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The Journals of Gerontology Series B: Psychological Sciences and Social Sciences logoLink to The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
. 2020 Jun 1;75(10):2268–2277. doi: 10.1093/geronb/gbaa070

Driver License Renewal Laws and Older Adults’ Daily Driving, United States, 2003–2017

Sijun Shen 1,2, Kendra L Ratnapradipa 3, Gina C Pervall 4, Meredith Sweeney 5, Motao Zhu 1,2,6,✉
Editor: Deborah Carr
PMCID: PMC7664315  PMID: 32479637

Abstract

Objectives

Around the world, aging populations pose significant concerns regarding their community mobility and transportation safety. Most previous studies in the United States have focused on the associations between driver license renewal laws and crash outcomes among older adults (65 years and older). Few studies have evaluated the impact of driver license renewal laws on older adults’ community mobility. This study aimed to identify the associations between driver license renewal laws and older males’ and females’ daily driving likelihood and duration.

Method

The 2003–2017 American Time Use Survey data were merged with driver license renewal legislation using ages 55–64 to control for effects of non-licensure factors (e.g., gasoline price). Weighted Poisson and linear regression models were used to estimate the associations of various driver licensure provisions with older males’ and females’ daily driving likelihood and duration.

Results

A shorter in-person renewal period and the presence of mandatory reporting laws for physicians were associated with a lower daily driving likelihood and shorter driving duration among females aged 75 years or older. The presence of mandatory reporting laws was also associated with reduced daily driving likelihood and duration for males aged 65–74 years.

Discussion

Policymakers should be aware that males and females may respond differently to older driver licensure laws, which may require distinct interventions to preserve their mobility. Future studies should consider the gender disparities when examining the association between driver licensure policies and older adults’ transportation safety and mobility.

Keywords: Driving, Epidemiology, Mobility, Travel behavior

By 2030, older adults (aged 65 years or older) are expected to make up at least 20% of the U.S. population (Colby & Ortman, 2015). Compared to the previous generation, Baby Boomers are projected to drive more miles later in life (Wang & Carr, 2004). Driving is expected to remain the primary means of transportation and is a key component of mobility and functional independence (Choi, Adams, & Mezuk, 2012; Dickerson et al., 2007; Dickerson et al., 2019; Shen et al., 2017). However, age- and health-related conditions may impair older adults’ ability to drive safely (Anstey et al., 2016), and older adults are expected to outlive their driving lifespan by several years (Foley et al., 2002). Hence, there is an urgent need to address mobility for this increasingly active and mobile population (Dickerson et al., 2019).

Older adult driving cessation is associated with several negative outcomes, including increases in mortality (Edwards, Perkins, et al., 2009), depression (Fonda, Wallace, & Herzog, 2001), health decline (Edwards, Lunsman, et al., 2009), and cognitive decline (Choi, Lohman, & Mezuk, 2014). Factors associated with driving reduction and cessation include physical and mental health (Anstey et al., 2006; Freund & Szinovacz, 2002), alternative transportation availability (Zhu, Cummings, Chu, & Xiang, 2008; Oxley & Whelan, 2008), and concern of others (e.g., family members, friends, and health care providers) about safe driving ability (Betz et al., 2013; Choi & Mezuk, 2013). Gender is also a factor that may influence older adults’ driving cessation. Females are more likely to stop driving than males (Choi et al., 2013; Freedman, Martin, & Schoeni, 2002). Males with more education are more likely to stop driving than males with less education, but the situation is reversed for females (Choi et al., 2013). Married (vs non-married) older males have a lower likelihood of driving cessation, but marital status is not significant for females (Choi et al., 2013).

Older adult transportation safety is a public health concern. Due to age-related physical and cognitive decline and increased frailty and fragility, older drivers are more likely to be involved in crashes and to be severely injured than their younger counterparts (Anstey et al., 2005; Braver & Trempel, 2004; Lyman et al., 2002; Shen & Neyens, 2015). To mitigate the high crash risk associated with older drivers, many U.S. states have enacted licensing laws specifically pertaining to older adults. A competing public health need arises in promoting older adults’ mobility while balancing their risk of traffic injuries.

