Aging in Place or Moving to Higher Ground: Older Adults’ Adaptation to Sea Level Rise in Honolulu, Hawaii

Abstract

Coastal communities face escalating risks from rising sea levels and the increasing growth of vulnerable, aging populations in high-risk zones. These threats are expected to intensify as population growth and aging trends continue. In response to these challenges, this study represents a novel investigation into the synergistic impacts of demographic shifts and climate change in shaping the vulnerability of coastal communities, particularly focusing on elderly populations. This study’s primary objectives are to assess the potential impacts of these threats on vulnerable older adults and to explore effective adaptation strategies. To achieve these objectives, we used census tract data from Hawaii and the Hamilton–Perry cohort-component method to project the elderly population trends in each census tract for Honolulu in 2050. The vulnerabilities of older adults were estimated under different sea level rise level conditions and mapped according to three planning scenarios: (1) maintaining the status quo; (2) relocating or redeveloping vulnerable elderly residents to safer, low-density neighborhoods; (3) relocating or redeveloping vulnerable elderly residents to secure, high-density areas with amenities for older adults. We further evaluated transportation accessibility to emergency services in these scenarios. The findings reveal that with a projected sea level rise of 1.1 feet, the number of elderly individuals without timely access (within 8 min) to emergency and healthcare services would double by 2050. This is primarily attributed to reduced transportation access and increased aging in high-risk areas. Compared to the status quo, both relocation (or redevelopment) strategies significantly improve the vulnerable elderly population’s access to emergency and healthcare services, even without enhancements in transportation and infrastructure. Given that many developments and aging trends are yet to fully unfold, we propose that existing adaptation strategies should prioritize land use development, along with housing and transportation solutions that align with development scenarios 2 and 3, to support age-friendly activities and lifestyles. By directing population growth towards less vulnerable zones in the coming decades, we can achieve protective effects equivalent to those of future relocation efforts, but without incurring substantial protection or relocation costs.

1. Introduction

As a result of climate change, coastal communities are expected to face the impacts of sea level rise, tidal inundation, coastal erosion, and increasingly frequent and intense storms [1,2,3]. These effects are likely to be particularly pronounced in densely populated urban areas [4], creating a critical need for research on climate vulnerability and resilience [4,5]. Frail populations are especially vulnerable to these changes, including the elderly, who are increasingly choosing to reside in coastal regions despite the inherent risks [6]. This growing trend significantly heightens their exposure to climate risks. The unique geographical features, coastal development, and a burgeoning elderly population make Hawaii a region of particular concern with regard to sea level rise and climate change. Hence, it has become vital to study how the increasing elderly population will be affected by sea level rise and coastal flooding in the coming years.

The primary aim of this research is to investigate the implications of sea level rise for Hawaii’s aging population, focusing on how the anticipated sea level rise and coastal flooding might affect elderly populations’ access to essential services in the coming years. It explores the potential of three distinct development scenarios as adaptation strategies. The first scenario, the ‘do-nothing’ approach, allows the risks of exposure and vulnerability to rise unchecked. The second scenario proposes the relocation of future elderly residents (or development for current residents) to nearby safe zones with a low population density. The third scenario suggests relocating the future elderly population (or developing for current populations) to safe zones with a high population density. We compare the levels of accessibility to emergency services and medical care under these scenarios. By analyzing how the projected future elderly population’s access to essential services might be affected by the projected sea level rise in three scenarios, we seek to elucidate the potential of land use planning as a mitigation strategy and investigate its implications for transportation accessibility to emergency services and medical care.

Our paper aims to test the potential of land use planning as a more sustainable, long-term adaptation strategy, focusing on guiding future elderly populations (i.e., current young generations) into relatively safer zones. This approach promotes the concept of safe aging in place during the upcoming decades, with the goal of minimizing the climate risk and preventing future losses. The novelty and importance of this research lies in its integration of demographic projections, climate change impacts, and urban planning scenarios, creating a comprehensive and innovative framework for informing policy and planning decisions. This study provides actionable insights that emphasize the urgency and feasibility of planning for more resilient communities amidst the dual challenges of an aging population and climate change.

2. Literature Review

Urban populations’ rapid growth demands an urgent response to manage and adapt to climate change [1]. As a consequence of climate change, sea level rise poses substantial threats to coastal communities, requiring comprehensive solutions [2]. The projections suggest that there will be an average expected sea level rise of 1.1 feet by the mid-21st century and 3.2 feet by the end of the century globally [3]. These physical changes have potential impacts on elderly people’s access to essential services, raising significant concerns [7].

