Influence of Refractive Status, Residential Climate, and Adverse Environmental Factors in Contact Lens Dropout: Insights from a Survey-Based Study

Abstract

Introduction

This study aimed to analyze the influence of refractive status, residential climate, and exposure to adverse environmental factors in contact lens (CL) dropout.

Methods

This cross-sectional study involved a face-to-face survey conducted by trained optometrists among former and current CL wearers (CLWs) at General Óptica centers throughout Spain. The survey included questions related to demographic characteristics, refractive status, residential climate, and adverse environmental factors. The chi-square test and a forward stepwise binary logistic regression analysis were performed.

Results

A total of 1094 surveys were included, comprising 509 former CLWs and 585 current CLWs. Age (B = 0.03; OR 1.03, 95% CI 1.02–1.04) and exposure to chemical (B = 3.51; OR 41.67, 95% CI 12.06–143.95) or dusty environments (B = 1.05; OR 2.93, 95% CI 1.16–7.41) were significantly associated with CL dropout. However, residing in a continental climate was associated with a lower CL dropout compared with a Mediterranean climate (B = − 1.39; OR 0.25, 95% CI 0.15–0.42). Spherical refraction, cylindrical refraction, and near addition power did not show statistically significant associations with CL dropout. Furthermore, the model excluded sex, exposure to high-humidity or dry environments, and the interactions between adverse environmental factors and residential climate as predictive factors.

Conclusions

Older age, residence in the Mediterranean climate, and exposure to chemical or dusty environments increase the risk of contact lens dropout. However, climate-specific conditions do not appear to significantly influence dropout rates, suggesting that other factors may play a more important role.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40123-025-01290-0.

Key Summary Points

Why carry out this study?

Contact lens (CL) dropout remains a major concern for eye care professionals. Reported dropout rates vary considerably across studies, ranging from 12% to 51%.

The existing literature has predominantly focused on contact lens-related reasons for dropout. However, a limited number of studies have examined how refractive status and environmental factors may contribute to contact lens dropout, particularly in the context of Southern European populations.

What was learned from the study?

Older age, residence in the Mediterranean climate, and exposure to chemical or dusty environments are predictive factors that significantly influence contact lens dropout in Spain.

Climate-specific conditions—such as humidity environments in the Mediterranean climate or dry environments in the continental climate—do not significantly influence CL dropout, indicating that other factors may play a more relevant role.

Introduction

Contact lenses (CL) are commonly used for the correction of refractive errors, providing advantages in terms of aesthetics, comfort, and visual performance [1, 2] which significantly improve patients’ quality of life [3]. Despite significant advancements in CL materials, designs, and fitting techniques, CL dropout remains a major concern for eye care professionals. Reported dropout rates vary considerably across studies, ranging from 12% to 51%, which suggests that a substantial proportion of patients discontinue CL use either temporarily or permanently [4, 5].

The existing literature has predominantly focused on CL-related reasons for dropout. Early studies by Pritchard et al. [4], Young et al. [6], and Richdale et al. [7] identified “discomfort” and “dryness” as the primary contributing reasons. Additionally, more recent research by Dumbleton et al. [8] has further confirmed that “discomfort” and “dryness” remain the leading reasons for CL discontinuation. However, a limited number of studies have examined how refractive status and environmental factors may contribute to CL dropout.

In terms of refractive status, a survey of 251 patients conducted in Portugal found that hyperopic CL wearers (CLWs) reported a higher prevalence of dry eye symptoms compared to myopic CLWs [9], which may suggest a higher dropout rate among hyperopes than myopes. Furthermore, Young et al. [6] demonstrated that dropout rates are higher for toric (31%) and multifocal CL (47%) compared to spherical CL (9%). Similarly, Sulley et al. [10] reported lower dropout rates in spherical CL (19%), with higher dropout rates in toric (25%) and multifocal CL (31%). These findings also suggest that refractive status influences the choice of CL design, which may consequently affect dropout rates. Concerning environmental factors, most studies have been conducted in North America or Northern Europe [4, 7, 8], regions with climatic and occupational characteristics that may not be generalizable to Southern European countries. In Spain, the predominant climate is Mediterranean, although continental and Atlantic zones are also present. The Atlantic climate is characterized by mild temperatures, high humidity, frequent rainfall, and limited seasonal variation due to oceanic influence [11]. In contrast, the continental climate presents more extreme conditions, with hot summers, cold winters, and low humidity, reflecting the absence of maritime moderation [12]. The Mediterranean climate features hot, dry summers and mild, wet winters, with pronounced seasonal contrasts driven by subtropical high-pressure systems [13]. These distinct climatic patterns contribute to a wide range of environmental exposures that may affect ocular surface health and CL tolerance. Several studies have identified environmental conditions as contributing factors to CL dropout. Early surveys reported that exposure to dust, smoke, and workplace irritants can aggravate CL intolerance [4]. More recent research has shown that, despite advances in lens materials, dissatisfaction among CLWs often persists in challenging environments [7, 8]. Furthermore, the TFOS Lifestyle Report highlights that environmental conditions such as air pollution, low humidity, and strong airflow can significantly compromise ocular surface health [14]. These factors are known to exacerbate symptoms such as dryness, irritation, and discomfort among CLWs [14]. However, while these environmental conditions are recognized contributors to ocular surface dysfunction, their direct association with CL dropout remains insufficiently established [15].