Numerous studies have evaluated the effects of driver licensure provisions on older drivers’ traffic deaths and/or injuries (Decina & Staplin, 1993; Grabowski, Campbell, & Morrisey, 2004; Lange & McKnight, 1996; Levy, Vernick, & Howard, 1995; Tefft, 2014). To the best of our knowledge, however, the evidence for the relationship between licensure provisions and older adults’ mobility is still lacking. Levy (1995) identified that vision and on-road tests were associated with reduced licensure rate for U.S. adults 70 years or older. However, a survey-based study conducted in Florida did not show that vision test was a deterrent for adults aged 80 years or older seeking license renewal (McGwin et al., 2008). Additionally, using the 1993–2000 U.S. Asset and Health Dynamics of the Oldest Old study database, Kulikov (2011) found that the presence of an accelerated license renewal period and the requirement of renewing license in-person were associated with reduced driving by older adults. However, Kulikov coded law provisions as binary variables that lacked nuance. For example, the presence of an accelerated renewal period for older adults did not necessarily indicate a shorter renewal period. In 2008, the accelerated renewal period in Florida was 6 years, whereas the standard renewal period in California was 5 years. Furthermore, no study in the United States has investigated the effects of mandatory physician reporting laws on older adults’ daily driving behaviors. Thus, the objective of this study was to comprehensively evaluate the associations between driver licensure provisions and older adults’ daily driving time and trips. We stratified our analysis by gender to account for gender-based differences in driving behaviors.

Materials and Methods

Dataset

The 2003–2017 American Time Use Survey (ATUS) was used for this study. ATUS was conducted by the U.S. Census Bureau and can be accessed on the website of the Bureau of Labor Statistics at the U.S. Department of Labor (U.S. Census Bureau, 2017). A detailed description of the ATUS methodology can be found elsewhere (U.S. Census Bureau, 2017) but is briefly described here. ATUS was developed to provide nationally-representative estimates of how U.S. residents 15 years or older spend their time on daily activities (U.S. Census Bureau, 2017). ATUS covers all residents living in U.S. households except active military personnel and people residing in institutions (e.g., nursing homes or prisons) (U.S. Census Bureau, 2017). Each respondent of ATUS was asked to report daily activities staring at 4:00 am on the previous day and ending at 4:00 a.m. on the interview day. With assigned weights, respondents’ data can be normalized to U.S. national scale. Each respondent was also given 160 replicate weights, which could be used to compute the standard errors for national estimates.

For each activity reported by respondents, the duration of the activity, whether the activity was travel-related, and where the activity took place were recorded. Thus, for our study, if an activity was travel-related and took place in a privately owned vehicle (POV) where the respondent was a driver, the activity was counted as a driving-related activity. Respondents who had at least one driving-related activity were coded as driving vehicles on their diary date; otherwise, they were coded as not driving vehicles on that day. The duration of driving-related activities for each respondent was summed to obtain the respondent’s total driving duration on the diary date. Driving duration has been suggested as a reasonable driving exposure measure for U.S. drivers (Shen et al., 2020). Respondents coded as not driving vehicles on their dairy date had zero driving duration.

The summarized ATUS dataset was merged with a dataset of state driver license laws to link individual respondents to their state driver licensure provisions effective on the diary date. State driver license laws were retrieved from the database used by Tefft (Tefft, 2014) and online legislation databases (Heinonline, 2017; LexisNexis Academic, 2017). Details of the driver license renewal laws by state are presented in Supplementary Appendix A. Overall, the provisions of state driver license laws included length of renewal period; length of in-person renewal period; vision, knowledge, and on-road tests; and mandatory (vs voluntary) physician reporting laws. Two researchers coded state driver license laws separately and verified each other’s work with input from a third researcher if there was a discrepancy.

Statistical Analysis

Our study population consisted of adults aged 55 years or older in the 50 states and DC. Adults 65 years or older were divided into two subgroups: 65–74 years and 75 years or older. Adults 55–64 years were included in the analysis to control for the effects of non-licensure factors that also might influence the daily driving behaviors, such as changes in socioeconomic factors including gasoline price and unemployment rate. The age group 55–64 years was chosen because this group was close to those 65 years or older, but their mobility might not be affected by driver license laws. We did not classify adults 85 years or older as a separate group because ATUS top-coded adults aged 80 years or older as “80” in 2003 and 2004. In addition, the sample size of adults 85 years or older was small (3,109 respondents aged 85 years or older vs 20,599 adults aged 65–74 years in the 2005–2017 ATUS).

To estimate daily driving likelihood for older males and females, two individual weighted Poisson regression models for complex survey design were used with driving vehicles on the dairy date as the outcome (0 = not driving vehicles, and 1 = driving vehicles) and the provisions of driver license laws as the explanatory variables. The Poisson regression model with robust errors was suggested as an alternative to the log-binomial regression model to estimate the risk ratios (RRs) of the explanatory variables due to convergence issues related to the log-binomial regression model (Spiegelman & Hertzmark, 2005).

