Abstract
Environmental endocrine disruptors (EDCs) are chemicals that disrupt the endocrine system and pose significant health risks. Perceived sensitivity to illness refers to the heightened susceptibility of an individual due to genetic or environmental factors. This study aims to examine how the awareness of women on EDCs influences their motivation to adopt health behaviors, focusing on the mediating role of perceived illness sensitivity. From October to November 2024, we conducted a cross-sectional survey of 200 adult women in Seoul and Gyeonggi Province, South Korea. Participants were recruited from community-based institutions and completed an online questionnaire assessing their EDCs knowledge, perceived illness sensitivity, and motivation for health behaviors. Data were analyzed using descriptive statistics, parametric tests (t-test, ANOVA) for normally distributed variables, and nonparametric tests (Mann–Whitney U, Kruskal–Wallis) for non-normally distributed variables. Pearson correlations and mediation analysis were also performed. The average knowledge score on EDCs was 65.9 (SD = 20.7). Perceived illness sensitivity averaged 49.5 (SD = 7.4), and health behavior motivation was 45.2 (SD = 7.5). Significant differences in EDCs knowledge, perceived illness sensitivity, and health behavior motivation were observed based on age, marital status, education level, and menopausal status. EDCs knowledge positively correlated with perceived illness sensitivity and motivation. Perceived illness sensitivity was also positively linked to motivation. Mediation analysis revealed that perceived sensitivity partially mediated the relationship between EDCs knowledge and motivation. These findings suggest that knowledge alone may not be sufficient to promote behavior change; cognitive and emotional awareness of illness risk plays a key mediating role. Therefore, effective interventions should combine education with strategies to enhance perceived illness sensitivity.
Keywords: environmental endocrine disruptors, health behaviors, knowledge, women
1. Introduction
Researchers widely recognize the potential health risks of environmental endocrine-disrupting chemicals (EDCs) – including bisphenol A, phthalates, and polychlorinated biphenyls – particularly in women, whose hormonal regulation is closely linked to environmental factors.[1] Studies report that EDCs is associated with increased incidences of diseases such as breast cancer, reproductive disorders, metabolic syndromes, and neurodegenerative diseases, including Alzheimer and Parkinson.[1,2] EDCs are widespread in the environment and disrupt endocrine homeostasis by interfering with essential hormonal processes, including synthesis, secretion, transport, metabolism, and elimination.[3,4] Compared to acute exposure, these adverse health outcomes typically result from chronic accumulation of EDCs in the body.[5] This gradual, often invisible exposure may lead individuals to underestimate the risks associated with EDCs.
Despite growing evidence of EDCs-related health risks, public awareness of these chemicals remains limited. Many individuals – particularly women – are unaware of EDCs or their links to health conditions such as cancer, infertility, and developmental disorders.[6,7] Some participants had never heard of specific EDCs. This lack of knowledge may hinder the adoption of preventive health behaviors, despite rising societal concern about environmental exposures.[8] Preventative measures that people can adopt to reduce their exposure to EDCs include avoiding plastic containers with recycling codes 3 or 7, limiting the use of canned foods, choosing fragrance-free personal care products, and avoiding the use of nonstick or plastic cookware.[9]
Additionally, challenges remain in identifying EDCs types, assessing disease risk, and measuring individual exposure levels. Few studies have examined public understanding of EDCs, and existing evidence consistently shows inadequate knowledge and awareness.[10] Given the significant health risks EDCs pose, especially to women, and the gap in public understanding, investigating how knowledge of EDCs influences health-related behaviors is crucial. Furthermore, individual sensitivity or perceived vulnerability to EDCs-related illness may mediate this relationship. Based on findings from prior studies, the conceptual framework in Figure 1 outlines the relationships explored in this study. Specifically, this study explores how the knowledge of women about EDCs influences their motivation to engage in preventive health behaviors, with a particular focus on the mediating role of perceived sensitivity to an illness.
Figure 1.
