Abstract
Objectives.secondary enforcement laws (police may issue a safety belt citation only if the vehicle has been stopped for another reason).
Methods. We analyzed 2002 Behavioral Risk Factor Surveillance System data from 50 states and the District of Columbia. We performed multivariable, log-linear regression analyses to assess the effect of sociodemographic characteristics and safety belt laws on safety belt use. Analyses were stratified by the type of enforcement permitted by state laws.
Results. Reported safety belt use was higher in states that had primary versus secondary enforcement laws, both overall and for each sociodemographic characteristic examined. Safety belt use was 85% in states that had primary enforcement laws and 74% in states that had secondary enforcement laws. Cross-sectional data suggested that primary enforcement laws may have the greatest effect on sociodemographic groups that reported lower levels of safety belt use.
Conclusions. Primary enforcement laws are an effective population-based strategy for reducing disparities in safety belt use and may, therefore, reduce disparities in crash-related injuries and fatalities.
Motor vehicle crashes kill more than 40000 people in the United States each year and are the leading cause of death among Americans aged 1–34 years.1 Safety belts are the single most effective way to reduce crash-related deaths; estimates of effectiveness range from 45% to 60%.2
Although rates of safety belt use in the United States have increased substantially since the first state law was passed in 1984, many motor vehicle occupants continue to travel unrestrained. Published reports have shown that people who are male, young, less educated, have a lower income, and reside in rural areas are less likely than their counterparts to wear safety belts.3–6 There is less consistency in reported safety belt use by race/ethnicity.3–5,7–8
In the United States, safety belt laws can be classified according to the type of enforcement authorized in the state. Primary laws allow police to stop and ticket a motorist solely for being unbelted. Secondary laws allow police to issue a safety belt citation only if the vehicle has been stopped for another reason (e.g., speeding). Numerous evaluations have shown that primary laws are more effective than secondary laws at increasing safety belt use and reducing traffic fatalities and serious injuries.9–15
A 2004 study used data from the 2002 Behavioral Risk Factor Surveillance System (BRFSS), a survey administered by the Centers for Disease Control and Prevention, to examine the influence of primary enforcement laws at the state level.16 We extended that analysis by examining the effect of primary enforcement laws by sociodemographic characteristics (i.e., gender, race/ethnicity, age, education, household income, marital status, population density, body mass index [BMI], and driving after drinking). We found very few studies that addressed the effect of type of safety belt law on sociodemographic characteristics, and those that did were limited in scope.17–19 Our study is unique in that the large, nationally representative data set contained information about a variety of demographic, behavioral, and environmental characteristics that are independently associated with safety belt use. We used multivariable analysis to simultaneously explore the effect of safety belt laws and sociodemographic characteristics on the use of safety belts.
METHODS
The BRFSS is a state-based, random digit–dialed telephone survey administered by the Centers for Disease Control and Prevention. All 50 states, the District of Columbia (DC), and 3 US territories participated. The sample is representative of noninstitutionalized, civilian adults aged 18 years and older. A detailed description of the BRFSS is available elsewhere.20
We analyzed 2002 data from the 50 states and DC (US territories were not included). The overall sample size for this study was 238141 persons. The median response rate for all states and DC was 58.6% (range: 42.2% to 82.6%). Respondents were asked how often they use seat belts when driving or riding in a car (always, nearly always, sometimes, seldom, or never). Safety belt use was dichotomized for analysis (always vs less than always). Respondents who never rode in cars, refused to respond, or responded “don’t know” were excluded from all analyses (n = 777).
Sociodemographic variables examined in this analysis included gender, race/ethnicity, age, education, annual household income, marital status, population density, BMI (weight in kilograms divided by height in meters squared), and driving after drinking. Race and ethnicity were grouped together into 6 categories: Whites, Blacks, Asian or Pacific Islanders, American Indians or Alaska Natives, Hispanics, and other or multiraces. Marital status was defined as married (included unmarried couples) or unmarried. Population density was defined as urban or suburban versus rural place of residence (based on whether or not the respondent lived in a metropolitan or micropolitan statistical area). BMI was grouped into 3 categories: underweight or normal (< 25.0 kg/m2), overweight (25.0–29.9 kg/m2), and obese (≥ 30.0 kg/m2). Respondents also were asked how often, in the last 30 days, they had driven after having “perhaps too much” to drink. Responses were grouped into 2 categories: 1 or more times versus none (included respondents who do not drink).
