Free Access
Issue
Mov Sport Sci/Sci Mot
Number 106, 2019
Page(s) 7 - 17
DOI https://doi.org/10.1051/sm/2018021
Published online 20 November 2018

© ACAPS, 2020

1 Introduction

Physical activity (PA) provides significant physical and mental health benefits (Physical Activity Guidelines Advisory Committee, 2008; Warburton, Nicol, & Bredin, 2006). Walking is the most natural type of exercise (Morris & Hardman, 1997) which does not need specific equipment. It is feasible at any age or at any time and allows expending enough energy to meet WHO’s recommendations. Regular walking (at least 30 minutes 5 times/week, Brownson et al., 2000) increases life expectancy, reduces the incidence of non-communicable diseases (WHO, 2014), improves cardiovascular capacity (Morris & Hardman, 1997), and decreases cardiovascular disease risk (Manson et al., 2002; Murtagh et al., 2015). In sedentary individuals, even a slight increase in physical activity leads to reduction in cardiovascular risk (Li & Siegrist, 2012). Specifically, regular walking allows a reduction in systolic and diastolic blood pressure (−2.59 mmHg and −1.68 mmHg, respectively, Whelton, Chin, Xin, and He, 2002), and in waist circumference (between 3.1 and 6.5%), a surrogate of visceral fat associated to metabolic syndrome and cardiovascular risk (Ross et al., 2004). In a population presenting a high cardiovascular risk assessed by the SCORE defined by Conroy et al. (2003), an inverse relationship has been shown between the number of steps per day and systolic blood pressure, an important determinant of the SCORE (Mendelson et al., 2014). Regarding the effects on lipid profile, regular brisk walking increases the high-density lipoprotein cholesterol (HDL-C) level by 5% despite lack of change in low-density lipoprotein cholesterol (LDL-C) or weight loss (Kodama et al., 2007) and decreases triglycerides (TG) level (change depending on baseline levels: more important decrease in subjects with high TG basal levels; Durstine, Grandjean, Cox, and Thompson, 2002). Low- to moderate-intensity exercise has also a beneficial effect on glycaemia by increasing the muscle capacity to store glycogen (Braun, Sharoff, Chipkin, & Beaudoin, 2004; Galbo, Tobin, & van Loon, 2007; Pruchnic et al., 2004), lipid metabolism (Wang, Simar, & Fiatarone Singh, 2009), and by improving insulin sensitivity (Houmard et al., 2004).

A minimum of 150 minutes of moderate intensity aerobic PA at least 5 times per week is recommended for health (WHO, 2010). However, 51% of French population does not achieve the recommended PA level (Vuillemin, Escalon, & Bossard, 2008). The most cited barriers to PA are lack of time, motivation (Cerin, Leslie, Sugiyama, & Owen, 2010; King et al., 2000), and financial difficulties (European Commission, 2014). In addition, since it is admitted that people with low to modest socio-economic status neglects their health there is a need to direct public health policy toward this population (Sallis et al., 2016). Hence, to be relevant PA/walking promoting programs should be developed to overcome these three major barriers. At the community level, promoting walking as an active transport mode for short distances (below 2 km) or as a leisure time PA (through media campaigns, policy and environmental changes, community events, PA counseling and education at work sites and at schools, and community health fairs) is recommended (WHO, 2004).

Recently, it has been shown that urban environment (e.g., net residential density, intersection density, public transport density, and local parks) had the potential to increase PA by 90 min/week i.e. 60% of the amount recommended (Sallis et al., 2016). However, studies of built environment and PA have been criticized for relying only on self-reported measures (Ding & Gebel, 2012). There is a need to correlate objective measures of PA, such as steps number, with objective measures of environmental attributes relevant to PA, such as pedestrian signage. Moreover, the long-term longitudinal effects of device designed to increase physical activity is scarcely evaluated since the approach is more often correlational by nature (Sallis et al., 2016).

Urban pedestrian signage with time travel indication could be an incentive mean for people to walk more and has been implemented in numerous cities in the world (e.g. Hamburg – Germany, London – UK, Brisbane – Australia, Paris – France). In France in 2011, 16% of responders (9 cities) declared that the signage was easy to spot and visible and that they were encouraged to walk more (INPES, 2011). Nevertheless, to our knowledge, the long-term efficiency of urban pedestrian signage has not been thoroughly assessed particularly in a longitudinal design study. Moreover, impact of such environment intervention on health indicators is always assumed but rarely tested.

