Perceived built environment, health-related quality of life and health care utilization.

Previous research has shown that the built environment plays a crucial role for health-related quality of life (HRQoL) and health care utilization. But, there is limited evidence on the independence of this association from lifestyle and social environment. The objective of this cross-sectional study was to investigate these associations, independent of the social environment, physical activity and body mass index (BMI). We used data from the third follow-up of the Swiss study on Air Pollution and Lung and Heart diseases In Adults (SAPALDIA), a population based cohort with associated biobank. Covariate adjusted multiple quantile and polytomous logistic regressions were performed to test associations of variables describing the perceived built environment with HRQoL and health care utilization. Higher HRQoL and less health care utilization were associated with less reported transportation noise annoyance. Higher HRQoL was also associated with greater satisfaction with the living environment and more perceived access to greenspaces. These results were independent of the social environment (living alone and social engagement) and lifestyle (physical activity level and BMI). This study provides further evidence that the built environment should be designed to integrate living and green spaces but separate living and traffic spaces in order to improve health and wellbeing and potentially save health care costs.

1. Introduction

The environment, which can range from the natural (greenspaces, lightly populated), built or physical environment (man-made, densely populated) to the social environment (family, peers, community engagement), serves as the context of life, and contributes to its quality in terms of health, well-being and diseases [1,2]. The built environment impacts exposures such as noise, environmental pollutants and general neighborhood conditions including infrastructural adequacy, which can facilitate or hinder physical and psychological functioning [1-6].

Multiple health outcomes including headaches, arthritis and various respiratory morbidities were also associated to the built environment [7,8]. The perception of the built environment seems to affect HRQoL, defined as “how well a person functions in their life and his or her perceived well-being in physical, mental, and social domains of health” [9]. HRQoL is highly correlated with the health status [10,11]. Positive perceptions of neighborhood aesthethics, access to shops, services, public transportation and green spaces were associated with higher HRQoL scores [12,13].

A more integrated approach investigating both, different domains ofthe perceived built environment and individual lifestyle characteristics on HRQoL is critical to the advancement of Public Health policies and urban planning enabling healthy aging for large parts of the population. But the understanding of pathways and mechanisms linking the perceived built environment to HRQoL remains limited. In particular, evidence on the role of the perceived social environment and of physical activity in relation to the built environment remains understudied [14]. Individuals with poor perceptions of social support seem to evolve more aggravated mental health issues with stronger symptoms in disease-outcomes compared to individuals perceiving their social network environment positively, even though reverse causation cannot be excluded in these cases [15,16]. However, whether the association of the perceived built environment with HRQoL is independent of the perception of the social environment is not clear.

Furthermore, physical activity (and related to it obesity) is a priority factor when investigating mechanisms interlinking the built environment and HRQoL, given the rising prevalence of physical activity limitations and associated social, physical, and financial costs in urban and aging populations [17-19]. It is broadly documented that the living environment plays a central role in promoting or inhibiting physical activity [20-22]. In contrast, whether the association of the perceived built environment with HRQoL is independent of physical activity levels remains elusive.

The perception of environmental characteristics might not only influence HRQoL, but also health-seeking behavior [23,24]. From a “Health in All Policy” perspective [25,26], it seems important to show the associations of HRQoL and health care utilization in order to highlight inadequacies related to environmental and social policies. Yet, no studies that we could find have linked single characteristics of the physical environment to health care utilization as a downstream consequence of poor HRQoL [27,28].

In this cross-sectional analysis embedded in the population-based Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) we investigated: (1) the association of the perceived built environment with HRQoL and health care utilization and (2) whether the association was independent of the social environment, physical activity and BMI.

2. Methods

2.1 Study population

SAPALDIA, initiated in 1991 (SAPALDIA1), is a population-based cohort with associated biobank involving 9’651 adults (18–62 years) drawn from eight representative Swiss areas aimed originally at understanding the respiratory impact of air pollution exposure in the Swiss population [29]. In the subsequent three follow-ups completed over 25 years (SAPALDIA2, 2001/2002, 8’047 participants; SAPALDIA3, 2010/2011, 6’088 participants [30]; and SAPALDIA4, 2017/2018, 5’149 participants) the study expanded into cardio-metabolic outcomes, well-being and healthy aging. The current cross-sectional analysis was performed using SAPALDIA4 data. We included 1980 SAPALDIA4 participants who had complete data on the perceived built and social environment, HRQoL, health care utilization as well as other relevant covariates. The SAPALDIA cohort study procedures comply with the Declaration of Helsinki. For each survey, ethics approvals were granted by the regional ethics committees and participants provided written informed consent prior to participation.

2.2 Measures of Health-Related Quality Of Life (HRQoL)

The SAPALDIA 4 questionnaires included the 36-Item Short-Form Health Survey (SF-36), a widely-used and validated tool for measuring HRQoL in both population-based and clinical settings [31,32]. The questionnaire provides a summary of physical (PCS) and mental health (MCS) component scores, based on eight domains. The physical component comprises physical functioning (PF), bodily pain (BP), role physical (RP) and general health perception (GH). The mental component comprises vitality (VT), social role functioning (SF), role emotional (RE) and mental health perception (MH). Scores for each subscale range from 0–100, and higher scores indicate better HRQoL [33]. In our results we considered the two main domains GH & MH.

2.3 Measures of perceived built environment

We extracted relevant information on the perceived built from the SAPALDIA4 questionnaire. We considered personal satisfaction with apartment and neighborhood (score of four questions); proximity (in minutes) to supermarkets, local services, restaurants and cafés, public transportation services, sports facilities, parks and green spaces as well as quiet places; transportation noise annoyance (standardized rating Scale 0–10) [34].

2.4 Health care utilization

We defined health care utilization as use of medical services, also measured using the SAPALDIA4 questionnaire. We defined it as a variable, which combined the visit of either physician(s) or hospital(s) in the 12 months preceding the survey (0, 1 and 2 visits respectively).

