You are currently viewing a new version of our website. To view the old version click .
MDPIMDPI
Search all articles
Environments
Download PDF
  • Editor’s Choice
  • Article
  • Open Access

25 April 2025

The Development and Reliability Testing of a Tool to Assess Women’s Perceptions and Avoidance of Endocrine Disruptors in Personal and Household Products

,
,
,
and
Department of Health Sciences, Ontario Tech University, Oshawa, ON L1G 0C5, Canada
*
Author to whom correspondence should be addressed.
Environments2025, 12(5), 138;https://doi.org/10.3390/environments12050138
This article belongs to the Special Issue Environmental Pollution Risk Assessment
Version Notes
Order Reprints

Abstract

Personal care and household products (PCHPs) often contain endocrine-disrupting chemicals (EDCs) that pose health risks, especially for women. Women, frequent users of PCHPs, are exposed to approximately 168 chemicals daily. However, there are gaps in understanding women’s knowledge, risk perceptions, and beliefs regarding these chemicals, as well as how these constructs influence their avoidance behavior. Existing questionnaires on EDCs in PCHPs lack reliability and comprehensiveness. Guided by the Health Belief Model, this study developed a self-administered questionnaire targeting four key constructs: knowledge, health risk perceptions, beliefs, and avoidance behaviors related to six EDCs commonly found in PCHPs (lead, parabens, Bisphenol A, phthalates, triclosan, and perchloroethylene). The questionnaire was distributed to 200 women at in-person events and online. The internal consistency of the constructs was tested using Cronbach’s alpha. The questionnaire included six items assessing knowledge, seven items on risk perceptions, five items on beliefs, and six items on avoidance behavior for each endocrine-disrupting chemical. Cronbach’s alpha values indicated strong reliability across all constructs. This newly developed questionnaire offers a reliable tool for assessing women’s knowledge, risk perceptions, beliefs, and behaviors toward EDCs in PCHPs. These findings could inform public health research and intervention strategies aimed at reducing women’s exposure to EDCs.

1. Introduction

Exposure to a range of endocrine-disrupting chemicals (EDCs) is an everyday reality for individuals, particularly, for women, through personal care and household products (PCHPs). Among these are six EDCs: lead, parabens, bisphenol A (BPA), phthalates, triclosan, and perchloroethylene (PERC), all of which can be encountered in daily routines [,,]. These chemicals are frequently added during manufacturing to extend the shelf-life of PCHPs, potentially increasing individual exposure []. In fact, 2016 and 2017 data from the Canadian Health Measures Survey (CHMS) revealed that over 81% of Canadians had detectable levels of BPA in their urine []. Furthermore, the cost of exposure to EDCs among the Canadian population amounted to CAD 24.6 billion (2010), which amounted to 1.25% of the Canadian GDP in 2010 [].
Research suggests that individuals typically use at least two personal care products per day, applying them approximately 11 times daily, amounting to up to 22 applications within 24 h [,]. Chemicals serve multiple roles within these products. For instance, parabens and phthalates act as plasticizers or solvents and fragrances in products, such as shampoo []. Additionally, lead is sometimes found in lip and eye products []. Household products, including disinfectants, multipurpose cleaners, and laundry detergents, are also common sources of EDC exposure given their frequent use []. Chemicals, such as PERC and BPA, are often found in household products, with PERC being prevalent in dry cleaning solutions and floor cleaners due to its efficacy in dissolving greases and oils [].
Women, in particular, are vulnerable to the adverse health effects of these chemicals [,]. EDCs, such as lead, parabens, BPA, phthalates, triclosan, and PERC, are recognized as reproductive toxicants, capable of crossing the placental barrier and posing potential risks to fetal development [,,,,]. Chronic exposure to these chemicals has been associated with adverse reproductive outcomes, including miscarriage, impaired fertility, fetal brain developmental toxicity, and, in some cases, intrauterine fetal death or distress [,,,,,,]. Studies indicate that EDC exposure during pregnancy may increase the risk of preeclampsia, gestational diabetes, excessive weight gain, and preterm birth [,,].
Despite the various negative health effects of EDCs, there are low levels of awareness of EDCs. To highlight, a recent study revealed a lack of awareness among women regarding the safety of their PCHPs, with approximately 80% uncertain about EDCs in their products and 48.6% expressing uncertainty about safety with daily product use []. In this context, a previous study explored pregnant women’s attitudes toward environmental toxicants, revealing that around 60% viewed these chemicals as health risks, with educated women being more likely to avoid such chemicals []. Additionally, it was found that while over half of pregnant respondents recognized the risks associated with cosmetics during pregnancy, only a minority intended to reduce their usage []. Women who read product labels tended to engage more in exposure-reducing behaviors; however, though 74% of reproductive-aged women recognized the health risks from chemicals like phthalates, only 29% adopted protective measures [,].
Despite a limited awareness of EDCs among women, research suggests women still purchase more ‘green’ products and prefer eco-labeled items compared to men []. However, eco-labels do not guarantee the absence of EDCs, as studies show these products may still contain undisclosed hazardous ingredients []. This introduces the concept of pseudo safety, which gives consumers a false sense of security over their PCHPs that they believe are safe. Thus, it is important for women to access tools that help identify EDCs in PCHPs, and engage in personal research as opposed to solely relying on “green” or “eco-friendly” product labels. There are resources that women can access for EDC-free PCHPs, which include the Environmental Working Group Guide to Healthy Cleaning and Personal Care Products [,]. Tools like the Yuka App, which scores products based on harmful ingredients (with 100 indicating safety), help women identify endocrine disruptors, allergens, and pollutants in PCHPs []. To our knowledge, these resources are supported by scientific literature, which makes them valid sources for women to access in order to identify EDC-free PCHPs. It is important for consumers to adopt a holistic approach to chemical exposures by considering the cumulative impact of all products they use daily, and purchasing all PCHPs that are EDC-free, as opposed to selecting only a few products.
A review of the literature on women’s attitudes toward EDCs in PCHPs reveals significant methodological limitations that may undermine the reliability and interpretability of findings. Many studies lack a theoretical framework in questionnaire design, which is essential for structuring items and ensuring rigorous interpretation []. Furthermore, the absence of reliability and internal consistency testing in prior tools raises concerns about the stability of the findings []. These gaps limit the validity of this research that could otherwise inform public health policies and interventions effectively.
In response to information gaps related to women’s knowledge and attitudes toward EDCs in PCHPs, as well as the apparent disconnect between awareness and the adoption of safer behaviors, this study focuses on developing a questionnaire to assess women’s knowledge, awareness, and attitudes concerning these chemicals and their associated health risks. Specifically, the study objectives are as follows: (i) develop a tool measuring knowledge, risk perceptions, beliefs, and avoidance behavior constructs related to key EDCs in PCHPs (i.e., lead, parabens, BPA, phthalates, triclosan, and PERC); (ii) conduct a pilot test of the tool; and (iii) assess internal reliability for each of the constructs.