Conceptual framework of the study. EDCs = endocrine-disrupting chemicals.
This study aims to: investigate the knowledge of women on EDCs, their perceived sensitivity to EDCs-related illness, and motivation for engaging in EDCs-related health behaviors; examine knowledge, perceived illness sensitivity, and health behavior motivation related to EDCs across demographic characteristics; and analyze the direct effect of EDCs knowledge on motivation, as well as its total effect mediated through perceived illness sensitivity. By identifying these relationships, the findings of this study could contribute to the development of more effective educational and behavioral interventions to reduce EDCs exposure risks.
2. Materials and methods
2.1. Study design
We conducted a cross-sectional survey among women in South Korea from October to November 2024 to perform mediation analysis.
2.2. Participants
The target population included adult women aged ≥ 19 residing in Seoul and Gyeonggi Province. These regions were chosen due to their high concentration of women, urbanization, and educational diversity. Seoul and Gyeonggi, both economically and culturally interconnected metropolitan areas, represent a broad demographic of Korean adult women. The study focused on urban women with likely access to health information on EDCs, limiting the survey to the Seoul Metropolitan Area. As of 2025, the total population of South Korea is approximately 51.71 million, with Seoul and Gyeonggi accounting for about 10.4 million and 14.18 million individuals, respectively – approximately 20.1% and 27.4% of the national population.[11,12] The female population in both regions comprises nearly half of their total populations, with a relatively balanced sex distribution. Based on these demographic characteristics, this study collected data from women residing in Seoul and Gyeonggi Province, where population density is high and women are well-represented.
During data collection, participants were invited to complete an online survey. Inclusion criteria included women aged ≥ 19, capable of communication, and able to complete a self-reported questionnaire. The sample size was calculated using G*Power 3.1. For regression analysis (α = 0.05, power = 90%, effect size f = 0.15, and 20 predictors), the minimum required sample was 191. Accounting for a 5% dropout rate, the target sample size was 201 participants. In total, 200 participants completed the survey, ensuring a balanced age distribution.
2.3. Data collection
Participants were recruited from churches, cultural centers, religious organizations, and universities to ensure diverse representation of women across various age groups, educational levels, and social backgrounds. Churches and religious organizations were chosen for their high proportion of female members, regular participation in community activities, and strong representation of middle-aged and older women. Cultural centers were included for their wide range of programs targeted at women, which often attract those with a proactive interest in health and environmental issues. Universities provided access to younger, highly educated women, making them particularly suitable for surveys on environmental health awareness. Additionally, university students tend to have a strong understanding of research participation and provide reliable questionnaire responses.
These community-based and educational settings provided opportunities to engage women with varying levels of health awareness and offered environments conducive to informed, voluntary participation. Such venues typically attract women who are actively involved in community life, education, and personal development, making them suitable recruitment channels for investigating knowledge, perceptions, and health behaviors related to environmental health issues.
The researcher explained the purpose and methodology of the study to participants and gave them detailed information about privacy protections and estimated survey completion time before obtaining their voluntary consent. Written informed consent was initially obtained through face-to-face interaction with potential participants. Only those who agreed to participate were then provided with a link to the survey, which was created using Google Forms to digitize each questionnaire. The survey took approximately 15 minutes to complete.
2.4. Ethical consideration
This study, which involved a general population survey, was exempted from the Institutional Review Board (IRB) approval. Exemption approval (Waiver No. 2024-054) was obtained before recruiting participants. The study protocol followed the principles outlined in the Declaration of Helsinki (1964, revised in 2024). The online survey did not collect any personally identifiable information, and all collected data were used solely for research purposes. Participants had the right to withdraw at any time. As a token of appreciation for their participation, a small incentive was provided.
