4.1 Socioeconomic factor and cataract
Consistent with prior studies [6, 7, 8, 9, 10, 13, 19, 20, 21], the multivariate analysis revealed a strong association between increasing age and the prevalence of cataract. For self-reported diagnosed cataract, prevalence rates ranged from 11.4% (95% CI = 9.7–13.1) in adults aged 60–69 years to 60.7% (95% CI = 55.1–66.2) in those aged 90 and above. In comparison to research conducted in China, where the prevalence of cataract based on ophthalmological examination, rather than self-reported data, ranged from 24% in those aged 60–65 years to 75% in individuals aged 85–89 years [22]. According to GUS, a Polish Census Bureau, Poland's population continues to age [23], and therefore there might be an expected increase in the number of individuals affected by cataract [1].
Our research, along with other relevant studies, indicated a higher prevalence of cataract diagnosis among women compared to men [9,11,21,24,25,]. Some studies suggest that women, on average, have longer lifespans than men, consequently placing them at a higher risk of developing age-related eye conditions [1]. Moreover, analysis of population-based surveys conducted in low- and middle-income countries consistently reveals that women are significantly less likely than men to undergo cataract surgery [26, 27]. We have previously addressed this gender disparity in our published work [27].
Our research showed that there was a correlation between living in rural areas and diminished risk of self-reported cataract. This was also evidenced in other studies that assessed cataract prevalence through surveys [6, 8]. This correlation may indicate that factors associated with rural living, such as reduced exposure to environmental pollutants, less screen time, or potentially even dietary differences, could have a protective effect against cataract development. However, we couldn't establish causation using these cross-sectional data.
In our view, this correlation could stem from individuals residing in rural areas having limited access to healthcare, resulting in lower awareness of the disease compared to those in urban areas. Studies employing slit lamp examination found no discrepancy in cataract prevalence between rural and urban dwellings [19, 28].
The prevalence of self-reported cataract in univariate logistic regression analysis was also found to be associated with primary education, self-reported poverty, medium, and low QoL. However, these factors did not demonstrate significance in the multivariate regression analysis, as reported in another study [7, 13].
4.2 Comorbidities and cataract
Our study corroborated the conclusions of prior research, indicating a higher prevalence of cataract among individuals with hypertension [6, 7, 8, 9, 25, 29, 30] and diabetes mellitus [6, 7, 8, 9, 10, 11, 20, 21, 31, 32, 33, 34]. Multivariate logistic regression analysis indicated that the prevalence of cataract was 1.47 times higher for individuals with diabetes and 1.20 with hypertension. Cataract formation in individuals with diabetes seemed to be related to hyperglycemia or to increased senile lens opacity [31, 34]. Previous studies show that diabetic patients are 2–5 times more at risk for cataract formation and are more likely to get it at an earlier age [33, 34]. Hypertension can cause cataract by inducing intense systemic inflammation [35]. Although several plausible mechanisms have been proposed based on laboratory results, the conclusions from epidemiologic studies remain inconsistent [30].
Our analysis revealed a relatively higher prevalence of self-reported diagnosed cataract among elderly patients with PNS, a finding confirmed by univariate regression analysis. However, there was no significant difference observed in multivariate logistic regression analysis. Also, our study found no difference between individuals with obesity and those with normal BMI. Other studies done in the areas of obesity, malnutrition and cataract show similar results. For example, in older Australian population there was no causal association between obesity and cataract [36] and obesity wasn’t associated with cataract in other studies [6, 8, 12]. Another study that showed similar results to ours, suggested that there was an association between protein undernutrition and an increased risk of cataract [37]. The study indicated that low protein intake may induce deficiencies of specific amino acids that are needed to maintain the health of the lens [37]. Low BMI may be associated with an increased risk for cataract [21].
