realities.

This study responds to that need by offering an integrated mapping of research on the intersection of ageing and insurance. Combining bibliometric techniques with a structured systematic review, it synthesises 134 peer-reviewed journal articles indexed in Scopus and conducts in-depth thematic analysis of 31 high-quality empirical studies. The review specifically examines how ageing-related risks are conceptualised, how insurance mechanisms are institutionalised, and how theoretical and methodological approaches shape the field’s development. Rather than treating thematic clusters as endpoints, this study uses them as entry points for integration: the bibliometric component identifies the field’s dominant domains, and the systematic synthesis then traces, within and across these domains, how risk conceptualisations, scheme design choices, and governance conditions are linked to observed outcomes. It is guided by 3 objectives: (1) to examine publication trends in ageing-related insurance research; (2) to identify and synthesise major thematic clusters across the literature; and (3) to assess how empirical studies conceptualise risk, apply theory, and address governance.

By bridging quantitative mapping with thematic synthesis, this study contributes a conceptual foundation for advancing ageing-insurance scholarship and actionable insights for policy. It highlights not only what has been studied, but—more crucially—what remains underexplored: the governance of ageing-related insurance systems, the behavioural complexity of older populations, and the institutional pathways through which risk is framed and managed. On this basis, the review articulates a multilevel agenda that connects micro-level behavioural responses, meso-level institutional design, and macro-level governance constraints—so that future research can specify not only whether insurance interventions matter, but through which mechanisms and under what institutional conditions they do. For scholars, it offers a future research agenda that moves beyond product-based silos towards integrated, multilevel models. For policymakers and practitioners, it reveals design challenges and equity trade-offs that are critical to building inclusive, resilient insurance systems in rapidly ageing societies.

Methods

This study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline¹⁸ and adopts a mixed-method design that integrates bibliometric analysis with a structured systematic review to examine the structure, thematic landscape, and methodological patterns in ageing and insurance research. This approach aligns with established recommendations^19
-21 and leverages the complementary strengths of quantitative mapping and qualitative synthesis. Specifically, bibliometric analysis is employed as a structuring stage to trace the field’s developmental trajectory and delineate dominant thematic clusters, within which the systematic review is subsequently conducted to enable focussed, in-depth conceptual analysis and critical evaluation.^22
-24

Data were retrieved from Scopus, selected for its comprehensive coverage, bibliometric reliability, and suitability for single-source designs that minimise cross-database inconsistencies.^25
-27 The search was conducted in June 2025, using the following string applied to article titles:

TITLE (aging OR ageing) AND TITLE (insurance OR coverage)

To ensure topical relevance and avoid the inclusion of articles where ageing and insurance were only mentioned peripherally, the search scope was restricted to article titles. No restrictions were applied at the search stage with respect to publication year, language, or document type; eligibility criteria were applied only at the systematic review screening stage.²⁵ A total of 134 articles were retrieved and included in the bibliometric analysis.

Statistical Analysis

Prior to co-word analysis, keyword data were cleaned and standardised using OpenRefine to merge synonymous expressions and remove irrelevant terms. Co-word analysis was then conducted to identify thematic concentrations by mapping author keyword co-occurrences,^25,28 resulting in 3 distinct clusters characterised by high-frequency terms that reflected major research directions.

The systematic review builds on this structure. The thematic clusters generated by the bibliometric co-word analysis were used to organise the subsequent screening and selection of studies. Articles were screened based on 3 exclusion criteria: (1) journals not indexed in SCI/SSCI or with an impact factor below 1 (n = 53),^23,29 (2) articles lacking substantive relevance despite keyword inclusion (n = 38), and (3) inaccessible full texts (n = 2). Additionally, 10 articles were excluded due to weak linkage with the identified thematic clusters. The resulting analytical sample comprised 31 high-quality empirical studies, which formed the basis for the subsequent systematic review and qualitative synthesis.

