Sex Differences in the Amount and Patterns of Car-Driving Exposure in Spain, 2014 to 2017: An Application of a Quasi-Induced Exposure Approach
Abstract
:1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Bouaoun, L.; Haddak, M.M.; Amoros, E. Road Crash Fatality Rates in France: A Comparison of Road User Types, Taking Account of Travel Practices. Accid Anal. Prev. 2015, 75, 217–225. [Google Scholar] [CrossRef] [PubMed]
- Dhondt, S.; Macharis, C.; Terryn, N.; Van Malderen, F.; Putman, K. Health Burden of Road Traffic Accidents, an Analysis of Clinical Data on Disability and Mortality Exposure Rates in Flanders and Brussels. Accid Anal. Prev. 2013, 50, 659–666. [Google Scholar] [CrossRef] [PubMed]
- González-Sánchez, G.; Maeso-González, E.; Olmo-Sánchez, M.I.; Gutiérrez-Bedmar, M.; Mariscal, A.; García-Rodríguez, A. Road Traffic Injuries, Mobility and Gender. Patterns of Risk in Southern Europe. J. Transp. Health 2018, 8, 35–43. [Google Scholar] [CrossRef]
- McAndrews, C.; Beyer, K.; Guse, C.E.; Layde, P. Revisiting Exposure: Fatal and Non-Fatal Traffic Injury Risk across Different Populations of Travelers in Wisconsin, 2001–2009. Accid Anal. Prev. 2013, 60, 103–112. [Google Scholar] [CrossRef] [PubMed]
- Mindell, J.S.; Leslie, D.; Wardlaw, M. Exposure-Based, ‘Like-for-Like’ Assessment of Road Safety by Travel Mode Using Routine Health Data. PLoS ONE 2012, 7, e50606. [Google Scholar] [CrossRef]
- Van den Bossche, F.A.M.; Wets, G.; Brijs, T. Analysis of Road Risk by Age and Gender Category: Time Series Approach. Transp. Res. Rec. 2007, 2019, 7–14. [Google Scholar] [CrossRef]
- Al-Balbissi, A.H. Role of Gender in Road Accidents. Traffic Inj. Prev. 2003, 4, 64–73. [Google Scholar] [CrossRef] [Green Version]
- Cullen, P.; Möller, H.; Woodward, M.; Senserrick, T.; Boufous, S.; Rogers, K.; Brown, J.; Ivers, R. Are There Sex Differences in Crash and Crash-Related Injury between Men and Women? A 13-Year Cohort Study of Young Drivers in Australia. SSM Popul. Health 2021, 14, 100816. [Google Scholar] [CrossRef]
- Massie, D.L.; Green, P.E.; Campbell, K.L. Crash Involvement Rates by Driver Gender and the Role of Average Annual Mileage. Accid Anal. Prev. 1997, 29, 675–685. [Google Scholar] [CrossRef]
- Regev, S.; Rolison, J.J.; Moutari, S. Crash Risk by Driver Age, Gender, and Time of Day Using a New Exposure Methodology. J. Saf. Res. 2018, 66, 131–140. [Google Scholar] [CrossRef]
- Santamariña-Rubio, E.; Pérez, K.; Olabarria, M.; Novoa, A.M. Gender Differences in Road Traffic Injury Rate Using Time Travelled as a Measure of Exposure. Accid Anal. Prev. 2014, 65, 1–7. [Google Scholar] [CrossRef]
- Visby, R.H.; Lundholt, K. Gender Differences in Danish Road Accidents. Transp. Res. Rec. 2018, 2672, 166–174. [Google Scholar] [CrossRef]
- Claret, P.L.; del Castillo, J.D.D.L.; Moleón, J.J.J.; Cavanillas, A.B.; Martín, M.G.; Vargas, R.G. Age and Sex Differences in the Risk of Causing Vehicle Collisions in Spain, 1990 to 1999. Accid Anal. Prev. 2003, 35, 261–272. [Google Scholar] [CrossRef]