In 2002, 18 states and DC had primary enforcement laws in effect (hereafter referred to as primary law states). Washington State was considered to be a primary law state for the entire year, although the primary law was enacted there in July 2002. New Hampshire had no adult safety belt law and was treated as a secondary law state for our analysis; the remaining states had secondary enforcement laws in effect during the entire year (hereafter referred to as secondary law states). Analyses also were run with New Hampshire data excluded, Washington State data excluded, and Washington State data classified by whether interviews were completed before or after the primary law was enacted. None of these alternate classifications changed the results.
SUDAAN21 was used for analyses to account for the complex sampling design. We calculated prevalence and 95% confidence intervals (CIs) of safety belt use by sociodemographic characteristics. We also calculated the prevalence difference in safety belt use between primary law and secondary law states by sociodemographic characteristics. CIs were used as a conservative test of significance; differences were considered significant if the 95% CIs did not overlap.
We constructed multivariable log-linear regression models to assess the effect of selected sociodemographic characteristics on safety belt use. Variables were selected on the basis of a review of the relevant literature. Law type was determined to be an effect modifier for each of the exposure variables examined. Because safety belt use differed by law type, we constructed separate regression models for persons in primary law and secondary law states to independently explore the effect of sociodemographic characteristics on safety belt use. The use of log-linear regression methods facilitated the direct estimation of prevalence ratios; we used the Wald χ2 statistic for statistical tests.
RESULTS
The populations of both primary law and secondary law states were very similar with respect to the sociodemographic factors under investigation (data not shown). However, residents of primary law states were less likely than were residents in secondary states to be White (64% vs 80%) and more likely to be Hispanic (17% vs 7%). Residents of primary law states also were less likely than those in secondary law states to live in rural areas (18% vs 26%).
In 2002, 80.4% (95% CI = 80.1, 80.7) of the study population always wore safety belts; 2.8% (95% CI = 2.7, 3.0) never wore safety belts. The population that always wore safety belts was 11 percentage points higher in primary law states (85.3%; 95% CI = 84.9, 85.7) than in secondary law states (74.4%; 95% CI = 74.1, 74.8; Table 1 ▶).
1.
Prevalence of Participants Reporting Safety Belt Use in States with Primary and Secondary Enforcement Laws and Overall: United States, Behavioral Risk Factor Surveillance System, 2002
| Reported Safety Belt Use | Primary Law States (n = 93 757),a % (95% CI) | Secondary Law States (n = 143 607), % (95% CI) | Total (n = 237 364), % (95% CI) |
| Always | 85.3 (84.9,85.7) | 74.4 (74.1, 74.8) | 80.4 (80.1, 80.7) |
| Nearly always | 8.3 ( 8.0, 8.6) | 11.8 (11.5, 12.1) | 9.9 (9.7, 10.1) |
| Sometimes | 3.2 (3.0, 3.4) | 6.4 (6.2, 6.6) | 4.7 (4.5, 4.8) |
| Seldom | 1.3 (1.2, 1.5) | 3.3 (3.1, 3.4) | 2.2 (2.1, 2.3) |
| Never | 1.8 (1.7, 2.0) | 4.1 (3.9, 4.3) | 2.8 (2.7, 3.0) |
Note. CI = confidence interval. Primary law states are those in which police may stop and ticket a motorist solely for being unbelted; secondary law states are those in which police may issue a safety belt citation only if the vehicle has been stopped for another reason. All 50 states and the District of Columbia were included in the analysis.
aWithin sample sizes, all percentages were calculated on the basis of weighted estimates.
