Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-15T09:11:09.813Z Has data issue: false hasContentIssue false

Association of dietary inflammatory index with risk of gestational diabetes mellitus and preeclampsia: a systematic review and meta-analysis

Published online by Cambridge University Press:  31 July 2023

Li Hong
Affiliation:
School of Nursing, Anhui Medical University, Hefei, People’s Republic of China
Liyuan Zhu
Affiliation:
Department of Nursing, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People’s Republic of China
Jinru Zhang
Affiliation:
School of Nursing, Anhui Medical University, Hefei, People’s Republic of China
Yueqi Fu
Affiliation:
School of Nursing, Anhui Medical University, Hefei, People’s Republic of China
Xiaoyan Qi
Affiliation:
School of Nursing, Anhui Medical University, Hefei, People’s Republic of China
Mei Zhao*
Affiliation:
School of Nursing, Anhui Medical University, Hefei, People’s Republic of China
*
*Corresponding author: Mei Zhao, email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Findings from observational studies have suggested a possible association between dietary inflammatory index (DII) and risk of gestational diabetes mellitus (GDM) and preeclampsia (PE). However, the results of these studies were inconclusive. A systematic review and meta-analysis was carried out to illuminate this association. Systematic literature search was conducted in PubMed, Web of Science, Cochrane Library, EMBASE, Scopus and other databases from inception until January 2023. The qualities of included studies were assessed using the Newcastle–Ottawa scale. Nine studies (seven cohort, two case–control) were included in the meta-analysis, including 11 423 participants from five different countries. The meta-analysis indicated that a 1-unit increase in the DII score, representing pro-inflammatory diet, was associated with 13 % higher risk of GDM (OR = 1·13; 95 % CI 1·02, 1·25, I2 = 68·4 %, P = 0·004) and 24 % higher risk of PE (OR = 1·24; 95 % CI 1·14, 1·35, I2 = 52·0 %, P = 0·125). Subgroup analysis found that this association was evident among studies with Chinese populations (OR = 1·16; 95 % CI 1·06, 1·28) and studies with mid pregnancy (OR = 1·20; 95 % CI 1·07, 1·34). The findings indicate that pro-inflammatory diet can increase the risk of GDM and PE. Considering some limitations in this study, more studies are needed to verify this association.

Type
Systematic Review and Meta-Analysis
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Nutrition Society

Gestational diabetes mellitus (GDM) refers to abnormal glucose tolerance with onset or first recognition during pregnancy(Reference Moon and Jang1). Study has shown that the prevalence of GDM has significantly increased two to three times in 10 years(Reference Yang and Wu2), and the total incidence is 14·8 %(Reference Gao, Sun and Lu3). Preeclampsia (PE) is a serious pregnancy complication next only to GDM, with an estimated average incidence of 5 %(Reference Gu, Lin and Hou4). GDM and PE in pregnant women are syndromes associated with substantially increased risk of preterm delivery, low birth weight, fetal growth restriction and caesarean section(Reference Rocha5Reference Champion, Battarbee and Biggio7). The causes of GDM and PE are multifaceted, involving genetic, physiological and lifestyle-related risk factors. Recently, the role of chronic inflammation has received increasing attention(Reference Phoswa and Khaliq8,Reference McElwain, Tuboly and McCarthy9) . Moreover, studies have shown that diet can regulate the level of inflammation in the body by altering the expression of inflammatory genes and the concentration of inflammatory markers(Reference Bordoni, Danesi and Dardevet10,Reference Gardener, Rainey-Smith and Martins11) . Therefore, recent studies have begun to explore the association between dietary inflammatory potential and risk of GDM and PE.

The dietary inflammatory index (DII) has been developed as the major dietary measurement to evaluate the inflammatory potential of diet, helping to identify the relationship between diet, inflammation and disease. Compared with single food or nutrient intake, DII has been demonstrated to be a reasonable and important indicator for measuring the overall inflammatory potential of diet and an effective tool for studying the relationship between overall diet and diseases(Reference Vicente, Lucio Dos Santos Quaresma and Maria de Melo12). Multiple studies have explored the association between dietary inflammatory potential (evaluated by DII) and the risk of GDM and PE, but the results are inconsistent. A cohort study based on 2639 women in China showed that DII score was positively associated with the risk of GDM(Reference Zhang, Wu and Zhong13). Another case–control study based on 932 women in China suggested that individuals with higher DII score were associated with increased PE risk(Reference Liu, Zheng and Cheng14). However, another Ireland cohort study based on 434 women participants suggested that there was no significant association with GDM or PE(Reference Killeen, Phillips and Delahunt15). To date, only Gao et al.’ s meta-analysis(Reference Gao, Zheng and Jiang16), which primarily focused on the relationship between diet quality and GDM risk, mentioned the association between DII score and GDM risk. However, their meta-analysis only included four studies and missed some eligible publications. Moreover, no comprehensive and systematic meta-analysis has been performed to evaluate the association between DII score and the risk of PE.