The renewal period (ranging from 1 to 12 years) and in-person renewal period (ranging from 1 to 24 years) entered the models as continuous variables. For states which did not require in-person renewals, we coded the in-person renewal period as 25 years. Sensitivity analyses about the coding of no in-person renewal were conducted (coded as 25 vs 30 and 35 years, and complete removal of the records for states that did not require in-person renewal; Supplementary Appendix B). The correlation between the renewal period and in-person renewal period was 0.21, which was not likely to introduce multicollinearity issue into our models. The vision test at in-person renewal, vision test without in-person renewal, knowledge test, mandatory physician reporting, and on-road test entered the models as binary variables (0 = absence, 1 = presence).

The interactions of age-specific variables (65–74 years and 75 years or older) and licensure provisions were also included in the model. The effects of non-licensure factors were measured by the corresponding RR for the control group (aged 55–64 years). To adjust for the non-licensure factors’ effects on driving vehicles on individuals’ dairy date, the RRs for law provisions of 65–74 years and 75 years or older were divided by the ones of 55–64 years to calculate the relative risk ratio (rRR), as well as the confidence intervals (CIs) (i.e., the rRRs were equal to the exponential of the interactions of licensure provisions with indicators for older adults). The model also included three dummy variables for quarters to control for the seasonal effects and 14 dummy variables for years to account for the nationwide yearly variation in adults’ driving exposure.

The Poisson models we used were comprehensive in which the estimate of a specific licensure provision was adjusted by the effects of other licensure provisions and time factors (i.e., quarter and year). We tested the multiplicative interactions between the licensure provisions (the two-way interaction variables between law provisions, such as vision test at in-person renewal × mandatory reporting laws). These multiplicative interactions either did not exist (e.g., no state required older adults to have both vision test at in-person renewal and knowledge test) or were not statistically significant at 0.05. Thus, the multiplicative interactions were not included in the final models.

Additionally, although having a job often increased adults’ driving exposure (Kulikov, 2011), employment status was not included in our analysis. We did not identify significant relationships between employment status and licensure provisions, suggesting that it was not necessary to control employment status in our model. Furthermore, it is also possible that driver license laws influence older adults’ employment status, which subsequentially affects driving exposure. In this case, employment status may be an intermediate factor between license laws and daily driving exposure for older adults. Including employment status may result in underestimation of the effects of driver license laws.

To estimate daily driving duration, weighted linear regression models for complex survey design were used with the log of driving duration as the outcome. As some observations of driving duration were equal to zero, all observations of driving duration were inflated by 0.01 min when entering the model. The explanatory variables in this model were the same as those in the weighted Poisson regression model used to predict daily driving likelihoods. To adjust for the non-licensure factors’ effects on driving duration on individuals’ dairy date, the ratios for law provisions of 65–74 years and 75 years or older were divided by the ones of 55–64 years to calculate the relative ratio, as well as the CIs (i.e., the relative ratios were equal to the exponential of the interactions of licensure provisions with indicators for older adults).

Additionally, as no state required adults in the control group to take an on-road test for the driver license renewal, the rRRs and relative ratios for on-road test could not be computed. Individual weighted Poisson and linear regression models without the control group were built to calculate the RRs and ratios of on-road test for adults aged 75 years or older. The svy glm and svy regress functions for complex surveys in Stata/IC 14.0 were used to build the weighted Poisson and linear regression models, respectively. The successive difference replication (SDR) method was used to obtain the variance of each estimate in both models. The statistical significance level for this analysis was set to 0.05.

Results

The dataset for this analysis included 29,273 respondents aged 55–64 years, 20,599 aged 65–74 years, and 16,173 aged 75 years or older. Normalized to the U.S. national scale, daily driving occurred for 69.9% of adults aged 55–64 years and 60.3% of adults aged 65–74 years, whereas only 46.0% of adults aged 75 years or older. The average daily driving duration for those three age groups were 51.6 (55–64 years), 40.9 (65–74 years), and 27.3 (75 years or older) min, respectively.

