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Article

A National, Ecological Study on the Impact of Extreme Precipitation on Walking and Cycling to Work, 2005–2018

by
Marilyn E. Wende
1,*,
Jessica Stroope
2,
Karin Valentine Goins
3,
M. Renée Umstattd Meyer
4,
Jeanette Gustat
5 and
Semra A. Aytur
6
1
Department of Health Education and Behavior, College of Health and Human Performance, University of Florida, Gainesville, FL 32608, USA
2
School of Kinesiology, College of Human Sciences and Education, Louisiana State University, Baton Rouge, LA 70803, USA
3
Division of Preventive and Behavioral Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
4
Department of Public Health, Robbins College of Health and Human Sciences, Baylor University, Waco, TX 76798, USA
5
Department of Epidemiology, Celia Scott Weatherhead School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
6
Department of Health Management and Policy, University of New Hampshire, Durham, NH 03824, USA
*
Author to whom correspondence should be addressed.
Sustainability 2026, 18(4), 1874; https://doi.org/10.3390/su18041874
Submission received: 19 December 2025 / Revised: 4 February 2026 / Accepted: 5 February 2026 / Published: 12 February 2026
(This article belongs to the Special Issue Health, Nature-Based Strategies, and Resilience)
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Abstract

Limited research has examined how increasing extreme precipitation affects active transportation across the United States. This study assesses the longitudinal relationship between extreme precipitation and walking and cycling to work in the context of rising extreme weather and flooding. We conducted a county-level longitudinal analysis using data from the National Environmental Public Health Tracking Network (2005–2018). Five-year estimates of walking and cycling to work among adults aged 16 years and older were obtained from the American Community Survey, and annual population-weighted averages of days with extreme precipitation (≥2 inches) were derived from the North American Land Data Assimilation System. Mixed-effects models with restricted maximum likelihood estimation assessed associations with active transportation, accounting for county-level clustering and adjusting for year, region, poverty rate, water cover, metropolitan status, and park access. Across 3142 U.S. counties, extreme precipitation days increased over time, while walking and cycling to work declined. Each additional extreme precipitation day was associated with a 12.3% decrease in walking and a 3.7% decrease in cycling at baseline, with stronger negative associations over time. Effects were most pronounced in non-metropolitan and Midwestern counties. Findings underscore the importance of climate-resilient transportation planning for sustaining low-carbon, equitable mobility and advancing sustainable development.

