Abstract
-
Purpose
The majority of adolescents use smartphones, and their overdependence on smartphones has emerged as a serious social issue. Although studies have explored the effect of smartphone overdependence on adolescent problem behaviors, research on its influence on sexual behavior is scarce. This study aimed to examine the association between smartphone overdependence and sexual behavior among adolescents.
-
Methods
This study used data from the 19th Korea Youth Risk Behavior Web-Based Survey conducted in 2023. Smartphone overdependence was the independent variable, and sexual behaviors (sexual intercourse and contraceptive use) were the dependent variables. Multivariate regression analysis was performed to control for confounding variables.
-
Results
The study participants included 52,880 adolescents aged 13–18 years. Among them, 28.0% (n=14,672) were classified as smartphone overdependent, 6.5% (n=3,349) had sexual experience, and 65% (n=2,182) of those with sexual experience reported using contraception. Smartphone overdependence was not significantly associated with sexual experience but was significantly associated with contraceptive use. Adolescents in the non-overdependent group were 1.27 times more likely to use contraception than those in the smartphone overdependent group (95% confidence interval, 1.07–1.52; p<.007).
-
Conclusion
The findings highlight a significant association between smartphone overdependence and contraceptive use among adolescents. Policy interventions and educational strategies that consider adolescents’ smartphone usage patterns and trait factors are necessary.
-
Key words: Adolescent; Korea; Secondary data analysis; Sexual behavior; Smartphone
INTRODUCTION
The introduction of the first-generation iPhone in 2007 signaled the onset of the smartphone era, and since then, smartphone use has rapidly increased across the globe. As of 2023, 69.4% of the world’s population uses a smartphone [
1], and 94.8% of South Korea’s population uses a smartphone [
2]. Consistent with this trend, smartphone penetration among teenagers has grown rapidly, with 95% of teenagers in both the United States and South Korea now owning a mobile device. Smartphone ownership among teenagers worldwide is nearly universal [
2].
Smartphones are equipped with various convenient features that enable activities such as communication, information searching, entertainment, healthcare management, and financial transactions. They are also characterized by their ability to provide users with unrestricted access to attractive content at any time, leading to addiction problems, such as smartphone overdependence [
2,
3]. In South Korea, the percentage of smartphone dependence steadily increased until 2021, reaching 24.2%, and it decreased slightly to 23.1% in 2023. However, adolescents have the highest rate compared with that of other age groups, at 40.1% in 2023, and this rate is still rising [
3].
South Korean adolescents are reported to use smartphones primarily to watch video content and play games, spending the most time per day using smartphones compared with other age groups [
2,
3]. Video and game content accessible on smartphones often contains harmful and problematic elements, which may be associated with problematic behaviors in young people [
4]. Sexual content is a common form of harmful material to which adolescents are often exposed. Statistics on the mediums through which youth encounter sexualized material show that internet searches and ads, YouTube, social media, and chat apps accessible on smartphones top the list [
5]. With the rapid advancement of smartphones and internet technology, communication through various media has become widespread, increasing adolescents’ exposure to sexual content. This exposure can increase sexual curiosity and potentially lead to sexual encounters [
6]. Additionally, adolescents who use social media—primarily through smartphones—are reported to be more than twice as likely to engage in risky sexual behaviors, such as not using contraception during intercourse, than those who do not use social media [
7].
Adolescence is a period of increased sexual urges and curiosity, and unprotected sexual activity during this period can lead to sexually transmitted infections (STIs), pregnancy, and miscarriage [
8]. Although the rate of sexual intercourse among adolescents in the United States is higher than that in other developed countries, it has been steadily declining, from 45.7% in the early 2000s to 38.4% in 2019 [
8]. In contrast, the prevalence of sexual intercourse among South Korean adolescents is low in absolute terms—5.1% in 2006 and 6.5% in 2023—but is increasing [
9,
10]. Most pregnant adolescents experience health challenges and disruptions to their education, social life, and economic stability, which affects the teenagers themselves as well as their families and communities [
11].
