1. Introduction
A key sustainable development goal [
1] is developing supportive communities that foster health and wellbeing [
2]. In line with this, there has been increasing interest in understanding how the built environment can impact wellbeing [
3]; recently established cross-disciplinary research agendas, such as Neuro-Urbanism [
4] and Community Gerontology [
5], have proposed to look more closely at the psychological and cognitive impact of the lived environment, particularly, the neighbourhood [
6,
7,
8,
9], as the most proximal form of environmental exposure outside the house [
7]. Within these frameworks, there are growing calls for the promotion of neighbourhood liveability through the design of environments that are cognitive-friendly [
8,
10] and that foster neurodiversity [
11]. Theoretical models that link the neighbourhood environment to cognition propose two main possible pathways, one indirect and one direct [
8,
9]: Characteristics of the community can have an indirect influence on cognition and mental health by providing or limiting opportunities for a physically and socially active lifestyle, which in turn can have a knock on effect on cognitive wellbeing via cardiovascular health and social stimulation [
6,
9]. However, recent research has shown an interest in the possibility that the physical or ‘contextual’ environment may act as a direct source of cognitive stimulation based on the perceptual and cognitive complexity presented, and, thus, on the demands posed on cognitive skills [
7,
8]. Considering the direct pathway, it is suggested that environments which are under-stimulating (e.g., rural areas) or over-stimulating (urban areas) from a cognitive point of view may be detrimental for cognitive wellbeing [
8,
12]. A wealth of research using either objective or subjective measures of the environment has demonstrated that physical aspects of the built environment (e.g., walkability) can have an indirect impact on mental health and cognition [
13] by influencing lifestyle [
14,
15,
16]; however, in order to clarify what makes an environment ‘cognitive-friendly’, a crucial step is to understand how the sociophysical components of the neighbourhood can influence the cognitive wellbeing of an individual based on the level of perceptual and mental stimulation afforded [
8,
12,
17]. A small number of experimental studies that looked at the direct impact of the physical environment on brain processing using wearable electroencephalography integrated with qualitative accounts of subjective experiences with older and younger individuals show brain activity associated with relaxation when sitting/walking in urban areas characterised by the presence of green, quietness, or in familiar places [
18,
19,
20,
21]. However, these studies do not take into account the potential influence of individual-level or contextual factors. In the present study, we investigated whether neighbourhood characteristics are associated with cognitive characteristics of the individual and with their sensory sensitivity, and whether age and levels of urbanity moderate this association.
Individual characteristics such as sensory sensitivity can modify the restorative effects of green spaces on cognition [
22], suggesting that individual differences in cognitive and sensory processing may influence a person’s interaction with outdoor spaces. In line with this, in a recent study with older adults, we observed a negative association between sensory/cognitive sensitivity and preferences for walking in crowded outdoor spaces in individuals living in very rural or very urbanised places, but not in areas with intermediate levels of urbanity [
17].
Understanding which demographic groups are the most cognitively vulnerable and what environmental characteristics are associated with such vulnerability is thus important to identify how communities can sustain good cognitive health and design environmental interventions or transformations.
A recent systematic review [
6] pointed at the need to study potential individual-level moderators, such as age, to better understand the associations between neighbourhood environment and cognition. The cognitive impact of neighbourhood design has been investigated extensively in relation to vulnerable populations such as individuals with dementia [
10,
23,
24], but there is limited evidence of whether the association between neighbourhood characteristics and cognitive wellbeing varies across the lifespan [
25]. We know from existing research that availability of resources or infrastructure (e.g., walkability) in the neighbourhood which promote active lifestyles and social integration provide a mental boost for both younger and older groups [
26,
27,
28,
29]. However, at the neighbourhood level, the role of the physical environment is underexplored, and it is not known whether cognitive benefits are associated with the proximal environment of residence in younger and older people. Presumably older adults live longer in their neighbourhood; therefore, one may argue for an accumulation effect whereby the impact of the neighbourhood design on cognition could be observed more strongly for older rather than younger individuals [
9,
12]. Thus, a question that needs investigation is whether neighbourhood characteristics are cognitively relevant for older people only, or whether we can observe an association in younger cohorts also.
Considering the contextual level of influence, epidemiological studies have demonstrated urban–rural variations in cognitive health in older populations [
9,
30], suggesting a direct impact of the contextual aspects of the lived environment on perception and cognitive outcomes [
7]. Considering younger groups, natural settings, as opposed to urban places, appear to benefit cognition, especially in terms of attentional functioning [
22,
31,
32]. However, inconsistencies in the positive impact of nature across the lifespan have been observed [
31], and the same may hold true for urban environments. This poses the question of whether levels of urbanisation moderate the association between neighbourhood characteristics and cognition; addressing such question would enable us to pinpoint where environmental interventions are most needed.
