Fish Consumption and Age-Related Macular Degeneration Incidence: A Meta-Analysis and Systematic Review of Prospective Cohort Studies
Abstract
:1. Introduction
2. Methods
2.1. Search Strategy and Inclusion Criteria
2.2. Data Extraction and Assessment of Study Quality
2.3. Statistical Methods for the Meta-Analysis
3. Results
3.1. Identification and Selection of Studies
3.2. Study Characters and Quality Scores
3.3. Fish Consumption and Risk of AMD
3.4. Heterogeneity and Sensitivity Analysis
3.5. Dose-Response Meta-Analysis
3.6. Publication Bias
4. Discussion
5. Conclusions
Conflicts of Interest
References
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Author, Year | Study; Follow-up | Duration | Study Design | Site | Age (Year) | Gender, Percent | No. of Case/Cohort | Adjustments of Confounding Factors | Question | Exposure Definition | Study Quality * |
---|---|---|---|---|---|---|---|---|---|---|---|
Tan et al., 2009 [23] | Melbourne Collaborative Cohort Study > 10 years | 1992–2004 | Population-based | Australia | ≥49 | F: 57% | 232/2684 | Age, sex, and smoking | 145-item FFQ | <1/M (Q1) vs. ≥3/W (Q3) | 8 |
Seddon et al., 2003 [24] | AREDS, 4.6 years | 1989–1998 | Hospital-based | USA | ≥65 | F: 61% | 51/312 | Age-sex group, education, body mass index, systolic blood pressure, cardiovascular disease, log energy, protein intake, energy-adjusted log beta carotene intake, alcohol intake, physical activity, and initial age-related macular degeneration grade, total intake of energy-adjusted log zinc, vitamin C, and vitamin E. | 61-item FFQ | <1/W (Q1) vs. ≥2/W (Q3) | 8 |
Christen et al., 2011 [25] | Women’s Health Study, 10 years | 1993–2004 | Population-based | USA | ≥45 | F:100% | 235/38257 | Age, randomized treatment assignment, smoking, alcohol use, BMI, menopausal status and use of HT, history of hypertension, history of high cholesterol, history of diabetes multivitamin use, history of eye exam in the last 2 years | 131-item FFQ | <1/M (Q1) vs. >1/M (Q3) | 7 |
SanGiovanni et al., 2008 [26] | Massachusetts Eye and Ear Infirmary, 6.3 years | 1992–1998 | Population-based | USA | 55–80 | F: 56.1% | 311/2623 | Age, sex, AREDS therapy group, education, race, BMI, smoking, antacid use, iris colour, DHA intake, EPA intake, combined DHA-EPA intake | 90-item FFQ | <1/M (Q1) vs. >2/M (Q5) | 9 |
Chong et al., 2009 [27] | Nurses’ Health Study, 13 years | 1990–2006 | Population-based | Australia | 66–85 | F: 61% | 1099/7098 | Age, sex, smoking (current, past, or never), energy, vitamin C, vitamin E, carotene, zinc, lutein, zeaxanthin, and supplements (vitamin C, vitamin E, cod liver oil and fish oil (yes/no)) | 121-item FFQ | 0–0.5/W (Q1) vs. ≥2/W (Q3) | 9 |
Cho et al., 2001 [28] | Blue Mountains Eye Study, 12 years | 1984–1996 | Population-based | USA | 56 | F: 59.0% | 567/73056 | 2-year period, age , smoking, energy and lutein and zeaxanthin intakes, BMI, profession, physical activity (metabolic equivalent quintiles), and alcohol intake | 130-item FFQ | ≤1/M (Q1) vs. ≥4/W (Q5) | 9 |
Arnarsson et al., 2006 [29] | Reykjavik Eye Study, 5 years | 1996–2001 | Population-based | Iceland | ≥50 | F: 55.8% | 134/1379 | Age, smoking, and sex | 16-item FFQ | ≤1/M (Q1) vs. ≥4/W(Q4) | 7 |
Wang et al., 2014 [30] | Rotterdam Study, 15 years | 1990–2001 | Population-based | The Netherlands | ≥55 | F: 58.8% | 1573/3579 | Age- and sex-adjusted | 170-item FFQ | <1/W (Q1) vs. ≥1/W(Q2) | 8 |
Subgroups | No. of Studies | Summary Effect | Study Heterogeneity | ||
---|---|---|---|---|---|
RR (95% CI) | p Value | I2, % | p Value | ||
Data source | |||||
Population based | 7 | 0.75; (0.63–0.89) | 0.001 | 56.7 | 0.031 |
Hospital based | 1 | 0.88 (0.49–1.59) | 0.672 | - | - |
Country | |||||
USA | 4 | 0.84 (0.72–0.98) | <0.001 | 0 | 0.724 |
Australia | 2 | 0.74 (0.48–1.14) | 0.174 | 68.50 | 0.075 |
Iceland | 1 | 0.61 (0.38–0.98) | 0.002 | - | - |
Netherlands | 1 | 0.98 (0.83–1.15) | 0.787 | - | - |
Follow-up | |||||
>10 years | 5 | 0.81 (0.67–0.97) | 0.024 | 53.6 | 0.072 |
< 10 years | 3 | 0.70 (0.51–0.97) | 0.033 | 0 | 0.638 |
Subgroups | Summary Effect | Study Heterogeneity | ||||
---|---|---|---|---|---|---|
RR | 95% Lower Limiter | 95% Upper Limiter | p Value | I2, % | p Value | |
Fish types | ||||||
Dark meat fish | 0.68 | 0.46 | 0.99 | 0.047 | 53.70 | 0.091 |
Tuna fish | 0.58 | 0.47 | 0.71 | <0.001 | 0 | 0.934 |
Other dark meat fish | 0.96 | 0.75 | 1.24 | 0.34 | - | - |
Non-dark meat fish | 0.82 | 0.65 | 1.03 | 0.088 | 0.80 | 0.315 |
Processing | ||||||
Baked or broiled | 0.98 | 0.87 | 1.11 | 0.762 | 0 | 0.488 |
Fried fish | 0.97 | 0.83 | 1.14 | 0.731 | 0 | 0.508 |
Smoked fish | 0.88 | 0.54 | 1.43 | 0.600 | 0 | 0.974 |
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Zhu, W.; Wu, Y.; Meng, Y.-F.; Xing, Q.; Tao, J.-J.; Lu, J. Fish Consumption and Age-Related Macular Degeneration Incidence: A Meta-Analysis and Systematic Review of Prospective Cohort Studies. Nutrients 2016, 8, 743. https://doi.org/10.3390/nu8110743
Zhu W, Wu Y, Meng Y-F, Xing Q, Tao J-J, Lu J. Fish Consumption and Age-Related Macular Degeneration Incidence: A Meta-Analysis and Systematic Review of Prospective Cohort Studies. Nutrients. 2016; 8(11):743. https://doi.org/10.3390/nu8110743
Chicago/Turabian StyleZhu, Wei, Yan Wu, Yi-Fang Meng, Qian Xing, Jian-Jun Tao, and Jiong Lu. 2016. "Fish Consumption and Age-Related Macular Degeneration Incidence: A Meta-Analysis and Systematic Review of Prospective Cohort Studies" Nutrients 8, no. 11: 743. https://doi.org/10.3390/nu8110743
APA StyleZhu, W., Wu, Y., Meng, Y.-F., Xing, Q., Tao, J.-J., & Lu, J. (2016). Fish Consumption and Age-Related Macular Degeneration Incidence: A Meta-Analysis and Systematic Review of Prospective Cohort Studies. Nutrients, 8(11), 743. https://doi.org/10.3390/nu8110743