License Renewal Period

The renewal period decreased with increasing age (Table 1). The national average license renewal period was 5.7 years for ages 55–64 years, 5.2 years for ages 65–74 years, and 4.9 for ages 75 years or older. For males aged 55–64 years, a one-year reduction in the renewal period was not associated with daily driving likelihood (Table 2, RR: 1.00, 95% CI: 1.00–1.01) and daily driving duration (Table 3, rate: 1.03, 95% CI: 0.98–1.08). For males 65–74 years, after controlling for other license renewal provisions and non-licensure factors, a 1-year reduction in the renewal period was not associated with daily driving likelihood (Table 2, rRR: 1.01, 95% CI: 1.00–1.03) or daily driving duration (Table 3; relative ratio:1.08, 95% CI: 0.98–1.18). Overall, a 1-year reduction in the renewal period was not statistically significant for any of our gender-stratified analyses for daily driving likelihood (Tables 2 and 4) or driving duration (Tables 3 and 5).

Table 1.

Status of Driver Licensure Provisions by Age Group, the United States, 2003–2017

Provisions of driver license renewal laws 55–64 years 65–74 years 75 years or older
Mean 95% CIa Mean 95% CI Mean 95% CI
Renewal period (years) 5.66 5.63–5.69 5.24 5.21–5.27 4.88 4.85–4.91
In-person renewal periodb 10.86 10.77–10.95 9.87 9.76–9.98 8.05 7.92–8.17
Prop. (%) 95% CI Prop. (%) 95% CI Prop. (%) 95% CI
Vision test at the in-person renewal 78.54 77.92–79.15 81.28 80.60–81.96 81.79 80.97–82.61
Vision test without in-person renewal 7.51 7.12–7.91 8.06 7.53–8.59 8.58 7.86–9.29
Knowledge test 4.39 4.06–4.72 8.03 7.56–8.51 14.04 13.67–15.13
Mandatory reporting laws for physicians 19.23 18.60–19.87 18.85 18.15–19.56 20.60 19.69–21.50
On-road test — b — — b — 4.86 4.43–5.28
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Notes:  aCI refers to confidence interval.

bNo state requires adults 55–64 and 65–74 years to pass an on-road driving test at routine in-person license renewal during the study time.

Table 2.

Risk Ratios and Relative Risk Ratios of Daily Driving Likelihood by Age Group, Males

55–64 years 65–74 years 75 years or older
Risk ratioa Renewal period (1-year reduction) 1.00 (1.00, 1.01) 1.02 (0.99, 1.04) 1.00 (0.97, 1.04)
In-person renewal period (1-year reduction) 1.00 (1.00, 1.00) 1.00 (0.99, 1.01) 1.00 (0.99, 1.01)
Vision test at in-person renewal 1.01 (0.97, 1.04) 0.99 (0.90, 1.09) 0.98 (0.86, 1.11)
Vision test without in-person renewal 1.07 (1.03, 1.11) 0.99 (0.89, 1.11) 1.09 (0.94, 1.26)
Knowledge test 1.02 (0.96, 1.08) 0.95 (0.80, 1.11) 1.01 (0.84, 1.22)
Mandatory reporting laws 1.01 (0.97, 1.04) 0.90 (0.82, 1.00) 1.00 (0.87, 1.15)
On-road test — — 1.01 (0.93, 1.11)
Relative risk ratiob Renewal period (1-year reduction) — 1.01 (1.00, 1.03) 0.99 (0.97, 1.02)
In-person renewal period (1-year reduction) — 1.00 (1.00, 1.00) 1.00 (0.99, 1.01)
Vision test at in-person renewal — 0.98 (0.93, 1.05) 0.97 (0.88, 1.07)
Vision test without in-person renewal — 0.93 (0.84, 1.00) 1.02 (0.91, 1.14)
Knowledge test — 0.93 (0.84, 1.03) 0.99 (0.88, 1.13)
Mandatory reporting laws — 0.90 (0.84, 0.95) 0.99 (0.89, 1.10)
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Notes: Bold indicates statistical significance.

aThe risk ratios were to compare adult daily driving likelihood for each provision of driver license renew laws.

bRelative risk ratios were to compare daily driving likelihood for each provision of driver license renew laws adjusted for effects of non-driver-licensing-laws factors.

Table 3.

