How walkable are our cities for older adults? Mediation of comfort, convenience, and aesthetics

Linkage of government policies on infrastructure with comfort, convenience, and aesthetics

The interconnection between government policies on infrastructure and the comfort aspects of walkability is pivotal for fostering pedestrian-friendly built environment for walkability. Infrastructure policies have a profound impact on the physical layout and amenities that directly impact the comfort of individuals navigating on foot (Fan & Cui, 2023). Well-designed and comfortable sidewalks, benches, and aesthetically pleasing landscaping contribute to the physical comfort of pedestrians and promote walkability (Ali & Baper, 2023). Infrastructure policies, which dictate the design and maintenance of public spaces, sidewalks, and thoroughfares, have a profound influence on the aesthetics of the built environment for walkability (Mandeli, 2019). The government policies on infrastructures, which prioritize green spaces, street trees, and landscaping, not only contribute to the visual beauty of walkable areas but also provide shade and a sense of tranquility (Elderbrock et al., 2020).

While these are the findings of earlier studies, there is no empirical proof to support these findings; hence, the following hypothesis is postulated.

Linkage of community engagement programs with comfort, convenience, and aesthetics

Community engagement programs serves as a conduit for understanding the diverse needs and preferences of residents, fostering a collaborative approach to enhancing the comfort of public spaces (Bull et al., 2008). Through participatory planning processes and community-led initiatives, residents become active contributors to the design and activation of public spaces, ensuring that these areas align with their cultural, social, and recreational aspirations (Vercher et al., 2021). Community engagement programs serve as crucial platforms for fostering collaborative dialogue between community members and local authorities, enabling the identification of specific needs related to convenience in walkability (Svara & Denhardt, 2010). Engagement programs often lead to the incorporation of culturally significant elements into the urban fabric, creating visually stimulating environments that celebrate diversity and enhance the overall aesthetic experience of walking (Chan et al., 2012).

There are many such conceptualizations related to these two variables; however, the empirical proof is missing, and hence, the following hypothesis is postulated.

Linkage of age-friendly urban design policies with comfort, convenience, and aesthetics

Comfortable walking experiences involve protection from harsh weather conditions, such as excessive sunlight or rain, and design elements such as trees, awnings, or covered walkways contribute to the overall comfort of pedestrians, allowing them to enjoy their walks in various weather conditions (Rosenberg et al., 2013). Benches strategically placed along pathways not only provide physical comfort but also contribute to a sense of comfort, encouraging older adults to engage in outdoor activities confidently (Finlay et al., 2015). Age-friendly urban design policies prioritizes the integration of green spaces, well-maintained landscapes, and public art, fostering an aesthetically pleasing environment that encourages individuals to engage in outdoor activities (Caronte-Veisz, 2022). The design of pathways, pedestrian zones, and street furniture is thoughtfully curated to blend functionality with beauty, creating visually attractive spaces that promote a sense of well-being (King et al., 2020).

While these facts are established on the basis of observations through qualitative studies, there is no empirical proof for these findings; hence, the following hypothesis is postulated.

Linkage of comfort with increased physical activity level, increased socialization and improved quality of life

Physical comfort, derived from ergonomic spaces, cosy homes, and comfortable attire, directly influences an individual’s sense of relaxation and reduces physical stressors in daily life (Heijs & Stringer, 1987). Comfort extends to environmental aspects as well, encompassing surroundings that offer tranquility, access to nature, and amenities that enhance daily life (Brochado & Pereira, 2017). Emotional comfort arising from positive social interactions and a welcoming atmosphere reduces feelings of isolation and anxiety and promotes a sense of security, creating an environment conducive to open communication and togetherness (Khairy et al., 2023). Emotional comfort, derived from positive social interactions, supportive relationships, and a sense of togetherness, plays a crucial role in boosting morale, reducing feelings of isolation, and promoting emotional resilience (Suaib, 2024).