Despite these studies, the influence of refractive status and environmental factors on CL dropout remains insufficiently explored—particularly in the context of Southern European populations. Therefore, this study aims to evaluate the influence of refractive status and environmental factors on CL dropout in a Spanish population. By incorporating these aspects, the research seeks to generate data relevant to clinical practice in Southern European regions.

Methods

Study Design

This was an observational, cross-sectional study involving face-to-face surveys, which was approved by the Medication Research Ethics Committee of the Fundació Assistencial Mútua Terrassa in March 2023 (ID: P/23-002/Universitat Politècnica de Catalunya). The study adhered to the ethical principles outlined in the Declaration of Helsinki (1975, revised in Tokyo in 2013). In addition, informed written consent was obtained from all participants prior to their inclusion in the study.

Recruitment and Survey

Participants were recruited from General Óptica, a company associated with the Board of Trustees of the Faculty of Optics and Optometry of Terrassa (FOOT). General Óptica operates 212 optical centers across Spain, with 90 of these centers participating in the study. An in-person survey was carried out from April to September 2023, involving a sample of patients attending different General Óptica locations throughout Spain.

Inclusion criteria consisted of former and current CLWs aged 18 years or older. Current CLWs were defined as patients who reported using CL for at least 4 days per week and a minimum of 6 h per day. These thresholds were chosen to ensure a clear distinction between habitual wearers and individuals who use CL only occasionally, whose patterns of use may not reflect sustained or consistent wear behavior. Former CLWs were defined as patients who had discontinued CL use for at least 1 year prior to participation. A minimum interval of 1 year was selected to avoid misclassifying temporary interruptions—such as short-term discontinuation for convenience, ocular irritation, or lens refitting—as true dropout, thereby ensuring accurate identification of long-term former CLWs. To avoid misclassification of environmental exposure, participants whose current residence differed from where they lived during the period of CL wear or discontinuation were excluded. Patients who reported refractive surgery as the dropout reason, who were unable or unwilling to provide informed consent, or who lacked the capacity to understand it were also excluded from the study.

The survey was conducted by trained optometrists at General Óptica centers, who received standardized instruction on the administration protocol. The questionnaire was developed and approved by a panel of CL experts from the Faculty of Optics and Optometry of Terrassa and consisted of two sections. The first section, completed by the optometrist using patient records, collected (1) basic demographic information (age, gender, and postal code) and (2) refractive data, including (2.1) sphere and (2.2) cylinder values for both eyes and (2.3) near addition power, when applicable. The postal code of residence was used to classify participants into (3) residential climate categories: (3.1) Atlantic (provinces bordering the Atlantic Ocean), (3.2) continental (inland provinces without coastal borders), and (3.3) Mediterranean (provinces bordering the Mediterranean Sea). The second section focused on CL wear or discontinuation and the reasons for dropout. It also included a question regarding (4) exposure to adverse environmental factors, namely (4.1) chemical, (4.2) dusty, (4.3) dry, and (4.4) high-humidity environments. For this question, the optometrists administering the survey provided examples to ensure consistent interpretation of each environmental condition, following the standardized training. A copy of the questionnaire is available as supplementary material for reference.