Within each cluster, studies were systematically analysed by extracting and comparing core characteristics, including theoretical foundation, country context, insurance type, research design, data collection methods, and data analysis techniques. This structured coding enabled cross-cluster insights into how ageing-related risk is conceptualised, how insurance mechanisms are institutionalised, and how methodological approaches vary across studies. Screening was conducted independently by 2 reviewers, with intercoder reliability assessed at the screening stage on a random subsample of 10 articles, yielding 90% agreement, consistent with the acceptable benchmark proposed by Rust and Cooil.³⁰ Disagreements were resolved through team discussion to reach consensus prior to final inclusion decisions. An overview of the research design and review process is presented in Figure 1.

Figure 1.

Flowchart of the research design and search strategy.

Results

Bibliometric Analysis

Figure 2 presents the temporal evolution (1953-2025) of publications and citations in ageing and insurance research. From 2006 onwards, the field entered a phase of steady growth, with annual outputs peaking at 12 articles in 2021 and remaining consistently high from 2018 through 2024. As of June 2025, 8 articles had already been published, suggesting the potential for a new peak by year-end. This sustained productivity aligns with rising global concern over population ageing and the corresponding institutional reforms in long-term care and insurance systems. Citation trends exhibit a clear temporal lag relative to publication activity, with a pronounced spike in 2011 reflecting the accumulated impact of high-impact articles published in preceding years. Secondary citation peaks in 2015 and 2021 further indicate concentrated scholarly engagement during key policy moments. Together, the trends suggest a shift from sporadic interest to a more structured and interdisciplinary research trajectory, shaped by both demographic urgency and evolving policy agendas.

Figure 2.

Total publications and citations by year.

Figure 3 presents the results of a co-word analysis based on author keywords (minimum frequency: 2) through VOSviewer software (Supplemental Appendix 1), which revealed 3 major thematic clusters that reflect the conceptual structure of ageing and insurance research. These clusters—focussing respectively on health outcomes, systemic policy, and financial insurance—highlight distinct orientations in the literature and provide a coherent basis for organising the subsequent systematic review.

Figure 3.

Author keyword co-occurrence network.

The red cluster centres on healthy and active ageing, featuring keywords such as successful ageing, private health insurance, and quality of life. This cluster reflects a strong emphasis on individual well-being, often approached through qualitative or discourse-based methods. The inclusion of terms like discourse analysis, HIV, and Asia points to socially constructed health narratives and population-specific concerns. Overall, this cluster aligns with research focussed on subjective ageing experiences, public health messaging, and preventive care.

The green cluster is dominated by structural terms such as ageing, population ageing, health insurance, and health policy, capturing research that addresses demographic transitions and public health systems. Keywords like pensions, simulation, and fund sustainability suggest analytical and planning-oriented studies, with China and Mexico frequently appearing as regional anchors. This cluster bridges macro-level challenges with policy design and system-level reforms, distinguishing itself by its broad, often quantitative, systems-level orientation.

The blue cluster concentrates on long-term care insurance, universal health coverage, and financial protection, reflecting a strong focus on the institutional and fiscal dimensions of insurance provision for ageing populations. Keywords such as social insurance, inequality, and catastrophic expenditure indicate attention to equity, financing models, and protection from age-related financial risks. The presence of Japan and Hong Kong underscores East Asia’s leadership in developing advanced, often government-backed, insurance schemes tailored to older adults.

Together, these clusters reveal a thematic divide: while the red cluster emphasises individual and health-centred perspectives, the blue cluster is anchored in institutional design and financial security, and the green cluster serves as a conceptual bridge linking the 2. This structure underscores the interdisciplinary nature of the field, shaped by diverse goals—from enhancing personal well-being to securing population-level sustainability. These clusters form the analytical foundation for the systematic review that follows, enabling comparative synthesis across thematic domains, regional emphases, and theoretical orientations.

Systematic Synthesis by Thematic Cluster

Based on the bibliometric mapping of 134 studies, this section provides a systematic synthesis of 31 rigorously screened articles (Supplemental Appendix 2), critically analysed within 3 thematic clusters.

Health and Active Ageing (Red Cluster): Conceptual Diffusion and Methodological Fragmentation

This cluster centres on research addressing healthy and active ageing, with recurring themes such as successful ageing, private health insurance, universal health coverage, and quality of life. The 5 systematically reviewed studies within this cluster reflect a shared concern with older adults’ health experiences and psychosocial outcomes across diverse contexts, yet reveal considerable inconsistencies in theoretical coherence, construct clarity, and methodological precision.