Hawaii’s vulnerability to sea level rise is amplified due to its dense population, properties, and transport infrastructure along the coastline. As they are located thousands of miles away from the nearest state, the islands have limited access to mutual assistance from other communities. In anticipation of these changes, Hawaii has adopted sea level rise projections from the 5th Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, which indicate rises of 1.1 feet by 2050 and 3.2 feet by the end of the century [8,9]. The current high-tide conditions, along with moderate sea level rise, already significantly impact residents’ accessibility to essential services [10]. Furthermore, the state has witnessed a substantial growth in its population that is aged 65 and older since 2010, with a 37.5% increase, comparing to a 4.1% increase in the overall population during the same period [11]. This demographic shift, coupled with the negative growth in the total population in 2017 and the ongoing growth of the elderly population, emphasizes the urgent need to study the implications of sea level rise and coastal flooding on the vulnerable elderly population in the future [11,12].

Understanding vulnerability is essential for assessing the impacts of climate change [13]. Vulnerability, in the context of disaster risk management, encompasses both the physical resistance of engineering structures and the characteristics of social and environmental processes [14]. Cutter [15] and Aday [16] define vulnerability as “the potential for loss” and vulnerable populations as those “at risk of poor physical, psychological, and/or social health”, respectively. While all people are vulnerable to some extent, certain populations, particularly the elderly, are at higher risk of harm due to them having chronic or pre-existing medical conditions [17]. Several studies have highlighted the increased vulnerability of the elderly to flooding, emphasizing the importance of reducing vulnerabilities via coping strategies [6,18,19]. For example, Hossain and Meng [18] compared the vulnerability of different demographic groups to urban flooding and found that children and the elderly are more vulnerable to harm than others are. Kaźmierczak and Cavan [19] made similar observations about children and the elderly population and focused on coping strategies to reduce vulnerabilities to flooding. Wang and Yarnal [6] found that elderly people living in flood risk zones are especially vulnerable because access to evacuation routes and essential services can be blocked.

The vulnerability of the elderly population extends beyond physical exposure. Designing age-friendly cities involves considering the elderly’s needs and providing necessary resources to reduce vulnerabilities [20]. Factors such as population trends, socioeconomic conditions, health conditions, and social inclusion play significant roles in constructing an age-friendly environment [21]. A “Sense-of-place”, which includes a place identity, a sense of purpose, belonging, and living a meaningful life, is also crucial in age-friendly communities [22]. Age-friendly communities strongly emphasize “place”, because the physical and social support in the place where one lives has a large influence on elders [23,24]. Aging in place policies have become popular as they enable older people to maintain independence and continue living in their community [25,26,27]. Pani-Harreman et al. [27] identified five key themes of aging in place: place, social networks, support, technology, and personal characteristics. In studying the narratives of older adults on place and gentrification, Weil [28] proposed five repertories, including: (1) the losses of friends, services, and places; (2) the difference between insiders and outsiders wanting to shape their identity to the changing neighborhood; (3) social connectivity and how they speak about new ways to get themselves involved in the neighborhood; (4) converting to neighborhood change during gentrification; (5) the gentrification-based change of neighborhood. Integrating age-friendly design and planning with climate change adaptation has been identified as a way to enable elderly people to remain active and engaged in their communities amidst projected climate and environmental changes [29].

In the development of aging-friendly climate adaptation strategies, planners and transportation service operators need to consider various factors, including the impacts of climate change, weather, hazards, and access to safe, affordable, and pleasant travel modes [27,30]. Mitigation and adaptation planning for natural hazards and climate change should also include emergency evacuation, travel to emergency shelters, the provision of mass care, and other disaster response and relief capabilities [30]. While strategies, such as hard structure projections, urban stormwater management systems improvement, and sand nourishment techniques, have been suggested to mitigate the impact of sea level rise, relocation has emerged as a widely discussed, long-term adaptation strategy [1,4,5,6,7,29]. However, challenges arise in the context of necessary relocation due to increasing climate risks, as governments often face difficulties and political opposition when attempting to relocate households to higher ground [31]. In particular, relocating elderly populations to higher ground presents challenges due to the considerations of place and aging in place [31]. Given these considerations, it is crucial to develop future land use plans that support safe aging in place and minimize the need for future relocations.