With the rates of sexual activity among adolescents on the rise, contraception is an important issue. Contraception is a cost-effective and safe way of preventing the negative effects of sexual intercourse among adolescents in terms of personal health and social outcomes [
8]. Sexual and reproductive health behaviors formed during adolescence are crucial because they lay the foundation for health behaviors in adulthood [
12]. The prevalence of contraceptive use among South Korean adolescents increased from 39.1% in 2006 to 77.3% in 2023 [
9,
10]. However, this remains lower than the 98.9% contraceptive prevalence rate among the US adolescents in 2019 [
8]. Consequently, in South Korea, continued attention and targeted interventions are necessary to promote adolescent sexual health and improve contraceptive use considering the increasing prevalence of sexual activity among youth.
Therefore, this study aimed to examine whether differences exist in actual sexual behaviors between adolescents with high levels of smartphone use—characterized as smartphone overdependence—and those without such dependence. To this end, data from the 19th Korea Youth Risk Behavior Survey (KYRBS) [
10], a large-scale cross-sectional survey of middle and high school students, were used to analyze the association between smartphone overdependence and sexual behaviors (i.e., sexual intercourse experience and contraceptive use). The specific objectives of this study were to examine whether sexual behaviors among Korean adolescents differ based on their level of smartphone dependence and to investigate the influence of smartphone dependence on these sexual behaviors.
METHODS
Ethical statements: This study was a secondary analysis of existing data and did not require institutional review board approval or informed consent.
1. Study Design
In this study, we conducted a secondary analysis of raw data from the 19th KYRBWS to investigate the association between smartphone overdependence and sexual behavior among adolescents [
10]. The reporting of this study adhered to the guidelines outlined in Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiative [
13].
The KYRBS is an annual government-approved statistical survey (approval number: 117058) conducted jointly by the Ministry of Education, Ministry of Health and Welfare, and Korea Disease Control and Prevention Agency to assess the health status of Korean adolescents [
10]. The survey is conducted using an anonymous self-administered online questionnaire. In 2023, 52,880 middle and high school students from 799 schools (399 middle schools and 400 high schools) participated in the survey, achieving a participation rate of 92.9% based on the student population. Students with long-term absences, those unable to participate independently due to special needs, and students with literacy disabilities were excluded from the study population. Data collection occurred from August to October 2023. Students individually accessed the survey system on their mobile devices using a participation code printed on the survey instruction while in classrooms with internet access. Furthermore, KYRBWS employs a complex sampling design, and the dataset includes weights to account for selection probability, response rates, and population composition.
1) General characteristics
In this study, general characteristics were selected through a literature review to analyze factors associated with sexual behavior among adolescents. A previous study using data from the KYRBWS identified factors influencing sexual experience among middle school students, including school type, grade level, smoking experience, alcohol use, drug use, economic status, average weekly allowance, and cohabitation with family [
15]. Based on these findings, this study included the following variables as general characteristics: gender, school type, subjective academic performance, subjective economic status, cohabitation with family, experience of sex education at school, lifetime smoking experience, lifetime alcohol use, and lifetime drug use.
2) Smartphone overdepence
The smartphone overdependence instrument consists of a 10-item self-reported questionnaire measured on a 4-point Likert scale [
14]. The total score ranges from a minimum of 10 to a maximum of 40, with higher scores indicating greater levels of smartphone overdependence. Based on the total score, participants can be categorized into three groups: normal group (10–22 points), potential risk group (23–30 points), and high-risk group (31–40 points). In this study, the potential risk and high-risk groups were combined into a single risk group (23–40 points) and compared with the normal group (10–22 points).
