In Utero/Childhood/ Adolescence Exposure to Tobacco Smoke and Elderly-Onset Cataract: A Large Prospective Cohort Study

Abstract

Purpose: Cataract remains the primary cause of blindness in middle-income and low-income countries, with a known association with environmental factors including smoking. However, the relationship between early-life tobacco smoke exposures, including in utero tobacco smoke exposure and early initiation of smoking, and the risk of cataract incidence remains unclear. We aimed to examine the associations of early-life exposure to tobacco smoke with the risk of elderly-onset cataract.

Methods: In this prospective study, we included 330,528 participants aged 40 years or older who were recruited between 2006 and 2010. Early-life tobacco smoke exposures, including in utero, childhood, and adolescence exposure to tobacco smoke, as well as the type of tobacco smoke, were ascertained based on questionnaires at baseline. Elderly-onset cataract was ascertained using hospital inpatient records and cataract surgery records. Multivariable-adjusted Cox proportional hazards models were used to examine the association between early-life tobacco smoke exposures and incident cataract. Additionally, the association between different types of tobacco smoke and cataract risk was also explored.

Results: During a median follow-up of 12.04 years, 14,754 cases of incident cataract were documented. After adjusting confounders, the incidence of cataract significantly increased among participants with tobacco smoke exposures (hazard ratio [HR] = 1.13, 95% confidence interval [CI] = 1.09–1.18). Furthermore, individuals who were exposed to tobacco smoke in childhood (HR = 1.10, 95% CI = 1.03–1.21), adolescence (HR = 1.15, 95% CI = 1.10–1.21), and adulthood (HR = 1.12, 95% CI = 1.05–1.19) had an increased risk of cataract. Additionally, individuals who smoked cigars or pipes (HR = 1.26, 95% CI = 1.11–1.44), hand-rolled cigarettes (HR = 1.20, 95% CI = 1.05–1.36), and manufactured cigarettes (HR = 1.12, 95% CI = 1.08–1.17) were associated with an increased risk of cataract.

Conclusions: Individuals with early-life tobacco smoke exposures in childhood and adolescence significantly elevate the risks of cataract incidence in older age.

Translational Relevance: This study identified cataract-associated risks and suggested interventions like banning youth smoking to reduce future cataract incidence.

Introduction

Approximately 94 million people globally suffer from moderate or severe distance vision impairment or blindness caused by unaddressed cataract.¹ Cataract treatment relies solely on surgery, imposing a considerable economic and social burden on underdeveloped regions.² Given this, it emphasized the importance of identifying and proactively controlling risk factors for cataract. Over several decades, extensive efforts have been made to identify risk factors for cataract, including age, sex, race, and potential environmental factors such as ultraviolet light exposure and tobacco smoke exposure.³ 

Many large cohort studies have shown that tobacco smoke exposure is associated with several blinding eye diseases, such as cataract, glaucoma, and age-related macular degeneration.^4,5 However, most studies on tobacco smoke exposure and cataract have been cross-sectional. For example, an Indian cross-sectional study involving 10,293 subjects aged 15 years revealed a strong association between tobacco smoking and a higher prevalence of nuclear and cortical cataract, as well as a history of prior cataract surgery.⁶ In the Korea National Health and Nutrition Examination Survey, current smoking was correlated with cataract.⁷ In addition, the evidence regarding the relationship between early-life tobacco smoke exposures and elderly-onset cataract was limited. Therefore, a longitudinal cohort study is needed to investigate the relationship between early-life tobacco smoke exposures and elderly-onset cataract incidence. 

In this study, we examined the association between early-life tobacco smoke exposures and incident cataract based on the large, prospective UK Biobank cohort. We examined the associations of tobacco smoke exposures at different stages (in utero, childhood, and adolescence) and different types (cigars or pipes, hand-rolled cigarettes, and manufactured cigarettes) with incident cataract. Additionally, we explored the dose-effect relationship between the number of cigarettes smoked daily and cataract incidence. 