We acknowledge that as demographics shift, emergency services may change their coverage areas. However, our study proposes to evaluate land use planning with the addition of new emergency facilities as an adaptation strategy to sea level rise in the study area. This is because none of the existing emergency service facilities will be at direct inundation risk due to the projected 1.1 feet sea level rise. Rather, the primary issues stem from the inundation of residential properties and the roads that connect these properties to emergency services, thereby affecting service accessibility. While protecting the properties and the connecting roads with hard structures could provide temporary, but costly, alleviation, this approach will not offer a long-term solution in the face of continuously rising sea levels.

3. Materials and Methods

In order to gauge the impacts of anticipated sea level rise, projecting the future size and distribution of the elderly population is essential. There are various methods for projecting population, each with a unique set of assumptions and limitations [32]. Long and McMillen [33] have categorized several methods employed by the U.S. Census Bureau, which include demographic accounting and more complex deterministic and explanatory methods. The choice of a projection method hinges on several factors, among which are the size of the geographic unit and data availability. While smaller geographic regions often produce spatially targeted results, projecting population trends for these areas typically necessitates models that factor in housing, the economic base, or land use allocation [34], which require extensive datasets that are not always readily available.

Among these projection methods, the cohort-component method is a popular choice due to its simplicity and reliability [35,36]. A ‘cohort’ is a group of individuals experiencing a similar demographic event within a specific time period, such as aging, marriage, or death [37]. The Hamilton–Perry method is a variant of this approach, and it is used to estimate cohort change ratios (CCR) between two recent census datasets to predict future population trends [35,36,38]. This iterative process can theoretically continue indefinitely, with each projected population serving as the foundation for the subsequent projection cycle [34].

However, such as other cohort-component methods do, the Hamilton–Perry method fundamentally assumes that past demographic trends—fertility, mortality, and migration rates—will persist into the future. Unanticipated changes in these factors could, however, lead to inaccurate results [35,36]. This method also assumes stability in the CCR over time, suggesting that the ratio for each age group will remain constant in the future. Yet, the CCR can be influenced by a range of factors, such as changes in public policy, economic conditions, and social behaviors. These can vary significantly over time, thus necessitating further validation in future studies [35,36]. Another limitation of the Hamilton–Perry method is its potential inadequacy in accounting for significant changes in the boundaries of geographic areas over time [35]. In rapidly evolving or growing areas, substantial boundary changes between censuses can lead to errors in population projections. Finally, in areas with small populations, irregular migration patterns, or significant demographic shifts, the method may not be as reliable since it heavily relies on the stability and predictability of demographic trends [35,36]. Therefore, while the Hamilton–Perry method provides a straightforward and reliable approach for population projection, it is crucial to acknowledge these assumptions and potential limitations when interpreting the projected outcomes.

Given the relatively stable census tract boundaries between 2010 and 2019 in the study area, the City and County of Honolulu, we chose to use the Hamilton–Perry method to project the future elderly population in each census tract for 2050, taking into account data availability. We used the most recent American Community Survey (ACS) data from 2010 and 2019 to estimate the elderly population (age 65+) for 2020 via simple linear regression models for each census tract (

Table 1. Data sources.

Data	Resource	Publisher	URL
2019 Honolulu census tracts data—by age group	American Community Survey 2019—5-year dataset that includes all geographic areas down to the block group level	American Community Survey	https://census.hawaii.gov/acs/acs-2019/ (accessed on 30 July 2021)
2010 Honolulu census tracts data—by age group	2010 American Community Survey (5-Year Estimates) Hawaii Geographic Area Profiles—census tracts	American Community Survey	https://census.hawaii.gov/acs/acs2010/acs2010_5_year/acs_hi_2010_profiles_5yr_estimate/acs_hi_2010_profiles_ct/ (accessed on 30 July 2021)
SLR 1.1 ft exposure	State of Hawaii Sea Level Rise Viewer|PacIOOS	Tetra Tech, Inc. and University of Hawaii Coastal Geology Group. 2017	https://www.pacioos.hawaii.edu/shoreline/slr-hawaii/ (accessed on 30 July 2021)
Road network	Honolulu Open Geospatial Data, 2021	City and County of Honolulu	https://honolulu-cchnl.opendata.arcgis.com/ (accessed on 30 July 2021)
Fire Station	Honolulu Open Geospatial Data, 2021	City and County of Honolulu	https://honolulu-cchnl.opendata.arcgis.com/ (accessed on 30 July 2021)
Hospital and Clinic	Honolulu Open Geospatial Data, 2021	City and County of Honolulu	https://honolulu-cchnl.opendata.arcgis.com/ (accessed on 30 July 2021)

). The estimated 2020 elderly population and 2010 ACS data were then utilized to project the elderly population for each census tract for 2050 using Equations (1) and (2).

