| Literature DB >> 25369040 |
E Song1, Hongpeng Sun2, Yong Xu2, Yana Ma2, Hong Zhu2, Chen-Wei Pan2.
Abstract
PURPOSE: Changes in lens may reflect the status of systemic health of human beings but the supporting evidences are not well summarized yet. We aimed to determine the relationship of age-related cataract, cataract surgery and long-term mortality by pooling the results of published population-based studies.Entities:
Mesh:
Year: 2014 PMID: 25369040 PMCID: PMC4219834 DOI: 10.1371/journal.pone.0112054
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Flow diagram showing the selection process for inclusion of studies.
Characteristics of the included studies.
| Author (year) | Study Name | Location | Ethnicity | Sample Size at baseline | Age at baseline (years) | Follow up period (yrs) | Incidence of mortality: N (%) |
| Knudtson et al (2006) | The Beaver Dam Eye Study | United States | Whites | 4926 | 43–84 | 14 | 1576 (32) |
| Nucci et al (2004) | The Priverno Eye Study | Italy | Italians | 860 | 45–69 | 7 | 44 (5.1) |
| Clemons et al (2004) | The Age-Related Eye Disease Study | United States | Whites | 4753 | 55–81 | 9 | 534 (11) |
| Cugati et al (2007) | The Blue Mountains Eye Study | Australia | Whites | 3654 | ≥49 | 11 | 1051 (28.9) |
| Hennis et al (2000) | The Barbados Eye Study | United States | Blacks | 4709 | 40–84 | 4 | 306 (6.8) |
| Borger et al (2003) | The Rotterdam Study | Netherlands | Whites | 6339 | ≥55 | 7 | 1359 (21.4) |
| West et al (2004) | The Salisbury Eye Project | United States | Whites and Blacks | 2520 | 65–84 | 2 | 147 (5.8 |
| Xu et al (2009) | The Beijing Eye Study | China | Chinese | 4439 | ≥40 | 5 | 143 (3.2) |
| McCarty et al (2001) | Melbourne Visual Impairment Project | Australia | White | 3271 | 40–98 | 5 | 231 (7.1) |
| Khanna et al (2013) | The Andhra Pradesh Eye Diseases Study | India | Indians | 4188 | ≥30 | 11 | 799 (19.1) |
Assessment of methodological quality of included studies.
| Study | Methods for selecting study participants | Methods for measuring exposure (cataract) | Methods for measuring outcome (mortality) | Design-specific sources of bias | Methods for controlling confounding, and statistical methods | Conflict of Interest |
| Knudtson et al (2006) | 4926 persons aged from 43 to 84 years in the period from September 15, 1987, to May 4, 1988, participated in the baseline examination of the population-based Beaver Dam Eye Study and were followed by about 10 years. | Wisconsin Grading System | National Death Index was used for matching against national death data. | Lost to follow up bias; survival bias; chance finding; residual confounding | Adjustments for age, sex, proteinuria, history of cancer, BMI, ratio of total to high-density lipoprotein cholesterol level, smoking, pulse rate,diabetes status, cardiovascular disease history, sedentary lifestyle, education, and systolic blood pressure were made using Cox proportional hazards models | None reported |
| Nucci et al (2004) | 860 legal residents of Priverno represented 70% of a random sample selected to participate in the Di.S.Co. Project—a population-based study on cardiovascular risk factors carried out by the Italian National Institute of Health. | Slit-lamp examination | Review of municipality records | Lack of statistical power; lost to follow up bias; survival bias; chance finding; residual confounding | Adjusting for age, gender, diabetes, serum cholesterol, high-density lipoprotein cholesterol, and cardiovascular diseases using Cox proportional-hazards regression model. | None reported |
| Clemons et al (2004) | A total of 4757 persons aged 55 to 81 years at enrollment were entered into the study at 11 clinical centers between 1992 and 1998 and were followed up by 9 years | The Age-Related Eye Disease Study (AREDS) system | Hospital records and death certificates. | Lost to follow up bias; chance finding; residual confounding | Cox proportional-hazards regression model adjusting for age, sex, race, education, smoking status, body mass index, diabetes mellitus, angina, cancer, and hypertension | None reported |
| Cugati et al (2007) | Australian adults aged 49 years and older at baseline in the Blue Mountains area were followed up for about 11 years | Wisconsin Grading System | The Australian National Death Index data | Lost to follow up bias; survival bias; chance finding; residual confounding | Cox regression models assessed associations between cataract and mortality risk during 11 years after adjusting for age, sex, BMI, hypertension, diabetes mellitus, current smoking, and history of stroke, angina, or myocardial infarction | None reported |