Statistical Analysis

Statistical analyses were performed with SPSS statistics software, version 28.0 (IBM Corporation, NY, USA). The sample size calculation was based on data from the National Statistics Institute of Spain, which reported that 8% of individuals aged 15–65 use CL. Using this estimate, the required sample size to achieve a 95% confidence level with a 5% margin of error was determined to be 385 participants. For the analysis, both former and current CLWs were included. To analyze refractive data, one eye was randomly selected for each participant using the Research Randomizer software, Version 4.0 (http://www.randomizer.org/). The Kolmogorov–Smirnov test was applied to assess the normality of continuous variables. Student’s t tests were employed to compare differences between the two groups for continuous variables. Chi-square tests were performed in the following situations: (1) to evaluate significant differences between groups for ordinal categorical variables such as sex, refractive status, residential climate, and exposure to adverse environmental factors; (2) to assess the association between residential climate and exposure to adverse environmental factors; and (3) to examine significant differences between groups exposed to a specific adverse environmental factor within a given residential climate. When a significant chi-square result was observed, a post hoc analysis was performed using standardized adjusted residuals to identify which cells contributed to the association. To control for type I error due to multiple comparisons, Bonferroni correction was applied by multiplying the individual P values by the number of comparisons. A forward stepwise binary logistic regression analysis was also performed to identify the factors associated with CL dropout. All variables included in the study were introduced into the model. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to estimate the strength of the associations. Model performance was assessed using the Hosmer–Lemeshow test, the Nagelkerke R-square, and overall classification accuracy. Continuous variables are presented as the mean ± standard deviation (SD), while ordinal categorical variables are reported as frequencies (n) and percentages. Statistical significance was defined as a P value < 0.05.

Results

A total of 1094 participants, including 509 (46.5%) former CLWs and 585 (53.4%) current CLWs, completed the survey and were deemed eligible for analysis. Responses were received from all provinces and territories in Spain, with the highest number of responses originating from Barcelona (8.7%), followed by Alicante (7.8%), Asturias (6.4%), and Madrid (6.4%). The characteristics of the participants are presented in Table 1. Regarding demographic characteristics, the mean age of participants was 40.6 ± 14.1 years, with 773 (70.6%) being female. In terms of refractive status, 817 (74.7%) were myopic, 27 (2.5%) were emmetropes, 250 (22.8%) were hyperopes, 864 (78.9%) had astigmatism, and 342 (31.3%) were presbyopic. Concerning climatic conditions, 470 (42.9%) participants resided in the continental climate, 402 (36.9%) in the Mediterranean climate, and 222 (20.2%) in the Atlantic climate. The classification of these climatic zones was based on long-term climatological data from the National Geographic Institute of Spain, corresponding to the 1981–2010 reference period. As for environmental exposure, 385 (35.2%) participants were generally exposed to adverse environmental conditions. Specifically, 198 (18.0%) were exposed to dusty environments, 156 (14.2%) to dry environments, 116 (10.6%) to chemical environments, and 105 (9.6%) to high-humidity environments. No significant differences were found between former and current CLWs in terms of age and sex (all P > 0.05), indicating that both groups are comparable.

Table 1.

Demographic characteristics, refractive status, residential climate, and adverse environmental factors in former and current CLWs

Characteristics	Current CLWs (n = 585)	Former CLWs (n = 509)	P value
Age, mean ± SD, years	37.3 ± 13.6	44.0 ± 14.5	0.089a
Sex, n (%)
Male/female	174 (29.7)/411 (70.3)	147 (28.8)/362 (71.2)	0.543b
Spherical refraction, D
+ 5.25 to 10	14 (2.4)	5 (0.9)	> 1c
+ 3.75 to + 5	17 (2.9)	17 (3.3)	> 1c
+ 1.75 to + 3.50	53 (9.1)	58 (11.4)	> 1c
+ 0.25 to + 1.50	25 (4.3)	61 (12)	0.079c
0	0 (0)	27 (5.3)	0.002c,*
− 0.25 to − 1.50	82 (14)	119 (23.3)	0.688c
− 1.75 to − 3.50	187 (32)	128 (25.1)	> 1c
− 3.75 to − 5	103 (17.6)	52 (10.2)	> 1c
− 5.25 to − 10	97 (16.6)	37 (7.6)	0.090c
> − 10	7 (1.1)	5 (0.9)	> 1c
Cylindrical refraction, D
0 to − 1	438 (74.9)	362 (71.2)	0.359b
− 1.25 to − 2.50	124 (21.2)	122 (23.9)
> − 2.50	23 (3.9)	25 (4.9)
Near addition power, D
+ 0.50 to + 1.25	36 (20.7)	47 (18.7)	0.484b
+ 1.50 to + 2.25	88 (50.6)	116 (46.2)
> + 2.50	50 (28.7)	50 (35.1)
Climate
Atlantic	126 (21.5)	96 (18.8)	> 1c
Continental	269 (46.0)	201 (39.5)	0.288c
Mediterranean	190 (32.5)	212 (41.7)	0.022c,*
Adverse environments
Chemical	43 (7.4)	73 (14.3)	0.0004c,*
Dusty	87 (14.9)	111 (21.8)	0.006c,*
Dry	78 (13.3)	78 (15.3)	0.348c
High-humidity	42 (7.2)	63 (12.4)	0.007c,*