3) Sexual behavior
Sexual behavior was assessed using questions about sexual intercourse experiences and contraceptive use. Sexual intercourse experiences were determined by asking the following question: “Have you ever had sexual intercourse?” The use of contraception was assessed among participants with sexual experience by asking the following question: “Did you use contraception to prevent pregnancy during sexual intercourse?” Participants who responded “always” or “most of the time” were categorized as the contraceptive use group, whereas those who responded “occasionally” or “never” were categorized as the non-contraceptive use group.
4. Data Analysis
Data analysis was performed using IBM SPSS Statistics software ver. 26.0 (IBM Corp.). For complex sample data analysis, we used the stratification, clusters, and weights information provided in the KYRBWS raw data guidelines [
10]. Descriptive statistical analysis was performed to examine the general characteristics of the adolescents included in the survey. All chi-square tests were used to identify differences in sexual experience and contraceptive use based on smartphone overdependence. Multivariate logistic regression analysis was performed to examine the association between smartphone overdependence and sexual behaviors among adolescents. To ensure accuracy, general characteristics showing statistically significant differences based on sexual intercourse experience and contraceptive use were included as covariates in the analysis.
RESULTS
1. General Characteristics of the Study Population
The general characteristics of the study population revealed that 51.5% (n=26,769) were male and 50.9% (n=28,401) were middle school students. Regarding subjective academic performance, 29.4% (n=15,540) rated their performance as “average.” In addition, 44.8% (n=23,981) of respondents rated their subjective economic status as “average.” A total of 95.9% (n=50,362) of the participants reported living with their families, and 72.1% (n=38,527) reported having received sex education at school. Most participants reported no history of smoking, alcohol use, or drug use in their lifetime, with proportions of 89.8% (n=47,525), 67.4% (n=35,604), and 98.3% (n=52,041), respectively. Regarding levels of smartphone overdependence, 72.0% (n=38,208) were categorized as the normal group, whereas 28.0% (n=14,672) were classified as the risk group (
Table 1).
Sexual intercourse and contraceptive use were analyzed according to the general characteristics of the study participants (
Table 2). Among the participants (n=52,880), 6.5% (n=3,349) reported having had sexual experience, and contraceptive use was assessed for these 3,349 participants. Sexual experience showed statistically significant differences according to gender, school type, subjective academic performance, subjective economic status, cohabitation with family, experience of sex education at school, lifetime smoking experience, lifetime alcohol use, and lifetime drug use. Contraceptive use showed statistically significant differences across all variables except for gender, including school type, subjective academic performance, subjective economic status, cohabitation with family, experience of sex education at school, lifetime smoking experience, lifetime alcohol use, and lifetime drug use. Additionally, when analyzing differences in sexual experience and contraceptive use based on smartphone overdependence, all variables showed significant differences according to smartphone overdependence (
Table 2).
1) Sexual intercourse
A logistic regression analysis was conducted to examine the association between smartphone overdependence and sexual intercourse experience among adolescents. As presented in
Table 2, nine general characteristics expected to affect sexual intercourse were included as covariates. The results showed that smartphone overdependence was not significantly associated with sexual intercourse experience (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.87–1.07;
p=.529). The overall model was statistically significant (Wald χ
2=3,653.42, degrees of freedom [df]=15.31,
p<.001) (
Table 3).
Regarding the covariates, males were significantly less likely than females to have experienced sexual intercourse (OR, 0.86; 95% CI, 0.78–0.94;
p=.001). High school students had significantly lower odds of sexual intercourse compared to middle school students (OR, 0.42; 95% CI, 0.38–0.46;
p<.001). Lower perceived economic status was associated with higher odds of sexual intercourse; in particular, the “low” group showed significantly higher odds compared to the “high” group (OR, 1.29; 95% CI, 1.00–1.66;
p=.049). In addition, co-residence with family members and lifetime experiences of smoking, drinking, and drug use were significantly associated with sexual intercourse experience (
Table 3).
