Health-Related Quality of Life and Behaviors Risky to Health among Adults Aged 18–24 Years in Secondary or Higher Education—United States, 2003–2005
Article Outline
Abstract
Purpose
To identify the demographic characteristics and behaviors risky to health contributing to health-related quality of life (HRQOL), defined as the perceived physical or mental health over time.
Methods
Information on students aged 18–24 years from the aggregated Behavioral Risk Factor Surveillance System survey (BRFSS) 2003, 2004, and 2005 data for the 50 states and District of Columbia was studied. Selected HRQOL measures, health care access, behaviors risky to health (i.e., leisure-time physical activity or exercise, cigarette smoking, binge drinking, and indicators of risky sex behaviors), and selected health conditions were analyzed.
Results
Overall, students aged 18–24 years reported more mentally unhealthy days than physically unhealthy days. Compared with students in secondary education, younger graduate students reported better mental health, self-rated health, and fewer behaviors risky to health. Regardless of educational level, reported physically or mentally unhealthy days differed by selected demographic characteristics, health care access, behaviors risky to health, and health conditions.
Conclusions
Behaviors risky to health and their associations with mental health should be recognized and addressed in any health prevention or intervention program for student populations. Public health professionals should promote evidence-based health promotion programs to prevent young adults from initiating risky behaviors, continue to promote risk-reduction and cessation skills to those engaged in these behaviors, and incorporate mental health promotion into risk-reduction intervention programs.
Keywords: Adolescents, High school student, College students, Graduate students, Health-related quality of life, Mental health, Risky behavior, Health care access, Demographics
Students in secondary and higher education may be involved in behaviors risky to health that often begin at an early age and continue into adulthood [1], [2]. Several ongoing efforts have monitored these students' risky behaviors and health needs. The Youth Risk Behavior Surveillance System (YRBSS), for example, is a national school-based survey that monitors six categories of priority health-risk behaviors among students in grades 9–12 attending public and private schools [2]. The American College Health Association-National College Health Assessment (ACHA-NCHA) survey provides in a convenience sample of colleges' and universities' information about students' health status, health problems, risky behaviors, protective behaviors, and access to health care [3].
Research on adults has explored the relationship between health risk behaviors and health-related quality of life (HRQOL), defined as their perceived physical and mental health over time [4]. HRQOL data have been used for a number of years to assess the population burden of illness and disability, to identify health disparities and needs, and to monitor changes over time [5], [6], [7]. For example, HRQOL measures developed by the Centers for Disease Control and Prevention (CDC) have been part of the Behavioral Risk Factor Surveillance System (BRFSS) since 1993 [8] and of the National Health and Nutrition Examination Survey (NHANES) since 2000 [9]. The four main CDC HRQOL measures (HRQOL-4) have demonstrated reliability and validity in assessing the health of younger [10], [11], [12] and older adults [13], [14]. Findings from previous studies among adults [7], [13], [14], [15], [16], [17], [18], [19] have shown how HRQOL is associated with chronic diseases, disability, behaviors risky to health, socioeconomic factors, and demographic factors.
For example, females, Native Americans/Alaska natives, unemployed persons, smokers, and binge drinkers report more physically and mentally unhealthy days than males, individuals of white ethnicity, employed persons, non-smokers, and non-binge drinkers, respectively [4], [18].
However, although some studies have assessed health and behaviors risky to health among students in secondary or higher education locally or nationally [2], [3], [20], [21], only one study assessed behaviors risky to health (i.e., indicators of risky sex behaviors, cigarette smoking, and binge drinking) simultaneously in both high school and college students [22]. Moreover, only a few studies examined whether and how HRQOL is associated with behaviors risky to health among young adults either in secondary or higher education [23], [24]. This study is unique because the sample was nationally representative (50 states and District of Columbia), included students in secondary and higher education, and assessed risky health behaviors and HRQOL simultaneously, permitting comparisons of differences between student subgroups. Almost all previous studies used different survey questions and methodologies and did not include both secondary and higher education students simultaneously, severely limiting comparisons between groups.
In this study, we seek to extend previous research [2], [3], [7], [18], [20], [21], [22], [23], [24], [25], [26] to estimate the prevalence of behaviors risky to health and to examine the association between HRQOL and demographic characteristics, health care access, behaviors risky to health, and health conditions in a nationally representative sample of adults aged 18–24 years in secondary or higher education. Examining HRQOL in 18- to 24-year-olds is important because HRQOL can indicate risk for suicide [27], the third leading cause of death for young people 18–24 years of age [28] . The 2005 YRBSS data indicated that 8.4% of high school students had attempted suicide in the 12 months before the survey [2]. Among Oregon residents, the more days a respondent experienced poor mental health, the more likely he or she was to consider suicide. Even after controlling for other factors, respondents who said their mental health was not good during all of the previous 30 days were 24 times more likely to have suicidal ideation than those reporting no more than 1 day during the past 30 days [27].
