Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK

Keywords Air pollution, clean air zone, low emission zone, attitudes, acceptability, travel behaviour, urban, ethnicity ALL Metrics - Views Downloads How to cite this article Mebrahtu T, McEachan RRC, Knamiller C et al. Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.13730.2) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente Select a format first ▬ ✚ Research Article Revised Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved] Teumzghi Mebrahtu https://orcid.org/0000-0003-4821-2304 1, Rosemary R. C. McEachan https://orcid.org/0000-0003-1302-6675 1,2, Cathy Knamiller https://orcid.org/0009-0002-5456-6918 1, Gillian Santorelli1, Rumana Hossain1, Maria Bryant https://orcid.org/0000-0001-7690-4098 3,4Teumzghi Mebrahtu https://orcid.org/0000-0003-4821-2304 1, Rosemary R. C. McEachan https://orcid.org/0000-0003-1302-6675 1,2, [...] Cathy Knamiller https://orcid.org/0009-0002-5456-6918 1, Gillian Santorelli1, Rumana Hossain1, Maria Bryant https://orcid.org/0000-0001-7690-4098 3,4 PUBLISHED 17 Mar 2025 Author details Author details 1 Bradford Teaching Hospitals NHS Foundation Trust, Bradford Institute for Health Research, Bradford, England, BD9 6RJ, UK 2 Population Health Improvement UK, UK, UK 3 Hull York Medical School, Hull, England, UK 4 University of York Department of Health Sciences, York, England, YO10 5DD, UK 2 Population Health Improvement UK, UK, UK 3 Hull York Medical School, Hull, England, UK 4 University of York Department of Health Sciences, York, England, YO10 5DD, UK Teumzghi Mebrahtu Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Rosemary R. C. McEachan Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing Cathy Knamiller Roles: Conceptualization, Investigation, Project Administration, Writing – Review & Editing Roles: Conceptualization, Investigation, Project Administration, Writing – Review & Editing Gillian Santorelli Roles: Data Curation, Funding Acquisition, Supervision, Writing – Review & Editing Roles: Data Curation, Funding Acquisition, Supervision, Writing – Review & Editing Rumana Hossain Roles: Investigation, Project Administration, Writing – Review & Editing Roles: Investigation, Project Administration, Writing – Review & Editing Maria Bryant Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing OPEN PEER REVIEW REVIEWER STATUS Despite the popularity of low emissions zones (LEZ) across Europe their public acceptability and impact on travel behaviours are scarcely studied. We aimed to explore changes in acceptability, perceptions of air quality, and travel behaviours in a multi-ethnic sample living in Bradford, UK after the implementation of a Clean Air Zone (a type of LEZ). Telephone, in-person and online surveys were conducted one year pre- and one year post implementation. Participants included members of the representative Born in Bradford (BiB) cohort and members of the general public. A repeated cross-sectional analysis explored changes in responses between baseline and follow-up questions using chi-square tests and tests of proportions. Multinomial regressions explored whether socio-demographic variables were associated with changes in attitudes longitudinally. A total of 1,949 and 2,085 individuals participated in the baseline and follow-up surveys; 814 participants completed both. Participants were mostly female, aged 35–44. Half were white British, and 30% of Pakistani origin. The majority of participants supported the clean air zone at follow-up (59–64%), although these figures were lower than at baseline (by 4.9% for BiB families and 10.8% for members of the general public). A third indicated high concern about air quality (34–38%). Personal travel behaviours showed little variation pre to post implementation. On the whole, attitudes of those completing both surveys remained stable, and there were no systematic relationships between socio-demographic variables and whether attitudes worsened or became more positive. Whilst CAZ support remained high, we observed small decreases in support after the CAZ implementation. As public acceptability is a key facilitator to the success of initiatives such as CAZ, a decrease in public support may threaten their sustainability. Communication about the need for CAZ, and demonstrations of their positive impact will be important to maintain levels of acceptability. This study looked at how people in Bradford, UK, felt about a new Clean Air Zone (CAZ) and if it changed how they travelled. A CAZ is an area in cities where older, more polluting vehicles are charged a daily fee to enter. They aim to reduce pollution. In Bradford, a CAZ was implemented in 2022 which charges older taxis, buses, vans and lorries, but does not charge people’s private vehicles. Researchers asked people living in Bradford questions one year before and one year after the CAZ was put in place to see what they thought about the CAZ, pollution in the city, and to ask about how they travelled about the city (for example, using private vehicles, public transport, or walking and cycling). A total of 1,949 people responded to the first questionnaire, and 2,085 to the second. Out of these, 814 people answered both times. About one-third of people were very worried about pollution. The number of people supporting the CAZ fell from about 70% before it was in place, to about 60% after it has been in place for a year. People did not change the way they travelled around the city after the CAZ was implemented, and generally attitudes remained similar before and after the CAZ was implemented. People’s backgrounds, for example their ethnicity, age and whether they lived in the CAZ zone didn’t seem to affect whether people’s opinions changes. The study suggests that to keep people supporting the CAZ, it's important to explain why it is needed and show its benefits. Air pollution, clean air zone, low emission zone, attitudes, acceptability, travel behaviour, urban, ethnicity Corresponding Author(s) Rosemary R. C. McEachan ([email protected]) Grant information: This project is funded by the National Institute for Health and Care Research (NIHR) under its Leadership in Applied Health Research and Care Yorkshire and Humber (Grant Reference Number NIHR200166) and by the Public Health Research Programme (Grant Reference Number NIHR128833). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2025 Mebrahtu T et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Mebrahtu T, McEachan RRC, Knamiller C et al. Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.13730.2) First published: 15 Nov 2024, 4:71 (https://doi.org/10.3310/nihropenres.13730.1) Latest published: 17 Mar 2025, 4:71 (https://doi.org/10.3310/nihropenres.13730.2) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We have restructured our findings and discussion to clarify the key messages. We have moved some tables to an extended data repository and have added a new figure which summarise the key results of the multinomial regressions. We have restructured our findings and discussion to clarify the key messages. We have moved some tables to an extended data repository and have added a new figure which summarise the key results of the multinomial regressions. See the authors' detailed response to the review by Yifu Ou See the authors' detailed response to the review by Christian Oltra Air pollution is a major environmental health risk and is associated with 6.7 million premature deaths annually worldwide (World Health Organisation, 2021). Deaths due to air pollution exposure in Europe alone costs around $1.4 trillion per year (United Nations, 2015). A total of 64,000 deaths occur due to air pollution in the UK every year (Lelieveld et al., 2019), costing the country $83 billion a year (World Health Organisation, 2015). Around 64% of the exceedance of air quality standards in Europe are caused by traffic pollution (European Environment Agency, 2022). To counter this, urban vehicle access regulations have been introduced in many cities across Europe (CLARS, 2023). One example of how these are operationalised is via low emission zones (LEZ), where the most polluting vehicles have restricted access to certain areas (CLARS, 2023). LEZ are a popular solution to reduce outdoor pollution, with over 320 zones in place across EU member states by the end of June 2022 (Tiseo, 2023). LEZ are complex interventions, usually implemented as part of wider city or regional strategies which aim to reduce pollution but also encourage more sustainable and active travel modes (Tarriño-Ortiz et al., 2022). They provide a catalyst for the upgrading and retrofitting of existing vehicles to compliant standards, encourage the purchase of cleaner vehicles, and may also reduce numbers of vehicles driving in the zone. They are also thought to impact on peoples’ attitudes and behaviours by raising awareness of air quality issues, and thus encouraging people to use more sustainable travel options (McEachan et al., 2022; Public Health Scotland, 2023), although impacts on personal travel behaviour might be limited if LEZ do not target private vehicle use. While evidence of the impact of LEZ on health outcomes is emerging (Chamberlain et al., 2023), there is scant evidence exploring the impact of LEZ on other outcomes such as attitudes or personal travel behaviours. Despite their increasing popularity, LEZs can be controversial, due to a perception that they can disadvantage some communities (De Vrij & Vanoutrive, 2022), with many examples of LEZ being delayed or abolished following vocal public opposition (Morton et al., 2021). A recent study conducted in real time as a LEZ was being planned highlighted how local political opposition and conflicts serve to shape negative public discourse and polarise opinions, heightening tensions and reducing the confidence of local implementers (Knamiller et al., 2024). However, these ‘loud voices’ may not be representative of wider public opinion. A number of recent cross-sectional surveys exploring public’s acceptability of LEZ either pre (Mebrahtu et al., 2023; Player et al., 2023) or just after implementation (Oltra et al., 2021; Rizki et al., 2022; Tarriño-Ortiz et al., 2021) all reported finding majority support for a LEZ from the participants they surveyed. Perceptions of LEZ acceptability can vary by demographic factors, beliefs about efficacy of the schemes, personality traits, and the extent to which citizens are personally affected (Kowalska-Pyzalska, 2022; Player et al., 2023). Mebrahtu et al. (2023) found that concern about air quality and acceptability of a proposed LEZ was lower for more economically deprived and multi-ethnic populations in the City of Bradford, UK one year before its implementation. Within these communities, there had been concern that the introduction of a LEZ would disproportionately impact low-income families and thus exacerbate existing health inequalities (Rashid et al., 2021). As public acceptability of LEZ is vital to their continued success, it is important to understand how attitudes and acceptability may change after implementation, and whether changes vary by key socio-demographic characteristics. However there have been no studies which have explored changes in attitudes longitudinally after a LEZ had been implemented. In terms of the impact of LEZ on travel behaviours, a descriptive analysis of the London Ultra Low Emission zone one year post implementation concluded that there was a 5% reduction in all vehicles in the zone, and 3% reduction in traffic flows (Mayor of London, 2023). Tarriño-Ortiz et al. (2022) reported a 28% reduction in self-reported car use, and 8% increases