It is clearly necessary to provide more convincing evidence to clarify the association of DII score with the risk of GDM and PE. Therefore, we performed a systematic review and meta-analysis based on observational studies to explore the association, in order to provide a theoretical basis for maternal diet management.

Methods

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines(Reference Moher, Liberati and Tetzlaff17) and registered in the PROSPERO international prospective register of systematic reviews (CRD42023407877).

Search strategy

Electronic databases, including PubMed, Web of Science, Cochrane Library, EMBASE, Scopus, China National Knowledge Infrastructure, Wan Fang Database and VIP Database, were searched to screen for all relevant published studies on the DII score with risk of GDM and PE from database inception to January 2023, using the following combined keywords: (‘dietary inflammatory index’ OR ‘dietary inflammatory’ OR ‘DII’ OR ‘inflammation’ OR ‘diet’) AND (‘gestational diabetes mellitus’ OR ‘gestational diabetes’ OR ‘GDM’ OR ‘preeclampsia’ OR ‘gestational hypertension’ OR ‘pregnancy-induced hypertension’ OR ‘pregnancy hypertension’ OR ‘hypertensive disorder of pregnancy’). Moreover, we also searched the reference lists of pertinent articles for any missing articles.

Inclusion and exclusion criteria

Studies were considered eligible if they met the following criteria: (1) studies reported the association between DII and GDM or PE; (2) studies that reported OR, hazard ratio or risk ratio with 95 % CI and (3) studies with either a cohort study, case–control study or cross-sectional study.

Studies were excluded if they met the following criteria: (1) studies without complete data; (2) studies for which the effect sizes could not be extracted and (3) studies such as systemic reviews, comments, case reports and editorials.

Data extraction

Two researchers independently searched the articles strictly according to the inclusion and exclusion criteria and provided articles with differences to third researcher for analysis to decide whether they should be included. The extracted data included the first author’s name, publication year, country, study design, age, pregnancy, sample sizes, DII/DIP/E-DII components, exposure assessment, outcome examined and adjustment for confounders.

Quality assessment

The Newcastle–Ottawa scale was used to evaluate the quality of the literature in all finally included studies(Reference Stang18). The Newcastle–Ottawa scale consists of three dimensions and eight items, including selection, comparability and outcome (cohort study) or exposure (case–control study). The maximum score for selection, comparability and outcome or exposure was 4, 2 and 3, respectively, for a maximum total score of 9. A total score of 0–3 indicated high risk of bias, 4–6 adequate risk of bias and 7–9 low risk of bias(Reference Fan, Wang and Yang19). Studies with a high risk of bias were excluded from the meta-analysis.

Statistical analysis

All statistical analyses were performed by STATA16.0. OR and 95 % CI were selected for the combined effect size; when both crude and adjusted OR were provided, we used the most fully adjusted OR for all studies. Heterogeneity between studies was assessed and quantified with Cochran’s Q test and the I2 statistic, in which P < 0·1 and I2 > 50 % were defined as statistically significant heterogeneity. When there existed significant heterogeneity, we used a random-effects model; otherwise, a fixed-effects model was used(Reference Zhao, Wu and Gao20). Subgroup analyses were conducted stratifying by study design, exposure assessment, country, pregnancy, sample size, inflammation assessment tool and energy adjustment. Egger test was conducted to assess the publication bias for each outcome and a sensitivity analysis was performed to examine the robustness of the results.

Results

Study selection and characteristics

A total of 568 articles were retrieved in the database according to the established search strategy, and 405 articles were removed due to duplication. Subsequently, during screening through the title and abstract, 121 irrelevant studies, twenty-three systematic reviews and the other three studies unrelated to GDM were excluded. We then further searched the full text of sixteen articles to assess their eligibility, of which four without complete data, one did not use DII, one study was duplication and one study did not provide useful data were excluded. Eventually, we included nine original studies to investigate the association between DII score with the risk of GDM and PE(Reference Zhang, Wu and Zhong13Reference Killeen, Phillips and Delahunt15,Reference Sen, Rifas-Shiman and Shivappa21Reference Pajunen, Korkalo and Koivuniemi26) . The flow of the above-described procedures is shown in Fig. 1.