In our univariable analysis, we observed an association between hypercholesterolemia and a decreased prevalence of self-reported cataract; however, this did not maintain significance in the multivariate logistic regression analysis. The oldest individuals, who are more likely to have cataract, tend to have lower cholesterol levels [38], thereby contributing to the observed association of low cholesterol with the higher prevalence of cataract. This suggests that the association in the univariate analysis is likely confounded by age. Interestingly, our findings contrast with those of other studies. For instance, research conducted among the Chinese population suggested significantly higher total cholesterol concentration in age-related cataract (ARC) patients compared to those without ARC [25]. However, hypercholesterolemia in this study was defined as a total cholesterol serum level of ≥ 5.20 mmol/L [25]. Hence, disparities between our study and theirs may arise from differences in these criteria. Notably, another study has reported no association between dyslipidemia and cataract development [39].
Our research also examined stroke as another comorbidity. Although our study showed a higher prevalence of cataract among individuals with prior stroke, this association did not emerge as a significant independent factor in multiple analyses, which is concurrent with findings from other studies [7, 8]. However, based on some studies the association between cataract and individuals with a previous history of stroke remains unclear [7, 8].
Our study also revealed a higher prevalence of self-reported diagnosed cataract among individuals with symptoms of depression compared to those without, which is consistent with findings from prior research [8, 10]. Another study, however, explored the possibility of reverse causation [40]. It found that cataract may be a risk factor for major depressive disorder in the elderly, especially among the male population [40]. Research is also investigating the impact of antidepressants on the formation of cataract [41, 42].
4.3 Health behavior and cataract
Smoking is a risk factor with robust evidence regarding the higher prevalence of cataract [6, 20, 43], which was also found in our study. The odds of self-reported diagnosed cataract were 1.25 for tobacco users compared to their counterparts (95% CI: 1.08–1.44, p = 0.003).
Interestingly, other studies revealed that while there was a significant positive correlation between smoking and cataract, the cataractogenic impact was lower among former smokers compared to current smokers. This finding highlights the potential for reversibility in this context [20, 44].
Furthermore, in our study nondrinkers reported significantly higher rates of cataract (32.3%) compared to light and moderate to heavy drinkers. According to a meta-analysis of one study, heavy alcohol consumption significantly elevates the risk of ARC, while moderate consumption may offer protection against cataract [45]. This meta-analysis specifically included studies that assessed cataract through lens photographs or diagnosis by ophthalmologists, excluding those reliant on self-reported questionnaires for cataract measurement. Additionally, another study indicates that individuals with low to moderate alcohol consumption have a reduced likelihood of needing cataract surgery [46].
4.4 Strengths and limitations of study
Our study has several notable strengths. Firstly, we gathered data from a large, representative, community-dwelling population aged 60 and over, with a high proportion of older individuals. Secondly, our study not only examined conventional health hazards like diabetes and smoking but also delved into less commonly explored factors such as PNS and hypercholesterolemia.
Furthermore, we employed rigorous diagnostic criteria, diagnosing hypercholesterolemia and diabetes through laboratory tests, evaluating hypertension via blood pressure measurements, and assessing PNS and depression using specialized scales. Additionally, we utilized an approved Tanita BC-545N portable electronic scale to determine obesity.
Perhaps most importantly, the findings we obtained might fill a crucial gap in cataract epidemiology within Poland and enhance understanding of the risk factors associated with cataract in the Polish population. Consequently, our study holds the potential to aid in the prevention of cataract.
However, our study comes with several limitations. Firstly, the prevalence of cataract was determined solely based on participants' self-reported diagnoses by a doctor, potentially leading to an underestimation of the true prevalence. Similarly, data on the prevalence of stroke, sociodemographic factors, and health behaviors also relied on self-reported survey responses.
Additionally, symptoms of depression were excluded from the regression analysis due to the limited sample size of individuals assessed with the GDS scale. The size of the sample was impacted by the exclusion of individuals with MMSE scores below 19 from the analysis.
Lastly, it's important to note that our analysis is cross-sectional in nature, which means it only examines correlations between variables and doesn't establish causation. This design limitation precludes the assessment of causal relationships between variables within the study.