2) Use of contraception
A logistic regression analysis was conducted to examine the association between smartphone overdependence and contraceptive use among adolescents who had experienced sexual intercourse. As presented in
Table 2, nine general characteristics expected to affect contraceptive use were included as covariates. The results showed that adolescents in the smartphone overdependence group were significantly less likely to use contraception compared to those in the normal group (OR, 0.77; 95% CI, 0.65–0.92;
p=.004). The overall regression model was statistically significant (Wald χ
2=137.54, df=15.26,
p<.001) (
Table 3).
Regarding the covariates, high school students were significantly less likely than middle school students to use contraception (OR, 0.45; 95% CI, 0.38–0.54;
p<.001). Adolescents in the lowest economic group were significantly less likely to use contraception than those in the highest group (OR, 0.64; 95% CI, 0.44–0.94;
p=.022). Additionally, co-residence with family members, sex education experience, and lifetime experiences of smoking and drug use were significantly associated with contraceptive use (
Table 3).
DISCUSSION
In this study, we examined the sexual behavior of smartphone-dependent adolescents and analyzed the effect of smartphone dependence on sexual behavior. Using representative data from the 19th KYRBS [
10], we found that smartphone dependence among adolescents was associated with contraceptive use.
Adolescents who were more dependent on their smartphones were less likely to use contraception than those who were not. Smartphone-dependent adolescents may have fewer opportunities to engage in conversations about contraception. According to the social control theory, social bonds among adolescents are critical in deterring delinquent behavior [
16]. Parents, teachers, and peers are key sources of social support for adolescents [
17]. In addition, smartphone overdependence is more common among adolescents who receive less support from parents or peers [
18,
19]. These findings indicate that adolescents with smartphone overdependence may experience a lack of parental warmth, supervision, rational guidance, and close friendships [
18]. Parent–child communication and peer counseling have protective effects on contraceptive use [
20,
21]. Considering these findings, adolescents who are overdependent on smartphones may have lower rates of contraceptive use due to limited communication with parents and peers about contraception. In South Korea, only 16.2% of adolescents reported having discussed sex with others, indicating a very low level of sexual communication [
5]. These statistics highlight the need for efforts to improve contraceptive behaviors through enhanced communication between parents and adolescents and among peers. Because smartphone-dependent adolescents often lack adequate social support, it is necessary to provide them with opportunities or platforms to discuss topics such as contraception.
A review of previous studies on factors influencing smartphone overdependence and contraceptive use indicates that certain adolescent traits have been identified as factors. Traits such as depression, impulsivity, self-regulation, and self-esteem influence smartphone overdependence and contraceptive behavior [
3,
19,
22-
25]. Although >80% of youth in South Korea receive education on healthy smartphone use and sexual health [
26], adolescents often cannot translate this knowledge into action [
10], indicating that interventions should focus on education as well as identifying and addressing underlying trait factors.
The lower likelihood of contraceptive use among adolescents who are overdependent on smartphones may be influenced by their exposure to harmful content. The 19th KYRBS data analyzed in this study does not include specific details on the contents adolescents are exposed to on their smartphones, making it difficult to draw definitive conclusions [
10]. However, it is necessary to analyze the association considering that adolescents who are overdependent on smartphones primarily consume video content on these devices, that videos constitute the most common form of sexualized media encountered by adolescents, and that the main channels through which such content is accessed—such as internet searches, advertisements, social media, and YouTube—are readily available via smartphones [
2,
3,
5]. A previous study reported that exposure to sexual content among adolescents is associated with an increased likelihood of engaging in unprotected sex [
27]. Thus, it is necessary to examine whether exposure to sexualized content mediates the relationship between smartphone overdependence and contraceptive behavior to draw clearer conclusions. Additionally, studies should examine the differences in content quality accessed by smartphone-dependent and non-dependent adolescents and analyze how this affects their sexual behavior.