In addition, the lack of motivation being a major PA participation barrier, a crucial question is whether pedestrian signage is an incentive strategy that may impact individuals’ motivation for PA. Self Determination Theory (SDT) is a macro theory of motivation that explains the patterns of behavior change processes (Deci & Ryan, 2002). According to SDT there are many types of motivation that are more or less autonomous (intrinsic motivation, integrated and identified regulations) or controlled (external and introjected regulations; Deci and Ryan, 2002) and have direct effects on behavior (Teixeira, Carraça, Markland, Silva, & Ryan, 2012). Autonomous forms of motivation are related to spontaneous and regular PA adherence, whereas controlled forms of motivation are associated with lack of commitment and abandonment of activity (Hagger & Chatzisarantis, 2007). Recently Niven and Markland (2016) examined the relationship between different types of motivation and walking behavior. This study confirms the previous findings in exercise domain (Teixeira et al., 2012) – more autonomous forms of motivation are positively related to walking for transport or walking for leisure, whereas more controlled forms were negatively related to those behaviors (Niven & Markland, 2016). Thus, the programs that promote walking should take into account promotion of intrinsic experiences (process of internalization) that are the key to long-term adherence. However, sometimes controlled forms of motivations (integrated and identified regulations) are also important especially in adoption stage of new behaviors (Teixeira et al., 2012). Thus, one ambition of this study was to examine whether pedestrian signage might develop autonomous motivation toward walking as a transport mode.

In sum, the first aim of this study was to evaluate long-term (1 year) effects of pedestrian signage on attendance of the general population in an equipped neighborhood of Grenoble city (France). Secondly, we aimed to assess the effects of this pedestrian signage on walking activity level, motivation toward PA and cardiometabolic health indicators on a sample of Grenoble citizens living in this neighborhood in which the socioeconomic status is low to moderate. We hypothesized a long-term (1 year) positive impact of urban pedestrian signage on attendance of the general population, and on commitment to walk, motivation toward PA and in turn an improvement in cardiometabolic health indicators in the recruited population.

2 Methods

This study was approved by local ethic committee for non-interventional research of Grenoble Alpes University (CERNI; authorization number: 2013-03-19-11).

2.1 Experimental neighborhoods characteristics

This study was conducted in two neighborhoods of Grenoble city. One of these neighborhoods was equipped with the pedestrian signage (pedestrian signage neighborhood: PSN) whereas the other was not equipped (control neighborhood: CN). Those two neighborhoods were chosen by the Public and Environmental Health Direction of Grenoble and were similar. Indeed, the experimental districts are located in east-central part of the city and totalized at the beginning of the study an area of 1.15 km−2, (0.65 and 0.50 km−2 for PSN and CN, respectively). The total number of inhabitants was 9925 at that time representing 6.5% of the total population of Grenoble city (4423 and 4502 for PSN and CN, respectively). On a socio-economic point of view, these neighborhoods were similar too. For instance, the incomes of their inhabitants were lower compared to the Grenoble city general population (precarious situation: 32% and 34% for PSN and CN, respectively versus 20% for Grenoble city). Moreover, in these neighborhoods the education level was the lowest of Grenoble city.

2.2 Implementation of pedestrian signage

In 2013, the pedestrian signage was implemented in the city of Grenoble to encourage walking in the frame of the national campaign: “Moving 30 minutes per day, it’s easy!” led by the National Institute for Health Prevention and Education (INPES). Two hundred and seventy panels (length: 100 cm, height: 25 cm) indicating direction toward point of interest (e.g. station), place and travel time were installed in the city of Grenoble. One part of the signs was installed in the downtown area before the study. However, the PSN was equipped with this dispositive in May 2013 only.

2.3 Attendance study on general population

The attendance study was performed on general population by counting manually the number of passages on 4 crossroads (two in neighborhood with pedestrian signage, PSN and two in control neighborhood, CN) 4 times per week (Monday, Wednesday, Thursday and Saturday). The measurements were performed every 3 months (i.e., 5 measure occasions: March’13; June; September; December; March’14) between 1 PM and 5 PM from March 2013 to March 2014 by a licensed company (Alyce Sofreco, Lyon, France). The crossroads (chosen by the Public and Environmental Health Direction of Grenoble) had similar characteristics: proximity of bus stops, shops and number of inhabitants.