Methods
BRFSS is an ongoing, state-based, cross-sectional, random-digit-dialed telephone survey of non-institutionalized adults aged 18 years or older that is conducted in the 50 states, the District of Columbia (DC), Guam, Puerto Rico, and the Virgin Islands [8]. It has been used to monitor the prevalence of key behaviors risky to health, clinical preventive health practices, and health care access, primarily related to chronic disease and injury. For this study, we aggregated BRFSS 2003, 2004, and 2005 data from the 50 states and DC to improve statistical power for subgroup analyses.
The student subgroup from the BRFSS data was defined according to the responses to two survey questions besides age. The first question was as follows: “Are you currently employed for wages, self-employed, out of work for more than 1 year, out of work for less than 1 year, a homemaker, a student, retired, or unable to work?” Response options were as follows: (1) employed for wages (2) self-employed (3) out of work for more than 1 year (4) out of work for less than 1 year (5) a homemaker (6) a student (7) retired (8) unable to work.
Respondents reporting they were students from 18–24 years old comprised the study population. This student population (n = 12,835) was then categorized into three subgroups based on the response to the second question, “What is the highest grade or year of school you completed?” Response options were as follows: (1) never attended school or only kindergarten; (2) grades 1–8 (elementary); (3) grades 9–11 (some high school); (4) grade 12 or GED (high school graduate); (5) college 1 year to 3 years (some college or technical school); (6) college 4 years or more (college graduate).
Students without a high school (HS) diploma comprised the first subgroup, students with a HS diploma or with some college education the second subgroup, and students with a college degree the third subgroup (Figure). Because of the age distribution and educational level attained in this study sample, we assumed that students without a HS diploma were students in secondary education. Similarly, because we could not distinguish students in technical schools from those in college, we assumed that students with a HS diploma or with some college education were students in technical school or college and those students with a college degree were younger graduate students. About 13.1% of surveyed adults were 18–24 years old, and about a quarter (25.8%) of these were students. Of the students, 12.3% (n = 1,522) were in secondary education; 75.6% (n = 9,472) technical school or college; and 12.1% (n = 1,841) in graduate school.
Figure.
Identifying study population (18 to 24-year-old persons).
We studied all the students and the three subgroups with respect to the following: (1) demographic factors (i.e., age, sex, race/ethnicity, annual household income); (2) health care access (i.e., health care coverage and the need to see a doctor but could not because of cost during past 12 months); (3) behaviors risky to health (i.e., no leisure-time physical activity or exercise during the past month; cigarette smoking; having five or more alcoholic beverages on one occasion in the past month [“binge drinking”]; and any indicators of risky sex behaviors during the past year such as intravenous drug use, having been treated for a sexually transmitted disease, having received money or drugs in exchange for sex, or having had anal sex without a condom); and (4) health conditions (i.e., body mass index; activity limitation because of physical, mental, or emotional problems; and current asthma status).
Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters for every respondent except pregnant women. BMI categories were defined as underweight (<18.5 kg/m2); normal (18.5–24.9 kg/m2); overweight (25.0–29.9 kg/m2); and obese (≥30.0 kg/m2). Current asthma status was assessed from affirmative answers to both of the following questions: “Have you ever had asthma?” and “Do you still have asthma?” The number of behaviors risky to health for each respondent was the sum of no leisure-time physical activity during the past month, current smoking, binge drinking, and engaging in a risky sex behavior. Because less than 4% of the students had more than two such behaviors, we grouped students into those having no behavior risky to health, one behavior risky to health, or two or more behaviors risky to health.
We examined the relationship between HRQOL and demographic characteristics, health care access, behaviors risky to health, and health conditions. The following three of the CDC HRQOL-4 measures were included in the analysis: (1) Self-rated general health status, with responses categorized as excellent or very good, good, and fair or poor; (2) physically unhealthy days (i.e., including physical illness or injury, the number of days during the preceding 30 days when physical health was not good); and (3) mentally unhealthy days (i.e., including stress, depression, or emotional problems, the number of days during the preceding 30 days when mental health was not good).