2. Methods

2.1. Study Design

This study followed a two-phase approach to tool development. Grounded in the Health Belief Model (HBM), the first phase focused on designing and constructing the questionnaire, while the second phase assessed the internal consistency of its key constructs within a defined target population. The HBM framework (Figure 1) consists of six core components: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy [,], making it well-suited to explain behavior changes by assessing an individual’s perceived ability and motivation to adopt healthier practices [,]. For instance, if a woman perceives a heightened risk of breast cancer due to paraben exposure (health risk perception) and recognizes the serious health implications of breast cancer (knowledge), her concerns about the health risks of chemical-based PCHPs may increase. Furthermore, if she believes that opting for paraben-free products could lower her risk, she is likely to shift her purchasing behavior toward safer alternatives (avoidance behavior).
Figure 1. The Health Belief Model Framework [].

2.2. Development of the Questionnaire

The study questionnaire was developed through a comprehensive literature review to identify commonly studied EDCs in PCHPs, populations most vulnerable to their effects, and relevant survey items addressing knowledge, health risk perception, beliefs, and avoidance behaviors. The search was conducted in PubMed and Ovid Medline using terms, such as “personal care products”, “cleaning products”, “endocrine-disrupting chemicals”, “toxic chemicals”, “health attitudes”, and “perceptions”. Titles, keywords, and abstracts were screened to assess the relevance of each paper with inclusion criteria specifying scholarly, peer-reviewed articles written in English.
The survey began with a demographic section, followed by dedicated sections for each EDC. Within each section, items were either adapted or newly developed to measure participants’ knowledge, health risk behaviors, beliefs, and avoidance behaviors regarding each toxin. Items utilized a 6-point Likert scale (ranging from strongly agree to strongly disagree), except for avoidance behavior items, which used a 5-point scale (from Always to Never). To improve response accuracy, a neutral midpoint option was included to capture respondents’ indifference, and an ‘unsure’ option was added to discourage neutral responses when participants were unfamiliar with the content []. This structure aimed to ensure that participants’ responses reflected their knowledge, risk perceptions, beliefs, and avoidance behaviors regarding EDCs in PCHPs.

2.3. Questionnaire Piloting and Testing

Participants were selected based on the prevalence of PCHP usage and its implications for population health. This study focused on women aged 18 to 35, a range selected to capture the pre-conception and conception stages. According to Statistics Canada, most women in Ontario have their first child between the ages of 25 and 35, with an average age of 32 []. This age group was chosen due to its higher PCHP usage and the potential link to fetal exposure to EDCs during early development [,]. To determine the appropriate sample size, the authors reviewed other exploratory studies, which included sample sizes of 173 [], and 161 []. Following this precedent, the study set the target sample size at 200 participants. Ethical approval for this study was granted by the Ontario Tech University Ethics Committee [REB#16949]. Participants were recruited voluntarily and provided written informed consent after reviewing the study details, ensuring their understanding of the research procedures. All data collected were anonymized to protect participant confidentiality.
The final questionnaire was administered to participants via a Google Forms link. Data collection began at the 2022 National Women’s Show (18–19 November 2022) and continued with online recruitment via social media campaigns between December 2022 and January 2023. The final phase of participant recruitment took place on 9 February, 2023, at Ontario Tech University in Oshawa, Canada. Participants received a CAD 5 gift certificate as an incentive for their participation. In total, the study questionnaire was pilot-tested on 200 women.