Fig.1. PRISMA flow diagram of study selection process. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; GDM, gestational diabetes mellitus; DII, dietary inflammatory index.

Nine studies were included in the meta-analysis; there were seven(Reference Zhang, Wu and Zhong13,Reference Killeen, Phillips and Delahunt15,Reference Zhao, Yu and Wang22Reference Pajunen, Korkalo and Koivuniemi26) and three(Reference Liu, Zheng and Cheng14,Reference Killeen, Phillips and Delahunt15,Reference Sen, Rifas-Shiman and Shivappa21) studies evaluating the relationship of DII with GDM and PE. A total of 11 423 participants from various countries were involved, including Finland(Reference Pajunen, Korkalo and Koivuniemi26), China(Reference Zhang, Wu and Zhong13,Reference Liu, Zheng and Cheng14,Reference Zhao, Yu and Wang22,Reference Yang25) , Iran(Reference Shivappa, Hébert and Akhoundan23,Reference Soltani, Aminianfar and Hajianfar24) , USA(Reference Sen, Rifas-Shiman and Shivappa21) and Ireland(Reference Killeen, Phillips and Delahunt15). All nine studies were published in the years from 2016 to 2022 inclusively. With regard to study design, there were seven cohort studies and two case–control studies, and the sample sizes ranged from 336 to 4189 participants. All the studies utilised either FFQ or 3-d food diaries as exposure assessment to calculate dietary intake. Continuous DII score was used to evaluate the relationship between DII score with risk of GDM and PE. Adjusted OR was reported in all nine studies and controlled for different types of confounding factors such as age, BMI, energy intake, pregnancy exercise and education level. Detailed information about the nine studies in the analyses is presented in Table 1. According to the Newcastle–Ottawa scale, three studies scored 6 points, five studies scored 7 points and one study scored 8 points, and the methodological quality of all nine studies was high (Table 2).

Table 1. Characteristics of the included studies

DII, dietary inflammatory index; PE, preeclampsia; GDM, gestational diabetes mellitus; DIP, dietary inflammatory potential; E-DII, energy-adjusted dietary inflammatory index.

Table 2. Methodological quality assessment score of the included studies

Association between dietary inflammatory index and the risk of gestational diabetes mellitus

Seven studies evaluated the association between DII score and the risk of GDM, three studies showed that GDM was associated with DII and the rest were considered unrelated; the total sample sizes were 9149. There was moderate heterogeneity among the studies (P = 0·004, I2 = 68·4 %), the meta-analysis result showed that there was a significant association between DII score and risk of GDM (OR = 1·13; 95 % CI 1·02, 1·25) and the difference was statistically significant (Fig. 2).

Fig. 2. Forest plot showing the association between the dietary inflammatory index score and the risk of gestational diabetes mellitus.

Association between dietary inflammatory index and the risk of preeclampsia

Three studies evaluated the association between DII score and risk of PE, and one study showed that PE was associated with DII; the total sample sizes were 2708. In the meta-analysis, there was a significant association between DII score and the risk of PE (OR = 1·24; 95 % CI 1·14, 1·35) with heterogeneity (P = 0·125, I2 = 52·0 %) (Fig. 3).

Fig. 3. Forest plot showing the association between the dietary inflammatory index score and the risk of preeclampsia.

Subgroup analysis

Subgroup analysis of PE was not performed because only three studies were included. To explore the sources of heterogeneity between DII score and risk of GDM, a total of seven subgroup variables were selected for meta-analysis (Table 3). Subgroup analysis was conducted for study design and exposure assessment, and the results indicated that both were no significant reduction in heterogeneity. A higher DII score predicted a greater risk of GDM, especially in individuals with mid pregnancy (OR = 1·20; 95 % CI 1·07, 1·34, I2 = 36·1 %, P = 0·209). Stratification by country, sample size, inflammation assessment tool and energy adjustment partly reduced the heterogeneity between studies, and the association differed significantly between studies that sample size ≥ 1000 (OR = 1·12; 95 % CI 1·03, 1·20, I2 = 0·0 %, P = 0·908) and those that < 1000 (OR = 1·14; 95 % CI 0·96, 1·35, I2 = 78·3 %, P = 0·001). Furthermore, stratification by energy adjustment partly reduced the heterogeneity between studies, especially for studies that used covariate method to adjust energy intake (I2 = 22·2 %) (online Supplementary Fig. S1S7). In addition to variables in the subgroup analysis, differences in the dietary parameters used to calculate DII score across studies, with a maximum of 35 and a minimum of only 20, were also a possible reason, which may help explain the moderate heterogeneity (online Supplementary Table 1).

Table 3. Subgroup analyses of the association between the DII score and GDM (95 % confidence intervals)

DII, dietary inflammatory index; GDM, gestational diabetes mellitus; E-DII, energy-adjusted dietary inflammatory index; DIP, dietary inflammatory potential.

Early pregnancy, pregnancy < 16 weeks; mid pregnancy, pregnancy ≥ 16 weeks. In addition, we combined the instructions of the authors in the original studies, defined pregnancy < 18 weeks as early pregnancy, 13–28 weeks as mid pregnancy.

Sensitivity analysis

Sensitivity analysis was conducted after removing any one of seven studies, to confirm that our results were not determined by a single study. The results showed that removing most of the studies had no significant effect on our results; the only exceptions were found in the removal of the studies by Zhao(Reference Zhao, Yu and Wang22) and Pajunen(Reference Pajunen, Korkalo and Koivuniemi26) changed the relative effect from significant to non-significant in the sensitivity analysis (OR = 1·10; 95 % CI 1·00, 1·20 and OR = 1·11; 95 % CI 1·00, 1·23), as shown in Fig. 4.

Fig. 4. Sensitivity analysis of dietary inflammatory index and gestational diabetes mellitus.

Publication bias

Egger test was adopted to evaluate the publication bias included in the study; the Egger test obtained P = 0·202 for GDM and P = 0·538 for PE, indicating that there was no significant publication bias in the included studies.

Discussion

This study provides a systematic review and meta-analysis that evaluated all available observational studies on the association between DII score and risk of GDM and PE and provides the most comprehensive evidence in this research field. We included nine studies with 11 423 participants from five different countries. More importantly, we performed a detailed subgroup analysis, including pregnancy, inflammation assessment tools and type of energy adjustment, thus improving statistical power.

The meta-analysis indicated that a 1-unit increase in the DII score was associated with 13 % higher risk of GDM (OR = 1·13; 95 % CI 1·02, 1·25) and 24 % higher risk of PE (OR = 1·24; 95 % CI 1·14, 1·35). Similarly, in a review by Moslehi et al.(Reference Moslehi, Sakak and Teymoori27), it was concluded that DII was directly associated with increased odds of GDM. In addition, results from our study were in line with other study that reported an association of pro-inflammatory diet indicated by DII, with increased incidence of diabetes mellitus(Reference Tan, Du and Gao28). At present, the relationship between DII score and risk of GDM and PE is controversial, mainly because of the differences of country, sample sizes, energy intake and pregnancy. With regard to country, the pooled results of studies conducted in China(Reference Zhang, Wu and Zhong13,Reference Liu, Zheng and Cheng14,Reference Zhao, Yu and Wang22,Reference Yang25) , including DII score and risk of GDM and PE, showed an association, whereas the other studies indicated no association(Reference Killeen, Phillips and Delahunt15,Reference Sen, Rifas-Shiman and Shivappa21,Reference Shivappa, Hébert and Akhoundan23,Reference Soltani, Aminianfar and Hajianfar24,Reference Pajunen, Korkalo and Koivuniemi26) ; the differences in country between these studies may partly explain the inconsistent findings. The sample sizes considered ≥ 1000 showed an almost strong association between DII score and GDM risk(Reference Zhang, Wu and Zhong13,Reference Yang25) . However, the smaller sample sizes of studies failed to show a significant association between DII score and GDM risk(Reference Killeen, Phillips and Delahunt15,Reference Zhao, Yu and Wang22Reference Soltani, Aminianfar and Hajianfar24,Reference Pajunen, Korkalo and Koivuniemi26) . Therefore, studies assessing the inflammatory potential of diet on GDM risk need larger sample sizes. In addition, among the variables investigated, adjusted for energy intake was critical for achieving significant results, including covariate method(Reference Zhang, Wu and Zhong13,Reference Zhao, Yu and Wang22,Reference Shivappa, Hébert and Akhoundan23,Reference Yang25) and nutrient-density method(Reference Killeen, Phillips and Delahunt15,Reference Pajunen, Korkalo and Koivuniemi26) , as compared with studies that did not utilise such adjustment(Reference Soltani, Aminianfar and Hajianfar24). The possible reason is that higher energy intake reflects more food intake, which may be variably distributed among pro-inflammatory and anti-inflammatory related foods. The DII score of women in the mid pregnancy(Reference Zhao, Yu and Wang22,Reference Shivappa, Hébert and Akhoundan23,Reference Yang25) was more strongly associated with GDM risk than those in the early pregnancy(Reference Zhang, Wu and Zhong13,Reference Killeen, Phillips and Delahunt15,Reference Soltani, Aminianfar and Hajianfar24,Reference Pajunen, Korkalo and Koivuniemi26) , one possible reason is that compared with the mid pregnancy, women in the early pregnancy intake less due to vomiting or other reasons, and are less likely to intake foods with higher DII score.