| Hennis et al (2000) | The studies were based on a simple random sample of Barbados African Americans, 40 to 84 years old. 4631 persons completed baseline examinations at the study site. Surviving members of the cohort were invited to return for a 4-year follow-up visit. | Lens Opacities Classification System II | Ministry of Health records | Lost to follow up bias; survival bias; chance finding; residual confounding | Cox proportional-hazards regression. age; gender; self-reported history of diabetes, cardiac disease, and stroke, or combination of these major illnesses; family history of diabetes and hypertension; body mass index; waist-to-hip ratio; alcohol use; and cigarette smoking. | None reported |
| Borger et al (2003) | A prospective cohort study of all residents aged 55 years and older from a suburb of Rotterdam | Lens Opacities Classification System II | Municipal registry and medical records. | Lost to follow up bias; chance finding; residual confounding | Cox proportional hazard regression analysis, adjusted for appropriate confounders (age, gender, smoking status, body mass index, cholesterol level, atherosclerosis, hypertension, history of cardiovascular disease, and diabetes mellitus) | None reported |
| West et al (2004) | A random sample of 2520 residents of Salisbury aged 65 to 84 years was recruited for a home interview and an examination at the SEE clinic. Two-year follow-up was conducted. | Wilmer grading scheme. | Hospital records and the National Death Index | Lost to follow up bias; survival bias; chance finding; residual confounding | Logistic regression model adjusting for age, sex, smoking, diabetes, cormorbid conditions and body mass index. | None reported |
| Xu et al (2009) | At baseline in 2001, the Beijing Eye Study examined 4439 subjects with an age of 40 years or more. In 2006, all study participants were invited for a follow-up examination. | The Age-Related Eye Disease Study (AREDS) system | Death certificate, hospital medical records | Lost to follow up bias; survival bias; chance finding; residual confounding | Logistic regression was used to investigate the associations of the binary dependent variable mortality with the continuous or categorical independent variables. | None reported |
| McCarty et al(2001) | Cluster random sampling was employed to identify nine pairs of census collector districts in the Melbourne statistical division from which to recruit eligible residents. Baseline examinations were conducted between 1992 and 1994. In 1997, 5 year follow up examinations of the original cohort commenced. | Wilmer grading scheme. | National Death Index | Lack of statistical power, lost to follow up bias; survival bias; chance finding; residual confounding | Multivariate logistic regression adjusting for age, sex, country of birth, smoking, hypertension, arthritis, best corrected visual acuity, age related maculopathy, glaucoma, uncorrected refractive error,diabetes,gout and cardiovascular disease. | None reported |
| Khanna et al (2013) | A large-scale prevalence survey of blindness and visual impairment was conducted between 1996–2000 on 10,293 individuals of all ages in three rural and one urban clusters in Andhra Pradesh, Southern India. More than a decade later, participants in rural clusters were traced to determine ocular risk factors for mortality. | Wilmer grading scheme. | Questionnaire | Lack of statistical power, lost to follow up bias; survival bias; chance finding; residual confounding | Cox-proportional hazard model after adjusting for age, gender, diabetes, hypertension, body mass index, smoking and education status | None reported |
Figure 2Random effects meta-analysis investigating the association between nuclear cataract and all-cause mortality.
HR = hazards ratio; CI = confidence interval.
Figure 3Random effects meta-analysis investigating the association between cortical cataract and all-cause mortality.
HR = hazards ratio; CI = confidence interval.
Figure 4Random effects meta-analysis investigating the association between posterior subcapsular cataract and all-cause mortality.
HR = hazards ratio; CI = confidence interval.
Figure 5Random effects meta-analysis investigating the association between cataract surgery and all-cause mortality.
HR = hazards ratio; CI = confidence interval.
Association between cataract and mortality by follow-up years and cataract diagnosis.
| Nuclear cataract | Cortical Cataract | Posterior Subcapsular Cataract | Cataract Surgery | |||||||||||||
| N | HR | 95% CI | I2 (%) | N | HR | 95% CI | I2 (%) | N | HR | 95% CI | I2 (%) | N | HR | 95% CI | I2 (%) | |
|
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| More than 5 years | 5 | 1.32 | 1.09, 1.60 | 68.0 | 5 | 1.2 | 1.10, 1.32 | 0 | 4 | 1.16 | 1.01, 1.33 | 0 | 6 | 1.33 | 0.98,1.80 | 82.1 |
| No more than 5 years | 4 | 1.73 | 0.84, 3.56 | 93.6 | 3 | 1.52 | 1.03,2.25 | 55 | 2 | 2.31 | 1.12, 4.77 | 61.9 | 2 | 1.06 | 0.56,2.00 | 45.6 |
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| By photographs | 7 | 1.50 | 1.09, 2.06 | 91.5 | 7 | 1.27 | 1.13, 1.44 | 36 | 6 | 1.37 | 1.04, 1.80 | 67.3 | 6 | 1.2 | 0.92, 1.56 | 74.8 |
| By Ophthalmologist clinically | 2 | 2.07 | 0.80, 5.35 | 56.3 | 1 | 0.75 | 0.21, 2.67 | - | 0 | - | - | - | 2 | 4.08 | 0.29, 58.07 | 89 |
N = number of studies RR = hazards ratio CI = confidence interval.