Our sea level rise projections adhere to the upper-end forecast in the 5th Assessment Report (AR5) by the Intergovernmental Panel on Climate Change, suggesting a rise of 1.1 ft by 2050. We utilized SLR exposure data from the University of Hawaii’s Coastal Geology Group [39] to assess the potential risk to land, population, road networks, and facilities (Table 1). However, it is worth acknowledging the limitations of this approach. SLR exposure data comprise three chronic flooding hazards linked to sea level rise: passive flooding, annual high wave flooding, and coastal erosion. These data present a conservative estimation of potential long-term, chronic hazards due to sea level rise, but they exclude extreme high wave flooding, storm surge, and tsunami events [39]. This exclusion could potentially underestimate the risks associated with sea level rise.

Equations (1) and (2) were utilized to estimate the cohort change ratios and project the elderly population trends for each census tract in the study area. By overlaying the 2019 ACS data and the projected elderly population for 2050 with the projected 1.1 ft sea level rise exposure [39], we were able to identify the most vulnerable census tracts, which were largely concentrated within elderly populations. It should be noted, however, that this analysis assumes an even population density within each census tract, which may not hold true for large tracts with substantial undeveloped land.

Equation (1) is used to estimate the cohort change ratios for each census tract, i, for each decade between 2020 and 2050.

$${CCR}_x=\frac{\left(n{P}_{x,t,i}\right)}{\left(n{P}_{x-k,t-k,i}\right)}$$

(1)

where

$n{P}_{x,t,i}$ is the population aged x to x + n at time t for area, i, which is typically the most recent census.

$n{P}_{x-k,t-k,i}$ is the population aged from x − k to x − k + n at a preceding point in time (t − k) for area, i, which is typically the 2nd most recent census,

k is the number of years between the most recent census at time t and the one preceding it at time t − k.

The estimated CCR was used to project elderly population for each decade in each census tract using Equation (2).

$$n{P}_{x+k,t+k,i}=\left(n{CCR}_{x,i}\right)\ast \left(n{P}_{x,t,i}\right)$$

(2)

where

$n{P}_{x+k,t+k,i}$ is the projected population aged x + k to x + k + n at time (t + k) for area, i,

$n{CCR}_{x,i}$ is the cohort change ratio as described earlier, and

$n{P}_{x,t,i}$ is the population aged x to x + n at the most recent census (t) for area, i.

Furthermore, we identified potential redevelopment or future relocation zones for the future elderly population by calculating the percentage of land affected by a 1.1 ft sea level rise in each census tract and assessing the current population density to represent the potential to accommodate more development or future relocation. We conducted network analysis to estimate the number of elderly population with and without appropriate emergency and health care coverage in each scenario to compare the efficacies of these adaptation strategies. However, this approach assumes that current redevelopment and future relocation are viable strategies, an assumption that may face challenges and resistance given the preference for aging in place. Rather than advocating for future relocation, we suggest using the findings to inform current development plans, steering future growth towards less vulnerable areas. It is worth noting that this approach assumes the capacity of high-density areas to accommodate the targeted population, which may not always be the case. These assumptions and potential limitations should be taken into account when interpreting the results.

4. Results

Based on the 2019 ACS data, cohort-component method, and calculations using Equations (1) and (2), the number of census tracts and vulnerable elderly residents most likely to be impacted by future coastal flooding under present day and 2050 projection are summarized in

Table 2. Population, elderly residents, and areas impacted by sea level rise.

