Introduction

Urban regeneration programmes are complex interventions aimed at enhancing wellbeing in disadvantaged communities [1]. Looking for long-term advances, policy-makers are changing the focus of these programmes to improving the built and social environments [2]. This way, regeneration can encompass a broad range of policy sectors, from housing, public spaces and mobility, to social services, information technologies and economy. Moreover, social problems tend to be spatially distributed in an unequal way, which can make urban programmes more suitable than traditional sector programmes [3]. An unequal provision of resources among individuals and social groups in an urban environment can lead to health inequalities. Comprehensive urban regeneration programmes aim to facilitate access to and availability of a wide range of these resources. Therefore, it is expected that urban regeneration programmes comprising a greater diversity of interventions will favour access to dispositional resources and provide wider options for a better life. Finally, urban regeneration programmes can be seen as public health interventions that potentially improve the wellbeing of recipients and indirectly benefit the entire population [4, 5].

Previous literature reported that good built and social environments are associated with desirable social and health outcomes, like social cohesion and physical activity, and inversely associated with others like overweight and alcohol abuse [6, 7]. However, when individual characteristics are taken into consideration, the literature found mixed evidence for urban regeneration programmes to improve wellbeing [1, 8], especially for mental health [9–11]. The variability in results could be due to the heterogeneity of the interventions and different methodological threads. In particular: changes in population composition (e.g., gentrification), non-observed confounding factors, and previous trends; and different analyses (short- or long-term effects) [1, 12]. Despite variability, several studies found evidence for urban regeneration programmes to improve wellbeing in different situations: when citizens participate in them [13], in areas of high-intensity intervention [14–16], and among citizens residing in the intervention area for a long time [17].

Urban regeneration programmes have been implemented in Europe since the early 90’s under the Urban pilot projects 1990–1993, and more decisively with the URBAN programmes (1994–2006). In this context, the Catalonia Neighbourhood’s Law (Law 2/2004) was designed to improve living conditions in the most disadvantaged neighbourhoods, mainly through town planning interventions. In Barcelona city, these urban regeneration programmes have been associated with improvements in self-perceived health, mainly among low-income citizens [18]. Therefore, in 2016, the city council promoted a new urban regeneration programme, “Pla de Barris (PdB) 2016–2020”. PdB was a multicomponent, comprehensive, intersectoral, and community engagement programme with a total budget of 150 million euros implemented in 16 disadvantaged neighbourhoods with a total population of 225,631 people in 2016. It aimed to decrease inequalities by involving citizens in the development of projects that addressed the built and social environments. It was assumed that the benefits of the intervention would be neighbourhood-wide, and not restricted to participants.

The objective of our study was to assess the impact of the PdB urban regeneration programme on wellbeing in deprived neighbourhoods of Barcelona, characterised by lower indicators in terms of income, education level, residential vulnerability indices, higher unemployment rates, a higher percentage of the foreign population and material deprivation. To achieve this, we assessed selected health outcomes and health-related behaviours through routine health survey data in a pre-post design with a comparison group. To overcome some methodological limitations mentioned above, a differentiation was made between the moderate and high-intensity intervention neighbourhoods according to the amount of investment per inhabitant. The difference-in-difference method with reweighting was applied to reduce possible bias in socio-economic characteristics between the comparison and intervention groups in the pre- and post-intervention periods.

Materials and methods

Results

The most frequent sociodemographic characteristics both of men and women in the intervention and comparison groups were the following: being 35- to 64-year-old, being employed in manual occupations, being autochthonous, and having been living for more than 6 years in the neighbourhood. In 2016, before the intervention, there was higher unemployment among men and more foreign-born men and women in the intervention groups (Table 1). After intervention, there were differences in age among women and in country of birth among men between the comparison and intervention groups. These differences were removed after weighting data derived from the propensity score for the pre-intervention and post-intervention period (S1 Table 1 in S1 File). Table 1 also shows no population turnover (gentrification) in the sample according to the number of years living in the neighbourhood. This was confirmed by the official population registration data: there were no differences by sex or age group between 2016 and 2021, and the education level improved at a common rate both in the comparison and the intervention groups (S1 Table 2 in S1 File).

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 1. Characteristics of the study population stratified by sex and group.