Diet can regulate the systemic inflammation level through pro-inflammatory or anti-inflammatory mechanisms of foods, nutrients and dietary patterns(Reference Cavalcante, Lima and Parente29,Reference Menzel, Biemann and Longree30) . Studies have shown that higher adherence to the Mediterranean diet was significantly associated with lower levels of inflammation, including reduced levels of CRP (C-Reactive Protein) IL-6 and fibrinogen(Reference Itsiopoulos, Mayr and Thomas31). The Mediterranean diet is characterised by a high intake of fruits, vegetables, fish and whole grains. It is rich in dietary fibre, vitamin C, vitamin E, folate, carotenoids and PUFA. Previous studies have shown that greater intake of the Mediterranean diet during pregnancy is associated with a reduced risk of GDM and PE(Reference Melero, García de la Torre and Assaf-Balut32Reference Ou, Zhang and Zhao35). The Western diet, characterised by a greater intake of red meat, processed meat and fried foods, is rich in SFA, nitrosamines and other compounds related to oxidative stress and insulin resistance, which may increase the level of serum inflammatory markers(Reference Quan, Zeng and Jiao36,Reference Asadi, Yaghooti-Khorasani and Ghazizadeh37) . Studies have linked a high intake of Western diet and energy from SFA in early pregnancy may contribute to an increased risk of developing GDM and PE(Reference Mizgier, Jarzabek-Bielecka and Mruczyk38,Reference Herlambang, Puspasari and Maharani39) .

From a mechanistic point of view, the role of diet-related inflammation in GDM and PE can be explained by several mechanisms. First, the pro-inflammatory potential of dietary components may led to an imbalance in the level of inflammation by increasing the level of inflammatory factors, such as CRP, TNF-α and IL-6. High level of inflammatory factors induces phosphorylation of insulin receptor substrate-1, leading to its inactivation, and, in turn, inhibits the insulin receptor from phosphorylating this substrate, thus suppressing insulin receptor signalling(Reference Stephens, Lee and Pilch40Reference Aleksandrova, Koelman and Rodrigues42). Inflammatory factors also disrupt the expression of insulin responsive GLUT4, thus reducing insulin-dependent glucose transport and peripheral glucose utilisation(Reference Stephens, Lee and Pilch40,Reference Piuri, Basello and Rossi41) . Meanwhile, previous studies have shown an association between cytokines and the risk of PE, with women at higher risk of PE when the pro-inflammatory cytokines TNF-α and IL-6 were elevated and the anti-inflammatory cytokines IL-4 and IL-10 were decreased(Reference Aggarwal, Jain and Mittal43,Reference Nath, Cubro and McCormick44) . The imbalanced level of inflammation causes activation of associated cellular signalling pathways like Toll-like receptor and NF-κB, and the downstream targets of these pathways may further affect the placental immune tolerance by impacting a negative effect on the secretion of trophoblastic microvesicles and endothelial cells disruption, thus leading to several adverse pregnancy complication like PE(Reference Aggarwal, Jain and Mittal43). Another mechanistic hypothesis relies on the gut microbiota. Gut microbiota are essential modulators of immune homoeostasis, and diet can directly or indirectly affect the composition of gut microbiota, which is associated with gut barrier function(Reference Hasain, Mokhtar and Kamaruddin45,Reference Ding, Hu and Fu46) . For example, a long-term high-fat diet decreases the expression of tight junction proteins in gut epithelial cells and increases the permeability of the gut mucosa, which fails to act as an integral barrier to migrating pathogens; thus, a large amount of bacterial lipopolysaccharide is released into the blood, activating the low-grade chronic inflammation of islets, and inflammation can lead to the structural damage and dysfunction of pancreatic islet B cells, promote B cell apoptosis and cause insufficient insulin secretion, which in turn triggers GDM(Reference Ding, Hu and Fu46).

However, several limitations of this study should be considered when interpreting the findings of this study. First, the results of this study were based primarily on observational studies, so causality cannot be firmly established. All nine included studies adjusted for confounding factors, but some studies did not adjust for energy intake, gestational weight gain and family history of diabetes, which may be important risk factors for GDM and PE. Most of the included studies were cohort studies, which had the risk of loss to follow-up, but some studies did not describe it. In addition, the substantial heterogeneity across studies was not fully eliminated with subgroup meta-analyses by common study characteristic. Finally, generalisability of our findings to diverse populations should be taken with caution because most of the participants were of Chinese.