in reports of public transport and active travel in a cross-sectional sample of 799 residents after the implementation of the Madrid Central LEZ. In the same context, Gonzalez et al. found that evidence that the Madrid LEZ, combined with parking restrictions encouraged a shift to more sustainable behaviour (Gonzalez et al., 2023). However, like the studies on attitudes reported above, there has been no longitudinal study tracking changes in travel behaviour pre and post implementation of a LEZ. In the UK, a number of Clean Air Zones (CAZ, a type of LEZ) have been implemented in urban areas as part of the Government’s Clean Air Framework policy (Department of Transport, 2021a). The aim of the current study was to explore changes in acceptability, attitudes towards air quality and travel behaviours of residents one year after a CAZ had been implemented in a large Northern UK City. We also aimed to explore whether any changes in ratings of acceptability of the CAZ and attitudes towards air quality were related to key socio-demographic characteristics. A pollution research advisory group was formed including 12 members of the general public living within the CAZ boundary in Bradford. They met regularly throughout the duration of the study to provided advice on all aspects of the wider study (McEachan et al., 2022). For the current study, they gave specific feedback on the wording of participant information sheets and content of questionnaires, and have helped to interpret key findings. This study was part of a wider evaluation of the heath and economic impacts of a Clean Air Zone (CAZ) which was implemented in the city of Bradford, UK, in September 2022 (McEachan et al., 2022). We conducted a population-based survey prior to, and 12 months after the launch of the CAZ. The first survey was conducted between April 2021 and December 2021 (previously reported in Mebrahtu et al., 2023). The second survey was conducted one year after the CAZ implementation (between July – November 2023) and included both participants who responded to the first survey, and additional participants responding to the second survey only. The study thus includes a longitudinal and repeated cross-sectional element. Bradford is the fifth largest metropolitan district in England, with a population of over 546,000 (Office of National Statistics, 2022). Residents of the city are predominantly of white British (57%) and Pakistani origin (25%) (Bradford Metropolitan District Council (BMDC), 2022). A third of the population live in the most deprived Index of Multiple Deprivation (IMD) decile according to England averages (Bradford Metropolitan District Council (BMDC), 2019). The city has higher than average levels of respiratory morbidity (Mebrahtu, 2015; Mebrahtu et al., 2016; Mebrahtu et al., 2015). It is home to the representative longitudinal Born in Bradford (BiB) birth cohort, which recruited 12,453 mothers, with 13,776 pregnancies and 3,448 partners between 2007–2011; 42% of the BiB cohort are of Pakistani origin and 37% are of White British origin (McEachan et al., 2024). In 2018, the UK government identified Bradford as exceeding legal limits of pollutants at several parts of the city and directed the local authority to develop and implement a charging Clean Air Zone as part of a wider plan to tackle pollution (McEachan et al., 2022). The resulting Bradford Clean Air Plan included a Class C CAZ, where non-compliant buses, coaches, heavy goods vehicles, vans, minibuses, taxis and private hire vehicles are charged a daily fee to enter the zone. Private vehicles are not charged (McEachan et al., 2022). Details of baseline survey recruitment are reported in detail elsewhere (Mebrahtu et al., 2023). Eligible participants were either i) participants of the BiB cohort or ii) members of the general public. Our baseline sample included 1137 BiB participants and 812 members of the general public who completed the survey online, via telephone or via post. For the follow-up survey we recontacted all baseline BiB participants, and the general public participants who had provided contact details (N=340) via email (asking participants to complete an online survey) or telephone interview. These participants’ questionnaires were given a unique ID code which allowed baseline and follow-up surveys to be matched. To boost the sample at follow-up, we recruited additional members of the general public online via a survey link which was distributed widely via online mailing lists. We also publicised the link in person via pop-up stands in three local hospital sites, 9 general practice sites, and at 12 community events (e.g. park fun days). See Figure 1. Three categories of variables were collected: 1) attitudes towards the CAZ, 2) air quality perceptions, 3) travel behaviours, see Table 1. Demographic data were already available for the BiB families. We asked members of the general public to complete demographic questions; however, in order to maximise completion rates, these questions were not mandatory and were located at the end of the questionnaire. | Item | Information collected | Categories | Simplified categories for longitudinal sample | |---|---|---|---| | Perception of CAZ | 1. Do you think the Clean Air Zone is a good idea? | Three (yes, no, and don’t Know) | No change | | 2. To what extent do you agree or disagree that the Clean Air Zone covers the right areas of Bradford? | Five (strongly agree, agree, neither agree nor disagree, disagree, and strongly disagree) | Three (Agree [strongly agree/agree]; Neutral [neither agree nor disagree]; Disagree [Strongly disagree/Disagree]) | | | 3. How much do you agree or disagree with the following statement: the CAZ will improve the health of my family/community? | Five (strongly agree, agree, neither agree nor disagree, disagree, and strongly disagree) | Three (Agree [strongly agree/agree]; Neutral [neither agree nor disagree]; Disagree [Strongly disagree/Disagree]) | | | Perception of air quality | 1. What do you think about the air quality in Bradford generally? | Five (very poor, poor, fair, good, and excellent) | Two (Negative [very poor/poor]; Positive [fair/ good/excellent]) | | 2. How do you think this compares to other parts of the UK? | Four (don’t know, better, about the same, and worse) | No change | | | 3. How concerned are you about air quality in Bradford? | Six (not at all concerned, slightly concerned, somewhat concerned, moderately concerned, extremely concerned, and don’t know) | Four (Not concerned [Not at all concerned]; Some concern [slightly/somewhat concerned]; Moderate to high concern [moderately concerned and extremely concerned]; Unsure [Don’t know]) | | | 4. Do you think other people in Bradford are concerned about air quality? | Six (not at all concerned, slightly concerned, somewhat concerned, moderately concerned, extremely concerned, and don’t know) | Four (Not concerned [Not at all concerned]; Some concern [slightly/somewhat concerned]; Moderate to high concern [moderately concerned and extremely concerned]; Unsure [Don’t know]) | | | 5. How important do you think it is to improve air quality? | Six (not at all important, slightly important, somewhat important, moderately important, extremely important, and don’t know) | Two (Less important [not all important/slightly important/somewhat important]; More important [moderately important/extremely important] | | | Mode of travel | 1. How does the main earner get to work? | Three (public (bus, taxi, and train), private (petrol/diesel car/van and electric/hybrid car), and active travel (bicycle and walking)) | Not included in multinomial regressions | | 2. How do your children normally travel to school now | Three (public (bus, taxi, and train), private (petrol/diesel car/van and electric/hybrid car), and active travel (bicycle and walking)) | Not included in multinomial regressions | | | 3. How did you normally travel around Bradford District for things other than getting to work or school? | Three (public (bus, taxi, and train), private (petrol/diesel car/van and electric/hybrid car), and active travel (bicycle and walking)) | Not included in multinomial regressions | | | 4. How often do you use your car for journeys of 0.5 miles or less? 0.5 miles is roughly the distance of a 10-minute walk | Six (never, rarely, sometimes, Often, All the time, and not applicable) | Not included in multinomial regressions | | | Demographicsa | Age (in years) | Six (18–24, 25–34, 35–44, 45–54, 55–64, and 65+) | Three (18–34; 35–44; 45+) | | Ethnicity | Three (White British, Pakistani- origin and Other) | No change | | | Gender | Four (male, female, prefer to use own term, and prefer not to say) | No changec | | | Bradford Index of Multiple Deprivation (IMD)b | Five (quintile 1, quintile 2, quintile 3, quintile 4, and quintile 5) | No change | | | CAZ boundary | Two (inside and outside) | No change | Notes: a demographics were obtained from existing information for BiB families, and were self-reported by members of the general public; b As there is limited variation in IMD score for Bradford (42% in most deprived quintile) we present the equivalised score using Bradford addresses; c Male and female were the only recorded responses in the longitudinal sample First, sociodemographic characteristics of participants were tabulated and descriptively summarised. Individual items for perceptions of air quality, perceptions of the CAZ and travel mode behaviour were also summarised descriptively. Comparisons between the cross-sectional baseline and follow-up responses were made using chi-square tests and tests of proportions. We identified differences between patterns of responses for the two samples (BiB vs general public) in the baseline sample, and thus, for the repeated cross-sectional analysis, we report BiB participants and members of the general public separately. To explore changes in attitudes towards the CAZ and perceptions of air quality (i.e., longitudinal analysis), response options were re-categorised to simplify interpretation of results (Table 1, final column). Multi-collinearity was first assessed by running a series of ordinary logistic least square regressions of each independent variable against all other variables. The mean variance inflation factor for all regressions was <2, indicating limited risk of multi-collinearity between the independent variables. Multinomial regressions, which are appropriate for multi-category outcomes, were used to explore whether changes in attitudes (reference: no change) were associated with demographic factors including ethnicity (white British[reference], Pakistani origin, other), sex (male[reference], female), Age (18–34[reference], 35–44, 45+), and Bradford IMD quintile (reference IMD 1 – most deprived) and whether respondents lived inside (reference) or outside the CAZ zone. Analyses were conducting using the mlogit command in Stata (v17 Statacorp 2023). The analyses were based on those who provided complete data (i.e., complete case analysis). A total of 1,949 (BiB families=1,137; general public=812) and 2,085 (BiB families=640; general public=1,445) individuals participated in the baseline and follow up surveys, respectively. Demographic data were available for most of the BiB families but were missing for a substantial proportion of the general public sample (Table 2). BiB participants were predominately female (90% baseline, 92% follow-up), aged 35–54 (88% baseline, 85% follow-up). At baseline, 44% were of white British origin and 38% were of Pakistani origin. At follow up, these figures were 49% and 32% respectively. Around a quarter lived within the CAZ boundary at baseline and follow-up. At baseline, 42% lived in the most deprived quintiles in Bradford, compared with 35% at follow-up. | BiB families | General public | Longitudinal sample (N=814)a | ||| |---|---|---|---|---|---| | Baseline (N=1,137), n (%) | Follow up (N=640), n (%) | Baseline (N=812), n (%) | Follow up (N=1,445), n (%) | || | Age (in years) | ||||| | 18–24 | 0 (0.0) | 0 (0.0) | 48 (5.9) | 57 (3.9) | 8 (1.0) | | 25–34 | 110 (9.7) | 63 (9.8) | 115 (14.2) | 236 (16.3) | 89 (10.9) | | 35–44 | 629 (55.3) | 341 (53.3) | 173 (21.3) | 212 (14.7) | 382 (46.9) | | 45–54 | 370 (32.5) | 207 (32.3) | 130 (16.0) | 115 (8.0) | 249 (30.6) | | 55–64 | 21 (1.9) | 12 (1.9) | 97 (12.0) | 92 (6.4) | 47 (5.8) | | 65+ | 0 (0.0) | 2 (0.3) | 89 (11.0) | 94 (6.5) | 33 (4.1) | | Missing | 7(0.6) | 18 (2.8) | 160(19.7) | 639 (44.2) | 6 (0.7) | | Ethnicity | ||||| | White British | 498 (43.8) | 314 (49.1) | 444 (54.7) | 436 (30.2) | 323 (39.7) | | Pakistani origin | 431 (37.9) | 204 (31.9) | 87 (10.7) | 274 (19.0) | 214 (26.3) | | Other | 170 (15.0) | 87 (13.6) | 82 (10.1) | 200 (13.8) | 261 (32.1) | | Missing | 38(3.3) | 35 (5.5) | 199(24.5) | 535 (37.0) | 16 (2.0) | | Gender | ||||| | Male | 104 (9.2) | 32 (5.0) | 214 (26.4) | 304 (21.0) | 105 (12.9) | | Female | 1026 (90.2) | 590 (92.2) | 418 (51.5) | 592 (41.0) | 701 (86.1) | | Prefer to use own term | 0 (0.0) | 0 (0.0) | 4 (0.5) | 8 (0.6) | 0 (0) | | Prefer not to say | 0 (0.0) | 0 (0.0) | 19 (2.0) | 22 (1.5) | 0 (0) | | Missing | 7(0.6) | 18 (2.8) | 157 (19.3) | 519 (35.9) | 8 (1.0) | | Bradford IMD | ||||| | Quintile 1 | 228 (20.1) | 105 (16.4) | 92 (11.3) | 224 (15.5) | 117 (14.4) | | Quintile 2 | 250 (22.0) | 120 (18.8) | 100 (12.3) | 229 (15.8) | 141 (17.3) | | Quintile 3 | 255 (22.4) | 137 (21.4) | 158 (19.5) | 279 (19.3) | 196 (24.1) | | Quintile 4 | 223 (19.6) | 146 (22.8) | 159 (19.6) | 218 (15.1) | 191 (23.5) | | Quintile 5 | 104 (9.1) | 78 (12.2) | 116 (14.3) | 149 (10.3) | 107 (13.1) | | Missing | 77 (6.8) | 54 (8.4) | 187 (23.0) | 346 (23.9) | 62 (7.6) | | CAZ boundary | ||||| | Inside | 297(26.1) | 148 (23.1) | 181(22.3) | 330 (22.8) | 208 (25.6) | | Outside | 768(67.5) | 446(69.7) | 544(67.0) | 904 (62.6) | 544 (66.8) | | Missing | 72(6.3) | 46 (7.2) | 87(10.7) | 211 (14.6) | 62 (7.6) | Where demographic data were reported for the general public sample, around half were female (52% baseline, 41% follow-up), two-fifths were aged 18–44 (41% baseline and 35% follow-up) and just over one-fifth reported living in the CAZ boundary (22% at baseline and 23% follow-up). At follow-up there was an increase in the proportion of Pakistani (19%) and other ethnic origin participants (14%) and more reported being living in the most deprived quintiles of Bradford (31% vs. 23% at baseline). See Table 2. Cross-sectional analysis: In our repeated cross-sectional data, acceptability of the CAZ at follow-up was lower for both BiB and general public samples than at baseline, see Figure 2. At follow-up, 64.2% of BiB participants, and 59.4% of general public participants said that they felt the CAZ was a good idea; (a drop of 4.9% (95% CI: -9.4 to -0.3%, and 10.8% (95% CI: -14.9 to -6.8%), respectively). Fewer participants reported that they felt the CAZ covered the right geographical areas (i.e., responded agree or strongly agree) with 28.6% of BiB participants (a reduction of 8.7%, 95% CI: -13.0 to -4.2%) vs 31.6% of general public participants agreeing or strongly agreeing (reduction of 8.0%, 95%CI: -12.1 to -3.8%). The numbers of respondents who agreed or strongly agreed that the CAZ would improve the health of their family or community also reduced. Agreement dropped by 13.4% for BiB participants (to 51.1%) and by 13% for general public participants (to 48%). See Table 3 and Figure 2. | BiB families | General Public | ||||| |---|---|---|---|---|---|---| | Baseline (N=1137) | Follow-up (N=640) | X2 p- value | Baseline (N=812) | Follow-up (N=1445) | X2 p- value | | | Do you think the Clean Air Zone is a good idea? | |||||| | Yes | 786 (69.1) | 411 (64.2) | 0.02 | 571 (70.3) | 859 (59.4) | <0.00 | | No | 108 (9.5) | 81 (12.7) | 109 (13.4) | 269 (18.6) | || | Don’t Know | 213 (18.7) | 96 (15.0) | 84 (10.3) | 146 (10.1) | || | To what extent do you agree or disagree that the Clean Air Zone covers the right areas of Bradford? | |||||| | Strongly Agree | 64 (5.6) | 15 (2.3) | <0.01 | 60 (7.4) | 63 (4.4) | 0.01 | | Agree | 360 (31.7) | 168 (26.3) | 261 (32.1) | 393 (27.2) | || | Neither Agree nor Disagree | 483 (42.5) | 313 (48.9) | 269 (33.1) | 525 (36.3) | || | Disagree | 125 (11.0) | 62 (9.7) | 106 (13.1) | 161 (11.1) | || | Strongly Disagree | 52 (4.6) | 28 (4.4) | 74 (9.1) | 133 (9.2) | || | How much do you agree or disagree with the following statement: the CAZ will improve the health of my family/community? | |||||| | Strongly Agree | 218 (19.2) | 68 (10.6) | <0.01 | 170 (20.9) | 255 (17.6) | <0.01 | | Agree | 515 (45.3) | 259 (40.5) | 326 (40.1) | 454 (31.4) | || | Neither Agree nor Disagree | 249 (21.9) | 175 (27.3) | 151 (18.6) | 278 (19.2) | || | Disagree | 63 (5.5) | 43 (6.7) | 67 (8.3) | 110 (7.6) | || | Strongly Disagree | 66 (5.8) | 44 (6.9) | 55 (6.8) | 162 (11.2) | || | What do you think about the air quality in Bradford generally? | |||||| | Excellent | 12 (1.1) | 2 (0.3) | 0.16 | 10 (1.2) | 50 (3.5) | <0.01 | | Good | 156 (13.7) | 78 (12.2) | 63 (7.8) | 211 (14.6) | || | Fair | 570 (50.1) | 292 (45.6) | 239 (29.4) | 536 (37.1) | || | Poor | 303 (26.6) | 192 (30.0) | 347 (42.7) | 392 (27.1) | || | Very poor | 83 (7.3) | 46 (7.2) | 150 (18.5) | 136 (9.4) | || | How do you think this compares to other parts of the UK? | |||||| | Better | 114 (10.0) | 49 (7.7) | 0.28 | 66 (8.1) | 163 (11.3) | <0.01 | | About the same | 466 (41.0) | 244 (38.1) | 266 (32.8) | 524 (36.3) | || | Worse | 294 (25.9) | 180 (28.1) | 381 (46.9) | 380 (26.3) | || | Don’t Know | 250 (22.0) | 130 (20.3) | 99 (12.2) | 253 (17.5) | || | How concerned are you about air quality in Bradford? | |||||| | Extremely Concerned | 136 (12.0) | 84 (13.1) | 0.08 | 262 (32.3) | 260 (18.0) | <0.01 | | Moderately Concerned | 205 (18.0) | 136 (21.3) | 175 (21.6) | 300 (20.8) | || | Somewhat Concerned | 310 (27.3) | 155 (24.2) | 152 (18.7) | 302 (20.9) | || | Slightly Concerned | 282 (24.8) | 156 (24.4) | 130 (16.0) | 208 (14.4) | || | Not at all Concerned | 123 (10.8) | 50 (7.8) | 74 (9.1) | 210 (14.5) | || | Don’t Know | 70 (6.2) | 28 (4.4) | 17 (2.1) | 43 (3.0) | || | Do you think other people in Bradford are concerned about air quality? | |||||| | Extremely Concerned | 34 (3.0) | 22 (3.4) | 0.13 | 54 (6.7) | 65 (4.5) | 0.55 | | Moderately Concerned | 141 (12.4) | 94 (14.7) | 138 (17.0) | 218 (15.1) | || | Somewhat Concerned | 302 (26.6) | 153 (23.9) | 201 (24.8) | 325 (22.5) | || | Slightly Concerned | 244 (21.5) | 151 (23.6) | 181 (22.3) | 303 (21.0) | || | Not at all Concerned | 133 (11.7) | 65 (10.2) | 120 (14.8) | 216 (14.9) | || | Don’t Know | 273 (24.0) | 122 (19.1) | 114 (14.0) | 199 (13.8) | || | How important do you think it is to improve air quality? | |||||| | Extremely Important | 733 (64.5) | 347 (54.2) | <0.01 | 568 (70.0) | 812 (56.2) | <0.01 | | Moderately Important | 185 (16.3) | 155 (24.2) | 107 (13.2) | 224 (15.5) | || | Neutral | 126 (11.1) | 56 (8.8) | 65 (8.0) | 123 (8.5) | || | Slightly Important | 45 (4.0) | 30 (4.7) | 43 (5.3) | 79 (5.5) | || | Not at all Important | 6 (0.5) | 5 (0.8) | 16 (2.0) | 67 (4.6) | || | Don’t Know | 33 (2.9) | 17 (2.7) | <0.01 | 8 (1.0) | 23 (1.6) | <0.01 | | How does the main earner get to work?* | |||||| | Public transport | 77 (6.8) | 70 (10.9) | 0.56 | 87 (10.7) | 180 (12.5) | 0. 1 | | Private transport | 734 (64.6) | 451 (70.5) | <0.01 | 386 (47.5) | 831 (57.5) | <0.01 | | Active travel | 109 (9.6) | 78 (12.2) | 0.023 | 117 (14.4) | 163 (11.3) | 0.01 | | Not applicable | 78 (6.9) | 21 (3.3) | <0.01 | 85 (10.5) | 168 (11.6) | 0.40 | | How do your children normally travel to school now* | |||||| | Public transport | 246 (21.6) | 158 (24.7) | 0.07 | 49 (6.0) | 114 (7.9) | 0.05 | | Private transport | 652 (57.3) | 284 (44.4) | <0.01 | 159 (19.6) | 360 (24.9) | <0.01 | | Active travel | 632 (55.6) | 316 (49.4) | <0.01 | 166 (20.4) | 319 (22.1) | 0.18 | | Not applicable | 4 (0.4) | 158 (24.7) | <0.01 | 377 (46.4) | 114 (7.9) | <0.01 | | How did you normally travel around Bradford District for things other than getting to work or school?* | |||||| | Public transport | 218 (19.2) | 149 (23.3) | 0.02 | 224 (27.6) | 428 (29.6) | 0.15 | | Private transport | 1002 (88.1) | 506 (79.1) | <0.01 | 523 (64.4) | 956 (66.2) | 0.20 | | Active travel | 351 (30.9) | 179 (28.0) | 0.9 | 264 (32.5) | 385 (26.6) | <0.01 | | Not applicable | 9 (0.8) | 3 (0.5) | 0.43 | 30 (3.7) | 41 (2.8) | 0.26 | | How often do you use your car for journeys of 0.5 miles or less? 0.5 miles is roughly the distance of a 10 minute walk? | |||||| | All the time | 82 (7.2) | 39 (6.1) | 0.793 | 32 (3.9) | 112 (7.8) | <0.001 | | Often | 129 (11.3) | 60 (9.4) | 51 (6.3) | 122 (8.4) | || | Sometimes | 262 (23.0) | 144 (22.5) | 106 (13.1) | 257 (17.8) | || | Rarely | 344 (30.3) | 185 (28.9) | 228 (28.1) | 363 (25.1) | || | Never | 214 (18.8) | 122 (19.1) | 190 (23.4) | 308 (21.3) | || | Not Applicable | 69 (6.1) | 30 (4.7) | 78 (9.6) | 63 (4.4) | Longitudinal analysis. We include the full descriptives for CAZ and air quality perceptions for the N=814 participants completed both surveys in extended data (see Table S1), These are not discussed further. Table 4 and Figure 3 show the percentage of people whose attitudes remained stable, or changed. The majority of participants attitudes towards the CAZ remained stable pre and post CAZ launch. Just over half (55.9%) of the longitudinal sample felt that the CAZ was a good idea, and two fifths (41%) agreed it would improve the health of their community at both baseline and follow-up (i.e. maintaining consistent attitudes). Multinomial regressions comparing those whose attitudes had changed from baseline found few consistent relationships with socio-demographic variables, full results can be found in the extended data (see Table S2). Significant relationships are highlighted in Figure 4. Positive change in support for the CAZ: Those living outside the CAZ boundary were more likely to have a positive change in their support of the CAZ than those who lived inside the boundary (coefficient=0.71; 95% CI: 0.10 to 1.32). Participants from less deprived areas (quintile 3: coefficient=-0.82; 95% CI:-1.56 to -0.07; quintile 4 (coefficient=-0.87; 95% CI: -1.67 to -0.08) were less likely to be in this group compared with the most deprived participants. Negative change in support for the CAZ: Compared to white British participants, the other ethnic minority participants were less likely to be in this group (coefficient=-0.79; 95% CI: -1.53 to -0.04). Those living in the in the least deprived areas were less likely to become negative about the CAZ than those in the most deprived category (coefficient=-1.25; 95% CI: -2.51 to -0.01). Decrease in agreement, or becoming unsure that CAZ will improve health: White British participants were more likely to be in the group that reported a decrease in agreement that the CAZ would improve health compared with Pakistani participants (coefficient: -0 .77, 95%CI: -1.51 to -0.04), or be in the group that reported becoming neutral compared with other ethnic minority participants (coefficient: -0.76, 95%CI: (-1.27 to -0.25). Cross-sectional analysis: Perceptions of air quality appeared relatively similar between baseline and follow-up for BiB participants but varied more for members of the general public (Table 