The data were weighted to estimate population parameters (i.e., means, proportions). Multivariable-adjusted means, percentages, and 95% two-side confidence intervals (CIs) were calculated with SUDAAN software (version 9; Research Triangle Institute, Research Triangle Park, NC) to account for the complex survey design of the BRFSS. We declared differences in estimates between subgroups as statistically significant (α = 0.05) only if their 95% CIs did not overlap.
Logistic regression or multinomial logit models were used to adjust for age, sex, race, and ethnicity in the analysis of categorical dependent variables with two or more categories respectively, such as demographic characteristics, health care access, risky behaviors, and health conditions. Multiple linear regression models were used to adjust for these demographic characteristics in predicting the two continuous HRQOL measures, i.e., physically or mentally unhealthy days. None of the independent variables in these models were collinear. All results were adjusted for age, sex, race, and ethnicity to account for the observed differences among student subgroups.
Results
Characteristics of the study population are shown in Table 1. Students aged 18–24 years were predominantly single (87.6%), and their ages increased with their educational level (mean age for students in secondary education, 18.5 years; students in technical school or college, 20.1 years; and younger graduate students, 22.6 years). The percentage of males decreased with educational level (students in secondary education: 56.0%; students in technical school or college: 49.2%; and younger graduate students: 47.8%). Approximately 60% of students were non-Hispanic white. The percentage of non-Hispanic blacks and Hispanics decreased, and the percentage of Asian/Pacific Islanders increased with educational level, but these differences were not statistically significant. Reported annual household incomes also did not differ among student subgroups.
Table 1. Characteristics of students aged 18 to 24 years—United States, Behavioral Risk Factor Surveillance System, 2003–2005
| Total (n = 12,835) | Students in secondary education (n = 1,522) | Students in technical school or college (n = 9,472) | Younger graduate students (n = 1,841) | |||||
|---|---|---|---|---|---|---|---|---|
| Characteristic | n | % (95% CI)a | n | % (95% CI)a | n | % (95% CI)a | n | % (95% CI)a |
| Age in years (mean) | 20.2 | 18.5 | 20.1 | 22.6 | ||||
| Age in years (median) | 20 | 18 | 20 | 23 | ||||
| Sex | ||||||||
 Male | 5,186 | 49.9(48.3–51.5) | 720 | 56.0(51.5–60.5) | 3,771 | 49.2(47.4–51.1) | 695 | 47.8(43.1–52.5) |
| Female | 7,649 | 50.1(48.5–51.7) | 802 | 44.0(39.5–48.5) | 5,701 | 50.8(48.9–52.6) | 1,146 | 52.2(47.5–56.9) |
| Race/ethnicity | ||||||||
| White, non-Hispanic | 8,993 | 62.8(61.2–64.4) | 973 | 58.9(54.1–63.6) | 6,642 | 62.4(60.5–64.2) | 1,378 | 70.1(65.7–74.6) |
| Black, non-Hispanic | 1,483 | 12.2(11.2–13.2) | 244 | 20.1(16.0–24.2) | 1,075 | 11.6(10.5–12.8) | 164 | 8.3(6.2–10.5) |
| Hispanic | 1,091 | 14.2(12.8–15.6) | 166 | 13.3(9.7–16.8) | 836 | 15.3(13.6–17.0) | 89 | 7.9(4.8–11.1) |
| Asian/Pacific Islander | 536 | 6.8(5.8–7.9) | 42 | 5.1(2.2–8.1) | 366 | 6.4(5.2–7.6) | 128 | 10.1(6.8–13.5) |
| Native American/Alaskan Natives | 236 | 0.9(0.6–1.2) | 54 | 0.7(0.3–1.1) | 174 | 1.0(0.7–1.3) | 8 | 0.8(0.0–1.6) |
| Other race, non-Hispanic | 427 | 3.0(2.5–3.6) | 38 | 2.0(0.8–3.2) | 334 | 3.2(2.6–3.9) | 55 | 2.7(1.4–3.9) |
| Annual household income | ||||||||
| <$15,000 | 2,540 | 22.4(20.8–23.9) | 173 | 23.5(18.0–28.9) | 1,859 | 21.8(20.0–23.6) | 508 | 23.8(19.6–28.1) |
| $15,000-$24,999 | 2,225 | 18.8(17.5–20.2) | 187 | 23.2(18.2–28.1) | 1,604 | 19.0(17.4–20.6) | 434 | 16.0(13.0–18.9) |