CLWs contact lens wearers, D diopters, n frequency, SD standard deviation

^aStudent’s t test

^bChi-square test

^cPost hoc residual analysis with Bonferroni correction

*Statistical significance with P < 0.05

Chi-Square Associations

Refractive Status

The frequencies of spherical refraction in former and current CLWs are shown in Fig. 1. The frequency of former CLWs without spherical refraction was higher compared to current CLWs (100% vs. 0%; P = 0.002), whereas no significant differences were found between the two groups for spherical refraction values ranging from + 0.25 D to > + 10 D and − 0.25 D to < − 10 D. No significant differences were found between the two groups in terms of cylindrical refraction (P = 0.359) and near addition power (P = 0.484).

Fig. 1.

Bar chart illustrating the frequency of spherical refraction in former and current CLWs. The graph indicates that for no spherical refraction, the frequency of former CLWs was higher compared to current CLWs (100% vs. 0%; P = 0.002). No significant differences were found between the two groups for spherical refraction values ranging from + 0.25 D to >  + 10 D and − 0.25 D to < − 10 D

Residential Climate Conditions

The frequencies of former and current CLWs across different climates is shown in Fig. 2. Former CLWs were more prevalent than current CLWs in the Mediterranean climate (56.20% vs. 43.80%; P = 0.022), while no significant differences were observed between the two groups in the Atlantic (46.78% vs. 53.22%; P > 1) and continental climates (46.20% vs. 53.80%; P = 0.288).

Fig. 2.

Pie charts representing the frequency of different climate types in which former and current CLWs reside. Former CLWs were more prevalent than current CLWs in the Mediterranean climate (56.20% vs. 43.80%; P = 0.022), while no significant differences were observed in the Atlantic (46.78% vs. 53.22%; P > 1) and continental climates (46.20% vs. 53.80%; P = 0.288)

Adverse Environmental Factors

Overall exposure to adverse environmental factors is shown in Fig. 3a. Former CLWs were more exposed than current CLWs (55.92% vs. 44.08%; P = 0.007). Exposure to specific adverse environmental factors is shown in Fig. 3b. Former CLWs also showed a higher exposure than current CLWs to chemical environments (14.3% vs. 7.4%; P = 0.0004), dusty environments (21.8% vs. 14.9%; P = 0.006), and high-humidity environments (12.4% vs. 7.2%; P = 0.007). However, no significant differences were found between the two groups in dry environments (15.3% vs. 13.3%; P = 0.348).

Fig. 3.

a Pie chart depicting the overall exposure to adverse environmental factors. Former CLWs were more exposed than current CLWs (55.92% vs. 44.08%; P = 0.007) to adverse environmental factors. b Bar chart showing the exposure to specific adverse environmental factors. Former CLWs also showed higher exposure than current CLWs to chemical (14.3% vs. 7.4%; P < 0.0004), dusty (21.8% vs. 14.9%; P = 0.006) and high-humidity environments (12.4% vs. 7.2%; P = 0.007)