2.5 Potential confounders

We a priori selected the following potential confounders measured at SAPALDIA4, based on existing literature and prior knowledge: age (years), sex (male/female), years of formal education (≤9/≤12/>12 years equivalent to primary, secondary and tertiary education), occupational status (full-time job, part-time job, retired, retired but still working); study area (Basel, Wald, Geneva, Payerne, Lugano, Aarau, Davos, Montana), smoking status (never/former/current).

We specifically investigated the effect of additional adjustment for the social environment—living status of the participants (living alone vs. living with a partner) and social engagement (score built on eleven items); the specific questions are displayed in Table A1 in S1 Appendix.

Moreover, we investigated the effect of additional adjustment for physical activity (sufficient moderate to vigorous physical activity (<150/≥150 minutes per week)) and body mass index (BMI; kg/m2).

2.6 Statistical analysis

In a first step (see 3.1), we described the characteristics of the study population, summarizing continuous variables as means and interquartile ranges (SF-36), and categorical variables as proportions. The median HRQoL GH score and the percentage of persons with at least one physician or hospital visit in the last 12 month are reported according to the levels of the characteristics.

In a second step (see 3.2), we investigated associations of perceived built environment variables with HRQoL using multiple quantile regression models mutually adjusted for predictor variables while adjusting for covariates (sex, age, education, occupational status, smoking status and study area). We chose this approach as values of SF-36 derived HRQoL scores are highly left-skewed, which means that most participants scored relatively high on the investigated scales (Figure A1 in S1 Appendix).

In a third step (see 3.3) we examined the modifying role of the social environment (living alone versus with a partner & social engagement) as well as physical activity and BMI in the association of the perceived built environment with HRQoL.

In a fourth step (see 3.4) we examined the associations of the perceived built environment with health care utilization, modified by the above mentioned variables, by performing multinomial (polytomous) logistic regression models.

We assessed all variables of the perceived built environment along their tertiles (low, medium and high). Due to their skewed distribution and the limited number of subjects in the respective categories, it was often not possible to have equal number of participants in each class as seen in Table 1. All of the above models were adjusted for potential individual-level and context-level confounders measured, including sex, age, education, occupational status, smoking status and study area.

Table 1

Characteristics of the study populations and sub-group specific HRQoL score (GH) and health care utilization.

Variable	Total n = 1980	Percent (%)	Median score of overall HRQoL (GH)	Visited physician/hospital ≥1 previous 12 months (%)
Sex
Male	1013	51	71	80
Female	967	49	72	89
Age (Mean, SD)	64.20(10.21)
Age (years)
<55	1025	52	74	81
55–64	652	33	70	89
≥65	303	15	67	88
Education
Low	57	3	69	93
Middle	1209	61	72	84
High	714	36	72	84
Occupational status
Full-time	674	34	74	78
Part-time	294	15	74	86
Retired	758	38	68	89
Retired & Working	254	13	72	87
Smoking Status
Never	879	44	73	83
Former	812	41	70	87
Current	289	15	71	82
Satisfaction with apartment and neighbourhood
Low	469	24	66	86
Medium	471	24	72	83
High	1040	52	73	85
Proximity to social places
Low	677	34	71	83
Medium	780	39	72	85
High	523	26	71	87
Proximity to public transportation
Low	318	16	71	84
Medium	574	29	71	87
High	1088	55	72	83
Proximity to sports facilities
Low	841	43	71	85
Medium	583	30	72	85
High	555	28	71	83
Proximity to quiet green places
Low	732	37	70	85
Medium	658	33	72	84
High	590	30	73	84
Noise annoyance
Low	812	41	73	81
Mid	601	30	70	87
High	568	29	71	86
Living alone	498	25	70	85
Living with a partner	1482	75	72	84
Social engagement
Low	728	37	70	84
Medium	670	34	72	84
High	582	29	73	86
Physical Activity Guidelines (WHO)
Inactive	709	36	67	84
Sufficiently active	1271	64	74	85
BMI (Median)	25.5
Physician/Hospital visit last 12 months
0	307	16	77	n.a
1	1371	69	72	n.a
2+	302	15	65	n.a

Education: Low = Primary School (≤ 9years), Middle = Secondary school, middle school or apprenticeship (≤12 years), High = Technical College or University (≥12 years); Occupational status: Unemployment omitted due to class size (n = 11).

Physical Activity Guidelines (WHO).

Inactive: <150 min of MPA and <75 VPA per week.

Sufficient: >150 min of MPA or >75 VPA per week.

We performed all analyses using Stata 15 (Stata Corporation, College Station, Texas) and considered associations as statistically significant at an alpha-level of 0.05. We conducted a total of 3 different statistical tests (not considering models that tested for the effect of additional adjustment). We provide in the footnote of the Tables information on which tests remained statistically significant after Bonferroni correction (adjusted p-values for 3 Models (General Health, Mental Health and Health care utilization).

3. Results

3.1 Characteristics of the study population

The characteristics of the study population are presented in Table 1. The mean age of the included participants was 64 years (43 to 87 years), with an equal distribution by sex. Approximately 61% of the subjects reported medium education levels. Half of the participants were still occupationally active (full-time or part-time) and half were retired. Relatively few participants were current smoker (15%) and nearly two third (64%) met the WHO guidelines for physical activity. 52% of the study population reported being satisfied with their apartment and neighborhood. With regards to perceived proximity measures, about a fourth of the study participants reported high levels of proximity to social places, sports facilities and quiet green places, whereas 55% reported public transportation to be available in proximity to their residence. Most subjects (75%) lived with a partner and showed low to medium social engagement.

On average participants reported high HRQoL scores across all domains. The median score of the GH HRQoL domain showed small or no differences by sex, proximity to social places, sports facilities and public transportation and peer support for daily activities. Descriptive differences in visits to either physicians and/or hospitals the last 12 months were detected for sex, age categories, noise annoyance ratings, occupational status, education and smoking status. The correlations between the social and perceived built environment variables are summarized in Table A2 in S1 Appendix.

