Long-Term Exposure to Residential Greenness and Neurodegenerative Disease Mortality Among the Elderly: A 13-Year Follow-Up Cohort Study

doi:10.21203/rs.3.rs-1324929/v1

Background

Living in greener areas is associated with slower cognitive decline and reduced dementia risk among the elderly, but the evidence with neurodegenerative disease mortality is scarce. We studied the association between residential surrounding greenness and neurodegenerative disease mortality in an elderly population.

Methods

We used data from the 2001 Belgian census linked to mortality register data during 2001-2014. We included individuals aged 60 years or older and residing in the five largest Belgian urban areas at baseline (2001). Exposure to residential surrounding greenness was assessed using the Normalized Difference Vegetation Index (NDVI) within 500-m from residence. We considered all neurodegenerative diseases and four specific outcomes: Alzheimer’s disease, vascular dementia, unspecified dementia, and Parkinson’s disease. We fitted Cox proportional hazard models to obtain hazard ratios (HR) and 95% confidence intervals (CI) of the associations between one interquartile range (IQR) increment in surrounding greenness and neurodegenerative disease mortality outcomes. Furthermore, we conducted mediation analyses to assess potential mediation by air pollution (PM_2.5), and stratification analyses to explore effect modification by sociodemographic characteristics.

Results

From 1,134,502 individuals included at baseline, 6.1% died from neurodegenerative diseases during follow-up. After full adjustment, one IQR (0.22) increment of surrounding greenness was associated with a 4-5% reduction in premature mortality from neurodegenerative diseases, Alzheimer’s disease, vascular and unspecified dementia [e.g., for Alzheimer’s disease mortality: HR 0.95 (95%CI: 0.93, 0.98)]. No association was found with Parkinson’s disease mortality. Reductions in air pollution concentrations could potentially mediate 58% (95%CI: 31.7%, 95.7%) of the observed effect with all neurodegenerative disease mortality. Associations were strongest in the lower educated and residents from most deprived neighbourhoods.

Conclusions

Living near greener spaces may reduce the risk of neurodegenerative disease mortality among the elderly, partly mediated by a reduction in air pollution concentrations. Socioeconomically disadvantaged groups may experience the greatest beneficial effect.

Greenness

Mortality

Neurodegenerative disease

Dementia

Air pollution

Long-term exposure

Worldwide, the population is ageing, driving a dramatic increase in the burden of neurodegenerative diseases [1]. Moreover, population ageing is occurring faster in urban areas [2], which could contribute to an exacerbated risk of neurodegenerative diseases following exposure to urban environmental hazards [3–5].

Exposure to green spaces may benefit urban dwellers by promoting healthy ageing [6] and reducing premature mortality [7]. Hypothesized mechanisms include inducing stress restoration, providing opportunities for physical activity and social cohesion, and mitigating environmental hazards [8]. However, the available evidence on the association between green spaces and neurodegenerative diseases among the elderly is mixed and inconclusive, and studies have so far primarily focused on dementia or its precursor, cognitive decline [9, 10, 19–21, 11–18]. As far as we are aware, only one ecological and three longitudinal studies investigated the relationship between exposure to green spaces and neurodegenerative disease mortality: two longitudinal studies reported no association [22, 23], while the other two observed a beneficial association [24, 25]. Of these, only two further used a specific outcome of neurodegenerative disease mortality, namely, dementia mortality [23, 24].

Among the suggested mechanisms underlying the beneficial effects of green spaces, mitigation of ambient air pollution may be important for neurodegenerative diseases, as it is estimated to account for 4% of the total risk of dementia in later life [26]. Still, the effect of air pollution on other neurodegenerative diseases remains unclear [27, 28].

Finally, the health-related effect of green spaces could differ across social strata, as individual and neighbourhood social factors may influence exposure and susceptibility to residential green spaces [29, 30]. However, this has been scarcely addressed in relation to neurodegenerative diseases [13, 18].

In this study we examined the association between long-term exposure to green spaces and general and specific neurodegenerative disease mortality among the elderly (aged 60 years and older) residing in the five largest Belgian urban areas. Additionally, we assessed mediation by air pollution, and effect modification by social factors (gender and individual and neighbourhood socioeconomic position) in the studied associations.