2.4. Data Analysis

Data analysis was conducted using SPSS v.28. Prior to analysis, the dataset was cleaned and coded. Variables were categorized as follows. Age was dichotomized into two categories: “early adulthood” (18–35 years) and “later adulthood” (26–35 years), consistent with the Iowa State University’s definition of adulthood []. Annual household income was classified according to the Canadian Low-Income Cut-Off (LICO) thresholds, adjusted for household size and pre-tax income within Census Metropolitan Areas []. Educational attainment was dichotomized into individuals who had completed post-secondary education and those who had not, reflecting the substantial representation of participants with secondary education within the sample. The reproductive stage was determined by participants’ responses to questions regarding pregnancy status, attempts to conceive, breastfeeding, or having a child under 18 years of age. Participants meeting any of these criteria were categorized as being in a reproductive stage, whereas those who did not were classified as not in a reproductive stage.
Mean imputation was applied to replace ‘unsure’ responses, rather than scoring them as zero [], based on observed response patterns. This approach was chosen because participants with differing knowledge, health risk perceptions, and beliefs could produce similar final scores despite varying ‘unsure’ answers.
Indices for the knowledge, health risk perceptions, beliefs, and avoidance behavior scales were calculated by summing the scores of related items. Composite scores were created to provide a more comprehensive representation of these less concrete constructs []. A higher total score indicated a greater understanding or stronger health risk perceptions, beliefs, and avoidance behaviors regarding EDCs in PCHPs. To summarize respondent scores, descriptive statistics, such as mean, standard deviation, and median, were calculated.
The reliability of the questionnaire was assessed using Cronbach’s Alpha Test of Internal Consistency for the final participant scores []. Acceptable values of alpha range from 0.70 to 1.0, and these values were used to evaluate the consistency of participants’ responses across the measured constructs [].

3. Results and Discussion

3.1. Literature Review

The literature review revealed that the most frequently studied EDCs in PCHPs are lead, parabens, BPA, phthalates, triclosan, and PERC [,,,]. Women, particularly those of a reproductive age, were identified as the population most susceptible to the adverse health effects of these chemicals [,]. Questionnaires were the primary tool utilized to assess knowledge [,], health risk perceptions/attitudes [,,], beliefs [], and behaviors [,,,] regarding EDC exposure in PCHPs, whereas one study included both semi-structured interviews and questionnaires to assess health risk perceptions of pregnant women towards chemicals in consumer products [].

3.2. Questionnaire Development

The final questionnaire consisted of 37 items divided into 42 sections. The first section collected demographic data, such as age, ethnicity, education, household income, chemical sensitivity diagnosis, and reproductive stages. The following sections of the questionnaire assessed participants’ knowledge, health risk perceptions, beliefs, and avoidance behavior regarding EDCs in PCHPs.
Items adopted from previous literature are displayed in Table 1, while a complete list of questionnaire items is listed in Table 2. Beliefs were measured using five items that assessed subjective beliefs concerning the potential health impacts of each EDC. Seven items were included to measure health risk perceptions. Each item aimed to assess the extent to which participants perceived that exposure to specific EDCs could negatively impact health. Six items were included to measure knowledge regarding access to current resources, whether the participant had sufficient information on product safety, and the likelihood of expressing interest in more information on product safety and risk exposure. Avoidance behavior was assessed using six items on participants’ purchasing behavior, specifically the avoidance of EDCs in their PCHPs. Indices for the knowledge, health risk perceptions, beliefs, and avoidance behavior scales ranged from 6 to 30 for knowledge, 7 to 35 for health risk perceptions, 5 to 25 for beliefs, and 6 to 30 for avoidance behavior.
Table 1. Extracted items from existing literature on EDCs in PCHPs.
Table 2. A complete list of items and respective constructs used in the development of the study questionnaire.