| $25,000-$49,999 | 2,130 | 22.5(20.9–24.1) | 186 | 22.4(17.5–27.3) | 1,605 | 22.7(20.9–24.5) | 339 | 21.1(17.0–25.2) |
| ≥$50,000 | 2,739 | 36.3(34.5–38.1) | 274 | 31.0(25.6–36.3) | 2,146 | 36.5(34.5–38.6) | 319 | 39.1(33.5–44.7) |
| Does not have health care coverage | 2,312 | 18.8(17.4–20.1) | 303 | 29.3(24.8–33.8) | 1,760 | 19.3(17.7–20.8) | 249 | 9.9(7.6–12.2) |
| Needed to see a doctor but could not because of cost during past 12 months | 1,459 | 10.7(9.7–11.7) | 140 | 12.8(9.3–16.3) | 1,116 | 11.2(10.0–12.5) | 203 | 7.5(5.5–9.4) |
| No leisure time physical activity or exercise in past month | 1,517 | 12.7(11.6–13.9) | 248 | 18.7(15.1–22.2) | 1,127 | 12.8(11.4–14.2) | 142 | 6.9(4.9–8.8) |
| Cigarette smoking status | ||||||||
| Current smoker | 2,191 | 16.2(15.0–17.4) | 292 | 23.8(19.6–28.1) | 1,678 | 17.5(16.0–19.0) | 221 | 6.1(4.7–7.5) |
| Former smoker | 852 | 5.8(5.0–6.5) | 60 | 4.5(2.5–6.6) | 626 | 6.0(5.1–6.9) | 166 | 5.0(3.6–6.3) |
| Never smoked | 9,766 | 78.1(76.7–79.4) | 1,168 | 71.7(67.3–76.0) | 7,148 | 76.5(74.9–78.1) | 1,450 | 88.9(87.0–90.9) |
| Binge drinkingb | 3,256 | 25.7(24.3–27.1) | 200 | 15.9(12.3–19.4) | 2,459 | 26.9(25.2–28.5) | 597 | 27.0(23.3–30.7) |
| Had any indicators of risky sex behaviors in past year | 872 | 7.6(6.6–8.6) | 135 | 9.2(6.6–11.9) | 653 | 7.8(6.7–9.0) | 84 | 4.9(2.7–7.1) |
| Number of behaviors risky to healthc | ||||||||
| No risky behavior | 7,064 | 55.3(53.7–56.9) | 880 | 53.9(49.5–58.4) | 2,982 | 54.2(52.3–56.0) | 1,025 | 62.0(57.5–66.4) |
| One risky behavior | 4,044 | 31.2(29.8–32.7) | 448 | 28.0(24.0–31.9) | 1,331 | 31.4(29.6–33.1) | 614 | 31.4(27.2–35.7) |
| Two or more risky behaviors | 1,727 | 13.5(12.3–14.6) | 194 | 18.0(14.0–22.0) | 5,159 | 14.5(13.0–15.9) | 202 | 6.6(5.0–8.3) |
| Body mass indexd,e | ||||||||
| Underweight | 578 | 5.0(4.1–5.8) | 87 | 6.1(3.9–8.4) | 425 | 5.1(4.1–6.0) | 66 | 3.4(1.5–5.4) |
| Normal | 7,565 | 60.8(59.2–62.4) | 861 | 58.8(54.0–63.7) | 5,591 | 60.6(58.7–62.5) | 1,113 | 63.5(59.0–68.0) |
| Overweight | 2,789 | 23.5(22.0–24.9) | 306 | 21.0(17.0–25.0) | 2,044 | 23.8(22.1–25.5) | 439 | 23.9(19.9–27.9) |
| Obese | 1,341 | 10.8(9.7–11.8) | 162 | 14.0(10.3–17.8) | 1,003 | 10.6(9.4–11.8) | 176 | 9.2(6.3–12.0) |
| Self-rated health | ||||||||
| Excellent or very good | 8,802 | 68.4(66.9–70.0) | 892 | 59.3(54.9–63.8) | 6,457 | 68.3(66.5–70.1) | 1,453 | 78.3(74.4–82.2) |
| Good | 3,323 | 25.7(24.3–27.2) | 490 | 29.5(25.5–33.5) | 2,497 | 26.0(24.4–27.7) | 336 | 19.5(15.7–23.3) |
| Fair or poor | 697 | 5.8(4.9–6.7) | 138 | 11.2(8.0–14.4) | 509 | 5.7(4.6–6.8) | 50 | 2.2(1.1–3.3) |
| Activity limitation because of physical, mental, or emotional problems | 1,095 | 8.7(7.8–9.7) | 149 | 10.0(7.4–12.7) | 805 | 8.4(7.4–9.5) | 141 | 9.3(6.2–12.4) |
| Have asthma now | 1,304 | 9.7(8.7–10.6) | 182 | 11.5(8.7–14.2) | 938 | 9.1(8.1–10.2) | 184 | 11.3(8.3–14.3) |
aWeighted and adjusted (i.e., sex, race/ethnicity, and age) percentage and 95% confidence intervals (CI). |
bHaving five or more alcoholic beverages on one occasion in past month. |
cNumber of any of these health risk behaviors: no leisure time physical activity in past month, current smoker, binge drinking in past month, and participated in sexually transmitted disease–related health risk behaviors in past year. |
dBody mass index categories are underweight (<18.5 kg/m2); normal (18.5–24.9 kg/m2); overweight (25.0–29.9 kg/m2); obese (≥30.0 kg/m2). |
ePregnant respondents were excluded from body mass index calculation. |
Students in secondary education more often (29.3%) reported not having health care coverage than students in technical school or college (19.3%) and younger graduate students (9.9%). About 10% of each student subgroup reported needing to see a doctor but not being able to afford one in the past 12 months.