We suggest the following recommendations for future studies. Future studies can be carried out in large samples and multi-centre populations, and at the same time, the race, economic status and BMI of the population should be considered in the sampling. The existing studies focused on the association between DII score and risk of GDM and PE, but there were few discussions on the mechanism, which can be studied in the future. Finally, when possible, adequately powered randomised controlled trials should be conducted to support better causal inferences.

Conclusion

In conclusion, this study conducts a systematic review and meta-analysis of nine included studies, and the results show that pro-inflammatory diet estimated by a higher DII score is independently associated with an increased risk of GDM and PE. The finds prompt interventions of GDM and PE patients from the perspective of dietary inflammation. However, more prospective longitudinal studies with improved methodology are warranted to confirm the current findings.

Acknowledgements

This work was supported by Key Foundation of Social Science and Humanities of Ministry of Education of Anhui Province (No.SK2021ZD0030); Key Training Program of School of Nursing, Anhui Medical University (No. hlzd2020003) and The Seedling Cultivation Program of School of Nursing, Anhui Medical University (No. hlqm12023021).

L. H., L. Y. Z. and M. Z. designed this study. M. Z. obtained the funding. L. H. and L. Y. Z. extracted and confirmed the data. L. H. performed the statistical analysis and drafted the initial manuscript. L. H., L. Y. Z., M. Z., J. R. Z., Y. Q. F. and X. Y. Q. made substantial revisions to the manuscript. All authors read and approved the final manuscript.

There are no conflicts of interest.

Supplementary material

For supplementary material referred to in this article, please visit https://doi.org/10.1017/S0007114523001678

Footnotes

These authors have contributed equally to this work and share first authorship.