2.5. Measurement tools
2.5.1. Knowledge of EDCs
This study assessed knowledge of EDCs by adapting a tool developed by Kim and Kim,[13] modifying it to focus on food, can, and plastic containers, as well as related substances and associated diseases. The tool comprised 33 items, each with “Yes,” “No,” or “I don’t know” responses. Correct answers received 100 points, while incorrect answers and “I don’t know” responses received zero points. The correct response rate was then calculated, with a higher score indicating greater knowledge.
Example items included statements such as “Endocrine disruptors interfere with and disturb hormone function in organisms” and “Endocrine disruptors can decrease human sperm count,” among others. The questions also addressed topics such as types of endocrine disruptors and sources of related information. In this study, Cronbach α was 0.94, indicating excellent internal consistency and high reliability.
2.5.2. Motivation for health behaviors related to EDCs
We adapted the motivation measure from Kim et al[14] to assess the motivation of participants for health behaviors related to EDCs. In this study, motivation refers to the driving force behind actions that reduce EDCs exposure. These behaviors support personal health and promote similar actions in others.
The study defines motivation as comprising 2 components: personal motivation, which reflects the intention of an individual to reduce EDCs exposure, and social motivation, which represents the social support encouraging such behaviors. To identify the underlying factors driving individuals to adopt EDCs-reducing health behaviors, the researchers used a motivation scale specifically developed for this purpose.
The instrument included 8 items, divided into 2 subfactors: 4 items assessing personal motivation, and another 4 assessing social motivation. Participants rated each item on a 7-point Likert scale (1 = Not at all true to 7 = Very true), with a score range of 8 to 56 points. Higher scores indicated stronger motivation to engage in EDCs-related health behaviors. Kim et al[14] report a reliability of Cronbach α = .91 at development. In the present study, the reliability was α = .93, indicating high internal consistency.
2.5.3. Perceived sensitivity to EDCs-related to illness
In this study, we defined perceived sensitivity to EDCs-related illness as the extent to which individuals recognize the potential health risks of EDCs and perceive susceptibility to those risks. We measured this by adapting the perceived sensitivity scale for lifestyle-related diseases developed by Lee et al[15] to align with the objectives of our study. The final instrument included 13 items, rated on a 5-point scale (1 = Not at all true to 5 = Very true). Higher scores indicate greater perceived sensitivity to EDCs-related illness. The original scale had a Cronbach α = .77,[12] while in our study, the reliability improved to α = .91, indicating strong internal consistency.
2.6. Statistical analysis
We analyzed how knowledge of EDCs influences motivation to engage in health behaviors related to EDCs exposure. Using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp., Armonk), we conducted descriptive statistics to analyze general characteristics and variable distributions. Prior to group comparisons, continuous variables were tested for normality using the Shapiro–Wilk test. Variables meeting the normality assumption were analyzed with independent sample t-tests (two groups) or one-way ANOVA (3 or more groups), followed by Scheffé post hoc test for multiple comparisons. For non-normally distributed variables (P < .05), we applied nonparametric methods, including the Mann–Whitney U and Kruskal–Wallis tests, and reported data as median (interquartile range, IQR) instead of mean ± SD. For correlation analysis, Spearman rank correlation coefficients was calculated.
To investigate whether perceived sensitivity to EDCs-related illness mediates the relationship between EDCs knowledge and health behavior motivation, we utilized the SPSS PROCESS macro (Model 4) developed by Hayes.[16] Mediation was tested with a bootstrap method using 5000 resamples to generate confidence intervals. In the PROCESS analysis, age, marital status, education level, and menopausal status were included as covariates to control for potential confounders. All statistical tests were 2-tailed, with significance set at P < .05.
3. Results
3.1. General characteristics and differences in knowledge, perceived sensitivity to illness, and health behavior motivation concerning EDCs
Table 1 summarizes the general characteristics of participants and variations in key research variables. The mean and median ages were 45.6 years (SD = 15.4) and 45.0 years, respectively. Age was evenly distributed across 5 groups (20s, 30s, 40s, 50s, and ≥ 65 years), with 40 participants in each group (20% of the total sample). Over half (54%) were married. Additionally, 50.5% were nondrinkers, 90.0% were nonsmokers, and 66.5% exercised regularly. Educationally, 70.5% had a college degree or higher. Moreover, 33.5% reported chronic diseases, and 39.5% were postmenopausal. Regarding perceived economic status, 63.0% selected the “middle” category.