3.3. Pilot Sample Characteristics

Overall, 114 (57%) participants were aged 18–25, and approximately 84 (42%) identifying as white (Table 3). Regarding socioeconomic status, 131 participants (65%) were above the LICO, and 133 individuals (66%) held post-secondary degrees or higher qualifications. The majority of respondents (79%) were born in Canada, and 156 (78%) resided in the Greater Toronto Area. Additionally, 20 participants (10%) reported diagnosed chemical sensitivities. A small subset (3%) of the sample were pregnant, and nine women (5%) were attempting pregnancy. Lastly, 26 women (13%) had a child under the age of 18 years old. Since there were multiple recruitment sites, statistical testing was done to identify any differences between the samples, however not enough of a difference was detected. Thus, all sites were combined into one sample.
Table 3. Sociodemographic characteristics of study sample (n = 200).
The respondents were of high economic status, considering the high frequency of higher educational attainment and participants above the LICO. Overall, 66% of participants indicated that they have completed higher education. This result aligns with the population of Ontario, where nearly 66% of the adult population (ages 25–64 years) has completed some form of post-secondary education in 2016 []. Thus, the sample may be considered representative of the general population of Ontario based on educational level. It is worth noting that socioeconomic status can have an impact on EDC awareness, as a previous study in Turkey found that women with lower education and income levels had lower EDC awareness []. Considering that socioeconomic status can have an impact on EDC exposure to certain populations, knowledge translation tools and targeted interventions should be focused on these groups in order to reduce exposure []. Additional statistical tests on this topic will be done in a separate manuscript [].
An interesting finding was regarding the number of respondents who self-reported a diagnosis of multiple chemical sensitivity (MCS). Approximately 10% of the study sample reported a diagnosis of MCS, which is higher than a recent study conducted at 1.6% []. This discrepancy may be attributed to the steady increase in reported cases of chemical sensitivities in Canada, as well as the growing recognition of MCS as a legitimate diagnosis []. Another factor could be that participants were asked if either they or a household member had been diagnosed with MCS, which may have led to higher reporting rates on behalf of household members. It is important to note that women are disproportionally affected by MCS, highlighting gendered exposure to chemicals and the continued importance of investigations in this domain [].

3.4. Calculating Respondent Scores

The results of the univariate analysis are presented in Table 4. Further information on the participant’s Likert-Scale responses for each construct can be found in the Supplementary Material. The developed constructs were indexed, using participants’ composite scores. Using descriptive statistics, the mean and median were used to capture overall scores for health risk perceptions, knowledge, beliefs, and avoidance behavior.
Table 4. Indices of knowledge, risk perceptions, beliefs, and avoidance behavior for each EDC (n = 200).
The analysis revealed that parabens consistently had the lowest health risk perception scores across all constructs, indicating limited awareness or concern among participants. Conversely, triclosan and PERC exhibited the highest scores across constructs, despite being among the least recognized chemicals within the study sample. This finding suggests that individuals with greater knowledge are informed about the toxicological effects of various EDCs or compounds and the transgenerational health defects associated with increased exposure to these chemicals, thereby, adopting proactive resource access and avoidance behaviors concerning EDCs in PCHPs. As mentioned previously, eco-product or “green” labeling can be misleading, sometimes containing hazardous ingredients, including EDCs. For instance, many consumers trust The International Fragrance Industry Association (IFRA) which claims their products are safe []. However, diethyl phthalate is not prohibited [], raising concerns about the safety of IFRA-regulated products, as research suggests minimizing cumulative phthalate exposure [,]. Thus, it is important for women to be guided towards accessing credible resources on avoiding EDC exposure from PCHPs.
In this study, 38% of women reported being aware of BPA, a significantly lower percentage compared to a previous study, where 93% of women had prior knowledge of the chemical []. Parabens, on the other hand, were among the most recognized chemicals, with 72% of women reporting awareness. This is substantially higher than previous findings, where only 24% of participants recognized parabens []. Despite significant media attention in the early 2010s, BPA recognition was relatively low in our study []. This discrepancy may be explained by the younger age of our sample (18–25 years), as they may have had less exposure to earlier public discussions on BPA. These results are in line with previous findings; for instance, a study done in Serbia indicated that mothers had low knowledge of EDCs, and as a result, 93.2% of participants wanted additional information about EDCs before pregnancy, highlighting a growing need for product safety resources and conversations []

3.5. Reliability Testing

We assessed the internal consistency for each construct for parabens, lead, phthalates, BPA, Triclosan, and PERC. The risk perception construct yielded alpha coefficients ranging from 0.87 to 0.93 across the six EDCs (Table 5). Beliefs demonstrated alpha coefficients ranging from 0.76 to 0.96. The knowledge construct exhibited alpha coefficients ranging from 0.77 to 0.93. Additionally, avoidance behavior showed alpha coefficients ranging from 0.93 to 0.98.
Table 5. Cronbach’s Alpha Test (α) for Internal Consistency for knowledge, risk perceptions, beliefs, and avoidance behavior (n = 200).
Cronbach’s alpha values for the developed scales ranged from 0.70 to 1.0 across the targeted chemicals, reflecting an acceptable level of internal consistency []. This suggests a strong coherence among the questionnaire items, affirming that each scale effectively measured the same underlying constructs—knowledge, health risk perceptions, beliefs, and avoidance behavior—across the range of EDCs assessed []. This consistency instills confidence in the questionnaire’s ability to yield reliable data across PCHP EDC exposures, supporting its use for examining perceptions and behaviors.
It is important to note that the alpha values were inconsistent across the scales, which may be due to a few possibilities. There may be a high degree of redundancy in the terms used for the items, which may explain the high alpha values for the avoidance behavior scale, versus other scales []. Beliefs displayed the lowest range of alpha values, which may be explained by the lower number of items in this construct, which is a factor known to decrease Cronbach’s alpha values []. Researchers have suggested utilizing scales with more than three items, particularly favoring ten-point, seven-point, and nine-point scales []. This preference may explain the higher level of consistency observed within the health risk perceptions scale, which consisted of seven items. Also, there was a degree of inconsistency across alpha values throughout the six EDCs, which in part may be due to the motivation for completing the questionnaire []. If participant motivation was low, it is plausible that they may not have given direct consideration to their responses, potentially leading to inconsistency.