Adverse Environmental Factors by Residential Climate

The exposure to adverse environmental factors by residential climate is shown in Table 2. A significant association was observed between residential climate type and exposure to high-humidity environments (P < 0.0001). Specifically, post hoc analysis revealed that continental climate was associated with lower exposure to high-humidity environments (P = 0.002), whereas Mediterranean climate was associated with higher exposure to high-humidity environments (P = 0.007). However, when comparing exposure to high-humidity environments between former and current CLWs within each residential climate, no significant differences were observed in the continental (6.8% vs. 3.8%; P = 0.160) or Mediterranean climate (14.7% vs. 12.4%; P = 0.501). Similarly, a significant association was found between residential climate and exposure to dry environments (P < 0.0001). Post hoc analysis indicated that continental climate was associated with greater exposure to dry environments (P = 0.0009), while Mediterranean climate was associated with lower exposure to dry environments (P = 0.027). Nonetheless, no significant differences in exposure to dry environments were observed between former and current CLWs within either continental (19.3% vs. 19.5%; P = 0.959) or Mediterranean climates (10.6% vs. 9.6%; P = 0.543). No significant associations were found between residential climate and exposure to chemical (P = 0.814) or dusty environments (P = 0.244).

Table 2.

Association between adverse environmental factors and residential climate

Environments, n (%)	Residential climate
	Atlantic	Continental	Mediterranean	P valuea
Chemical
Exposure	23 (22.1)	40 (38.4)	41 (39.5)	0.814
Non-exposure	207 (23.3)	360 (40.5)	322 (36.2)
Dusty
Exposure	33 (18.4)	75 (41.8)	71 (39.8)	0.244
Non-exposure	197 (24.2)	325 (39.9)	292 (35.9)
Dry
Exposure	27 (19.2)	78 (55.7)	35 (25)	< 0.0001*
Non-exposure	203 (23.7)	322 (37.7)	328 (38.6)
P valueb	> 1	0.0009*	0.027*
High-humidity
Exposure	23 (25)	20 (21.7)	49 (53.3)	< 0.0001*
Non-exposure	207 (22.9)	380 (42.2)	314 (34.9)
P valueb	> 1	0.002*	0.007*

^aChi-square test

^bPost hoc residual analysis with Bonferroni correction

*Statistical significance with P value < 0.05

Forward Stepwise Binary Logistic Regression

The final eight-step model was statistically significant (chi-square 734.66, P < 0.0001) and showed a good fit according to the Hosmer and Lemeshow test (P = 0.770). Overall, it explained 65.3% of the variance in the dependent variable (Nagelkerke R-square) and showed high predictive accuracy, correctly classifying 83.4% of the cases. The results indicated that age and exposure to chemical or dusty environments were significantly associated with CL dropout. Specifically, for each 1-year increase in age, the odds of discontinuing CL use increased by 1.03 times (B = 0.03; OR 1.03, 95% CI 1.02–1.04). Exposure to dusty environments increased the odds of CL dropout by 2.93 times (B = 1.05; OR 2.93, 95% CI 1.16–7.41), while exposure to chemical environments represented the most influential factor, increasing the odds by 41.67 times (B = 3.51, OR 41.67, 95% CI 12.06–143.95). In contrast, residing in a continental climate was associated with a 75% reduction in the odds of CL dropout compared with a Mediterranean climate (B = − 1.39, OR 0.25, 95% CI 0.15–0.42). Spherical refraction, cylindrical refraction, and near addition power did not show statistically significant associations with CL dropout. Furthermore, the model excluded sex and exposure to high-humidity or dry environments, as well as the interactions between adverse environmental factors (Table 3).

Table 3.

Forward stepwise binary logistic regression analysis for the causal factors associated with contact lens (CL) dropout

Factorsa,b	B	ORs	P value	95% CI
Age	0.03	1.03	< 0.0001	1.02–1.04
Spherical refractionc	–	–	0.249	–
Cylindrical refractiond	–	–	1	–
Near addition powere	–	–	1	–
Climatef	–	–	< 0.0001	–
Continental climatef	− 1.39	0.25	< 0.0001	0.15–0.42
Chemical environmentg	3.51	41.67	< 0.0001	12.06–143.95
Dusty environmenth	1.05	2.93	0.027	1.16–7.41

B logit coefficient, CI confidence intervals, CL contact lens, CLWs contact lens wearers, ORs odds ratios

The final model, derived from a forward stepwise procedure that utilized 8 steps, is statistically significant (chi-square 734.66; P < 0.0001) and demonstrates a good fit according to the Hosmer–Lemeshow test (P = 0.770). The model’s ability to account for the variance in the dependent variable is 65.3% (Nagelkerke R-square). The predictive accuracy of the model is high, correctly classifying 83.4% of the cases

^aDependent variable: group (0 = current CLWS; 1 = former CLWS)