Table 1.
Participant characteristics and differences in knowledge, perceived sensitivity to an illness, and health behavior motivation related to endocrine-disrupting chemicals (N = 200).
| n (%) | Knowledge of EDCs Median (IQR) |
Perceived sensitivity to EDCs-related illness Median (IQR) |
Motivation for health behaviors related to EDCs mean (SD) |
|
|---|---|---|---|---|
| Age group, M (SD) | 45.6 (15.4) | |||
| Median age | 45.0 | |||
| 19–29 | 40 (20.0) | 60.6 (34.85) | 44.0 (10.00) | 44.7 (7.4) |
| 30–39 | 40 (20.0) | 63.6 (34.85) | 42.0 (10.75) | 42.0 (7.3) |
| 40–49 | 40 (20.0) | 69.6 (17.42) | 46.5 (8.75) | 45.1 (7.6) |
| 50–64 | 40 (20.0) | 71.2 (21.21) | 47.0 (6.75) | 46.2 (8.5) |
| ≥65 | 40 (20.0) | 75.7 (22.73) | 48.5 (8.75) | 48.3 (5.6) |
| H (P)/F (P) Scheffé | 16.79 (.002) | 17.58 (.001) | 4.0 (.004) b < e |
|
| Marital status | ||||
| Single | 76 (38.0) | 63.6 (28.79) | 43.5 (11.75) | 43.22 (7.2) |
| Married | 108 (54.0) | 72.7 (21.21) | 48.0 (8.75) | 46.37 (7.8) |
| Divorced or widowed | 16 (8.0) | 72.7 (20.45) | 46.0 (9.00) | 47.18 (5.5) |
| H (P)/F (P) Scheffé | 14.94 (.001) | 12.34 (.002) | 4.62 (.011) a < b |
|
| Alcohol consumption | ||||
| Yes | 99 (49.5) | 66.6 (24.24) | 45.0 (10.00) | 44.46 (7.5) |
| No | 101 (50.5) | 69.6 (21.21) | 47.0 (9.00) | 46.00 (7.6) |
| Z (P) / t (P) | −1.35 (.176) | −1.71 (.087) | −1.44 (.151) | |
| Smoking | ||||
| Yes | 20 (10.0) | 62.1 (31.82) | 44.0 (10.00) | 43.95 (7.8) |
| No | 180 (90.0) | 69.6 (21.21) | 47.0 (9.00) | 45.38 (7.5) |
| Z (P) / t (P) | −1.22 (.221) | −0.88 (.375) | −0.81 (.422) | |
| Regular exercise | ||||
| Yes | 133 (66.5) | 69.6 (24.24) | 47.0 (10.50) | 45.60 (7.6) |
| No | 67 (33.5) | 69.6 (21.21) | 45.0 (9.00) | 44.50 (7.4) |
| Z (P) / t (P) | −0.17 (.862) | −1.10 (.269) | 0.97 (.331) | |
| Education level | ||||
| ≤ High school | 59 (29.5) | 63.6 (21.21) | 45.0 (10.00) | 44.47 (7.4) |
| ≥ College | 141 (70.5) | 69.6 (22.73) | 47.0 (9.00) | 45.56 (7.6) |
| Z (P) / t (P) | −3.19 (.002) | −1.053 (.029) | −0.93 (.355) | |
| Economic status | ||||
| High | 6 (3.0) | 77.2 (39.39) | 47.5 (6.25) | 48.00 (4.5) |
| Middle | 126 (63.0) | 69.6 (28.03) | 46.0 (11.00) | 45.25 (8.1) |
| Low | 68 (34.0) | 66.6 (15.15) | 46.0 (9.00) | 44.97 (6.7) |
| H (P) / F (P) Scheffé | 2.32 (.313) | 0.94 (.623) | 0.44 (.643) | |
| Chronic disease status | ||||
| Yes | 67 (33.5) | 69.6 (24.24) | 47.0 (9.00) | 45.88 (8.2) |
| No | 133 (66.5) | 69.6 (21.21) | 46.0 (10.50) | 44.91 (7.2) |
| Z (P) / t (P) | −0.63 (.523) | −1.29 (.195) | 0.85 (.395) | |
| Menopause | ||||
| Yes | 79 (39.5) | 72.7 (21.21) | 48.0 (8.00) | 46.58 (7.7) |
| No | 121 (60.5) | 63.6 (27.27) | 45.0 (11.50) | 44.36 (7.4) |
| Z (P) / t (P) | −3.55 (<.001) | −2.54 (.012) | 2.05 (.042) | |