4. Conclusions

The tool we developed to measure participants’ knowledge, health risk perceptions, beliefs, and avoidance behavior regarding EDCs in PCHPs holds significant potential for public health and policy disciplines for several reasons. Firstly, by better understanding women’s knowledge, perceptions, beliefs, and avoidance behavior with respect to endocrine-disrupting chemicals, targeted educational interventions can be developed to improve women’s knowledge and awareness regarding EDCs commonly found in their PCHPs. This is especially crucial for women of childbearing age. Empowering women with this information is important for enabling informed decision-making when selecting PCHPs, ultimately helping to reduce exposure to harmful chemicals. By minimizing EDC exposure, this tool has the potential to contribute to improved health outcomes for women.

Strengths and Limitations

A key limitation of this study is the reliance on Cronbach’s alpha as the sole measure of internal consistency, which, while informative, does not assess the stability of the questionnaire over time, or the potential of an increase in sample size. Additional psychometric evaluations, such as test–retest reliability and construct validity, were beyond this study’s scope but are recommended for future research []. Additionally, the use of mean imputation to address missing data, though practical given time constraints, may have reduced response variability [,]. Future studies should consider advanced methods, such as multiple imputation, to better preserve data variability. Furthermore, there were no comparisons with a control group (i.e., men of the same age group or older women). It is important to note that there are other sources of EDCs, such as materials and products (plastics, foods, etc.), as well as many other EDC compounds and non-EDC compounds, which were not addressed in this study []. Future research may benefit from including the strategy of using less products or using products less frequently to reduce EDC exposure as an aspect of the avoidance behavior construct. Lastly, future research may benefit from conducting a longitudinal study to better understand the issues presented in this study.
Despite these limitations, this study still adds to the lack of public health knowledge in the domain of women’s health perceptions and attitudes toward EDC exposure from PCHPs. The internal consistency of participant responses is a strength of this research, suggesting that the underlying constructs may have been measured accordingly. Our study addressed prior gaps in the literature concerning reliability testing and the use of a theoretical framework.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/environments12050138/s1. Participant Likert-Scale Responses and associated Study Questionnaire.

Author Contributions

Conceptualization, A.T., R.A.G. and C.B.; Methodology, A.T., J.A.-D., R.A.G. and C.B.; Formal analysis, A.T., N.K.R. and C.B.; Writing—original draft, A.T.; Writing—review & editing, N.K.R., J.A.-D. and C.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded using internal funds from the Faculty of Health Sciences, Ontario Tech University, Oshawa, Ontario (Grant Number #16949). The authors have no relevant financial or non-financial interests to disclose. All participants volunteered to be a part of this study, and consent was obtained prior to completion of research materials. We would like to acknowledge all study participants for their contributions to this study.

Institutional Review Board Statement

Ethical approval for this study was granted by the Ontario Tech University Ethics Committee [REB#16949].

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, [Adrianna Trifunovski], upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
Endocrine-Disrupting Chemicals (EDCs)Endocrine-disrupting chemicals (EDCs) are natural or human-made chemicals that may mimic, block, or interfere with the body’s hormones