Theoretical engagement is highly uneven. Only 2 studies clearly articulate guiding frameworks: Lee et al⁷ adopt proactive coping theory to examine how resilience and perceived stressors influence private insurance uptake among older adults in South Korea, while Van den Bogaert et al³¹ apply positioning theory to investigate how ageing persons are discursively constructed within Belgium’s social health insurance system. The remaining studies either adopt policy-oriented assumptions^32,33 or rely on classification-based operational models³ without formal theoretical scaffolding. This lack of conceptual depth limits theoretical accumulation and inhibits cross-contextual comparison.

Construct ambiguity is another persistent issue. “Successful ageing” and “quality of life” appear frequently across studies, yet few offer standardised or validated measures. Chen et al,³ for instance, segment geriatric populations using administrative care-level distinctions under Japan’s LTCI, but without theoretical justification or discussion of construct validity. Similarly, Kowal et al³³ treat “unmet need” as a global indicator of UHC performance across 83 countries, but do not consider socio-political differences in healthcare access thresholds or self-reporting behaviour, raising concerns about cross-national comparability.

Methodologically, the studies rely heavily on secondary data and large-scale survey instruments, with minimal triangulation. Lee et al⁷ conduct logistic regression using a national database, yet the underlying psychological constructs (eg, coping, life satisfaction) are operationalised via non-standardised proxies. In contrast, Van den Bogaert et al³¹ offer rich qualitative insights into discursive practices but remain disconnected from outcome-level indicators. The absence of mixed-method approaches results in an analytical gap between subjective ageing experiences and the structural features of insurance systems.

Moreover, population segmentation is frequently under-theorised. Some studies target frail elderly populations,³ while others address self-managing older adults with purchasing power,⁷ yet few explain their sampling logic or clarify how population attributes (eg, socioeconomic status, dependency level) interact with insurance behaviours. This results in a conceptual conflation between vulnerability and agency, weakening the explanatory power of policy recommendations. Even terms such as “older adult” or “elderly” are deployed without consistent age thresholds or contextual grounding.

Rather than summarising ageing as a generalised phenomenon, future research should pursue more differentiated conceptualisations. Empirical studies must clarify which segment of the ageing population is being addressed (eg, pre-retirement, frail elderly, affluent retirees), adopt validated instruments to capture psychosocial dimensions, and align these with theoretical frameworks that link individual behaviour to structural constraints in insurance design. Cross-national work, in particular, should account for institutional logics and cultural norms, moving beyond descriptive comparisons to explanatory models that integrate macro-policies and micro-behavioural dynamics.

Systemic Policy Challenges (Green Cluster): Structural Convergence and Comparative Blind Spots

This cluster focuses on the fiscal and institutional implications of population ageing, particularly in relation to the sustainability of public insurance and pension systems. Keywords such as “population ageing,” “fund sustainability,” and “health policy” underscore a collective concern with managing macro-level pressures in ageing societies. The 16 studies in this cluster, predominantly drawn from East Asia and Latin America, adopt simulation-heavy, data-driven approaches to evaluate systemic solvency under demographic strain.

While methodologically rigorous, the cluster demonstrates notable conceptual uniformity. Studies such as Jiang et al,⁶ Qiu et al,³⁴ and Yu et al³⁵ model China’s insurance funds using overlapping generation and actuarial frameworks, often treating ageing as a singular, exogenous variable. In doing so, they abstract demographic change from lived inequality—ignoring variations across income groups, urban-rural divides, and local governance. Similarly, health system analyses in Mexico³⁶ and Thailand³⁷ simulate universal health coverage under demographic stress, but do not engage with political feasibility, institutional design, or public receptiveness to reform.

The theoretical landscape of the cluster is equally narrow. Only a few studies invoke explicit frameworks, such as life-cycle theory^38,39 or social insurance theory.⁴⁰ Most assume a form of demographic determinism: as populations age, rational policy responses are expected to follow. Yet, this overlooks how institutional inertia, governance quality, or citizen preferences might constrain or redirect policy trajectories. Wark,⁴¹ for instance, draws from case comparisons of disability insurance but stops short of theorising how institutional legacies mediate policy transfer or reform adoption.