Note. SD, standard deviation; EDCs, endocrine-disrupting chemicals; IQR, Interquartile Range. Continuous variables were tested for normality using the Shapiro–Wilk test. Parametric tests (t-test, ANOVA) were used for normally distributed variables, while nonparametric tests (Mann–Whitney U, Kruskal–Wallis) were applied for non-normally distributed variables. Knowledge of EDCs and perceived sensitivity to EDC-related illness were analyzed using nonparametric tests. t = independent samples t-test; F = one-way ANOVA; H = Kruskal–Wallis test statistic; Z = Mann–Whitney U test statistic.
Significant differences in the median (IQR) knowledge scores of EDCs were observed across age groups (H = 16.79, P = .002), with the highest in participants aged ≥ 65 years (75.7 [22.73]) and the lowest in those aged 19 to 29 years (60.6 [34.85]). Perceived sensitivity also differed significantly by age (H = 17.58, P = .001), with participants ≥ 65 years scoring higher (48.5 [8.75]) than those aged 30 to 39 years (42.0 [10.75]). Motivation for EDCs-related health behaviors differed based on age (F = 4.0, P = .004), with the ≥ 65 group scoring higher than the 30 to 39 group.
For marital status, knowledge differed significantly (H = 14.94, P = .001), with married (72.7 [21.21]) and divorced/widowed participants scoring higher (72.7 [20.45]) than single participants (63.6 [28.79]). Perceived sensitivity varied significantly (H = 12.34, P = .002), with married participants scoring higher (48.0 [8.75]) than single participants (43.5 [11.75]). Motivation for EDCs-related health behaviors also differed (F = 4.62, P = .011), with married participants scoring higher than single participants.
Participants with a college education or higher had significantly greater knowledge of EDCs (Z = −3.19, P = .002) and perceived sensitivity (Z = −1.05, P = .029) than those with a high school education or less. Menopausal status was also significant: postmenopausal participants scored higher than premenopausal participants in knowledge (Z = −3.55, P < .001), perceived sensitivity (Z = −2.54, P = .012), and motivation for EDCs-related health behaviors (t = 2.05, P = .042).
3.2. Levels of knowledge, perceived sensitivity to illness, and health behavior motivation regarding EDCs
Table 2 shows the means and SDs for knowledge of EDCs, perceived sensitivity to EDCs-related illnesses, and motivation for EDCs-related health behaviors. Mean scores were 65.9 (SD = 20.7) for knowledge, 49.5 (SD = 7.4) for perceived sensitivity, and 45.2 (SD = 7.5) for motivation.
Table 2.
Level of knowledge, perceived illness sensitivity, and health behavior motivation related to endocrine-disrupting chemicals (N = 200).
| Variable | Min–Max | Mean (SD) |
|---|---|---|
| Knowledge of EDCs | 3.0–97.0 | 65.9 (20.7) |
| Perceived sensitivity to EDCs-related illness | 31–65 | 49.5 (7.4) |
| Motivation for health behaviors related to EDCs | 8–56 | 45.2 (7.5) |
EDCs = endocrine-disrupting chemicals, SD = standard deviation.