1. Introduction

Extreme weather patterns are increasingly prevalent across the United States (US) and globally, from uncontrollable wildfires and droughts to deadly and destructive hurricanes and historic flooding [1,2,3,4]. Within this broader pattern, extreme precipitation or flooding has been increasing in frequency and severity over time in the US. These trends have particularly destructive effects on physical infrastructure and natural landscapes [5]. Beyond the immediate and obvious health effects of these extreme weather patterns, such as unintentional injury and death, there are longer-term direct and indirect effects on physical and mental health outcomes, health behaviors, and access to important health resources [6,7]. Cascading effects of extreme weather events include the following health consequences: stress-related mental disorders [8,9,10,11], poor health-related quality of life [9,12], acute myocardial infarction [9,12], malnutrition [9], less physical activity [6,13,14], and chronic and infectious diseases [9,11,15,16]. While there are many established relationships between extreme weather events and various health behaviors and outcomes, other health behaviors, such as active transportation, remain understudied [6,7,17].
Regular active transportation, or walking and cycling for transportation, positively influences physical activity and related health outcomes (e.g., diabetes, cardiovascular outcomes, many types of cancer) that contribute to leading causes of death globally [18,19,20,21]. In addition to these health benefits, active transportation is a cornerstone of resilient, environmentally sustainable mobility, reducing greenhouse gas emissions, air pollution, and dependence on fossil fuels [22]. Despite this, active transportation rates in the US are low. According to 2007–2011 American Community Survey data, only 3.44% of rural residents and 2.77% of urban residents walked to work, while just 0.40% of rural and 0.58% of urban residents commuted by bicycle [23]. Climate-related extreme precipitation represents a growing threat to the sustainability and resilience of active transportation systems [24]. Research has investigated the effects of increasing frequency of extreme flood events on rates of active transportation [17,25,26,27,28,29], and there are clear mechanisms through which this relationship might exist [6]. First, it is well known that trails and greenways are crucial for facilitating active transportation [30,31,32,33]. What is less widely known is that trails and greenways are commonly located on riparian corridors (i.e., river edges, ocean fronts) and benefit human health by serving as a vegetative buffer that protects communities from flooding [31,34,35]. As multi-functional infrastructure supporting both sustainable transportation and climate adaptation, trails and greenways may be temporarily or indefinitely unavailable for active transportation following flooding events [36]. Additionally, a study in 2019 found that 37% of people live near roads that can be swept away by floods [37]. This means that basic streetscape and sidewalk environments, which are the most common venues for active transportation, may be unavailable during and after flooding [38,39,40]. This is likely to impact human behavior, as neighborhood walkability and pedestrian infrastructure support active transportation [41]. Finally, critical destinations are often in flood zones across the US, including health and transportation facilities (17.9%), medical institutions (2.7%), and educational institutions (2.7%) [35,42], further challenging the long-term sustainability and equity of active transportation under changing climate conditions.
Guided by socioecological models of health behavior and frameworks on social and environmental determinants of health, we propose a conceptual model in which extreme precipitation influences active transportation through interacting environmental, infrastructural, behavioral, and social pathways that shape community resilience [2,43,44,45,46,47]. Extreme precipitation can disrupt sidewalks, trails, greenways, road networks, and bicycle facilities through flooding and erosion, reducing route availability, connectivity, and safety [38,39,40]. Loss or degradation of bike lanes may force cyclists into mixed traffic, increasing crash risk, while rain and wind can reduce visibility, surface stability, and cycling control [27,28,41]. Storm-related congestion and vehicle rerouting may further elevate exposure to traffic hazards for pedestrians and cyclists [48,49]. Perceived and actual safety risks and uncertainty about route accessibility may lead to behavioral avoidance, even after floodwaters recede [41,50,51]. These effects may be amplified among necessity-based commuters (i.e., those with lower socioeconomic status) with limited transportation alternatives, and are modified by contextual factors such as urbanicity, regional climate, baseline infrastructure quality, and neighborhood socioeconomic vulnerability [52,53]. Over time, repeated exposure may compound infrastructure degradation and behavioral shifts unless mitigated by resilient design and policy interventions.
Consistent with this conceptual framework, the negative health consequences of extreme flooding and precipitation do not affect all populations equally [8,54]. Certain socio-demographic groups are more likely to experience more serious and longer-term health issues related to extreme precipitation or flooding events [8,54], and lose access to critical resources during and after flooding [55]. These unequal impacts reflect broader challenges to social sustainability and climate equity, whereby vulnerable populations bear a disproportionate share of climate-related harms [56]. Moreover, improvements to walkability and pedestrian infrastructure during recovery efforts after storms are likely to benefit high socioeconomic status communities disproportionately [57,58,59], potentially reinforcing existing inequities in access to safe and sustainable transportation. Lower economic status counties are less likely to receive Flood Mitigation Assistance funding [60]. Emerging evidence shows that green infrastructure (i.e., practices that use natural processes to manage stormwater runoff, like bioswales, constructed wetlands) is an effective flood risk strategy [54,61,62], but may be less likely to be developed in lower-income areas [63], raising concerns about equitable access to sustainability-oriented solutions. Risk of flooding has also been shown to be higher in rural areas and has more damaging effects on health outcomes due to higher rates of poverty and material deprivation in rural communities [64,65]. Finally, low-income individuals are more likely to walk or cycle to work due to the lack of other affordable or accessible alternatives [52,53], making the protection and resilience of active transportation systems particularly critical for advancing equitable and sustainable development.
Despite increasing reports of floods and related infrastructure damage across the US [66,67,68,69], there is minimal research identifying the potential impact of flooding on active transportation patterns on a national scale. To our knowledge, no research has examined these relationships longitudinally to understand how more extreme weather patterns may negatively influence activity patterns over time, or how to make active transportation systems more resilient. Prior research by Saneinejad et al. in Toronto, Canada (2012) demonstrates that wind speed and rain showers negatively influence cyclists more strongly than pedestrians [25]. Therefore, there may be a need to examine cycling and pedestrian transportation and their relationships with weather patterns separately. Given these considerations, this study assessed the longitudinal relationships between extreme precipitation and both pedestrian and bicycle-based active transportation across the US from 2005 to 2018, examining whether observed trends are consistent with hypothesized infrastructure disruption, behavioral adaptation, and differential vulnerability pathways. We hypothesized that higher frequency of extreme precipitation would be associated with longitudinal declines in walking and cycling to work across U.S. counties, with stronger negative associations in non-metropolitan areas and regions with greater vulnerability to flooding and infrastructure disruption (e.g., the South).

2. Materials and Methods

2.1. Study Design and Setting

This longitudinal, ecological study was conducted at the county level (n = 3142) across the US and incorporated data across multiple years from 2005 to 2018. The time period under study was chosen based on data availability, using data from the Centers for Disease Control and Prevention’s National Environmental Public Health Tracking Network [70].

