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BRIEF RESEARCH REPORT article

Front. Public Health, 14 March 2024
Sec. Environmental Health and Exposome

Reliability and validity of the Chinese version of the sunlight exposure questionnaire

Xiaoxia Wang&#x;Xiaoxia Wang1Qin Wang,&#x;Qin Wang1,2Zhe Li,&#x;Zhe Li3,4Mengjie ChenMengjie Chen1Maoting GuoMaoting Guo1Laixi KongLaixi Kong1Liyuan ChenLiyuan Chen5Xiaolong LiXiaolong Li5Junjun LiJunjun Li1Qieyan CaoQieyan Cao6Zhenhua Luo
Zhenhua Luo5*Zhenzhen Xiong,
Zhenzhen Xiong1,7*Dan Zhao
Dan Zhao1*
  • 1School of Nursing, Chengdu Medical College, Chengdu, China
  • 2School of Health and Medicine, Polus International College, Chengdu, China
  • 3Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
  • 4Sichuan Clinical Medical Research Center for Mental Disorders, Chengdu, China
  • 5Xindu Hospital of Traditional Chinese Medicine •The First Affiliated Hospital of Traditional Chinese Medicine, Chengdu Medical College, Chengdu, China
  • 6Second Affiliated Hospital of Chengdu Medical College, Chengdu, China
  • 7Nursing Key Laboratory of Sichuan Province, Chengdu, China

Objective: This study aimed to translate and validate the reliability and validity of the Chinese version of the Philippines Sunlight Exposure Questionnaire.

Methods: A total of 392 Chinese individuals aged at least 18 years, residing in various cities in Sichuan province for at least 1 year, were recruited. The reliability of the Chinese version of the questionnaire was measured through internal consistency, split-half reliability, and retest reliability, while validity was determined using the content validity index and the structure validity index.

Results: The Chinese version of the Sunlight Exposure Questionnaire, which includes 19 items covering 5 factors, demonstrated McDonald’s omega coefficient of 0.788. The split-half reliability of the questionnaire was 0.823, and the retest reliability was 0.940. The content validity index (S-CVI) was 0.952. The five-factor structure, supported by eigenvalues, explained 66.2% of the total variance. Confirmatory factor analysis indicated favorable model fit.

Results: The chi-square value degrees of freedom ratio (χ2/df) = 1.852, the goodness-of-fit index (GFI) = 0.938, the normed fit index (NFI) = 0.922, the incremental fit index (IFI) = 0.962, the comparative fit index (CFI) = 0.962, the Tucker–Lewis index (TLI) = 0.952, and root mean square error of approximation (RMSEA) = 0.047. The indicators of the fit of the model were within reasonable bounds.

Conclusion: The Chinese version of the Sunlight Exposure Questionnaire shows validity and good reliability for assessing sun exposure among adults in a Chinese cultural context.

Introduction

Sunlight is important for human health and helps regulate physiology, psychology, and behavior (1). For example, sunlight influences melatonin secretion, which in turn affects circadian pacing by the supraoptic nucleus in the brain, such that lack of natural daylight can disturb sleep–wake rhythms (2, 3). Through its effects on circadian rhythms, sunlight can influence the neuroendocrine system, cognitive function, and mood (4). Moreover, a large number of epidemiological studies have substantiated the correlation between sunlight exposure levels and a diminished risk of all-cause mortality (5), as well as various related diseases such as myopia (6), asthma (7), type 1 diabetes (8), autism (9), colorectal cancer (10), and Alzheimer’s disease (11). Additionally, a potential mechanism underlying the connection between sunlight and public health is the conversion of 7-dehydrocholesterol in the human skin into vitamin D. This process is essential for the vitamin D synthesis of the body (12, 13), a deficiency of which can contribute to osteoporosis (14), multiple sclerosis (15), diabetes mellitus (16, 17), cardiovascular diseases (18), sleep disorders (19, 20), obesity (21), depression (22), and anxiety and cognitive impairment (23, 24).

Accurate assessment of sunlight exposure in the population can help to predict the risk of related diseases so that healthcare providers can intervene in advance to minimize or even prevent problems related to inadequate or excessive exposure. Such assessments may be particularly important in the wake of the coronavirus pandemic, when many people spent much more time indoors during the daytime, increasing the risk of inadequate daily sunlight exposure. This deficiency is notably associated with diminished sleep quality (25). Similarly, such assessments may be particularly important for populations living in parts of the world that receive below-average sunlight.

Photometers and ultraviolet (UV) dosimeters can accurately measure sunlight exposure, but they are not accessible in many environments and they cannot be distributed in large numbers to analyze samples that are large or geographically dispersed. A more cost-effective measurement tool is the Sunlight Exposure Questionnaire, several of which have been developed for different linguistic and cultural contexts, including the Pakistan Sunlight Exposure Measurement Questionnaire in English and Urdu (26), the Harvard Light Exposure Assessment (27) in English, and the Philippines Sunlight Exposure Questionnaire (28) in English and Filipino. The sunlight exposure estimated from these questionnaires correlates with vitamin D levels in serum (29), supporting their reliability.

Several questionnaires to assess sunlight exposure have been developed in Chinese (30, 31). Notably, one such assessment tool, crafted by Hong Kong scholars Shenghui Wu et al. (30), stands out for its commendable questionnaire reliability and validity. This instrument aims to evaluate lifetime sunlight exposure within the Chinese population and comprises 62 items. However, the considerable time investment required for participants, particularly the Older Adult, diminishes its generalizability and applicability in real-world studies. In China, numerous studies (22, 32) have utilized the variable “sunlight exposure time” as an indicator of light exposure. Conversely, fewer studies have employed the mature Sunlight Exposure Questionnaire to assess the degree of sunlight exposure among study participants. This discrepancy may introduce inaccuracies in the assessment of individual sunlight exposure, given that various factors, such as the quantity and duration of sunlight exposure, weather conditions, outdoor activities, and sun protection measures, collectively influence individual sunlight exposure. However, they were custom-designed and have yet to be validated on large populations or other ethnic groups. We are unaware of an internationally validated questionnaire in Chinese for assessing sunlight exposure (26), which makes international comparisons difficult.