Study design and study population

We used a longitudinal dataset based on a linkage between the 2001 Belgian census (baseline) and register data on emigration and mortality for the follow-up period from October 1, 2001, until December 31, 2014. Furthermore, environmental data (i.e., green spaces and air pollution) were linked to this dataset using the residential address of each person at baseline. Our study population included all non-institutionalized individuals aged 60 years and older, and officially residing in one of the five largest Belgian urban areas (Antwerp, Ghent, Brussels, Charleroi, and Liège). These areas were identified following the definition of urban area provided by Statistics Belgium (in Dutch: stadsgewest), consisting of the city and its respective commuting zone [31]. We included individuals with complete data on the residential address (observations excluded: n=11,824; 1.03%).

Neurodegenerative disease mortality

Mortality data included the causes of death issued from the death certificates, using the codes from the 10th revision of the International Classification of Disease (ICD-10) [32]. We defined several outcomes of neurodegenerative disease mortality according to previous literature [23, 33]. We considered deaths from all neurodegenerative diseases [including dementia (ICD-10: F00-F03); motor-neuron disease (ICD-10: G12.2); Parkinson’s disease (ICD-10: G20-G22); Alzheimer’s disease (ICD-10: G30); other neurodegenerative diseases of the nervous system, not elsewhere classified (ICD-10: G31); and multiple sclerosis (ICD-10: G35)] and four specific outcomes: Alzheimer’s disease (AD) (G30); vascular dementia (F01); unspecified dementia (F03); and Parkinson’s disease (PD) (G20-G22). Neurodegenerative diseases are often under-reported in death certificates [34, 35]. We therefore included all death certificates with any mention to the abovementioned outcomes (as an underlying, immediate, intermediate, or additional cause of death).

Residential surrounding greenness

Surrounding greenness around the residential address at baseline was measured using the Normalized Difference Vegetation Index (NDVI). A detailed description of the methodology used for the obtention of the indicator, as well as on the individual assignment of the exposure can be found in Bauwelinck et al. (2021). In brief, this metric captures vegetation density and is derived by applying the ratio between visible and near-infrared light bands to atmospherically corrected satellite images [37]. These were obtained for the 2006 summer period, with a 30 m resolution. Negative NDVI values representing water surfaces were set to zero prior to the calculation of the residential surrounding greenness indicator [36]. The index therefore ranged from 0 to 1, corresponding to no green and maximum green density, respectively. We calculated the average index of surrounding greenness in three circular buffers at Euclidean distances of 300-m, 500-m, and 1,000-m from the residence.

Ambient air pollution

We considered air pollution as a potential mediator in the associations between residential surrounding greenness and neurodegenerative disease mortality. Data was obtained from the Belgian Interregional Environmental Agency (IRCEL-CELINE) (www.irceline.be). Air pollutant concentrations are constantly measured through a vast network of monitoring stations and then used in spatial-temporal (kriging) interpolation models. These data are further combined with Gaussian models including traffic and industrial sources and meteorological data to estimate air pollutant concentrations at high spatial resolution (25 m) in the whole Belgian territory [38, 39]. We used 2005 annual average concentrations (µg/m³) of fine particulate matter (PM_2.5).

Sociodemographic and socioeconomic characteristics

Sociodemographic and socioeconomic characteristics at baseline were obtained from the 2001 Belgian census. Sociodemographic covariates included age [both as a continuous and with a 5-year categorization, from [60-65) until [95 and older)], gender, migrant background origin [Belgium, other high-income country (HIC), and low and middle-income country (LMIC)] and household living arrangement [cohabiting, single and other (e.g., multigenerational households)]. Individual socioeconomic position (SEP) was measured through attained educational level (tertiary, higher secondary, lower secondary, and lower and no education) and housing tenure (owner and tenant). Neighbourhood SEP was approximated using the median net taxable household income for the year 2005 at the level of the census tract (i.e., due to privacy reasons, the smallest geographical unit for which residential address is reported, comparable to neighbourhoods), available at Statistics Belgium (https://statbel.fgov.be/en), and unemployment rate in the census tract derived from the 2001 Belgian census.