Table 2 ▶ provides comparisons of safety belt use among sociodemographic groups on the basis of whether primary or secondary laws were in effect. For all sociodemographic groups examined, differences in safety belt use were observed on the basis of the type of enforcement present in the state of residence (Table 2 ▶). For example, men in primary law states were more likely to always wear safety belts than were men in secondary law states (80.8% vs 68.1%, respectively). Likewise, women in primary law states were more likely to always wear safety belts than were women in secondary law states (89.6% vs 80.3%, respectively). The largest prevalence differences were observed for American Indians/Alaska Natives, people with less than a high school education, people aged 18–24 years, obese people, and people who reported driving after drinking; the prevalence difference in safety belt use for each of these groups was at least 14 percentage points (Table 2 ▶).
2.
Prevalence of Reporting Always Wearing a Safety Belt, by Type of State Safety Belt Law and Selected Sociodemographic Factors: United States, Behavioral Risk Factor Surveillance System, 2002
| Characteristic | Primary Law States, % (95% CI) | Secondary Law States, % (95% CI) | Prevalence Differencea |
| Gender | |||
| Men | 80.8 (80.1, 81.5) | 68.1 (67.5, 68.7) | 12.7 |
| Women | 89.6 (89.1, 90.0) | 80.3 (79.9, 80.8) | 9.3 |
| Race/ethnicity | |||
| Whites | 84.2 (83.7, 84.7) | 74.5 (74.1, 74.8) | 9.7 |
| Blacks | 83.4 ( 82.1, 84.8) | 70.7 (69.2, 72.3) | 12.7 |
| Hispanics | 89.3 (88.2, 90.5) | 78.2 (76.3, 80.0) | 11.1 |
| Asian or Pacific Islanders | 91.4 (89.1, 93.2) | 85.8 (82.5, 88.6) | 5.6 |
| American Indians/Alaska Natives | 84.0 (80.5, 87.5) | 67.6 (63.7, 71.5) | 16.4 |
| Other race or multiracial | 84.3 (81.4, 86.8) | 71.2 (68.3, 74.0) | 13.1 |
| Education | |||
| Less than high school | 84.6 (83.3, 85.9) | 67.3 (65.9, 68.6) | 17.3 |
| High school graduate | 83.2 (82.5, 84.0) | 70.4 (69.7, 71.0) | 12.8 |
| Some college | 85.2 (84.4, 86.0) | 74.6 (73.9, 75.3) | 10.6 |
| College graduate | 87.7 ( 87.1, 88.4) | 81.6 (81.0, 82.2) | 6.1 |
| Age, y | |||
| 18–24 | 80.0 (78.4, 81.6) | 65.9 (64.4, 67.3) | 14.1 |
| 25–34 | 83.1 (82.1, 84.1) | 71.5 (70.6, 72.5) | 11.6 |
| 35–64 | 86.5 (86.0, 87.0) | 75.6 (75.1, 76.0) | 10.9 |
| ≥ 65 | 88.6 (87.8, 89.4) | 80.1 (79.4, 80.8) | 8.5 |
| Annual household income, $ | |||
| < 20 000 | 85.9 (84.7, 86.9) | 72.0 (71.0, 73.0) | 13.9 |
| 20 000–49 999 | 84.1 (83.4, 84.7) | 71.7 (71.1, 72.3) | 12.4 |
| ≥ 50 000 | 85.8 (85.1, 86.4) | 77.6 (77.0, 78.3) | 8.2 |
| Marital status | |||
| Marriedb | 86.8 (86.4, 87.3) | 76.4 (76.0, 76.9) | 10.4 |
| Unmarried | 82.9 (82.1, 83.6) | 71.2 (70.5, 71.8) | 11.7 |
| Population density | |||
| Urban or suburban | 86.3 (85.8, 86.8) | 76.6 (76.2, 77.1) | 9.7 |
| Rural | 80.7 (79.9, 81.5) | 68.2 (67.5, 68.8) | 12.5 |
| Body mass indexc | |||
| Underweight or normal | 86.8 (86.1, 87.5) | 77.6 (77.1, 78.2) | 9.2 |
| Overweight | 85.1 (84.4, 85.8) | 74.1 (73.5, 74.8) | 11.0 |
| Obese | 82.4 (81.5, 83.2) | 68.1 (67.2, 69.0) | 14.3 |
| Drinking after driving (last 30 days) | |||
| None | 85.7 (85.3, 86.1) | 74.9 (74.5, 75.3) | 10.8 |
| ≥ 1 times | 70.5 (66.4, 74.2) | 55.8 (52.9, 58.8) | 14.7 |
Note. CI = confidence interval. Primary law states are those in which police may stop and ticket a motorist solely for being unbelted; secondary law states are those in which police may issue a safety belt citation only if the vehicle has been stopped for another reason. All 50 states and the District of Columbia were included in the analysis.