^bIndependent variables excluded by the forward stepwise binary logistic regression logistic regression: sex, dry environment, high-humidity environment, climate × chemical environment, climate × dusty environment, climate × dry environment, and climate × high-humidity environment

^cSpherical refraction (0 = high myopia [reference]; 1 = medium myopia; 2 = low myopia; 3 = emmetropia; 4 = low hyperopia; 5 = medium hyperopia; 6 = high hyperopia)

^dCylindrical refraction (0 = low [reference]; 1 = medium; 2 = high)

^eNear addition power (0 = no addition [reference]; 1 = low; 2 = medium; 3 = high)

^fClimate (0 = Atlantic; 1 = continental; 2 = Mediterranean [reference])

^gContinental climate compare to the reference (Mediterranean climate)

^hChemical environment (0 = exposure; 1 = non-exposure)

ⁱDusty environment (0 = exposure; 1 = non-exposure)

*Statistical significance with P value < 0.05

Discussion

This study explored the influence of refractive status, residential climate, and exposure to adverse environmental factors on CL dropout in Spain. The findings indicate that former CLWs were significantly associated with low spherical refraction (P = 0.002), residence in the Mediterranean climate (P = 0.022), and increased exposure to adverse environmental factors (P = 0.007), including chemical (P < 0.0004), dusty (P = 0.006), and high-humidity environments (P = 0.007). However, when all the variables were entered into a forward stepwise binary logistic regression model, only age, exposure to chemical or dusty environments, and residential climate remained significant predictors. This indicates that these factors independently contribute to the likelihood of CL dropout, whereas the effects of other variables observed in the chi-square test were no longer significant after adjustment for potential confounders.

Regarding refractive status, the higher dropout rate observed among patients without spherical refraction suggests that they may perceive fewer benefits from CL use, regardless of their cylindrical refraction or near addition power. This result is consistent with previous studies [5, 10]. In a retrospective study with neophyte CLWs, Sulley et al. [5] reported a dropout rate of 43.4% among CLWs with spherical refraction between + 2.00 and 0 D, whereas those with spherical refraction lower than − 2.25 D or greater than + 2.25 D showed a dropout rate of ≤ 27%. Results showing a similar trend were subsequently reported by Sulley et al. [10] in a prospective study, who observed a dropout rate of 31.6% among neophyte CLWs with spherical refraction between + 2.00 D and 0 D, while those with spherical refraction lower than − 2.25 D or greater than + 2.25 D showed a dropout rate ≤ 30.6%. On the other hand, no significant differences were found in cylindrical refraction or near addition power between former and current CLWs, suggesting that these refractive parameters may have less influence than spherical refraction on CL dropout. However, some studies suggest an association between dropout rates and the design of the CL [6, 10], with patients fitted with toric and multifocal designs being more likely to discontinue CL use due to poor vision quality [6, 10, 16]. Furthermore, it is important to mention that CLWs with low spherical refraction [17], or those dissatisfied with toric or multifocal designs [18, 19], may perceive spectacles as a satisfactory alternative, particularly when exposed to adverse environmental factors. Nonetheless, the binary logistic regression analysis indicated that spherical refraction, cylindrical refraction, and near addition power did not appear to be causal factors associated with CL dropout. Additionally, although evidence in the literature regarding the effect of age on CL discontinuation is limited, the present study suggests that with each additional year of age, the odds of discontinuing CL use increase by approximately 3%.