- Jones, S.J. Girls Crash Too: Trends in Single Vehicle Crash Rates in Young and Adult, Male and Female Drivers. Inj. Prev. 2017, 23, 186–189. [Google Scholar] [CrossRef]
- Mannocci, A.; Saulle, R.; Villari, P.; La Torre, G. Male Gender, Age and Low Income Are Risk Factors for Road Traffic Injuries among Adolescents: An Umbrella Review of Systematic Reviews and Meta-Analyses. J. Public Health 2019, 27, 263–272. [Google Scholar] [CrossRef]
- Monárrez-Espino, J.; Hasselberg, M.; Laflamme, L. First Year as a Licensed Car Driver: Gender Differences in Crash Experience. Saf. Sci. 2006, 44, 75–85. [Google Scholar] [CrossRef]
- Massie, D.L.; Campbell, K.L.; Williams, A.F. Traffic Accident Involvement Rates by Driver Age and Gender. Accid Anal. Prev. 1995, 27, 73–87. [Google Scholar] [CrossRef]
- Frändberg, L.; Vilhelmson, B. More or Less Travel: Personal Mobility Trends in the Swedish Population Focusing Gender and Cohort. J. Transp. Geogr. 2011, 19, 1235–1244. [Google Scholar] [CrossRef]
- McGuckin, N.A.; Fucci, A. Summary of Travel Trends: 2017 National Household Travel Survey; Report nº FHWA-PL-18-019; U.S. Department of Transportation, Federal Highway Administration: Washington, DC, USA, 2018. [Google Scholar]
- Minton, J.; Clark, J. Driving Segregation: Age, Gender and Emerging Inequalities. In Geographies of Transport and Ageing; Curl, A., Musselwhite, C., Eds.; Springer International Publishing: Cham, Switzerland, 2018; pp. 25–50. ISBN 978-3-319-76360-6. [Google Scholar]
- Rosenbloom, S. Understanding Women’s and Men’s Travel Patterns: The Research Challenge. In Proceedings of the Conference on Research on Women’s Issues in Transportation, Chicago, IL, USA, 18–20 November 2004. [Google Scholar]
- Sivak, M. Female Drivers in the United States, 1963-2013: From a Minority to a Majority? Report No. UMTRI-2015-16. 2015. Available online: https://deepblue.lib.umich.edu/handle/2027.42/111899 (accessed on 11 August 2021).
- Lourens, P.F.; Vissers, J.A.M.M.; Jessurun, M. Annual Mileage, Driving Violations, and Accident Involvement in Relation to Drivers’ Sex, Age, and Level of Education. Accid Anal. Prev. 1999, 31, 593–597. [Google Scholar] [CrossRef]
- Jiménez-Mejías, E.; Prieto, C.A.; Martínez-Ruiz, V.; del Castillo, J.D.D.L.; Lardelli-Claret, P.; Jiménez-Moleón, J.J. Gender-Related Differences in Distances Travelled, Driving Behaviour and Traffic Accidents among University Students. Transp. Res. Part. F Traffic Psychol. Behav. 2014, 27, 81–89. [Google Scholar] [CrossRef]
- INE (Instituto Nacional de Estadística). Cifras de Población. Available online: https://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176951&menu=ultiDatos&idp=1254735572981 (accessed on 10 August 2021).
- DGT. Portal Estadístico de La Dirección General de Tráfico. Available online: https://sedeapl.dgt.gob.es/WEB_IEST_CONSULTA/ (accessed on 11 August 2021).
- DGT. Comunicación de Accidentes de Tráfico—ARENA. Available online: https://sede.dgt.gob.es/es/movilidad/comunicacion_accidentes_trafico_ARENA/# (accessed on 11 August 2021).