References

  1. Khalid, M.; Abdollahi, M. Environmental Distribution of Personal Care Products and Their Effects on Human Health. Iran. J. Pharm. Res. 2021, 20, e124466. [Google Scholar] [CrossRef]
  2. Martín-Pozo, L.; Gómez-Regalado, M.; Moscoso-Ruiz, I.; Zafra-Gómez, A. Analytical methods for the determination of endocrine disrupting chemicals in cosmetics And personal care products: A review. Talanta 2021, 234, 122642. [Google Scholar] [CrossRef] [PubMed]
  3. Klančič, V.; Gobec, M.; Jakopin, Ž. Halogenated ingredients of household and personal care products as emerging endocrine disruptors. Chemosphere 2022, 303, 134824. [Google Scholar] [CrossRef] [PubMed]
  4. Malits, J.; Naidu, M.; Trasande, L. Exposure to endocrine disrupting chemicals in canada: Population-based estimates of disease burden and economic costs. Toxics 2022, 10, 146. [Google Scholar] [CrossRef]
  5. Lang, C.; Fisher, M.; Neisa, A.; MacKinnon, L.; Kuchta, S.; MacPherson, S.; Probert, A.; Arbuckle, T. Personal care product use in pregnancy and the postpartum period: Implications for exposure assessment. Int. J. Environ. Res. Public. Health 2016, 13, 105. [Google Scholar] [CrossRef]
  6. Land, K.L.; Ghuneim, S.M.; Williams, B.A.; Hannon, P.R. IMPACT OF REAL-LIFE ENVIRONMENTAL EXPOSURES ON REPRODUCTION: Phthalates disrupt female reproductive health: A call for enhanced investigation into mixtures. Reproduction 2025, 169, e240117. [Google Scholar] [CrossRef]
  7. Al-Saleh, I.; Al-Enazi, S.; Shinwari, N. Assessment of lead in cosmetic products. Regul. Toxicol. Pharmacol. 2009, 54, 105–113. [Google Scholar] [CrossRef]
  8. Garcia-Hidalgo, E.; von Goetz, N.; Siegrist, M.; Hungerbühler, K. Use-patterns of personal care and household cleaning products in switzerland. Food Chem. Toxicol. 2017, 99, 24–39. [Google Scholar] [CrossRef]
  9. ChemicalSafety Facts. Perchloroethylene—Chemical Safety Facts. 2024. Available online: https://www.chemicalsafetyfacts.org/chemicals/perchloroethylene/ (accessed on 3 May 2022).
  10. Liu, B.; Lu, X.; Jiang, A.; Lv, Y.; Zhang, H.; Xu, B. Influence of maternal endocrine disrupting chemicals exposure on adverse pregnancy outcomes: A systematic review and meta-analysis. Ecotoxicol. Environ. Saf. 2024, 270, 115851. [Google Scholar] [CrossRef]
  11. Ceballos, D.M.; Fellows, K.M.; Evans, A.E.; Janulewicz, P.A.; Lee, E.; Whittaker, S.G. Perchloroethylene and dry cleaning: It’s time to move the industry to safer alternatives. Front. Public. Health 2021, 9, 638082. [Google Scholar] [CrossRef]
  12. Pfadenhauer, L.; Burns, J.; Rohwer, A.; Rehfuess, E. Effectiveness of interventions to reduce exposure to lead through consumer products and drinking water: A systematic review. Environ. Res. 2016, 147, 525–536. [Google Scholar] [CrossRef] [PubMed]
  13. Wan, M.; Co, V.; El-Nezami, H. Endocrine disrupting chemicals and breast cancer: A systematic review of epidemiological studies. Crit. Rev. Food Sci. Nutr. 2021, 62, 6549–6576. [Google Scholar] [CrossRef] [PubMed]
  14. Abed, M.S.; Moosa, A.A.; Alzuhairi, M.A. Heavy metals in cosmetics and tattoos: A review of historical background, health impact, and regulatory limits. J. Hazard. Mater. Adv. 2024, 13, 100390. [Google Scholar] [CrossRef]
  15. Barton, C. Tetrachloroethylene. In Encyclopedia of Toxicology; Elsevier: Amsterdam, The Netherlands, 2014; pp. 498–502. [Google Scholar] [CrossRef]
  16. Aishwarya, S.; Vinodhini, V.; Renuka, P.; Saravanan, R.; Anuradha, M.; Gomathi, T.; Amuthavalli, V. Investigating the impact of endocrine-disrupting compounds on antepartum mental health at the nexus of genetic insights and maternal-fetal outcomes: A prospective study. Gen. Hosp. Psychiatry 2025, 94, 174–183. [Google Scholar] [CrossRef]
  17. Haggerty, D.K.; Upson, K.; Pacyga, D.C.; Franko, J.; Braun, J.M.; Strakovsky, R.S. Reproductive toxicology: Pregnancy exposure to endocrine disrupting chemicals: Implications for women’s health. Reproduction 2021, 162, F169–F180. [Google Scholar] [CrossRef]
  18. Barrett, E.S.; Sathyanarayana, S.; Janssen, S.; Redmon, J.; Nguyen, R.H.; Kobrosly, R.; Swan, S.H. Environmental health attitudes and behaviors: Findings from a large pregnancy cohort study. Eur. J. Obstet. Gynecol. Reprod. Biol. 2014, 176, 119–125. [Google Scholar] [CrossRef] [PubMed]
  19. Marie, C.; Cabut, S.; Vendittelli, F.; Sauvant-Rochat, M.-P. Changes in cosmetics use during pregnancy and risk perception by women. Int. J. Environ. Res. Public. Health 2016, 13, 383. [Google Scholar] [CrossRef]