Methods

Data Source and Study Population

The UK Biobank is a large community-based cohort of over 500,000 UK residents registered with the National Health Service and aged 40 to 69 years at enrollment. Baseline examinations, including basic information questionnaires and eye examinations, were carried out between 2006 and 2010 at 22 study assessment centers. The North West Multicenter Research Ethics Committee approved the study in accordance with the principles of the Declaration of Helsinki.⁸ The overall study protocol (http://www.ukbiobank.ac.uk/resources/) and protocols for individual tests (http://biobank.ctsu.ox.ac.uk/crystal/docs.cgi) are available online. All participants provided informed consent to use their anonymized data. This research was conducted under application ID #86091. A total of 330,528 participants were included in the main analysis, after excluding 1731 with baseline cataract or incident cataract surgery within 1 year, and 170,270 with missing data (Fig. 1). 

Figure 1.

 

Flowchart of population selection from the UK Biobank.

Assessment of Early-Life Tobacco Smoke Exposures

Information on early-life tobacco smoke exposures was obtained from a touchscreen self-administered questionnaire in the UK Biobank at baseline. In utero tobacco smoke exposure was assessed by a questionnaire about early life factors with the question “Did your mother smoke regularly around the time when you were born?” Early initiation of smoking was determined by a questionnaire about lifestyle and environment with the question “How old were you when you first started smoking on most days?” and were classified by smoking initiation in childhood (5–14 years), adolescence (15–18 years), and adulthood (18 years or older).⁹ The types of tobacco smoke exposure, such as manufactured cigarettes, hand-rolled cigarettes, cigars, and pipes, were identified through a lifestyle and environmental questionnaire. Furthermore, the daily number of cigarettes smoked was also ascertained. 

Ascertainment of Incident Cataract

Cataract cases in the UK Biobank were ascertained by combining hospital inpatient diagnoses and hospital inpatient operations. For hospital inpatient diagnoses, the codes for International Classification of Diseases (ICD) were used to identify incident cataract (ICD-10 codes: H250, H251, H252, H258, H259, H261, H262, H263, H264, H268, H269, H280, H281, and H282; and ICD-9 codes: 366, 3662, 3664, 3665, 3668, and 3669), including senile cataract, traumatic cataract, drug-induced cataract, diabetic cataract, and other specified cataract. Incident cataract surgery was ascertained through linkage to hospital operation records, namely, Hospital Episode Statistics for England, Scottish Morbidity Records for Scotland, and Patient Episode Database for Wales. Participants were determined to have had cataract surgery if they had an Office of Population Censuses and Surveys Classification of Interventions and Procedures (OPCS-4) Classification of Interventions and Procedures 4 code (C71, C72, C73, C74, and C75). We excluded participants with cataract surgery up to 1 year after the baseline assessment visit because this may indicate significant cataract having been present at baseline. Participants with self-reported cataract at baseline were also excluded from this study. It was defined in either eye, and the date of the event was defined as the date of first eye cataract in participants with a diagnosis of cataract or cataract surgery. 

Assessment of Covariates

Sociodemographic factors, including age, sex, ethnicity (White or other ethnicities), and education, were self-reported. Townsend deprivation index (an area-based proxy measure for socioeconomic status) and body mass index (BMI) were collected during the initial assessment visit. Participants completed a detailed questionnaire on a touch-screen computer about their lifestyle, including frequency of alcohol consumption and physical activity. Alcohol drinker status was identified through linkage to “alcohol drinker status” and recorded as never or former/current alcohol drinking. Physical activity was categorized as low, moderate, and high in the UK Biobank.¹⁰ 

Systemic conditions at baseline were defined based on self-reported data, interviews, or hospital inpatient records. Participants were asked whether they had ever been told by a doctor that they had certain common medical conditions, including hyperlipidemia, hypertension, and diabetes. Hyperlipidemia was identified through self-reported data, cholesterol ≥ 6.21 mmol/L, or taking statins and other antihyperlipidemia medication. Hypertension was identified through self-reported data, systolic blood pressure ≥ 130 mm Hg or diastolic blood pressure ≥ 80 mm Hg, or antihypertensive medication. Diabetes was identified through linkage to “diabetes diagnosed by the doctor,” HbA1c ≥ 48 mmol/mol, and/or use of insulin and other diabetes-related medication at baseline.¹¹ Health status was classified into poor or fair, and good or excellent. 