References

Moon, JH & Jang, HC (2022) Gestational diabetes mellitus: diagnostic approaches and maternal-offspring complications. Diabetes Metab J 46, 314.10.4093/dmj.2021.0335CrossRefGoogle ScholarPubMed
Yang, Y & Wu, N (2022) Gestational diabetes mellitus and preeclampsia: correlation and influencing factors. Front Cardiovasc Med 9, 831297. Google Scholar
Gao, C, Sun, X, Lu, L, et al. (2019) Prevalence of gestational diabetes mellitus in mainland China: a systematic review and meta-analysis. J Diabetes Investig 10, 154162.Google Scholar
Gu, W, Lin, J, Hou, YY, et al. (2020) Effects of low-dose aspirin on the prevention of preeclampsia and pregnancy outcomes: a randomized controlled trial from Shanghai, China. Eur J Obstet Gynecol Reprod Biol 248, 156163.Google Scholar
Rocha, G (2023) Consequences of early-onset preeclampsia on neonatal morbidity and mortality. Minerva Pediatr (Torino) 75, 8797.Google Scholar
Ye, W, Luo, C, Huang, J, et al. (2022) Gestational diabetes mellitus and adverse pregnancy outcomes: systematic review and meta-analysis. BMJ 377, e067946. Google Scholar
Champion, ML, Battarbee, AN, Biggio, JR, et al. (2022) Postpartum glucose intolerance following early gestational diabetes mellitus. Am J Obstet Gynecol MFM 4, 100609. Google Scholar
Phoswa, WN & Khaliq, OP (2021) The role of oxidative stress in hypertensive disorders of pregnancy (preeclampsia, gestational hypertension) and metabolic disorder of pregnancy (gestational diabetes mellitus). Oxid Med Cell Longev 2021, 5581570. Google Scholar
McElwain, CJ, Tuboly, E, McCarthy, FP, et al. (2020) Mechanisms of endothelial dysfunction in pre-eclampsia and gestational diabetes mellitus: windows into future cardiometabolic health. Front Endocrinol (Lausanne) 11, 655. Google Scholar
Bordoni, A, Danesi, F, Dardevet, D, et al. (2017) Dairy products and inflammation: a review of the clinical evidence. Crit Rev Food Sci Nutr 57, 24972525.10.1080/10408398.2014.967385CrossRefGoogle ScholarPubMed
Gardener, SL, Rainey-Smith, SR & Martins, RN (2016) Diet and inflammation in Alzheimer’s disease and related chronic diseases: a review. J Alzheimers Dis 50, 301334.10.3233/JAD-150765CrossRefGoogle ScholarPubMed
Vicente, BM, Lucio Dos Santos Quaresma, MV, Maria de Melo, C, et al. (2020) The dietary inflammatory index (DII®) and its association with cognition, frailty, and risk of disabilities in older adults: a systematic review. Clin Nutr ESPEN 40, 716.Google Scholar
Zhang, Z, Wu, Y, Zhong, C, et al. (2021) Association between dietary inflammatory index and gestational diabetes mellitus risk in a prospective birth cohort study. Nutr 87–88, 111193.Google Scholar
Liu, YH, Zheng, L, Cheng, C, et al. (2022) Dietary inflammatory index, inflammation biomarkers and preeclampsia risk: a hospital-based case-control study. Br J Nutr 129, 1528–1536.Google Scholar
Killeen, SL, Phillips, CM, Delahunt, A, et al. (2021) Effect of an antenatal lifestyle intervention on dietary inflammatory index and its associations with maternal and fetal outcomes: a secondary analysis of the PEARS trial. Nutrients 13, 2798. 10.3390/nu13082798CrossRefGoogle ScholarPubMed
Gao, X, Zheng, Q, Jiang, X, et al. (2022) The effect of diet quality on the risk of developing gestational diabetes mellitus: a systematic review and meta-analysis. Front Public Health 10, 1062304. Google Scholar
Moher, D, Liberati, A, Tetzlaff, J, et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6, e1000097.Google Scholar
Stang, A (2010) Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 25, 603605.Google Scholar
Fan, ZK, Wang, C, Yang, T, et al. (2022) Flavonoid subclasses and CHD risk: a meta-analysis of prospective cohort studies. Br J Nutr 128, 498508.Google Scholar
Zhao, Z, Wu, D, Gao, S, et al. (2023) The association between dairy products consumption and prostate cancer risk: a systematic review and meta-analysis. Br J Nutr 129, 17141731.Google Scholar
Sen, S, Rifas-Shiman, SL, Shivappa, N, et al. (2016) Dietary inflammatory potential during pregnancy is associated with lower fetal growth and breastfeeding failure: results from project viva. J Nutr 146, 728736.Google Scholar
Zhao, M, Yu, XL, Wang, HJ, et al. (2018) Dietary inflammatory index, inflammation biomarkers and preeclampsia risk: a hospital-based case-control study. Chin J Dis Control 22, 113116.Google Scholar
Shivappa, N, Hébert, JR, Akhoundan, M, et al. (2019) Association between inflammatory potential of diet and odds of gestational diabetes mellitus among Iranian women. J Matern Fetal Neonatal Med 32, 35523558.Google Scholar
Soltani, S, Aminianfar, A, Hajianfar, H, et al. (2021) Association between dietary inflammatory potential and risk of developing gestational diabetes: a prospective cohort study. Nutr J 20, 48. Google Scholar
Yang, XF (2021) Establishment of dietary inflammation index in Chinese pregnant women and its association with the risk of gestational diabetes mellitus: a prospective cohort study. Proceedings of the Special Nutrition and Health Promotion (2021) Symposium, 66–75.Google Scholar
Pajunen, L, Korkalo, L, Koivuniemi, E, et al. (2022) A healthy dietary pattern with a low inflammatory potential reduces the risk of gestational diabetes mellitus. Eur J Nutr 61, 14771490.Google Scholar
