Protective Effect of Dietary Calcium Intake on Esophageal Cancer Risk: A Meta-Analysis of Observational Studies
Abstract
1. Introduction
2. Materials and Methods
2.1. Search Strategy
2.2. Study Selection
2.3. Data Extraction
2.4. Statistical Analysis
3. Results
3.1. Characteristics of the Included Studies
3.2. Meta-Analysis of Calcium Intake and Esophageal Cancer Risk
3.3. Heterogeneity Analysis
3.4. Sensitivity Analysis and Publication Bias
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflict of Interest
References
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Author, Year | Country | Study-Design | Pathological Type | Source of Control | Dietary Assessment | Participants (Cases) | Comparison | OR or RR (95% CI) | NOS Score | Adjustment for Covariates |
---|---|---|---|---|---|---|---|---|---|---|
Hashemian, 2015 [8] | Iran | Cohort | ESCC | PB | FFQ-116 items, validated | 47,204 (201) | ≥1048.0 vs. <409 (mg/day) | 0.49 (0.29–0.82) | 8 | Age, sex, total energy, place of residence, smoking, wealth score, ethnicity, opiate use, BMI, education, marital status, physical activity score, and fruit and vegetable intakes |
Mulholland, 2011 [20] | Ireland | Case–control | EAC | PB | FFQ-101 items, validated | 252 (218) | ≥1262.0 vs. <929.3 (mg/day) | 0.88 (0.38–2.03) | 6 | Age, sex, energy intake, smoking status, BMI, education, occupation, alcohol, regular non-steroidal anti-inflammatory drug use, Helicobacter pylori infection, energy-adjusted glycemic index intake, energy-adjusted saturated fat intake, and location |
Wolfgarten, 2001 [21] | Germany | Case–control | EAC | PB | DHQ, NA | 100 (40) | >1590 vs. <986 (mg/day) | 0.4 (0.1–1.3) | 7 | Age, residence, and nationality |
Wolfgarten, 2001 [21] | Germany | Case–control | ESCC | PB | DHQ, NA | 100 (45) | >1590 vs. <986 (mg/day) | 0.4 (0.1–1.1) | 7 | Age, residence, and nationality |
Graham, 1990 [22] | United states | Case–control | Mix type | PB | FFQ, NA | 174 (178) | >1028.5 vs. <543.5 (mg/day) | 2.15 (1.14–4.06) | 4 | Sex, age, education, smoking, and alcohol ingestion |
Franceschi, 2000 [23] | Italy | Case–control | ESCC | HB | FFQ-78 items, validated | 743 (304) | Q5 vs. Q1 | 1.0 (0.6–1.7) | 8 | Age, gender, area of residence, education, physical activity, BMI, tobacco smoking, alcohol drinking, and non-alcohol energy |
Jessri, 2011 [24] | Iran | Case–control | ESCC | HB | FFQ-125 items, validated | 96 (47) | T3 vs. T1 | 0.49 (0.15–0.87) | 7 | Age, sex, gastroesophageal reflux disease symptoms, BMI, smoking status, smoking intensity and duration (pack-years), physical activity, and education level |
Chen, 2002 [25] | United states | Case–control | EAC | PB | DHQ, validated | 449 (124) | Q4 vs. Q1 | 0.5 (0.2–0.9) | 7 | Age, age squared, gender, respondent type, BMI, alcohol use, tobacco use, education level, family history of respective cancers, and vitamin supplement use |
Park, 2009 [26] | United states | Cohort | Mix type | PB | FFQ-124 items, validated | 29,3439 (468) | >1247 vs. <478 (mg/day) | 0.66 (0.49–0.90) | 9 | Smoking status, time since quitting smoking, smoking dose, antacid use, personal history of diabetes, and hypertension |
Lu, 2006 [27] | China | Case–control | ESCC | PB | FFQ-97 items, NA | 415 (218) | ≥344 vs. <157 (mg/day) | 0.82 (0.38–1.75) | 8 | Age, gender, educational level, income, BMI, total energy intake, smoking, and drinking. |
Rogers, 1993 [32] | United states | Case–control | Mix type | PB | FFQ, NA | 593 (127) | >1419 vs. <571 (mg/day) | 0.6 (0.3–1.5) | 6 | Age, sex, pack-years of cigarette use, drink-years of alcohol, energy intake, β-carotene intake, and ascorbic acid intake |
Tuyns, 1987 [28] | France | Cohort | mix type | PB | DHQ, validate | 2788 (743) | >1000 vs. <600 (mg/day) | 0.84 (0.56–1.25) | 3 | Age, alcohol consumption, and tobacco smoking |
Tzonou A 1996 [31] | Greece | Case–control | ESCC | HB | FFQ-115 items, validated | 243 (43) | Q5 vs. Q1 | 0.92 (0.64–1.32) | 7 | Gender, age, birthplace, schooling, height, analgesics, coffee drinking, alcohol intake, tobacco smoking, and energy intake. |