Statistical analyses

We conducted multiple imputation to minimize potential selection bias introduced by missing information on any of the variables, observed in 19.6% of the study population. We used chained equations, carrying out 25 imputations with 10 iterations that generated 25 datasets. All the covariates were used in the process of multiple imputation. We further included as a predictor in the imputation process the Nelson-Aalen estimator of the cumulative hazard to the survival time for all neurodegenerative diseases [40].

We examined Spearman correlations between surrounding greenness, PM_2.5, and neighbourhood SEP. We specified Cox proportional hazards models using age as underlying time scale. Hazard Ratios (HR) and corresponding 95% confidence intervals (95% CI) of the associations between residential surrounding greenness and neurodegenerative disease mortality. We a priori selected a 500-m buffer from residence for surrounding greenness, following the methodology used in previous studies [36, 41]. Observations were censored when the person died from other causes, emigrated from Belgium or end of the follow-up occurred. We included strata terms for each 5-year categorized age group and gender. We additionally specified a frailty term to account for the cluster effects of residing in one of the five largest urban areas. Our main model was built adjusting stepwise by covariates: Model 1 (M1) included the baseline hazard with the strata and the frailty terms; Model 2 (M2) was further adjusted by migrant background, household living arrangement, educational level, and housing tenure; and Model 3 (M3) added the median household income of the census tract of residence. The reported HRs were combined from the estimates obtained from the 25 imputed datasets according to Rubin’s rules [42]. To examine the linearity of the exposure-response relationship with surrounding greenness, we randomly selected one of the 25 imputed datasets and fitted natural splines with three degrees of freedom. We compared the improvement of goodness of fit with a likelihood ratio test (LRT) to the main model (M3). Only slight deviations from linearity were observed (Figure S1), hence we included surrounding greenness as a linear term into our models. Mortality associations were reported by one interquartile range (IQR) increment in surrounding greenness.

In additional analyses we investigated the role of air pollution in the studied associations [43]. We firstly further adjusted our main models (M3) for PM_2.5 concentrations. Next, we evaluated potential mediation by PM_2.5 in the associations between surrounding greenness and neurodegenerative disease mortality outcomes that were significant in our main models. We used the package mediation [44] in R statistical software to obtain the average causal mediation effects (ACME), also known as indirect effects, and the average direct effects (ADE) in each imputed dataset (n=25). This allows to calculate the proportion of the total effect mediated by air pollution dividing the ACME by the total effect [ACME/(ACME + ADE)]. Here it can be interpreted as the proportion of risk reduction of neurodegenerative disease mortality after exposure to surrounding greenness explained by a reduction in PM_2.5 concentrations [45]. We computed the average of the estimates and the corresponding 95% Quasi Bayesian confidence intervals (95%CI), based on 1,000 Monte Carlo simulations, obtained from the 25 imputed datasets.

To determine if the observed effect in our main models was modified by sociodemographic characteristics, we stratified our models by gender, educational level, and neighbourhood SEP (by quartiles of the median net taxable income in the census tract of residence).

Finally, to assess the robustness of our main models, we conducted several sensitivity analyses of our main models: (1) using surrounding greenness within 500-m categorized into quintiles; (2) using the 300-m and 1,000-m buffer sizes of residential surrounding greenness; (3) using perceived neighbourhood greenness as an alternative indicator of exposure to green spaces, following the methodology from a previous study [30]; (4) adjusting the main models for the unemployment rate in the census tract as an alternative indicator of neighbourhood SEP; (5) limiting our analyses to specific population groups: (a) the complete case population (i.e., individuals with no missing data on the covariates); (b) non-movers, i.e., individuals who resided in the same census tract between 1991 and 2001 (10 years prior to baseline); (c) individuals originating from Belgium; (d) individuals younger than 80 years old at baseline; and (e) individuals residing in the city, leaving out commuting zone residents.

All statistical analyses were conducted in R/4.0 [46], using the packages mice [47], survival [48], splines [46] and ggplot2 [49] and dependencies.

