
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

39312350
MD-D-24-03031
00051
10.1097/MD.0000000000039775
3
5700
Research Article
Systematic Review and Meta-Analysis
Folate intake and the risk of endometrial cancer: A dose–response meta-analysis
Long Jiaye MM 1145618270@qq.com
a
Wang Du MM 3813527429@qq.com
a
Yang Miyang MM 1239448106@qq.com
b
Pang Yingrong MM 2282153735@qq.com
c
Li Meiqiong MM 1663574842@qq.com
d
Qin Shuxin MM 77153999@qq.com
a
https://orcid.org/0009-0009-7539-9961
Cui Kai MM a*
a Department of Interventional Radiology, Inner Mongolia Forestry General Hospital, The Second Clinical Medical School of Inner Mongolia University for The Nationalities, Yakeshi, Inner Mongolia, China
b Department of Radiology, The First Clinical Medical College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
c Department of Cardiology, Inner Mongolia Forestry General Hospital, The Second Clinical Medical School of Inner Mongolia University for The Nationalities, Yakeshi, Inner Mongolia, China
d Department of Gynaecology and Obstetrics, Inner Mongolia Forestry General Hospital, The Second Clinical Medical School of Inner Mongolia University for The Nationalities, Yakeshi, Inner Mongolia, China.
* Correspondence: Kai Cui, Department of Interventional Radiology, Inner Mongolia Forestry General Hospital, The Second Clinical Medical School of Inner Mongolia University for The Nationalities, Yakeshi, Inner Mongolia, China (e-mail: 3773028948@qq.com).
20 9 2024
20 9 2024
103 38 e3977522 3 2024
27 5 2024
30 8 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background:

The relationship between folate intake and risk of endometrial cancer (EC) is debatable. The goal of this study was to examine the relationship between folate consumption and EC and then conduct a dose–response analysis in accordance with this.

Methods:

Up until February 1, 2024, we conducted a thorough search using PubMed, EMBASE, the Cochrane Library, and Web of Science. Stata 14 software was used to analyze the findings of the article. The study protocol was registered in PROSPERO (CRD42024505943), and the meta-analysis was conducted in accordance with PRISMA guidelines.

Results:

Nine case-control studies and 6 cohort studies were included, comprising 379,570 participants and 8660 EC cases. The highest level of folate consumption was associated with a 10% reduction in the occurrence of EC (relative risk [RR] = 0.90, 95% confidence intervals [CIs]: 0.78–1.05, I2 = 63.2%) compared to the lowest level of intake. The association exhibited a statistically significant linear trend (P = .231), with a combined RR of 0.974 (95% CI: 0.968–0.981) for each daily intake of 50 µg folate.

Conclusion:

Folate intake may reduce the risk of EC.

dose–response analysis
endometrial cancer
folate intake
meta-analysis
OPEN-ACCESSTRUE
SDCT
==== Body
pmc 1. Introduction

Endometrial cancer (EC), as a common cancer in the female reproductive system, ranks second and third in terms of new cases and deaths among gynecological malignancies, respectively.[1] According to statistics, the number of new cases and deaths of EC worldwide in 2020 was 417,367 and 97,370, respectively.[1] Even with advancements in imaging technology and anticancer drugs, EC is frequently discovered late, and its prognosis is not ideal.[2] Age, estrogen use, obesity, early menarche, late menopause, and lifestyle are among the most common risk factors for EC.[3] Developing effective prevention strategies and reducing its severity can be achieved by identifying the risk factors for EC.

Folate, also known as vitamin B9, is a nutrient that may influence cancer formation because it is a 1-carbon unit donor that aids the metabolism of nucleic and amino acids. In vitro evidence substantiating the antitumor properties of folate includes its participation in synthesizing purines and pyrimidines, facilitating DNA methylation, and significantly contributing to DNA repair.[4] According to epidemiological studies, folate can reduce the incidence of colorectal, esophageal, bladder, and pancreatic cancers.[5] Over the past 30 years, several studies have examined the relationship between folate intake and EC. While some studies have indicated that folate intake can lower the risk of EC,[6] many other studies have found no statistically significant relationship between folate intake and the risk of EC.[7] As such, the relationship between folate intake and EC remains controversial. A meta-analysis is necessary to examine the relationship between folate intake and EC risk in greater detail.