Statistical Analysis

Baseline demographic characteristics were described as frequency (percentage) and means ± standard deviations (SDs). Student’s t-tests were used to test the difference in continuous variables and χ² test in categorical variables. Differences in baseline demographic characteristics among groups were evaluated using one-way ANOVA. 

We conducted a survival analysis, and participants were censored at the following end points: date of cataract diagnosis, date of first cataract surgery, date of death, date of loss to follow-up, or end of the data linkage (April 28, 2021), whichever came first. Kaplan-Meier survival curves were plotted to visualize risk stratification. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for cataract incidence with tobacco smoke exposure. We carried out a two-step analysis. The first step was to compare the risk of incident cataract in participants with tobacco smoke exposures with that of never-smokers. The second step was to estimate the association between in utero/childhood/adolescence/adulthood tobacco smoke exposure and incident cataract. We further assessed the risk of incident cataract with the consumption of different types of tobacco. In addition, the restrictive cubic spline curve was used to analyze the dose-effect relationship between the number of cigarettes smoked daily and the incidence of cataract. All associations were examined using model 1 and model 2. Model 1 was adjusted for age and sex at recruitment. Model 2 included adjustments for model 1 plus ethnicity, education, BMI, Townsend deprivation index, physical activity, drinking status, history of hypertension, history of hyperlipidemia, history of diabetes, and health status. We conducted a sex stratification analysis to assess the association between smoking and cataract events in both male and female participants, considering the connection between sex, tobacco smoke exposure, and cataract risk. 

In sensitivity analysis, we examined the association between tobacco and incident cataract in individuals diagnosed by the OPCS-4 records only. We also conducted sensitivity analysis by first excluding incident cataract cases diagnosed with traumatic cataract, drug-induced cataract, and diabetic cataract, then further excluded participants with low educational levels and hyperopia. Both are adjusted by model 3. Model 3 was adjusted for model 2 plus nutrition condition, sleep condition, and diet condition. Data analyses were conducted using Stata (version 17; StataCorp, College Station, TX) and R (version 4.3.1; R Foundation for Statistical Computing, https://www.r-project.org/, Vienna, Austria). A 2-tailed P < 0.05 was considered significant. 

Results

Baseline Characteristics

A total of 330,528 participants (55.4% female participants) aged 40 to 70 years (mean ± SD = 56.4 ± 8.3) were included in this analysis (see Fig. 1). The median follow-up time was 12.04 years, during which 14,754 participants were diagnosed with cataract. Table 1 showed the characteristics of the study participants. One-way ANOVA shows age, sex, ethnicity, education, BMI, Townsend index, physical activity, drinking status, hypertension, hyperlipidemia, diabetes, and health status, and all had intergroup differences among groups (all P < 0.05). 

Table 1.

 

Comparison of Baseline Characteristics of Study Participants Among Different Groups of Tobacco Smoke Exposure

 

Table 2.