3.2. Associations of perceived built environment with HRQoL

The results on the covariate adjusted associations of variables (categorized as tertiles) describing the perceived built environment with HRQoL domains are illustrated in Fig 1A and 1B. The middle tertile of self-reported satisfaction with the apartment and neighbourhood showed statistically significant positive associations with GH (4.09 (95%CI: 1.85; 6.34)), while the upper tertiles showed statistically significant positive associations with GH (5.49 (3.56; 7.42)) and MH (4.07 (2.41; 5.72)), displaying a dose-response relationship. We found no association between proximity measures and HRQoL apart from a positive association of reported proximity to quiet and green spaces for the upper tertiles of this variable with both GH (1.61 (0.13; 3.09)) and MH (1.61 (0.13; 3.09)). We found a negative trend between tertiles of noise annoyance and HRQoL parameters. Compared to participants in the lowest tertile of noise annoyance, those in the middle and highest tertiles of noise annoyance showed statistically significant lower scores for MH (mid = -3.12 (-4.55; -1.70); high = -4.64 (-6.29; -3.00)). MH (mid = -3.37 (-4.81; -1.96); high = -4.57 (-6.15; -2.99)), with the highest tertile group having the lowest scores in this HRQoL parameters.

Fig 1

Association of variables describing the perceived built environment categorized as tertiles (1A = Middle tertiles; 1B = Upper tertiles) with health-related quality of life domains, adjusted for covariates (sex, age, education, smoking status, occupational status and study area).

3.3 The role of adjusting for social environment, physical activity & BMI in the association of the perceived build environment with HRQoL

We observed no substantial differences in the association between the perceived built environment and HRQoL when adjusting the models for the social environment as well as for physical activity and BMI respectively (Table 2).

Table 2

Alteration in associations of variables defining the perceived built environment with health-related quality of life by adjustment of social environment variables, physical activity and BMI.

Perceived built environment	General Health	Mental Health
Ref = Lowest tertile	Coef (95% CI)	Coef (95% CI)
Satisfaction with Apartment and Built Environment
Mid tertile	4.09 (1.85; 6.34)** +	1.51 (-0.21; 3.22)
Upper tertile	5.49 (3.56; 7.42)** +	4.07 (2.41; 5.72)** +
Proximity to social places
Mid tertile	0.84 (-1.08; 2.76)	0.63 (-1.01; 2.27)
Upper tertile	0.90 (-1.34; 3.14)	1.10 (-0.88; 3.07)
Proximity to public transportation
Mid tertile	-0.09 (-2.29; 2.11)	0.89 (-1.12; 2.89)
Upper tertile	0.39 (-1.74; 2.92)	-0.67 (-2.62; 1.29)
Proximity to sports facilities
Mid tertile	1.16 (-0.92; 3.23)	-0.18 (-1.71; 1.35)
Upper tertile	-0.33 (-2.31; 1.64)	0.14 (-1.48; 1.76)
Proximity to quiet green places
Mid tertile	1.72 (-0.04; 3.47)	0.65 (-0.78; 2.09)
Upper tertile	2.19 (0.25; 4.14)*	1.61 (0.13; 3.09)*
Noise annoyance
Mid tertile	-1.11 (-2.92; 0.65)	-3.12 (-4.55; -1.70)** +
Upper tertile	-1.79; (-3.61; 0.03)	-4.64 (-6.29; -3.00)** +
+ Social environment (Living alone versus with a partner & social engagement)
Satisfaction with Apartment and Built Environment
Mid tertile	4.56 (2.96; 6.63)** +	0.84 (-0.84; 2.52)
Upper tertile	5.97 (4.14; 7.80)** +	3.85 (2.19; 5.50)** +
Proximity to social places
Mid tertile	1.25 (-0.60; 3.10)	1.01 (-0.56; 2.59)
Upper tertile	1.16 (-1.13; 3.45)	1.48 (-0.49; 3.46)
Proximity to public transportation
Mid tertile	-0.33 (-2.55; 1.89)	1.00 (-0.94; 2.94)
Upper tertile	0.65 (-1.56; 2.85)	0.08 (-1.90; 1.73)
Proximity to sports facilities
Mid tertile	0.93 (-1.07; 2.93)	-0.53 (-1.99; 0.93)
Upper tertile	-0.20 (-2.13; 1.74)	-0.69 (-2.22; 0.83)
Proximity to quiet green places
Mid tertile	1.46 (-0.25; 3.18)	0.61 (-0.77; 1.99)
Upper tertile	1.80 (-0.10; 3.71)	1.72 (0.27; 3.17)*
Noise annoyance
Mid tertile	-1.02 (-2.85; 0.82)	-3.51 (-4.82; -2.20)** +
Upper tertile	-1.62 (-3.39; 0.13)	-4.22 (-5.91; -2.55)** +
+ Physical Activity & BMI (without social characteristics)
Satisfaction with Apartment and Built Environment
Mid tertile	4.44 (2.56; 6.40)** +	1.32 (-0.54; 3.18)
Upper tertile	6.63 (4.93; 8.32)** +	3.80 (2.11; 5.48)** +
Proximity to social places
Mid tertile	0.75 (-0.91; 2.41)	0.24 (-1.30; 1.78)
Upper tertile	-0.48 (-2.41; 1.45)	0.72 (-1.22; 2.67)
Proximity to public transportation
Mid tertile	0.39 (-1.98; 2.75)	1.05 (-0.80; 2.90)
Upper tertile	1.50 (-0.73; 3.72)	-0.19 (-1.94; 1.57)
Proximity to sports facilities
Mid tertile	0.83 (-1.07; 2.72)	0.14 (-1.65; 1.38)
Upper tertile	-0.10 (-1.52; 1.71)	-0.45 (-1.26; 1.26)
Proximity to quiet green places
Mid tertile	1.07 (-0.36; 2.51)	1.05 (-0.44; 2.54)
Upper tertile	1.18 (-0,48; 2.85)	2.32 (0.83; 3.81)*
Noise annoyance
Mid tertile	-1.96 (-3.49; -0.43)* +	-3.75 (-5.16; -2.35)** +
Upper tertile	-2.07 (-3.65; -0.48)* +	-4.37 (-5.98; -2.76)** +

*p<0.05

**p<0.001;

+p<0.05 after Bonferroni correction.