2. Materials and methods

2.1. Search strategy

From their founding until February 1, 2024, we thoroughly searched PubMed, EMBASE, Cochrane Library, and Web of Science databases. In addition to folate, vegetables, fruits, and diet were also employed as search keywords to prevent missing literature that satisfied the standards during retrieval, as folate intake is frequently 1 of the dietary elements under investigation. The fundamental steps in the meta-analysis retrieval process were as follows: (Folic Acid) OR (Vitamin M) OR (Vitamin B9) OR (Folate) OR (Die) OR (Vegetables) OR (Fruit) AND (Endometrial Neoplam) OR (Endometrial Carcinoma) OR (EC). The comprehensive search strategy was included in Table S1, Supplemental Digital Content, http://links.lww.com/MD/N614. This meta-analysis was conducted according to PRISMA guidelines (registration number: CRD40202505943).[8]

3. Inclusion and exclusion criteria

The inclusion criteria for this study were as follows: The study type was case-control or cohort studies, the relationship between folate intake (comprising total folate intake and dietary folate intake) and EC risk was investigated. Total folate intake encompasses all folate obtained from both food sources and supplementary supplements, whereas dietary folate intake specifically refers to folate obtained solely from food sources, the study furnished folate intake as exposure and EC incidence as outcome, the diagnostic information for EC was acquired through medical diagnosis, self-reporting, pathological diagnosis, medical records, and cancer registration, to assess the association between folate consumption and the EC, the study provided a relative risk (RR), odds ratio (OR), hazard ratio (HR), and 95% confidence intervals (CIs). The following were the criteria for exclusion, the research was published in a language other than English, the article categories consisted of case reports, meta-analyses, editorials, animal experiments, and reviews, the research contained insufficient data.

Two researchers (DW and JL) conducted independent literature reviews using the aforementioned inclusion and exclusion criteria. Disagreements that did arise throughout the screening process were be deliberated and analyzed collaboratively by 2 researchers. When 2 researchers could not reach an agreement, a third researcher (YP) addressed the issue.

4. Data extraction

The extracted data for each study comprised the following information: first author, publication year, study location, study design, sample size (number of EC cases and subjects), diet assessment, various levels of folate intake and their corresponding OR values, RR values, HR values, and their respective 95% CI. Additionally, the data included information on the adjusted confounding factors and quality scores. Data were individually extracted by a researcher (ML).

5. Quality assessment

To assess the quality of case-control and cohort studies, we employed the Newcastle-Ottawa Scale (NOS), which comprises three primary categories: population selection, intergroup comparability, and exposure/outcome assessment.[9] The scale has a maximum rating of 9 points. Studies with ratings below 4, between 5 and 6, and between 7 and 9 were classified as poor, medium, and high, respectively.

6. Data analysis

Given the uncommon occurrence of EC, the OR was approximately equivalent to the RR.[10] Consequently, the RR values and their 95% CIs were consistently utilized as point estimates in this study. The heterogeneity of the estimated values of the merged outcomes was assessed using the I2 statistic.[11] With minimal to moderate heterogeneity between studies, a fixed effect model (inverse variance method) is typically employed when I2 < 50%. When I2 > 50%, moderate to severe heterogeneity exists between studies; therefore, a random-effects model (Mantel-Haenszl method) is required.

Subgroup analysis was conducted if the study exhibited substantial heterogeneity. This involves stratifying the study area, study type, and adjusted confounding factors and assessing whether the subgroup analyses can provide an explanation for the observed heterogeneity. Three methods were employed to identify publication bias in the study: funnel plot,[12,13] Egger regression asymmetry test,[14] and Begg rank correlation test.[15] In the beginning, visually assess the symmetry of the dispersed points within the funnel plot. A study may have no publication bias if the dispersed points have a symmetrical distribution. Furthermore, Egger regression asymmetry test and Begg rank correlation test were implemented to quantify publication bias. Statistically substantial publication bias was indicated in the study when P < .05. Additionally, for the sensitivity analysis, we systematically removed each included study and assessed the impact on the overall results by examining the estimated merging points of the remaining studies.

Finally, we employed the methods advised by Greenland and Longnecker to examine the possible dose–response association between folate consumption and EC.[16] To conduct a dose–response analysis, each included study was divided into at least 3 folate intake groups and provided the following 4 sets of data: folate intake levels in each group, number of EC cases corresponding to folate intake levels in each group, number of people per/year in each group, point estimates for each group, and their respective 95% CIs. To assess whether the dose–response association between folate intake and EC is linear or nonlinear, we used a restricted cubic spline function with 4 nodes (5%, 35%, 65%, and 95%).[17] A linear dose–response association existed between folate consumption and EC when P < .05, but a nonlinear relationship otherwise. We calculated folate consumption for the original study group by taking the midpoint of the upper and lower bounds of the interval. For the upper open interval, we multiplied the endpoint by 1.5. For the lower open interval, we divided the interval endpoint by 1.5.