 

Cox Proportional Hazards Model of Tobacco Smoke Exposure With Cataract by Sex Stratification

 

Different Stages of Early-Life Tobacco Smoke Exposures and Incident Cataract

In model 1, participants who have tobacco smoke exposures were more likely to develop cataract than never-smokers (HR = 1.16, 95% CI = 1.12–1.20, P < 0.001). After adjusting for all covariables in model 2, participants who have tobacco smoke exposures were more likely to develop cataract (HR = 1.13, 95% CI = 1.09–1.18, P < 0.001) compared with never-smokers (Fig. 2). The associations between early-life tobacco smoke exposure and incident cataract among tobacco smokers and never-smokers are also shown in Figure 2. Compared with the never-smokers, participants who had exposure to tobacco in childhood (HR = 1.23, 95% CI = 1.14–1.33), adolescence (HR = 1.16, 95% CI = 1.11–1.21), and adulthood (HR = 1.12, 95% CI = 1.06–1.19) had a higher risk of cataract. In the model 2 adjusted analysis, participants who had tobacco smoke exposure in childhood (HR = 1.10, 95% CI = 1.03–1.21), adolescence (HR = 1.15, 95% CI = 1.10–1.21), and adulthood (HR = 1.12, 95% CI = 1.05–1.19) had a higher risk of incident cataract compared with those who were never-smokers (all P < 0.05). The Kaplan-Meier curves are shown in Supplementary Figure S1. Significant differences were observed. 

Figure 2.

 

Cox proportional hazards model of different groups of tobacco smoke exposure with cataract. Model 1 is adjusted for age, sex. Model 2 is adjusted for age, sex, ethnicity, education, body mass index, Townsend index, physical activity, drinking status, history of hypertension, history of hyperlipidemia, history of diabetes, and health status. Bold values denote statistical significance at the P < 0.05 level. CI, confidence interval.

In the sex-stratified analysis, the male participants had a higher risk of cataract when exposed to tobacco smoke in childhood (HR = 1.10, 95% CI = 1.00–1.19), adolescence (HR = 1.17, 95% CI = 1.05–1.31), and adulthood (HR = 1.22, 95% CI = 1.11–1.3, all P < 0.05). Female participants had a higher risk of cataract when exposed to tobacco smoke in adolescence (HR = 1.18, 95% CI = 1.10–1.26, P < 0.001; Table 2). In addition, there was no interaction between sex and early-life tobacco smoke exposures in different stages for the cataract incidence at different ages (all P values for interactions > 0.05). 

Table 3.

 

Cox Proportional Hazards Models of Different Types of Tobacco Smoke Exposure With Cataract

 

Different Types of Tobacco Smoke Exposures and Incident Cataract

We then examined the association of consumption of different tobacco smoke types with incident cataract. Compared with never-smokers, the risk of cataract was 12% higher among manufactured cigarette consumers (HR = 1.12, 95% CI = 1.08–1.17). Likewise, compared with never-smokers, hand-rolled cigarette consumers had a 20% higher risk of incident cataract (HR = 1.20, 95% CI = 1.05–1.36). Similarly, consumption of cigars or pipes had a 26% higher risk of incident cataract compared with never-smokers (HR = 1.26, 95% CI = 1.11–1.44; Table 3). 

The Number of Cigarettes and Incident Cataract

We used a restricted cubic spline plot to flexibly model and visualize the dose-response relationship between the number of cigarettes smoked daily and the incidence of cataract (Supplementary Fig. S2). The ordinate was the OR (0–3), and the abscissa was the number of cigarettes previously smoked daily (0–100). As shown in Supplementary Figure S2, the incidence of cataract increased with the increasing number of cigarettes previously smoked daily. 

Sensitivity Analyses

Given that the surgical diagnosis of cataract indicates a severe degree appropriate for surgery, we conducted a sensitivity analysis using only OPCS-4 records. Significant associations persisted among participants who underwent cataract surgery. Compared with never-smokers, participants with early-life tobacco smoke exposures had a higher risk of developing cataract in childhood (HR = 1.11, 95% CI = 1.01–1.22, P = 0.036), adolescence (HR = 1.16, 95% CI = 1.10–1.22, P < 0.001), and adulthood (HR = 1.11, 95% CI = 1.04–1.19, P = 0.002; Supplementary Table S1). After excluding incident cataract cases diagnosed with traumatic cataract, drug-induced cataract, and diabetic cataract, and adjusting for more covariates, the results were almost consistent with those of the main analysis (Supplementary Table S2). The results were also similar after further excluding participants with low educational levels and hyperopia (Supplementary Table S3). 