While these facts are established on the basis of observations through qualitative studies, there is no empirical proof for these findings; hence, the following hypothesis is postulated.

Linkage of convenience with increased physical activity level, increased socialization and improved quality of life

Physical activity is often impeded by barriers such as accessibility challenges or inconvenience, particularly for the elderly (Baert et al., 2011). The reciprocal relationship is evident, as increased convenience correlates with increased physical activity level, contributing to improved cardiovascular health, enhanced mobility, and overall well-being (Chen et al., 2011). Age-friendly communities with conveniently located healthcare facilities, accessible public spaces, and easily navigable urban layouts contribute to reduced stress and improved quality of life for older adults (Marston & Van Hoof, 2019). Additionally, convenience transportation options, home modifications for accessibility, and user-friendly technologies further empower aged adults to engage in activities they value (Dabelko-Schoeny et al., 2020).

While these facts are established on the basis of observations through qualitative studies, there is no empirical proof for these findings; hence, the following hypothesis is postulated.

Linkage of the aesthetics with the increased physical activity level, increased socialization and improved quality of life

Aesthetically pleasing spaces, such as well-maintained parks, scenic walking paths, and thoughtfully landscaped areas, create an inviting atmosphere that encourages seniors to engage in outdoor activities (Semenzato et al., 2011). Integrating art, greenery, and aesthetic elements into urban planning and recreational areas enhances overall ambiance, making physical activity more enticing for older adults (Zhang & Kim, 2023). Aesthetically pleasing communal spaces, adorned with greenery, public art, and inviting architecture, create a welcoming atmosphere that can lead to increased socialization among older adults (Cattell et al., 2008). Aesthetics, including the design of public spaces and community hubs, plays a crucial role in reducing feelings of isolation and loneliness, contributing to improved mental well-being for the elderly (Leikas, 2020). The linkage between aesthetics and an improved quality of life through walkability for aged adults encapsulates the transformative impact of visually appealing and well-designed environments on their overall well-being (Zhao & Chung, 2017). Aesthetically pleasing walkable spaces, characterized by charming landscapes, well-maintained pathways, and thoughtful urban design, not only motivate seniors to engage in regular physical activity but also contribute to increased enjoyment during their walks (Khder et al., 2016).

While these facts are established on the basis of observations through qualitative studies, there is no empirical proof for these findings; hence, the following hypothesis is postulated.

The hypothetical model is shown in Figure 1.

Figure 1. Hypothetical model.

Research Philosophy

This research is based on the positivist paradigm with a quantitative approach using a survey strategy. A self-administered questionnaire was used to collect quantitative data via both manual and electronic formats. The convenience sampling technique was used, as random selection through unique identifiers from a population size of 170,000 older adults from the sampling frame was not practicable, as demanded by probability sampling. Moreover, convenience sampling, particularly in the context of SEM analysis, is a widely accepted technique because it provides flexibility to maximize the sample through random selection from all seven taluks from the district (e.g., Mukuka, 2024). The analysis includes both descriptive statistics through a measurement model and inferential statistics through the structural model.

The study area

The Udupi District in Karnataka, India, is the geographical location selected for this research, as it is a typical urbanizing study area in a rapidly developing country. It is also the most common type after the destinations of older adults because of its proximity to essential services, parks, shrines, recreational areas surrounded by nature with the Arabian Sea on one side, and the Western Ghats of India on the other. Moreover, Udupi is also a popular tourist and pilgrimage destination known for its temples, beaches, and historical monuments (Ashimava Praharaj, 2016; Vikram, 2024). The district is home for approximately 1,70,000 older adults, for accounting 14% of district population. Udupi, signifies a medium size city in a developing country of India, offering interconnected streets, linked to business centres, religious nodes, local transport thus providing access to older adults. It is considered as retirement destination, that support parks and open spaces, medical services and other amenities, making it a suitable study area for this research. Due to infrastructure development, improved healthcare facilities and expansion of educational institutions in the past decade, the district has experienced rapid urbanization with the 18.3% population growth (Ramanna and Hanjagi, 2019). With the highest literacy rate (86.24%), Udupi represents a well-educated and receptive population, to engage in urban planning processes and mobility initiatives (Census, India). There is a need for age-friendly public infrastructure, due to nuclear family trends and also the increased life expectancy. Udupi becomes an ideal case due to its demographic factors for exploring walkability and tailored urban design policies. Udupi, a rapidly urbanizing fosters opportunities and challenges in balancing age inclusive infrastructure and modernization, in alignment with India’s smart city mission (Jahangir et al., 2024).