aPrevalence difference is the difference between the prevalence in primary law states and the prevalence in secondary law states.
bIncludes unmarried couples.
cBody mass index is weight in kilograms divided by height in meters squared. Underweight or normal was < 25.0 kg/m2, overweight was 25.0–29.9 kg/m2, and obese was ≥ 30.0 kg/m2.
The prevalence ratios presented in Table 3 ▶ provide estimates of the independent association between sociodemographic characteristics and safety belt use in primary law versus secondary law states. The adjusted regression models revealed that all demographic and behavioral factors examined were modestly associated with safety belt use, with the exception of income in the primary law states (Table 3 ▶). Race/ethnicity differences in safety belt use were observed only for Hispanics and Asian/Pacific Islanders, who were more likely than were Whites to always wear belts, regardless of the type of state enforcement law. Although the results in Table 2 ▶ demonstrate that groups in primary law states were more likely to always wear safety belts than were groups in secondary law states, the results in Table 3 ▶ demonstrate that, for many characteristics, the variability in safety belt use associated with a particular characteristic was generally less in the primary law states than it was in secondary law states. For example, residents aged 65 years or older in secondary law states were 20% more likely to wear safety belts than persons aged 18–24 years in those states. However, residents aged 65 years or older in primary law states were only 10% more likely to wear safety belts than were their younger counterparts (Table 3 ▶).
3.
Adjusted Prevalence Ratios for Reporting Always Wearing Safety Belts, by Type of State Safety Belt Law: United States, Behavioral Risk Factor Surveillance System, 2002
| Characteristic | Primary Law States Adjusted PR (95% CI) | Secondary Law States Adjusted PR (95% CI) |
| Gender | ||
| Men | Ref | Ref |
| Women | 1.11 (1.09, 1.12) | 1.17 (1.16, 1.18) |
| Race/ethnicity | ||
| Whites | Ref | Ref |
| Blacks | 1.01 (1.00, 1.03) | 1.00 (0.97, 1.02) |
| Hispanics | 1.09 (1.07, 1.11) | 1.09 (1.07, 1.12) |
| Asian or Pacific Islanders | 1.07 (1.04, 1.10) | 1.11 (1.06, 1.16) |
| American Indians/Alaska Natives | 1.03 (0.98, 1.08) | 0.98 (0.92, 1.05) |
| Other race or multiracial | 1.03 (0.99, 1.06) | 1.02 (0.98, 1.06) |
| Education | ||
| Less than high school | Ref | Ref |
| High school graduate | 1.02 (0.99, 1.04) | 1.04 (1.02, 1.07) |
| Some college | 1.03 (1.01, 1.06) | 1.11 (1.08, 1.13) |
| College graduate | 1.07 (1.04, 1.09) | 1.20 (1.17, 1.23) |
| Age, y | ||
| 18–24 | Ref | Ref |
| 25–34 | 1.01 (0.99, 1.04) | 1.04 (1.02, 1.07) |
| 35–64 | 1.07 (1.05, 1.10) | 1.11 (1.08, 1.14) |
| ≥ 65 | 1.10 (1.07, 1.13) | 1.20 (1.17, 1.23) |
| Annual household income, $ | ||
| < 20 000 | Refa | Ref |
| 20 000–49 999 | 0.98 (0.97, 1.00) | 0.98 (0.96, 0.99) |
| ≥ 50 000 | 0.98 (0.96, 1.00) | 1.01 (0.99, 1.03) |
| Marital status | ||
| Marriedb | 1.04 (1.03, 1.06) | 1.05 (1.03, 1.06) |
| Unmarried | Ref | Ref |
| Population density | ||
| Urban or suburban | 1.06 (1.05, 1.07) | 1.10 (1.09, 1.12) |
| Rural | Ref | Ref |
| Body mass indexc | ||
| Underweight or normal | Ref | Ref |
| Overweight | 0.99 (0.98, 1.00) | 0.97 (0.96, 0.98) |
| Obese | 0.95 (0.94, 0.97) | 0.90 (0.88, 0.91) |
| Drinking after driving (last 30 days) | ||
| None | Ref | Ref |
| ≥ 1 times | 0.87 (0.82, 0.92) | 0.81 (0.77, 0.86) |