Results were calculated using multivariate quantile regression model mutually adjusted for all exposure variables and confounders.

HRQoL was assessed using the SF-36.

Confounders: Sex, age, education, occupational status, smoking status, study area.

3.4 Perceived built environment and health care utilization

The results of the covariate adjusted associations of the perceived built environment variables with health care utilization are shown in Table 3. Participants reporting closer proximity to social places showed an increase of health care utilization with a relative risk ratio (RRR) of 1.54 (95%CI: 1.04; 2.39) compared to participants reporting living distant from social places. Subjects in the upper tertile of living proximate to sports facilities showed a decreased relative risk of visiting either physicians or hospitals more than once a year RRR = 0.56 (0.35; 0.88). We observed positive associations of noise annoyance with health care utilization for subjects in the middle tertile with 1 visit (RRR = 1.44 (1.05; 1.97)) and subjects in the upper tertile with more than 2 visits (RRR = 1.55 (1.00; 2.39)). When adjusting for the social environment, physical activity and BMI we did not observe substantial differences in the above mentioned associations.

Table 3

Associations of variables defining the perceived built environment with health care utilization, with and without adjustment for the social environment, physical activity and BMI.

Perceived built environment	Combined (physician & hospital) RRR (95% CI)
	0 = Reference	1	>2
Satisfaction with Apartment and Built Environment
Mid tertile		0.91 (0.63; 1.33)	1.24 (0.76; 2.03)
Upper tertile		1.01 (0.73; 1.41)	1.23 (0.79; 1.90)
Proximity to social places
Mid tertile		1.12 (0.81; 1.55)	1.23 (0.81; 1.88)
Upper tertile		1.54 (1.04; 2.39)*	1.63 (0.99; 2.68)
Proximity to public transportation
Mid tertile		1.24 (0.81; 1.91)	1.62 (0.91; 2.89)
Upper tertile		0.89 (0.60; 1.33)	1.25 (0.73; 2.17)
Proximity to sports facilities
Mid tertile		0.96 (0.68; 1.35)	0.88 (0.57; 1.36)
Upper tertile		0.88 (0.62; 1.25)	0.56 (0.35; 0.88)* +
Proximity to quiet green places
Mid tertile		0.98 (0.72; 1.34)	1.06 (0.72; 1.58)
Upper tertile		1.11 (0.80; 1.52)	1.07 (0.71; 1.63)
Noise annoyance
Mid tertile		1.44 (1.05; 1.97)*	1.26 (0.84; 1.89)
Upper tertile		1.39 (1.00; 1.94)	1.55 (1.00; 2.39)*
+ Social environment (Living alone versus with a partner & social engagement)
Satisfaction with Apartment and Built Environment
Mid tertile		0.89 (0.61; 1.29)	1.22 (0.75; 1.99)
Upper tertile		0.98 (0.70; 1.37)	1.21 (0.77; 1.87)
Proximity to social places
Mid tertile		1.15 (0.83; 1.59)	1.25 (0.82; 1.91)
Upper tertile		1.61 (1.08; 2.40)*	1.67 (1.02; 2.75)*
Proximity to public transportation
Mid tertile		1.26 (0.82; 1.94)	1.64 (0.92; 2.92)
Upper tertile		0.90 (0.60; 1.35)	1.27 (0.73; 2.19)
Proximity to sports facilities
Mid tertile		0.94 (0.67; 1.31)	0.86 (0.56; 1.33)
Upper tertile		0.86 (0.60; 1.22)	0.54 (0.344; 086)* +
Proximity to quiet green places
Mid tertile		0.98 (0.71; 1.34)	1.06 (0.72; 1.58)
Upper tertile		1.09 (0.78; 1.52)	1.07 (0.71; 1.62)
Noise annoyance
Mid tertile		1,43 (1.04; 1.95)*	1.26 (0.84; 1.90)
Upper tertile		1.41 (1.01; 1.97)*	1.56 (1.01; 2.42)*
+ Physical Activity & BMI (without social engagement)
Satisfaction with Apartment and Built Environment
Mid tertile		0.94 (0.64; 1.37)	1.36 (0.83; 2.22)
Upper tertile		1.00 (0.72; 1.40)	1.26 (0.81; 1.96)
Proximity to social places
Mid tertile		1.12 (0.81; 1.55)	1.23 (0.80; 1.87)
Upper tertile		1.58 (1.06; 2.35)*	1.64 (0.99; 2.69)
Proximity to public transportation
Mid tertile		1.24 (0.80; 1.91)	1.62 (0.91; 2.90)
Upper tertile		0.90 (0.60; 1.34)	1.27 (0.73; 2.21)
Proximity to sports facilities
Mid tertile		0.96 (0.68; 1.35)	0.93 (0.60; 1.44)
Upper tertile		0.87 (0.61; 1.24)	0.58 (0.37; 0.91)*
Proximity to quiet green places
Mid tertile		1.00 (0.73; 1.37)	1.10 (0.74; 1.63)
Upper tertile		1.14 (0.82; 1.58)	1.11 (0.73; 1.69)
Noise annoyance
Mid tertile		1.49 (1.09; 2.04)* +	1.36 (0.91; 2.05)
Upper tertile		1.46 (1.04; 2.04)*	1.73 (1.12; 2.69)* +

*p<0.05

**p<0.001;

+p<0.05 after Bonferroni correction.

RRR = Relative risk ratios.

Results were calculated using multinomial (polytomous) logistic regression models mutually adjusted for all exposure variables and confounders.

Physician and hospital visits were self-reported for the last 12 months.

Confounders: Sex, age, education, occupational status, smoking status, study area.

4. Discussion

The results of this study are in agreement with a beneficial effect on general and mental HRQoL of satisfaction with one’s apartment and the built environment around the residence and of proximity to green space. Only in the case of noise annoyance, which was associated with decreased HRQoL, did this association extend to an increased health care utilization. Proximity to social places was also associated with increased health care utilization, whereas proximity to sports facilities was associated with decreased health care utilization. Adjustment for the social environment or for physical activity and BMI did not change any of the associations.