Our study found no association between smartphone dependence and rates of sexual intercourse. Adolescents who use social media tend to have a strong need for interpersonal connections, whereas those who play games have a higher need for avoidance [
28]. In this regard, smartphone-dependent adolescents in South Korea predominantly use video content and games [
2,
3], indicating a higher tendency toward avoidance. Sex is more than just a physical act; it is associated with basic human needs for emotional connection and social support [
29]. Therefore, the high avoidance tendencies observed among smartphone-dependent youth in Korea are likely not associated with the rate of sexual experience. The model of the initiation of sexual activity indicates that both biological and psychosocial factors influence the initiation of sexual activity [
30]. Biological factors include the development of physical abilities and sexual motivation related to hormones, whereas psychosocial factors encompass cultural influences (such as regional differences, religion, school, and media), family, and peers that shape individual decisions. Culture, which includes media, also plays a role in influencing the initiation of sexual behavior. However, in the modern world, both smartphone- and non-smartphone-using teenagers have access to sexual information, making it unlikely that smartphone dependence alone will lead to significant differences in sexual experiences. The results of this study indicate that emphasis should be placed on the nature of smartphone use rather than merely the amount of time spent on smartphones. Therefore, future studies should analyze differences in sexual behavior based on smartphone usage characteristics. Additionally, other psychosocial factors outlined in the sexual initiation model may be key; thus, the rate of sexual experience should also be examined in terms of factors such as culture (e.g., education in school and social norms), home environment, and friendships.
Because of the nature of the data analyzed in this study, we could not perform an in-depth analysis of adolescents’ actual smartphone usage content or frequency of sexual intercourse. Moreover, the cross-sectional design limits the ability to determine causal relationships. Nevertheless, the significance of this study lies in its being the first to examine the association between smartphone overdependence and sexual behavior using nationally representative data from the 19th KYRBS.
CONCLUSION
In this study, we aimed to examine the association between smartphone overdependence and sexual behavior among adolescents using nationally representative panel data. This study is significant because it represents the first attempt to explore the effect of smartphone overdependence on sexual behavior within the broader context of recent efforts to understand the association between smartphone use and problematic behaviors among adolescents. The analysis revealed that smartphone overdependence was not associated with sexual intercourse. However, among adolescents who had experienced sexual intercourse, those classified as overdependent on smartphones reported