The present study aimed to advance our understanding of the association between subjective perceptions of the neighbourhood environment and cognitive, as well as sensory, vulnerability with the ultimate goal to identify which age groups in which residential areas are most in need of urban design interventions to improve cognitive wellbeing. To this end, we investigated two research questions:
3. Results
3.1. Sample Characteristics
In this sample, participants reported an average Cognitive Failures score of 33.57 (SD = 13.41) on a range from 0 to 100, and an average Sensory Sensitivity level of 19.80 (SD = 5.92) on a range 7–35. Neighbourhood overall quality had a mean of 4.00 (SD = 0.81, range 1–5) and neighbourhood streetscape had a mean of 3.31 (SD = 1.21, range = 1–5). Age groups were organised as follows: n = 73 (33.95%) in the youngest group, n = 73 (33.95%) in the middle-aged group, and n = 69 (32.09) in the older group. Over a third of respondents (38.3%) reported living in city suburbs, followed by 28.8% in the countryside, 13.5% in villages, 13.1% in inner city, and 10.8% in towns. Overall, the sample was highly educated, with 136 (61.3%) participants reporting third or higher level of education; participants reported overall very good health (median = 4.00, IQR = 1.00). Most participants reported having friends or family in their neighbourhood (85.3%). In terms of duration of residence, 40% of participants reported to have lived in their current neighbourhood of residence for more than 20 years, 24% between 10 and 20 years, 7% between 5 and 10 years, 16% between 1 and 5 years, and 13% less than one year.
3.2. Bivariate Analyses
Spearman’s correlations (
Table 1) showed that there were no significant associations between either measure of neighbourhood environment and any measure of cognitive vulnerability or health. On the other hand, cognitive failures and sensory sensitivity were positively correlated with each other (
rho = 0.29,
p < 0.001). A statistically significant negative correlation between levels of urbanity and neighbourhood pleasantness (
rho = −0.46,
p < 0.001) indicated that participants in more urbanised areas provided poorer ratings of neighbourhood pleasantness; on the contrary, increased levels of urbanity had a moderate positive correlation with ratings of streetscape quality (
rho = 0.41,
p < 0.001). No associations between urbanity and the two measures of cognitive vulnerability were observed.
Comparisons by age group are presented in
Table 2. These showed that, while the three age groups did not differ significantly in terms of cognitive vulnerability or neighbourhood streetscape, ratings of neighbourhood pleasantness were significantly more negative in the youngest group, although the differences were of small size. Notably, there were significantly more people in the younger than the other two age groups residing in the inner city and, conversely, significantly more older people in the countryside, although in all three age groups, over a third of respondents lived in city suburbs.
The three age groups did not differ significantly in terms of gender (chi2(4) = 4.62, p = 0.33) or health status (chi2(8) = 14.27, p = 0.07), but younger people were more likely to have higher levels of educational attainment than people in the middle-aged or older groups (chi2(4) = 54.24, p < 0.001, Cramer’s V = 0.35), while older people were more likely than younger groups to have lived in their neighbourhood for longer (chi2(8) = 82.99, p < 0.001, Cramer’s V = 0.44) and to report a larger social network (chi2(4) = 27.56, p < 0.001, Cramer’s V = 0.26).
Considering levels of urbanity, we found no statistically significant variations in Cognitive Failures (Kruskal–Wallis H(4) = 2.38, p = 0.66) or Sensory Sensitivity (Kruskal–Wallis H(4) = 1.89, p = 0.75), but significant differences were observed for both measures of neighbourhood environment: Neighbourhood pleasantness was rated higher in less urbanised areas (Kruskal–Wallis H(4) = 46.15, p < 0.001), whereas neighbourhood streetscape received more positive ratings in more urbanised areas (Kruskal–Wallis H(4) = 79.07, p < 0.001). In terms of covariates, there were no significant variations by level of urbanity for gender (chi2(4) = 4.63, p = 0.33), health status (chi2(16) = 10.13, p = 0.86), or education (chi2(8) = 7.08, p = 0.53); however, people in towns were more likely than other groups to have both family and friends living in their neighbourhood (chi2(8) = 18.27, p = 0.02, Cramer’s V = 0.29).