3). For BiB participants, at follow-up, just over a third of the sample (37%) felt air quality was ‘poor’ or ‘very poor’, and 38% felt it was the same as other areas in the UK. Thirty-four percent were moderately to extremely concerned about air quality, and 18% thought other people in Bradford were moderately to extremely concerned. There was a drop of around 10% (95% CI: -15 to -0.05%) in the numbers reporting that it was ‘extremely important’ to improve air quality. For the general public sample, there were significant differences in the distribution of responses to most air quality items. At follow-up, just over a third (36.5%) reported air quality to be ‘poor’ or ‘very poor’; a drop of 24.7% (95% CI: -28.8 to -20.5 %). The proportions of people that reported air quality in Bradford was worse than other areas (46.9%), those that reported fewer people were ‘extremely concerned’ (32%) and those that felt it was ‘extremely’ important to improve air quality (70%) also fell by 20.6% (95% CI:16.5 to 24.7%), 14.3% (95% CI: -18.0 to -10.5 %) and 13.8% (95% CI: -17.8 to -9.7 %)) respectively (see Table 3). Perceptions of ‘others’ concern was more similar, with around 20% reporting that others were moderately or extremely concerned, with no significant change from baseline. Longitudinal analysis: Attitudes towards air quality remained mostly stable pre and post CAZ launch. (Figure 5, Table 4). Where changes did occur, roughly equal numbers changed to a more positive standpoint (e.g. thinking air quality is better: 14%, compares better to other areas of the UK: 13.9%, and less concerned (e.g. reporting less concern: 14.0%, reporting others concern reduced 19.2%) compared with a more negative one (thinking air quality is worse: 13.6% and compares worse with other areas: 16.2%) or more concerned standpoint (14% and others more concerned: 12.5%). Multinomial regressions identified no relationships between any demographic factors and those whose attitudes or concern towards air quality had worsened (e.g. more likely to rate it worse, and compare it negatively to other areas of the UK) and those whose concern had either increased or reduced (see Extended data). However, there were some significant associations as follows, as outlined in Figure 4. Positive change in attitudes towards air quality: Those in the ‘other’ ethnic origin category were more likely to have positive change of attitude about Bradford air quality than white British ethnic origin participants (coefficient=0.78; 95% CI:0.26 to 1.31). Positive change in how Bradford compares to the rest of the UK: Compared to the most deprived group, those in IMD quintile 2 were more likely to report change comparing Bradford favourably to the rest of the UK compared to those in the most deprived quintile (co-efficient=0.83, 95%CI - 0.03 to 1.62). Increase in perceptions of others concern about air quality: Those in the oldest age group (45+) were more likely to be in the group whose perceptions of others concern about air quality increased compared with those in the younger age group (18–34, coefficient=1.32, 95%CI 0.22-2.22). Importance of improving air quality increased: There were some differences by IMD quintile. Compared with the most deprived areas, those in more affluent areas were less likely to report increased importance of tackling pollution (compared with quintile 1: quintile 3 coefficient= -0.87, 95%CI -1.64 to -0.10; quintile 5 coefficient=-1.11; 95% CI: -2.06 to -0.17). Importance of improving air quality decreased. Those 45+ years old were less likely to say that importance of improving air quality decreased (coefficient=-1.13; 95% CI: -2.00 to -0.26) compared with those 18–34 age group. Private transport was the dominant mode of travel for getting to work and travelling for leisure for both samples. There were slight increases in the numbers reporting private transport for work in our repeated cross-sectional sample (64.6% baseline to 70.5% at follow up for BiB participants, and from 47.5% baseline to 57.5% follow up for general public participants). There was a slight decrease in the numbers of BiB participants reporting private transport for leisure (88.1% at baseline and 79.1% follow up) and a minor increase for the general public (64.4% baseline and 66.2% follow up) participants. More baseline BiB families than the follow up BiB families participants used active travel (walked or cycled) to take children to school (55.6% baseline vs 49.4% follow up) whilst only a quarter of the general public used active travel during the same period (20.4% baseline vs 22.1% follow up). Private transport was the most used mode of transport for leisure by the BiB families The proportion of using a car for a 10 minutes’ walk by the BiB families (7% baseline vs 6% follow up) and general public (4% baseline vs 8% follow up) remained small in both surveys (Table 3). We explored whether perceptions of acceptability of the CAZ, air quality, and travel behaviours changed after the implementation of a CAZ in a large, urban multi-ethnic city. On the whole, the majority of participants felt that the CAZ was a good idea and had the potential to improve health. However, there was a slight drop in the number of people finding that it was acceptable between the baseline and follow-up surveys. We found that just over a third of respondents thought air quality was poor and were concerned about air quality at follow-up. To our knowledge, this is first repeated survey study that has explored the changes in perceptions of air quality, acceptability of CAZ and travel behaviours. Our findings add to the limited literature on the acceptability of policies such as LEZ amongst communities living in areas directly affected by the policy. Like others (Oltra et al., 2021) we found that the majority of respondents expressed support for the CAZ, after it has been in place for over a year, despite the ‘loud’ vocal opposition that was apparent before the CAZ was launched (Knamiller et al., 2024). We did however find a small drop in support for the CAZ, along with less agreement that the CAZ would benefit the health of families, an increase in positivity about air quality, and a drop in numbers reporting it was important to improve air quality at follow-up. This may imply two competing scenarios. On the positive side, it could mean that participants felt the air quality has improved after the implementation of CAZ, so it has become less of a concern and priority for them. However, on the negative side, it could also mean that although the air quality has improved, CAZ popularity has dropped after implementation due to its impact on the residents’ daily life. Evidence from qualitative interviews and focus groups with members of the public (Knamiller et al., in preparation) suggests some potential reasons for this decline in acceptability including the pressures felt by communities by the ‘cost of living’ crisis (which saw increases in cost of energy, fuel and food), a lack of trust in the authorities implementing the zone, and a lack of knowledge about whether the zone was working. Amongst our longitudinal sample we found that on the whole attitudes remained largely stable pre to post implementation. This is in contrast to other research similar initiatives which found an increase in positivity towards the interventions (Oltra et al., 2021; Schuitema et al., 2010; Seter et al., 2023) after their implementation. Where attitudes for some did change, there were largely no relationships between key socio-demographic variables and perception changes, which is common with other studies in which there were no visible or very weak trends, and inconclusive evidence from different studies (Oltra et al., 2021; Player et al., 2023). Certain groups, for example, ethnic minority groups, and those living outside of the CAZ boundary were more likely to report a positive change of views (or lack of negative change) towards the CAZ. Those in more affluent areas were less likely to report increases in the importance of tackling pollution compared with deprived areas. The reasons for any change in attitudes cannot be deduced from the current study and future research should aim to qualitatively explore which key factors of LEZ policy may impact on support over time. Travel behaviour remained similar over the implementation year. Private car was the most used mode of transport during the baseline and follow-up survey periods for main earners of the household This is not surprising, as unlike the previous studies which did indicate changes in travel behaviour (Gonzalez et al., 2023; Mayor of London, 2023; Tarriño-Ortiz et al., 2022), the current CAZ did not charge private vehicles. We found low numbers reporting using public transport to get to work or school (~10%), with slightly higher numbers using public transport for leisure purposes (30%). In order to encourage shifts to more sustainable travel modes other initiatives which discourage private vehicle use such as reducing parking availability may be more effective than CAZ, but these need to be done in the context of strong public transport links (Department of Transport, 2021b). Our study has a number of strengths. It recruited a large multi ethnic sample of participants, living in deprived areas of a large city which has recently introduced a CAZ. Previous research has found that these communities may be more likely to be impacted by pollution, and can also be seldom heard in research and therefore this is an important group to study. Second, the study used comparative analyses of pre and post implementation attitudes which has provided useful information of the perception of residents on air quality and acceptability of CAZ at different stages of implementation. The information can be useful for efforts to understand how public acceptability of CAZ may influence implementation. Third, by including a longitudinal component we were able to directly test whether attitudes changed after the implementation of the CAZ. We found attitudes to be relatively stable, indicating that assessment prior to initiatives being implemented are a valid way of predicting later opinions. However, there are some weaknesses. First, our surveys are prone to selection bias due to participants being those who were willing to participate. In particular, the general public participants may have been motivated mainly by a vested interest in the topic, whereas BiB participants were approached directly to take part as part of routine research interactions. This was particularly apparent in the baseline survey where large variations in the patterns of responses were seen between the general public and BiB participants. In particular, the baseline general public survey appeared to have higher numbers of people who were extremely concerned about air quality. In order to mitigate against self-selection bias for the follow-up survey we attempted to recruit members of the general public in a variety of ways, including attending community events and healthcare settings. This approach appears to have also helped to boost numbers of ethnic minority participants in the follow-up sample. Second, information on socio demographic factors were substantially missing for the follow up general public survey participants hence the responses obtained here may not reflect the district’s population view. Finally, we did not ask about attitudes to wider transport policy, which may impact on CAZ-related views. In conclusion, we found concerns about air quality, the need to improve air quality and support of CAZ were felt by the majority of residents we surveyed, and these remained