3.3. Correlation among variables
Correlations among knowledge of EDCs, perceived sensitivity to EDCs-related illness, and motivation for EDCs-related health behaviors were examined. Knowledge of EDCs was significantly and positively correlated with perceived sensitivity to EDCs-related illness (ρ = .48, P < .001) and with motivation for health behaviors (ρ = .39, P < .001). Perceived sensitivity also exhibited a significant positive correlation with motivation (ρ = .42, P < .001).
3.4. Mediating effect of sensitivity to endocrine-disrupting chemical-related diseases on the link between knowledge and health behavior motivation
The mediation model tested whether perceived sensitivity to EDCs-related illness mediates the relationship between knowledge of EDCs and motivation to engage in EDCs-related health behaviors (Table 3, Fig. 2). Knowledge of EDCs had a significant total effect on motivation (β = 0.16, SE = 0.025, t = 5.66, P < .001, 95% bias-corrected [BC] confidence interval [CI]:0.095, 0.196), indicating that greater knowledge was associated with stronger motivation to adopt preventive health behaviors.
Table 3.
Total, direct, and indirect effects of the mediator model (N = 200).
| Model | Effect | SE | t | P | 95% BC CI |
|---|---|---|---|---|---|
| Total effect of Knowledge of EDCs→ Motivation to engage in EDCs-related health behaviors | 0.16 | 0.025 | 5.66 | <.001 | [0.095, 0.196] |
| Direct effect of Knowledge of EDCs→ Motivation to engage in EDCs-related health behaviors | 0.06 | 0.029 | 2.26 | 0.024 | [0.008, 0.123] |
| Indirect effect via perceived sensitivity to EDCs-related illness | 0.07 | 0.018 | [0.044, 0.114] |
BC = bias-corrected, CI = confidence interval, EDCs = endocrine-disrupting chemicals, SE = standard error.
Figure 2.
Results of the multiple mediation model. EDCs = endocrine-disrupting chemicals.
When perceived sensitivity to EDCs-related illness was included as a mediator, the direct effect of knowledge on motivation remained significant but decreased (β = 0.06, SE = 0.029, t = 2.26, P = .024, 95% BC CI: 0.008, 0.123). The indirect effect of knowledge on motivation through perceived sensitivity was statistically significant (β = 0.07, SE = 0.018, 95% BC CI: 0.044, 0.114), confirming partial mediation.
Figure 2 supports these results: knowledge significantly predicted perceived sensitivity (B = 0.21, P < .001), which in turn significantly predicted motivation (B = 0.37, P < .001). The direct path from knowledge to motivation also remained significant, though reduced (B = 0.06, P = .024), consistent with partial mediation (Table 3). The model explained 33% of the variance in perceived sensitivity (R2 =.33) and 28% in motivation (R2 =.28).
4. Discussion
This study examined how knowledge of EDCs influences motivation to adopt protective health behaviors, focusing on the mediating role of perceived sensitivity to EDC-related illness. Individuals with greater knowledge of EDCs were more likely to adopt protective health behaviors. Furthermore, perceived sensitivity partially mediated this relationship, suggesting that knowledge directly influences health behaviors and indirectly promotes motivation by increasing awareness of health risks.
This partial mediation of perceived sensitivity to EDCs-related illness suggests that increased knowledge heightens awareness of associated health risks, thereby motivating protective action. However, the direct effect of knowledge on behavior highlights its independent role in promoting health-conscious decisions. These findings underscore the need to disseminate accurate information and increase public sensitivity to the health risks of EDCs exposure. Accordingly, guidelines issued by governments and international organizations, including the World Health Organization, the United Nations, the European Union, and regulatory agencies such as the U.S. Environmental Protection Agency,[17] should be clearly summarized and made widely accessible. These guidelines recommend reducing exposure to EDCs, especially among vulnerable groups such as infants and pregnant women, strengthening regulations and international testing standards, increasing research funding, and promoting public awareness and consumer protection.