Compared to internationally available sunlight exposure questionnaires primarily designed for non-Asians, the Philippines Sunlight Exposure Questionnaire stands out, developed by Marc Gregory et al. (28) in 2018. With a more streamlined total of 25 items, this questionnaire offers items that are easy to comprehend, rendering it applicable to a broader demographic. Notably, it incorporates inquiries concerning individuals’ perceived risks and benefits associated with sun exposure, a pivotal factor in assessing an individual’s sun exposure. Furthermore, this questionnaire has undergone rigorous testing, affirming its robust reliability and validity. Given the increasing focus on the health effects of light in contemporary research, and considering the ease of administration of the questionnaire, it proves highly applicable as a research tool for assessing sunlight exposure in large cross-sectional studies. Therefore, the objective of this study was to translate the Philippines Sunlight Exposure Questionnaire (28) into Chinese and validate its reliability and validity. We validated the questionnaire in a sample of 392 adults, providing a rigorous tool for testing hypotheses about associations between sunlight exposure and human health.

Methods

Study design

The study is a cross-sectional study. We utilized convenience sampling to recruit a total of 392 adults from various cities in Sichuan, China, in August 2022, employing Questionnaire Star as an online data collection platform in China. The sampled cities encompassed Chengdu, Mianyang, and other urban areas within Sichuan. The validation procedure was approved by the Ethics Committee of Chengdu Medical College (2022 No. 33). The URL link to the questionnaire was posted on social media, and participants who met the following inclusion criteria were invited to click on the link and forward it to others: (1) Participants had to be at least 18 years old, (2) they had to have been living at their current address for at least 1 year, and (3) they had to be able to read and understand the text. Participants were excluded if they reported being pregnant, currently having skin disease, or being in an immunocompromised state. Participants were recruited from cities all over Sichuan province.

The minimal sample size to test the validity and reliability of the 25-item questionnaire was defined as 250 because surveying at least 10 times as many people as items can provide an adequate and stable assessment of validity (33). We decided to administer the survey to 300 people to account for losses if 20% of invalid questionnaires had to be excluded. Before completing the questionnaire, participants were provided with a detailed explanation of the purpose and significance of the study, and they were assured that their responses would be kept confidential and used only for research purposes. After providing consent, participants were able to access the questionnaire.

After submitting the questionnaires, participants were excluded if subsequent analysis suggested that they had not understood the questions, such as if they did not respond to any of the questions or they gave the same response to all items. In addition, questionnaires were excluded if at least three items were unanswered or if the participant took only 1–5 min to complete the questionnaire. If one individual submitted multiple questionnaires from different cell phones or IP addresses, only one of the questionnaires was retained.

In accordance with the recommendation of a retest reliability sample size ranging from 10 to 20% of the total sample size (34), 2 weeks after the initial survey administration, 80 respondents were invited to repeat the survey in order to assess test–retest reliability.

Development of the Chinese version of the sunlight exposure questionnaire

We started with the Philippines Sunlight Exposure Questionnaire (28), which contains 25 items covering three factors: (1) intensity of sunlight exposure, items 1–7; (2) factors affecting sunlight exposure, items 8–19; and (3) sunlight protection measures, items 20–25. Respondents answer each item on a 4-point Likert scale comprising “never” (1 point), “sometimes” (2 points), “often” (3 points), and “always” (4 points). Scores for items within each factor are averaged to obtain the factor score, and the three-factor scores are averaged to yield an overall score. Overall scores of 1.0–2.0 indicate low sunlight exposure; >2.0–3.0, moderate exposure; and > 3.0–4.0, high exposure. Cronbach’s α coefficient in the original validation study was 0.80 (28).

Translation process

With the developers’ permission, the Philippines Sunlight Exposure Questionnaire was initially translated into Chinese by two native Chinese speakers. One of the translators, a nurse with a master’s degree, and the other holding a master’s degree in a non-medical discipline, worked independently. Discrepancies in their translations were thoroughly discussed by the research team and the two translators, with resolutions achieved through consensus. Subsequently, the questionnaire underwent counter-translation into English by two professional English teachers. The translated versions were scrutinized, and modifications were made through group discussions. Furthermore, to enhance cultural appropriateness and maximize content validity, five nursing experts were involved in the cultural adaptation of the translated questionnaire. This expert panel, comprising two professors and three associate professors, four of whom held master’s degrees and one a doctorate, possessed an average of 19.6 ± 5.04 years of professional experience. Finally, to ensure semantic clarity and appropriateness, a preliminary survey was conducted with 20 adults using the translated questionnaire. Participants were asked to complete the questionnaire and provide feedback on its difficulty. Adjustments were made based on their comments, culminating in the final version of the Chinese adaptation of the Philippines Sunlight Exposure Questionnaire.

Statistical analysis

Data were imported into Microsoft Excel 2010 and analyzed statistically using SPSS 26.0 (IBM, Chicago, IL, United States), AMOS 26.0 (IBM, Chicago, IL, United States), and Jamovi 2.3.28. Item analysis, validity, and reliability of the questionnaire were assessed. Results associated with p < 0.05 were considered statistically significant.

Item analysis

Item analysis means to test the quality of each item, whose purpose is to test the suitability or reliability of instruments and individual items. The results can be used as the basis for the screening or modification of individual items. The analysis of items involved the utilization of the critical ratio (CR) and correlation analysis between questionnaire items and total scores. The CR was determined by ranking the total scores obtained from the questionnaire from highest to lowest. Subsequently, the total scores of the top 27% were compared with those of the bottom 27% using an independent-samples t-test (34). Items were removed if their CR was not statistically significant or if the correlation coefficient between the score on the item and the overall score was below 0.300 (35).