Comparative learning is particularly underdeveloped. Although the cluster covers diverse settings—from Ghana⁴² to Poland⁴³—cross-country insights are seldom synthesised. Institutional variations in eligibility criteria, financing mechanisms, or provider networks are not systematically compared, resulting in a conceptually disjointed body of evidence. Even in multi-country studies, such as Liu and Flöthmann⁴⁰ or Macinko et al,⁸ demographic convergence is emphasised at the expense of institutional or cultural divergence. The absence of such comparative logics constrains the field’s ability to identify what works, for whom, and under what conditions.

A further limitation lies in the marginal attention to individual agency and behavioural responses. Several studies model household expenditure or insurance take-up,^44,45 but these remain exceptions. Most accounts treat insurance systems as static environments, omitting how citizens navigate policy ambiguity, coverage gaps, or affordability constraints. As a result, questions about the real-world impact of policy reform on the ageing population—who gets left out, who adapts, and how—remain underexplored.

Critically, even when private or hybrid models are included—such as in Brazil⁸ or Spain³⁹—financial metrics dominate the analysis, with limited attention to broader institutional resilience or access equity. There is scant theorisation of how pluralistic insurance architectures respond differently to ageing pressures or how fragmentation affects coverage continuity. This blind spot is especially salient in emerging economies where public-private overlaps are the norm, not the exception.

Thus, rather than treating ageing as a purely actuarial input into solvency projections, future research should conceptualise it as a multilevel governance problem—shaped by institutional histories, reform politics, and behavioural adaptation. Mechanism-oriented and comparative frameworks are urgently needed to move beyond deterministic forecasting and towards causal explanations of insurance resilience in diverse policy ecosystems.

Financial Insurance Models (Blue Cluster): Institutional Experiments and Equity Trade-Offs

This cluster explores how institutional insurance models—particularly long-term care insurance (LTCI) and universal health coverage (UHC)—are designed to mitigate ageing-related financial risks. Thematically unified by keywords such as “financing,” “financial protection,” and “catastrophic expenditure,” the 10 studies in this cluster collectively highlight the policy innovation occurring in ageing societies, especially in East Asia. However, this innovation is often framed through a narrow technocratic lens that downplays critical governance, equity, and behavioural questions.

A notable pattern is the reliance on East Asian contexts—Japan, South Korea, and Hong Kong—as testing grounds for LTCI and UHC reforms. Studies such as He et al⁴⁶ and He et al.⁴ adopt discrete choice modelling to estimate older adults’ willingness to pay for LTCI products, revealing granular insights into demand preferences in super-aged societies. Meanwhile, Okamoto and Komamura⁴⁷ and Okamoto et al.² document how Japan’s LTCI system seeks to align service access with fiscal sustainability, using large-scale data to evaluate unmet healthcare needs and catastrophic health expenditures. These studies offer empirically grounded designs for insurance innovation but often treat consumers as rational and fully informed agents. This assumption overlooks how decision-making is shaped by cognitive ageing, limited health literacy, or cultural reluctance towards institutional care—factors especially salient in late adulthood.

Equity concerns form another thread within this cluster. Studies consistently document gaps between formal coverage and effective protection. For example, Murakami and Hashimoto⁵ show that universal dental coverage in Japan fails to eliminate wealth-related inequalities, while Garg et al⁴⁸ demonstrate that publicly funded insurance in India does not shield the poorest from catastrophic hospitalisation costs. Even where national systems are operationally efficient, coverage depth, service uptake, and out-of-pocket burdens remain unevenly distributed across income, age, and geographic subgroups. Yet these observations, though valuable, are rarely analytically expanded. Most studies treat inequality as a residual outcome rather than as a product of institutional design, political negotiation, or regulatory failure.

Theoretical engagement in this cluster is sparse and largely instrumental. Some studies employ Anderson’s behavioural model⁴ or Grossman’s health production function,² but these are applied descriptively to justify variable selection rather than to interrogate underlying mechanisms. The dominant paradigm remains actuarial—framing ageing as a solvable fiscal problem—while questions of power, legitimacy, and normative justice remain underexplored. Insurance governance is often reduced to pricing and subsidy structures, ignoring how trust, procedural accountability, and political capacity influence uptake, compliance, and redistributive legitimacy.