2.2. Measures

Active transportation is the outcome variable and was measured using 5-year estimates from the annual American Community Survey (ACS), which reports the percentage of workers aged 16 and older who commute to work by walking or cycling (2005–2009 to 2018–2022) [71]. Self-reported walking and cycling were analyzed separately. Data were aggregated at the county level and reflect work commute trips only, and do not include non-work travel and information on trip distance or duration.
Extreme precipitation was measured using modeled data from the North American Land Data Assimilation System (NLDAS), available for all US states except Alaska and Hawaii (2005–2018) [70,72]. Daily precipitation estimates were aggregated to the county level using a population-weighted method, and extreme precipitation days were defined as the number of days between May and September with at least 2 inches of total precipitation. Extreme precipitation was also measured as the number of days where rainfall was in the 99th percentile for sensitivity analyses. Daily precipitation percentiles were calculated separately for each county using its own historical time series of data from 1991–2020 (May–September). While there is no universal approach for defining extreme precipitation, a cut-off of 2 inches of precipitation per day was used to account for the fact that, in some regions of the US, 2 inches is considered extreme [73,74,75]. Additionally, applying a relative threshold (99th percentile) may capture locally extreme events that would be missed by an absolute threshold, accounting for regional variability in typical precipitation patterns [76]. This approach allowed for consistent identification of high-precipitation events across regions and years.
Extreme heat was measured using modeled data from the North American Land Data Assimilation System (NLDAS-2), which provides high-resolution weather estimates for the contiguous USA (2005–2018) [70]. Extreme heat days were defined as days between April and October when the daily maximum heat index exceeded the county-specific 95th percentile for the 1991–2020 baseline period [70]. Daily values were aggregated to the county level using a population-weighted approach to reflect population exposure to extreme heat [70].
The percentage of the population with household income at or below 200% of the federal poverty level was estimated using 5-year estimates from the American Community Survey (ACS) (2006–2010 to 2017–2021). This measure was calculated at the county level to reflect relative economic disadvantage within communities.
Access to parks was measured as the percentage of the population living within 1 mile of a publicly accessible park, using data from the National Environmental Public Health Tracking Network (2010, 2015, 2020) [70]. Estimates were derived using an area-proportion technique, which first calculates the proportion of each Census tract that lies within the 1-mile buffer of park boundaries and then applies this proportion to the tract’s population to estimate the number of people living near a park [70]. These tract-level estimates were aggregated to the county level, and percentages were calculated by dividing the estimated number of people living within 1 mile of a park by the total county population. Spatial analyses were conducted using ESRI basemap data.
The percentage of water cover was measured using data from the National Land Cover Database, which classifies 30 m × 30 m land grid cells by land type [70,77]. The percentage of land covered by water in each county was calculated as the proportion of grid cells classified as “Open Water” or “Perennial Ice/Snow” within county boundaries. This variable provides a proxy for geographic water presence, which may influence local infrastructure, transportation patterns, or exposure to weather-related flooding.
Rural-Urban Continuum Codes (RUCC) from 2013, developed by the US Department of Agriculture, classify counties based on population size and proximity to metropolitan areas [78]. The codes range from 1 (counties in metro areas of 1 million or more) to 9 (nonmetro, completely rural and not adjacent to a metro area). For this analysis, counties were categorized as metropolitan (RUCC codes 1–3) and non-metropolitan (RUCC codes 4–9) to examine differences in environmental exposures and active transportation outcomes by urbanicity.
Counties were grouped into four standard US Census regions based on their state location: Northeast, Midwest, South, and West. This classification follows the US Census Bureau’s regional framework, which is commonly used to examine geographic variation in population characteristics and environmental exposures [79].

2.3. Statistical Analysis

County-level characteristics were presented by year, and one-way ANOVA is used to test for differences in active transportation across year categories. Mixed-effects models used REML to analyze predictors of walking and cycling percentages, incorporating random effects for county-level clustering. Random effects were modeled with a variance components structure, assuming independent, normally distributed county-level effects. Within-county residuals were assumed independent with constant variance. Alternative covariance structures for repeated measures over time (compound symmetry, autoregressive, unstructured) were compared using model fit statistics, and the final structure was selected based on best fit and model convergence. The models included fixed effects including days of precipitation (exposure), year, region (South, Northeast, West, Midwest), percentage of county population designated as low income, water cover percentage, metropolitan/non-metropolitan status, and percentage of people with a park within 1 mile, along with interaction terms for year and days of extreme precipitation, water cover percentage, and access to parks. All covariates were selected using backward elimination with a retention criterion of α = 0.05. In addition, interaction terms were tested between extreme precipitation and extreme heat, region, and rurality, and were included in the final model where significant (with α = 0.05). Stratified analyses were presented for significant interaction terms. To test the robustness of results, a sensitivity analysis was performed using an alternative definition of extreme precipitation based on the 99th percentile of daily precipitation for each county. Tests were considered significant with α = 0.05. Regression coefficients represent absolute changes in percentage points of walking or cycling associated with a one-unit change in the predictor. SAS 9.4 software was used.