All statistical analyses were performed using Stata 14.0 (StataCorp, College Station, TX, USA). P < .05 was considered statistically significant.

7. Results

7.1. Literature search

Following an initial search, a comprehensive compilation of 2466 documents was extracted from the 4 databases. An additional record was acquired via other resources. The initial search yielded 2467 scholarly articles. Following the elimination of duplicate studies, 1856 records remained. After reviewing their titles and abstracts, a total of 1834 items were excluded, leaving 22 studies. 2 articles with outdated data and 5 that failed to provide point estimates were excluded after thorough examination of the entire text. Finally, 15 studies were included in the meta-analysis (Fig. 1).

Figure 1. Literature search and screening process.

8. Study characteristics

Table 1 presented the research characteristics of this study. Of the 15 included studies, 6 were cohort studies[19,23,26,28–30] and 9 were case-control studies.[6,7,18,20–22,24,25,27] Seven studies were conducted in USA,[6,7,20,24,26,28,30] 5 studies in Canada[18,19,23,25,29] 1 in Mexico,[21] 1 in Europe,[27] and 1 in China.[22] With 379,570 participants, this study documented 8660 cases of EC. To assess folate intake, 15 studies employed food frequency questionnaires (FFQ). The majority of studies have considered or controlled for confounding variables that influence EC, such as age, BMI, estrogen use, contraceptive use, total energy consumption, parity, smoking, education, age at menarche, history of diabetes, and menopause. Case-control studies and cohort studies obtained mean quality assessment scores of 8.00 (SD = 0.71) and 7.67 (SD = 1.03), respectively (Table 1, Table S2, Supplemental Digital Content, http://links.lww.com/MD/N614).

Table 1 Characteristics of included studies.

Author	Region	Study type	Case/ subjects	Diet
assessment	Intake measurement	RR (95% CI)	Adjustment	Quality score	
Potischman et al[7] (1993)	USA	Case-control	399/296	Validated FFQ (60 items)	Folate-rich foods
Q1 (<6.4 times/wk)
Q2 (6.4–10.7 times/wk)
Q3 (10.8–15.9 times/wk)
Q4 (>15.9 times/wk)	1.0
0.8 (0.5–1.3)
0.9 (0.5–1.4)
0.9 (0.6–1.6)	Age, BMI, used hormone replacement therapy, ever-contraceptive usage, parity, smoking, education, total energy	8	
Jain et al[18] (2000)	Canada	Case-control	552/562	Validated FFQ (142 items)	Q1 (low)
Q2
Q3
Q4 (high)	1.0
1.17 (0.83–1.65)
0.88 (0.62–1.26)
0.96 (0.67–1.36)	Age, total energy, body weight, smoking, history of diabetes, ever-contraceptive usage, used hormone replacement therapy, education, parity, age at menarche	8	
Jain et al[19] (2000)	Canada	Cohort	221/56,837	Validated FFQ (86 items)	Q1 (low)
Q2
Q3
Q4 (high)	1.00
0.95 (0.62–1.44)
1.44 (0.77–1.70)
1.18 (0.79–1.74)	Age, total energy, body weight, smoking, history of diabetes, ever-contraceptive usage, used hormone replacement therapy, education, parity, age at menarche	6	
McCann et al[6](2000)	USA	Case-control	232/639	Validated FFQ (172 items)	Q1 (<296 μg/d)
Q2 (297–256 μg/d)
Q3 (357–448 μg/d)
Q4 (>448 μg/d)	1.0
0.5 (0.3–0.9)
0.7 (0.4–1.1)
0.4 (0.2–0.7)	Age, education, BMI, diabetes, hypertension, smoking, age at menarche, parity, ever-contraceptive usage, menopause status, used hormone replacement therapy, total energy	9	
Paynter et al[20] (2004)	USA	Case-control	201/603	Validated FFQ (no mention)	<400 μg/d
≥400 μg/d	1.00
0.74 (0.52–1.07)	Age, alcohol, total energy	7	
Martinez et al[21] (2005)	Mexico	Case-control	85/629	Validated FFQ (116 items)	≤197 μg/d
198–321 μg/d
≥322 μg/d	1.00
0.84 (0.44–1.61)
1.04 (0.48–2.23)	Age, total energy intake, parity, BMI, physical activity, and history of diabetes	7	
Xu et al[22] (2007)	China	Case-control	1204/1212	Validated FFQ (71 items)	Q1 (low)
Q2
Q3
Q4	1.0
0.8 (0.7–1.1)
0.6 (0.5–0.8)
0.6 (0.4–0.7)	Age, education, menopausal status, history of diabetes, alcohol consumption, BMI, physical activity, total energy, total animal food intake, and total fruit and vegetable intake	8	
 Kabat et al[23] (2008)	Canada	Cohort	426/49,654	Validated FFQ (86 items)	<237 μg/d
237 to <281 μg/d
281 to <321 μg/d
321 to <374 μg/d
374+	1.00
0.91 (0.65–1.26)
1.07 (0.78–1.48)
1.12 (0.81–1.54)
0.79 (0.55–1.13)	Age, BMI, education, menopausal status, parity, age at menarche, ever-contraceptive usage, used hormone replacement therapy, and total energy, calcium, and raw vegetables	8	
Yeh et al[24] (2009)	USA	Case-control	541/541	Validated FFQ (44 items)	Q1 (≤288 μg/d)
Q2 (289–371 μg/d)
Q3 (372–473 μg/d)
Q4 (≥474 μg/d)	1.00
0.74 (0.51–1.07)
0.69 (0.46–1.01)
0.57 (0.36–0.91)	Age, BMI, used hormone replacement therapy, smoking, lifetime duration of menstruation, and total energy	8	
Biel et al[25] (2011)	Canada	Case-control	506/981	Validated FFQ (124 items)	≤277.6 μg/d
>277.6 to ≤322.5 μg/d
322.5 to ≤377.6 μg/d
>377.6 to ≤851.3 μg/d	1.00
0.80 (0.57–1.12)
1.14 (0.83–1.57)
1.18 (0.85–1.63)	Age, total energy, nutrient-specific supplement use, age at menarche, BMI, parity, education, hyperteosion history, ever-contraceptive usage, used hormone replacement therapy, menopausal status, and alcohol consumption	9	
Uccella et al[26] (2011)	USA	Cohort	471/23,356*
71
/23,356†	Validated FFQ (126 items)	Type I endometrial cancer:
43.5 to 250.1 μg/d
250.2 to 348.6 μg/d
348.7 to 560.9 μg/d
>560.9 μg/d
Type II endometrial cancer:
43.5 to 250.1 μg/d
250.2 to 348.6 μg/d
348.7 to 560.9 μg/d
>560.9 μg/d	1.00
0.85 (0.64–1.13)
1.08 (0.81–1.44)
1.00 (0.76–1.32)