Our total (imputed) study population consisted of 1,134,502 individuals aged 60 years or older and residing in the five largest Belgian urban areas in 2001 (Table 1). During follow-up (2001-2014), 69,149 individuals (6.1%) died from neurodegenerative diseases as any cause of death, 21,039 (1.9%) died from Alzheimer’s disease (AD), and 31,302 (2.8%) died from unspecified dementia. Fewer individuals died from vascular dementia or Parkinson’s disease (PD) (0.5% and 0.9%, respectively). The average age at baseline was 72 years (SD ± 7.7). The population was mainly composed by women, residents originating from Belgium, individuals with primary or no formal education, and cohabiting with their partner. The median exposure to residential surrounding greenness (buffer size: 500-m) was 0.61 (IQR: 0.22). In the complete case population (n=911,648), deaths from these diseases were slightly lower (e.g., death from all neurodegenerative diseases: n=52,780, 5.8%), while environmental exposures were similar. A detailed description of all environmental variables in both populations is shown in Table S1.

Table 1

Neurodegenerative disease mortality (2001-2014) and baseline characteristics in the full imputed and complete case population.
	Full (imputed) population (n=1134502)	Complete case population (n=911648)
Neurodegenerative disease mortality, n (%)
All neurodegenerative diseases	69149 (6.10)	52780 (5.79)
Alzheimer's disease	21039 (1.85)	16161 (1.77)
Vascular dementia	5651 (0.50)	4204 (0.46)
Unspecified dementia	31302 (2.76)	23570 (2.59)
Parkinson's disease	10054 (0.89)	7932 (0.87)
Age at baseline, mean ± SD	71.8 ± 7.7	71.5 ± 7.6
Women, n (%)	644687 (56.8)	514121 (56.4)
Migrant background, n (%)
Belgian	1001938 (88.3)	813136 (89.2)
Other HIC	94811 (8.4)	70497 (7.7)
LMIC	37753 (3.3)	28015 (3.1)
Educational level, n (%)
Tertiary	143927 (12.7)	118543 (13.0)
Higher Secondary	182750 (16.1)	150398 (16.5)
Lower Secondary	299778 (26.4)	242632 (26.6)
Low/Primary	508047 (44.8)	400075 (43.9)
Housing tenure, n (%)
Owner	859624 (75.8)	700281 (76.8)
Tenant	274878 (24.2)	211367 (23.2)
Household living arrangement, n (%)
Cohabiting	715546 (63.1)	591646 (64.9)
Single	389895 (34.4)	298746 (32.8)
Other	29061 (2.6)	21256 (2.3)
Median net taxable income (€), median (IQR)	19094 (4,620)	19206 (4,530)
Non-movers (1991-2001), n (%)	1003052 (88.4)	810682 (88.9)
Urban area, n (%)
Antwerp	248391 (21.9)	207726 (22.8)
Ghent	120809 (10.6)	101904 (11.2)
Brussels	505297 (44.5)	403091 (44.2)
Charleroi	104774 (9.2)	78782 (8.6)
Liège	155231 (13.7)	120145 (13.2)
Residential surrounding greenness (NDVI, 500-m), median (IQR)	0.61 (0.22)	0.61 (0.22)
Ambient air pollution [PM_2.5 (µg/m³)], median (IQR)	19.05 (2.09)	19.07 (2.09)
Note: SD, Standard Deviation; IQR, interquartile range; €, euro currency; NDVI, Normalized Difference Vegetation Index; PM_2.5, Particulate Matter with an aerodynamic diameter < 2.5 µm. Five largest Belgian urban areas, 2001-2014.

[Insert Table 1 (at the bottom of the file) here]

Spearman correlations are displayed in Figure S2. We observed moderate negative correlations between surrounding greenness and PM_2.5 concentrations (e.g., for surrounding greenness within 500-m: r=-0.58). Neighbourhood SEP (median income) was moderately correlated with surrounding greenness (r=0.50 for all buffer sizes), and weakly negatively correlated with air pollution (r=-0.23).

Surrounding greenness associations generally attenuated with increasing covariate adjustment in our stepwise models. Associations in fully adjusted models (M3) showed a reduction of 4% in the risk of all neurodegenerative disease mortality, and of 5% in the risk of AD, vascular dementia and unspecified dementia mortality (Figure 1 and Table S2). Contrarily, for PD mortality, we observed a non-significant, almost null association.