The prevalence of no leisure-time physical activity decreased as educational level increased (students in secondary education: 18.7%; students in technical school or college: 12.8%; and younger graduate students: 6.9%). Similarly, students in secondary education were more likely to be current smokers (23.8%) than students in technical school or college (17.5%) and younger graduate students (6.1%). The prevalence of any indicator of risky sex behaviors also gradually declined with educational level, but these differences were not statistically significant (students in secondary education: 9.2%; students in technical school or college: 7.8%; and younger graduate students: 4.9%). On the other hand, students in secondary education were less likely to report binge drinking (15.9%) than students in technical school or college (26.9%) and younger graduate students (27.0%). Overall, 55.3% of students had no behaviors risky to health; 31.2% had one, and 13.5% had two or more. Although the prevalence of one risky behavior was similar among the three student subgroups, the prevalence of two or more risky behaviors was similar only among students in secondary education (18.0%) and students in technical school or college (14.5%) but exceeded that among younger graduate students (6.6%).
The student subgroups did not differ by activity limitation (9%), current asthma status (10%), or BMI category (5.0% were underweight, 60.8% were normal, 23.5% were overweight, and 10.8% were obese).
The percentage rating their health as excellent or very good increased with educational level (students in secondary education: 59.3%; students in technical school or college: 68.3%; and younger graduate students: 78.3%). Correspondingly, the percentage rating their health as fair or poor decreased as educational level increased (students in secondary education: 11.2%; students in technical school or college: 5.7%; and younger graduate students: 2.2%).
Health-related quality of life among study participants is reported in Table 2. Overall, these students reported about 2 days of physically unhealthy days and about 4 days of mentally unhealthy days in the past 30 days. Mean physically unhealthy days did not differ among student subgroups. However, mean mentally unhealthy days among younger graduate students (2.8 days) was less than that among students in secondary education (4.4 days) and in technical school or college (4.0 days).
Table 2. Health related-quality of life among students aged 18–24 years by educational status, demographic characteristics, health care access, behaviors risky to health, and health conditions—United States, Behavioral Risk Factor Surveillance System, 2003–2005
| Characteristic | Sample size | Physically unhealthy days Mean (95% CI)a | Mentally unhealthy days Mean (95% CI)a |
|---|---|---|---|
| Student group | |||
| Students in secondary education | 1,522 | 2.2(1.9–2.4) | 4.4(3.7–5.0) |
| Students in technical school or college | 9,472 | 2.3(1.9–2.8) | 4.0(3.8–4.3) |
| Younger graduate students | 1,841 | 2.4(1.7–3.1) | 2.8(2.3–3.4) |
| All students(18–24 years) | |||
| Total | 12,835 | 2.2(1.8–2.5) | 3.9(3.5–4.4) |
| Sex | |||
| Male | 5,186 | 1.9(1.6–2.2) | 3.2(2.8–3.5) |
| Female | 7,649 | 2.5(2.2–2.7) | 4.7(4.4–5.5) |
| Race/ethnicity | |||
| White, non-Hispanic | 8,993 | 2.2(2.0–2.4) | 4.0(3.7–4.3) |
| Black, non-Hispanic | 1,483 | 1.8(1.4–2.3) | 3.7(3.1–4.4) |
| Hispanic | 1,091 | 2.5(1.7–3.4) | 3.8(3.0–4.5) |
| Asian/Pacific Islander | 536 | 1.9(1.1–2.6) | 2.7(2.1–3.4) |
| Native American/Alaska Natives | 236 | 2.6(1.3–4.0) | 6.8(3.8–9.6) |