- Jiang, X.; Lyles, R.W.; Guo, R. A Comprehensive Review on the Quasi-Induced Exposure Technique. Accid Anal. Prev. 2014, 65, 36–46. [Google Scholar] [CrossRef]
- R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2019. [Google Scholar]
- Wickham, H.; Averick, M.; Bryan, J.; Chang, W.; McGowan, L.D.; François, R.; Grolemund, G.; Hayes, A.; Henry, L.; Hester, J.; et al. Welcome to the Tidyverse. J. Open Source Softw. 2019, 4, 1686. [Google Scholar] [CrossRef]
- StataCorp. Stata Statistical Software: Release 15; StataCorp LLC: College Station, TX, USA, 2017. [Google Scholar]
- Delbosc, A.; Currie, G. Changing Demographics and Young Adult Driver License Decline in Melbourne, Australia (1994–2009). Transportation 2014, 41, 529–542. [Google Scholar] [CrossRef]
- Hjorthol, R. Decreasing Popularity of the Car? Changes in Driving Licence and Access to a Car among Young Adults over a 25-Year Period in Norway. J. Transp. Geogr. 2016, 51, 140–146. [Google Scholar] [CrossRef] [Green Version]
- Siren, A.; Haustein, S. Driving Cessation Anno 2010: Which Older Drivers Give Up Their License and Why? Evidence From Denmark. J. Appl. Gerontol. 2016, 35, 18–38. [Google Scholar] [CrossRef] [Green Version]
- Barrett, A.E.; Gumber, C.; Douglas, R. Explaining Gender Differences in Self-Regulated Driving: What Roles Do Health Limitations and Driving Alternatives Play? Ageing Soc. 2018, 38, 2122–2145. [Google Scholar] [CrossRef]
- Gauvin, L.; Tizzoni, M.; Piaggesi, S.; Young, A.; Adler, N.; Verhulst, S.; Ferres, L.; Cattuto, C. Gender Gaps in Urban Mobility. Humanit. Soc. Sci. Commun. 2020, 7, 11. [Google Scholar] [CrossRef]
- McQuaid, R.W.; Chen, T. Commuting Times—The Role of Gender, Children and Part-Time Work. Res. Transp. Econ. 2012, 34, 66–73. [Google Scholar] [CrossRef]
- Wei-Shiuen, N.; Acker, A. Understanding Urban Travel Behaviour by Gender for Efficient and Equitable Transport Policies. 2018. Available online: https://www.itf-oecd.org/understanding-urban-travel-behaviour-gender-efficient-and-equitable-transport-policies (accessed on 11 August 2021).
- Gwyther, H.; Holland, C. The Effect of Age, Gender and Attitudes on Self-Regulation in Driving. Accid Anal. Prev. 2012, 45, 19–28. [Google Scholar] [CrossRef] [PubMed]
- Taylor, J.E. The Extent and Characteristics of Driving Anxiety. Transp. Res. Part. F Traffic Psychol. Behav. 2018, 58, 70–79. [Google Scholar] [CrossRef]
- Tilley, S.; Houston, D. The Gender Turnaround: Young Women Now Travelling More than Young Men. J. Transp. Geogr. 2016, 54, 349–358. [Google Scholar] [CrossRef] [Green Version]
- Asse, L.M.D.; Fabrigoule, C.; Helmer, C.; Laumon, B.; Lafont, S. Automobile Driving in Older Adults: Factors Affecting Driving Restriction in Men and Women. J. Am. Geriatr. Soc. 2014, 62, 2071–2078. [Google Scholar] [CrossRef]
- Hakamies-Blomqvist, L.; Siren, A. Deconstructing a Gender Difference: Driving Cessation and Personal Driving History of Older Women. J. Saf. Res. 2003, 34, 383–388. [Google Scholar] [CrossRef]
- Hassan, H.H.S.A.; King, M.; Watt, K. Older adults and driving reduction: Is the gender gap narrowing? In Proceedings of the 2015 Australasian Road Safety Conference (ARSC2015), Gold Coast, Australia, 14–16 October 2015; Cameron, I., Haworth, N., McIntosh, L., Eds.; Australasian College of Road Safety (ACRS): Sydney, Australia, 2015; pp. 1–10. [Google Scholar]
- Koppel, S.; Charlton, J.; Kopinathan, C.; Taranto, D. Are Child Occupants a Significant Source of Driving Distraction? Accid Anal. Prev. 2011, 43, 1236–1244. [Google Scholar] [CrossRef]