Research design

This research is a correlational study with a cross-sectional design and a quantitative approach. A self-administered questionnaire built on a 5-point Likert scale was used and analysed through SEM to determine the statistical significance of the relationships between the study variables. To ensure data reliability and validity in this type of research design, measures such as Cronbach’s alpha, composite reliability, discriminant validity, and Rho-A were employed. This methodological approach offers a robust research design for exploring how government policies on infrastructure, community engagement programs, and age-friendly urban design policies impact the mediation of comfort, convenience and aesthetics issues related to walkability for older adults in the built environment.

Sampling procedure

Udupi has a older adults’ population of approximately 1,70,000. As unique identifiers are not practical, the option left was through convenience sampling technique. A sample of 333 older adults aged 60 years and above living in Udupi Distric was selected. The respondents were residents of Udupi for more than 5 years, and are been physically active. The sampling method used in this research was convenience sampling. Cohen’s effect size method is a method for testing sample size adequacy. Effect size influences the power of statistical tests and the ability to detect meaningful relationships within the model (Hair and Alamer, 2022). The most common method is the G*Power estimate (Christopher Westland, 2010). The online G*Power Estimation Tool (version 3.1.9.7) was used with the following considerations as applicable to this research. For the effect size (f ²) = 0.3 (medium effect) and alpha error probability (α) = 0.05, the G-Power (1 - β) was found to be 0.99, confirming the adequacy of the sample size. The sample was drawn from various built environments within Udupi districts, ensuring diverse representations of the age groups of older adults, genders, marital statuses, educational backgrounds, and socioeconomic statuses.

Questionnaire design

The questionnaire design followed the standard procedure of selecting items from standard scales designed by earlier researchers. Items from the Urban Accessibility Index (UAI), Infrastructure Quality Index (IQI), and Sustainable Infrastructure Index (SII) (Alderete. 2020; Benítez-Márquez et al., 2022; Lai & Cole, 2023) were chosen for government policies on infrastructure; items from the Community Engagement Scale (CES), Community Participation Scale (CPS), and Citizen Participation Assessment Tool (CPAT) (Doolittle & Faul, 2013; Chipuer & Pretty. 1999) were chosen for community engagement programs, and items from the WHO Age-Friendly Cities Questionnaire (WAFQ), Age-Friendly Communities Scale (AFCS), and Built Environment Assessment Tool (BEAT) (Dikken et al., 2020; Glanz et al., 2016; Gibberd, 2019) were chosen for the AUG; the Pedestrian Comfort and Safety Assessment (PCSA) (Asadi-Shekari et al., 2015) and Perceived Comfort Scale (PCS) (Zegeer, 2006) were chosen for the comfort scale; the Pedestrian Convenience Sampling Assessment Tool (PCAT) (Aghaabbasi et al., 2018) and Walkability Audit Tool (WAT) (Soltani et al., 2018) were chosen for convenience; the Walkable Design Visual Quality Assessment (VQA) (Abdelfattah & Nasreldin, 2019) was chosen for the aesthetics scale; the International Physical Activity Questionnaire (IPAQ) (Armstrong & Bull, 2006) was chosen for increased physical activity level; and the Neighborhood Social Cohesion Questionnaire (NSCQ) (Agampodi et al., 2015) was chosen for increased socialization. The items in the questionnaire were modified slightly to suit the local context; hence, reliability and validity were reassessed through Cronbach’s alpha reliability measures.