3. Results

Between 2005 and 2018, the average number of extreme precipitation days per year increased significantly across US counties in the sample, rising from 1.14 days in 2005–2006 to 1.50 days in 2017–2018 (p < 0.0001) (Table 1; Figure 1). During the same period, the percentage of adults walking to work decreased from 3.33% to 2.69% (p < 0.0001), and the rate of adults cycling to work also decreased from 0.35% to 0.27% (p < 0.0001) (Table 1; Figure 1). Approximately 34.95% (n = 2173) of counties were considered metropolitan, and 65.05% (n = 4044) were considered non-metropolitan. Regionally, 6.98% (n = 3039) of counties were in the Northeast, 33.95% (n = 14,777) in the Midwest, 45.75% (n = 19,913) in the South, and 13.32% (n = 5796) in the West. Averaging 2005–2018, the South had the most extreme precipitation days (1.99 metropolitan, 1.91 non-metropolitan), while the West had the fewest (0.27 metropolitan, 0.26 non-metropolitan) (Figure 2). Generally, there were only slight differences between number of extreme precipitation days between metropolitan and non-metropolitan counties, with the most pronounced differences observed in the Northeast (1.35 metropolitan, 0.89 non-metropolitan). Non-metropolitan areas generally reported higher walking-to-work rates, especially in the West (5.91% vs. 2.76%) and Midwest (4.02% vs. 2.31%), with the South lowest overall (2.07% vs. 1.76%) (Figure 3). Cycling was less common, with metropolitan areas usually higher, most notably in the West (0.98% vs. 0.74%), though the Midwest showed a slight rural advantage (0.36% vs. 0.32%) (Figure 4).
Table 2 presents the longitudinal relationships between days of extreme precipitation, defined as days of rainfall over 2 inches, and rates of walking and cycling to work for counties across the US. At baseline, each additional day of extreme precipitation was associated with 12.32% lower rates of walking to work (95% CI: −16.46%, −8.17%). Over time, this negative effect worsened slightly, by 0.002% per year (95% CI: 0.001%, 0.005%). For cycling to work, each additional day of extreme precipitation was associated with 3.65% lower rates at baseline (95% CI: −4.72%, −2.57%), and this negative effect also worsened slightly, by 0.0066% per year (95% CI: 0.004%, 0.008%).
In metropolitan counties, each additional day of extreme precipitation was associated with 6.36% lower rates of walking to work at baseline (95% CI: −9.62%, −3.11%). This negative effect worsened by 0.003% per year over time (95% CI: 0.001%, 0.005%). For cycling to work in metropolitan counties, each additional day of extreme precipitation was associated with 3.40% lower rates at baseline (95% CI: −4.35%, −2.46%), and this effect worsened slightly by 0.002% per year (95% CI: 0.001%, 0.002%).
In non-metropolitan counties, each additional day of extreme precipitation was associated with 13.46% lower rates of walking to work at baseline (95% CI: −19.70%, −7.21%), and this negative effect worsened slightly by 0.007% annually (95% CI: 0.004%, 0.010%). For cycling to work in non-metropolitan counties, each additional day of extreme precipitation was associated with 3.53% lower rates at baseline (95% CI: −5.13%, −1.93%), with the negative effect worsening by 0.002% per year (95% CI: 0.001%, 0.003%).
In the Northeast, extreme precipitation was not significantly associated with walking to work (p = 0.0526). However, cycling to work in the Northeast showed 3.96% lower rates per day of extreme precipitation at baseline (95% CI: −6.92%, −0.99%), and this negative effect worsened slightly over time, by 0.002% annually (95% CI: 0.0005%, 0.0034%).
In the Midwest, each additional day of extreme precipitation was associated with 25.48% lower rates of walking to work at baseline (95% CI: −35.01%, −15.96%), and this negative effect increased over time by 0.013% per year (95% CI: 0.008%, 0.017%). For cycling to work in the Midwest, each additional day of extreme precipitation was associated with 4.11% lower rates at baseline (95% CI: −6.30%, −1.92%), and this negative effect worsened by 0.002% per year (95% CI: 0.0009%, 0.0032%).
In the South and West, extreme precipitation was not significantly associated with either walking or cycling to work (Table 2).
Sensitivity analyses using a more extreme threshold for precipitation (the 99th percentile) are presented in Supplemental Table S1, with descriptive information included in Supplemental Figure S1.

4. Discussion

This ecological study is, to our knowledge, the first to establish the longitudinal relationship between the annual number of extreme precipitation days and rates of active transportation to work across the US. Overall, the findings suggest that increases in extreme precipitation are associated with slightly declining rates of both walking and cycling to work across US counties, threatening the viability of active transportation as a sustainable, low-carbon mode of daily travel. These negative associations were especially pronounced in non-metropolitan and Midwestern areas, suggesting that certain populations may be more vulnerable to the effects of extreme weather on active commuting. Notably, the interaction terms indicate that in areas with significant negative associations (i.e., the Midwest and Northeast, as well as Metropolitan and Non-Metropolitan areas), the effect of extreme precipitation on reducing active transportation intensified over time. This temporal strengthening highlights a growing sustainability challenge: as climate change accelerates, extreme weather increasingly undermines behaviors that support environmental sustainability, public health, and equitable mobility. Together, these findings suggest the need for climate-resilient, adaptive transportation infrastructure and policy responses, such as improved stormwater management, protected walking and cycling facilities, and climate-informed land-use planning, to sustain active transportation and support long-term sustainable development under worsening weather conditions.