Sea Level Rise	No. of Census Tracts at Risk	Land at Risk (Acres)	Population at Risk (Current, 2019)	Elderly at Risk (Current, 2019)	Elderly at Risk (2050)
0.5 ft	115	4898	15,277	2507	9608
1.1 ft	115	5313	16,393	2685	10,441
2.0 ft	117	6391	19,431	3174	12,864
3.2 ft	123	9402	33,159	5512	19,463

. It shows under the current population distribution pattern, total population at risk and the elderly population at risk will increase as sea level rises of 0.5 feet, 1.1 feet, 2.0 feet, and 3.2 feet. If we extrapolate these data, the size of the elderly population at risk in a sea level rise scenario in 2050 would have a 385% increase on average.

Without active adaptation, the trend of an aging population and the risks associated with sea level rise will cause a drastic increase in the proportion of the elderly population exposed to this hazard by 2050. Figure 1 illustrates this, displaying the distribution of the population over age 65 that is exposed to sea level rise by census tract in 2019, alongside future projections. The size of the red circles represents the number of elderly people at risk of coastal flooding hazards due to sea level rise.

We estimate that the total number of elderly individuals in the vulnerable census tracts will almost quintuple from 2685 in 2019 to 10,441 in 2050. Geographical changes will also occur: by 2050, there will be more aging people in urban Honolulu and west Oahu low-lying areas, such as Kapolei and Ewa beach, compared to those in Hawaii Kai and the windward side currently. It is important to note that these shifts do not indicate significant reduction in areas such as Hawaii Kai or windward side; rather, it highlights the extraordinary increase in population aging in West Oahu and North shore by 2050.

In terms of land vulnerability, Figure 2a shows the census tracts most at risk due to 1.1 feet of SLR, measured in terms of the percentage of land area most at risk of flooding. The red areas signify the highest risk, with about 30% of the land being vulnerable to flooding, while high risk tracts (orange) have 10–20% of the land area at risk of flooding from 1.1 feet of SLR. Tracts with less than 5% of land area at risk of flooding (green) are considered to be at low-level risk. Similarly, Panel 2b displays the population densities measured by persons per acre in 2019, with the darkest blue color signifying the highest density. Most of the densely populated tracts are located in the primary urban center, although there are other high density locations west of the city center in the Salt Lake, Waipahu, and Pearl City neighborhoods.

To illustrate the adaptation scenarios, Figure 3 identifies the high-risk zones (shown in red) that encompass significant concentrations of vulnerable elderly populations in 2050. The green areas indicate safe zones. In areas with a risk of less than 5%, we assume that vulnerable elderly individuals could adapt within the same census tract. Based on these assumptions, there are a total of 8659 vulnerable elderly individuals at high-level risk. Figure 3 visually presents the locations of these populations (red areas) and potential sites for relocation or redevelopment (green areas). Two scenarios, (a) and (b), are represented, proposing different strategies for relocation or redevelopment. Scenario (a) focuses on directing the vulnerable elderly population to the nearest low-density safe zones, while Scenario (b) directs them to the nearest high-/medium-density safe zones. Opting for development and future elderly populations in low-density tracts (Figure 3a) offers more land and space for development, distributing the population and associated risks across a broader area and multiple tracts. This approach contrasts with concentrating the risks in existing densely populated areas, which are primarily located in urban settings downtown, East Honolulu, in Kailua, Central Oahu, Wahiawa, and West Oahu (Figure 3b).

Taking into account the socioeconomic characteristics of at-risk tracts and safe tracts, Figure 4 presents the median household income and the proportion of Native Hawaiian and Pacific Islanders in these areas. The height of the bar represents the median household income for the relevant census tracts. The color of the bar represents the types of census tracts: red bar represents the median household income for census tracts that need relocation or development change, blue represents the median household income for receiving census tracts with relatively high densities, and red represents the median household income for receiving census tracts with relatively low density. The rest of the census tracts that does not need development change are shown as white. The data reveal no substantial disparities in the median income and the proportions of Native Hawaiian and Pacific Islanders between tracts that are at risk and those that are considered to be safer nearby. This suggests that neighboring tracts share a similar socioeconomic status and racial demographics, and thus, the proposed relocation or redevelopment to nearby safer zones would not disproportionately burden marginalized communities, given the comparable socioeconomic conditions. However, we acknowledge the necessity to consider other factors that could potentially affect marginalized communities during development or relocation, such as social networks, access to services, and cultural ties to specific areas. Detailed studies on these considerations should be performed in future research before moving to policy considerations.