  20. Rouillon, S.; El Ouazzani, H.; Rabouan, S.; Migeot, V.; Albouy-Llaty, M. Determinants of risk perception related to exposure to endocrine disruptors during pregnancy: A qualitative and quantitative study on french women. Int. J. Environ. Res. Public. Health 2018, 15, 2231. [Google Scholar] [CrossRef]
  21. Ricke, I.J.; Oglesby, A.; Lyden, G.R.; Barrett, E.S.; Moe, S.; Nguyen, R.H.N. Knowledge, Attitudes, and Behaviors Regarding Chemical Exposure among a Population Sample of Reproductive-Aged Women. Int. J. Environ. Res. Public. Health 2022, 19, 3015. [Google Scholar] [CrossRef]
  22. Zhao, Z.; Gong, Y.; Li, Y.; Zhang, L.; Sun, Y. Gender-related beliefs, norms, and the link with green consumption. Front. Psychol. 2021, 12, 710239. [Google Scholar] [CrossRef]
  23. Steinemann, A. Fragranced consumer products: Exposures and effects from emissions. Air Qual. Atmos. Health 2016, 9, 861–866. [Google Scholar] [CrossRef]
  24. FitzPatrick, M. Endocrine Disrupting Chemicals and Personal Care Products: Risk Awareness and Exposure Assessment for Women’s Reproductive Health. Ph.D. Thesis, Boston University, Boston, MA, USA, 2021. Available online: https://open.bu.edu/items/9b1d4020-eb0c-4fd9-9604-6c3be994f30f (accessed on 7 October 2022).
  25. Environmental Working Group (EWG). Ewg Verified®: Products for Your Health; EWG: Washington, DC, USA, 2025; Available online: https://www.ewg.org/ewgverified/ (accessed on 1 April 2025).
  26. Yuka. Yuka—The Mobile App That Scans Your Diet and Cosmetics; Yuka: Paris, France, 2024; Available online: https://yuka.io/en/ (accessed on 1 April 2025).
  27. Hawkins, M.; Elsworth, G.R.; Hoban, E.; Osborne, R.H. Questionnaire validation practice within a theoretical framework: A systematic descriptive literature review of health literacy assessments. BMJ Open 2020, 10, e035974. [Google Scholar] [CrossRef]
  28. Souza, A.; Alexandre, N.; Guirardello, E.; Souza, A.; Alexandre, N.; Guirardello, E. Propriedades psicométricas na avaliação de instrumentos: Avaliação da confiabilidade e da validade. Epidemiol. E Serviços De. Saúde 2017, 26, 649–659. [Google Scholar] [CrossRef]
  29. Rosenstock, I.M.; Strecher, V.J.; Becker, M.H. Social learning theory and the health belief model. Health Educ. Q. 1988, 15, 175–183. [Google Scholar] [CrossRef]
  30. Norman, P.; Conner, M. Health behavior. In Reference Module in Neuroscience and Biobehavioral Psychology; Elsevier: Amsterdam, The Netherlands, 2017. [Google Scholar] [CrossRef]
  31. Che, S.-R.; Barrett, E.S.; Velez, M.; Conn, K.; Heinert, S.; Qiu, X. Using the health belief model to illustrate factors that influence risk assessment during pregnancy and implications for prenatal education about endocrine disruptors. Policy Futures Educ. 2014, 12, 961–974. [Google Scholar] [CrossRef]
  32. Albadr, T.; Alfawzan, S.; Aljarba, B.; Alshehri, R.; Mahboub, S. Use of health belief model to explain the behaviour of following safety measures during the use of household chemical products among adult females in Riyadh. Int. J. Res. Med. Sci. 2020, 9, 9–14. [Google Scholar] [CrossRef]
  33. Chyung, S.; Roberts, K.; Swanson, I.; Hankinson, A. Evidence-based survey design:The use of a midpoint on the likert scale. Perform. Improv. 2017, 56, 15–23. [Google Scholar] [CrossRef]
  34. Statistics Canada. Fertility: Overview, 2012 to 2016. 2018. Available online: https://www150.statcan.gc.ca/n1/pub/91-209-x/2018001/article/54956-eng.htm (accessed on 4 September 2022).
  35. Mi, M.; Zhang, Y. Culturally competent library services and related factors among health sciences librarians: An exploratory study. J. Med. Libr. Assoc. 2017, 105, 132. [Google Scholar] [CrossRef]
  36. Joo, S.; Kim, S.; Kim, Y. An exploratory study of health scientists’ data reuse behaviors. Aslib J. Inf. Manag. 2017, 69, 389–407. [Google Scholar] [CrossRef]
  37. Lally, M.; Valentine-French, S. Emerging and Early Adulthood—Parenting and Family Diversity Issues; Iowa State University: Ames, IA, ISA, 2020; Available online: https://iastate.pressbooks.pub/parentingfamilydiversity/chapter/early-adulthood/ (accessed on 14 May 2023).
  38. Statistics Canada. Low Income Cut-Offs. Government of Canada. Retrieved 2023. 2021. Available online: https://www.canada.ca/en/employment-social-development/services/foreign-workers/caregiver/financial-ability.html (accessed on 14 May 2023).