3.3. Interactions of Neighbourhood Environment, Age, and Urbanity
Negative binomial regression analyses were carried out separately for cognitive failures and sensory sensitivity, each with two separate models including either neighbourhood pleasantness or streetscape (given the absence of correlation between the two measures). The tables with the results of the regressions are presented in
Supplementary File 1 (Tables S1–S4). Here, we present the main findings on the interactions.
3.3.1. Cognitive Failures
For cognitive failures (CFQ), when using neighbourhood pleasantness as a predictor and controlling for all covariates, a statistically significant three-way interaction was observed with age and urbanity level,
chi2(8) = 21.51,
p = 0.006. As presented in
Figure 1, when compared with younger people, older people showed different patterns of cognitive failures based on where they lived and their ratings of neighbourhood qualities: Older people in the countryside or inner city reported lower cognitive failures with increasing ratings of neighbourhood pleasantness, whereas those in intermediate levels of urbanity showed a negligent amount of variation in cognitive vulnerability associated with ratings of neighbourhood pleasantness (using countryside as the reference, older people in villages
IRR = 14.48,
p < 0.001, towns
IRR = 2.85,
p = 0.09, city suburbs
IRR = 3.47,
p = 0.008, inner city
IRR = 1.62,
p = 0.36). A similar pattern, although of smaller size, was seen for middle-aged participants (villages
IRR = 3.98,
p = 0.008, towns
IRR = 1.38,
p = 0.45, city suburbs
IRR = 2.23,
p = 0.03, inner city
IRR = 0.03,
p = 0.05).
When looking at the effect of neighbourhood streetscape on cognitive failures controlling for covariates, the three-way interaction was not significant (chi2(8) = 13.62, p = 0.09), and two-way interactions did not reach the significance threshold. A statistically significant effect of age was found (chi2(2) =12.83, p = 0.002), whereby, compared to the young group, statistically significant lower rates of sensory sensitivity were observed in the middle-aged group (IRR = 0.51, p = 0.01) and to a larger extent, in the older group (IRR = 0.25, p = 0.001).
3.3.2. Sensory Sensitivity
For sensory sensitivity, when controlling for all covariates, no significant interactions or main effects were noted when considering neighbourhood pleasantness. When using neighbourhood streetscape as a predictor, we observed no statistically significant interactions or main effects (see
Supplementary File 1).
3.4. Subsample Analysis of Qualitative Ratings
A total of 142 participants (63.39% of the total sample) indicated in the survey the aspect of their neighbourhood that they liked the most and the one they liked the least. The age distribution of the subsample was: n = 72 (51.43%) in the young group, n = 51 (36.43%) in the middle-aged group, n = 17 (12.14%) in the older group. The distribution of urbanity was as follows: n = 24 (16.90%) in the countryside, n = 20 (14.08%) in villages, n = 23 (16.20%) in towns, n = 51 (35.92%) in city suburbs, and n = 24 (16.90%) in inner city. A distribution of positive and negative neighbourhood ratings is presented in
Table 3. Over a third of participants (36.62%) named an element related to accessibility when asked about the thing they liked the most about their neighbourhood; these included close distance to services or amenities, as well as public transport. This was followed by social aspects (sense of community, friends living nearby), rated as positive by 22.54% of the sample, and by absence of perceptual stressors (particularly quietness and absence of traffic) mentioned by 18.31% of respondents. Road lighting was mentioned as a positive aspect only by two participants. The two observations were excluded from subsequent bivariate analyses.
On the other hand, 31.78% of people mentioned perceptual stressors (such as noise or traffic) as a negative aspect of their neighbourhood, followed by accessibility issues (18.60%, lack of transport or easy access to services or amenities) and issues with pleasantness (17.83%, lack of scenery or litter).
There were no statistically significant age-related variations either for positive ratings (chi2(8) = 14.47, p = 0.07), although older people (47.06%) valued social aspects of their neighbourhood (sense of community, positive relationships), whereas the majority of middle-aged and young respondents (respectively, 32.65% and 44.44%) valued mainly accessibility aspects of their local area (access to work, services, or amenities). No statistically significant age-related variations were found for negative ratings (chi2(10) = 6.28, p = 0.79).
Statistically significant associations were observed between neighbourhood ratings and urbanity levels (positive ratings:
chi2(16) = 53.34,
p < 0.001; negative ratings:
chi2(20) = 31.86,
p = 0.05). As it can be seen in
Figure 2, accessibility was rated as a strong positive aspect in urbanised areas, but as a negative aspect in less urbanised areas; on the other hand, perceptual stressors such as noise and traffic constituted positive aspects of more rural places and negative aspects of urban areas.