Furthermore, the portrayal of institutional design tends to privilege financial logics while marginalising normative ones. Yin and He⁴⁹ compare health financing reforms in Hong Kong and Singapore but focus mainly on cost-sharing and coverage breadth, neglecting how societal norms and intergenerational expectations shape preferences for institutional care. Kim and Kwon,⁵⁰ in reviewing South Korea’s decade-long LTCI experience, highlight fiscal lessons but remain silent on whether the programme aligns with citizens’ evolving care needs or values.

Comparative insight remains another underdeveloped area. While multinational studies like De Castries⁵¹ and Feng and Glinskaya⁵² emphasise global learning, they often list policy instruments rather than explaining the contextual conditions under which these instruments succeed or fail. The overrepresentation of East Asia risks crowding out insights from alternative welfare models or from lower-income countries where ageing and coverage expansion unfold under vastly different institutional constraints.

The deeper issue is that this literature often assumes that more insurance equals better outcomes, neglecting the socio-political embeddedness of “insurance” itself. Future studies should question how insurance systems construct eligibility, how care is valued across regimes, and how individuals negotiate responsibility between state, market, and family. This shift demands theoretical pluralism and methodologically richer designs—such as institutional ethnography, mixed-method governance mapping, or comparative process tracing—to capture the recursive interactions among ageing subjects, insurance infrastructures, and the values they encode.

Discussion

Key Gaps and Integrative Challenges

The evidence synthesised in this review indicates an empirically active yet under-integrated research landscape. Studies within the red cluster advance understanding of psychosocial ageing and insurance-related outcomes, but often rely on uneven theorisation, inconsistent construct operationalisation, and weakly justified population segmentation. The green cluster provides rigorous modelling of fiscal sustainability and demographic pressures, yet commonly treats ageing as an exogenous demographic driver, with limited attention to behavioural adaptation, governance constraints, or political feasibility. The blue cluster documents institutional experimentation in LTCI and UHC and recurrent equity gaps, but frequently frames reform through technocratic design parameters, leaving legitimacy, administrative implementation, and accountability mechanisms under-specified. These cluster-specific patterns help explain why findings tend to accumulate in parallel streams rather than converging into transferable explanations.

A central challenge lies in the disconnection between individual-level behaviour and system-level mechanisms. Behavioural studies often foreground decision-making, coping, or subjective well-being but isolate these phenomena from the eligibility rules, benefit structures, provider arrangements, and claims processes that shape insurance access and realised protection. Conversely, actuarial and fiscal models frequently treat older adults as homogeneous demographic inputs, abstracting from heterogeneity in cognitive ageing, caregiving roles, health literacy, digital capacity, and economic precarity. Bridging this gap requires multilevel explanations that trace how perceptions of ageing, risk, and fairness emerge within institutional settings and feed back into system dynamics through enrolment, utilisation, compliance, and political support.

The concept of risk is handled in divergent registers. In psychosocial studies, risk is individualised and internalised—as something to be anticipated and mitigated through proactive behaviour. In policy models, risk becomes actuarial—quantified, pooled, and priced. In institutional design studies, risk is often inferred from financial protection outcomes (eg, catastrophic expenditure or unmet need), without fully specifying how governance arrangements and administrative processes convert formal entitlements into effective protection. A more coherent research programme should therefore treat ageing-related risk as co-produced: individual vulnerabilities and expectations interact with institutional classifications, eligibility thresholds, and coverage rules that determine which risks are recognised, shared, and shifted back to households.

Geographical asymmetries further inhibit theoretical generalisation. Evidence remains disproportionately concentrated in East Asian systems, frequently framed as laboratories for long-term care and financing innovation. Yet comparative learning is underdeveloped: cross-country work rarely specifies which institutional features travel across contexts and which remain contingent on welfare regimes, labour market structures, service delivery capacity, and cultural expectations of family care. Without comparative institutional analysis, the field struggles to move from descriptive contrasts to transferable explanation about why similar reforms yield divergent equity and sustainability outcomes.