Reliability analysis

The reliability of the questionnaire was assessed in terms of internal consistency, test–retest reliability, and split-half reliability as described (36). Internal consistency refers to the homogeneity among items and internal correlation among tools. This is evaluated through the utilization of Cronbach’s α coefficient and McDonald’s omega. Both McDonald’s omega and Cronbach’s α coefficient are employed as metrics for gauging the reliability of the scale. A score equal to or exceeding 0.7 is deemed acceptable (37, 38). Higher scores indicate better internal consistency. Test–retest reliability was expressed by calculating the Pearson correlation coefficient between the total score and each factor score to indicate the temporal stability of the questionnaire, and a correlation coefficient greater than or equal to 0.50 indicates acceptable reliability. Split-half reliability evaluates the internal consistency of the questionnaire by comparing the results of both halves of all items. A coefficient greater than 0.70 is considered satisfactory.

Validity analysis

Validity refers to the accuracy of the scale and is assessed by convergent validity and discriminant validity. The validity of the questionnaire was assessed in terms of content validity and structural validity. The content validity index is calculated based on the values obtained from expert opinions. It was assessed in terms of the content validity index (I-CVI) and the average content validity index (S-CVI) at the item level (39). A 4-point scale was used to assess the content validity of each item, ranging from “not relevant” (1 point) to “very relevant” (4 points). I-CVI means that each item appropriately reflects the extent of the concept to be measured, and S-CVI indicates the mean value of I-CVI of all items. I-CVI ≥0.78 and S-CVI ≥0.90 are considered acceptable (39).

The construct validity was assessed using factor analysis including exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The Kaiser–Meyer–Olkin (KMO) test and Bartlett’s spherical test (χ2) were used to examine the suitability for factor analysis. A KMO value ≥0.80 and a significant Bartlett’s chi-square (p < 0.05) indicated the appropriateness of factor analysis (40). For EFA, principal component analysis and varimax rotation were used to extract the common factors (eigenvalues >1) of the questionnaire items. A factor was deleted if a load of the item on a factor was below 0.40 or load differed less than 0.05 from the load of other factors. Indicators of good construct validity included item factor loadings >0.40 and cumulative variance contributions >60%. For CFA, AMOS 26.0 (IBM, Chicago, IL, United States) was utilized to analyze the applicability of model fit indices. The model fit indices assessed in this study included the chi-square value degrees of freedom ratio (χ2/df), goodness-of-fit index (GFI), comparative fit index (CFI), incremental fit index (IFI), normed fit index (NFI), and Tucker–Lewis index (TLI). Additionally, the root mean square error of approximation (RMSEA) was considered. The criteria for a good fit were χ2/df < 3.000, and GFI, CFI, IFI, NFI, and TLI values were above 0.90, with RMSEA values <0.08.

Results

Demographic characteristics

Of the 424 questionnaires received, 32 were excluded because 22 were incomplete and 10 contained the same response to all items. The final analysis contained 392 questionnaires, primarily from women (303, 77.3%). Across all participants, the average age was 30.3 ± 9.1 years, and 236 (60.2%) had completed secondary school (Table 1). The sample represented a diverse range of occupations, such as students (90, 23%), healthcare workers (80, 20.4%), freelancers (64, 16.3%), farmers (51, 13%), and government workers (10, 2.6%). Most respondents indicated that they worked indoors (267, 68.1%) or a combination of indoors and outdoors (104, 26.5%). All respondents came from Sichuan province, with nearly half (162, 41.3%) living in Chengdu and 116 (29.6%) living in Mianyang.

Table 1
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Table 1. Characteristics of participants in the validation study (N = 392).

Item analysis

The results of this study showed that the CR, which ranged from −2.650 to −12.369, was significant for all items except items 24–25, and the absolute value of CR of item 1 was less than 3 (Table 2). Additionally, we also examined the correlations of scores on each item with the overall score. Items 1, 2, 7, 23, 24, and 25 had correlation coefficients <0.300 (Table 2), with p > 0.05 for the correlation coefficients of items 24 and 25 (Table 2). As relevant literature (35), the deletion criteria included items with an absolute value of CR < 3 and p > 0.05 as well as items with a correlation coefficient < 0.3 and p > 0.05. Such items are considered insufficient in discriminating between high and low scores, displaying less homogeneity with other items and inadequate discriminatory capacity, leading to their proposed deletion. Consequently, items 1, 2, 7, 23, 24, and 25 were suggested for removal due to not meeting the retention criteria from a statistical perspective. Despite the statistical recommendations, caution is advised when deleting items, as the process involves a combination of statistical knowledge and professional background knowledge. Following expert group discussions, it was agreed that the content of item 7 (“What time of day are you usually exposed to the sun?”) was closely related to individuals’ degree of sunlight exposure. Therefore, based on a comprehensive evaluation of statistical results, item semantics, and professional significance, the analysis led to the retention of item 7 and the deletion of items 1, 2, 23, 24, and 25. The 20 retained items demonstrated better differentiation and homogeneity, aligning with the anticipated discrimination and homogeneity outcomes reflected in the survey results. Therefore, we decided to evaluate whether the remaining factors should be deleted based on the analyses of the exploratory and validation factors (see below) as well as theoretical considerations.

Table 2
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Table 2. Critical ratios for each item and their correlation coefficients with overall score on the Chinese version of the sunlight exposure questionnaire.

Reliability analysis

Internal consistency

For the Chinese version of the Sunlight Exposure Questionnaire, McDonald’s omega coefficient was 0.788. Cronbach’s α coefficient for each factor ranged from 0.668 to 0.861, Cronbach’s α coefficient was 0.779, and deleting each item one by one from the analysis did not increase Cronbach’s α coefficient, indicating good internal consistency of the Chinese version of the Sunlight Exposure Questionnaire.

Test–retest reliability

Test–retest reliability was 0.940 based on total score correlation analysis.

Split-half reliability

For the 19-item version, split-half reliability was 0.823 for the total questionnaire, and the reliability ranged from 0.669 to 0.838 across the different factors.