stable over the duration of the study. Systematically assessing communities’ support for measures such as LEZ is an important step in the implementation process and ensuring that communities who are ‘seldom-heard’ are included is crucial to balance what can be often loud and vocal opposition. Whilst small, we did find some evidence of a decrease in support for the CAZ. If this drop in support continues, it may threaten the sustainability of the CAZ. Continuous communication with stakeholders and communities will be important to share benefits and outcomes of the CAZ to maintain levels of public support. Ethical approval was granted from the Bradford Leeds Research NHS research ethics committee on the 30/06/2020 (Ref 20/YH/0158), in accordance with the declaration of Helsinki. All participants received a participant information sheet and were asked to indicate their written consent which was recorded on the landing page of the survey prior to completing the questionnaires. Data are available for sharing can be requested via the Born in Bradford executive group ([email protected]). A detailed data dictionary can be found here: https://borninbradford.github.io/datadict/bib_breathes.html and further details on how to make an application can be found here: https://borninbradford.nhs.uk/research/how-to-access-data/. Information sheets and questionnaires can be found on the Born in Bradford website: https://borninbradford.nhs.uk/research/study-documents/ OpenScience Framework: Extended data: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK DOI http://dx.doi.org/10.17605/OSF.IO/CJFSE This project contains the following extended data: Table S1. CAZ and air quality attitudes of participants who participated in baseline and follow-up surveys. Table S2. Results of multinomial regression for changes in Clean Air Zone attitudes. Table S3. Results of multinomial regression for changes in air quality attitudes. TM: Conceptualisation, Formal Analysis, Methodology, Supervision, Writing-original draft, Writing -review and editing RM: Conceptualisation, Funding acquisition, Methodology, Project administration, Supervision, Writing – review and editing CK: Conceptualisation, Investigation, Project administration, Writing – review and editing GS: Funding acquisition, Data curation, Supervision, Writing – review and editing RH: Investigation, project administration, Writing – review and editing MB: Conceptualisation, Funding acquisition, Methodology, Project administration, Supervision, Writing – review and editing Born in Bradford (BiB) is only possible because of the enthusiasm and commitment of the children and parents in BiB. We are grateful to all the participants, health professionals, schools and researchers who have made Born in Bradford happen. 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Reference Source Author details Author details 1 Bradford Teaching Hospitals NHS Foundation Trust, Bradford Institute for Health Research, Bradford, England, BD9 6RJ, UK 2 Population Health Improvement UK, UK, UK 3 Hull York Medical School, Hull, England, UK 4 University of York Department of Health Sciences, York, England, YO10 5DD, UK 2 Population Health Improvement UK, UK, UK 3 Hull York Medical School, Hull, England, UK 4 University of York Department of Health Sciences, York, England, YO10 5DD, UK Teumzghi Mebrahtu Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Rosemary R. C. McEachan Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing Cathy Knamiller Roles: Conceptualization, Investigation, Project Administration, Writing – Review & Editing Roles: Conceptualization, Investigation, Project Administration, Writing – Review & Editing Gillian Santorelli Roles: Data Curation, Funding Acquisition, Supervision, Writing – Review & Editing Roles: Data Curation, Funding Acquisition, Supervision, Writing – Review & Editing Rumana Hossain Roles: Investigation, Project Administration, Writing – Review & Editing Roles: Investigation, Project Administration, Writing – Review & Editing Maria Bryant Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information This project is funded by the National Institute for Health and Care Research (NIHR) under its Leadership in Applied Health Research and Care Yorkshire and Humber (Grant Reference Number NIHR200166) and by the Public Health Research Programme (Grant Reference Number NIHR128833). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (2) Copyright © 2025 Mebrahtu T et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. metrics VIEWS $counts.viewCount downloads Citations CITE how to cite this article Mebrahtu T, McEachan RRC, Knamiller C et al. Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.13730.2) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. track receive updates on this article Track an article to receive email alerts on any updates to this article. Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions Version 2 VERSION 2 PUBLISHED 17 Mar 2025 Revised Views 0 How to cite this report: Oltra C. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.15156.r34989) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34989 https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34989 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Reviewer Report 25 Mar 2025 Christian Oltra, Socio-Technical Research Centre, CIEMAT, Barcelona, Spain Approved VIEWS 0 Overall, the authors have addressed the previous comments and made significant improvements ... Continue reading I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close Overall, the authors have addressed the previous comments and made significant improvements to the manuscript. I have no further major concerns at this stage. Competing Interests: No competing interests were disclosed. Reviewer Expertise: Risk perception CITE HOW TO CITE THIS REPORT Oltra C. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.15156.r34989) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34989 https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34989 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. Views 0 How to cite this report: Ou Y. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.15156.r34988) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34988 https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34988 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Reviewer Report 18 Mar 2025 Approved VIEWS 0 The authors have addressed most of my ... Continue reading I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close The authors have addressed most of my concerns, and I have no further comments. Competing Interests: No competing interests were disclosed. Reviewer Expertise: Environmental Economics, Air Pollution, Sustainable Transport and Land Use Planning CITE HOW TO CITE THIS REPORT Ou Y. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.15156.r34988) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34988 https://openresearch.nihr.ac.uk/articles/4-71/v2#referee-response-34988 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. Version 1 VERSION 1 PUBLISHED 15 Nov 2024 Views 0 How to cite this report: Oltra C. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.14911.r33654) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33654 https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33654 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Reviewer Report 17 Dec 2024 Christian Oltra, Socio-Technical Research Centre, CIEMAT, Barcelona, Spain Approved with Reservations VIEWS 0 I would like to congratulate you on your article, which addresses a highly relevant topic. Its longitudinal approach and the wealth of data presented are undoubtedly a valuable contribution to the field. However, to further improve the clarity and ... Continue reading I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close However, to further improve the clarity and ... Continue reading I would like to congratulate you on your article, which addresses a highly relevant topic. Its longitudinal approach and the wealth of data presented are undoubtedly a valuable contribution to the field. However, to further improve the clarity and accessibility of the article, I would like to offer some suggestions that could help focus the analysis and make it easier for readers to understand: 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, such as: 2. Restructure the narrative: I would propose organising the results around three broad thematic blocks: 3. Eliminating some tables and grouping similar results together or: Several tables could be synthesised into a summary graph or deleted if they are not directly connected to the main research questions. 4. Simplifying the presentation of statistical models: I find it useful to include a compact table summarising only the significant findings from the regression models. Technical details can be moved to the appendix, allowing the text to flow in a more narrative fashion. 5. Optimise data visualization: Replacing some dense tables with graphs could make the results more accessible. These recommendations are not intended to detract from the breadth of your work, but to highlight it in a way that allows readers to grasp the impact of your findings more easily. I am convinced that these small modifications could further enhance the scope and clarity of your contribution. Yours sincerely However, to further improve the clarity and accessibility of the article, I would like to offer some suggestions that could help focus the analysis and make it easier for readers to understand: 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, such as: - Changes in support for CAZ. - Perception of air quality. - Impacts on transport modes. 2. Restructure the narrative: I would propose organising the results around three broad thematic blocks: - Perception of the CAZ. - Perception of air quality. - Travel behaviours. 3. Eliminating some tables and grouping similar results together or: Several tables could be synthesised into a summary graph or deleted if they are not directly connected to the main research questions. 4. Simplifying the presentation of statistical models: I find it useful to include a compact table summarising only the significant findings from the regression models. Technical details can be moved to the appendix, allowing the text to flow in a more narrative fashion. 5. Optimise data visualization: Replacing some dense tables with graphs could make the results more accessible. These recommendations are not intended to detract from the breadth of your work, but to highlight it in a way that allows readers to grasp the impact of your findings more easily. I am convinced that these small modifications could further enhance the scope and clarity of your contribution. Yours sincerely - Is the work clearly and accurately presented and does it cite the current literature? Yes - Is the study design appropriate and is the work technically sound? Yes - Are sufficient details of methods and analysis provided to allow replication by others? Yes - If applicable, is the statistical analysis and its interpretation appropriate? Yes - Are all the source data underlying the results available to ensure full reproducibility? No - Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Risk perception CITE HOW TO CITE THIS REPORT Oltra C. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.14911.r33654) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33654 https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33654 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. - Author Response 17 Mar 2025Rosemary McEachan, Bradford Teaching Hospitals NHS Foundation Trust, Bradford Institute for Health Research, Bradford, BD9 6RJ, UK17 Mar 2025Author ResponseWe thank the reviewer for their positive and constructive comments. 