2.4 Impact of pedestrian signage in the recruited population in the studied neighborhoods

2.4.1 Subjects

We aimed to specifically recruit 140 subjects (preferably of low to moderate socio-economic status) in these two neighbourhoods (pedestrian signage group: PSG; control group: CG). These subjects were proposed to participate in a follow-up of their health during one year.

Inclusion criteria were the following: male or female subjects older than 40 years (because of greater cardiometabolic and leisure inactivity risks), inactive during leisure time (i.e. less than 1 hour/week of moderate intensity leisure PA which corresponds to an intensity at the limit of breathlessness), but able to walk. Recruitment was performed by identifying persons older than 40 years from electoral lists on a drawing of lot basis (Dwyer et al., 2011). Once identified, they were contacted by phone to check their eligibility for the study and to get their informed consent if they were willing to volunteer. In case of non-inclusion, we proceeded to new drawing lots with the goal to recruit 70 subjects by neighborhood, corresponding to the sample size calculated to provide a 4% increase in attendance in prompt of decision studies (Centers for Disease Control and Prevention, 2011). The recruitment period lasted 3 months. Owing to the difficulties to recruit 70 participants by neighborhood, the recruitment strategy was changed: ∼2000 brochures dropped out in mail-boxes, ∼1500 phone calls to potential participants and ∼2800 letters sent. A communication campaign on the usefulness of this device by the city of Grenoble (local TV channel, displays in bus shelters) followed baseline assessment of the recruited people.

To ensure the equivalence between these two small sub-samples, anthropometric characteristics were measured: height, weight, BMI, waist circumference, hip circumference and waist to hip ratio. The follow up of cardiometabolic health of participants was proposed using simple indicators.

In order to prevent bias linked to eventual modifications of walking behavior, the main goal of the study was not disclosed (influence of pedestrian signage on walking activity). The participants were informed that they were involved in a study following the general health of Grenoble citizens.

2.4.2 Experimental design

The total involvement of the participants in the study was 12 months (from Mars 2013 to June 2014). Walking activity level was evaluated every 3 months (March’13; June; September; December; March’14) during one week. The anthropometric and cardiometabolic variables were measured at the beginning and at the end of the study. The motivation toward PA was assessed at the beginning, after 6 months and at the end of the study.

2.4.3 Walking activity level

The objective walking activity level of the participants was assessed by pedometry using the YamaxDigi-Walker CW700 pedometer (Yamax Corp., Tokyo, Japan). This validated device (Schneider, Crouter, & Bassett, 2004) (worn on belt) provided and stored for 7 days (allowing control of the activity of the participants) steps number, expended calories, time of activity and distance measured with an accuracy of 98.5%. The participants were asked to wear the pedometer for 7 typical consecutive days every 3 months except for showering or engaging in any activity in wet environment (e.g. swimming). At each visit, every 3 months participants were asked about the occurrence of events that could interfere with the practice of walking or their health (e.g., new job, injury, illness, born of children, grandchildren…).

Participants were not aware that the device was designed to measure walking activity in order to avoid bias. They were informed that the monitor measured the hip movements helping to predict the risk of hip osteoarthritis. In order to mask the information displayed by the pedometers which could encourage participants to walk more (Bravata et al., 2007), the screen of the pedometers was masked with tape.

2.4.4 PA motivation questionnaire

The measure of motivation for active transport participation (walking/biking) was based on the Self-Regulation Questionnaire for exercise (SRQ-E; Ryan and Connell, 1989), with the amotivation scale added from the Sport Motivation Scale (Pelletier et al., 1995). This tool includes 16 items and assesses the multifaceted motivational regulations proposed by SDT. The participants responded to items reflecting intrinsic motivation (e.g., “walking/cycling is fun”), identified regulation (e.g., “I feel like it’s the best way to help myself”), controlled regulation (e.g., “I feel like I have to use an active transport mode”), and amotivation (e.g., “I don’t know, I can’t see what I gain when I am walking/biking”). Each item was rated on a 7-point Likert scale ranging from 1 (not true at all) to 7 (very true). The questionnaire was administered at the beginning, after 6 months and at the end of the study. In this study, all sub-scales had adequate Cronbach alphas ranged from 0.79 to 0.84. Thus, the average of the items on each sub-scale was used for our analysis.