Validity analysis

Content validity

For the expert panel, I-CVI ranged from 0.800 to 1.000, and S-CVI was 0.952 for the overall questionnaire.

Construct validity

Exploratory factor analysis

We did not remove any of the 25 items before performing exploratory factor analysis. We confirmed that such analysis could be performed because the KMO value was 0.811, greater than the cut-off of 0.800 (40), and χ2 = 3,748 (p < 0.001) in Bartlett’s spherical test (40). We analyzed the factor structure in terms of principal components and maximum variance with orthogonal rotation. Items with factor loadings <0.40 were removed, while items that loaded >0.40 onto more than one factor were assigned to the factor most conceptually related to them. After exploratory factor analysis with variance maximization and orthogonal rotation, item 10 (with a factor loading <0.4) was removed (34). Five common factors with initial eigenvalues >1 were extracted according to the Kaiser criterion (41), with a cumulative variance contribution of 66.2%. The factor loadings of each item ranged from 0.644 to 0.854, and there were no double loadings.

All items were retained in the validated factor analysis, except items 1, 2, 10, 23, 24, and 25. A total of five factors were defined: sunlight exposure intensity, items 3–7; outdoor exposure to sunlight, 8–9; factors promoting sunlight exposure, 11–14; factors reducing sunlight exposure, 15–19; and measures that protect against sunlight, 20–22. The final Chinese version of the questionnaire included 19 items covering 5 factors. The factor “factors affecting sunlight exposure” in the original questionnaire was divided into three factors in the Chinese version (see Table 3).

Table 3
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Table 3. Factor loading on the final Chinese version of the sunlight exposure questionnaire.

Confirmatory factor analysis

The reasonableness of the five-factor model was assessed using confirmatory factor analysis after the addition of seven residual paths (Figure 1). Construct validity based on model fit metrics showed that the model fit was good. The quality indicators of the model were within the ranges defined as satisfactory: (42) χ2/df = 1.852 (< 3.000), RMSEA was 0.047 (< 0.080), GFI was 0.938 (> 0.900), CFI was 0.962 (> 0.900), IFI was 0.962 (> 0.900), NFI was 0.922 (> 0.900), and TLI was 0.952 (> 0.900). All standardized path regression coefficients exceeded 0.40, ranging from 0.51 to 0.86.

Figure 1
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Figure 1. Standardized factor structure of the final Chinese version of the sunlight exposure questionnaire.

Discussion

We introduce and validate a Chinese adaptation of the Philippines Sunlight Exposure Questionnaire (28). The 19-item Chinese version encompasses 5 factors. Through our validation involving nearly 400 Chinese adults, the questionnaire demonstrates suitable convergent and discriminant construct validity, internal consistency, and test–retest reliability.

This survey is, to our knowledge, the first rigorously validated questionnaire for assessing sunlight exposure in adults. It may therefore provide a more solid basis for studies benchmarking Chinese populations against samples in other countries according to sunlight exposure, attitudes to such exposure, potential protective measures, and potential effects on health. Previously reported questionnaires in Chinese for assessing sunlight exposure (30, 31) were validated qualitatively but not quantitatively as in the present study.

Item 1 (“How do you describe your skin when it is exposed to the sun?”) and item 2 (“What part of your body is usually exposed to the sun?”) of the original questionnaire did not survive our validated factor analysis with a sample of Chinese adults. This may reflect that many Chinese know that UV exposure affects skin tone and causes sunburn, but their understanding may be vague and not based on science (43, 44). In any case, self-reported photoresponse may correlate weakly or not at all with actual photoresponse (45), so deletion of the original items 1–2 from our survey may not lead to loss of information in Chinese samples.

We also deleted item 10 from the original questionnaire (“How often do you engage in outdoor activities such as jogging, cycling, and swimming?”). This item showed little correlation with other items. This may reflect that most cities in Sichuan province have similarly warm and humid weather year-round, leading many to spend more time indoors (46). In addition, many in our sample were students, for whom the first priority may be studying, rather than exercising, even if they recognize the importance of exercise to their health (47, 48). Our deletion of item 23 (“When going out in the sun, how often do you use sunscreen containing at least SPF 30?”), item 24 (“When do you usually apply sunscreen?”), and item 25 (“Where do you usually apply sunscreen?”) from the original questionnaire may reflect the relatively low rate of use of sunscreen among Chinese adults, reflecting in part low awareness of the hazards of sunlight exposure (49, 50). Many Chinese adults may prefer to protect their skin by staying in the shade or wearing hats, rather than using sunscreen (49), which may reflect a Chinese preference for fair skin over tanned skin (51). Indeed, the original questionnaire focused on Manila (121°E, 15°N), which receives more sunlight than Sichuan province, where the major cities are Chengdu (102°54′–104°53′E, 30°05′–31°26′N) and Mianyang (103°45′–105°43′E, 30°42′–33°03′N).

The Chinese version of the Sunlight Exposure Questionnaire takes only minutes to complete, making it a straightforward and rigorous tool for surveying adults in the general population as well as in clinics and care homes. The questionnaire was employed in the following manner: First, participants were instructed to complete the questionnaire. Subsequently, participants’ sun exposure was evaluated based on the questionnaire scores. Overall scores falling within the range of 1.0–2.0 indicate low sunlight exposure, scores >2.0–3.0 indicate moderate exposure, and scores >3.0–4.0 indicate high exposure. In the contemporary landscape, there exists substantial public interest in understanding the risks and benefits associated with sun exposure. The potential utilization of this questionnaire for quantifying an individual’s exposure to sunlight opens avenues for new research opportunities. This may facilitate investigations into the relationship between sunlight exposure and health outcomes, offering insights into the advantageous aspects of sunlight exposure and contributing to the prevention or delay of the onset and progression of related diseases. The data gained with this questionnaire may help guide efforts to identify individuals at risk of inadequate sunlight exposure, which can increase the risk of morbidity (52), such as inflammatory bowel disease (53) or osteoporotic fractures (54). Measures to increase sunlight exposure of at-risk individuals can then be encouraged. Conversely, the questionnaire can identify individuals who receive abundant sunlight but may not protect themselves adequately, and who therefore may benefit from interventions that sensitize them to the dangers of excessive sunlight and educate them about appropriate protection measures. In this study, a significant proportion of participants dedicated more time indoors, primarily for study, living, and work-related reasons associated with their occupations. While this practice may mitigate excessive sunlight exposure, it raises concerns about potential insufficient sunlight exposure for these individuals. Therefore, the assessment of individual sun exposure becomes crucial. Accurate knowledge of specific sunlight exposure is imperative to implement measures aimed at enhancing public exposure to sunlight, a necessity for promoting both physical and mental health in the general population.