- Adanu, E.K.; Hainen, A.; Jones, S. Latent Class Analysis of Factors That Influence Weekday and Weekend Single-Vehicle Crash Severities. Accid Anal. Prev. 2018, 113, 187–192. [Google Scholar] [CrossRef]
- Kim, J.-K.; Ulfarsson, G.F.; Kim, S.; Shankar, V.N. Driver-Injury Severity in Single-Vehicle Crashes in California: A Mixed Logit Analysis of Heterogeneity Due to Age and Gender. Accid Anal. Prev. 2013, 50, 1073–1081. [Google Scholar] [CrossRef] [PubMed]
- Zhang, G.; Yau, K.K.W.; Zhang, X.; Li, Y. Traffic Accidents Involving Fatigue Driving and Their Extent of Casualties. Accid Anal. Prev. 2016, 87, 34–42. [Google Scholar] [CrossRef] [PubMed]
- Zwerling, C.; Peek-Asa, C.; Whitten, P.; Choi, S.; Sprince, N.; Jones, M. Fatal Motor Vehicle Crashes in Rural and Urban Areas: Decomposing Rates into Contributing Factors. Inj. Prev. 2005, 11, 24–28. [Google Scholar] [CrossRef]
- Biswas, S.; Singh, B.; Saha, A. Assessment of level-of-service on urban arterials: A case study in Kolkata metropolis. Int. J. Traffic Transp. Eng. 2016, 6, 303–312. [Google Scholar] [CrossRef]
- Demasi, F.; Loprencipe, G.; Moretti, L. Road Safety Analysis of Urban Roads: Case Study of an Italian Municipality. Safety 2018, 4, 58. [Google Scholar] [CrossRef] [Green Version]
- Alfonsi, R.; Persia, L.; Tripodi, A.; Usami, D.S. Advances in Road Safety Management Analysis. Transp. Res. Procedia 2016, 14, 2064–2073. [Google Scholar] [CrossRef] [Green Version]
- Amoros, E.; Martin, J.L.; Laumon, B. Under-reporting of road crash casualties in France. Accid Anal. Prev. 2006, 38, 627–635. [Google Scholar] [CrossRef]
- Abay, K.A. Investigating the nature and impact of reporting bias in road crash data. Transp. Res A Policy Pract 2015, 71, 31–45. [Google Scholar] [CrossRef]
- Sanjurjo-de-No, A.; Arenas-Ramírez, B.; Mira, J.; Aparicio-Izquierdo, F. Driver Liability Assessment in Vehicle Collisions in Spain. Int. J. Environ. Res. Public Health 2021, 18, 1475. [Google Scholar] [CrossRef]
- Cooper, P.J.; Meckle, W.; Andersen, L. The Efficiency of Using Non-Culpable Crash-Claim Involvements from Insurance Data as a Means of Estimating Travel Exposure for Road User Sub-Groups. J. Saf. Res. 2010, 41, 129–136. [Google Scholar] [CrossRef] [PubMed]
- Lardelli-Claret, P.; Luna-del-Castillo, J.D.; Jiménez-Mejías, E.; Pulido-Manzanero, J.; Barrio-Anta, G.; García-Martín, M.; Jiménez-Moleón, J.J. Comparison of Two Methods to Assess the Effect of Age and Sex on the Risk of Car Crashes. Accid Anal. Prev. 2011, 43, 1555–1561. [Google Scholar] [CrossRef] [PubMed]
- Shen, S.; Pope, C.N.; Stamatiadis, N.; Zhu, M. Validation of Not-at-Fault Driver Representativeness Assumption for Quasi-Induced Exposure Using, U.S. National Traffic Databases. J. Saf. Res. 2019, 71, 243–249. [Google Scholar] [CrossRef] [PubMed]
- Zhang, G.; Jiang, X.; Qiu, X.; Fan, Y.; Huang, C.; Wei, M. Validating the Underlying Assumption of Quasi-Induced Exposure Technique Disaggregated by Crash Injury Severity. J. Saf. Res. 2021, 76, 197–204. [Google Scholar] [CrossRef]
- Zhao, S.; Wang, K.; Jackson, E. Evaluation of Not-At-Fault Assumption in Quasi-Induced Exposure Method Using Traffic Crash Data at Varied Geographical Levels. Transp. Res. Rec. 2019, 2673, 593–604. [Google Scholar] [CrossRef]
- Murguialday, B.; Martínez, I.; Díaz, S.; Paz, V. Perspectiva de Género y Seguridad Vial. Available online: https://www.trafikoa.eus/wps/wcm/connect/trafico/8bc145004be87828b2cbffca98532cc5/Murgibe_INFORME+febrero2016.pdf?MOD=AJPERES&CVID=mflcHME (accessed on 11 August 2021).