Note. PR = prevalence ratio; CI = confidence interval; Ref = referent group. Primary law states are those in which police may stop and ticket a motorist solely for being unbelted; secondary law states are those in which police may issue a safety belt citation only if the vehicle has been stopped for another reason. All 50 states and the District of Columbia were included in the analysis.
aP = .073. All other comparisons were significant at P < .001.
bIncludes unmarried couples.
cBody mass index is weight in kilograms divided by height in meters squared. Underweight or normal was < 25.0 kg/m2, overweight was 25.0–29.9 kg/m2, and obese was ≥ 30.0 kg/m2.
DISCUSSION
This study supports previous findings that primary safety belt laws are effective in increasing belt use in the total population, including groups that tend to have lower use rates such as men, young adults, Blacks, and American Indians/Alaska Natives, residents of rural areas, and people who engage in other high-risk behaviors (e.g., driving after drinking).14,17–19 Furthermore, we found that primary enforcement laws appeared to have the greatest effect on those groups with lower rates of safety belt use. For example, the gender gap in belt use was smaller in primary law states than in secondary law states. These findings are important because of the demonstrated protective effect of safety belts for preventing crash-related injuries and fatalities.2,22–25 By narrowing the gap in safety belt use among different sociodemographic groups, primary enforcement may be an effective strategy for reducing disparities in motor vehicle occupant fatality rates.7
Primary safety belt laws also may affect belt use among obese people. There has not been much attention devoted to the issue of obesity and safety belt use since 1989 when Lichtenstein et al.26 reported the relation between decreased safety belt use and increased BMI. This association is of concern because obese people face an increased risk of injuries, including crash-related injuries,27–30 and may be more likely to experience medical complications following an injury.31 A large, national study of BMI and crash fatality concluded that both underweight and obese male drivers, but not female drivers, faced an increased risk of crash-related death, especially in high-speed crashes.32 We found that overweight and obese people were less likely to wear safety belts, which was consistent with findings by Lichtenstein et al.26 In addition, we found that belt use among obese persons was 14 percentage points higher in primary law states than in secondary law states, which suggests that this population is responsive to primary law enforcement. Reasons for lower levels of voluntary safety belt use among this group, including physical discomfort,33 should be explored and addressed as appropriate.
People who drive after drinking alcohol (drinking drivers) reported the lowest safety belt use rates of any subgroup in this study. However, we found that belt use among drinking drivers was nearly 15 percentage points higher in primary law states than in secondary law states, which suggests that this population is also responsive to primary law enforcement. Drinking drivers are of particular concern because of their low belt use rates,34–37 increased risk of severe crash involvement, and because alcohol impairment itself, independent of crash severity, causes poorer crash outcomes.38,39 Although they comprise only about 2% of the adult population,40 drinking drivers account for 26% of occupant fatalities.41 Increasing belt use among drinking drivers could substantially reduce crash-related fatalities.