lower rates of contraceptive use than their non-overdependent peers. Given that inadequate contraceptive use among adolescents can increase the risk of unintended pregnancies and STIs, this study highlights the need for early and targeted interventions. For adolescents who are overdependent on smartphones, it is important to promote communication with parents and peers about sexual topics and to identify psychological vulnerabilities to deliver integrated interventions that address both mental and sexual health. In addition, efforts should be made to incorporate digital media education and information literacy into existing sex education programs for this population.
ARTICLE INFORMATION
Table 1.General characteristics of the study population
|
Variable |
Category |
No. (%)a)
|
|
Sex |
Male |
26,769 (51.5) |
|
Female |
26,111 (48.5) |
|
School type |
High school |
24,479 (49.1) |
|
Middle school |
28,401 (50.9) |
|
Perceived academic performanceb)
|
High |
6,795 (12.9) |
|
Middle-high |
13,246 (25.2) |
|
Middle |
15,540 (29.4) |
|
Middle-low |
12,377 (23.3) |
|
Low |
4,917 (9.2) |
|
Perceived economic statusb),c)
|
High |
6,284 (12.3) |
|
Middle-high |
16,126 (31.1) |
|
Middle |
23,981 (44.8) |
|
Middle-low |
5,434 (9.8) |
|
Low |
1,050 (1.9) |
|
Co-residence with family membersb)
|
Yes |
50,362 (95.9) |
|
No |
2,511 (4.1) |
|
Sex education experience |
Yes |
38,527 (72.1) |
|
No |
14,353 (27.9) |
|
Lifetime smoking experience |
Yes |
5,355 (10.2) |
|
No |
47,525 (89.8) |
|
Lifetime drinking experience |
Yes |
17,276 (32.6) |
|
No |
35,604 (67.4) |
|
Lifetime drug use |
Yes |
839 (1.7) |
|
No |
52,041 (98.3) |
|
Smartphone overdependence |
Normal group |
38,208 (72.0) |
|
Risk group |
14,672 (28.0) |
Table 2.Comparison of sexual intercourse and contraceptive use based on sample characteristics
|
Variable |
Sexual intercourse (n=52,880) |
Use of contraception (n=3,349) |
|
Yes (n=3,349) |
No (n=49,531) |
χ2 (p) |
Yes (n=2,182) |
No (n=1,167) |
χ2 (p) |
|
Sex |
|
|
92.27 (<.001) |
|
|
0.30 (.584) |
|
Male |
2,018 (62.2) |
24,751 (50.8) |
|
1,314 (61.8) |
704 (62.9) |
|
|
Female |
1,331 (37.8) |
24,780 (49.2) |
|
868 (38.2) |
463 (37.1) |
|
|
School type |
|
|
623.67 (<.001) |
|
|
87.53 (<.001) |
|
High school |
2,455 (75.6) |
22,024 (47.3) |
|
1,720 (80.9) |
735 (65.2) |
|
|
Middle school |
894 (24.4) |
27,507 (52.7) |
|
462 (19.1) |
432 (34.8) |
|
|
Perceived academic performancea)
|
|
|
72.47 (<.001) |
|
|
3.12 (.015) |
|
High |
371 (10.9) |
6,424 (13.1) |
|
223 (10.2) |
148 (12.4) |
|
|
Middle-high |
669 (19.8) |
12,577 (25.6) |
|
447 (19.6) |
222 (20.3) |
|
|
Middle |
878 (26.5) |
14,662 (29.6) |
|
587 (27.5) |
291 (24.2) |
|
|
Middle-low |
840 (25.1) |
11,537 (23.2) |
|
566 (26.2) |
274 (23.0) |
|
|
Low |
591 (17.7) |
4,326 (8.5) |
|
359 (16.5) |
232 (20.1) |
|
|
Perceived economic statusa)
|
|
|
82.59 (<.001) |
|
|
9.48 (<.001) |
|
High |
472 (14.4) |
5,812 (12.2) |
|
272 (13.0) |
200 (17.2) |
|
|
Middle-high |
885 (26.9) |
15,241 (31.4) |
|
612 (28.6) |
273 (23.7) |
|
|
Middle |
1,329 (39.4) |
22,652 (45.2) |
|
895 (40.6) |
434 (37.0) |
|
|
Middle-low |
469 (13.5) |
4,965 (9.6) |
|
308 (13.6) |
161 (13.2) |