4.1. Comparison to Past Findings

Our findings align with past research in this field, showing that precipitation has a negative relationship with active transportation [17,25,26,27,28,29]. One past study by Chan and Wichman (2020) showed that the number and duration of bicycle trips through bikeshare programs decreased with increased rainfall in 16 North American cities (with 14 in the US) from 2010–2017 [80]. While this is consistent with our findings, bikeshare users may characteristically differ from other cyclists. Research indicates that bikeshare members generate trips more regularly than casual users, but usage remains highly skewed, with many members riding infrequently [81]. Our findings expand on this research by establishing the relationship between extreme precipitation and active commuting to work in a more representative sample of people who cycle to work.
Our findings differ somewhat from past research in Canada (2012), which showed that cyclists experienced the greatest decrease in the number of trips to work as a result of increased precipitation and walk trips to work experienced smaller declines as a result of precipitation compared to other travel modes (i.e., transit, walking, driving, passenger) [25]. In our study, extreme precipitation had a stronger negative effect on walking to work than on cycling, except in sensitivity analyses using a more conservative extreme precipitation cut-off, where extreme precipitation was negatively associated with cycling to work in metropolitan areas. This discrepancy may stem from differences in the type of precipitation examined. Saneinejad et al. (2012) observed the largest differences between cycling and walking when examining a 20% increase in hours with rain or showers (versus a 10% increase), highlighting that cycling behavior is especially sensitive to the precipitation measure used [25]. More recent evidence from a study of a bike-sharing system in Porto Alegre, Brazil (2025) found that extreme rainfall and flooding events were linked with sharp declines in shared bicycle trips (especially utilitarian trips), suggesting that extreme precipitation can meaningfully reduce active transport even in contexts where cycling is used regularly [27].
Our results demonstrated regional differences in the relationships between extreme precipitation and walking and cycling to work. Interestingly, this relationship was only significant in the Midwest. Some past research may help contextualize our findings. For instance, Dilling et al. (2023) found that people living in the Southern US, where hurricanes and flooding are increasingly common, may have developed a level of adaptive capacity to deal with flooding and extreme precipitation events [82]. Using a comparative case study, the authors found that social dimensions, including public acceptance, learning, trust, and collaboration, were crucial factors in developing adaptive capacity in the South [82]. Another explanation for our findings, which show no relationship between increasing precipitation and active transportation in the South, may be that there are higher rates of poverty in the South, suggesting that active transportation is based on need rather than choice. Low-income households are more likely to cycle or walk for transportation, and this is often due to financial motivations [53,83]. Although some research shows that active transportation is less common overall in rural areas, for low-income households, spatial variation between urban, suburban, and rural places decreases, with need-based active transportation driving rural active transportation behaviors [53,83].
Another important consideration is that our study examined extreme precipitation, defined as the total amount of rainfall that exceeded two inches per day. In some locations (e.g., the South), precipitation events exceeding 2 inches are more common [84,85]. In addition, urban areas have more direct runoff due to impermeable surfaces [86,87], which can overwhelm streams and waterways instead of soaking into the ground [88,89]. Considering these differences, there is no universal definition for “extreme precipitation” [85,90]. Therefore, this study included a sensitivity analysis that used a more conservative extreme precipitation cut-off (99th percentile). Sensitivity analyses applying a percentile-based extreme precipitation cut-off showed that extreme precipitation had a negative influence on active transportation over time, specifically for cycling overall and for walking in the Midwest. The sensitivity analysis strengthens confidence in these findings by showing that, even when applying a more conservative threshold for extreme precipitation that accounts for regional differences in what is considered “extreme”, the temporal worsening of its impact on cycling persisted and regional differences were still present. Using a 2-inch absolute cutoff captures universally heavy rainfall, including the core of most hurricanes, but may undercount extreme events in drier regions where 2 inches is rare and highly unusual. In contrast, the 99th percentile identifies days unusually wet relative to each county’s weather patterns, better capturing locally extreme rainfall, including hurricanes in the South and extreme storms in generally dry areas.

4.2. Implications for Research and Practice

This research has several implications for future research. First, greater attention is needed to how climate-resilient pedestrian infrastructure mediates the relationship between extreme precipitation and active transportation, particularly as a mechanism for sustaining low-carbon mobility under changing climate conditions. More granular data capturing infrastructure characteristics may help clarify whether pedestrian environments that offer multiple routes to the same destination are more supportive during extreme weather and enable individuals to adapt to increasing weather-related barriers to destinations [91,92]. Future studies would also benefit from incorporating measures of bicycle lane and shared use path availability, changes in vehicular traffic volume during storm events, and wind conditions, which may meaningfully influence safety, route choice, and willingness to walk or cycle but are not currently available in national datasets. Given that rates of walking and cycling to work were low and declines over time were associated with extreme precipitation, our findings underscore the importance of identifying strategies to stabilize or increase active transportation within sustainable transportation systems. While burgeoning research has highlighted strategies to promote physical activity during extreme heat [6,93,94,95,96], additional evidence-based approaches are needed to support physical activity and active commuting specifically under conditions of heavy rainfall and flooding that reduce exposure, improve perceived safety, and enhance reliability. Further research is also warranted on the intersectional effects of heat, flooding, mental health, and other interacting climate-related stressors [97]. Although extreme heat was not a significant covariate in the relationship between extreme precipitation and walking to work in this study, and no interactive effect between heat and precipitation was observed, the concurrent rise in multiple climate hazards highlights the need for integrative research approaches that reflect real-world exposure patterns [97]. Additional research is also needed on the individual level to understand how mental health may mediate the relationship between extreme precipitation and active transportation [98]. Research has underscored the crucial role of emotions and emotion regulation strategies in mitigating weather-related health impacts, although their specific role in maintaining active transportation and physical activity remains understudied [99,100]. Finally, future research should examine the rate of precipitation (e.g., inches per hour), which may better capture short-term intensity and localized flooding impacts that were not explored in our study.
This research has multiple implications for practice. First, our findings demonstrate a need to mitigate the negative influence of flooding and extreme weather. Green infrastructure and nature-based solutions [101,102,103], such as dune maintenance programs and living shorelines [35], can simultaneously reduce flood risk, enhance environmental sustainability, and support walkable and bikeable environments. Future work should explore how these interventions can maximize local benefits, particularly in low-income communities where green infrastructure investments have historically been lower cost (due to lower availability of funds), involve cost-sharing with wealthier communities, or hinder active transportation. It is critical to understand how to support lower-income communities in leveraging funding after extreme weather events to improve their active transportation facilities. Second, meaningful engagement of local communities is essential. Place attachment and ecological emotions, such as grief or concern over the loss of valued neighborhood spaces, can motivate civic participation and collective action, creating opportunities to advance locally grounded and socially sustainable adaptation strategies [99,104,105,106,107,108,109]. Strategies to leverage these motivations could strengthen adaptations to extreme weather and resilient active transportation initiatives [110,111]. Ultimately, strategies are required to address the low rates of active transportation during extreme precipitation, including infrastructure improvements, public awareness campaigns, and other evidence-based interventions aimed at reducing barriers and enhancing safety. The Building Resilience Against Climate Effects (BRACE) framework provides a flexible, practitioner-focused approach for public health agencies, including state, local, territorial, and Tribal health departments, to plan and implement adaptive, community-driven weather and health interventions [112]. Collectively, these strategies align with multiple United Nations Sustainable Development Goals, including SDG 3 (Good Health and Well-Being), SDG 11 (Sustainable Cities and Communities), SDG 10 (Reduced Inequalities), and SDG 13 (Climate Action), by promoting equitable, climate-resilient transportation systems that support long-term population health and community sustainability [113]. By integrating transportation, land use, and public health priorities, BRACE can support sustainable development goals by promoting health, equity, and resilience in the face of increasing extreme weather events [43,112,114].