When further adjusting our main models for PM_2.5 concentrations (Table 2) we generally observed an attenuation in the association between surrounding greenness and all outcomes

of neurodegenerative disease mortality, although became null for unspecified dementia and strengthened for vascular dementia mortality. Results from the mediation analyses by PM_2.5 are reported in Table S3. Assuming that all statistical assumptions to conduct mediation were met [50], our findings suggest that the average proportion of the effect of surrounding greenness on neurodegenerative disease mortality mediated by PM_2.5 concentrations was 58.0% (95%CI: 31.7%, 95.7%). The same pattern for mediation results was observed for AD and unspecified dementia mortality, but not for vascular dementia mortality. Moreover, for these specific outcomes, none of the estimates for mediation were statistically significant.

Table 2

Associations (HRs) and 95%CI between surrounding greenness and neurodegenerative disease mortality after adjustment for PM_2.5.
	Neurodegene-rative disease mortality	Alzheimer's disease mortality	Vascular dementia mortality	Unspecified dementia mortality	Parkinson's disease mortality
	HR (95%CI)	HR (95%CI)	HR (95%CI)	HR (95%CI)	HR (95%CI)
Main model (M3)	0.96 (0.95, 0.97)	0.95 (0.93, 0.98)	0.95 (0.90, 1.00)	0.95 (0.93, 0.97)	1.01 (0.97, 1.05)
Main model (M3) + PM_2.5 (µg/m³)	0.98 (0.97, 1.00)	0.97 (0.93, 1.00)	0.93 (0.87, 0.99)	1.00 (0.97, 1.03)	0.99 (0.95, 1.04)
Abbreviations:HR, Hazard Ratio; 95%CI, 95% confidence intervals; PM_2.5 (µg/m³), particulate matter with an aerodynamic diameter <2.5µm, measured in micrograms per cubic metre. Five largest Belgian urban areas, 2001-2014. Cox regression models using age as the underlying time scale for the follow-up period October 1, 2001 - December 31, 2014. Main model (M3) stratified by gender and 5-year age groups, adjusted by migrant background, household living arrangement, educational level, housing tenure, median net taxable income at the level of the statistical sector, and including a frailty term for the urban areas.

The results of the stratified analyses by gender, educational level, and neighbourhood SEP are shown in Figure 2 and are fully reported in Table S4. We found almost no differences between men and women. We did not observe a clear pattern across educational levels. However, individuals with primary or no formal education showed consistently a stronger beneficial effect of surrounding greenness for all neurodegenerative disease, AD, and unspecified dementia mortality [e.g., for AD: HR 0.93 (95%CI: 0.90, 0.97)]. By neighbourhood SEP, we observed that for all neurodegenerative disease and unspecified dementia mortality the beneficial effect of surrounding greenness was strongest in individuals living in the most deprived (Q1 and Q2) neighbourhoods [e.g., for unspecified dementia: HR 0.93 (95%CI: 0.90, 0.96), HR 0.91 (95%CI: 0.88, 0.96); respectively]. Contrarily, for AD mortality this was observed in residents from the least deprived (Q4) neighbourhoods [HR 0.91 (95%CI: 0.84, 0.98)]. For vascular dementia mortality significant beneficial associations were observed in individuals residing in the second least deprived (Q3) and the most deprived (Q1) neighbourhoods.

The results of the sensitivity analyses were overall consistent with our main findings shown in Figure 1 (Table S5-S6). Using the surrounding greenness indicator categorized into quintiles we observed the strongest associations for all neurodegenerative outcomes (except PD) for the greenest quintile compared to the least green quintile. The results using different buffer sizes were very similar. Using perceived neighbourhood greenness as alternative exposure indicator yielded null associations with AD and vascular dementia mortality, whereas with unspecified dementia it was stronger (HR 0.93, 95%CI: 0.91, 0.94). The associations with AD mortality lost significance after alternatively adjusting for unemployment rate in the census tract; in contrast, the inverse associations with vascular and unspecified dementia mortality were stronger. Using the complete case population and including only the population groups aged 60-80 and living in the city centre generally attenuated the associations, yielding in some cases a borderline non-significant association. Limiting the analyses to non-movers and residents originating from Belgium strengthened the observed associations. Finally, we observed an inverse but non-significant association with PD mortality when excluding individuals living in the commuting zone (HR 0.96, 95%CI: 0.91, 1.02).