- Polk, M. Gendering Climate Change through the Transport Sector. Kvinder Køn Forskning 2009, 73–78. [Google Scholar] [CrossRef] [Green Version]
Persons-Years of Spanish Population ≥18 y.o. | Person-Years of Licensed Car Drivers (≥18 y.o.) | NRDs * Involved in Clean Collisions | Licensed Drivers/Population | NRDs/Licensed Drivers | |||||
---|---|---|---|---|---|---|---|---|---|
Age | Males | Females | Males | Females | Males | Females | OR | OR | 95% CI |
All ages | 72,845,320 | 76,210,495 | 34,152,837 | 40,096,817 | 32,684 | 19,145 | 1.12 | 0.50 | (0.49–0.51) |
18 to 20 | 2,689,048 | 2,540,808 | 842,219 | 705,390 | 928 | 463 | 0.89 | 0.60 | (0.53–0.67) |
21 to 24 | 3,754,844 | 3,618,528 | 1,864,948 | 2,054,996 | 2129 | 1468 | 1.14 | 0.63 | (0.59–0.67) |
25 to 29 | 5,135,457 | 5,100,161 | 2,968,105 | 3,575,295 | 3360 | 2547 | 1.21 | 0.63 | (0.60–0.66) |
30 to 34 | 6,090,909 | 6,094,552 | 3,575,153 | 4,462,014 | 3755 | 2839 | 1.25 | 0.61 | (0.58–0.64) |
35 to 39 | 7,634,711 | 7,459,244 | 4,372,787 | 5,493,925 | 4488 | 3183 | 1.29 | 0.56 | (0.54–0.59) |
40 to 44 | 8,009,656 | 7,738,559 | 4,157,080 | 5,473,925 | 4213 | 2917 | 1.36 | 0.53 | (0.50–0.55) |
45 to 49 | 7,528,746 | 7,386,104 | 3,769,103 | 4,940,334 | 3535 | 2174 | 1.34 | 0.47 | (0.44–0.49) |
50 to 54 | 6,974,329 | 7,012,825 | 3,284,355 | 4,238,550 | 2947 | 1526 | 1.28 | 0.40 | (0.38–0.43) |
55 to 59 | 6,111,803 | 6,297,199 | 2,814,420 | 3,579,022 | 2477 | 992 | 1.23 | 0.31 | (0.29–0.34) |
60 to 64 | 5,066,409 | 5,360,808 | 2,325,983 | 2,551,835 | 1756 | 520 | 1.04 | 0.27 | (0.24–0.30) |
65 to 69 | 4,513,768 | 4,968,627 | 1,934,249 | 1,741,161 | 1372 | 300 | 0.82 | 0.24 | (0.21–0.28) |
70 to 74 | 3,751,614 | 4,355,627 | 1,186,658 | 851,112 | 907 | 145 | 0.62 | 0.22 | (0.19–0.27) |
>74 | 5,584,026 | 8,277,453 | 1,057,777 | 429,258 | 817 | 71 | 0.27 | 0.21 | (0.17–0.27) |
Variable | Categories | OR | 95% CI |
---|---|---|---|
Area | Urban | 0.55 | (0.53–0.56) |
Open roads | 0.47 | (0.45–0.48) | |
Type of road | Highway/Motorway | 0.49 | (0.47–0.51) |
Conventional two-lane roads | 0.46 | (0.44–0.47) | |
Streets | 0.55 | (0.53–0.57) | |
Other | 0.47 | (0.43–0.51) | |
Time of day | 12:00 to 5:59 a.m. | 0.35 | (0.32–0.39) |
6:00 to 11:00 a.m. | 0.54 | (0.52–0.56) | |
12:00 to 5:59 p.m. | 0.53 | (0.52–0.55) | |
6:00 to 11:59 p.m. | 0.44 | (0.42–0.45) | |
Type of day | Weekday | 0.53 | (0.52–0.54) |
Weekend | 0.39 | (0.37–0.40) | |
Road Surface | Normal | 0.50 | (0.49–0.51) |
Altered | 0.49 | (0.46–0.51) | |
Weather conditions | Good | 0.50 | (0.49–0.51) |
Adverse | 0.49 | (0.47–0.51) | |
Light conditions | Daylight | 0.52 | (0.51–0.53) |
Sunrise/sunset with artificial lighting | 0.48 | (0.44–0.53) | |
Sunrise/sunset without artificial lighting | 0.48 | (0.43–0.54) | |
Darkness with artificial lighting | 0.44 | (0.42–0.47) | |
Darkness without artificial lighting | 0.37 | (0.35–0.40) | |
Traffic density | Low | 0.47 | (0.46–0.48) |
Medium | 0.53 | (0.51–0.55) | |
High | 0.54 | (0.51–0.56) | |
Very high | 0.56 | (0.50–0.63) |