Governance remains analytically marginal despite being central to observed outcomes. Across clusters, studies focus heavily on coverage, benefit design, and fiscal sustainability, but seldom examine how insurance systems are governed, for whom, and through what mechanisms of legitimacy, accountability, and administrative capacity. This omission is consequential because the synthesis implies slippage between formal coverage and realised access: equity gaps persist even under universal or near-universal schemes, and reforms introduced for fiscal sustainability may generate distributional consequences through implementation discretion, procedural complexity, and uneven service capacity. As insurance increasingly intersects with algorithmic classification, fragmented care regimes, and cross-border portability of entitlements, legitimacy and accountability require explicit theorisation rather than implicit assumption.

Macroeconomic conditions are also insufficiently integrated into ageing–insurance research. Fiscal sustainability modelling implicitly depends on growth, productivity, labour market structure, and informality, yet these variables are rarely theorised as constraints shaping feasible policy menus and institutional trajectories. An ageing society with weak productivity growth and a shrinking tax base faces distinct limits on financing social insurance, expanding benefits, and subsidising vulnerable groups. Cross-country differences in fiscal space, informality, and macroeconomic volatility are therefore likely to moderate both the feasibility and distributive consequences of LTCI and UHC reforms, and should be incorporated as macro-level boundary conditions in multilevel explanations.

Future Research Directions

The reviewed evidence supports a unified conceptual framework in which ageing–insurance outcomes arise from micro–meso–macro interactions (Figure 4). At the micro level, ageing-risk appraisals, trust, literacy, and caregiving roles shape preferences and participation. At the meso level, scheme architecture and delivery—eligibility rules, benefit depth, premium–subsidy design, provider governance, claims processes, and digital interfaces—structure the translation of formal entitlements into realised protection. At the macro level, governance and political economy—regulatory credibility, accountability arrangements, administrative capacity, and fiscal space—condition both design choices and implementation quality. This framework clarifies why siloed evidence accumulates without integration and identifies where mechanisms and boundary conditions should be specified for cumulative explanation.

Figure 4.

A unified micro–meso–macro framework of ageing–insurance outcomes.

Three strategic directions follow. First, research should strengthen micro–meso integration by linking behavioural constructs to scheme rules and delivery mechanisms. Theory-informed models can examine how perceived transparency and fairness of eligibility and benefit rules shape trust and participation, and how these effects vary by risk/health literacy and caregiving circumstances. Second, temporal dynamics require longitudinal and process-tracing designs that capture policy feedback. Repeated exposure to co-payment changes, eligibility revisions, claims processes, or service bottlenecks may update trust and perceived fairness, generating behavioural adaptation that sustainability modelling often treats as exogenous. Third, a governance-centred agenda should theorise governance as mechanism rather than context: accountability, transparency, appealability, and administrative capacity shape legitimacy, compliance, and equity outcomes, particularly under mandatory participation, digital transitions, algorithmic classification, and portable entitlements. Established theories can anchor operationalisable propositions—for example, legitimacy theory⁵³ for acceptance and compliance under mandatory schemes and administrative burden theory⁵⁴ for understanding how enrolment and claims processes shape realised access and attrition.

To consolidate these directions and maintain clarity, Table 1 summarises future research directions, illustrative propositions, and example research questions.

Table 1.

Summary of Future Research Agenda for Ageing-Insurance Research.