1.00
0.93 (0.45–1.95)
0.97 (0.44–2.12)
1.71 (0.87–3.35)	Age, total energy, BMI, waist-to-hip ratio, history of diabetes, hypertension, age at menopause, used hormone replacement therapy, smoking, and alcohol use	8	
 Tavani et al[27] (2012)	Italy and Switzerland	Case-control	454/1366	Validated FFQ (78 items)	Q1
Q2
Q3
Q4	1.00
1.10 (0.77–1.57)
0.79 (0.53–1.18)
1.06 (0.67–1.67)	Age, sex, study center, year of interview, education, alcohol drinking, smoking, BMI, total energy, and physical activity at work	8	
Liu et al[28] (2013)	USA	Cohort	788/121,700	Validated FFQ (no mention)	Q1:275.8 μg/d
Q2:402.0 μg/d
Q3:509.7 μg/d
Q4:623.8 μg/d
Q5:794.0 μg/d	1.00
1.17 (0.93–1.48)
1.11 (0.87–1.41)
1.19 (0.94–1.51)
1.10 (0.87–1.41)	Age, calendar year, smoking, BMI, race, age at menarche, ever-contraceptive usage, menopausal status, used hormone replacement therapy, and parity	7	
 Arthur et al[29] (2019)	Canada	Cohort	180/2606	Validated FFQ (166 items)	≤389.5 μg/d
389.5–487.2 μg/d
487.3–614.9 μg/d
>614.9 μg/d	1.00
1.02 (0.68–1.53)
0.86 (0.56–1.31)
0.52 (0.29–0.93)	Education, smoking, alcohol intake, BMI, total energy, physical activity, age at menarche, parity, breastfeeding, menopausal status, HRT use, ever-contraceptive usage, family history	9	
Lu et al[30] (2019)	USA	Cohort	2329/114,414	Validated
FFQ (no mention)	Type I endometrial cancer:
Q1
Q2
Q3
Q4
Q5
Type II endometrial cancer:
Q1
Q2
Q3
Q4
Q5	1.00
1.09 (0.94–1.27)
1.07 (0.92–1.24)
1.10 (0.94–1.27)
1.15 (0.99–1.34)

1.00
1.07 (0.66–1.75)
1.16 (0.72–1.87)
0.82 (0.49–1.40)
1.13 (0.69–1.83)	Age, BMI, smoking, ever-contraceptive usage, used hormone replacement therapy, and total energy	8	