This study has several limitations. First, as this study was conducted during the COVID-19 epidemic, the sample was obtained through convenience sampling using an online questionnaire, resulting in a predominantly female, Sichuan-based, and urban-dwelling respondent pool, leading to a sex distribution imbalance. Future studies will have to strive to recruit more male participants and rural residents for a more comprehensive assessment of the Chinese version of the Sunlight Exposure Questionnaire across genders and regions in China. The second limitation is the absence of objective standardized measures of sunlight exposure, such as serum 25-hydroxyvitamin D (25-OHD) measurements. Skin synthesis via UV exposure serves as the primary source of vitamin D, and researchers have employed vitamin D measurements as a clinical tool for evaluating individual sun exposure in various studies (5557). Therefore, follow-up studies incorporating serum 25-OHD measurements could enhance the scientific accuracy of the investigations. The correlation between sunlight exposure questionnaires and serum vitamin D values could be further validated in subsequent studies.

Conclusion

Following translation and cross-cultural adaptation, the Philippines Sunlight Exposure Questionnaire has been introduced in China, demonstrating good reliability and validity. The Chinese version of the Sunlight Exposure Questionnaire is deemed suitable for evaluating sunlight exposure in Chinese adults. Moreover, the questionnaire serves as a valuable reference for health promoters in the development of educational programs and research interventions aimed at promoting the physical and mental health of the public.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Ethics Committee of Chengdu Medical College. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

XW: Investigation, Writing – original draft. QW: Writing – original draft, Investigation. ZLi: Investigation, Writing – original draft. MC: Investigation, Writing – review & editing. MG: Investigation, Writing – review & editing. LK: Investigation, Writing – review & editing. LC: Investigation, Writing – review & editing. XL: Investigation, Writing – review & editing. JL: Investigation, Writing – review & editing. QC: Investigation, Writing – review & editing. ZLu: Project administration, Writing – review & editing. ZX: Methodology, Supervision, Writing – review & editing. DZ: Project administration, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was supported by the Nursing Key Laboratory of Sichuan Province Fund Programme (HLKF2022-4), the 2022 Open Project of Development and Regeneration Key Lab of Sichuan Province (2022LHZYYB-17), the 2022 Open Project of Clinical Research Center for Geriatric Diseases (2022LHFSSYB-03), the 2022 Chengdu Medical College Graduate Student Innovation Fund (YCX2022-01-43), the 2022 Chengdu Medical College Graduate Student Innovation Fund (YCX2022-01-48), and the 2023 Open Project of Development and Regeneration Key Lab of Sichuan Province (23LHZJ04).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Izmir Tunahan, G, Altamirano, H, Teji, JU, and Ticleanu, C. Evaluation of daylight perception assessment methods. Front Psychol. (2022) 13:805796. doi: 10.3389/fpsyg.2022.805796

PubMed Abstract | Crossref Full Text | Google Scholar

2. Muñoz-González, C, Ruiz-Jaramillo, J, Cuerdo-Vilches, T, Joyanes-Díaz, MD, Montiel Vega, L, Cano-Martos, V, et al. Natural lighting in historic houses during times of pandemic. The case of housing in the Mediterranean climate. Int J Environ Res Public Health. (2021) 18:7264. doi: 10.3390/ijerph18147264

PubMed Abstract | Crossref Full Text | Google Scholar

3. Roenneberg, T, Kumar, CJ, and Merrow, M. The human circadian clock entrains to sun time. Curr Biol. (2007) 17:R44–5. doi: 10.1016/j.cub.2006.12.011

Crossref Full Text | Google Scholar

4. Kim, SY, Bang, M, Wee, JH, Min, C, Yoo, DM, Han, SM, et al. Short-and long-term exposure to air pollution and lack of sunlight are associated with an increased risk of depression: a nested case-control study using meteorological data and national sample cohort data. Sci Total Environ. (2021) 757:143960. doi: 10.1016/j.scitotenv.2020.143960

PubMed Abstract | Crossref Full Text | Google Scholar

5. Lindqvist, PG, Epstein, E, Nielsen, K, Landin-Olsson, M, Ingvar, C, and Olsson, H. Avoidance of sun exposure as a risk factor for major causes of death: a competing risk analysis of the melanoma in southern Sweden cohort. J Intern Med. (2016) 280:375–87. doi: 10.1111/joim.12496

PubMed Abstract | Crossref Full Text | Google Scholar

6. Cao, K, Wan, Y, Yusufu, M, and Wang, N. Significance of outdoor time for myopia prevention: a systematic review and Meta-analysis based on randomized controlled trials. Ophthalmic Res. (2020) 63:97–105. doi: 10.1159/000501937

PubMed Abstract | Crossref Full Text | Google Scholar

7. Morgan, KA, Mann, EH, Young, AR, and Hawrylowicz, CM. ASTHMA – comparing the impact of vitamin D versus UVR on clinical and immune parameters. Photochem Photobiol Sci. (2017) 16:399–410. doi: 10.1039/c6pp00407e