The first section of the questionnaire was reserved for assimilating sociodemographic information, and the second section comprised 5-point Likert scale items to measure the perceptions of the built environment for walkability by older adults of government policies on infrastructure, community engagement programs, age-friendly urban design policies, comfort, convenience, aesthetics, increased physical activity level, increased socialization, and improved quality of life.

Data collection process

The data collection process was carried out between March and June 2024 for over a four-month period. The researcher personally collected physical copies of the self-administered questionnaire filled out by participants in their homes, parks, and community centers across different locations in the Udupi district. The items in the questionnaire were briefly presented by the researcher to the participants, highlighting their importance during the personal model of data collection. A brief explanation of the research was provided in the Google Form with the contact details of the researcher to revert in case of any queries/difficulty. Google forms were also distributed to the participants where it was not possible to take physical copies. 186 hard copies were collected through physical copies of the completed questionnaire, the remaining 147 were obtained through Google Forms. Physical copies yielded a response rate of 37.2%. However, the 147 responses were through google forms, resulting a return rate of 73.5%.

Ethical considerations

The study was conducted in adherence to the ethical guidelines, with the rights and well-being of the participants being protected through the process. The ethical clearance was formally given by the Kasturba Medical College Institution and Kasturba Hospital (constituent unit of the Manipal Academy of Higher Education, Manipal-576104), the Ethics Committee (Registration No. ECR/146/Inst/KA/2013/RR-19) (DHR Registration No. EC/NEW/INST/2019/374), having ratified the entire research procedure with approval number -IEC1: 387/2022. The approval remains valid from 5 July 2023 to 31 May 2027. Further, informed consent was obtained from all participants before the commencement of data collection. Anonymity and the confidentiality of the responses were declared in the questionnaire, which communicated well to all the respondents. They were informed that their participation was voluntary and that they could withdraw from the study at any point without any consequences.

Data analysis

The analysis included descriptive statistics facilitated through a measurement model and inferential statistics through the structural model. The suitability of convenience sampling, particularly in the context of SEM analysis, has been widely accepted by earlier researchers owing to the voluntary nature of the research and wider reachability to the respondents (e.g., (Mukuka, 2024). The analysis includes both descriptive statistics through the measurement model and inferential statistics through the structural model. Structural equation modelling is particularly well suited for this research because it enables the examination of complex relationships among multiple latent variables, such as comfort, convenience, and aesthetics as the mediating variables between the contextual factors and the outcome of walkability through the built environment for walkability for older adults. Additionally, structural equation modelling accounts for measurement errors, which enhances the accuracy of the results and allows for the simultaneous estimation of both direct and indirect effects during hypothesis testing. These features make structural equation modelling an ideal tool for modelling the interdependencies within the conceptual model. Further reliability and validity was tested in the study. Reliability in quantitative research signifies how consistently and stably the measurement tools perform, typically gauged by internal consistency indices such as Cronbach’s alpha (Hair et al., 2010). Validity, conversely, guarantees that the tool genuinely captures the constructs it purports to measure, and it is normally assessed through content, construct, and the policies of convergent and discriminant validity (Fornell & Larcker, 1981). This study reinforced quantitative rigor by using already validated scales, determining internal consistency via Cronbach’s alpha, and executing confirmatory factor analysis to examine construct validity. To further substantiate the reliability and validity of the constructs, Composite Reliability (CR) and Average Variance Extracted (AVE) were additionally calculated within the context of the structural equation modelling framework.