9. Overall analysis and dose–response analysis

The association between folate intake and EC was depicted in Figure 2. The RR values included in the study ranged from McCann et al’s 0.40 (95% CI: 0.20–0.70)[6] to Uccella et al’s 1.71 (95% CI: 0.87–3.35).[26] The highest group folate intake can reduce the incidence of EC by 10% (RR = 0.90; 95% CI: 0.78–1.05) compared to the lowest group intake. A random effects model was employed due to the moderate heterogeneity (I2 = 63.2%, P = .0000) observed in the summary study. Visual examination of the funnel plot revealed that the scattered points at both extremities were symmetrically distributed, and there was no discernible publication bias (Fig. 3). Concurrently, both Egger test (P = .132) (Figure S1, Supplemental Digital Content, http://links.lww.com/MD/N614) and Begg test (P = .246) (Figure S2, Supplemental Digital Content, http://links.lww.com/MD/N614) failed to identify any indications of publication bias.

Figure 2. Forest plot of the association between folate intake and EC.

Figure 3. The result of funnel plot.

The dose–response analysis results were illustrated in Figure 4. Research has shown that the intake of folate may reduce the risk of EC (RR = 0.90; 95% CI: 0.78–1.05). The risk of EC is decreased by 2.57% with each daily addition of 50 micrograms of folate (RR = 0.974, 95% CI: 0.968–0.981, P = .231).

Figure 4. RR for endometrial cancer by doses of folate consumption in light of the results of the dose–response meta-analyses.

10. Subgroup analysis and sensitivity analysis

Table 2 displayed the subgroup analysis results by study type, area, and adjustment factors. When stratified by study type, folate intake reduced the incidence of EC in case-control studies (RR = 0.80, 95% CI: 0.70–0.91) but not in cohort studies (RR = 1.07, 95% CI: 0.97–1.19). When stratified by research region, studies from China suggest that folate intake can reduce the risk of EC (RR = 0.60, 95% CI: 0.45–0.79), but studies from the USA (RR = 1.02, 95% CI: 0.92–1.12), Canada (RR = 0.90, 95% CI: 0.81–1.14), Mexico (RR = 1.04, 95% CI: 0.48–2.24), and Europe (RR = 1.06, 95% CI: 0.67–1.67) do not believe folate intake can reduce the risk of EC. Adjustment for BMI, contraceptive use, hormone replacement therapy, parity, smoking, education, total energy intake, age at menarche, diabetes history, and menopause had no significant effect on the risk of EC in the subgroup analysis.

Table 2 Subgroup analysis of folate intake with the risk of EC.

	No of studies	Summary RR	95% Cl	I2 (%)	P-value	
Overall	15	0.90	(0.78–1.02)	63.2	.000	
Study type	
 Case-control	9	0.80	(0.70–0.91)	59.2	.012	
 Cohort	6	1.07	(0.97–1.19)	41.2	.103	
Region	
 USA	7	1.02	(0.92–1.12)	65.4	.003	
 Canada	5	0.96	(0.81–1.14)	49.8	.093	
 Mexico	1	1.04	(0.48–2.24)			
 China	1	0.60	(0.45–0.79)			
 Italy and Switzerland	1	1.06	(0.67–1.67)			
Adjustment for confounders	
 BMI	
  Yes	12	0.99	(0.91–1.08)	61.1	.001	
  No	3	0.76	(0.60–0.96)	65.1	.057	
 Ever-contraceptive usage	
  Yes	9	1.04	(0.94–1.14)	55.3	.017	
  No	6	0.81	(0.70–0.94)	61.5	.016	
 Hormone replacement therapy	
  Yes	10	1.04	(0.95–1.14)	52.8	.016	
  No	5	0.71	(0.59–0.85)	37.9	.168	
 Parity	
  Yes	8	0.99	(0.86–1.13)	54.9	.030	
  No	7	0.95	(0.86–1.05)	71.2	.001	
 Smoking	
  Yes	10	1.03	(0.94–1.13)	57.5	.007	
  No	5	0.79	(0.68–0.93)	60.6	.038	
 Education	
  Yes	8	0.88	(0.78–1.00)	55.1	.023	
  No	7	1.02	(0.93–1.13)	69.2	.002	
 Total energy intake	
  Yes	12	0.98	(0.89–1.07)	64.0	.001	
  No	3	0.91	(0.76–1.09)	70.9	.032	
 Age at menarche	
  Yes	7	0.94	(0.85–1.05)	70.6	.001	
  No	8	0.99	(0.87–1.11)	58.8	.013	
 History of diabetes	
  Yes	10	0.99	(0.90–1.09)	64.7	.002	
  No	5	0.90	(0.78–1.05)	64.7	.015	
 Menopause status	
  Yes	10	1.02	(0.92–1.12)	45.0	.045	
  No	5	0.86	(0.75–0.99)	79.9	.001	

11. Discussion

The current meta-analysis included 15 observational studies (nine case-control studies and 6 cohort studies), revealing a boundary-negative connection between folate consumption and EC (RR = 0.90, 95% CI: 0.78–1.05). Du et al[31] conducted the first meta-analysis on the association between folate intake and EC. We performed an additional dose–response analysis on this premise. According to our findings, taking an extra 50 µg of folate daily lowered the risk of EC by 2.57% (RR = 0.974, 95% CI: 0.968–0.981, P = .231).