2.4.5 Anthropometric measures and cardiometabolic health indicators

We chose these measurements since they are associated with the cardiometabolic syndrome and cardiovascular risk (Alberti, Zimmet, & Shaw, 2005) and they are modifiable by regular walking (Li & Siegrist, 2012). Hence in the present study, they were expected to objectify an effect of pedestrian signage on walking activity. They consisted in measuring body weight (in light clothing and without shoes), height (and BMI) waist circumference (taken at midway between the lowest rib margin and the iliac crest), hip circumference (taken at the widest level over the greater trochanters), blood pressure (3 measures separated with 1-minute rest were taken using M6 Comfort automatic blood pressure monitor, Omron Healthcare Co., Ltd., Kyoto, Japan; after having the participant seated quietly for 5 minutes). The results of lipid profile (total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides) and glycaemia at the beginning of the study and 12 months after were obtained from the participants. We estimated the ten-year risk of fatal cardiovascular disease with the online HeartScore version of SCORE risk charts (Systematic COronary Risk Evaluation; Conroy et al., 2003; European Society of Cardiology).

2.4.6 Pedestrian signage questionnaire

To evaluate the recognition and visibility of pedestrian signage implemented in the city, the participants responded to three questions one year after their inclusion in the study: 1) “In the past year, do you remember seeing the pedestrian signage placed in the city streets”?; 2) “Do you think that you are concerned by this signage”?; 3) “Do you think that the signage has encouraged you to walk more/will encourage you to walk more in the future”?

2.4.7 Statistical analysis

Results are expressed as mean ± standard deviation. The statistical analysis was performed using statistical software STATISTICA version 6 (StatSoft France 2004, www.statsoft.com). Normality was assessed using tests of Skewness and Kurtosis and equality of variance was assessed by Levene’s test. Differences between groups were examined over time using two-way (group × time) repeated measure ANOVA, followed by student’s t-test with a Bonferroni correction for multiple comparisons in case of significance. Effect sizes (Cohen’s d) were calculated using the online software available at: http://www.danielsoper.com/statcalc3/. A P < 0.05 level of statistical significance was used for all analyses.

3 Results

3.1 Attendance assessed on general population

In average, for each time point, the attendance (average passage number on all crossroads in each neighborhood) was greater in the pedestrian signage neighborhood (March’13: 435 ± 261 vs. 321 ± 118; June: 392 ± 181 vs. 303 ± 124; September: 453 ± 186 vs. 256 ± 95; December: 541 ± 279 vs. 282 ± 156; March’14: 486 ± 283 vs. 252 ± 119 for PSN and CN, respectively) but did not reach statistical significance (ANOVA group factor: F(1, 10) = 1.87; p = 0.22). There were no major changes observed in the number of passages between the two groups at any time point. The attendance in PSN was significantly greater in December than in June (ANOVA interaction effect F(4,40) = 3.24; p = 0.03; effect size: 0.5; p < 0.05; Fig. 1).

thumbnail Fig. 1

Mean attendance in PSN and CN on weekdays (Monday, Wednesday, Thursday) (a) and on weekend day (Saturday) (b), and mean attendance on weekdays and weekends (c); * p < 0.05 between June and December for PSN.

3.2 Impact of pedestrian signage in the recruited population in the studied neighborhoods

3.2.1 Recruitment

Only forty-two participants (17 men and 25 women) were recruited from 2 neighborhoods (PSG: n = 22; CG: n = 20) presenting the same characteristics (area, number of citizens) and noticeably low to moderate socio-economic levels (imposed by the Public and Environmental Health Direction of Grenoble city based on a report dealing with social needs of Grenoble citizens). One of these two districts was equipped with pedestrian signage (recruited pedestrian signage group: PSG, n = 22; 8 men and 14 women), while the other was not (recruited control group: CG, n = 20; 9 men and 11 women). The main characteristics of the recruited subjects are presented in Table 1.