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, ... Continue reading We thank the reviewer for their positive and constructive comments. 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, such as: Changes in support for CAZ. Perception of air quality. Impacts on transport modes. This would allow the reader to focus on the most relevant results 2. Restructure the narrative: I would propose organising the results around three broad thematic blocks: Perception of the CAZ. Perception of air quality. Travel behaviours. This will provide a clearer framework for presenting the findings and hold the reader's attention.- We thank the reviewer for these two thoughtful suggestions and have restructured our findings as follows: - 1. Acceptability of the clean air zone, presenting first the cross-sectional analyses and subsequently the longitudinal analysis (e.g. attitude change); - 2. Perceptions of air quality (cross-sectional, then changes; - 3. Travel behaviors - We have restructured the discussion. This covers: - Overall summary of results - Discussion about changes in attitudes to CAZ and air quality - Discussion about stability of attitudes - Discussion about travel behaviour - Strengths and limitations - Conclusion - We agree – we have now uploaded three tables into extended data: Table S2. Results of multinomial regression for changes in Clean Air Zone attitudes. Table S3. Results of multinomial regression for changes in air quality attitudes. 4. Simplifying the presentation of statistical models: I find it useful to include a compact table summarising only the significant findings from the regression models. Technical details can be moved to the appendix, allowing the text to flow in a more narrative fashion. 5. Optimise data visualization: Replacing some dense tables with graphs could make the results more accessible.- Thank you for these two comments. We have included a summary figure (Figure 4) which highlights the key findings from the multinomial regression and have removed the tables to the extended data (see response above). We thank the reviewer for their positive and constructive comments.Competing Interests: No competing interests were disclosed. Close 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, such as: Changes in support for CAZ. Perception of air quality. Impacts on transport modes. This would allow the reader to focus on the most relevant results 2. Restructure the narrative: I would propose organising the results around three broad thematic blocks: Perception of the CAZ. Perception of air quality. Travel behaviours. This will provide a clearer framework for presenting the findings and hold the reader's attention.- We thank the reviewer for these two thoughtful suggestions and have restructured our findings as follows: - 1. Acceptability of the clean air zone, presenting first the cross-sectional analyses and subsequently the longitudinal analysis (e.g. attitude change); - 2. Perceptions of air quality (cross-sectional, then changes; - 3. Travel behaviors - We have restructured the discussion. This covers: - Overall summary of results - Discussion about changes in attitudes to CAZ and air quality - Discussion about stability of attitudes - Discussion about travel behaviour - Strengths and limitations - Conclusion - We agree – we have now uploaded three tables into extended data: Table S2. Results of multinomial regression for changes in Clean Air Zone attitudes. Table S3. Results of multinomial regression for changes in air quality attitudes. 4. Simplifying the presentation of statistical models: I find it useful to include a compact table summarising only the significant findings from the regression models. Technical details can be moved to the appendix, allowing the text to flow in a more narrative fashion. 5. Optimise data visualization: Replacing some dense tables with graphs could make the results more accessible.- Thank you for these two comments. We have included a summary figure (Figure 4) which highlights the key findings from the multinomial regression and have removed the tables to the extended data (see response above). - We thank the reviewer for these two thoughtful suggestions and have restructured our findings as follows: COMMENTS ON THIS REPORT - Author Response 17 Mar 2025Rosemary McEachan, Bradford Teaching Hospitals NHS Foundation Trust, Bradford Institute for Health Research, Bradford, BD9 6RJ, UK17 Mar 2025Author ResponseWe thank the reviewer for their positive and constructive comments. 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, ... Continue reading We thank the reviewer for their positive and constructive comments. 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, such as: Changes in support for CAZ. Perception of air quality. Impacts on transport modes. This would allow the reader to focus on the most relevant results 2. Restructure the narrative: I would propose organising the results around three broad thematic blocks: Perception of the CAZ. Perception of air quality. Travel behaviours. This will provide a clearer framework for presenting the findings and hold the reader's attention.- We thank the reviewer for these two thoughtful suggestions and have restructured our findings as follows: - 1. Acceptability of the clean air zone, presenting first the cross-sectional analyses and subsequently the longitudinal analysis (e.g. attitude change); - 2. Perceptions of air quality (cross-sectional, then changes; - 3. Travel behaviors - We have restructured the discussion. This covers: - Overall summary of results - Discussion about changes in attitudes to CAZ and air quality - Discussion about stability of attitudes - Discussion about travel behaviour - Strengths and limitations - Conclusion - We agree – we have now uploaded three tables into extended data: Table S2. Results of multinomial regression for changes in Clean Air Zone attitudes. Table S3. Results of multinomial regression for changes in air quality attitudes. 4. Simplifying the presentation of statistical models: I find it useful to include a compact table summarising only the significant findings from the regression models. Technical details can be moved to the appendix, allowing the text to flow in a more narrative fashion. 5. Optimise data visualization: Replacing some dense tables with graphs could make the results more accessible.- Thank you for these two comments. We have included a summary figure (Figure 4) which highlights the key findings from the multinomial regression and have removed the tables to the extended data (see response above). We thank the reviewer for their positive and constructive comments.Competing Interests: No competing interests were disclosed. Close 1. Prioritise key findings. I recommend focusing on the findings most directly related to the objectives of the study, such as: Changes in support for CAZ. Perception of air quality. Impacts on transport modes. This would allow the reader to focus on the most relevant results 2. Restructure the narrative: I would propose organising the results around three broad thematic blocks: Perception of the CAZ. Perception of air quality. Travel behaviours. This will provide a clearer framework for presenting the findings and hold the reader's attention.- We thank the reviewer for these two thoughtful suggestions and have restructured our findings as follows: - 1. Acceptability of the clean air zone, presenting first the cross-sectional analyses and subsequently the longitudinal analysis (e.g. attitude change); - 2. Perceptions of air quality (cross-sectional, then changes; - 3. Travel behaviors - We have restructured the discussion. This covers: - Overall summary of results - Discussion about changes in attitudes to CAZ and air quality - Discussion about stability of attitudes - Discussion about travel behaviour - Strengths and limitations - Conclusion - We agree – we have now uploaded three tables into extended data: Table S2. Results of multinomial regression for changes in Clean Air Zone attitudes. Table S3. Results of multinomial regression for changes in air quality attitudes. 4. Simplifying the presentation of statistical models: I find it useful to include a compact table summarising only the significant findings from the regression models. Technical details can be moved to the appendix, allowing the text to flow in a more narrative fashion. 5. Optimise data visualization: Replacing some dense tables with graphs could make the results more accessible.- Thank you for these two comments. We have included a summary figure (Figure 4) which highlights the key findings from the multinomial regression and have removed the tables to the extended data (see response above). - We thank the reviewer for these two thoughtful suggestions and have restructured our findings as follows: Views 0 How to cite this report: Ou Y. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.14911.r33648) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33648 https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33648 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Reviewer Report 22 Nov 2024 Approved with Reservations VIEWS 0 This study investigates the impact of implementing a low emission zone (LEZ) on perceptions of air quality, acceptability, and travel behavior in Bradford, UK. Overall, the manuscript is well-structured, addressing an interesting and relevant topic with satisfactory writing quality. My ... Continue reading I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close This study investigates the impact of implementing a low emission zone (LEZ) on perceptions of air quality, acceptability, and travel behavior in Bradford, UK. Overall, the manuscript is well-structured, addressing an interesting and relevant topic with satisfactory writing quality. My detailed comments for further improvement are as follows: (1) In the Statistical Analysis section, the authors are advised to provide a more detailed explanation of their choice of model. Specifically, why was Multinomial Regression chosen over other commonly used statistical models, such as Structural Equation Modeling? (2) Multicollinearity Problem: The authors are advised to test for potential multicollinearity problems, using variance inflation factor (VIF) before conducting regression analysis. For example, the IMD quintile might be correlated with other demographic characteristics like sex, age, and ethnicity. Including all these variables in a regression model could potentially cause multicollinearity problems and bias the estimation results. (3) Omitted Variable Problem: Since LEZ is essentially a type of transport policy, people's perceptions of LEZ-related issues may also be influenced by the availability of transport infrastructure. Specifically, failing to account for various forms of transport services (e.g., increased bus frequency, urban rail transit development) provided during the study period could lead to an omitted variable problem and bias the estimation results. (4) The authors should include more in-depth discussions when interpreting their results. For example, they could provide a detailed explanation of why the number of people finding the LEZ acceptable decreased after its implementation. In addition, they should also explore why the travel behavior of residents remained unchanged, in contrast to other parts of Europe where LEZs have significantly influenced travel patterns. (5) The authors are advised to include a detailed