There were no statistically significant associations between neighbourhood ratings and either cognitive failures (positive ratings: Kruskal–Wallis H(4) = 5.06, p = 0.28; negative ratings: Kruskal–Wallis H(5) = 1.69, p = 0.89) or sensory sensitivity (positive ratings: Kruskal–Wallis H(4) = 2.61, p = 0.63; negative ratings: Kruskal–Wallis H(5) = 0.97, p = 0.96). No interaction analyses were carried out for these ratings, as they would be underpowered by the limited number of observations in each subcategory.
4. Discussion
In this cross-sectional study, we aimed to test associations between perceived qualities of the neighbourhood of residence (pleasantness and streetscape) and measures of cognitive vulnerability in a sample of community-dwelling adults, looking at the potential moderation of age and level of urbanity of the place of residence.
We observed no statistically significant independent associations of neighbourhood pleasantness or streetscape with either measure of cognitive vulnerability. Similarly, our subsample analysis found no associations between positive or negative ratings of neighbourhood characteristics and cognitive measures. However, when looking at interactions controlling for demographic, social, and residential covariates, the association between cognitive failures (but not sensory sensitivity) with neighbourhood pleasantness (but not with neighbourhood streetscape) varied significantly based on age and urbanity level. For the oldest group in our sample (when compared to the youngest group), and to a smaller extent middle-aged people, those living in the countryside or in inner city areas were more likely to report lower rates of cognitive failures if rating their neighbourhood as more pleasant, whereas this variation was not observed in older people residing in areas with intermediate levels of urbanisation. Bivariate analyses revealed that overall, participants living in more urbanised areas rated their neighbourhood as less pleasant than those living in more rural areas; also, younger respondents in this study, who were more likely to live in the most urbanised areas, rated their neighbourhoods as less pleasant than middle-aged or older people; however, older people and, to a smaller extent, middle-aged people in the countryside and inner city had a similar pattern of decreased cognitive vulnerability with increasing neighbourhood pleasantness. This could indicate that neighbourhood characteristics may not determine wellbeing outcomes equally depending on where a person lives, with the most rural and most urbanised areas potentially making a person more susceptible to the perceived levels of neighbourhood safety, cleanliness, aesthetics, noise, or crowding. While the absence of overall age-related variations in cognitive vulnerability, particularly cognitive failures, resonates with the evidence outlined in a recent systematic review of healthy populations [
43], these findings support the idea that both age and urbanity levels contribute to influence the association between neighbourhood quality and cognitive vulnerability, revealing for this sample that neighbourhood pleasantness (i.e., how safe, clean, aesthetically appealing and quiet the area of residence is perceived) can contribute to lower rates of cognitive failures, particularly in older people who live in the most rural or urbanised areas. This finding is in line with evidence of interactions between the level of urbanity, neighbourhood perceptions, and quality of life in older people [
44], as well as age-related variations in the association between neighbourhood characteristics and wellbeing [
25]. Furthermore, as in our sample older people had lived significantly longer in the same neighbourhood compared to younger groups, our findings support the idea that neighbourhood characteristics may be particularly important to older people from a cognitive point of view because of a potential accumulation effect linked to living longer in the same place [
8]. However, the present study adds an understanding of these variations with regards to cognitive wellbeing and in a lifespan perspective, confirming a stronger effect in older people rather than younger groups; this gives context to our previous study (conducted on the older group only) where we found that, compared to older people living in areas with intermediate urbanity level, those residing in rural or very urbanised areas who were more cognitively vulnerable were also more selective of outdoor spaces for walking based on the amount of stimulation afforded [
17]. Interestingly, the present findings confirm growing epidemiological evidence of a nonlinear association between urbanity and cognitive health in older populations, especially when considering individual-level moderators [
6,
12,
45,
46]. Here, broad contextual factors such as urbanity level and neighbourhood-level characteristics seem to operate as two interacting factors for cognitive vulnerability; however, whether there is a cumulative cognitive load of the two (i.e., urbanity and neighbourhood pleasantness provide two different forms of cognitive load) remains to be established.
While we found moderating effects for neighbourhood pleasantness, neighbourhood streetscape was not associated with cognitive measures. It might be that streetscape characteristics were not relevant to our cognitive outcomes for this sample, although other studies have found significant links between street layout and cognitive health in older people [
24].