| Other race, non-Hispanic | 427 | 2.2(1.5–2.9) | 5.8(4.4–7.1) |
| Annual household income | |||
| <$15,000 | 2,540 | 2.2(1.8–2.6) | 3.9(3.4–4.3) |
| $15,000-$24,999 | 2,225 | 2.3(1.8–2.8) | 4.3(3.5–5.0) |
| $25,000-$49,999 | 2,130 | 2.1(1.5–2.7) | 4.0(3.5–4.4) |
| ≥$50,000 | 2,739 | 2.2(1.7–2.6) | 4.0(3.6–4.5) |
| Have health care coverage | |||
| Yes | 10,195 | 2.2(2.0–2.5) | 3.9(3.7–4.2) |
| No | 2,312 | 2.0(1.6–2.4) | 4.2(3.6–4.7) |
| Needed to see a doctor but could not because of cost during past 12 months | |||
| Yes | 1,459 | 3.8(3.1–4.6) | 6.1(5.4–6.8) |
| No | 11,358 | 2.0(1.8–2.2) | 3.7(3.4–3.9) |
| Leisure time physical activity or exercise in past month | |||
| Yes | 11,311 | 2.0(1.8–2.3) | 3.9(3.6–4.1) |
| No | 1,517 | 3.0(2.2–3.9) | 4.3(3.5–5.1) |
| Cigarette smoking status | |||
| Current smoker | 2,191 | 2.9(2.2–3.6) | 6.5(5.6–7.3) |
| Former smoker | 852 | 2.3(1.6–2.9) | 5.9(4.9–6.9) |
| Never smoked | 9,766 | 2.0(1.8–2.2) | 3.3(3.0–3.5) |
| Binge drinkingb | |||
| Yes | 3,256 | 2.6(2.1–3.1) | 5.2(4.7–5.7) |
| No | 9,460 | 2.0(1.8–2.3) | 3.5(3.2–3.7) |
| Participated in any risky sex behaviors in past year | |||
| Yes | 872 | 3.3(2.4–4.3) | 7.5(6.1–8.8) |
| No | 11,487 | 2.1(1.9–2.3) | 3.7(3.4–3.9) |
| Number of behaviors risky to healthc | |||
| None | 7,064 | 1.8(1.6–2.0) | 3.1(2.8–3.3) |
| One | 4,044 | 2.4(2.1–2.8) | 4.3(3.8–4.7) |
| Two or more | 1,727 | 3.1(2.3–3.8) | 6.7(5.8–7.6) |
| Body mass indexd,e | |||
| Underweight | 578 | 2.2(1.6–2.8) | 4.4(3.4–5.4) |
| Normal | 7,565 | 2.1(1.8–2.4) | 3.7(3.5–4.0) |
| Overweight | 2,789 | 2.0(1.7–2.4) | 3.9(3.4–4.4) |
| Obese | 1,341 | 3.2(2.4–4.0) | 4.7(3.9–5.5) |
| Self-rated health | |||
| Excellent or very good | 8,802 | 1.6(1.4–1.8) | 3.3(3.0–3.5) |
| Good | 3,323 | 2.6(2.2–3.0) | 4.9(4.4–5.4) |
| Fair or poor | 697 | 6.7(5.1–8.2) | 7.2(6.0–8.3) |
| Activity limitation because of physical, mental, or emotional problems | |||
| Yes | 1,095 | 6.5(5.4–7.6) | 7.4(6.7–8.8) |
| No | 11,506 | 1.8(1.6–2.0) | 3.4(3.4–3.8) |
| (continuedonnextpage) | |||
| Have asthma now | |||
| Yes | 1,304 | 3.6(2.9–4.3) | 5.2(4.5–5.9) |
| No | 11,461 | 2.0(1.8–2.2) | 3.8(3.6–4.0) |
aWeighted and adjusted (i.e., sex, race/ethnicity, and age) means and 95% confidence intervals (CI). |
bHaving five or more alcoholic beverages on one occasion. |
cNumber of the following risky behaviors: no leisure time physical activity, current smoking, binge drinking, and ever participated in sexually transmitted disease–related high-risk behaviors. |
dBody mass index categories are underweight (<18.5 kg/m2); normal (18.5–24.9 kg/m2); overweight (25.0–29.9 kg/m2); obese (≥30.0 kg/m2). |
ePregnant respondents were excluded from body mass index calculation. |
Reported physically and mentally unhealthy days among students in all three subgroups were associated with selected demographic characteristics, health care access, behaviors risky to health, and health conditions. Compared with males, females reported significantly more physically unhealthy days (2.5 days vs. 1.9 days) and mentally unhealthy days (4.7 days vs. 3.2 days). Mentally unhealthy days but not physically unhealthy days differed by race/ethnicity: Asian/Pacific Islander students reported fewer mentally unhealthy days (2.7 days) than white students (4.0 days), Native American/Alaska Native students (6.8 days), or students of “other races” (5.8 days). Reported physically and mentally unhealthy days also did not differ by marital status (data not shown), annual household income, or health care coverage.