Table 1

Anthropometric characteristics, indicators of cardiovascular health and motivation.

3.2.2 Socio-demographic characteristics of the recruited participants

Among the participants, there were 25 retired (PSG: 14; CG: 11), 15 professionally active (PSG: 7; CG: 8) and 2 housewives (PSG: 1; CG: 1), 24 had higher education level (PSG: 15; CG: 9), 14 secondary education level (PSG: 5; CG: 9) and the 4 remaining subjects did not give any answer to this question. Walking was the main way of locomotion for 8 subjects (PSG: 4; CG: 4), whereas for 17 participants (PSG: 9; CG: 8) it was walking combined with public or individual transport (e.g. bus, car, bike). The other 17 participants did not use walking as a transport mode at all.

3.2.3 Anthropometrics of the recruited participants

There were no significant differences (Tab. 1) in: age, height, weight or BMI between both groups before (pre) and at the end of the study (post).

3.2.4 Walking activity level: (pedometry) of the recruited participants

Table 2 presents the daily steps number measured by pedometry. Although greater in average over the year in the CG, the number of steps/day did not significantly differ between the groups at any time measurement (Tab. 2). Moreover we did not observe any time effect. The analysis of the daily steps number of the participants that use other modes of transport than walking (17 participants, 9 in PSG and 8 in CG) showed no significant differences between the measurement points (ANOVA interaction effect: F(4,60) = 1.65; p = 0.19).

Table 2

Walking activity level measured by pedometry during weekdays (Monday to Friday) and weekend days (Saturday and Sunday).

3.2.5 Cardiometabolic health

Neither anthropometric characteristics nor indices of cardiometabolic indicators differed between groups and between the different measure points (pre vs. post) for a given group (Tab. 1).

3.2.6 Motivation for PA

The level of autonomous motivation was high, and that of controlled motivation was low before, during (results not presented) and at the end of the study but it did not differ between groups (Tab. 1).

3.2.7 Pedestrian signage questionnaire

In both groups, the majority of the participants indicated that they did not see the pedestrian signage in the city (PSG: 15; CG: 12) and the other 12 participants (PSG: 7; CG: 5; 3 participants in CG did not respond to this questionnaire) acknowledged the presence of the panels in the city (Fig. 2). Although, the majority of the participants felt concerned by those signs (PSG: 12; CG: 12 vs. 15 not concerned: PSG: 10; CG: 5) they have not been encouraged/will not be encouraged to walk more (PSG: 9; CG: 8). Only 5 participants reported that the panels had or can have an influence on their behavior (PSG: 3; CG: 2; results not shown), but no such change was observed.

thumbnail Fig. 2

Results of pedestrian signage questionnaire. MD: missing data.

4 Discussion

The present study firstly assessed the impact of pedestrian signage on general population of Grenoble city by measurement of the attendance over one year on two important crossroads in a neighborhood equipped with pedestrian signage compared to another non-equipped. Secondly, we tried to study the receptiveness (impact on walking activity and consequences on cardiometabolic health and motivation toward PA) to this pedestrian signage of low to moderate socioeconomic status Grenoble citizens living in this neighborhood. For this purpose, we tried to recruit and study the latter population longitudinally.

The first part of our study showed a transitory increase in attendance by general population in the equipped neighborhood between June and December not sustained in the long-term.

In the second part of the study, we failed to include low to moderate socio-economic citizens. The number of subjects recruited was well below that needed to get a statistical power of 80%. Moreover, 70% of the recruited subjects did not see the pedestrian signage. This sample did not change its walking activity level, cardiometabolic risk as well as PA motivation.

4.1 Attendance study on general population

The lack of long-term effect of the pedestrian signage on attendance could be contrasted with classical studies performed in the field. Indeed, according to literature studying the effect of similar devices, an overall median increase of 161% in the number of walkers has been reported (Heath et al., 2006). However, the majority of the studies performed in this field report acute/very short-term effects as in prompt of decision studies. Hence, our study questions the efficiency of such devices on the long-term. Indeed, the methodology we used to assess effectiveness is original since we repeat evaluation over one year. In our opinion, it is the best way to conclude on the definitively real efficiency of a device and overall to quantify it. However, it would have been more relevant to increase the period measurement over one complete day. Indeed, for financial reasons, the attendance has been measured only in the afternoon.