Lastly, in the subsample analysis, we gained further insights on variations in perceived neighbourhood qualities by age and urbanity level. Older people appeared to value more social aspects, whereas younger groups valued accessibility. Considering urbanity levels, the most frequently mentioned dimensions in both positive and negative ratings were accessibility (as a positive aspect of urban areas but negative in rural areas) and the presence/absence of stressors (a positive in rural areas but a negative aspect for urban dwellers). Previous studies have noted the importance attached by older people to social dimensions of their place of residence and outdoor places that they choose to use [
17,
47]; as social aspects were not investigated in our quantitative questions on neighbourhood characteristics, further investigation of this aspect is warranted. Overall, our findings on variations in accessibility across urban and rural neighbourhoods support the extensive literature on walkability [
48] and the negative impact of stressors on health has been demonstrated in urban studies [
49]. As these factors can act as mediators between environmental characteristics and cognitive wellbeing [
8], they further support the importance of thinking about environmental interventions in light of these contextual features such as urbanity level. As we observed no variations in these ratings across age groups, and we found no clear variations related to neighbourhood streetscape, which was used in this study as an index of potential hazards and accessibility in the neighbourhood, it is possible that these issues may be relevant to wellbeing independent of age. However, in this study, we found no links between these dimensions and cognitive measures; furthermore, these analyses were only exploratory, given the limited number of participants who provided qualitative ratings.
The present study is one of the few to use a lifespan perspective to look at associations between neighbourhood environment and cognitive wellbeing and combined quantitative and qualitative modes of data collection to gather richer insights on perceptions of neighbourhood characteristics. Nonetheless, the study is not without limitations: Firstly, our convenience sampling, recruitment methods, and self-reported measures mean that we cannot exclude selection bias (e.g., most of our participants were healthy and highly educated) as well as social desirability issues. While the cognitive impact of neighbourhood characteristics has increasingly been demonstrated using both objective and subjective data [
19], integrating subjective perceptions of neighbourhood characteristics with an objective assessment and gathering information on the use of the neighbourhood might have provided richer information on variability across neighbourhoods in our sample and enhanced our understanding of contextual factors associated with cognitive vulnerability. Similarly, self-reported measures of cognition should be integrated with an objective assessment of cognition. Furthermore, most participants did not identify geographically the location of their neighbourhoods, limiting our ability to fully capture potential variability across neighbourhoods. The items related to neighbourhood characteristics were informed by the literature and selected as the most relevant to tease out direct associations with cognitive measures [
9]. However, the qualitative ratings of neighbourhood characteristics, which were spontaneously provided by participants without prompt, generated aspects of the neighbourhood that had not been included in our quantitative questions (e.g., access to nature and social dimensions); thus, our indexes of neighbourhood pleasantness and streetscape are to be considered as a first attempt to identify cognitive-relevant neighbourhood dimensions, and need further development. We could not explore qualitative ratings interactions with urbanity and age in relation to cognitive measure due to the sample size, which could be addressed in a larger study. We did not include lifestyle measures in this study because the neighbourhood of residence could have an impact independent of how active a person is; however, a potential mediating effect cannot be excluded [
50]. The significant interaction observed for cognitive failures supports the study hypothesis that the association between neighbourhood characteristics and cognitive vulnerability is not the same for all individuals, but varies based on their age and their place of residence; however, we cannot rule out the possibility of a spurious finding given the absence of an independent association between neighbourhood pleasantness and cognitive vulnerability. The lack of an independent relationship may be due to the fact that this study included a healthy sample; thus, one recommendation would be to compare the association between cognitively healthy and clinical groups (e.g., older people with mild cognitive impairment). It is also possible that the relationship did not emerge given the medium effect size that we used for our sample calculations, thus warranting further study with a larger sample. Lastly, given the cross-sectional design of the study, we cannot reach conclusions of causality and cannot exclude potential reversed causality (i.e., cognitive characteristics influencing ratings of neighbourhood characteristics); notwithstanding this limitation, our findings point out an important association that deserves further investigation.
Overall, our study stimulates further research not only on the associations between specific neighbourhood characteristics and cognitive wellbeing, but also looking at individual and contextual level moderators. From a theoretical viewpoint, it provides evidence for a direct non-linear association between cognition, perception, and perceived neighbourhood quality, supporting the idea that a positive appraisal of the lived environment is associated with better cognition. This idea should be tested in future work. Our subsample analysis also suggests that elements of safety and social dimensions might be the most important aspects to capitalise upon in areas inhabited mainly by older people, whereas enhancing accessibility and reducing the presence of potential stressors could be applied based on level of urbanity rather than the age profile. Such research may inform more tailored and cost-effective environmental interventions that take into account comprehensively the demographic profile of the residents as well as broader contextual circumstances.