Several studies on the differences in safety belt use by race or ethnicity reported that the disparity between Whites and Blacks was reduced or even eliminated in areas that had primary law enforcement.17–18,42–44 In addition to confirming this finding, we found that differences in safety belt use between Whites and Blacks in secondary law states disappeared after adjustment for other factors. Although we found that Hispanics were more likely to wear safety belts than were Whites, regardless of law type, Davis et al.17 reported the opposite pattern. This discrepancy might be explained by differences in the study populations, including possible differences in whether the participants were immigrants or US born. Among immigrants, differences in level of acculturation have been shown to influence safety belt use among Hispanics.45
The population of states with secondary enforcement laws was very similar to that of states with primary enforcement laws, which suggests that conversion to primary laws could lead to levels of safety belt use similar to those now observed in primary law states. One notable exception is the disproportionate distribution of rural residents in our study, which may contribute in part to the lower overall rates of belt use observed in states that have secondary laws. Rural residence has been linked to nonuse of safety belts.5,46 However, safety belt use was 12.5 percentage points higher among rural residents of primary law states than of secondary law states. It may, therefore, be reasonable to expect a similar increase in safety belt use among rural residents in secondary law states if those states converted to primary laws.
Limitations
Our findings are subject to several limitations. First, response rates were low in some states and ranged from 42.2% to 82.6%. Second, the BRFSS methodology excludes households without telephones. However, telephone noncoverage in the United States is estimated at 2.4% and thus, would have a minimal effect on our findings.47 Third, the BRFSS sample is limited to noninstitutionalized, civilian adults and cannot be generalized to children, institutionalized persons, or military personnel. Fourth, social-desirability bias could result in overestimates of safety belt use, and it is possible that this bias could have a differential effect depending on the type of belt enforcement present in a state. However, differential reporting seems unlikely because most people believe their state’s law provides for primary enforcement, regardless of whether that is the case,5 and an evaluation of the BRFSS has shown minimal bias in the data.20 Finally, the BRFSS data are cross-sectional and therefore do not allow us to draw any conclusions about causality. An advantage of self-reported survey data is that the data can provide estimates of “usual” behavior rather than behavior at 1 point in time, which is collected in observational surveys. Other advantages of self-reported survey data over observational survey data are that more accurate measures of age and race/ethnicity as well as other important sociodemographic variables are collected from the respondents.
Although many people do not distinguish between the enforcement provision provided by their state’s law,5 primary enforcement laws may contribute to higher levels of belt use because of an increased likelihood of (1) tickets being issued by police and (2) those tickets resulting in court convictions.48 High-visibility enforcement, which plays a critical role in promoting safety belt use,10,49 is both easier to conduct and more effective in primary law states.49 In addition to the enforcement provision, other characteristics of safety belt laws, such as the monetary amount of the fine and coverage (e.g., front seat occupants or all occupants), may affect rates of belt use.
Conclusions
Primary enforcement legislation along with high-visibility enforcement is an effective population-based intervention.10 Among all of the sociodemographic characteristics examined, safety belt use was higher in states with primary laws than in states with secondary laws. Primary laws may have the greatest effect on the groups at greatest risk for not wearing safety belts, as evidenced by the association of primary laws with both higher levels of belt use and smaller sociodemographic disparities in belt use. These findings provide additional support for primary enforcement laws. To reduce crash-related death and disability, states should consider primary enforcement safety belt legislation that covers all age-appropriate occupants, in all seats, for all vehicles equipped with safety belts.9,10,15,44,50
Acknowledgments
We thank the state Behavioral Risk Factor Surveillance System Coordinators for their roles in the collection of data.
Human Participant Protection No protocol or institutional review board approval was needed for this study, because data were collected anonymously from a public health surveillance system in which adults voluntarily consented to telephone interviews.
Peer Reviewed
Note. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
Contributors L. F. Beck analyzed and interpreted data and wrote the article. R. A. Shults conceptualized the analysis plan and assisted with writing the article. K. A. Mack assisted with writing the article. G. W. Ryan analyzed and interpreted data and modified the article.
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