  39. Li, P.; Stuart, E.A.; Allison, D.B. Multiple imputation. JAMA 2015, 314, 1966. [Google Scholar] [CrossRef]
  40. Sullivan, G.M.; Artino, A.R. Analyzing and interpreting data from likert-type scales. J. Grad. Med. Educ. 2013, 5, 541–542. [Google Scholar] [CrossRef]
  41. Zhan, W.; Yang, H.; Zhang, J.; Chen, Q. Association between co-exposure to phenols and phthalates mixture and infertility risk in women. Environ. Res. 2022, 215, 114244. [Google Scholar] [CrossRef]
  42. Deierlein, A.L.; Grayon, A.R.; Zhu, X.; Sun, Y.; Liu, X.; Kohlasch, K.; Stein, C.R. Personal care and household cleaning product use among pregnant women and new Mothers during the COVID-19 pandemic. Int. J. Environ. Res. Public. Health 2022, 19, 5645. [Google Scholar] [CrossRef]
  43. Ministry of Finance. Educational Attainment. 2022. Available online: https://www150.statcan.gc.ca/n1/daily-quotidien/211004/dq211004c-eng.htm (accessed on 5 May 2023).
  44. Miral, M.T.; Koç, E. Awareness and attitudes of pregnant women regarding endocrine disruptors. Afr. J. Reprod. Health 2025, 29, 59–69. [Google Scholar] [CrossRef]
  45. Trifunovski, A.; Rotondi, N.K.; Abbass-Dick, J.; Barakat, C. Hidden Hazards: Knowledge, Health Risk Perceptions, Beliefs and Avoidance Behaviour of Women in Relation to Toxic Chemicals Commonly Found in Personal Care and Household Products. Toxics 2025, in press.
  46. Lu, X.; Hisada, A.; Anai, A.; Nakashita, C.; Masuda, S.; Fujiwara, Y.; Kunugita, N.; Katoh, T. Study of the correlation between multiple chemical sensitivity and personality using the quick environmental exposure sensitivity inventory questionnaire and the temperament and character inventory. J. Occup. Environ. Med. 2020, 62, e348–e354. [Google Scholar] [CrossRef]
  47. Peris, R. Multiple Chemical Sensitivity (MCS)—Aseq-Ehaq. ASEQ-EHAQ. 8 April 2021. Available online: https://aseq-ehaq.ca/en/multiple-chemical-sensitivity-mcs/ (accessed on 4 October 2024).
  48. Živančević, K.; Marić, Đ.; Manić, L.; Bonderović, V.; Živanović, J.; Djukic-Cosic, D.; Bulat, Z.; Antonijevic, B.; Vilendecic, Z.; Ilić, S.; et al. Perceptions and awareness of endocrine disruptors among mothers in serbia and health implications. Endocr. Connect. 2025, 14, e240678. [Google Scholar] [CrossRef]
  49. The International Fragrance Association (IFRA). n.d. Home. Available online: https://ifrafragrance.org/ (accessed on 2 April 2025).
  50. IFRA. IFRA Position Statement on Diethyl Phthalate (DEP) [PDF]. 2005. Available online: https://www.sunseye.com/wp-content/uploads/2018/05/IFRA-position-on-DEP.pdf (accessed on 2 April 2025).
  51. Good Authority. How the Media Put Bpa on the Agenda in the States. 2013. Available online: https://goodauthority.org/news/how-the-media-put-bpa-on-the-agenda-in-the-states/?utm (accessed on 3 April 2025).
  52. Fong, D.; Ho, S.Y.; Lam, T.H. Evaluation of internal reliability in the presence of inconsistent responses. Health Qual. Life Outcomes 2010, 8, 27. [Google Scholar] [CrossRef]
  53. Tavakol, M.; Dennick, R. Making sense of cronbach. Int. J. Med. Educ. 2011, 2, 53–55. [Google Scholar] [CrossRef]
  54. Taber, K.S. The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Res. Sci. Educ. 2018, 48, 1273–1296. [Google Scholar] [CrossRef]
  55. Preston, C.C.; Colman, A.M. Optimal number of response categories in rating scales: Reliability, validity, discriminating power, and respondent preferences. Acta Psychol. 2000, 104, 1–15. [Google Scholar] [CrossRef]
  56. Price, P.C.; Jhangiani, R.; Chiang, C.A. Reliability and Validity of Measurement. In Research Methods in Psychology, 2nd ed.; BC Campus: Victoria, BC, Canada, 2020; Available online: https://opentextbc.ca/researchmethods/chapter/reliability-and-validity-of-measurement/ (accessed on 27 May 2024).
  57. Austin, P.C.; White, I.R.; Lee, D.S.; van Buuren, S. Missing data in clinical research: A tutorial on multiple imputation. Can. J. Cardiol. 2021, 37, 1322–1331. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Download PDF
Barriers to Effective Management of Mediterranean Coastal Lagoons Following Key European Union Directives: Perceptions of Managers of Natura 2000 Lagoon Sites in South France
Previous
Study of Inhibitory Effects on Aerobic Biomass: Interaction Between Per-/Polyfluoroalkyl Substances (PFAS) and Traditional Toxic Compounds
Next