Residential climate has emerged as another significant factor influencing CL dropout. The Mediterranean climate is characterized by mild, wet winters, and warm to hot summers, with episodic heavy rainfall predominantly occurring in autumn [13]. This climatic variability exposes residents to adverse environmental factors—such as high temperatures, strong winds, and dust events—that may exacerbate CL discomfort and lead to increased dropout rates [14]. Consistent with this, the present study revealed higher dropout rates in the Mediterranean regions (P = 0.022), which suggest that residential climate may influence CL retention. This hypothesis is further supported by the binary logistic regression, which showed that CLWs residing in a continental climate had 75% lower odds of CL dropout compared with those living in a Mediterranean climate. This study also confirms a significant influence of adverse environmental factors on CL dropout. Patients exposed to chemical (P = 0.0004) or dusty (P = 0.006) environments were more likely to discontinue CL use, which aligns with previous studies. In the context of chemical environments, Nilsson and Andersson [20] reported that soft CL can significantly absorb volatile organic compounds, with trichlorethylene concentrations reaching up to 88 times higher than in ambient air in CL with 38% water content, and up to 170 times higher in CL with 75% water content after 10 min of exposure. Cerulli et al. [21] also indicate that exposure to isopropyl and ethyl alcohol may pose risks to CLWs in the occupational settings. Moreover, the National Institute for Occupational Safety and Health (NIOSH) recommends against CL use when working with acrylonitrile, methylene chloride, 1,2-dibromo-3-chloropropane, ethylene oxide, and methylene dianiline [22]. With respect to dusty environments, several studies suggest that soft CL can readily trap dust allergens, including pollen particles [23, 24] and cosmetic powders [25]. The accumulation of these allergens on the lens surface may exacerbate symptoms of allergic conjunctivitis, thereby precluding their use [26, 27]. In addition to these adverse environments, the present study also found that patients exposed to high-humidity environments were more likely to discontinue CL use (P = 0.007), whereas no significant differences were observed in dry environments (P = 0.348). Despite these findings, the binary logistic regression showed that only exposure to chemical or dusty environments increased the odds of CL dropout, by 41.67 and 2.93 times, respectively. These results are consistent with current evidence summarized in the TFOS DEWS III Report, which emphasizes the substantial influence of environmental and lifestyle factors on tear film homeostasis and ocular surface function. According to this updated framework, variations in humidity, temperature, air quality, and airborne particulate exposure can disrupt tear film stability and increase ocular discomfort, particularly in CLWs [28]. TFOS DEWS III also highlights the growing role of lifestyle-related exposures—including prolonged digital device use, time spent in air-conditioned or heated indoor environments, and modern work routines—in exacerbating ocular surface stress and reducing tolerance to CL [28]. These observations align with the TFOS Lifestyle Report, which similarly identifies environmental control, digital behavior, and daily activity patterns as key determinants of comfort and successful CL wear [14]. Together, these insights support the interpretation that the higher dropout rates observed in Mediterranean regions may reflect not only climatic characteristics but also lifestyle-dependent interactions with the ocular surface.

Given the observed influence of residential climate and adverse environmental factors on CL dropout, an analysis was performed to examine the potential association between these variables. The findings revealed that residing in the Mediterranean climate was significantly related to greater exposure to high-humidity environments (P = 0.007), whereas living in the continental climate was more frequently associated with exposure to dry environments (P = 0.0009). These results are consistent with data reported by the National Geographic Institute of Spain [29]. Although the average annual temperature is similar across the different regions of both climates—ranging from 12.5 to 22.5 °C—the relative humidity in the continental climate fluctuates between 60% and 65%, whereas in the Mediterranean climate it ranges from 65% to 75% [29]. This lower relative humidity in the continental climate results in reduced moisture content in the air, leading to drier environments [30].

Based on these results, a more detailed analysis was conducted to determine the influence of climate-specific conditions on CL dropout. This analysis revealed no significant differences in exposure to high-humidity environments between former and current CLWs residing in the Mediterranean climate (14.7% vs. 12.4%; P = 0.501). This finding suggests that the significant difference observed between former and current CLWs exposed to high-humidity environments (12.4% vs. 7.2%; P = 0.007) may be due to a climate-related response bias. In the present study, a higher proportion of former than current CLWs was found in the Mediterranean climate (56.20% vs. 43.80%; P = 0.022). Furthermore, this climate was significantly associated with high-humidity environments (P = 0.007). Therefore, it is likely that when participants were asked about exposure to high-humidity environments, those living in the Mediterranean regions were more inclined to respond affirmatively. A similar explanation may account for the lack of significant differences between former and current CLWs exposed to dry environments (15.3% vs. 13.3%; P = 0.348). It should also be noted that continental climate was significantly associated with dry environments (P = 0.0009) and no significant differences in exposure to dry environments were observed between former and current CLWs residing in the continental climate (19.3% vs. 19.5%; P = 0.959). Therefore, all these findings suggest that the climate-specific conditions—high-humidity environments in the Mediterranean climate and dry environments in the continental climate—do not appear to have a significant influence on CL dropout. This hypothesis is also supported by the binary logistic regression, in which the model excluded all interactions between adverse environmental factors and residential climate. Moreover, given that 34.7% of the variance in the dependent variable remains unexplained by the independent variables, these results suggest that additional factors may contribute to CL dropout. A previous study conducted among 502 former CLWs in Spain identified both CL-related and non-CL-related reasons influencing dropout [17]. The most frequently reported CL-related reasons were ocular symptoms (43.8%) and poor vision quality (13.8%) [17]. In contrast, the main non-CL-related reasons were a preference for wearing spectacles (13.1%) and refractive surgery (9.4%) [17]. However, this study did not consider other potentially relevant non-CL-related reasons, such as refractive status, residential climate, or exposure to adverse environmental factors. This underscores the need for further studies employing multiple linear regression analyses to identify the variables that best predict CL dropout, and to quantify the relative contribution of both CL-related and non-CL-related factors, including refractive status, climate, and exposure to adverse environmental factors.