Driving on Open Roads (Ref.: Urban Areas) | Driving from 12:00 to 5:59 a.m. (Ref.: 6:00 to 11:59 a.m.) | Driving from 6:00 to 23:59 p.m. (Ref.: 6:00 to 11:59 a.m.) | Driving without Natural or Artificial Light (Ref.: Daylight) | Driving on Weekends (Ref: Weekday) | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Age | OR | 95% CI | RRR | 95% CI | RRR | 95% CI | RRR | 95% CI | OR | 95% CI |
18 to 20 | 1.24 | (0.99–1.55) | 1.06 | (0.64–1.76) | 1.15 | (0.89–1.49) | 0.73 | (0.47–1.12) | 0.90 | (0.69–1.17) |
21 to 24 | 0.98 | (0.86–1.12) | 0.76 | (0.56–1.04) | 0.86 | (0.73–1.00) | 0.77 | (0.60–1.00) | 0.92 | (0.79–1.08) |
25 to 29 | 0.97 | (0.88–1.08) | 0.70 | (0.53–0.91) | 0.77 | (0.68–0.87) | 0.68 | (0.56–0.83) | 0.71 | (0.63–0.81) |
30 to 34 | 0.94 | (0.85–1.04) | 0.50 | (0.37–0.69) | 0.75 | (0.67–0.85) | 0.63 | (0.52–0.76) | 0.68 | (0.61–0.77) |
35 to 39 | 0.88 | (0.81–0.97) | 0.54 | (0.39–0.74) | 0.71 | (0.63–0.79) | 0.60 | (0.50–0.72) | 0.71 | (0.63–0.79) |
40 to 44 | 0.80 | (0.73–0.88) | 0.56 | (0.41–0.78) | 0.78 | (0.69–0.87) | 0.61 | (0.50–0.73) | 0.72 | (0.64–0.81) |
45 to 49 | 0.79 | (0.71–0.88) | 0.70 | (0.49–0.98) | 0.87 | (0.76–0.99) | 0.76 | (0.61–0.94) | 0.71 | (0.62–0.82) |
50 to 54 | 0.86 | (0.76–0.98) | 0.42 | (0.26–0.71) | 0.81 | (0.69–0.94) | 0.79 | (0.61–1.02) | 0.70 | (0.60–0.81) |
55 to 59 | 0.83 | (0.71–0.96) | 0.30 | (0.16–0.55) | 0.76 | (0.64–0.92) | 0.66 | (0.49–0.89) | 0.66 | (0.55–0.80) |
60 to 64 | 0.74 | (0.61–0.90) | 0.64 | (0.32–1.29) | 0.73 | (0.57–0.94) | 0.88 | (0.58–1.33) | 0.76 | (0.59–0.96) |
65 to 69 | 0.66 | (0.52–0.86) | 1.37 | (0.57–3.27) | 0.95 | (0.70–1.29) | 0.99 | (0.61–1.60) | 0.91 | (0.67–1.22) |
70 to 74 | 0.54 | (0.38–0.78) | 1.24 | (0.14–10.82) | 0.86 | (0.55–1.34) | 0.44 | (0.16–1.23) | 0.70 | (0.45–1.10) |
>74 | 0.80 | (0.48–1.34) | 1.37 | (0.17–11.11) | 1.19 | (0.61–2.34) | 1.12 | (0.39–3.24) | 1.18 | (0.68–2.05) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Mateos-Granados, J.; Martín-delosReyes, L.M.; Rivera-Izquierdo, M.; Jiménez-Mejías, E.; Martínez-Ruiz, V.; Lardelli-Claret, P. Sex Differences in the Amount and Patterns of Car-Driving Exposure in Spain, 2014 to 2017: An Application of a Quasi-Induced Exposure Approach. Int. J. Environ. Res. Public Health 2021, 18, 13255. https://doi.org/10.3390/ijerph182413255
Mateos-Granados J, Martín-delosReyes LM, Rivera-Izquierdo M, Jiménez-Mejías E, Martínez-Ruiz V, Lardelli-Claret P. Sex Differences in the Amount and Patterns of Car-Driving Exposure in Spain, 2014 to 2017: An Application of a Quasi-Induced Exposure Approach. International Journal of Environmental Research and Public Health. 2021; 18(24):13255. https://doi.org/10.3390/ijerph182413255
Chicago/Turabian StyleMateos-Granados, José, Luis Miguel Martín-delosReyes, Mario Rivera-Izquierdo, Eladio Jiménez-Mejías, Virginia Martínez-Ruiz, and Pablo Lardelli-Claret. 2021. "Sex Differences in the Amount and Patterns of Car-Driving Exposure in Spain, 2014 to 2017: An Application of a Quasi-Induced Exposure Approach" International Journal of Environmental Research and Public Health 18, no. 24: 13255. https://doi.org/10.3390/ijerph182413255