A significant component of the perceived built environment was satisfaction with the apartment and neighbourhood. This variable associated most strongly with higher scores in both measured HRQoL domains. The results were consistent after adjusting for variables describing the social environment. The findings of Wong et al., 2018 agree with our results, even though the study was conducted in a cultural and geographical different region (Hong Kong) and with somewhat younger populations (on average 45 years) compared to the current study [35].

The observation of higher noise annoyance being associated with poorer HRQoL, especially for MCS, agrees with similar findings from several previous studies [36-39]. In addition, we observed a tendency of noise annoyance being associated with GH, suggesting that there might be an influence on poorer HRQoL aspects related to PCS. These findings not only add to the amount of literature showing adverse health effects of noise annoyance [40-42], but go a step further in showing increased need of healthcare and use of medical services for individuals reporting high noise annoyance ratings.

Our findings indicate that the perceived proximity to cultural, sports as well as public transportation may not be major determinants of HRQoL. Regarding these proximity measures, our results contradict some studies [12,43,44], yet agree with another study, assessing 5000 adults in Berlin, Paris, London, New York and Toronto, which suggests no direct association of neighbourhood proximity characteristics with HRQoL for older adults (similar age distribution as this study) [45]. On the contrary, the same study found relevant association of proximity measures for younger adults and declared that older adults valued provision of services and healthcare facilities more, compared to proximity to social and recreational amenities. There might be several explanations for the lack of associations with proximity characteristics. Residents with very low HRQoL could be less aware of a city’s attractiveness as they leave their apartment less frequently. A hypothesis of Machón et al. 2017 stated that if people live for many decades in the same city they get used to the environment, which could lead to a lack of associations with HRQoL [46]. A possible approach to overcome these issues and increase HRQoL of city residents is communal living. This type of living environment is expected to improve the housing crisis and at the same time help people in need, such as disabled older aged persons [47].

However, we can only hypothesize about these clarifications, as there may be numerous unknown factors contributing to individual preferences or aversions when dealing with perceptions of environments. Also, the cross-sectional nature of the study does not allow investigation in the directionality of the associations.

Regarding health care utilization, noise annoyance showed statistically significant associations with visiting physicians or hospitals more than once a year. This implies that the association of transportation noise annoyance with HRQoL has downstream costs by leading to increased doctors and hospital visits. We further identified an increased use of health services for people living closer to social places and a decreased use for people living closer to sports facilities. These findings may imply a connection of living closer to social places, and most importantly medical facilities with an increased use of health services. In contrast, living closer to sports facilities may be one of many factors that prevents an increased use of health services. Future studies need to investigate the cost-effectiveness of decreasing transportation noise in urban environments and further investigate the associations of living closer to sports facilities and social places with health service utilization.

As we did not find substantial differences when adjusting for social environment, physical activity and BMI, independent pathways from the built environment to HRQoL and health care utilization may be expected and need to be investigated in future studies.

4.1 Strength and limitations

A major strength of this study is the comprehensive consideration of the perception of built environmental parameters with HRQoL outcomes and healthcare seeking behavior. Exhaustive analysis were conducted to investigate independence of these associations from the social environment and lifestyle behavior. In addition, the investigation with health care utilization, facilitates the transfer of our results to clinical relevant domains plus builds a basis for health economic evaluation of environmental risks and burdens for healthcare systems. The population-based design of this study favors the generalizability of the findings within the Swiss setting. However, due to participation and survivor bias, validity and generalizability are always at risk in longitudinal cohort settings. In particular, compared to similar settings the sample from Switzerland aged 55 years and older, showed higher HRQoL scores, which may be an issue when comparing with other countries and studies.

Due to the cross-sectional nature of the study, inferring causality and directionality of the associations is not possible. This may be particularly relevant for the observed association of proximity to social places with health care utilization. Persons with existing limitations and higher needs for health care services may choose to live closer to such services. We looked at perceptions of the built environment, which may have introduced a bias of subjective validation. However, the perception of environment is a relevant aspects despite being subjectively biased by nature.

Due to the lack of air pollution information at SAPALDIA 4, we were unable to take this potentially important confounder into consideration. Finally, due to the restricted sample size there is a chance that some relevant associations went unnoticed.

5. Conclusion

Our study contributes to the understanding of an independent role of the perceived built environment on residents’ HRQoL. In particular, the study points to a potentially high benefit gained from decreasing transportation noise for both, HRQoL and health care utilization.

Supplementary information.

(DOCX)

Click here for additional data file.

16 Nov 2020

PONE-D-20-27261

Elucidating independent and joint associations of the social and perceived built environment with health-related quality of life and health care utilization

PLOS ONE

Dear Dr. Probst-Hensch,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Brecht Devleesschauwer

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This paper looks at associations between the built environment and health related quality of life

You have very few significant results among a lot of statistical tests – do you think your significant results might be type 1 error?

Line 40 what about the natural environment?

Line 42 define built and social environment here

Line 43 ‘impacts’ instead of ‘comprises’

Line4 64 define HRQOL and its relationship to health

Line 134 were those few values suggesting good, average or poor health?

Line 175 did you check for multicollinearity in your analysis? Did you account for sample design (clustering) in your analysis

Line 214 why use some tertiles and some dichotomised?

Line 226 – age at what point –baseline or final follow up

Line 229 are these characteristics typical for the Swiss population?

Discussion – Does the Swiss population have higher HRQOL than elsewhere and or higher housing quality than elsewhere? If so research elsewhere might find different associations?

Would you suggest communal living as a solution to living alone? https://www.theguardian.com/cities/2019/sep/03/co-living-the-end-of-urban-loneliness-or-cynical-corporate-dormitories

Reviewer #2: In general, the manuscript is very long and lack of conciseness. We fail to clearly understand the results and the key messages among the multitude of statistical analyses performed.