Our research results were primarily based on case-control studies, as evidenced by the summary analysis of case-control studies that suggested that folate intake could lower the risk of EC (RR = 0.80, 95% CI: 0.70–0.91). However, this relationship was not significant (RR = 1.07, 95% CI: 0.97–1.19) in cohort studies. The correlation between China (RR = 0.60, 95% CI: 0.45–0.79), Canada (RR = 0.96, 95% CI: 0.81–1.14), and the USA (RR = 1.02, 95% CI: 0.92–1.12) was higher when stratified analysis by study area than between Mexico (RR = 1.04, 95% CI: 0.48–2.24) and Europe (RR = 1.06, 95% CI: 0.67–1.67). This suggests that regional variations could account for some of the moderate heterogeneity observed in the study findings. In addition, 4 of the 7 studies included in the USA were case-control studies,[6,7,20,24] which could account for the internal heterogeneity of the studies. A subgroup analysis of the significant confounding variables that influenced the incidence of EC was also performed. These variables included BMI, contraceptive use, hormone replacement therapy, parity, smoking, education, total energy intake, age at menarche, history of diabetes, and menopause.

There is no denying that the study population could be a source of heterogeneity. To make the study more thorough, we did not establish exclusion criteria for the study population. Two studies examined the association between vitamin B intake and the risk of common tumors in women.[23,29] 3 studies examined the link between carbon metabolism EC risk.[26,28,30] 3 studies examined the association between MTHFR gene types and EC risk.[20,22,28] There are several mechanisms by which folate can influence on tumor development: regulates DNA methylation process. By providing methyl groups to homocysteine, the active component of folate, known as 5-methyltetrahydrofolate, facilitates the synthesis of methionine.[32] S-adenosylmethionine (SAM) is produced through the methylation of methionine. SAM methylates cytosine through DNA methyltransferase activity, thereby regulating gene transcription and expression[33]; regulate the integrity of DNA. A reduction in folate levels results in a depletion of 5,10-methylenetetrahydrofolate levels within cells, which subsequently inhibits the methylation of deoxyuridine monophosphate (dUTP) to deoxythymidine triphosphate (dTTP) in a proportional fashion.[32] Temporary single-strand breaks may result from DNA polymerase incorporating uracil into DNA in response to decreased dUMP/dTMP ratio.[33] Chromosomal breaking can transpire due to 2 gaps oriented in opposing directions, potentially leading to the progression of malignancies.[33] Folic acid, or pteroylglutamic acid, is derived from fortified foods, supplements, and medications. It is an artificially produced version of folate. Folate, scientifically referred to as 5-methyltetrahydrofolate, is derived from green leafy vegetables and is a biologically active form of folate acquired through the processes of reduction and methylation. Our meta-analysis included 8 studies that reported dietary folate intake and 7 studies that reported total folate intake. Our research indicates that consuming dietary folate can lower the risk of EC (RR = 0.81, 95% CI: 0.71–0.93), providing evidence that aligns with the aforementioned theoretical foundation.

Dihydrofolate reductase converts folic acid into tetrahydrofolate. Exceeding 400 mg of folic acid can completely saturate dihydrofolate reductase, resulting in residual folic acid.[4] This leftover folic acid has the potential to cause cancer.[4] Simultaneously, increased folic acid supplementation may have a tumor-promoting effect on pre-tumor lesions.[34] Our analysis revealed that total folate intake increased the incidence of EC (RR = 1.05, 95% CI: 0.95–1.16), although this association was not statistically significant. However, total folate intake included both folic acid supplementation and dietary folate intake. Therefore, our results may be influenced by both the negative and positive effects of folate on folic levels. Prospective research is needed to assess the association between folic acid supplementation and EC.