Ratios and Relative Ratios of Daily Driving Duration by Age Group, Males

55–64 years 65–74 years 75 years or older
Ratiosa Renewal period (1-year reduction) 1.03 (0.98, 1.08) 1.11 (0.96, 1.28) 0.97 (0.82, 1.28)
In-person renewal period (1-year reduction) 0.99 (0.98, 1.01) 0.99 (0.95, 1.03) 1.01 (0.95, 1.06)
Vision test at in-person renewal 1.03 (0.83, 1.27) 0.98 (0.53, 1.79) 0.84 (0.42, 1.70)
Vision test without in-person renewal 1.48 (1.12, 1.96) 1.02 (0.49, 2.12) 1.51 (0.62, 3.67)
Knowledge test 1.22 (0.80, 1.85) 0.75 (0.26, 2.17) 1.16 (0.39, 3.44)
Mandatory reporting laws 1.05 (0.83, 1.33) 0.56 (0.31, 1.03) 0.94 (0.43, 2.05)
On-road test — — 1.10 (0.70, 1.70)
Relative ratiosb Renewal period (1-year reduction) — 1.08 (0.98, 1.18) 0.94 (0.83, 1.07)
In-person renewal period (1-year reduction) — 1.00 (0.98, 1.03) 1.01 (0.98, 1.05)
Vision test at in-person renewal — 0.95 (0.64, 1.41) 0.82 (0.50, 1.33)
Vision test without in-person renewal — 0.69 (0.44, 1.08) 1.02 (0.55, 1.87)
Knowledge test — 0.61 (0.32, 1.17) 0.95 (0.49, 1.86)
Mandatory reporting laws — 0.53 (0.37, 0.77) 0.89 (0.52, 1.54)
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Notes: Bold indicates statistical significance.

aThe ratios were to compare adult daily driving duration for each provision of driver license renew laws.

bRelative ratios were to compare adults daily driving duration for each provision of driver license renew laws adjusted for effects of non-driver-license-laws factors.

Table 4.

Risk Ratios and Relative Risk Ratios of Daily Driving Likelihood by Age Group, Females

55–64 years 65–74 years 75 years or older
Risk ratioa Renewal period (1-year reduction) 1.01 (1.00, 1.02) 1.02 (0.99, 1.05) 1.03 (1.00, 1.05)
In-person renewal period (1-year reduction) 1.00 (1.00, 1.01) 1.00 (0.99, 1.01) 1.00 (0.99, 1.01)
Vision test at in-person renewal 1.02 (0.98, 1.07) 1.01 (0.90, 1.14) 1.11 (0.94, 1.32)
Vision test without in-person renewal 1.02 (0.96, 1.09) 1.07 (0.89, 1.28) 1.28 (1.02, 1.60)
Knowledge test 1.00 (0.94, 1.07) 0.97 (0.82, 1.15) 0.96 (0.79, 1.17)
Mandatory reporting laws 1.02 (0.98, 1.07) 1.05 (0.92, 1.19) 0.90 (0.77, 1.04)
On-road test — — 0.93 (0.84, 1.02)
Relative risk ratiob Renewal period (1-year reduction) — 1.01 (0.99, 1.03) 1.02 (1.00, 1.05)
In-person renewal period (1-year reduction) — 1.00 (0.99, 1.00) 0.99 (0.99, 1.00)
Vision test at in-person renewal — 0.99 (0.91, 1.07) 1.08 (0.95, 1.23)
Vision test without in-person renewal — 1.04 (0.93, 1.15) 1.12 (0.97, 1.30)
Knowledge test — 0.97 (0.87, 1.07) 0.96 (0.85, 1.09)
Mandatory reporting laws — 1.02 (0.94, 1.10) 0.88 (0.79, 0.97)
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Notes: Bold indicates statistical significance.

aThe risk ratios were to compare adult daily driving likelihood for each provision of driver license renew laws.

bRelative risk ratios were to compare daily driving likelihood for each provision of driver license renew laws adjusted for effects of non-driver-licensing-laws factors.

Table 5.