Our findings suggest that exposure to urban residential greenness reduces mortality from all neurodegenerative diseases, and specifically from Alzheimer’s disease (AD) and dementia. We found no significant associations with Parkinson’s disease (PD) mortality. The observed beneficial effects were potentially mediated by a reduction in air pollution concentrations. Moreover, we found that this protective effect was generally stronger in individuals with lower education. We also found the strongest beneficial associations for overall neurodegenerative diseases and unspecified dementia mortality in individuals residing in the most deprived neighbourhoods. In contrast, for AD mortality, the strongest beneficial association was observed in wealthier neighbourhoods.

Our results regarding reduced premature mortality from neurodegenerative diseases with increased surrounding greenness are comparable to those reported by Klompmaker et al. (2021) in a study over 10 million adults (aged ≥30 years). Using the same classification of neurodegenerative diseases, the authors observed a 2% reduction (per 0.14 increase) in neurodegenerative disease mortality with surrounding greenness. Stratified by age, results were similar in the elderly (≥65 years) [24]. An ecological study in Greece also found a significant inverse association (HR 0.91) between greenness and mortality from diseases of the nervous system (ICD-10 codes G00-G99) [25]. Two longitudinal studies found a protective but non-significant association with neurodegenerative disease mortality [22, 23]. James et al. (2016) included 108,630 elderly female nurses followed between 2000-2008, yielding an HR of 0.93 per 0.1 increase in surrounding greenness. Klompmaker et al. (2020) used survey data of 339,633 individuals linked with mortality data (2003-2007), and showed a similar effect estimate as Klompmaker et al. (2021), but with wider confidence intervals. Potentially these studies did not find significant associations because of an insufficient statistical power due to smaller study populations combined with shorter mortality follow-up periods.

Our study findings were consistent for different dementia subtypes. Two of the abovementioned studies additionally assessed dementia mortality (all dementia types, ICD-10 codes: F00-F03). Klompmaker et al. (2021) showed a significant 4% reduction in the risk of dementia mortality with increased surrounding greenness. Klompmaker et al. (2020) reported a similar but non-significant effect. Other longitudinal studies using health administrative databases found a beneficial association between green spaces and an outcome including all dementia types and AD (ICD-10 codes: F00-F03, G30, respectively) [16, 17]. However, studies evaluating the effect of green spaces on AD alone have shown contradictory findings [18–21]. Moreover, we are not aware of prior studies evaluating the association between green spaces and vascular dementia. Thus, further research is needed to confirm our results.

Suggested mechanisms underlying the direct beneficial effect of exposure to green spaces on neurodegenerative disease mortality include inducing psychological restoration and reducing stress [8], potentially preventing depression, a risk factor for dementia [51]. Additionally, there is suggestive evidence that green spaces could increase physical activity in the elderly [6], reducing the risk of dementia and AD [52]. Social isolation is moreover associated with an increased risk of cognitive decline and dementia [53], and greener neighbourhoods could enhance social cohesion and mitigate feelings of loneliness in older adults [54, 55]. Finally, green spaces could contribute to the mitigation of environmental hazards, including air pollution [56]. Our findings suggest that the associations between residential greenness and neurodegenerative disease mortality are partly mediated by a reduction in air pollution. We only reported results with PM_2.5. In alternative models with NO₂ (results not shown), we observed similar findings. So far, only one longitudinal study on green spaces and cognitive function explored potential mediation by air pollution, but no evidence of mediation effects was found [13]. Current evidence establishes a strong link between air pollution and AD and dementia [26]. The filtering effect of green spaces removing pollutants from the atmosphere has been proven to be generally small [57, 58]. However, green spaces could decrease temperature in cities [59], indirectly improving air quality by reducing the generation, transportation and toxicity of pollutants [60]. Likewise, fewer sources of air pollution are found in greener areas [43]. Noise pollution or proximity to roads have also been associated with an increased risk of dementia independently from air pollution levels [3, 4], but we unfortunately lacked such information.