Regarding the research question, the scientific relevance of studying the joint association of the built and the social environment on HRQL/Health care utilization is not sufficiently explained. In the introduction, it is mentioned that the mechanisms are not yet well understood but the performed analysis do not allow to explore the mechanisms. The analysis with latent classes assess the association of the combined exposure to social and built environment with HQLR but not explain the mechanisms by which this environment affect the HRQL/Health care utilization. Mediation analyses or different regression models performed with an increasing level of adjustment for covariates would have been more adequate if the goal was to explore the mechanisms. It would have been interesting to consider the “social environment” as a mediator in the association between the built environment and the HRQL/health care utilization The ability of cities to offer places and services could affect the HRQL through the impact on social connectedness.

Therefore, you should be careful with the following sentence in your conclusion: “ our study adds to the understanding of how the social and built environment contributes to the HRQL”. I would rather talk about the characteristics of the social and built environment that are associated with HRQL.

Question: what is the main added value of the analysis performed with the Latent classes? In my view, it could have been interesting to use them in case of high multi-collinearity between variables or if latent classes would have provided very distinctive groups. If the aim of the study is to assess the joint association, why didn’t you choose instead to include interaction terms in the regression model?

Also, including each dimension of the HRQL in the analyses (BP, VT, etc.) seems to me too exhaustive and make the final interpretation more complicated. The interpretation could have been simplified by using an aggregated score of the HRQL.

The performed statistical models and the data do not allow to completely answer the research question which aim to investigate the independent and joint association between the perceived built and social environment and HRQL and Health care utilization. All your models are adjusted for lifestyle factors (physical activity, BMI and smoking) that are potential mediators in the association between the built environment and health. The estimates of your model do not take into account the part of the effect due to those factors. However, we know from the literature that one of the mechanism by which the built environment affect the health status is linked to healthy lifestyles. For example, many urban environments lack green and open spaces that encourage exercise. In your discussion part (line 449), you write “ the perceived proximity to cultural, sports and green amenities may not be a major determinant of HRQL”, but this result is maybe due to the fact that you adjusted your model for “physical activity”.

Some comments regarding the validity of the variables selected in the models to approach the concept of social environment, built environment and Health care utilization:

The social environment is a very wide concept that encompasses many dimensions such as social support, socio-economic status, family composition etc. The distinction between the variables selected to define the “social environment” and the socio-economic variables selected to adjust the model is not clear. Why did you choose to include the “occupational status” in the “social environment” and not in the confounders such as the “educational level”? Regarding the “occupational status”, why is there no unemployment status?

An important dimension of the built environment that is missing in your study is air pollution. This should be mentioned in the discussion. Air pollution could be a confounding factor in the association found between noise annoyance and HRQL.

Regarding the health care utilization, you decide to dichotomize the variable, with 0 or >=1 Physician visit in the last 12 months. But what do we really aim to measure with this binomial variable? What is considered as a normal or healthy behavior in health care utilization? Is the variable really measuring a poor health status or could it reflect a problem of access to health care?

Specific comments:

Line 540: “an increased satisfaction living situation associated with increased health care utilization”. I do not find this association in the results.

Lline 583: A point is lacking

Table 2: you could make a smaller table by removing one of the two lines describing the variables with 2 categories (High/low)

Figure 3: in my view, this figure could be in the annexes

Recommendation:

- Run the models without adjusting for BMI and Physical activity

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

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Reviewer #1: No

Reviewer #2: No

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9 Mar 2021

Dear Reviewers,

Many thanks for your time and very constructive comments. We substantially changed the focus of the manuscript on the basis of your comments. We redirected the aim of the manuscript to investigating the association of the perceived built environment with health-related quality of life and health care utilization. Moreover, we elucidated the independence of the observed associations from social environment, physical activity and BMI.

Please find all the specific changes and answers to your comments below.

Reviewer #1: This paper looks at associations between the built environment and health related quality of life

You have very few significant results among a lot of statistical tests – do you think your significant results might be type 1 error?

- We now adapted the objectives of this manuscript as described above. Furthermore, we only considered the two main domains of the SF-36 (GH & MH) to generate more concise and concrete results. The perceived environmental domains were mutually adjusted in the models, however we ran separate models for the associations with HRQoL and health care utilization and conducted a total of 3 statistical tests (not considering the additional models testing the effect of additional adjustment). We therefore provide in the footnote of each table the Bonferroni corrected results.

Line 40 what about the natural environment?

- We added the natural environment (line 47)

Line 42 define built and social environment here

- Definition of the built environment have been added. Social environment adapted as not anymore the focus of the manuscript (line 47-54).

Line 43 ‘impacts’ instead of ‘comprises’

- Changed accordingly (line 50)

Line4 64 define HRQOL and its relationship to health

- We added an information on the correlation (line 60-61)

Line 134 were those few values suggesting good, average or poor health?

- We changed this section and added explanations.

Line 175 did you check for multicollinearity in your analysis? Did you account for sample design (clustering) in your analysis

- We did not detect high correlations between the predictor variables as seen in Table A1.

Line 214 why use some tertiles and some dichotomised?

- We now consistently used tertiles for all the predictor variables.

Line 226 – age at what point –baseline or final follow up

- We added the information that data was captured at SAPALDIA4 in section 2.1.

Line 229 are these characteristics typical for the Swiss population?

- We excluded the latent class analysis, hence this information is not listed anymore.

Discussion – Does the Swiss population have higher HRQOL than elsewhere and or higher housing quality than elsewhere? If so research elsewhere might find different associations?

- We added information on this in the limitations section of the discussion

Would you suggest communal living as a solution to living alone? https://www.theguardian.com/cities/2019/sep/03/co-living-the-end-of-urban-loneliness-or-cynical-corporate-dormitories

- Indeed a very interesting approach, we added information on communal living in the discussion (line 338-341)

Reviewer #2: In general, the manuscript is very long and lack of conciseness. We fail to clearly understand the results and the key messages among the multitude of statistical analyses performed.

Regarding the research question, the scientific relevance of studying the joint association of the built and the social environment on HRQL/Health care utilization is not sufficiently explained. In the introduction, it is mentioned that the mechanisms are not yet well understood but the performed analysis do not allow to explore the mechanisms.