Barcelona, 2016 and 2021.

https://doi.org/10.1371/journal.pone.0300470.t001

Table 2 shows the results of the intervention on selected outcomes from the DiD weighted regression. High-intensity intervention significantly reduced the relative frequency of women with poor mental health by 15.5% with respect to the comparison group. In the high-intensity intervention group, the frequency of women with poor self-perceived health was significantly reduced by 21.7%, and the frequency of women doing moderate and intense physical activity significantly increased by 13.7%. For these two indicators, the improvement was mainly due to the favourable evolution of the high-intensity intervention group. Finally, the frequency of women with obesity significantly decreased (9.7%), but alcohol abuse increased (5.8%) in the moderate-intensity intervention group; however, these results were not significant in the sensitivity analysis (S1 Table 3 in S1 File).

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 2. Health outcomes and health-related behaviours in the study population stratified by sex and group.

Barcelona, 2016 and 2021.

https://doi.org/10.1371/journal.pone.0300470.t002

Regarding men, the only significant result was an increase of 10.3% in the frequency of those using psychotropic drugs in the high-intensity intervention group. This result was due to a drop in the comparison group, while the two intervention groups showed a parallel ascending trend.

Discussion

This study found a positive impact of urban regeneration programmes on mental health, self-perceived health, and physical activity among women in the high-intensity intervention group.

Apart from the amount invested, citizen participation also seemed to favour the effectiveness of our intervention [13, 15, 16]. The improvements in women’s health but not in men’s may be related to many factors. First, women participated more than men in the actions of the PdB. Indeed, women in the most deprived neighbourhoods are usually less included in the labour market and so tend to have more free time. In addition, in order to reconcile work and family life, female workers often choose jobs close to home or part-time [22]; therefore, they might spend more time in their neighbourhoods and be more sensitive to the impact of an urban regeneration programme than men [23]. Moreover, women in the intervention groups showed worse health outcomes at pre-intervention than men, leaving more room for improvement.

An improvement in mental health was previously detected among different populations in other urban regeneration programmes: among women of the high-intensity intervention group in the neighbourhood-wide intervention ‘District Approach’ in the Netherlands [23]; among men and women in the programme ‘GoWell’ in Glasgow [14]; in deprived areas in Wales, without differentiation by gender [17]. Moreover, in our study, indicators related to psychological distress and physical health status move in the same favourable direction among women. In the Spanish context, previous research has also found effects of benefits (on preventable causes of mortality) in areas of higher investment intensity where two or more urban regeneration programmes overlap [24, 25]. In general, although wide-neighbourhood intervention programmes and citizen participation seem to benefit mental health in areas of high-intensity intervention, the evidence is not clear. For instance, the evaluation of the participatory ‘New Deal for Communities’ intervention in England found no overall effect on mental health, except for most disadvantaged groups [26], neither in the area of intervention in Glasgow [2], nor in the urban regeneration in Northern Ireland [27], nor in the ‘Well London’ project [14].

Self-perceived health status is a less studied outcome. There is weak evidence for its improvement in the ‘Neighbourhood Law’ for 2006–2011 in Barcelona [18] and in the neighbourhood renewal programme in Northern Ireland [25]. No effect on self-perceived health status was observed neither in the greening space intervention in the context of the ‘District Approach’ in the Netherlands [28], nor in the ‘Neighbourhood Renewal Strategy’ in Australia, except for the small subgroup involved in the partnership activities [29]. In our case, the reduction in poor self-perceived health among women is consistent with the reduction in poor mental health; both pre-intervention frequencies evolved downward.

The effects of the interventions on physical activity have been shown to depend on citizen participation [30], and the quality, safety, and civility of urban green spaces [31]. Even though our evaluation makes no distinction between actions undertaken for these different areas of action, we observed an overall improvement in physical activity among women in the high-intensity intervention group. In fact, physical activity and obesity move in the same direction in favour of the intervention for both sexes, even though they are not all statistically significant. In our case, as in a previous study, more walkable public spaces may have been the cause of the improvement in overall health [32].