Crossref Full Text | Google Scholar

8. Miller, KM, Hart, PH, Lucas, RM, Davis, EA, and de Klerk, NH. Higher ultraviolet radiation during early life is associated with lower risk of childhood type 1 diabetes among boys. Sci Rep. (2021) 11:18597. doi: 10.1038/s41598-021-97469-z

PubMed Abstract | Crossref Full Text | Google Scholar

9. Liang, Y, Yu, H, Ke, X, Eyles, D, Sun, R, Wang, Z, et al. Vitamin D deficiency worsens maternal diabetes induced neurodevelopmental disorder by potentiating hyperglycemia-mediated epigenetic changes. Ann N Y Acad Sci. (2021) 1491:74–88. doi: 10.1111/nyas.14535

PubMed Abstract | Crossref Full Text | Google Scholar

10. Pedersen, JE, and Hansen, J. Colorectal cancer and occupational exposure to solar ultraviolet B radiation in Denmark. Environ Res. (2022) 215:114260. doi: 10.1016/j.envres.2022.114260

PubMed Abstract | Crossref Full Text | Google Scholar

11. Li, Q, Peng, J, Luo, Y, Zhou, J, Li, T, Cao, L, et al. Far infrared light irradiation enhances Aβ clearance via increased exocytotic microglial ATP and ameliorates cognitive deficit in Alzheimer's disease-like mice. J Neuroinflammation. (2022) 19:145. doi: 10.1186/s12974-022-02521-y

PubMed Abstract | Crossref Full Text | Google Scholar

12. Tuckey, RC, Cheng, CYS, and Slominski, AT. The serum vitamin D metabolome: what we know and what is still to discover. J Steroid Biochem Mol Biol. (2019) 186:4–21. doi: 10.1016/j.jsbmb.2018.09.003

PubMed Abstract | Crossref Full Text | Google Scholar

13. Chinese Geriatric Health Care Medical Research Association - Geriatric Health Services and Standardization Branch, Editorial Board of “Chinese Geriatric Health Care Medicine. Consensus on the specification of vitamin D supplementation for the elderly. Chin J Geriatr Care. (2019) 17:42–5. doi: 10.3969/j.issn.1672-2671.2019.04.011

Crossref Full Text | Google Scholar

14. Polzonetti, V, Pucciarelli, S, Vincenzetti, S, and Polidori, P. Dietary intake of vitamin D from dairy products reduces the risk of osteoporosis. Nutrients. (2020) 12:1743. doi: 10.3390/nu12061743

PubMed Abstract | Crossref Full Text | Google Scholar

15. Jagannath, VA, Filippini, G, Di Pietrantonj, C, Asokan, GV, Robak, EW, Whamond, L, et al. Vitamin D for the management of multiple sclerosis. Cochrane Database Syst Rev. (2018) 2023:CD008422. doi: 10.1002/14651858.CD008422.pub3

PubMed Abstract | Crossref Full Text | Google Scholar

16. Liu, Q, Zheng, X, Liu, Z, and Qiu, L. Vitamin D status is associated with 1, 5-anhydro-d-glucitol status in patients with type 2 diabetes mellitus. Appl Physiol Nutr Metab. (2019) 44:857–60. doi: 10.1139/apnm-2018-0719

PubMed Abstract | Crossref Full Text | Google Scholar

17. Lu, L, Bennett, DA, Millwood, IY, Parish, S, McCarthy, MI, Mahajan, A, et al. Association of vitamin D with risk of type 2 diabetes: a Mendelian randomisation study in European and Chinese adults. PLoS Med. (2018) 15:e1002566. doi: 10.1371/journal.pmed.1002566

PubMed Abstract | Crossref Full Text | Google Scholar

18. Chen, X, Zhou, M, Yan, H, Chen, J, Wang, Y, and Mo, X. Association of serum total 25-hydroxy-vitamin D concentration and risk of all-cause, cardiovascular and malignancies-specific mortality in patients with hyperlipidemia in the United States. Front Nutr. (2022) 9:971720. doi: 10.3389/fnut.2022.971720

PubMed Abstract | Crossref Full Text | Google Scholar

19. Majid, MS, Ahmad, HS, Bizhan, H, Hosein, HZM, and Mohammad, A. The effect of vitamin D supplement on the score and quality of sleep in 20-50 year-old people with sleep disorders compared with control group. Nutr Neurosci. (2018) 21:511–9. doi: 10.1080/1028415X.2017.1317395

PubMed Abstract | Crossref Full Text | Google Scholar

20. de Menezes-Junior, LAA, Sabiao, TDS, de Moura, SS, Batista, AP, de Menezes, MC, Carraro, JCC, et al. Influence of sunlight on the association between 25-hydroxyvitamin D levels and sleep quality in Brazilian adults: a population-based study. Nutrition. (2023) 110:112008. doi: 10.1016/j.nut.2023.112008

PubMed Abstract | Crossref Full Text | Google Scholar

21. Chen, R, Yang, C, Li, P, Wang, J, Liang, Z, Wang, W, et al. Long-term exposure to ambient PM, sunlight, and obesity: a nationwide study in China. Front Endocrinol (Lausanne). (2021) 12:790294. doi: 10.3389/fendo.2021.790294

PubMed Abstract | Crossref Full Text | Google Scholar

22. Cui, Y, Gong, Q, Huang, C, Guo, F, Li, W, Wang, Y, et al. The relationship between sunlight exposure duration and depressive symptoms: a cross-sectional study on elderly Chinese women. PLoS One. (2021) 16:e0254856. doi: 10.1371/journal.pone.0254856

PubMed Abstract | Crossref Full Text | Google Scholar

23. Wu, H, Khuram Raza, H, Li, Z, Li, Z, Zu, J, Xu, C, et al. Correlation between serum 25 (OH) D and cognitive impairment in Parkinson's disease. J Clin Neurosci. (2022) 100:192–5. doi: 10.1016/j.jocn.2022.04.015