The transitory effect on attendance we observed in the PSN is, however, encouraging and suggests a possible positive effect of the pedestrian signage. Hence, we cannot totally exclude the effectiveness of such a device. One may wonder why the potential positive effect of pedestrian signage is only observed particularly on the weekend day (the Saturday) between June and December.

Since the attendance was greater in December for a rather less favorable whether compared to spring or summer; this result does not seem to be due to a seasonal effect. This is opposed to a recent meta-analysis performed on the level of PA in general population (McGrath, Hopkins, & Hinckson, 2015). However, it has been reported in elderly women that physical activity level is similar between the seasons (winter vs. summer) (Lawlor, Taylor, Bedford, & Ebrahim, 2002). Moreover, the attendance did not decrease in the control neighborhood. It could be supposed that the increased attendance observed in PSN was linked for instance to Christmas preparation (gifts shopping). Of note, in average, for each time point, the attendance was greater in the pedestrian signage neighborhood but this difference did not reach statistical significance. However, since this non-significantly difference seems to exist in March 2013, just before the installation of signage, we cannot exclude a crossroad effect i.e. more frequented crossroads in PSN than in CN. But since, the attendance is increased between June and December in PSN whereas it remained stable in CN this hypothesis appears unlikely.

4.2 Impact of pedestrian signage in the recruited population in the studied neighborhoods

Owing to infrequent use of standardized measures in the field of urban environment (Sallis et al., 2016) and the need of objective measures of PA (McGrath et al., 2015), the present study attempted to evaluate long-term effects (1 year) of pedestrian signage on the attendance of general population. In addition, we evaluated the effect of this pedestrian signage on walking activity level, motivation toward PA and cardiometabolic health indicators of a sample of Grenoble citizens living in a low to moderate socio-economic district. We assessed daily steps counts using pedometer, which is considered as a good correlate of objective PA induced by built environment (Ding, Sallis, Kerr, Lee, & Rosenberg, 2011). In addition, the impact of such a device on cardiometabolic health indicators and on motivation toward PA was assessed. The follow up of long-term effects constitutes the originality of our study as underlined previously and obviously the main difficulty of this ambitious study since generally the approach to assess the efficiency of urban environment is correlational by nature (Sallis et al., 2016).

The main difficulty of our study was the participants’ recruitment, especially in the targeted population by Public and Environmental Health Direction of Grenoble city. Yet, we visited regularly (2–3 times/week) social centers in order to recruit participants with low to moderate socio-economic status. This observation confirms the difficulty to commit people with low to moderate socio-economic status in healthy behaviors, justifying the priority to increase health risk prevention in this population (Sallis et al., 2016; Salmon, Owen, Bauman, Schmitz, & Booth, 2000). To encourage people with lower education level and with low to moderate socioeconomic status to increase their PA participation it is important to find adequate promotional strategies. For instance, an important communication on the potential health effects of such a device and the importance of healthy behaviors could be proposed in the future.

Consequently, owing to recruitment difficulties, only 42 participants were included leading to underpowering of this study. The main reasons of this non-participation were lack of interest, time, gratification for participation, personal issues, health issues or too good health.

The main characteristics of the recruited participants were the following: most of them were about 60 years old, women, retired, in good health, with high education level and with a better socio-economic status compared to the population targeted for this study.

Walking activity (measured with pedometry) and cardiometabolic health indicators did not differ between the groups at any time point (no interaction effect). Based on this result, we could not confirm the efficiency of the pedestrian signage in the experimental sample of Grenoble citizens. As stated above, the lack of difference might have been due to insufficient sample size. However, such a hypothesis is very difficult to sustain owing to the insignificant variation of daily steps counts and cardiometabolic indicators along the year whatever the group considered. As shown in Table 2, the mean numbers of steps achieved at baseline by participants were slightly greater than those of the French population around 65 years of age (week: 5850 steps/day; weekend: 5751 steps/day) at the time of our study (Assureurs Prévention, 2013). However, the participants could be categorized as low active taking into account the minimum amount of 7500 steps/day to get health benefits (Tudor-Locke et al., 2011). Hence, despite normal healthy status, they do not seem to have the appropriate behavior regarding walking activity. It might have been expected that pedestrian signage associated to health messages have induced healthy behaviors regarding physical activity other than walking. However, despite a high level of autonomous motivation, participants did not report involvement in other physical activities (results not shown).