The increase in the use of psychotropic drugs by men in the high-intensity group was an unexpected result; however, it was driven by a drop in the comparison group. This result contrasts with the null effects found in Denmark for the years 2015 to 2020 [33], and with the favourable evolution of residents in urban regeneration areas in Andalusia (Spain) during the years 2008 to 2015 [34]. We must bear in mind that during the years under study, there have also been two relevant circumstances. On the one hand, the long-lasting effects of the economic crisis during 2016 and the emergence of the COVID-19 pandemic in early 2020. Both events have led to a worsening of mental-related health problems, especially among the male population during the economic crisis and among young adult women during the lockdown of COVID-19. It is difficult to identify to what extent both crises may have differentially affected our comparison and intervention groups and through which mechanisms. If this were the case, it would be a limitation of our research. There is evidence of oscillations in health inequalities during both crises, but in the medium term, they translate into the persistence of inequalities [35, 36]. For this reason, we believe that the effects of both crises on the different evolution of health status between the intervention and control groups are small. In any case, the effects of the intervention must be interpreted depending on the contextual characteristics of the neighbourhoods.

Of the lessons learned about intervention design, the excessive number of interventions rather than focusing on the most determinant ones in each area of action is noteworthy. Second, participation is uneven across neighbourhoods and is lower in the most deprived neighbourhoods. It is therefore necessary to implement a plan to strengthen the capacity for collective action in these neighbourhoods.

This study has several limitations. Caution should be exercised when interpreting the results causally. Even though we used comparison areas and propensity score to make the distributions of population features between comparison and intervention groups comparable, threads of causality could arise if other factors affect both groups differently in previous trends or during the intervention. If the health indicators between the intervention and control groups did not move in parallel in the previous periods, this would imply that factors other than the intervention were at work and the results obtained could not be attributed to the intervention. For example, if the lasting effects of the 2008 economic crisis had affected the intervention group more severely than the control group. This could have further worsened their health indicators in 2016. In such a case, these indicators would tend to return to normal in 2021, and the improvement would not be attributable to the intervention. Another circumstance that could occur is that the intervention itself has changed the social context, and therefore the observed improvements in health cannot be attributed to the intervention. However, we believe that these effects, even if they exist, should be limited and not compromise the overall results. A low sample size is another limitation, especially in the high-intervention group, which does not allow for the analysis of the impact on health inequalities or the testing of heterogeneous results among socioeconomic groups within neighbourhoods. It was not possible to assess if the effect among participants was greater because of the lack of data. Finally, the time when to study the impact of an intervention represents a controversial issue: on the one hand, it may take time to change health behaviours, such as dietary habits or obesity; on the other hand, the impact of the interventions may decay and confounding factors may increase with time. For example, limited results were found in the ‘New Deal for Communities’ intervention within 3.5 years after the intervention, but no results were found after 6 years [26], nor in the ‘District Approach’ intervention [37]. Therefore, for our intervention, a long-term evaluation will be needed to see if the positive health outcomes are sustained over time.

This study also has several strengths. First, it adds evidence to the impact of regeneration programmes on health outcomes and health-related behaviours, an area where evidence is still scarce. Second, the different surveys make it possible to have numerous comparable health outcomes in the two periods and will allow a long-term evaluation. Third, the quasi-experimental design with a comparison group helps to minimise the threats to the internal validity of the study. Finally, the analysis used propensity score to reduce potential biases from possible failure to meet the parallel assumption and diminish the potential compositional change between comparison and intervention groups during the period.

Our results can be useful to implement urban regeneration programmes in other areas. In particular, we derived several lessons from them. First, urban planning practice can probably do better to integrate insights from public health, explicitly establishing the links between the built environment and health outcomes. Second, under budgetary constraints, actions should be designed to concentrate resources on the target population or areas with worse living conditions within neighbourhoods where there is more room for improvement. Third, a specific strategy to target men is needed. Fourth, a qualitative study to report on the perceptions and experiences of local residents could play a pivotal role in strengthening the study’s ability to establish a more robust causal link between the regeneration programme and the observed positive health outcomes. Finally, the re-assessment of urban regeneration programmes at different times would make it possible to disentangle if the impact observed is maintained in the long term.

Conclusions

This study shows positive short-term effects of the urban regeneration programme Pla de Barris 2016–2020 on health outcomes in women in the high-intensity intervention group. These results can guide future interventions in other areas.

Supporting information