As part of the sensitivity analyses, we used perceived neighbourhood greenness as alternative exposure indicator, where we found no association with AD nor vascular dementia mortality and a stronger association with unspecified dementia compared to the results of our main models using surrounding greenness. We suspect that perceived neighbourhood greenness may partly capture certain aspects of neighbourhood socioeconomic position (SEP). As such, this model may be overadjusted for SEP. Our findings are probably explained by individuals with high SEP having a higher likelihood of getting a record of dementia aetiology in death certificates [61], and, moreover, residing more often in areas where a higher proportion of individuals report very good neighbourhood greenspace provision.

No beneficial association between greenness and PD mortality was found, probably a result of the differing aetiology of PD compared to that of the other neurodegenerative diseases under study [62]. Additionally, in sensitivity analysis the associations with PD changed direction and became beneficial when commuting zone residents were excluded. Morphologically, these areas are characterized by an extensive land use in both housing and commercial activities [31]. Thus, we may speculate that increased risk of PD mortality could partly be explained by exposure to agricultural land, potentially encompassing exposure to pesticides, although this has been mainly explored for agricultural workers [62], being the evidence available for residential exposures currently limited [63]. Furthermore, we were not able to further explore this hypothesis since we lacked data on different types of green such as agricultural land.

Comparison between different population subgroups in the stratified analyses should be done with caution, given statistical restrictions in such interpretations. We observed strongest beneficial effects of living near greener areas in the lower educated for all neurodegenerative diseases and AD mortality. No clear patterns were found for other studied causes. Similarly, the longitudinal study of de Keijzer et al. (2018) did not find consistent evidence for differences between different education groups in the association with residential greenness and cognitive decline. Regarding neighbourhood SEP, we observed a general trend for all neurodegenerative disease and dementia mortality, where strongest associations with residential greenness were found in more socially deprived areas. The aforementioned study by de Keijzer et al. (2018) observed similar patterns with cognitive decline. Lower SEP has been linked to both poorer living conditions and limited access to resources which may be related to increased risk of cognitive decline in later life [64]. Additionally, availability of residential green has been associated to reduced risk of mortality, where health benefits seemed to be largest among most deprived population groups [65]. Such gradient was partly confirmed by our study results, although for AD mortality we found strongest beneficial associations in individuals residing in wealthier areas. This contradicts the findings from Brown et al. (2018), in which a trend by neighbourhood SEP in the association between greenness and AD prevalence was found, showing the strongest estimate in low-income neighbourhoods.

Our study comes with several limitations. The major limitation of our study is that we were not able to control for lifestyle factors, e.g., body mass index (BMI), smoking status and alcohol consumption, which are well-known risk factors for AD and dementia [26]. Prior studies that were able to account for these factors observed a small attenuation in the association [22, 23]. However, comparability of findings after such adjustment is challenging given several important differences in study design, population characteristics and exposure assessment. Hence, the direction of potential bias in our effect estimates remains unclear. Furthermore, our study did not include time-varying variables of exposure throughout the follow-up period. We only had one measure of surrounding greenness for the year 2006, close to the middle of the follow-up period, which is another limitation of our study. We assumed that, although the quantity of green spaces may vary across time, their spatial distribution remains relatively stable. However, no other exposure information was available for other years to test this. Moreover, exposure assessment was based on the geocoded residential address at baseline (2001), and we lacked information on residential mobility during follow-up (2001-2014). Still, we were able to limit the analyses to a group of residents who did not move in the last 10 years prior to baseline, which did not invalidate our main results. Surrounding greenness captured all types and sizes of green spaces, independently of these being private or public. Also, limiting greenspace exposure assessment to the residence may result in exposure misclassification, as it potentially ignores exposure in other life spheres, e.g., working place. Similarly, episodes of nature interaction were not measured in quality (e.g., accessibility, type of use) nor in time (e.g., frequency, duration). We also relied on baseline information of sociodemographic characteristics, but these may not vary considerably among the elderly population. Applied missing values techniques present limitations given that the missing values may not be completely at random, which potentially affects generalizability of our findings. However, by using two approaches to handle missing data (i.e., multiple imputation and listwise deletion), we may assume that main conclusions are fairly robust. Lastly, we excluded the institutionalized population (i.e., care homes) to minimise selection bias, given that almost half of individuals diagnosed with neurodegenerative diseases live in institutions [66].