4.3. Limitations and Strengths

This study has several limitations. First, our active transportation measure focused on commuting to work among adults and did not capture leisure-time walking and bicycling, or active transportation among children and adolescents. As a result, our estimates likely underestimate total active transportation, particularly among populations less likely to engage in formal work commuting, including children, retirees, informal workers, and rural residents [115,116,117]. Extreme precipitation may have a more profound effect on leisure-time walking and bicycling, given that those who walk or cycle to work may do so out of necessity rather than choice [52,53]. Future research should examine how extreme precipitation affects multiple domains of physical activity and transportation beyond work-based travel. In addition, increasing telework and hybrid work trends may further reduce the representativeness of commuting-based measures and alter exposure to weather-related barriers, highlighting the need to capture broader mobility patterns in future studies [118,119]. Next, Census tract and county-level estimates of precipitation are obtained by processing modeled data. The process of converting grid-level data to other geographies using a population-weighted centroid approach may lead to potential misclassification of precipitation for some areas [120,121]. Modeled data performs relatively well in estimating precipitation; however, the estimates may differ when compared to weather station-based observations [120,121]. As a result, an area may be described as having higher or lower levels of precipitation than occurred. Nonetheless, the data used for this project employed rigorous methods on a national level. Additionally, extreme precipitation exposure was restricted to May–September, excluding winter precipitation such as snow and ice. While this approach aligns with the study focus on rainfall-related flooding and ensures consistency in defining extreme precipitation across regions, findings may not generalize to winter weather conditions that may influence active transportation through different mechanisms (e.g., icy surfaces, snow accumulation, seasonal travel behavior) [122,123,124]. Next, the exposure metric captures the frequency of extreme precipitation days but cannot distinguish whether observed associations reflect short-term behavioral disruption, longer-term infrastructure damage, or adaptive avoidance over time [125]. Finally, this study is conducted at the county level and does not capture the relationship between more local weather patterns and individual active transportation outcomes [126]. While this is an important direction for future research, our study was crucial for establishing an ecological relationship between extreme precipitation and active transportation to work over time.
This study also has several strengths. This is the first study (to our knowledge) to establish the relationship between extreme precipitation and active transportation to work on the national level across the US. This ecological analysis used county-level data to understand the effect of precipitation on population-level active transportation, which may be most useful for informing policy and practice. Next, our study examined the interactive effect of increasing heat exposure and precipitation, as increasing precipitation patterns may coincide with increasing heat exposure. We also accounted for other sociodemographic and environmental factors, including parks and recreational facilities as proxy measures for green infrastructure that may mitigate the negative influence of extreme precipitation. Finally, this study established a temporal relationship between extreme precipitation and active transportation to work as a first step to determining whether this relationship is causal.

5. Conclusions

In conclusion, this study provides longitudinal, national-level evidence that increasing extreme precipitation is associated with declines in walking and cycling to work across U.S. counties, with particularly pronounced effects in non-metropolitan and Midwestern areas. Consistent with our hypothesis, a higher frequency of extreme precipitation was associated with longitudinal reductions in active commuting, and these negative associations were stronger in non-metropolitan settings. Regional patterns partially corroborated the hypothesized vulnerability gradient, with the strongest effects observed in the Midwest rather than the South. These findings demonstrate how climate-driven changes in precipitation patterns can undermine active transportation, a key component of sustainable, low-carbon, and health-promoting mobility systems. By exacerbating physical, infrastructural, and behavioral barriers to walking and cycling, extreme precipitation may widen existing geographic and socio-economic inequities in access to safe and reliable active transportation. Taken together, these results support the need for research, planning, and policy efforts that integrate climate adaptation into transportation and land-use decision-making to support resilience and sustainable mobility under worsening weather conditions. Future research should examine the role of resilient pedestrian infrastructure, the compounding effects of multiple climate-related stressors and mental health, and the influence of precipitation intensity on active transportation and leisure-time walking and cycling behaviors. Addressing these gaps is critical for advancing transportation systems that are not only resilient to climate change but also equitable and supportive of long-term public health and sustainable development goals.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su18041874/s1, Figure S1: Average Days of Extreme Precipitation (defined as days of rainfall over the 99th percentile, 2005–2018) by Region and Metropolitan/Non-metropolitan Status for Counties across the United States, N = 3142; Table S1: Sensitivity analysis for the longitudinal relationship between days of extreme precipitation, defined as in the 99th percentile, and rates of walking and cycling to work for counties across the United States, N = 3142.