Ratios and Relative Ratios of Daily Driving Duration by Age Group, Females

55–64 years 65–74 years 75 years or older
Ratiosa Renewal period (1-year reduction) 1.03 (0.98, 1.08) 1.07 (0.93, 1.24) 1.09 (0.95, 1.24)
In-person renewal period (1-year reduction) 1.02 (1.00, 1.04) 1.00 (0.96, 1.05) 0.99 (0.84, 1.40)
Vision test at in-person renewal 1.12 (0.89, 1.40) 1.09 (0.60, 1.99) 1.39 (0.72, 2.70)
Vision test without in-person renewal 1.13 (0.80, 1.59) 1.22 (0.52, 2.90) 1.70 (0.67, 4.34)
Knowledge test 1.07 (0.74, 1.56) 0.85 (0.35, 2.07) 0.92 (0.39, 2.18)
Mandatory reporting laws 1.18 (0.91, 1.53) 1.22 (0.64, 2.33) 0.72 (0.38, 1.35)
On-road test — — 0.77 (0.57, 1.05)
Relative ratiosb Renewal period (1-year reduction) — 1.04 (0.95, 1.15) 1.06 (0.97, 1.16)
In-person renewal period (1-year reduction) — 0.98 (0.96, 1.01) 0.97 (0.95, 1.00)
Vision test at in-person renewal — 0.97 (0.67, 1.42) 1.23 (0.80, 1.91)
Vision test without in-person renewal — 1.08 (0.64, 1.82) 1.50 (0.83, 2.72)
Knowledge test — 0.79 (0.48, 1.33) 0.85 (0.52, 1.40)
Mandatory reporting laws — 1.04 (0.71, 1.52) 0.61 (0.42, 0.88)
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Notes: Bold indicates statistical significance.

aThe ratios were to compare adult daily driving duration for each provision of driver license renew laws.

bRelative ratios were to compare adults daily driving duration for each provision of driver license renew laws adjusted for effects of non-driver-license-laws factors.

In-Person Renewal Period

Most states required drivers to renew their license in-person every renewal or every other renewal. In general, older drivers were required to renew license in-person more frequently than younger drivers. The average in-person renewal periods were 10.86, 9.87, and 8.05 years for ages 55–64, 65–74, and 75 years or older, respectively. For males of any age group, a 1-year reduction of the in-person renewal period was not associated with daily driving likelihood (Table 2) or driving duration (Table 3). However, a 1-year reduction of in-person renewal period was associated with a 3% reduction in daily driving duration for females 75 years older (Table 5, relative ratio: 0.97, 95% CI: 0.95–1.00). The sensitivity analysis (Supplementary Appendix B) shows that the estimates of in-person renewal are quite robust to how we coded the infinite in-person renewal period, as the point estimates in Supplementary Appendix B are similar to their counterparts in Tables 2–5.

Vision Test

Most states required drivers to take a vision test at their in-person renewal regardless of their age, although only three states (Colorado, Florida, and Nevada) required drivers to pass a vision test when the license renewal was not conducted in-person during the study period. The proportions of adults who were subject to vision test at the in-person renewal and without the in-person renewal are presented in Table 1. Overall, a vision test at in-person renewal or without in-person renewal was not associated with changes in daily driving likelihood and duration for male or female older adults (Tables 2–5).

Knowledge Test

During the study period, only five states required (California and Illinois) or had required (Indiana, Kansas, and Michigan) any drivers or drivers above a certain age to pass a knowledge test at in-person renewal. California required drivers 70 years or older to take a knowledge test, and Illinois required all drivers to pass a knowledge test. Three states repealed laws requiring a knowledge test at routine in-person renewal: Indiana (2004), Kansas (2010), and Michigan (2003). Knowledge test was not statistically significant for any tested associations with daily driving likelihood or duration.

Mandatory Reporting Laws

During the study period, 6 states (California, Delaware, New Jersey, Nevada, Oregon, and Pennsylvania) and DC required physicians to report patients to licensing authority under specified conditions. It should be noted that the mandatory reporting conditions varied by state. The results showed that for females aged 75 years or older (Tables 4 and 5), the reporting laws were associated with 12% lower daily driving likelihood (rRR: 0.88, 95% CI: 0.79–0.97) and 39% shorter daily driving duration (relative ratio: 0.61, 95% CI: 0.42–0.88). For males aged 65–74 years, mandatory reporting laws were significantly associated with a lower daily driving likelihood (rRR: 0.90, 95% CI: 0.84–0.95) and shorter duration (relative ratio: 0.53, 95% CI: 0.37–0.77) (Tables 2 and 3).

On-Road Test

On-road test was only given to drivers aged above 75 years by three states (Illinois, Indiana, and New Hampshire), but Indiana and New Hampshire repealed on-road test laws in 2005 and 2011, respectively. Given that no states require drivers in the control group (55–64 years) to pass an on-road test at in-person renewal, the rRRs and relative ratios could not be computed. Thus, the estimates of this variable may be confounded by unobserved time-variant variables. Overall, the on-road test was not associated with older adults’ daily driving likelihood or duration.