Notwithstanding the limitations described, our study counts with an important number of strengths. We analysed the association between surrounding greenness and neurodegenerative diseases over a longer follow-up period (13.25 years) than prior studies [22–24]. We also relied on a high resolution environmental database, linked to the geocoded residential address of each individual officially residing in the five largest Belgian urban areas at baseline [36]. Our study was also the first to conduct mediation analyses in the studied associations by air pollution concentrations using individually linked exposure data. Finally, using large administrative data allowed us to study effect modification by gender and socioeconomic characteristics through stratification for representative subgroups.

In a large population-based cohort of elderly individuals, we observed a reduced risk of overall and specific neurodegenerative disease mortality (except for Parkinson’s disease) associated to exposure to residential surrounding greenness. We also found that these associations are potentially mediated by reductions in air pollution concentrations. Additionally, the beneficial effect of exposure to green spaces on neurodegenerative disease mortality might be stronger in lower educated groups and individuals residing in more deprived neighbourhoods. In Europe, neurological disorders represent the third leading cause of death and disability, after cardiovascular diseases and cancer [67]. Still, up to 40% of dementia cases can be potentially prevented (WHO 2021). Our results highlight the importance of the living environment to promote healthy ageing and reduce the burden of neurodegenerative diseases, especially among the most vulnerable populations. Future research is needed to confirm our findings in other settings and to explore other underlying mechanisms linking surrounding greenness with neurodegenerative diseases.

NDVI, Normalised Difference Vegetation Index; IQR, interquartile range; HR, hazard ratio; 95%CI, 95% confidence interval; PM_2.5, particulate matter with an aerodynamic matter smaller than 2.5µm; AD, Alzheimer’s disease; PD, Parkinson’s disease; SEP, socioeconomic position.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The data that support the findings of this study includes identifying information on participants and was used under license for the current study, and hence not publicly available. Data codebooks and syntaxes used for the statistical analyses are however available from the authors upon request.

Competing interests

The authors declare that they have no competing interests.

Funding

Lucía Rodríguez Loureiro is funded by the Brussels Institute for Research and Innovation (INNOVIRIS) [project number: 2019-ANTICIPATE-26100]. Mariska Bauwelinck is funded by an individual PhD grant supported by the Research Foundation-Flanders (FWO) [grant number 11A9718N].

Authors’ contributions

Lucía Rodríguez Loureiro: Conceptualization, Methodology, Formal Analysis, Visualization, Writing-Original Draft, Writing-Review & Editing; Sylvie Gadeyne: Conceptualization, Writing-Review & Editing, Supervision, Funding acquisition; Mariska Bauwelinck: Resources, Writing-Review & Editing; Wouter Lefebvre: Resources; Charlotte Vanpoucke: Resources; Lidia Casas: Conceptualization, Writing-Review & Editing, Supervision, Funding acquisition. All authors read and approved the final manuscript.

Acknowledgements

We would like to acknowledge the important role of Statbel in this study (Directorate-general Statistics – Statistics Belgium) for geocoding the census data and facilitating data linkages. We would also like to thank IRCEL-CELINE (Belgian Interregional Environment Agency) for providing the air pollution data. We furthermore thank Dr Tim Nawrot, from the University of Hasselt and the KULeuven, for his insightful comments of preliminary findings and useful suggestions for the development of the study objectives. The resources and services used in this work were provided by the VSC (Flemish Supercomputer Centre), funded by the Research Foundation – Flanders (FWO) and the Flemish Government.

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SupplementaryMaterial.docx

Long-Term Exposure to Residential Greenness and Neurodegenerative Disease Mortality Among the Elderly: A 13-Year Follow-Up Cohort Study

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Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Study design and study population

Neurodegenerative disease mortality

Residential surrounding greenness

Ambient air pollution

Sociodemographic and socioeconomic characteristics

Statistical analyses

Results

Discussion

Conclusions

List Of Abbreviations

Declarations

References

Supplementary Files

Status:

Version 1