Tzonou A 1996 [31] | Greece | Case–control | EAC | HB | FFQ-115 items, validated | 256 (56) | Q5 vs. Q1 | 1 (0.72–1.4) | 7 | Gender, age, birthplace, schooling, height, analgesics, coffee drinking, alcohol intake, tobacco smoking, and energy intake, though not mutually |
Zhang, 1997 [29] | United States | Case–control | EAC | HB | HHHQ, validated | 189 (29) | Q4 vs. Q1 | 1.3 (0.5–3.3) | 5 | Age, sex, race, education, total dietary intake of calories. Smoking, alcohol use, and BMI |
Tang, 2014 [30] | China | Case–control | mix type | HB | FFQ-137 items, validated | 739 (359) | >470 vs. <260 (mg/day) | 0.75 (0.52–1.1) | 8 | Age, gender, education level, BMI, total energy intake, smoking status, alcohol drinking, and family history of cancer in first-degree relatives. |
Hu,1994 [33] | China | Case–control | mix type | HB | FFQ-32 items, NA | 588 (196) | Q4 vs. Q1 | 0.8 (0.4–1.4) | 7 | Alcohol intake, smoking. and family income |
Subgroups | No. of Studies | No. of Cases | Pooled ORs (95% CI) | p | Heterogeneity Test | ||
---|---|---|---|---|---|---|---|
Chi-Square | I2 | Phet | |||||
All studies | 17 | 3396 | 0.80 (0.71, 0.91) | 0.001 | 24.11 | 33.6% | 0.087 |
Location | |||||||
Europe | 7 | 1449 | 0.90 (0.75, 1.08) | 0.262 | 3.97 | 0.0% | 0.681 |
America | 5 | 926 | 0.88 (0.51, 1.49) | 0.625 | 13.83 | 71.1% | 0.008 |
Asia | 5 | 1021 | 0.67 (0.52, 0.86) | 0.002 | 2.80 | 0.0% | 0.591 |
Study design | |||||||
Cohort | 3 | 1412 | 0.67 (0.54, 0.84) | 0.000 | 2.62 | 23.6% | 0.270 |
PBCC | 7 | 950 | 0.84 (0.61, 1.14) | 0.261 | 13.68 | 56.2% | 0.033 |
HBCC | 7 | 1034 | 0.89 (0.74, 1.06) | 0.182 | 4.00 | 0.0% | 0.677 |
Pathological type | |||||||
ESCC | 6 | 858 | 0.76 (0.60, 0.96) | 0.019 | 6.97 | 28.3% | 0.223 |
EAC | 5 | 467 | 0.89 (0.68, 1.16) | 0.381 | 4.84 | 17.4% | 0.304 |
Mixed type | 6 | 2071 | 0.84 (0.63, 1.13) | 0.252 | 11.50 | 56.5% | 0.042 |
Dietary assessment | |||||||
Validated method | 11 | 2592 | 0.79 (0.69, 0.90) | 0.001 | 11.84 | 15.5% | 0.296 |
Not Validated method | 6 | 804 | 0.81 (0.48, 1.35) | 0.413 | 11.68 | 57.2% | 0.039 |
NOS score | |||||||
Low quality | 1 | 743 | 0.84 (0.56, 1.25) | 0.395 | 0.00 | N/A | N/A |
Moderate quality | 4 | 552 | 1.14 (0.63, 2.05) | 0.671 | 6.64 | 54.8% | 0.084 |
High quality | 12 | 2101 | 0.76 (0.66, 0.87) | 0.000 | 12.60 | 12.7% | 0.320 |
Adjustment for energy intake | |||||||
Yes | 8 | 1251 | 0.83 (0.70, 0.98) | 0.031 | 7.26 | 3.6% | 0.402 |
No | 9 | 2145 | 0.78 (0.58, 1.04) | 0.093 | 16.61 | 51.8% | 0.034 |
Adjustment forBMI | |||||||
Yes | 8 | 1500 | 0.72 (0.58, 0.90) | 0.003 | 7.16 | 2.2% | 0.413 |
No | 9 | 1896 | 0.85 (0.73, 0.99) | 0.037 | 15.57 | 48.6% | 0.049 |
Publication year | |||||||
Before/in 2000 | 8 | 1676 | 0.97 (0.82, 1.16) | 0.767 | 8.75 | 20.0% | 0.271 |
After 2000 | 9 | 1720 | 0.64 (0.53, 0.77) | 0.000 | 4.58 | 0.0% | 0.802 |
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Li, Q.; Cui, L.; Tian, Y.; Cui, H.; Li, L.; Dou, W.; Li, H.; Wang, L. Protective Effect of Dietary Calcium Intake on Esophageal Cancer Risk: A Meta-Analysis of Observational Studies. Nutrients 2017, 9, 510. https://doi.org/10.3390/nu9050510
Li Q, Cui L, Tian Y, Cui H, Li L, Dou W, Li H, Wang L. Protective Effect of Dietary Calcium Intake on Esophageal Cancer Risk: A Meta-Analysis of Observational Studies. Nutrients. 2017; 9(5):510. https://doi.org/10.3390/nu9050510
Chicago/Turabian StyleLi, Qianwen, Lingling Cui, Yalan Tian, Han Cui, Li Li, Weifeng Dou, Haixia Li, and Ling Wang. 2017. "Protective Effect of Dietary Calcium Intake on Esophageal Cancer Risk: A Meta-Analysis of Observational Studies" Nutrients 9, no. 5: 510. https://doi.org/10.3390/nu9050510
APA StyleLi, Q., Cui, L., Tian, Y., Cui, H., Li, L., Dou, W., Li, H., & Wang, L. (2017). Protective Effect of Dietary Calcium Intake on Esophageal Cancer Risk: A Meta-Analysis of Observational Studies. Nutrients, 9(5), 510. https://doi.org/10.3390/nu9050510