Discussion

In this large prospective study, we explored tobacco smoke exposure and the risk of cataract in a long-term follow-up. We found that exposure to tobacco smoke increased the risk of cataract compared to non-exposed individuals. Childhood, adolescence, and adulthood exposure to tobacco smoke had a 10%, 15%, and 12% higher risk of incident cataract when compared with never-smokers, respectively. Male participants had a higher risk of cataract when they were exposed to tobacco smoke in childhood, adolescence, and adulthood. In addition, we found that exposure to cigars or pipes had the greatest risk of cataract, followed by hand-rolled cigarettes and manufactured cigarettes. 

Accumulating studies have indicated that early-life environmental or behavioral factors have a profound and lasting impact on disease susceptibility in adulthood.^12–14 In our study, we did not find a relationship between in utero tobacco smoke exposure and the risks of cataract incidence. However, tobacco smoke exposure in childhood and adolescence may increase cataract risks by causing damage to the lens in a critical developmental period.¹⁵ Our study showed that an earlier initiation of smoking (compared with never-smokers) was associated with a higher incidence of cataract, especially in childhood after adjusting for age and sex. Starting smoking in adolescence and adulthood also increases the risk of cataract by 15% and 12%, respectively. Observational and prospective studies have found an association between smoking and cataract risk, but there is little research on the association between the age at which smoking starts and cataract.^7,16 This may be due to the direct inhalation of tobacco smoke through the ocular surface or in vivo exposure to tobacco smoke, which cause DNA damage and changes in metal ions within the lens, making the lens more sensitive to tobacco smoke during childhood and adolescence.^17–19 Additionally, starting smoking in early life may cause greater cumulative exposure to tobacco smoke.¹⁷ Moreover, children and adolescents are less metabolically active to nicotine than adults, so they have longer exposure to nicotine in the central nervous system and are more prone to addiction, which may further increase tobacco smoke exposure doses in adulthood and cause greater lens damage.^20–22 

Studies suggest that sex differences in tobacco smoke exposure may also have profound and lasting effects on future disease susceptibility.^23–25 We found that male participants, regardless of the stage of exposure to tobacco smoke, have a higher risk of cataract. In female participants, the difference is significant only during adolescence. Compared to childhood exposure, adolescents exposed to smoking had a larger sample size. This may be a reason for not seeing that female subjects have a higher risk of cataract in childhood in model 2 while seeing it in model 1. The different susceptibility to tobacco smoke could reflect a gender difference in the metabolism of cigarette smoke or the inflammatory response to cigarette smoking due to hormonal effects.^24,26 In addition, different types of tobacco smoke exposure also contribute to inconsistent cataract rates, and we found that exposure to cigars or pipes had the highest risk of cataract. This may be because harmful compounds are present in different amounts and varieties in different types of tobacco smoke with the irreplaceable structural proteins of the lens slowly accumulating damage from the encounter with reactive molecular species.²⁷ The mean deliveries per liter of smoke and tar, nicotine, and carbon monoxide were highest for cigars, followed by hand-rolled and manufactured cigarettes, which supports our conclusion.²⁸ At last, we found a dose-effect relationship between the number of cigarettes smoked daily and cataract incidence, which means that the number of cigarettes smoked daily could be a significant predictor of the progression of cataract.²⁹ 