Sociodemographic characteristics of the samples

Table 1 shows a nearly equal gender distribution, with 52.9% male and 47.1% female respondents observed in the sample selected for this research. The age group of 60–65 years (45.0%) was the majority, followed by the age group of 65–70 years (40.9%). Among the respondents, the majority were married (41.5%), the next in the line widowed (26.1%), followed by unmarried (16.8%), with representations from other categories such as divorced (6.9%), separated (6.6%), and in the ‘other’ category (2.1%), which includes live-in relationships. Furthermore, slightly more than half of the respondents (51.3%) had a bachelor’s degree, followed by a master’s degree (26.4%), and a smaller percentage had diplomas (14.5%), while a small percentage had certificates (3.6%) or doctor of philosophy degrees (3.6%). Finally, the majority of participants (47.8%) belonged to middle-income group-1 (7,150–14,300 USD per annum), followed by middle-income group-2 (34.2%) (14,300–21,450 USD per annum), low-income group (11.7%) (3,565–7,150 USD per annum), and high-income group (6.3%) (greater than 21,450 USD per annum), with a small number (4.2%) below the poverty line (less than 3,565 USD per annum).

Measurement model

The reliability and validity measures in Table 2 demonstrate a high level of internal consistency and construct validity for all the variables, with Cronbach’s alpha values for all the constructs above 0.70, with most values exceeding 0.90, indicating high internal reliability, and the composite reliability scores for all the constructs also surpass 0.90, confirming the reliability of the construct (cut-off of 0.7 for both; McNeish, 2018). Internal consistency is also measured through Rho_A values, which in this research range from 0.79--0.96, demonstrating a high to very high level of acceptability (cut-off=0.7; Trejo et al., 2024). The factor loadings were well above 0.70 ( Table 2 and Figure 2), suggesting that each item strongly represents its respective construct (cut-off=0.7; Kamranfar et al., 2023). The average variance extracted (AVE) values were significantly greater, indicating that the variance captured by the construct’s items was sufficiently high, with minimal error (cut-off=0.5; Cheung et al., 2024).

Figure 2. Structural model.

Table 3 demonstrates discriminant validity, which confirms that each construct is distinct from rest of the constructs. The square roots of the AVE values (shown on the diagonal in bold) for each construct are all greater than the correlations with other constructs, indicating adequate discriminant validity. This pattern across all the constructs confirms that each construct in the model uniquely measures its intended concept, supporting the robustness of the measurement model. Thus, the indices in the measurement model confirm that the reliability and validity of the data and the questionnaire, respectively, are acceptable and that the data may be subjected to structural model analysis for hypothesis testing.

Figure 2 depicts path coefficients. This is the strength and direction of the relationships between the constructs in the model. Age-friendly urban design policies has a strong positive influence on aesthetics, with a path coefficient of 0.82, indicating that improvements in age-friendly urban design policies likely enhance perceptions of aesthetics. On the other hand, community engagement programs shows weak and negative associations with aesthetics (-0.09), comfort (-0.21), and convenience (-0.10), indicating that these programs may not effectively support perceptions of aesthetics, comfort, or convenience. Aesthetics positively impacts increased socialization, with a coefficient of 0.59, and increased physical activity level, with a coefficient of 0.43, indicating that safety perceptions are influential in promoting socialization and physical activity. Finally, convenience has a notably strong positive relationship with improved quality of life (0.70), suggesting that convenience is critical in enhancing the quality of life for older adults in this model.

Structural model

Table 4 shows that age-friendly urban design policies has a positive significant relationship with aesthetics (t=2.72; p=0.01), comfort (t=5.87; p=0.00), and convenience (t=4.62, p=0.00); aesthetics has a positive significant relationship with increased physical activity level (t=2.45; p=0.01) and increased socialization (p=2.93; t=0.00); comfort has a positive significant relationship with increased physical activity level (t=3.56; t=0.00); and convenience has a positive significant relationship with improved quality of life (t=2.70; p=0.01). Thus, the following hypotheses are supported ( Table 4, Figure 3):

Figure 3. Structural model.

The rest of the hypotheses are unsupported.

Practical implications

The practical implications of this research are for policy makers and urban designers in the form of suggestions to encourage the walkability of older adults. The specific implications are as follows.