|
|
Low |
194 (5.8) |
856 (1.6) |
|
95 (4.2) |
99 (8.9) |
|
|
Co-residence with family membersa)
|
|
|
241.18 (<.001) |
|
|
12.35 (<.001) |
|
Yes |
2,936 (89.2) |
47,426 (96.4) |
|
1,942 (90.8) |
994 (86.3) |
|
|
No |
412 (10.8) |
2,099 (3.6) |
|
240 (9.2) |
172 (13.7) |
|
|
Sex education experience |
|
|
78.66 (<.001) |
|
|
5.83 (.016) |
|
Yes |
2,193 (64.6) |
36,334 (72.6) |
|
1,465 (66.3) |
728 (61.4) |
|
|
No |
1,156 (35.4) |
13,197 (27.4) |
|
717 (33.7) |
439 (38.6) |
|
|
Lifetime smoking experience |
|
|
4,570.40 (<.001) |
|
|
4.86 (.028) |
|
Yes |
1,661 (49.3) |
3,694 (7.4) |
|
1,052 (47.8) |
609 (52.3) |
|
|
No |
1,688 (50.7) |
45,837 (92.6) |
|
1,130 (52.2) |
558 (47.7) |
|
|
Lifetime drinking experience |
|
|
1,860.64 (<.001) |
|
|
9.91 (.002) |
|
Yes |
2,445 (72.5) |
14,831 (29.8) |
|
1,639 (74.5) |
806 (68.7) |
|
|
No |
904 (27.5) |
34,700 (70.2) |
|
543 (25.5) |
361 (31.3) |
|
|
Lifetime drug use |
|
|
573.92 (<.001) |
|
|
14.86 (<.001) |
|
Yes |
251 (7.3) |
588 (1.3) |
|
130 (5.9) |
121 (10.1) |
|
|
No |
3,098 (92.7) |
48,943 (98.7) |
|
2,052 (94.1) |
1,046 (89.9) |
|
|
Smartphone overdependence |
|
|
8.04 (.005) |
|
|
12.03 (<.001) |
|
Normal group |
2,317 (69.5) |
35,891 (72.2) |
|
1,566 (71.6) |
751 (65.2) |
|
|
Risk group |
1,032 (30.5) |
13,640 (27.8) |
|
616 (28.4) |
416 (34.8) |
|
Table 3.Association between smartphone overdependence and sexual intercourse and contraceptive use among adolescents
|
Independent variable |
Category |
Dependent variable |
|
Sexual intercoursea) (n=52,880) |
Use of contraceptiona) (n=3,349) |
|
OR (95% CI) |
p
|
OR (95% CI) |
p
|
|
Smartphone overdependence |
Risk group (Ref: normal group) |
0.97 (0.87–1.07) |
.529 |
0.77 (0.65–0.92) |
.004 |
|
Sex |
Male (Ref: female) |
0.86 (0.78–0.94) |
.001 |
1.10 (0.93–1.30) |
.269 |
|
School type |
High school (Ref: middle school) |
0.42 (0.38–0.46) |
<.001 |
0.45 (0.38–0.54) |
<.001 |
|
Perceived academic performance |
(Ref: high) |
|
|
|
|
|
Middle-high |
0.87 (0.75–1.02) |
.082 |
0.92 (0.68–1.25) |
.599 |
|
Middle |
0.82 (0.70–0.96) |
.011 |
1.02 (0.75–1.38) |
.913 |
|
Middle-low |
0.88 (0.76–1.03) |
.120 |
1.04 (0.75–1.43) |
.818 |
|
Low |
1.14 (0.97–1.36) |
.119 |
0.88 (0.64–1.23) |
.456 |
|
Perceived economic status |
(Ref. high) |
|
|
|
|
|
Middle-high |
0.71 (0.62–0.83) |
<.001 |
1.40 (1.05–1.86) |
.021 |
|
Middle |
0.63 (0.55–0.72) |
<.001 |
1.20 (0.93–1.56) |
.170 |
|
Middle-low |
0.81 (0.68–0.96) |
.015 |
1.17 (0.85–1.60) |
.346 |
|
Low |
1.29 (1.00–1.66) |
.049 |
0.64 (0.44–0.94) |
.022 |
|
Co-residence with family members |
No (Ref: yes) |
0.60 (0.51–0.71) |
<.001 |
1.34 (1.03–1.74) |
.032 |
|
Sex education experience |
No (Ref: yes) |
0.97 (0.89–1.06) |
.491 |
1.30 (1.09–1.55) |
.004 |
|
Lifetime smoking experience |
Yes (Ref: no) |
0.18 (0.16–0.19) |
<.001 |
1.30 (1.09–1.56) |
.004 |
|
Lifetime drinking experience |
Yes (Ref: no) |
0.37 (0.33–0.41) |
<.001 |
0.74 (0.60–0.94) |
.004 |
|
Lifetime drug use |
Yes (Ref: no) |
0.40 (0.32–0.50) |
<.001 |
1.25 (0.90–1.72) |
.181 |
|
Wald χ2
|
|
3653.42 |
|
137.54 |
|
|
df (p) |
|
15.31 (<.001) |
|
15.26 (<.001) |
|
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