PubMed Abstract | Crossref Full Text | Google Scholar

24. Ma, L-Z, Ma, Y-H, Ou, Y-N, Chen, SD, Yang, L, Dong, Q, et al. Time spent in outdoor light is associated with the risk of dementia: a prospective cohort study of 362094 participants. BMC Med. (2022) 20:132. doi: 10.1186/s12916-022-02331-2

PubMed Abstract | Crossref Full Text | Google Scholar

25. de Menezes-Júnior, LAA, de Moura, SS, Miranda, AG, Andrade, AC, Machado-Coelho, GLL, Meireles, AL, et al. The mediating role of sun exposure on the association between sedentary behavior and sleep quality: a population-based cross-sectional study. Sleep Med. (2023) 108:98–9. doi: 10.1016/j.sleep.2023.05.024

PubMed Abstract | Crossref Full Text | Google Scholar

26. Humayun, Q, Iqbal, R, Azam, I, Khan, AH, Siddiqui, AR, and Baig-Ansari, N. Development and validation of sunlight exposure measurement questionnaire (SEM-Q) for use in adult population residing in Pakistan. BMC Public Health. (2012) 12:421. doi: 10.1186/1471-2458-12-421

PubMed Abstract | Crossref Full Text | Google Scholar

27. Bajaj, A, Rosner, B, Lockley, SW, and Schernhammer, ES. Validation of a light questionnaire with real-life photopic illuminance measurements: the Harvard light exposure assessment questionnaire. Cancer Epidemiol Biomarkers Prev. (2011) 20:1341–9. doi: 10.1158/1055-9965.EPI-11-0204

PubMed Abstract | Crossref Full Text | Google Scholar

28. Yu, MG, Castillo-Carandang, N, Sison, MEG, Uy, AB, Villarante, KL, Maningat, P, et al. Development and validation of a sunlight exposure questionnaire for urban adult Filipinos. Epidemiol Health. (2018) 40:e2018050. doi: 10.4178/epih.e2018050

PubMed Abstract | Crossref Full Text | Google Scholar

29. Mansibang, NMM, Yu, MGY, Jimeno, CA, and Lantion-Ang, FL. Association of sunlight exposure with 25-hydroxyvitamin D levels among working urban adult Filipinos. Osteoporos Sarcopenia. (2020) 6:133–8. doi: 10.1016/j.afos.2020.08.006

PubMed Abstract | Crossref Full Text | Google Scholar

30. Wu, S, Ho, SC, Lam, TP, Woo, J, Yuen, PY, Qin, L, et al. Development and validation of a lifetime exposure questionnaire for use among Chinese populations. Sci Rep. (2013) 3:2793. doi: 10.1038/srep02793

Crossref Full Text | Google Scholar

31. Yan, W, Jian, Z, Qiong, M, Jingxian, D, Sujiao, S, and Lihua, C. Investigation and analysis of Sun exposure and Sun protection behaviors among primary students in Dali area. J Dali Univ. (2016) 15:71–4.

Google Scholar

32. Zg, C, Chen, Y, Zhao, Y, Fu, J, Liu, Y, Tang, S, et al. Association of sunshine duration with acute myocardial infarction hospital admissions in Beijing, China: a time-series analysis within-summer. Sci Total Environ. (2022) 828:154528. doi: 10.1016/j.scitotenv.2022.154528

PubMed Abstract | Crossref Full Text | Google Scholar

33. Polit, DF, and Beck, CT. Nursing research: Principles and methods. Philadelphia, PA: Lippincott Williams & Wilkins (2004).

Google Scholar

34. Wu, M. Practice of questionnaire statistical analysis—SPSS operation and application. Chongqing: Chongqing University Press; (2010). 158–263.

Google Scholar

35. Zijlmans, EAO, Tijmstra, J, van der Ark, LA, and Sijtsma, K. Item-score reliability in empirical-data sets and its relationship with other item indices. Educ Psychol Meas. (2018) 78:998–1020. doi: 10.1177/0013164417728358

PubMed Abstract | Crossref Full Text | Google Scholar

36. Kottner, J, Audigé, L, Brorson, S, Donner, A, Gajewski, BJ, Hróbjartsson, A, et al. Guidelines for reporting reliability and agreement studies (GRRAS) were proposed. J Clin Epidemiol. (2011) 64:96–106. doi: 10.1016/j.jclinepi.2010.03.002

PubMed Abstract | Crossref Full Text | Google Scholar

37. Polit, DF, and Beck, CT. The content validity index: are you sure you know what's being reported? Critique and recommendations. Res Nurs Health. (2006) 29:489–97. doi: 10.1002/nur.20147

PubMed Abstract | Crossref Full Text | Google Scholar

38. Hayes, AF, and Coutts, JJ. Use omega rather than Cronbach’s alpha for estimating reliability. But …. Commun Methods Meas. (2020) 14:1–24. doi: 10.1080/19312458.2020.1718629

Crossref Full Text | Google Scholar

39. Almanasreh, E, Moles, R, and Chen, TF. Evaluation of methods used for estimating content validity. Res Soc Adm Pharm. (2019) 15:214–21. doi: 10.1016/j.sapharm.2018.03.066

Crossref Full Text | Google Scholar

40. Schreiber, JB . Issues and recommendations for exploratory factor analysis and principal component analysis. Res Soc Adm Pharm. (2021) 17:1004–11. doi: 10.1016/j.sapharm.2020.07.027

PubMed Abstract | Crossref Full Text | Google Scholar

41. Gaskin, CJ, and Happell, B. On exploratory factor analysis: a review of recent evidence, an assessment of current practice, and recommendations for future use. Int J Nurs Stud. (2014) 51:511–21. doi: 10.1016/j.ijnurstu.2013.10.005

PubMed Abstract | Crossref Full Text | Google Scholar

42. Alavi, M, Visentin, DC, Thapa, DK, Hunt, GE, Watson, R, and Cleary, M. Chi-square for model fit in confirmatory factor analysis. J Adv Nurs. (2020) 76:2209–11. doi: 10.1111/jan.14399