The analysis with latent classes assess the association of the combined exposure to social and built environment with HQLR but not explain the mechanisms by which this environment affect the HRQL/Health care utilization. Mediation analyses or different regression models performed with an increasing level of adjustment for covariates would have been more adequate if the goal was to explore the mechanisms. It would have been interesting to consider the “social environment” as a mediator in the association between the built environment and the HRQL/health care utilization The ability of cities to offer places and services could affect the HRQL through the impact on social connectedness.

Therefore, you should be careful with the following sentence in your conclusion: “ our study adds to the understanding of how the social and built environment contributes to the HRQL”. I would rather talk about the characteristics of the social and built environment that are associated with HRQL.

- We thank the reviewer for these helpful and important comments. It motivated us to reshape the objectives of the paper. Given the cross-sectional nature of our study, we abstained from conducting a mediation analysis. But we investigated whether or not the association of the perceived built environment is altered by adjustment for the social environment and for physical activity or BMI. As mentioned above we now redirected the objectives of the manuscript to focusing on the association of the perceived built environment with HRQoL and health care utilization.

Question: what is the main added value of the analysis performed with the Latent classes? In my view, it could have been interesting to use them in case of high multi-collinearity between variables or if latent classes would have provided very distinctive groups. If the aim of the study is to assess the joint association, why didn’t you choose instead to include interaction terms in the regression model?

- We excluded the LCA as we agree on the poor added value.

Also, including each dimension of the HRQL in the analyses (BP, VT, etc.) seems to me too exhaustive and make the final interpretation more complicated. The interpretation could have been simplified by using an aggregated score of the HRQL.

- We do agree also on this point and included only GH and MH in the results.

The performed statistical models and the data do not allow to completely answer the research question which aim to investigate the independent and joint association between the perceived built and social environment and HRQL and Health care utilization. All your models are adjusted for lifestyle factors (physical activity, BMI and smoking) that are potential mediators in the association between the built environment and health. The estimates of your model do not take into account the part of the effect due to those factors. However, we know from the literature that one of the mechanism by which the built environment affect the health status is linked to healthy lifestyles. For example, many urban environments lack green and open spaces that encourage exercise. In your discussion part (line 449), you write “ the perceived proximity to cultural, sports and green amenities may not be a major determinant of HRQL”, but this result is maybe due to the fact that you adjusted your model for “physical activity”.

- Please see our comments above on the redirection of the manuscript.

Some comments regarding the validity of the variables selected in the models to approach the concept of social environment, built environment and Health care utilization:

The social environment is a very wide concept that encompasses many dimensions such as social support, socio-economic status, family composition etc. The distinction between the variables selected to define the “social environment” and the socio-economic variables selected to adjust the model is not clear. Why did you choose to include the “occupational status” in the “social environment” and not in the confounders such as the “educational level”? Regarding the “occupational status”, why is there no unemployment status?

- We now included occupational status as a confounder. Unemployment was excluded as the group size was very small (n=11) and would have distorted the results. We now show the specific impact of adjusting for the social variables “social engagement” and “living alone”.

An important dimension of the built environment that is missing in your study is air pollution. This should be mentioned in the discussion. Air pollution could be a confounding factor in the association found between noise annoyance and HRQL.

- We agree. However, we could not include air pollution, as it was not measured in the last follow-up of SAPALDIA. We included this information in the limitations.

Regarding the health care utilization, you decide to dichotomize the variable, with 0 or >=1 Physician visit in the last 12 months. But what do we really aim to measure with this binomial variable? What is considered as a normal or healthy behavior in health care utilization? Is the variable really measuring a poor health status or could it reflect a problem of access to health care?

- We now categorized the variable to 0, 1 2+ visits.

Specific comments:

Line 540: “an increased satisfaction living situation associated with increased health care utilization”. I do not find this association in the results.

Line 583: A point is lacking

Table 2: you could make a smaller table by removing one of the two lines describing the variables with 2 categories (High/low)

Figure 3: in my view, this figure could be in the annexes

- As we substantially changed the manuscripts these comments were resolved.

Recommendation:

- Run the models without adjusting for BMI and Physical activity

- We ran the model with and without adjusting for physical activity and BMI

6 Apr 2021

PONE-D-20-27261R1

Perceived built environment, health-related quality of life and health care utilization

PLOS ONE

Dear Dr. Probst-Hensch,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by May 21 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

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An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Brecht Devleesschauwer

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study looks at how health and wellbeing might be associated with the built environment

This study is much improved but I have a few comments:

Line 25 add ‘and health care utilisation’ after ‘(HRQoL)’ Change “. However” to “but”

Line 26-27 delete “and on how the HRQoL associations extend to health care utilization”

Lines 28-30 replace “the association of the perceived built environment with HRQoL and health care utilization, independent of the social environment, 30 physical activity and body mass index (BMI)” with “these associations” – otherwise very repetitive

Line 36-44 might be more clearly written e.g.

“Higher HRQOL and less health care utilisation were associated with less reported noise annoyance from transport. Higher HRQOL was also associated with greater satisfaction with the living environment and more perceived access to greenspaces. These results were independent of the social environment (living alone and social engagement) and lifestyle (physical activity level and BMI).

This study provides further evidence that the built environment should be designed to integrate living and green spaces but separate living and traffic spaces in order to improve health and wellbeing and potentially save health care costs.”

Line 47 Define natural, built, physical and social environments

Line 56 to 60 Combine these two studies into one sentence e.g. Health outcomes including headaches, arthritis , respiratory disease and obesity have been linked to the built environment (Goldbberg et al Hogan etal)

Line 60 define HRQOL

Line 66 to 69 I can’t follow this sentence – too long

Line 71-72 physical activity in relation to what ?

Line 72 to 74 – might be closer to healthcare in a town than in the countryside so I don’t undersand this. Also you don’t look at interactions with age so probably irrelevant for your study

Line 75 -77. Reverse causation here: depression might cause people to rate their support as poor

Line 84 do you mean physical limitations associated with obesity?