In the same way, cardiometabolic health indicators were in the normal range values indicating that the participants were in rather good health and had low cardiometabolic risk. Hence, the participants’ relatively high level of PA (compared to French general population) and good health at baseline could have explained the lack of change.

The evaluation of motivation’s type showed that the participants of our study had a high baseline level of autonomous motivation. These results were not different in the two groups and they were stable throughout the study. This result could confirm the relationship between high level of autonomous motivation and regular PA participation (for review see Hagger & Chatzisarantis, 2007).

The absence of behavior change can be explained by the lack of relevance of pedestrian signage regarding participants’ answers to the questionnaire. In this study, 70% of participants declared they had not seen the pedestrian signage in the city. Perception and acceptability of this pedestrian signage have been also evaluated in 2012 (Maffei, 2012). The main results of this survey showed that 1) less than 20% of responders have seen this signage placed in the city, and 2) the panels were easy to understand but were not visible enough. The present study confirmed previous results: the pedestrian signage was not spotted enough in this urban environment. Thus, the location and/or the design of the pedestrian signage need to be thought again. This confirms the literature stating the need to make a high effort of communication to increase the effect of the urban environment on behavior change (Starnes, Troped, Klenosky, & Doehring, 2011).

Interestingly, this study allows identifying a group of participants conscious and sensitive to health problems and their prevention. Indeed, we recruited more elderly women, retired, with a high level of education, in good health with a better socio-economic status compared to the population targeted for this study, with high autonomous motivation toward PA. Since, it has been shown such a group is more prone to adopt healthy behaviors (Lawlor et al., 2002). This group might use this pedestrian signage if combined with a good communication.

4.3 Perspectives

Despite the lack of long-term effects of pedestrian signage on a sample of Grenoble citizens, we observed with more traditional evaluation a transitory greater attendance in the pedestrian signage neighborhood over one year compared to the control neighborhood. Moreover, attendance increased between June and December only in PSN. These results which need confirmation suggest the potential efficiency of pedestrian signage. Considering the difficulties to recruit population and the need to prevent/treat health problems, one perspective of our approach could be to target specific groups of persons e.g. with low to moderate socio-economic status, retired or with chronic diseases with a huge specific communication on the interest of pedestrian signage to assess the real impact of this device on health (secondary prevention).

5 Conclusion

Despite a slight transitory effect on attendance assessed with more traditional method, which needs to be confirmed, this study failed to show an effect of pedestrian signage on long-term objectively measured walking activity (pedometry), cardiometabolic indicators and motivation toward PA in a sample of recruited citizens. Low sample size not representative of the targeted population of neighborhood, fair level of PA, high autonomous motivation toward PA, and good health at baseline could explain in part these results. However, the lack of visibility of the panels is also an important result to consider, and suggests that the device must be more largely communicated (Starnes et al., 2011).

Finally, the originality of this study was to triangulate a traditional evaluation (attendance study) with objective measures (pedometry, cardiometabolic indicators) and self-reported measures (pedestrian signage and motivation questionnaires).

Funding source

This study was supported by a grant from Institut National de Prévention et d’Éducation pour la Santé and the city of Grenoble.

Acknowledgements

The authors thank the Public and Environmental Health Direction of Grenoble town for their logistic and administrative support.

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Cite this article as: Borowik A, Tessier D, Guinot M, & Flore P (2019) Evaluation of long-term effect of pedestrian signage with time travel indication in Grenoble city (France). Mov Sport Sci/Sci Mot, 106, 7–17

All Tables

Table 1

Anthropometric characteristics, indicators of cardiovascular health and motivation.

Table 2

Walking activity level measured by pedometry during weekdays (Monday to Friday) and weekend days (Saturday and Sunday).

All Figures

thumbnail Fig. 1

Mean attendance in PSN and CN on weekdays (Monday, Wednesday, Thursday) (a) and on weekend day (Saturday) (b), and mean attendance on weekdays and weekends (c); * p < 0.05 between June and December for PSN.

In the text
thumbnail Fig. 2

Results of pedestrian signage questionnaire. MD: missing data.

In the text

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