Reported physically and mentally unhealthy days did not differ by leisure-time physical activity status or by BMI. Students who needed to see a doctor but could not because of medical cost had worse HRQOL (3.8 physically unhealthy days and 6.1 mentally unhealthy days) than students who could afford this cost (2.0 physically unhealthy days and 3.7 mentally unhealthy days).
Current smokers or former smokers reported more mentally unhealthy days (6.5 days and 5.9 days, respectively) than students who never smoked (3.3 days). Current smokers reported more, but not significantly more (2.9 days), physically unhealthy days than students who never smoked (2.0 days). Binge drinkers did not report more physically unhealthy days but did report more mentally unhealthy days (5.2 days) than non–binge drinkers (3.5 days). Students who reported any indicator of risky sex behavior reported significantly more physically unhealthy days (3.3 days) and twice as many mentally unhealthy days (7.5 days) as students who did not report such behaviors (2.1 days and 3.7 days, respectively). Finally, students with one risky behavior or with two or more risky behaviors reported significantly more physically unhealthy days (2.4 vs. 3.1) and mentally unhealthy days (4.3 vs. 6.7) than students with no such behaviors (1.8 physically unhealthy days and 3.1 mentally unhealthy days, respectively).
Students with fair or poor health reported four times more physically unhealthy days (6.7) and twice as many mentally unhealthy days (7.2) than students with very good or excellent health (1.6 physically unhealthy days and 3.6 mentally unhealthy days). Students with an activity limitation reported three times as many physically unhealthy days (6.5) and twice as many mentally unhealthy days (7.4) as students without such a limitation (1.8 physically unhealthy days and 3.4 mentally unhealthy days). Compared with students without asthma (2.0 physically unhealthy days and 3.8 mentally unhealthy days), the students with asthma reported more physically unhealthy days (3.6) and mentally unhealthy days (5.2 days).
Discussion
The prevalence of behaviors risky to health and health care coverage differed substantially among student subgroups, partly because of differences in socio-demographic characteristics. The strong associations between HRQOL and both selected behaviors risky to health and health conditions were similar among student subgroups and consistent with those from previous studies [12], [13], [14], [15], [16].
Students in secondary education reported lower health care coverage than students in higher education, perhaps because the former group did not know about such coverage, which their parents are responsible for. Moreover, colleges and universities may provide health care coverage to their college and graduate students. Nonetheless, about 10% of all students could not afford the cost of visiting a doctor when they needed to—a possible gap in access to necessary health care.
The percentage of students who were physically inactive or who currently smoked decreased, but the percentage of binge drinkers markedly increased with increasing educational level. Because alcohol abuse is prevalent among students [2], [3], interventions should focus on students in both secondary and higher education. Although lower among graduate students, overall one tenth of all students engaged in two or more behaviors risky to health. Students at each level engaged in different risky behaviors. For example, smoking and no leisure time physical activity were more prevalent among students in secondary education; smoking and binge drinking were more prevalent among students in technical school or college; and binge drinking was more prevalent among younger graduate students.
Although reported mean physically unhealthy days did not differ by educational level, the percentage of students with fair or poor health decreased as educational level increased. The percentage of students in secondary education with fair or poor health (10%) in this study is consistent with the findings from the 2005 YRBS [2]. Nationwide, 8.0% of HS seniors describe their general health as fair or poor [2]. Our study also indicates high mean mentally unhealthy days among students in secondary education, consistent with the findings from the 2005 YRBS. During the 12 months preceding the latter survey, 26.4% of HS seniors reported that they felt sad or hopeless almost every day for at least 2 weeks in a row, causing them to stop engaging in some usual activities [2].