We compared these results with findings from previous studies to contextualize each pathway. Consistent with reports from Boronow et al,[10] our findings show that knowledge of EDCs positively influences health behavior, as reducing misconceptions about chemical exposure promoted behavioral changes aimed at limiting exposure. Similarly, providing information about health effects, exposure sources, and personalized recommendations to reduce exposure to EDCs increases individual readiness to adopt protective behaviors.[18] Although few studies have directly examined the knowledge-behavior link for EDCs, research in other health contexts supports our results. For example, individuals with greater knowledge of cardiovascular disease,[19,20] human papillomavirus (HPV),[21] or the coronavirus disease 2019 (COVID-19) were more likely to engage in health-promoting behaviors.[22]
Our analysis revealed that perceived sensitivity to EDCs-related illness significantly predicted motivation, even after controlling for potential confounders. While limited research has explored this relationship in the context of EDCs, similar findings have emerged in other health domains. For instance, Rountree et al[23] report that women who perceived themselves as susceptible to cardiovascular disease were more likely to change their behavior. van der Snoek et al[24] also report that individuals with high perceived human immunodeficiency virus severity were more likely to adopt protective sexual behaviors. However, evidence on HPV vaccination and COVID-19 behaviors is mixed. Kabarambi et al[21] report that perceived barriers, susceptibility, and knowledge were not significant predictors of HPV vaccination, while Leonard et al[22] show that perceived COVID-19 susceptibility may influence motivation in some contexts but not others.
Our findings suggest that individuals who perceive themselves as highly susceptible, whether due to increased awareness of exposure risk or the belief that they are already at risk, are more likely to adopt protective behaviors. This finding highlights the role of perceived sensitivity as a behavioral driver.
While few studies have examined the relationship between knowledge of EDCs and EDC-related illness, related research provides insight. For instance, Boulware et al[25] report that women with lower health literacy perceived themselves as less susceptible to chronic kidney disease compared to men with higher health literacy. This suggests that knowledge may influence perceived sensitivity, warranting further research to determine whether a similar pattern exists for EDCs.
Our study showed that knowledge had a direct effect of 0.09 on behavior, but was insufficient to explain behavior change. Perceived sensitivity exerted a stronger influence on motivation, with a total effect of 0.16. Although few studies have directly examined the interplay between knowledge, perceived sensitivity, and motivation in EDCs-related health behaviors, research in related contexts supports these dynamics. For example, Yoon and Kim[26] report that university students with greater knowledge of EDCs engaged more in exposure-reducing behaviors, a relationship mediated by perceived benefits and barriers. Similarly, Van Osch et al[27] report that women with greater knowledge of cancer symptoms, through increased sensitivity, were more likely to seek timely medical help. Socio-cognitive models[28] identify perceived susceptibility as a key driver of health behavior. Our findings support this theory, suggesting that individuals who view themselves as more vulnerable to EDCs-related illness are more likely to adopt protective measures.
Our study showed that older and married women were more knowledgeable about EDCs. Although few studies have directly compared EDCs knowledge between married and unmarried women or between women with and without childcare experience, some evidence suggests that older and caregiving women are more aware of EDCs risks. For example, a French study reports that older women had significantly higher risk perception of EDCs.[29] Similarly, a study on mothers and caregivers shows that these groups are more sensitive to information about EDCs exposure due to health-related concerns for their children.[10] This may be because older individuals, with more life experiences, often show greater interest in health and environmental issues, while married women or those with children are more likely to encounter EDCs-related information through childcare, health, and household practices. They may also become more cautious about using products containing EDCs, such as plastics, food packaging, cosmetics, and cleaning agents, during pregnancy and parenting. In summary, our findings indicate that knowledge of EDCs influences health behaviors directly and indirectly through perceived sensitivity to an illness. These findings are consistent with those of prior studies, suggesting that knowledge promotes behavioral changes, susceptibility influences behavior, and knowledge affects susceptibility. Our study provides empirical evidence of the partial mediating role of perceived sensitivity in the link between knowledge and behavior, specifically in the context of EDCs exposure.