Access to emergency services is a key consideration. Using established standards from the National Fire Protection Association (NFPA) [40], we modeled the 8 min response time for advanced life support. Eight-minute service area coverages were generated for fire stations and hospital/clinics based on travel times on the road network using ArcGIS Version 10.8.1 Network Analyst. The assumed travel speeds are 60 miles/hour for freeways, 45 miles/hour for arterial roads, 35 miles/hour for city streets, and 25 miles/hour for other minor roads. Fire station, hospital/clinic location, and street network data were obtained from City and County of Honolulu Open Geospatial Data Portal [41]. None of the 46 hospitals/clinics are located in 1.1 ft sea level rise inundation zone. Out of a total of 45 fire stations, only one fire station located in Hauula is within the 1.1 ft inundation zone, which was excluded from the analysis. There are 381 segments with a total of 89 miles (approximately 3%) of roadways at the risk of being affected by 1.1 ft sea level rise, which were excluded from the 2050 scenario analysis. The elderly populations are assumed to be evenly distributed within each census tract. Spatial join was conducted to calculate the number of elderly people outside the 8 min service area coverage for emergency services and health care.

The results are presented in

Table 3. Elderly population without high level of access to emergency services and medical care.

Scenario	Elderly Population Outside 8 min of Emergency Service Coverage		Elderly Population Outside 8 min of Hospital/Clinic Coverage
	Person	% of total elderly	Person	% of total elderly
Current (2019)	48,420	28.42%	52,507	30.82%
2050 Doing nothing	116,607	29.53%	144,930	36.70%
2050 Relocate to low-density area	105,126	26.62%	135,133	34.22%
2050 relocate to high-density area	101,612	25.73%	131,665	33.34%

for 2050 in three different scenarios: (1) do nothing; (2) relocate to low-density zones; (3) relocate to high-density zones. In 2019, 48,420 elders lived outside the 8 min coverage for emergency services, which is approximately 28% of the total elderly population. This number will more than double to 116,607 in 2050. Relocating the at-risk elderly population to low-density zones will increase the proportion served by emergency services to 289,787 (73.38% of total elderly population). Relocation to high-density zones will further increase the size of the elderly population with timely emergency services coverage to 293,303 (74.27%). In general, if emergency facilities remain in today’s place, the majority of the demand could be fulfilled in 2050. However, compared to emergency services, access to hospitals and clinics would be more severely affected. In 2019, 52,507 of the elderly residents (30.82%) live more than 8 min of travel away from a hospital or a medical clinic. By 2050, in the do nothing scenario, that number will almost triple to 144,930, representing 36.7% of the elderly population. Relocating residents to low-density communities reduces the number of elders without timely coverage to 135,133 (34.22%), but relocation to high-density zones further reduces the number to 131,665 (33.34%).

5. Discussion and Conclusions

By introducing a novel, integrated approach, this study examines the impact of sea level rise on the particularly vulnerable elderly population. By combining population projections with geographical and socioeconomic data, our research offers an in-depth and comprehensive analysis of the potential risks associated with sea level rise and increased coastal flooding. The research unveils striking trends of an aging population being in vulnerable coastal areas is projected to experience an almost five-fold increase by 2050 if no adaptive measures are taken. This research bears similar findings with studies that have examined the impact of climate change on vulnerable populations [10,42,43]. However, our study further refines these general observations with an emphasis on the elderly population in Hawaii, how projected sea level rise may affect their access to essential services, and the potential of land use planning as mitigation strategies. Moreover, this study devises unique adaptation scenarios for directing vulnerable elderly populations to safer zones. These scenarios take into account both the population density and sea level rise risk considerations, offering spatially explicit strategies for risk mitigation, which is a feature that is rarely seen in similar studies.

The findings indicate that compared to physical infrastructure damages, an aging population is at a high risk because of sea level rise due to its increasing size. This underscores the necessity for proactive development or relocation strategies. In the ‘do nothing’ scenario, the use of current demographic data would likely underestimate the future impacts. A consideration of the behaviors and sensitivity of vulnerable groups, such as the elderly living in coastal areas, is vital when crafting adaptation plans. Encouraging more current development or future relocation to less-exposed zones will likely mitigate flood risks, enhancing access to emergency and healthcare services for elderly people. Notably, the development or relocation to high-density areas with better transportation, medical, and other services will enhance service access more than development or relocation to low-density areas will. However, challenges, such as limited land availability and high development costs, may arise in densely populated urban areas. In contrast, low-density areas may offer more room for development, but could face resistance from current residents to limit growth. Balancing safety, service accessibility, mobility, and quality of life should be considered in potential adaptive development or relocation plans. The study acknowledges that moving to a different community may be difficult and unpopular, as long-time residents often prefer aging in place due to the familiarity of their home, neighborhood, relationships, and existing networks. Safety concerns, particularly in urban areas, can also arise. Therefore, the study emphasizes the importance of changing current development patterns to discourage attachment to high-risk areas and promote aging in safer locations, rather than relying solely on future relocation. With the projected impacts for 2050, there is still an opportunity window to utilize land use planning tools as a mitigation strategy.