Discussion

Preventing older driver traffic crashes while preserving older adult mobility is a global concern, especially in developed countries. Many U.S. states have enacted driver license renewal policies specific to older adults with the goal of preventing unsafe older drivers. Most previous studies focused on the impacts of those polices on older drivers’ traffic injury/death rates (Decina & Staplin, 1993; Grabowski et al., 2004; Lange & McKnight, 1996; Tefft, 2014), but few investigated the influence of these policies on older adults’ mobility (Levy, 1995; Kulikov, 2011; McGwin et al., 2008). The findings of previous studies are inconsistent (Levy, 1995; McGwin et al., 2008), and some studies examined a limited number of licensure provisions (Kulikov, 2011; McGwin et al., 2008). Furthermore, these studies did not consider whether the effects of licensure provisions differed by gender. Our study expands the current literature on the impacts of older driver license laws on older adults’ daily mobility by examining a comprehensive list of driver licensure renewal provisions and the gender disparities.

We found that for females aged 75 years or older, a 1-year reduction of in-person renewal period was associated with a 3% reduction in daily driving duration. If a state with a 4-year renewal period changed the in-person renewal frequency from every other renewal period to every renewal period, the daily driving duration for females 75 years or older would decrease by 11% (1-0.974 = 0.115). However, the change of in-person renewal period was not significantly associated with older males’ driving likelihood and duration. Policy designers should be aware that shortening the in-person renewal period may result in reduced daily driving exposure for females 75 years or older. Therefore, if the in-person renewal period is reduced, specific strategies to preserve females’ mobility should be considered, such as providing training programs (e.g., cognitive and physical interventions) to prolong driving mobility and improving the accessibility of alternative transportation. Previous studies have suggested that states with more frequent in-person renewal observed reduced fatal crash involvement among adults 85 years or older (Grabowski et al., 2004; Tefft, 2014). Together with our findings, older adults’ reduced fatal crash involvement may be partially due to their reduced driving exposure. Future studies should determine to what extent the safety benefits of driver license renewal laws were at the cost of older adults’ mobility and whether shortening the in-person renewal period removes unsafe older drivers or fosters premature driving cessation.

Mandatory reporting laws were associated with lower driving likelihoods and shorter duration for males aged 65–74 years and females aged 75 years or older. However, the effects of the presence of the mandatory reporting laws for physicians should be treated with caution because no state enacted or repealed such laws over the study period (2003–2017). The comparisons of the daily driving likelihood and driving duration for older adults were cross-sectional and may be confounded with state-specific effects. In addition, the mandatory reporting laws were not statistically significantly associated with reduced fatal crash rates for older adults (Tefft, 2014). Thus, policy designers should be careful in designing and implementing mandatory physician reporting laws.

Tefft (2014) argued that requiring older drivers to undergo any test as a component of in-person renewal may make minimal contributions toward excluding potentially unsafe drivers. Rather, he argued that license office staff may be able to identify unsafe older drivers during their interactions before mandating all drivers above a certain age to conduct a vision or knowledge test. This argument may explain the non-significant relationships of the vision test at in-person renewal and knowledge test with older adults’ daily driving exposure. Additionally, our study did not find sufficient evidence about the effects of the vision test without in-person renewal on older adults’ daily driving exposure. However, the non-significant results for vision test without in-person renewal might be due to the limited sample size.

Furthermore, our study provides additional evidence about the gender difference in driving cessation. Previous studies have identified that females are more likely to voluntarily stop driving than males as they age (Adler & Rottunda, 2006; Choi et al., 2013; Freedman et al., 2002). Females may plan earlier than males to reduce their driving exposures and transition to other modes of transportation (Bauer et al., 2003). Additionally, factors influencing driving behaviors differ by gender (Choi et al., 2013). Marriage, education, and health conditions differentially affect older male and female driving cessation (Choi et al., 2013). Our results suggest that older females (versus males) may be more impacted by stricter licensing laws. For example, a shorter in-person renewal period is associated with reduced driving duration for females 75 years or older, whereas older males’ daily driving duration is not influenced by the length of in-person renewal period. Given that females have a longer life-expectancy and better general health than males (Barford et al., 2006; Raleigh & Kiri, 1997), females may be more likely to be subject to the physician mandatory reporting laws at later age than males. Therefore, policymakers should be aware of the gender difference in responding to different provisions of licensure law. Interventions specifically targeting older males or females may be needed when new licensure laws are implemented to prolong older adults’ driving mobility or ease them into the transition from driving to non-driving mobility.