In contrast, the prevalence of current smoking among students in secondary education in our study was 17.0% and that among HS seniors in the 2005 YRBS was 27.6%. The prevalence of binge drinking among students in secondary education in our study (15.9%) was also less than half that of HS seniors in the 2005 YRBS (32.8%) [2]. Differences in the mode of survey administration may account for these discrepancies. The YRBS is a self-administered survey in the school, whereas the BRFSS is administered nationwide by an interviewer over the telephone. Especially with regard to sensitive topics such as sexual risk behaviors, individuals may feel more comfortable disclosing information anonymously in writing rather than orally during an interview. Individuals are more likely to under-report less socially desirable behaviors and more likely to over-report socially desirable behaviors in a phone interview than in a self-administered survey [29], [30]. This might explain lower percentage of undesirable behaviors in the BRFSS survey. However, the prevalence of binge drinking for students in higher education in our study is consistent with that from the Spring 2004 ACHA-NCHA report [3].
This study also indicates strong associations between HRQOL and selected factors. Female students, students who needed to see a doctor but could not because of medical cost, students engaging in one or more risky behaviors, students with fair-to-poor health, students with activity limitation, and students with asthma reported more physically and mentally unhealthy days than other students [12], [15], [31], [32], [33], [34]. Native American and Native Alaskan students also reported significantly more mentally unhealthy days than their same-age peers, a finding warranting further exploration. The association between risky behaviors and mental health might have serious consequences for impaired physical health as these students get older [34]. Transition from adolescence to young adulthood often leads to a decline in health status due to higher risk behaviors among young adults [35]. Young adults with chronic health limitations or living in poverty face even greater health challenges, especially in health care coverage and use [36], [37]. More research is needed to obtain a more thorough health profile and understanding of young adults. This study may lead to tailored programs and policies that would benefit vulnerable young adults in settings in which they engage, such as in secondary school, college, and technical school. Mental health counseling and interventions to reduce such risky behaviors for these students may prevent these consequences. Moreover, the large number of mentally unhealthy days among students with activity limitations and with asthma suggests that mental health counseling should be a central component of all comprehensive programs for students with these health conditions.
The major strengths of this study are its large sample size and its ability to assess behaviors risky to health and HRQOL within a nationally representative sample of students in secondary and higher education simultaneously. Studying students in secondary and higher education within the same study sample permits comparisons of different student subgroups. Previous studies did not include both secondary and higher education students in the same sample and utilized different survey questions and methodologies, severely limiting the ability to examine differences or similarities between groups.
This study has several limitations. First, students in secondary education and graduate students might have been under-represented in this study. Because the BRFSS includes only adults 18 years and older and because most students were likely to be younger than 24 years old, we imposed an older age cutoff of 24 years, thus excluding students younger than 18 years in secondary education and graduate students older than 24 years. Younger HS students may have been less exposed to behaviors risky to health; and older, presumably more mature graduate students may have avoided such behaviors. Second, because this study included only students 18–24 years old at the time of the survey, this study's findings may therefore not generalize to 18- to 24-year-olds who were not students, to students less than 18 years of age, or to students 24 or more years of age. Thus, a future study to assess HRQOL and risky behaviors among all young adults would be informative. Third, the cross-sectional nature of the BRFSS cannot distinguish whether HRQOL affects the behaviors risky to health or vice versa; for example, we could not determine whether risky behaviors preceded [38] or followed [34] poor mental health. Fourth, because the BRFSS is administered by an interviewer over the telephone, individuals are less likely to report socially undesirable behaviors. Finally, we could not measure individual characteristics (e.g., academic achievement, personality), the physical and the social environment (e.g., air pollution, poor housing, and violence), and availability of economic resources [1], [25], [26] that might account for additional observed differences among student subgroups.
In summary, selected demographic characteristics, health care access, risky behaviors, and health conditions among students aged 18–24 years in secondary and in higher education were associated with their physical and mental health. Evidence-based health promotion programs may prevent young adults from initiating risky behaviors and may foster risk-reduction and -cessation skills in those already engaged in these behaviors [39], thus improving their physical and mental health status.
Acknowledgments
This work was supported through an interagency agreement between the CDC and the U.S. Department of Energy, administered by the Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee (to H.S.Z). The authors acknowledge the support of David G. Moriarty who helped conceive the study, and also thank the Behavioral Risk Factor Surveillance System coordinators and the Behavioral Surveillance Branch staff for data collection and developing the database. The findings and the conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
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PII: S1054-139X(07)00219-4
doi:10.1016/j.jadohealth.2007.05.011
© 2007 Society for Adolescent Medicine. Published by Elsevier Inc. All rights reserved.