Line 95 your study does not include economic analysis of cost-benefit so I would rewrite this – instead talk about studies showing how HRQOL leads to health care utilisation and health care costs in Switzerland

Line 97 Either change “only very few” to “no studies that we could find” or describe the studies

Line 182 delete ‘at salpadia4’

Line 184 –explain further what this means (most respondents scored quite high on the scales??)

Line 195 – what do you mean by ‘classes’

Table 1 – is your study population similar to census characteristics of the Swiss population?

Figure 1 Please label the X axes

Line 299 word missing?

Line 301 why are these ‘critical’?

Line 303 delete ‘mutually’

Line 309 Perception being more important than actual built environment could suggest confounding by some sort of generalised negative affect so I would move that to the limitations section

Line 314 to 322 I think this paragraph relates to your old findings and should be deleted

Line 324 you did find sports was important

Line 325 to line 345 This paragraph looks at interactions with age which you did not explore so should be deleted. Instead you might need to explain why proximity to social spaces increased health care visits – it might be they were places that sell alcohol or unhealthy foods, perhaps to takeaway such as pizza?

Line 355 proximity to greenspace might have been confounded with physical activity and BMI?

Tables 2 and 3 – it would be useful to have bivariable associations in these tables

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

19 Apr 2021

Dear Reviewers,

Many thanks for your time and specific comments. Please find all the specific changes and answers to your comments below.

Reviewer #1: This study looks at how health and wellbeing might be associated with the built environment

This study is much improved but I have a few comments:

Line 25 add ‘and health care utilisation’ after ‘(HRQoL)’ Change “. However” to “but”

• Adapted accordingly

Line 26-27 delete “and on how the HRQoL associations extend to health care utilization”

• Adapted accordingly

Lines 28-30 replace “the association of the perceived built environment with HRQoL and health care utilization, independent of the social environment, 30 physical activity and body mass index (BMI)” with “these associations” – otherwise very repetitive

• We replaced the first part with “these associations” but kept the second part, to specify, which lifestyle variables we investigated.

Line 36-44 might be more clearly written e.g.

“Higher HRQOL and less health care utilisation were associated with less reported noise annoyance from transport. Higher HRQOL was also associated with greater satisfaction with the living environment and more perceived access to greenspaces. These results were independent of the social environment (living alone and social engagement) and lifestyle (physical activity level and BMI).

This study provides further evidence that the built environment should be designed to integrate living and green spaces but separate living and traffic spaces in order to improve health and wellbeing and potentially save health care costs.”

• Adapted accordingly. Except a minor change of “noise annoyance from transport” to “transportation noise annoyance”

Line 47 Define natural, built, physical and social environments

• Added definitions

Line 56 to 60 Combine these two studies into one sentence e.g. Health outcomes including headaches, arthritis, respiratory disease and obesity have been linked to the built environment (Goldbberg et al Hogan etal)

• We summarized the two references into one sentence

Line 60 define HRQOL

• Definition added

Line 66 to 69 I can’t follow this sentence – too long

• Sentence shortened and made more precise

Line 71-72 physical activity in relation to what ?

• Added “in relation to the built environment”

Line 72 to 74 – might be closer to healthcare in a town than in the countryside so I don’t undersand this. Also you don’t look at interactions with age so probably irrelevant for your study

• Deleted this sections as we agree that it is irrelevant for the new findings

Line 75 -77. Reverse causation here: depression might cause people to rate their support as poor

• Added a statement

Line 84 do you mean physical limitations associated with obesity?

• Changed to physical activity limitations, to clarify the relation to the built environment.

Line 95 your study does not include economic analysis of cost-benefit so I would rewrite this – instead talk about studies showing how HRQOL leads to health care utilisation and health care costs in Switzerland

• Adapted this section and focused more on the objectives of the present study

Line 97 Either change “only very few” to “no studies that we could find” or describe the studies

• Adapted accordingly

Line 182 delete ‘at salpadia4’

• Adapted accordingly

Line 184 –explain further what this means (most respondents scored quite high on the scales??)

• Added a further explanation

Line 195 – what do you mean by ‘classes’

• Changed to “subjects in the respective categories”

Table 1 – is your study population similar to census characteristics of the Swiss population?

• We compared our study population, and hence the characteristics, to other populations in section 4.1

Figure 1 Please label the X axes

• Added a label

Line 299 word missing?

• Added “change”

Line 301 why are these ‘critical’?

• Changed to significant

Line 303 delete ‘mutually’

• Adapted accordingly

Line 309 Perception being more important than actual built environment could suggest confounding by some sort of generalised negative affect so I would move that to the limitations section

• We deleted this section and added an explanation in the limitations section (Line 379)

Line 314 to 322 I think this paragraph relates to your old findings and should be deleted

• Dear Reviewer, we believe that the findings of noise annoyance on MCS are still very valid in our new findings. Hence, we would suggest to keep this section as it highlights that our findings on noise annoyance resonate well with other studies in this area.

Line 324 you did find sports was important

• In this line we refer to the findings for HRQoL, where we did not identify a relevant association of proximity to sports facilities with HRQoL.

Line 325 to line 345 This paragraph looks at interactions with age which you did not explore so should be deleted. Instead you might need to explain why proximity to social spaces increased health care visits – it might be they were places that sell alcohol or unhealthy foods, perhaps to takeaway such as pizza?

• This section refers to the HRQoL findings. However, we added interpretations of the findings on proximity to social places and sports facilities in the next section.

Line 355 proximity to greenspace might have been confounded with physical activity and BMI?

Tables 2 and 3 – it would be useful to have bivariable associations in these tables

• As we included Physical Activity and BMI in the models we adjusted for possible confounding of these variables in the association of green spaces and HRQoL. We showed that this association did not change substantially when including or excluding physical activity and BMI.

23 Apr 2021

Perceived built environment, health-related quality of life and health care utilization

PONE-D-20-27261R2

Dear Dr. Probst-Hensch,

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Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

27 Apr 2021

PONE-D-20-27261R2

Perceived built environment, health-related quality of life and health care utilization

Dear Dr. Probst-Hensch:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

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PLOS ONE