Figure 5 shows the current spatial distribution of senior care facilities (indicated in green) and the location of hospital and emergency service facilities in the primary urban core in Honolulu. The map includes the alignment of the elevated fixed rail rapid transit system and an overlay of the transportation network. Three observations that are pertinent to the potential development or relocation of elders in high density locations emerge. First, there are presently many care homes and housing opportunities for seniors to stay away from high-risk coastal locations. Second, the majority of existing care facilities are located in neighborhoods at a higher elevation and are not likely to be impacted by the projected 1.1 feet SLR in 2050. While there may be other climate stressors, such as riverine flooding, high heat, wildfire, and extreme weather events, encouraging current populations or future seniors into the urban core would reduce the risks of coastal flooding hazards. A third observation concerns the fixed rail system, integrating bus, paratransit, and ridesharing services in the urban core: the relocated seniors from high-risk coastal areas would have improved transportation, emergency services, medical care services, and amenities associated with urban living. The significant clusters of senior care homes also provide opportunities for greater social interaction and closer proximity to caregivers, family members, and others compared to those of isolated, coastal communities.

These findings highlight the importance of spatial planning in forging more resilient communities. They underline the urgent need for integrated strategies that account for demographic shifts, geographical hazards, and socioeconomic factors. Our research underscores the necessity of planning for the projected rise in sea level and the concurrent increase in the size of the elderly population. Our novel approach to assessing future vulnerability and the effectiveness of potential adaptation strategies provides an invaluable tool for policymakers and planners. It is evident that development strategies, coupled with a deep understanding of the demographic and socioeconomic landscapes, can greatly mitigate the impact of sea level rise on the vulnerable elderly population. This study signifies a crucial step forward in the convergence of demographic trends, climate change predictions, and urban planning. With potential implications extending beyond our study region, our findings are set to inform adaptive strategies in similar coastal areas.

There are three distinct policy options that emerge from this research. Firstly, it is crucial to inform current residents, including future elderly residents, about the risks associated with climate change and the challenges related to aging and accessing medical and emergency services. Secondly, transportation service providers and stakeholders involved in evacuation and emergency care should be attentive to potential disruptions caused by increased flooding, storms, and other climate-related hazards. Lastly, those engaged in planning, zoning, and development should address the needs of both the aging population and the threats posed by climate change. While improvements can be made within high-risk neighborhoods, promoting and encouraging growth in safer locations with better access to essential services, healthcare, and amenities for the aging population may also be necessary and more cost effective.

However, this study does have certain limitations. There are uncertainties with projecting population growth and estimating exposure, vulnerability, and risk. The use of census tracts as a unit of analysis may be too broad. It would be beneficial to have better, more disaggregated data on land use, flooding hazards, and neighborhood features to gain a deeper understanding of the local context and residents’ willingness to trade hazard risks for improved urban amenities. Additionally, it is important to consider other factors that contribute to the risks faced by the elderly, such as changes in trip generation patterns as an individual ages [44] and the need for improved transportation services, paratransit options, and mobility solutions such as ride sharing [45]. Creating mobility hubs that enhance connectivity among different modes of transportation, including public transit, while addressing first/last mile connections, can also be explored to improve access and mobility for the elderly population [46].

Future research could explore the potential of leveraging existing infrastructure, such as senior care facilities, to reduce the vulnerabilities of the future aging population. Additionally, future investigations could focus on alternative strategies, such as adding new emergency services, improving transportation services, establishing mobility hubs for the elderly, and developing automated vehicles and enhanced delivery services, to enhance community resilience. In conclusion, this study provides valuable insights for the future planning and development of age-friendly urban areas in response to sea level rise. It offers practical applications to inform development strategies and policy decisions for the aging population in Hawaii.