Author Contributions

M.E.W.: conceptualization, data curation, formal analysis, methodology, validation, visualization, writing—original draft and writing—reviewing and editing. M.R.U.M.: conceptualization, methodology, and writing—reviewing and editing. J.S.: conceptualization, methodology, writing—original draft and writing—reviewing and editing. S.A.A.: conceptualization, methodology, writing—original draft and writing—reviewing and editing. K.V.G.: conceptualization, methodology, and writing—reviewing and editing. J.G.: conceptualization, methodology, writing—original draft and writing—reviewing and editing. All authors have read and agreed to the published version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets analyzed during the current study are publicly available. Data from the National Environmental Public Health Tracking Network and the US Census American Community Survey can be accessed through their respective repositories.

Acknowledgments

This work is a product of the Physical Activity Policy Research and Evaluation Network (PAPREN). PAPREN is supported by the Health Promotion and Disease Prevention Research Center cooperative agreement #U48DP006885, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services (HHS). The contents are those of the authors and do not necessarily represent the official views of, nor an endorsement, by CDC/HHS, or the U.S. Government.

Conflicts of Interest

The authors declare no conflicts of interest.

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Sustainability 18 01874 g001
Figure 1. Trends in Walking to Work, Cycling to Work, and Extreme Precipitation (defined as days of rainfall over 2 inches, 2005–2018) for Counties across the United States, N = 3142.
Figure 1. Trends in Walking to Work, Cycling to Work, and Extreme Precipitation (defined as days of rainfall over 2 inches, 2005–2018) for Counties across the United States, N = 3142.
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Sustainability 18 01874 g002
Figure 2. Average Days of Extreme Precipitation (defined as days of rainfall over 2 inches, 2005–2018) by Region and Metropolitan/Non-metropolitan Status for Counties across the United States, N = 3142.
Figure 2. Average Days of Extreme Precipitation (defined as days of rainfall over 2 inches, 2005–2018) by Region and Metropolitan/Non-metropolitan Status for Counties across the United States, N = 3142.
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Sustainability 18 01874 g003
Figure 3. Average Percentage of those Walking to Work (2005–2018) by Region and Metropolitan/Non-metropolitan Status for Counties across the United States, N = 3142.
Figure 3. Average Percentage of those Walking to Work (2005–2018) by Region and Metropolitan/Non-metropolitan Status for Counties across the United States, N = 3142.
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Sustainability 18 01874 g004
Figure 4. Average Percentage of those Cycling to Work (2005–2018) by Region and Metropolitan/Non-metropolitan Status for Counties across the United States, N = 3142.
Figure 4. Average Percentage of those Cycling to Work (2005–2018) by Region and Metropolitan/Non-metropolitan Status for Counties across the United States, N = 3142.
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Table 1. Sample characteristics according to year in the sample of counties (N = 3142).
Table 1. Sample characteristics according to year in the sample of counties (N = 3142).
2005–2006
N (%) or Mean (SD)		2007–2008
N (%) or Mean (SD)		2009–2010
N (%) or Mean (SD)		2011–2012
N (%) or Mean (SD)		2013–
2014
N (%) or Mean (SD)		2015–2016
N (%) or Mean (SD)		2017–
2018
N (%) or Mean (SD)		Estimate and
p-Value for Time Trend *
Days of Extreme Precipitation Per Year1.14
(1.46)		1.22
(1.44)		1.30
(1.60)		1.06
(1.55)		1.39
(1.63)		1.47
(1.78)		1.50
(1.68)		61.97
(p < 0.0001)
Percent of Adults Walking to Work3.33
(2.84)		3.21
(2.73)		3.12
(2.66)		3.09
(2.77)		2.96
(2.84)		2.86
(2.77)		2.69
(2.50)		18.30
(p < 0.0001)
Percent of Adults Cycling to Work0.35
(0.66)		0.35
(0.66)		0.36
(0.73)		0.36
(0.72)		0.32
(0.64)		0.30
(0.62)		0.27
(0.59)		7.33
(p < 0.0001)
Percent Living in Poverty63.00 (10.26)62.17
(10.08)		61.39 (10.04)61.94 (10.08)63.25
(10.08)		64.87
(9.93)		65.81
(9.87)		63.74