Moslehi, N, Sakak, FR, Teymoori, F, et al. (2022) The role of nutrition in the development and management of gestational diabetes among Iranian women: a systematic review and meta-analysis. J Diabetes Metab Disord 21, 951970.Google Scholar
Tan, QQ, Du, XY, Gao, CL, et al. (2021) Higher dietary inflammatory index scores increase the risk of diabetes mellitus: a meta-analysis and systematic review. Front Endocrinol 12, 693144. Google Scholar
Cavalcante, R, Lima, MM, Parente, J, et al. (2020) Inflammatory bowel diseases and diet: an integrative review. Rev Assoc Med Bras (1992) 66, 14491454.Google Scholar
Menzel, J, Biemann, R, Longree, A, et al. (2020) Associations of a vegan diet with inflammatory biomarkers. Sci Rep 10, 1933. Google Scholar
Itsiopoulos, C, Mayr, HL & Thomas, CJ (2022) The anti-inflammatory effects of a Mediterranean diet: a review. Curr Opin Clin Nutr Metab Care 25, 415422.Google Scholar
Melero, V, García de la Torre, N, Assaf-Balut, C, et al. (2020) Effect of a Mediterranean Diet-based nutritional intervention on the risk of developing gestational diabetes mellitus and other maternal-fetal adverse events in Hispanic women residents in Spain. Nutrients 12, 3505. 10.3390/nu12113505CrossRefGoogle ScholarPubMed
Zhang, X, Gong, Y, Della Corte, K, et al. (2021) Relevance of dietary glycemic index, glycemic load and fiber intake before and during pregnancy for the risk of gestational diabetes mellitus and maternal glucose homeostasis. Clin Nutr 40, 27912799.Google Scholar
Minhas, AS, Hong, X, Wang, G, et al. (2022) Mediterranean-style diet and risk of preeclampsia by race in the Boston birth cohort. J Am Heart Assoc 11, e022589. Google Scholar
Ou, M, Zhang, Q, Zhao, H, et al. (2021) Polyunsaturated fatty acid diet and upregulation of lipoxin A4 reduce the inflammatory response of preeclampsia. J Proteome Res 20, 357368.Google Scholar
Quan, W, Zeng, M, Jiao, Y, et al. (2021) Western dietary patterns, foods, and risk of gestational diabetes mellitus: a systematic review and meta-analysis of prospective cohort studies. Adv Nutr 12, 13531364.Google Scholar
Asadi, Z, Yaghooti-Khorasani, M, Ghazizadeh, H, et al. (2020) Association between dietary inflammatory index and risk of cardiovascular disease in the Mashhad stroke and heart atherosclerotic disorder study population. IUBMB Life 72, 706715.Google Scholar
Mizgier, M, Jarzabek-Bielecka, G & Mruczyk, K (2021) Maternal diet and gestational diabetes mellitus development. J Matern Fetal Neonatal Med 34, 7786.Google Scholar
Herlambang, H, Puspasari, A, Maharani, C, et al. (2022) Comprehensive fatty acid fractionation profilling in preeclampsia: a case control study with multivariable analysis. BMC Pregnancy Childbirth 22, 8. Google Scholar
Stephens, JM, Lee, J & Pilch, PF (1997) Tumor necrosis factor-α-induced insulin resistance in 3T3-L1 adipocytes is accompanied by a loss of insulin receptor substrate-1 and GLUT4 expression without a loss of insulin receptor-mediated signal transduction. J Biol Chem 272, 971976.Google Scholar
Piuri, G, Basello, K, Rossi, G, et al. (2020) Methylglyoxal, glycated albumin, PAF, and TNF-α: possible inflammatory and metabolic biomarkers for management of gestational diabetes. Nutrients 12, 479.Google Scholar
Aleksandrova, K, Koelman, L & Rodrigues, CE (2021) Dietary patterns and biomarkers of oxidative stress and inflammation: a systematic review of observational and intervention studies. Redox Biol 42, 101869.10.1016/j.redox.2021.101869CrossRefGoogle ScholarPubMed
Aggarwal, R, Jain, AK, Mittal, P, et al. (2019) Association of pro- and anti-inflammatory cytokines in preeclampsia. J Clin Lab Anal 33, e22834. Google Scholar
Nath, MC, Cubro, H, McCormick, DJ, et al. (2020) Preeclamptic women have decreased circulating IL-10 (Interleukin-10) values at the time of preeclampsia diagnosis: systematic review and meta-analysis. Hypertension 76, 18171827.Google Scholar
Hasain, Z, Mokhtar, NM, Kamaruddin, NA, et al. (2020) Gut microbiota and gestational diabetes mellitus: a review of host-gut microbiota interactions and their therapeutic potential. Front Cell Infect Microbiol 10, 188.10.3389/fcimb.2020.00188CrossRefGoogle ScholarPubMed
Ding, Q, Hu, Y, Fu, Y, et al. (2021) Systematic review and meta-analysis of the correlation between intestinal flora and gestational diabetes mellitus. Ann Palliat Med 10, 97529764.Google Scholar
Figure 0

Fig.1. PRISMA flow diagram of study selection process. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; GDM, gestational diabetes mellitus; DII, dietary inflammatory index.

Figure 1

Table 1. Characteristics of the included studies

Figure 2

Table 2. Methodological quality assessment score of the included studies

Figure 3

Fig. 2. Forest plot showing the association between the dietary inflammatory index score and the risk of gestational diabetes mellitus.

Figure 4

Fig. 3. Forest plot showing the association between the dietary inflammatory index score and the risk of preeclampsia.

Figure 5

Table 3. Subgroup analyses of the association between the DII score and GDM (95 % confidence intervals)

Figure 6

Fig. 4. Sensitivity analysis of dietary inflammatory index and gestational diabetes mellitus.

Supplementary material: File

Hong et al. supplementary material

Table S1 and Figures S1-S7

Download Hong et al. supplementary material(File)
File 1.1 MB