The p53 gene mutation is a common feature of type II EC, with a mutation rate ranging from 71% to 85%.[35,36] The P53 mutation rate in type I EC is barely one-third.[35,36] In contrast, p53 mutations are associated with abnormal cell proliferation and DNA damage. As a result, different EC subtypes may react differently to folate intake. Nonetheless, our meta-analysis included only 2 studies that examined the relationship between folate consumption and the risk of EC in different subtypes.[26,30] Consequently, additional studies are needed to determine the relationship between folate consumption and the risk of different EC subtypes.

The benefit of our study is that we performed a further dose–response analysis to show a linear reduction in the risk of EC linked to folate consumption. Furthermore, subgroup analysis was performed to elucidate the moderate heterogeneity observed in this study. Our research does, however, have several limitations. First, to determine the frequency of dietary consumption and folate intake, all the included studies employed the FFQ, a tool for food nutrition evaluation. However, numerous studies have adjusted the FFQ to better reflect the variety of food in the study location, leading to variations in the items included in various studies. There were 44 items in some studies and 172 in others. The FFQ, however, depends on an individual’s accurate dietary recall. As a result, it is possible to overestimate or underestimate folate consumption, which could have impacted the findings of this study. Second, although we performed a subgroup analysis of the researched regions, 12 out of 15 studies came from North America. Thus, more studies on the association between folate intake and EC risk need to be conducted outside of North America. Third, case-control and cohort studies were the 2 categories of observational studies included in this research. However, recall, information, and confounding bias affect impact case-control studies. Fourth, due to the limited sample size we included in the study, we were unable to draw accurate conclusions. Finally, most clinical doctors will adjust their treatment strategies based on the molecular subtypes of EC patients. However, the studies included in this meta-analysis lack data on molecular subtypes and have not been able to further evaluate the risk of folate intake and different EC molecular subtypes.

In conclusion, our findings suggest that folate intake may be related to a lower EC risk. According to the results of dose–response research, taking an extra 50 µg of folate per day can reduce the risk of EC by 2.57%.

Author contributions

Conceptualization: Jiaye Long, Du Wang, Yingrong Pang.

Data curation: Du Wang.

Formal analysis: Yingrong Pang.

Investigation: Miyang Yang, Yingrong Pang.

Methodology: Miyang Yang.

Software: Meiqiong Li.

Supervision: Shuxin Qin.

Writing – original draft: Jiaye Long.

Writing – review & editing: Jiaye Long, Kai Cui.

Supplementary Material

Abbreviations:

CIs confidence intervals

dTTP deoxythymidine triphosphate

dUTP deoxyuridine monophosphate

EC endometrial cancer

FFQ food frequency questionnaires

HR hazard ratio

NOS Newcastle-Ottawa Scale

OR odds ratio

RR relative risk

SAM S-adenosylmethionine

An ethics statement is not applicable because this study is based exclusively on published literature

The authors have no funding and conflicts of interest to disclose.

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

Supplemental Digital Content is available for this article.

How to cite this article: Long J, Wang D, Yang M, Pang Y, Li M, Qin S, Cui K. Folate intake and the risk of endometrial cancer: A dose–response meta-analysis. Medicine 2024;103:38(e39775).

JL and DW contributed equally to this work.
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References