This study suggests that interventions promoting protective behaviors against EDCs exposure should go beyond simply providing information. While education campaigns remain important, they may be insufficient alone. To increase effectiveness, strategies should also enhance the sensitivity of individuals to EDCs-related health risks. Approaches such as personalized health messages, real-life case studies illustrating the consequences of EDCs exposure, and practical tips for reducing exposure in daily life may boost engagement and influence. Public health authorities and policymakers should likewise incorporate psychological and behavioral factors into their strategies to enhance campaign effectiveness.
Despite its contributions, this study has some limitations. First, while perceived sensitivity to illness was measured as a mediating variable, we did not differentiate between cognitive (e.g., logical risk assessment) and emotional (e.g., fear, concern) sensitivity. Therefore, clarifying this distinction could provide deeper insights into the mechanisms underlying behavior change. Second, the relationships between knowledge, perceived sensitivity, and health behaviors may vary across demographic groups, such as age cohorts or occupational categories (e.g., environmental professionals and healthcare workers). Subgroup analyses in future studies could clarify these variations. Finally, longitudinal designs are recommended to establish causal relationships and assess how changes in knowledge and perceived sensitivity influence behavior over time.
5. Conclusions
In conclusion, this study shows that knowledge of EDCs alone does not sufficiently drive behavior change, as indicated by its relatively small direct effect. In contrast, perceived sensitivity to EDCs-related illness is essential in shaping behavioral motivation. Awareness of EDCs-related health risks increases the perceived vulnerability of women, creating greater urgency to adopt preventive actions. Thus, heightened perceived sensitivity strengthens motivation to modify health-related behaviors.
These findings underscore the joint importance of knowledge and perceived sensitivity in promoting EDCs-related health behaviors and provide guidance for designing more effective educational and intervention programs that address informational gaps while incorporating psychological factors.
Author contributions
Conceptualization: Myung Kyung Lee, Jihyun Oh.
Data curation: Myung Kyung Lee, Jihyun Oh.
Formal analysis: Myung Kyung Lee, Jihyun Oh.
Funding acquisition: Jihyun Oh.
Investigation: Myung Kyung Lee, Jihyun Oh.
Methodology: Myung Kyung Lee, Jihyun Oh.
Project administration: Myung Kyung Lee, Jihyun Oh.
Resources: Myung Kyung Lee, Jihyun Oh.
Software: Myung Kyung Lee, Jihyun Oh.
Supervision: Myung Kyung Lee, Jihyun Oh.
Validation: Myung Kyung Lee, Jihyun Oh.
Visualization: Myung Kyung Lee, Jihyun Oh.
Writing – original draft: Myung Kyung Lee, Jihyun Oh.
Writing – review & editing: Myung Kyung Lee, Jihyun Oh.
Abbreviations:
- BC
- bias-corrected
- CI
- confidence interval
- COVID-19
- coronavirus disease 2019
- EDCs
- environmental endocrine disruptors
- HPV
- human papillomavirus
- IQR
- interquartile range
- SD
- standard deviation
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (Grant number RS-2023-00252730).
Informed consent was obtained from all subjects involved in the study.
The authors have no conflicts of interest to disclose.
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy restrictions.
This study was conducted in accordance with the principles of the Declaration of Helsinki. The study protocol was approved by the Institutional Review Board of the University (IRB No. 2024-054). Written informed consent was obtained from all participants prior to enrollment.
How to cite this article: Lee MK, Oh J. The influence of knowledge about endocrine-disrupting chemicals on motivation for health behaviors and the mediating role of perceived illness sensitivity: A cross-sectional analysis of women in South Korea. Medicine 2025;104:40(e44909).
References
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