Strengths and Limitations

This study addresses a gap in the literature regarding the influence of refractive status and environmental factors on CL dropout in Southern Europe. Additionally, the large and geographically diverse sample provides a robust basis for the validity of the results. However, some limitations should be acknowledged. This study relies on self-reported data, which may introduce recall bias. Additionally, although participants were asked about their exposure to adverse environmental factors such as high humidity, dryness, dust, or chemical compounds based on their residential climate, there is a possibility that some participants’ responses may have been influenced if any of these factors were present in their occupational settings. This bias may have also influenced the results. Another potential limitation of this study is that all participants were recruited from General Óptica centers, which could introduce some selection bias, as these individuals are regular customers of a specific optical chain and may share certain socioeconomic or behavioral characteristics. However, this potential bias is likely limited, as General Óptica is not a low-cost chain with a narrowly defined customer profile; rather, its wide network of centers is distributed across neighborhoods with diverse socioeconomic backgrounds, reducing the likelihood of systematic bias in participant characteristics. Finally, the lack of detailed information regarding CL material, wear modality, and care routines care regimen, duration of wear, and ocular surface parameters represents another limitation, as these factors may play a role in CL dropout and are potential confounders in the present study.

Conclusion

This study demonstrates that age, residential climate, and exposure to adverse environmental factors significantly influence CL dropout in Spain. Specifically, older age, residence in the Mediterranean climate, and exposure to chemical or dusty environments increase the risk of CL discontinuation. However, climate-specific conditions—such as high-humidity environments in the Mediterranean climate or dry environments in the continental climate—do not seem to significantly influence CL dropout, indicating that other factors may play a more relevant role. However, the results should be interpreted cautiously, as variations in climate conditions within the same province could influence outcomes. Overall, the study highlights the multifactorial nature of CL dropout, offering eye care practitioners insights into refractive and environmental factors to consider in clinical practice. This underscores the importance of personalized recommendations to improve CL retention across diverse geographic and occupational contexts.

Supplementary Information

Below is the link to the electronic supplementary material.

Author Contributions

Joan Gispets: Conceptualization, methodology, formal analysis, investigation, writing—original draft preparation, writing—review & editing. Aurora Torrents: Conceptualization, methodology, formal analysis, investigation, writing—original draft preparation, writing—review & editing. Hanan Haulani: Conceptualization, data curation, methodology, formal analysis, investigation, writing—review & editing. Antonio Ballesteros-Sánchez: Conceptualization, formal analysis, investigation, writing—original draft preparation, writing—review & editing.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. No funding or sponsorship was received for the publication of this article.

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Conflicts of Interest

Antonio Ballesteros-Sánchez is an Editorial Board member of Ophthalmology and Therapy. Antonio Ballesteros-Sánchez was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions. Joan Gispets, Aurora Torrents, and Hanan Haulani declare that they have no conflict of interest relevant to the content of this article.

Ethical Approval

This was an observational, cross-sectional study involving face-to-face surveys, which was approved by the Medication Research Ethics Committee of the Fundació Assistencial Mútua Terrassa in March 2023 (ID: P/23-002/Universitat Politècnica de Catalunya). The study fulfilled all the requirements of the Declaration of Helsinki and was approved by the Medication Research Ethics Committee of the Fundació Assistencial Mútua Terrassa in March 2023 (ID: P/23-002/Universitat Politècnica de Catalunya). Before initiating the study, informed and written consent was obtained from each patient.

Scale Permission

This study did not employ any proprietary or copyrighted assessment tools or scales that require special permissions for use. All methodologies and measurement instruments used are either original to this study or fall within the public domain.