model specification that allows the analysis and method to be replicated by others. (1) In the Statistical Analysis section, the authors are advised to provide a more detailed explanation of their choice of model. Specifically, why was Multinomial Regression chosen over other commonly used statistical models, such as Structural Equation Modeling? (2) Multicollinearity Problem: The authors are advised to test for potential multicollinearity problems, using variance inflation factor (VIF) before conducting regression analysis. For example, the IMD quintile might be correlated with other demographic characteristics like sex, age, and ethnicity. Including all these variables in a regression model could potentially cause multicollinearity problems and bias the estimation results. (3) Omitted Variable Problem: Since LEZ is essentially a type of transport policy, people's perceptions of LEZ-related issues may also be influenced by the availability of transport infrastructure. Specifically, failing to account for various forms of transport services (e.g., increased bus frequency, urban rail transit development) provided during the study period could lead to an omitted variable problem and bias the estimation results. (4) The authors should include more in-depth discussions when interpreting their results. For example, they could provide a detailed explanation of why the number of people finding the LEZ acceptable decreased after its implementation. In addition, they should also explore why the travel behavior of residents remained unchanged, in contrast to other parts of Europe where LEZs have significantly influenced travel patterns. (5) The authors are advised to include a detailed model specification that allows the analysis and method to be replicated by others. - Is the work clearly and accurately presented and does it cite the current literature? Yes - Is the study design appropriate and is the work technically sound? Partly - Are sufficient details of methods and analysis provided to allow replication by others? Partly - If applicable, is the statistical analysis and its interpretation appropriate? Yes - Are all the source data underlying the results available to ensure full reproducibility? Yes - Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Environmental Economics, Air Pollution, Sustainable Transport and Land Use Planning CITE HOW TO CITE THIS REPORT Ou Y. Reviewer Report For: Does implementation of a low emission zone change perceptions of air quality, acceptability and travel behaviour? a longitudinal and repeated cross-sectional survey study in Bradford, UK [version 2; peer review: 2 approved]. NIHR Open Res 2025, 4:71 (https://doi.org/10.3310/nihropenres.14911.r33648) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33648 https://openresearch.nihr.ac.uk/articles/4-71/v1#referee-response-33648 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. - Author Response 17 Mar 2025Rosemary McEachan, Bradford Teaching Hospitals NHS Foundation Trust, Bradford Institute for Health Research, Bradford, BD9 6RJ, UK17 Mar 2025Author Response - We thank the reviewer for their positive and constructive comments. My detailed comments for further improvement are as follows: (1) In the Statistical Analysis section, the ... Continue reading- We thank the reviewer for their positive and constructive comments. My detailed comments for further improvement are as follows: (1) In the Statistical Analysis section, the authors are advised to provide a more detailed explanation of their choice of model. Specifically, why was Multinomial Regression chosen over other commonly used statistical models, such as Structural Equation Modeling?- As our outcome variable was categorical (e.g. relating to whether attitudes had remained stable, or increased or decreased in valence) multi-nomial regression is a suitable analysis technique. We have added justification of our choice n the statistical analysis methods section as follows: “Multinomial regressions, which are appropriate for multi-category outcomes, were used to explore whether changes in attitudes (reference: no change) were associated with demographic factors including ethnicity (white British[reference], Pakistani origin, other), sex (male[reference], female), Age (18–34[reference], 35–44, 45+), and Bradford IMD quintile (reference IMD 1 – most deprived) and whether respondents lived inside (reference) or outside the CAZ zone.” (2) Multicollinearity Problem: The authors are advised to test for potential multicollinearity problems, using variance inflation factor (VIF) before conducting regression analysis. For example, the IMD quintile might be correlated with other demographic characteristics like sex, age, and ethnicity. Including all these variables in a regression model could potentially cause multicollinearity problems and bias the estimation results.- Thank you for this suggestion. We have tested for multi-collinearity by running a series of ordinary least square regression for each independent variable against all other variables. We limited risk of multi-collinearity. We have added an addition to the manuscript as follows: “Multi-collinearity was first assessed by running a series of ordinary logistic least square regressions of each independent variable against all other variables. The mean variance inflation factor for all regressions was <2, indicating limited risk of multi-collinearity between the independent variables.” (3) Omitted Variable Problem: Since LEZ is essentially a type of transport policy, people's perceptions of LEZ-related issues may also be influenced by the availability of transport infrastructure. Specifically, failing to account for various forms of transport services (e.g., increased bus frequency, urban rail transit development) provided during the study period could lead to an omitted variable problem and bias the estimation results.- Thank you for this comment, we agree that wider contextual factors may impact on CAZ related attitudes. Unfortunately, we were not able to measure these in the current study, however, we have explored these in depth in related qualitative work. We have added a limitation as follows: (4) The authors should include more in-depth discussions when interpreting their results. For example, they could provide a detailed explanation of why the number of people finding the LEZ acceptable decreased after its implementation. In addition, they should also explore why the travel behavior of residents remained unchanged, in contrast to other parts of Europe where LEZs have significantly influenced travel patterns. - We have restructured the discussion (see also Reviewer 2). The drop in acceptability was small. Further qualitative research which is in preparation can shed some light on the reasons for the changes in additions. We have amended the text as follows: Evidence from qualitative interviews and focus groups with members of the public ( (Knamiller et al, in preparation) suggests some potential reasons for this decline in acceptability including the pressures felt by communities by the ‘cost of living’ crisis (which saw increases in cost of energy, fuel and food), a lack of trust in the authorities implementing the zone, and a lack of knowledge about whether the zone was working.” - We hypothesise the reason that we do not see shifts in travel behaviour is because the CAZ did not charge private vehicles, and therefore there was less incentive for individuals to change their personal travel behaviours. We feel that we have adequately covered this in the discussion (line 398-407) and so for parsimony have not changed the text further. (5) The authors are advised to include a detailed model specification that allows the analysis and method to be replicated by others.- We have clarified the program (Stata 17, Statacorp, 2023) and the command used (mlogit); this together with information on the variables included should enable replication. Competing Interests: No competing interests were disclosed. Close- We thank the reviewer for their positive and constructive comments. My detailed comments for further improvement are as follows: (1) In the Statistical Analysis section, the authors are advised to provide a more detailed explanation of their choice of model. Specifically, why was Multinomial Regression chosen over other commonly used statistical models, such as Structural Equation Modeling?- As our outcome variable was categorical (e.g. relating to whether attitudes had remained stable, or increased or decreased in valence) multi-nomial regression is a suitable analysis technique. We have added justification of our choice n the statistical analysis methods section as follows: “Multinomial regressions, which are appropriate for multi-category outcomes, were used to explore whether changes in attitudes (reference: no change) were associated with demographic factors including ethnicity (white British[reference], Pakistani origin, other), sex (male[reference], female), Age (18–34[reference], 35–44, 45+), and Bradford IMD quintile (reference IMD 1 – most deprived) and whether respondents lived inside (reference) or outside the CAZ zone.” (2) Multicollinearity Problem: The authors are advised to test for potential multicollinearity problems, using variance inflation factor (VIF) before conducting regression analysis. For example, the IMD quintile might be correlated with other demographic characteristics like sex, age, and ethnicity. Including all these variables in a regression model could potentially cause multicollinearity problems and bias the estimation results.- Thank you for this suggestion. We have tested for multi-collinearity by running a series of ordinary least square regression for each independent variable against all other variables. We limited risk of multi-collinearity. We have added an addition to the manuscript as follows: “Multi-collinearity was first assessed by running a series of ordinary logistic least square regressions of each independent variable against all other variables. The mean variance inflation factor for all regressions was <2, indicating limited risk of multi-collinearity between the independent variables.” (3) Omitted Variable Problem: Since LEZ is essentially a type of transport policy, people's perceptions of LEZ-related issues may also be influenced by the availability of transport infrastructure. Specifically, failing to account for various forms of transport services (e.g., increased bus frequency, urban rail transit development) provided during the study period could lead to an omitted variable problem and bias the estimation results.- Thank you for this comment, we agree that wider contextual factors may impact on CAZ related attitudes. Unfortunately, we were not able to measure these in the current study, however, we have explored these in depth in related qualitative work. We have added a limitation as follows: (4) The authors should include more in-depth discussions when interpreting their results. For example, they could provide a detailed explanation of why the number of people finding the LEZ acceptable decreased after its implementation. In addition, they should also explore why the travel behavior of residents remained unchanged, in contrast to other parts of Europe where LEZs have significantly influenced travel patterns. - We have restructured the discussion (see also Reviewer 2). The drop in acceptability was small. Further qualitative research which is in preparation can shed some light on the reasons for the changes in additions. We have amended the text as follows: Evidence from qualitative interviews and focus groups with members of the public ( (Knamiller et al, in preparation) suggests some potential reasons for this decline in acceptability including the pressures felt by communities by the ‘cost of living’ crisis (which saw increases in cost of energy, fuel and food), a lack of trust in the authorities implementing the zone, and a lack of knowledge about whether the zone was working.” - We hypothesise the reason that we do not see shifts in travel behaviour is because the CAZ did not charge private vehicles, and therefore there was less incentive for individuals to change their personal travel behaviours. We feel that we have adequately covered this in the discussion (line 398-407) and so for parsimony have not changed the text further. (5) The authors are advised to include a detailed model specification that allows the analysis and method to be replicated by others.