(p < 0.0001)
Days of Extreme Heat Per Year11.39
(6.93)		11.95
(11.49)		17.13
(14.33)		32.85
(17.05)		15.61
(10.32)		10.41
(8.16)		9.74
(7.50)		94.28
(p < 0.0001)
Percent of the Land Covered by Water2.32
(3.78)		2.26
(3.61)		2.26
(3.61)		2.30
(3.66)		2.30
(3.66)		2.35
(3.80)		2.39
(3.94)		0.65
(0.8098)
Percent with a Park within 1 mile33.03 (29.51)33.03
(29.51)		26.33 (27.34)19.62 (23.11)19.63
(23.11)		33.02 (29.49)33.01 (29.46)183.89
(p < 0.0001)
Bolded values are significant with α = 0.05; * One-way ANOVA was used to test for differences across year categories.
Table 2. Longitudinal relationship between days of extreme precipitation, defined as days of rainfall over 2 inches, and rates of walking and cycling to work for counties across the United States, N = 3142.
Table 2. Longitudinal relationship between days of extreme precipitation, defined as days of rainfall over 2 inches, and rates of walking and cycling to work for counties across the United States, N = 3142.
ModelPercent Walking to WorkPercent Cycling to Work
β (95% CI)p-Valueβ (95% CI)p-Value
Overall
Days of Precipitation > 2in−12.32
(−4.72, −2.57) 1		<0.0001−3.65
(−4.72, −2.57) 2		<0.0001
Interaction: Days of Precipitation > 2in & Time (in years)0.002
(−16.46, −8.17) 1		<0.00010.006
(0.004, 0.008) 2		<0.0001
Metropolitan
Days of Precipitation > 2in−6.36
(−9.62, −3.11) 1		0.0001−3.40
(−4.35, −2.46) 2		<0.0001
Interaction: Days of Precipitation > 2in & Time (in years)0.003
(0.001, 0.005) 1		0.00010.002
(0.001, 0.002) 2		<0.0001
Non-Metropolitan
Days of Precipitation > 2in−13.46
(−19.70, −7.21) 1		<0.0001−3.53
(−5.13, −1.93) 2		<0.0001
Interaction: Days of Precipitation > 2in & Time (in years)0.007
(0.004, 0.010) 1		<0.00010.002
(0.001, 0.003) 2		<0.0001
Northeast
Days of Precipitation > 2in−10.14
(−20.38, 0.11) 1		0.0526−3.96
(−6.92, −0.99)		0.0089
Interaction: Days of Precipitation > 2in & Time (in years)0.005
(−0.000, 0.010) 1		0.05210.002
(0.0005, 0.0034)		0.0088
Midwest
Days of Precipitation > 2in−25.48
(−35.01, −15.96) 1		<0.0001−4.11
(−6.30, −1.92)		0.0005
Interaction: Days of Precipitation > 2in & Time (in years)0.013
(0.008, 0.017) 1		<0.00010.002
(0.0009, 0.0032)		0.0005
South
Days of Precipitation > 2in0.96
(−3.38, 5.30) 1		0.66470.52
(−0.49, 1.52)		0.3147
Interaction: Days of Precipitation > 2in & Time (in years)−0.0005
(−0.003, 0.002) 1		0.6603−0.0003
(−0.0008, 0.0002)		0.3161
West
Days of Precipitation > 2in11.45
(−16.74, 39.63) 1		0.4263−5.24
(−13.30, 2.83)		0.2036
Interaction: Days of Precipitation > 2in & Time (in years)−0.006
(−0.020, 0.008) 1		0.42820.003
(−0.001, 0.006)		0.2046
Bolded values are significant with α = 0.05; 1 Adjusting for days of percent living in poverty, region, rurality, days of precipitation × year, days of precipitation × rurality, and days of precipitation × region. 2 Adjusting for days of extreme heat, percent living in poverty, percent of the land covered in water, region, rurality, days of precipitation × year, extreme heat*year, and days of precipitation × region.
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Wende, M.E.; Stroope, J.; Valentine Goins, K.; Umstattd Meyer, M.R.; Gustat, J.; Aytur, S.A. A National, Ecological Study on the Impact of Extreme Precipitation on Walking and Cycling to Work, 2005–2018. Sustainability 2026, 18, 1874. https://doi.org/10.3390/su18041874

AMA Style

Wende ME, Stroope J, Valentine Goins K, Umstattd Meyer MR, Gustat J, Aytur SA. A National, Ecological Study on the Impact of Extreme Precipitation on Walking and Cycling to Work, 2005–2018. Sustainability. 2026; 18(4):1874. https://doi.org/10.3390/su18041874

Chicago/Turabian Style

Wende, Marilyn E., Jessica Stroope, Karin Valentine Goins, M. Renée Umstattd Meyer, Jeanette Gustat, and Semra A. Aytur. 2026. "A National, Ecological Study on the Impact of Extreme Precipitation on Walking and Cycling to Work, 2005–2018" Sustainability 18, no. 4: 1874. https://doi.org/10.3390/su18041874

APA Style

Wende, M. E., Stroope, J., Valentine Goins, K., Umstattd Meyer, M. R., Gustat, J., & Aytur, S. A. (2026). A National, Ecological Study on the Impact of Extreme Precipitation on Walking and Cycling to Work, 2005–2018. Sustainability, 18(4), 1874. https://doi.org/10.3390/su18041874

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