Our study also identifies areas for future research to account for gender difference when evaluating the mobility effects or safety benefits of licensure laws. Although gender differences in driving behavior are well-established in the literature, the underlying reasons for gender disparities in driving cessation are also worthy of investigation. Such research results are expected to better assist policymakers in designing effective licensure laws from mobility and safety perspectives. Furthermore, our study did not consider the interaction effects of licensure laws and other geographical factors (e.g., urbanicity, weather). The effects of licensure laws may also vary by and within states with different levels of urbanicity and built environment. Older adults living in urban area have better access to alternative traveling modes and as a result, may voluntarily stop driving before failing to renew their license than adults living in suburban or rural area. Future studies should further account for the geographical difference when investigating licensure law effects.

There are several limitations associated with this study. First, the date when each respondent renewed his/her license was not available. Thus, it was impossible to directly determine the licensure renewal provisions effective on the respondents’ driver license. The respondents’ renewal period might be subject to the previous renewal policies instead of the current renewal policies. The inability to determine the specific laws in effect at the time of renewal prior to the diary data may bias the estimates of the individual law provision’s effects on older adults’ daily driving likelihood and duration, but the directions of those effects should be valid. Second, our analyses did not include measures of state enforcement of specific policies. Evaluating the impacts of enforcement manners in strength, rigor, and difficulty for various policies was beyond the scope of this study. Future studies should further test if the difference in policy enforcement manner influences older adults’ daily driving exposure. Additionally, as no state required adults in the control group to take an on-road test to renew licensure, the estimate of the presence of on-road test might be confounded with other influential factors (e.g., economics factors). Furthermore, we used adults aged 55–64 years to control for the effects of unobserved non-licensure factors on driving exposure because the characteristics those adults were closest to older adults we examined here, but their driving exposure was not likely to be affected by driver license renewal laws. However, bias could still exist if the effects of unmeasured factors varied across age groups. Finally, we did not analyze the specific effects of driver license renewal laws on adults aged 85 years or older due to the coding limitation in ATUS and the small sample size for this age group.

Conclusion

The reduction of in-person renewal period was associated with a reduction in daily driving duration for females aged 75 years or older. Mandatory reporting laws were associated with reduced daily driving likelihood and duration for males aged 65–74 years and females aged 75 years or older. Our study shows that older males and females respond differently to driver license renewal laws. Future studies should consider the gender disparities when examining the association between driver licensure policies and older adults’ transportation safety and mobility.

Our study also sheds light on the impacts of various provisions of driver license renewal laws on older adults’ driving behaviors and provides valuable information for policymakers. Policymakers should be aware of gender disparities when designing older driver license laws and implement strategies to assist the more responsive groups to preserve their mobility. Previous research found lower frequency of in-person renewal was associated with reduced fatal crash rate for oldest adults (aged 85 years or older) (Tefft, 2014), and our study suggests that shorter length of in-person renewal period is associated reduced older females’ daily driving duration. Thus, the in-person renewal period should be carefully designed in order to remove unsafe older female drivers but not prematurely exclude safe ones. On the other hand, a shorter in-person renewal period was not associated with reduced driving exposure for older males. Shorter length of in-person renewal period may protect older males from traffic injuries but preserve their mobility. Thus, understanding gender and age differences in response to licensure provisions could help policymakers optimize policies from the perspectives of both protecting older adults from injurious crashes and preserving their mobility.

Funding

The work was supported by the U.S. National Institute on Aging (R01AG050581) and the U.S. National Institute of Child Health and Human Development (R01HD074594 and R21HD085122).

Supplementary Material

gbaa070_suppl_Supplementary_Appendix
Click here for additional data file. (28.7KB, docx)

Acknowledgments

We would like to thank Mr. Brian Tefft of the AAA Foundation for Traffic Safety for his critical review and helpful comments in our data analysis and manuscript preparation.

Author Contributions

S. Shen led the writing and conducted the data analysis. K. L. Ratnapradipa participated in the writing and the data analysis. G. C. Pervall and M. Sweeney critically reviewed and substantially revised the manuscript. M. Zhu mentored for the study design, data analysis, and manuscript writing. M. Zhu had full access to all of the data (including statistical reports and tables) in the study and can take full responsibility for the overall content.

Conflict of Interest

The opinions, views, or comments expressed in this paper are those of the authors and do not necessarily represent the official positions of funding agencies. Further, the funding bodies had no input on any aspect of this study. All authors declare no conflicts of interest.

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Supplementary Materials

gbaa070_suppl_Supplementary_Appendix
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