Most previous studies examining the association between tobacco smoke and cataract have been limited by the cross-sectional designs.^6,7 In the Andhra Pradesh eye disease study from India, tobacco smoking was strongly associated with a higher prevalence of nuclear and cortical cataract and a history of prior cataract surgery.⁶ Similarly, in the Korea National Health and Nutrition Examination Survey, current smoking was correlated with cataract.⁷ There have been only a small number of cohort studies that examined the relationship between tobacco smoke and cataract.^30,31 These studies have a small sample size, were mainly evaluated in Australia and Asia, and have reported inconsistent findings.^30,32 In a population-based cohort study in Australia with 9578 participants, smoking was found to be related to the cataract and cataract surgery in the general population.³² In contrast, in the Beijing Eye Study with 3251 subjects, the incidence of cataract was not significantly (P = 0.95) associated with smoke.³⁰ Furthermore, these studies did not report an association between early-life exposure to tobacco smoke and cataract. Our study is longitudinal in design and has a very large sample size in the European population. We demonstrated the relationship between tobacco smoke and cataract incidence in this large population-based cohort study, especially in early-life tobacco smoke exposure. Unlike previous studies, we excluded participants who had undergone cataract surgery up to 1 year from baseline to minimize the chance of reverse causality underlying our identified associations. Additionally, we evaluated the association between different tobacco smoke types with incident cataract. 

The present study has several limitations. First, because of the observational design of our study, causal relationships cannot be established based on our findings. Second, this study was limited to the method for assessing cataract, which was based on hospital inpatient diagnoses and hospital inpatient operations from the UK Biobank. Although previous studies have shown associations between different subtypes of cataract and tobacco smoke, it remains to be explored whether tobacco smoke exposure has diverse effects on incident cataract in different cataract subtypes. Third, although multiple risk factors for cataract were adjusted for in the analysis, potential confounding from other sources, such as levels of particulate matter, was unpreventable. Thus, residual confounding may explain our observational associations. Last, the analysis was restricted to European ancestry participants, thus, our findings need to be validated in other ethnic groups. 

Conclusions

We provide robust longitudinal evidence that in childhood and adolescence exposure to tobacco smoke elevates cataract incidence in older age, leveraging a large community-dwelling elderly cohort. Emphasizing the crucial role of early-life factors in influencing cataract risk later in life, our findings suggest anti-smoking publicity and legislation should start as early as childhood and adolescence. Future studies need to further collect detailed early-life exposure information to clarify the underlying genetic mechanisms. 

Acknowledgments

The authors thank all the participants and staff for their cooperation and assistance in the study. 

This research was conducted using the UK Biobank Resource (Application Number: 86091). 

Funded by the National Natural Science Foundation of China (82171075, 82301260, 82271125), China Postdoctoral Science Foundation (2024T170185), the Science and Technology Program of Guangzhou, China (20220610092), the launch fund of Guangdong Provincial People's Hospital for NSFC (8217040546, 8220040257, 8217040449, 8227040339), Personalized Medical Incubator Project, The fund for Precison Medicine Research and Industry Development in SIMQ (2023-31), Guangdong Basic and Applied Basic Research Foundation (2023B1515120028). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. 

Author Contributions: C.L., Y.W., X.Z., and H.Y. conceptualized the study and all authors contributed to the study design. C.L., Y.W., and Z.D. compiled the data and performed statistical analyses with supervisory input from H.Y. C.L. and H.Y. had access to and verified the underlying data used in this study. All authors contributed to the finalization of statistical models and interpretation of findings. C.L. wrote the first draft of the manuscript, and Y.W., X.Z., Z.D., S.W., Z.L., Y.F., H.L., X.Z., and H.Y. critically reviewed and edited the manuscript. All authors had full access to all the data in the study, approved the final manuscript, and accepted responsibility for the decision to submit for publication. 

Data Availability: UK Biobank data are available through application to the database https://www.ukbiobank.ac.uk/. 

Disclosure: C. Lai, None; Y. Wang, None; X. Zeng, None; Z. Du, None; S. Wang, None; Z. Lin, None; Y. Hu, None; Y. Fang, None; X. Zhang, None; H. Yu, None