- We have clarified the program (Stata 17, Statacorp, 2023) and the command used (mlogit); this together with information on the variables included should enable replication. COMMENTS ON THIS REPORT - Author Response 17 Mar 2025Rosemary McEachan, Bradford Teaching Hospitals NHS Foundation Trust, Bradford Institute for Health Research, Bradford, BD9 6RJ, UK17 Mar 2025Author Response - We thank the reviewer for their positive and constructive comments. My detailed comments for further improvement are as follows: (1) In the Statistical Analysis section, the ... Continue reading- We thank the reviewer for their positive and constructive comments. My detailed comments for further improvement are as follows: (1) In the Statistical Analysis section, the authors are advised to provide a more detailed explanation of their choice of model. Specifically, why was Multinomial Regression chosen over other commonly used statistical models, such as Structural Equation Modeling?- As our outcome variable was categorical (e.g. relating to whether attitudes had remained stable, or increased or decreased in valence) multi-nomial regression is a suitable analysis technique. We have added justification of our choice n the statistical analysis methods section as follows: “Multinomial regressions, which are appropriate for multi-category outcomes, were used to explore whether changes in attitudes (reference: no change) were associated with demographic factors including ethnicity (white British[reference], Pakistani origin, other), sex (male[reference], female), Age (18–34[reference], 35–44, 45+), and Bradford IMD quintile (reference IMD 1 – most deprived) and whether respondents lived inside (reference) or outside the CAZ zone.” (2) Multicollinearity Problem: The authors are advised to test for potential multicollinearity problems, using variance inflation factor (VIF) before conducting regression analysis. For example, the IMD quintile might be correlated with other demographic characteristics like sex, age, and ethnicity. Including all these variables in a regression model could potentially cause multicollinearity problems and bias the estimation results.- Thank you for this suggestion. We have tested for multi-collinearity by running a series of ordinary least square regression for each independent variable against all other variables. We limited risk of multi-collinearity. We have added an addition to the manuscript as follows: “Multi-collinearity was first assessed by running a series of ordinary logistic least square regressions of each independent variable against all other variables. The mean variance inflation factor for all regressions was <2, indicating limited risk of multi-collinearity between the independent variables.” (3) Omitted Variable Problem: Since LEZ is essentially a type of transport policy, people's perceptions of LEZ-related issues may also be influenced by the availability of transport infrastructure. Specifically, failing to account for various forms of transport services (e.g., increased bus frequency, urban rail transit development) provided during the study period could lead to an omitted variable problem and bias the estimation results.- Thank you for this comment, we agree that wider contextual factors may impact on CAZ related attitudes. Unfortunately, we were not able to measure these in the current study, however, we have explored these in depth in related qualitative work. We have added a limitation as follows: (4) The authors should include more in-depth discussions when interpreting their results. For example, they could provide a detailed explanation of why the number of people finding the LEZ acceptable decreased after its implementation. In addition, they should also explore why the travel behavior of residents remained unchanged, in contrast to other parts of Europe where LEZs have significantly influenced travel patterns. - We have restructured the discussion (see also Reviewer 2). The drop in acceptability was small. Further qualitative research which is in preparation can shed some light on the reasons for the changes in additions. We have amended the text as follows: Evidence from qualitative interviews and focus groups with members of the public ( (Knamiller et al, in preparation) suggests some potential reasons for this decline in acceptability including the pressures felt by communities by the ‘cost of living’ crisis (which saw increases in cost of energy, fuel and food), a lack of trust in the authorities implementing the zone, and a lack of knowledge about whether the zone was working.” - We hypothesise the reason that we do not see shifts in travel behaviour is because the CAZ did not charge private vehicles, and therefore there was less incentive for individuals to change their personal travel behaviours. We feel that we have adequately covered this in the discussion (line 398-407) and so for parsimony have not changed the text further. (5) The authors are advised to include a detailed model specification that allows the analysis and method to be replicated by others.- We have clarified the program (Stata 17, Statacorp, 2023) and the command used (mlogit); this together with information on the variables included should enable replication. Competing Interests: No competing interests were disclosed. Close- We thank the reviewer for their positive and constructive comments. My detailed comments for further improvement are as follows: (1) In the Statistical Analysis section, the authors are advised to provide a more detailed explanation of their choice of model. Specifically, why was Multinomial Regression chosen over other commonly used statistical models, such as Structural Equation Modeling?- As our outcome variable was categorical (e.g. relating to whether attitudes had remained stable, or increased or decreased in valence) multi-nomial regression is a suitable analysis technique. We have added justification of our choice n the statistical analysis methods section as follows: “Multinomial regressions, which are appropriate for multi-category outcomes, were used to explore whether changes in attitudes (reference: no change) were associated with demographic factors including ethnicity (white British[reference], Pakistani origin, other), sex (male[reference], female), Age (18–34[reference], 35–44, 45+), and Bradford IMD quintile (reference IMD 1 – most deprived) and whether respondents lived inside (reference) or outside the CAZ zone.” (2) Multicollinearity Problem: The authors are advised to test for potential multicollinearity problems, using variance inflation factor (VIF) before conducting regression analysis. For example, the IMD quintile might be correlated with other demographic characteristics like sex, age, and ethnicity. Including all these variables in a regression model could potentially cause multicollinearity problems and bias the estimation results.- Thank you for this suggestion. We have tested for multi-collinearity by running a series of ordinary least square regression for each independent variable against all other variables. We limited risk of multi-collinearity. We have added an addition to the manuscript as follows: “Multi-collinearity was first assessed by running a series of ordinary logistic least square regressions of each independent variable against all other variables. The mean variance inflation factor for all regressions was <2, indicating limited risk of multi-collinearity between the independent variables.” (3) Omitted Variable Problem: Since LEZ is essentially a type of transport policy, people's perceptions of LEZ-related issues may also be influenced by the availability of transport infrastructure. Specifically, failing to account for various forms of transport services (e.g., increased bus frequency, urban rail transit development) provided during the study period could lead to an omitted variable problem and bias the estimation results.- Thank you for this comment, we agree that wider contextual factors may impact on CAZ related attitudes. Unfortunately, we were not able to measure these in the current study, however, we have explored these in depth in related qualitative work. We have added a limitation as follows: (4) The authors should include more in-depth discussions when interpreting their results. For example, they could provide a detailed explanation of why the number of people finding the LEZ acceptable decreased after its implementation. In addition, they should also explore why the travel behavior of residents remained unchanged, in contrast to other parts of Europe where LEZs have significantly influenced travel patterns. - We have restructured the discussion (see also Reviewer 2). The drop in acceptability was small. Further qualitative research which is in preparation can shed some light on the reasons for the changes in additions. We have amended the text as follows: Evidence from qualitative interviews and focus groups with members of the public ( (Knamiller et al, in preparation) suggests some potential reasons for this decline in acceptability including the pressures felt by communities by the ‘cost of living’ crisis (which saw increases in cost of energy, fuel and food), a lack of trust in the authorities implementing the zone, and a lack of knowledge about whether the zone was working.” - We hypothesise the reason that we do not see shifts in travel behaviour is because the CAZ did not charge private vehicles, and therefore there was less incentive for individuals to change their personal travel behaviours. We feel that we have adequately covered this in the discussion (line 398-407) and so for parsimony have not changed the text further. (5) The authors are advised to include a detailed model specification that allows the analysis and method to be replicated by others.- We have clarified the program (Stata 17, Statacorp, 2023) and the command used (mlogit); this together with information on the variables included should enable replication. Alongside their report, reviewers assign a status to the article: - Approved - Approved with reservations - Not approved | Invited Reviewers | || |---|---|---| | 1 | 2 | | | Version 2 (revision) 17 Mar 25 | read | read | | Version 1 15 Nov 24 | read | read | Sign up for content alerts You are now signed up to receive this alert Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' - Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. - You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. - You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). - You work at the same institute as any of the authors. - You hope/expect to benefit (e.g. favour or employment) as a result of your submission. - You are an Editor for the journal in which the article is published. 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