Directions	Illustrative proposition	Example Research Questions
Unified multilevel conceptual framework	Ageing–insurance outcomes are jointly shaped by micro-level ageing-risk appraisals and trust, meso-level scheme design and delivery, and macro-level governance and fiscal capacity; misalignment across levels predicts gaps between formal coverage and realised protection.	How do eligibility rules, claims processes, and delivery capacity translate ageing-risk perceptions into enrolment and utilisation outcomes across welfare regimes?
Micro–meso integration	Institutional trust and perceived legitimacy mediate the relationship between perceived transparency/fairness of scheme rules (eligibility, contributions, benefit calculations) and participation (enrolment, utilisation, compliance); effects vary with risk/health literacy and caregiving roles.	How does perceived fairness in premium–benefit allocation influence LTCI uptake among low-income older adults? Does trust mediate the effect of information campaigns on enrolment behaviour?
Temporal dynamics and policy feedback	Administrative burden in enrolment/claims (learning, compliance, psychological costs) predicts lower renewal and higher attrition over time; supportive delivery infrastructure attenuates this relationship, particularly for individuals with lower digital literacy or greater cognitive constraints.	How do repeated reforms (co-payments, eligibility revisions, claim rules) shape trust formation and switching behaviour across insurance types over time?
Governance legitimacy and accountability	Legitimacy and compliance depend on procedural fairness, transparency, and accountability mechanisms; weak appealability and low regulator credibility amplify equity gaps even under universal schemes, especially under digital and algorithmic administration.	How do governance arrangements (appeals, complaint resolution, auditability) shape perceived legitimacy and compliance in mandatory schemes?
Macro political economy and fiscal space	Macroeconomic conditions (productivity growth, tax base, labour informality, fiscal space) constrain feasible insurance designs and moderate distributional outcomes; demographic pressure interacts with macroeconomic volatility to shape reform trajectories.	How do differences in fiscal capacity and labour informality alter feasible LTCI/UHC pathways in lower-resourced economies relative to high-income East Asian systems?

Practical Implications

This study offers practical insights for policymakers facing the dual challenge of demographic ageing and insurance reform. Many countries, particularly in East Asia, have introduced LTCI and UHC schemes, yet gaps in actual financial protection persist. Consistent with the review’s evidence on the “coverage–protection” gap, policy responses should prioritise implementation and governance levers—not only statutory expansion—to convert formal entitlement into realised access. For example, South Korea’s LTCI system—though widely praised—still produces disparities in out-of-pocket burden by income level and family support status. Policymakers should prioritise not only coverage expansion but also equity-sensitive implementation: (i) targeted default enrolment or contribution waivers for low-income/high-need groups with transparent thresholds; (ii) simplified claims and recertification by reducing documentation and consolidating verification; and (iii) decentralised administration with minimum national service standards to allow local adaptation without postcode inequities. Progress can be tracked through a small dashboard—enrolment/renewal, rejection rates, time-to-approval, and out-of-pocket shares—disaggregated by income, dependency level, and region. These reforms can help transform insurance from a formal entitlement into an accessible right.

For insurance providers, especially those designing products for ageing populations, this study highlights the need for segmentation beyond chronological age. The synthesis indicates that older adults vary systematically in dependency trajectories, caregiving roles, and literacy constraints, with direct implications for product fit and uptake. As shown in discrete choice experiments in Hong Kong, willingness to pay for LTCI varies significantly based on caregiving expectations and health literacy. Insurers can respond by offering modular coverage options—such as short-term home care plans, preventive care bundles, or co-payment caps—that reflect consumers’ caregiving roles and financial capacity. To reduce attrition, product design should be paired with delivery design: assisted enrolment, plain-language benefit calculators, and staged “coverage pathways” aligned with common ageing trajectories. In markets with low digital literacy, insurers should also reintroduce assisted offline enrolment channels and work with community health workers to build trust and improve product understanding among older clients.

Organisational managers in hospitals, care institutions, and health insurers should treat insurance design as an operational lever, not an external constraint. Many systems fail not due to inadequate funding, but due to the misalignment between financial coverage and service delivery. This aligns with the review’s finding that catastrophic expenditure and unmet need can persist despite formal coverage, pointing to delivery bottlenecks and administrative frictions as key failure points. For example, the Indian health insurance system formally covers hospitalisation costs but lacks accompanying transport, caregiver, and post-discharge support, leaving the most vulnerable still exposed. Managers should therefore embed insurance claims data into service audits, monitor benefit utilisation by population subgroup, and adapt resource allocation accordingly. Concrete steps include tracking the top denial/delay reasons, integrating discharge planning with entitlement checks, and deploying case-navigation support for older patients facing high administrative burden. Cross-training administrative and clinical staff on insurance entitlements can also reduce friction at the point of care.