Crossref Full Text | Google Scholar

43. Shunqin, S, Pingbing, Z, Sujiao, S, Lizhu, M, Zhengli, L, Jinghua, S, et al. A survey on the knowledge of UV damage and sun protection among the Dai and Wa ethnic groups in Lincang. Dermatol Venereol. (2021) 43:64–7. doi: 10.3969/j.issn.1002-1310.2021.01.031

Crossref Full Text | Google Scholar

44. Qin, L, Kaiping, Z, Jianbo, W, Jiquan, S, and Guifeng, X. Study on the relationship between the cognition and behavior of Sun protection and facial skin Photoaging from TCM perspective. J Hubei Univ Tradit Chin Med. (2020) 22:126–9. doi: 10.3969/j.issn.1008987x.2020.05.35

Crossref Full Text | Google Scholar

45. Park, SB, Suh, DH, and Youn, JI. Reliability of self-assessment in determining skin phototype for Korean brown skin. Photodermatol Photoimmunol Photomed. (1998) 14:160–3. doi: 10.1111/j.1600-0781.1998.tb00035.x

PubMed Abstract | Crossref Full Text | Google Scholar

46. Duan, Z, Ren, Y, Liu, X, Lei, H, Hua, X, Shu, X, et al. A comprehensive comparison of data fusion approaches to multi-source precipitation observations: a case study in Sichuan province, China. Environ Monit Assess. (2022) 194:422. doi: 10.1007/s10661-022-10098-5

PubMed Abstract | Crossref Full Text | Google Scholar

47. Hongyan, S . Investigation and countermeasures of youth sports. Youth Res. (2022) 2:68–78.

Google Scholar

48. Qiuju, Z . Study on the relationship between exercise habits, dietary habits and body composition and bone mineral density of college students. Chengdu: Sichuan Normal University (2021).

Google Scholar

49. Yan, S, Xu, F, Yang, C, Li, F, Fan, J, Wang, L, et al. Demographic differences in sun protection beliefs and behavior: a community-based study in Shanghai, China. Int J Environ Res Public Health. (2015) 12:3232–45. doi: 10.3390/ijerph120303232

PubMed Abstract | Crossref Full Text | Google Scholar

50. Wenbo, L, Mengjiao, F, Qin, H, and Zhenhua, W. Investigation on cognition and behavior of skin care in 628 women in Weifang. Chin J Lepr Skin Dis. (2021) 37:369–72. doi: 10.12144/zgmfskin202106369

Crossref Full Text | Google Scholar

51. Stephens, PM, Martin, B, Ghafari, G, Luong, J, Nahar, VK, Pham, L, et al. Skin Cancer knowledge, attitudes, and practices among Chinese population: a narrative review. Dermatol Res Pract. (2018) 2018:1965674–9. doi: 10.1155/2018/1965674

PubMed Abstract | Crossref Full Text | Google Scholar

52. Jaworeck, S, and Kriwy, P. It's sunny, be healthy? An international comparison of the influence of Sun exposure and latitude lines on self-rated health. Int J Environ Res Public Health. (2021) 18:4101. doi: 10.3390/ijerph18084101

Crossref Full Text | Google Scholar

53. Holmes, EA, Rodney Harris, RM, and Lucas, RM. Low sun exposure and vitamin D deficiency as risk factors for inflammatory bowel disease, with a focus on childhood onset. Photochem Photobiol. (2019) 95:105–18. doi: 10.1111/php.13007

PubMed Abstract | Crossref Full Text | Google Scholar

54. Lee, HJ, Kim, CO, and Lee, DC. Association between daily sunlight exposure and fractures in older Korean adults with osteoporosis: a nationwide population-based cross-sectional study. Yonsei Med J. (2021) 62:593–9. doi: 10.3349/ymj.2021.62.7.593

PubMed Abstract | Crossref Full Text | Google Scholar

55. Nikolac Gabaj, N, Unic, A, Miler, M, Pavicic, T, Culej, J, Bolanca, I, et al. In sickness and in health: pivotal role of vitamin D. Biochem Med (Zagreb). (2020) 30:020501:202–14. doi: 10.11613/BM.2020.020501

PubMed Abstract | Crossref Full Text | Google Scholar

56. O'Sullivan, F, Laird, E, Kelly, D, van Geffen, J, van Weele, M, McNulty, H, et al. Ambient UVB dose and Sun enjoyment are important predictors of vitamin D status in an older population. J Nutr. (2017) 147:858–68. doi: 10.3945/jn.116.244079

PubMed Abstract | Crossref Full Text | Google Scholar

57. Zerwekh, JE . Blood biomarkers of vitamin D status. Am J Clin Nutr. (2008) 87:1087S–91S. doi: 10.1093/ajcn/87.4.1087S

Crossref Full Text | Google Scholar

Keywords: sunlight, vitamin D, circadian rhythms, health, reliability, validity

Citation: Wang X, Wang Q, Li Z, Chen M, Guo M, Kong L, Chen L, Li X, Li J, Cao Q, Luo Z, Xiong Z and Zhao D (2024) Reliability and validity of the Chinese version of the sunlight exposure questionnaire. Front. Public Health. 12:1281301. doi: 10.3389/fpubh.2024.1281301

Received: 22 August 2023; Accepted: 22 February 2024;
Published: 14 March 2024.

Edited by:

Shenghui Wu, Appalachian State University, United States

Reviewed by:

Claudina Nogueira, University of Pretoria, South Africa
M. M. A. Faridi, ERA’s Lucknow Medical College, India
Luiz Menezes-Junior, Universidade Federal de Ouro Preto, Brazil
Antonino Maniaci, Kore University of Enna, Italy

Copyright © 2024 Wang, Wang, Li, Chen, Guo, Kong, Chen, Li, Li, Cao, Luo, Xiong and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Zhenhua Luo, 932635164@qq.com; Zhenzhen Xiong, xzz62308631@163.com; Dan Zhao, xiahuazhaodan@163.com

These authors contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.