[1] Sung H Ferlay J Siegel RL . Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71 :209–49.33538338
[2] Zhu G Li Z Tang L . Associations of dietary intakes with gynecological cancers: findings from a cross-sectional study. Nutrients. 2022;14 :5026.36501056
[3] Makker V MacKay H Ray-Coquard I . Endometrial cancer. Nat Rev Dis Primers. 2021;7 :88.34887451
[4] Liew SC . Folic acid and diseases: supplement it or not? Rev Assoc Med Bras (1992). 2016;62 :90–100.27008500
[5] Pieroth R Paver S Day S Lammersfeld C . Folate and its impact on cancer risk. Curr Nutr Rep. 2018;7 :70–84.30099693
[6] McCann SE Freudenheim JL Marshall JR Brasure JR Swanson MK Graham S . Diet in the epidemiology of endometrial cancer in western New York (United States). Cancer Causes Control. 2000;11 :965–74.11142531
[7] Potischman N Swanson CA Brinton LA . Dietary associations in a case-control study of endometrial cancer. Cancer Causes Control. 1993;4 :239–50.8318640
[8] Liberati A Altman DG Tetzlaff J . The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339 :b2700.19622552
[9] Stang A . Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25 :603–5.20652370
[10] Long J Liu Z Liang S Chen B . Cruciferous vegetable intake and risk of prostate cancer: a systematic review and meta-analysis. Urol Int. 2023;107 :723–33.37343525
[11] Higgins JP Thompson SG . Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21 :1539–58.12111919
[12] Peters JL Sutton AJ Jones DR Abrams KR Rushton L . Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol. 2008;61 :991–6.18538991
[13] Sterne JA Egger M . Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol. 2001;54 :1046–55.11576817
[14] Egger M Davey Smith G Schneider M Minder C . Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315 :629–34.9310563
[15] Begg CB Mazumdar M . Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50 :1088–101.7786990
[16] Greenland S Longnecker MP . Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. Am J Epidemiol. 1992;135 :1301–9.1626547
[17] Durrleman S Simon R . Flexible regression models with cubic splines. Stat Med. 1989;8 :551–61.2657958
[18] Jain MG Howe GR Rohan TE . Nutritional factors and endometrial cancer in Ontario, Canada. Cancer Control. 2000;7 :288–96.10832115
[19] Jain MG Rohan TE Howe GR Miller AB . A cohort study of nutritional factors and endometrial cancer. Eur J Epidemiol. 2000;16 :899–905.11338120
[20] Paynter RA Hankinson SE Hunter DJ De Vivo I . No association between MTHFR 677 C->T or 1298 A->C polymorphisms and endometrial cancer risk. Cancer Epidemiol Biomarkers Prev. 2004;13 :1088–9.15184272
[21] Salazar-Martinez E Lazcano-Ponce E Sanchez-Zamorano LM Gonzalez-Lira G Escudero-DE Los Rios P Hernandez-Avila M . Dietary factors and endometrial cancer risk. Results of a case-control study in Mexico. Int J Gynecol Cancer. 2005;15 :938–45.16174249
[22] Xu WH Shrubsole MJ Xiang YB . Dietary folate intake, MTHFR genetic polymorphisms, and the risk of endometrial cancer among Chinese women. Cancer Epidemiol Biomarkers Prev. 2007;16 :281–7.17301261
[23] Kabat GC Miller AB Jain M Rohan TE . Dietary intake of selected B vitamins in relation to risk of major cancers in women. Br J Cancer. 2008;99 :816–21.18665162
[24] Yeh M Moysich KB Jayaprakash V . Higher intakes of vegetables and vegetable-related nutrients are associated with lower endometrial cancer risks. J Nutr. 2009;139 :317–22.19074206
[25] Biel RK Csizmadi I Cook LS Courneya KS Magliocco AM Friedenreich CM . Risk of endometrial cancer in relation to individual nutrients from diet and supplements. Public Health Nutr. 2011;14 :1948–60.21752313
[26] Uccella S Mariani A Wang AH . Dietary and supplemental intake of one-carbon nutrients and the risk of type I and type II endometrial cancer: a prospective cohort study. Ann Oncol. 2011;22 :2129–36.21324952
[27] Tavani A Malerba S Pelucchi C . Dietary folates and cancer risk in a network of case-control studies. Ann Oncol. 2012;23 :2737–42.22898036
[28] Liu JJ Hazra A Giovannucci E . One-carbon metabolism factors and endometrial cancer risk. Br J Cancer. 2013;108 :183–7.23299529
[29] Arthur RS Kirsh VA Rohan TE . Dietary B-Vitamin intake and risk of breast, endometrial, ovarian and colorectal cancer among Canadians. Nutr Cancer. 2019;71 :1067–77.30955365
[30] Lu J Trabert B Liao LM Pfeiffer RM Michels KA . Dietary intake of nutrients involved in folate-mediated one-carbon metabolism and risk for endometrial cancer. Int J Epidemiol. 2019;48 :474–88.30544261
[31] Du L Wang Y Zhang H Zhang H Gao Y . Folate intake and the risk of endometrial cancer: a meta-analysis. Oncotarget. 2016;7 :85176–84.27835893
[32] Schmidt TT Sharma S Reyes GX . Inactivation of folylpolyglutamate synthetase Met7 results in genome instability driven by an increased dUTP/dTTP ratio. Nucleic Acids Res. 2020;48 :264–77.31647103
[33] Wang K Zhang Q Yang J . The effect of folate intake on ovarian cancer risk: a meta-analysis of observational studies. Medicine (Baltim). 2021;100 :e22605.
[34] Kim YI . Folic acid supplementation and cancer risk: point. Cancer Epidemiol Biomarkers Prev. 2008;17 :2220–5.18768486
[35] Francies FZ Marima R Hull R Molefi T Dlamini Z . Genomics and splicing events of type II endometrial cancers in the black population: racial disparity, socioeconomic and geographical differences. Am J Cancer Res. 2020;10 :3061–82.33163258
[36] Alhaj-Suliman SO Naguib YW Wafa EI . A ciprofloxacin derivative with four mechanisms of action overcomes paclitaxel resistance in p53-mutant and MDR1 gene-expressing type II human endometrial cancer. Biomaterials. 2023;296 :122093.36965280