Regulators and supervisory bodies must expand their oversight beyond solvency metrics to include indicators of fairness and legitimacy. As studies on Japan and India show, universal systems may still exclude high-need populations due to complex application procedures or ambiguous eligibility criteria. Regulatory agencies should mandate the publication of disaggregated claims rejection rates, implement complaint-resolution benchmarks, and enforce plain-language communication standards in insurance materials. To make oversight actionable, regulators can require standardised reporting of participation and rejection metrics by subgroup, minimum appealability standards (time limits, independent review, written justification), and periodic administrative-burden audits of enrolment and claims pathways. Where algorithmic underwriting is used, especially in private LTCI, regulators must ensure that digital systems are explainable, auditable, and do not disadvantage older adults with non-standard health histories. At minimum, this requires bias testing, documented governance controls, and an accessible human-review route for contested decisions.

International development actors—such as the World Health Organisation, the World Bank, and regional bodies—should take note of the geographic asymmetry revealed in this study. East Asia’s policy innovations provide valuable lessons, but are not universally transferable. In line with macro-level constraints emphasised in the review, external support should be calibrated to fiscal space, labour informality, and delivery capacity rather than promoting uniform contributory designs. In settings with large informal labour sectors or fragmented welfare states, transplanting contributory models may exacerbate exclusion. These actors can play a facilitative role by funding pilot studies on community-based insurance in lower-income contexts, supporting capacity-building for decentralised governance, and promoting south-south knowledge exchange on low-cost, culturally embedded protection strategies. Priority investments include comparable measurement of effective protection (not only coverage) and evaluation designs that capture policy feedback over time.

Conclusion

This study offers an integrated mapping of the research landscape at the intersection of ageing and insurance by combining bibliometric analysis with a structured systematic review. Based on a co-word analysis of 134 Scopus-indexed articles, 3 dominant thematic clusters were identified—health and active ageing, systemic policy challenges, and financial insurance models. Building on this structure, an in-depth synthesis of 31 empirically rigorous studies clarified how ageing-related risks are conceptualised, how scheme design and delivery shape realised protection, and how governance and political-economy constraints condition both equity and sustainability. Overall, the field appears regionally concentrated and conceptually dispersed—empirically active yet limited in theoretical integration, comparative explanation, and explicit governance theorisation. By linking bibliometrically derived themes to mechanism-oriented synthesis, this review provides an integrative lens and an operational research agenda to support cumulative, policy-relevant ageing–insurance scholarship.

Like any review-based study, this research is limited by its data source and scope. Relying solely on Scopus and high-impact, peer-reviewed journal articles may exclude relevant policy documents, grey literature, and practice-based insights. In addition, the title-restricted search strategy—although appropriate for bibliometric analysis—likely constrained the pool of studies eligible for the systematic synthesis. Future research could broaden coverage by integrating multiple databases and non-academic sources and expanding retrieval beyond titles (eg, abstracts and keywords) using refined, insurance-specific search terms. Such expansion would require more stringent and transparent screening procedures to maintain topical specificity and minimise noise from tangentially related articles.

Supplemental Material

sj-docx-1-inq-10.1177_00469580261438710 – Supplemental material for Publication Trends, Thematic Clusters and Governance in Ageing–Insurance Research: A Bibliometric and Systematic Review

Supplemental material, sj-docx-1-inq-10.1177_00469580261438710 for Publication Trends, Thematic Clusters and Governance in Ageing–Insurance Research: A Bibliometric and Systematic Review by B. A. M Hafizuddin-Syah, Zhangwei Zheng and Qin Lingda Tan in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

We sincerely thank our colleagues, mentors, and industry experts for their invaluable insights and guidance, which have been pivotal in advancing this research. Their commitment and constructive feedback have been essential to the development of our study.

ORCID iD

Zhangwei Zheng

Ethical Considerations

This article is a literature review and did not involve human participants, human data, or animal subjects. Therefore, ethics approval was not required.

Consent to Participate

Not applicable. This study did not involve human participants.

Author Contributions

All authors contributed to the study conception and design. Literature search, data extraction, and analysis were performed by ZZ and TQL under the supervision of BAMHS. The drafting of the original manuscript was primarily undertaken by ZZ, while BAMHS provided critical review and editing. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data sharing is not applicable to this review article since there was no generation or analysis of new data in the study.

Supplemental Material

Supplemental material for this article is available online.

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