Re: 임신 활성산소 증가 --＞ dietary antioxidant 2023년

[문형철]

Antioxidants (Basel)

. 2023 Jul 15;12(7):1427. doi: 10.3390/antiox12071427

The Effect of Dietary Patterns and Nutrient Intake on Oxidative Stress Levels in Pregnant Women: A Systematic Review

Samar El Sherbiny 1, Giulia Squillacioti 1,*, Nicoletta Colombi 2, Federica Ghelli 1, Elena Lenta 3, Cloè Dalla Costa 3, Roberto Bono 1

Editor: Gwonhwa Song

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PMCID: PMC10376333  PMID: 37507965

Abstract

During pregnancy, reactive oxygen species (ROS) may physiologically increase due to changes and growth of mother and fetal tissues. Consequently, oxidative stress (OS) may occur and be involved in the onset of pregnancy and newborn complications. Among exogenous antioxidant sources, diet is a cost-effective prevention strategy supporting the health of mothers and newborns; however, there is still a lack of nutritional education during pregnancy interviews. This review aims to systematically summarize the knowledge on the association between OS and diet during pregnancy. Four electronic databases (PubMed Central, EMBASE, Web of Science, and Food Science and Technology Abstracts) were searched on 22 December 2022. Among 4162 records, 13 original articles were finally included. Overall, 80% of the studies considered dietary patterns as exposure and 60% of them assessed the association with malondialdehyde levels in blood and urine. Three studies analyzed the influence of daily intakes of fruit and vegetables on different OS biomarkers (malondialdehyde, nitric oxide and 8-hydroxy-2′-deoxyguanosine). Among studies exploring dietary fat intakes (39%), 80% focused on polyunsaturated fatty acids, finding a positive association with glutathione peroxidase, biopirryn and isoprostane levels, respectively. Four studies analyzed vitamin intakes and 50% of them in association with 8-hydroxy-2′-deoxyguanosine.

요약

임신 중에는 

산모와 태아의 조직의 변화와 성장으로 인해 

활성산소(ROS)가 생리적으로 증가할 수 있습니다. 

결과적으로 

산화 스트레스(OS)가 발생하여 

임신과 신생아 합병증의 발병에 관여할 수 있습니다. 

외인성 항산화제 중 식이요법은 

산모와 신생아의 건강을 지원하는 비용 효율적인 예방 전략이지만, 

임신 상담 시 영양 교육이 여전히 부족합니다. 

이 리뷰는 임신 중 OS와 식이요법 사이의 연관성에 대한 지식을 체계적으로 요약하는 것을 목표로 합니다. 2022년 12월 22일에 4개의 전자 데이터베이스(PubMed Central, EMBASE, Web of Science, Food Science and Technology Abstracts)를 검색했습니다. 4162개의 기록 중 13개의 원본 기사가 최종적으로 포함되었습니다. 

전반적으로, 

연구의 80%가 식습관을 노출로 간주했고, 

그 중 60%가 혈액과 소변의 말론디알데히드 수치와의 연관성을 평가했습니다. 

세 가지 연구는 

과일과 채소를 매일 섭취하는 것이 

다양한 OS 바이오마커(말론디알데히드, 산화질소, 8-하이드록시-2'-데옥시구아노신)에 

미치는 영향을 분석했습니다. 

식이 지방 섭취량을 조사한 연구들(39%) 중 80%는 

다불포화 지방산에 초점을 맞추고, 

글루타티온 퍼옥시다아제, 

바이오피린,

이소프로스테인 수준과 긍정적인 상관관계를 발견했습니다. 

glutathione peroxidase, biopirryn and isoprostane levels

글루타티온 과산화효소(GPx) 검사검사법

• 분광광도법을 이용한 효소 활성도 측정이 가장 일반적
• NADPH의 산화를 340nm에서 측정하여 GPx 활성도 계산
• 상용화된 키트를 이용한 ELISA 방법도 사용됨

정상 범위 및 해석

• 혈액 GPx 활성도 정상 범위: 17-69 U/g Hb
• 낮은 수치: 산화 스트레스 방어 능력 저하 가능성
• 높은 수치: 산화 스트레스에 대한 적응 반응일 수 있음

바이오피린 검사검사법

• 소변 검체를 이용한 ELISA 방법이 주로 사용됨
• 크레아티닌으로 보정하여 결과 표시

정상 범위 및 해석

• 정상 범위: 1.21 ± 0.61 U/g 크레아티닌
• 높은 수치: 산화 스트레스 증가 의미
• 질병의 중증도와 양의 상관관계를 보임

이소프로스테인 검사검사법

• GC-MS 또는 LC-MS/MS가 가장 정확한 방법
• ELISA 키트를 이용한 방법도 사용됨

정상 범위 및 해석

• 혈장 정상 범위: 35 ± 6 pg/mL
• 소변 정상 범위: 1.6 ± 0.6 ng/mg 크레아티닌
• 높은 수치: 지질 과산화 및 산화 스트레스 증가 의미

세 가지 검사 모두 산화 스트레스를 평가하는 데 유용하며, 질병의 중증도나 치료 효과 모니터링에 활용될 수 있습니다. 다만 검사법 표준화와 정상 범위 설정에 대한 추가 연구가 필요한 상황입니다.

비타민 섭취량을 분석한 연구 4건 중 

50%는 8-하이드록시-2′-데옥시구아노신과 연관성을 발견했습니다.

Keywords: oxidative stress, public health, pregnancy, dietary patterns, biomarkers, antioxidants, diet

1. Introduction

In 2016, the World Health Organization (WHO) provided global guidelines for a positive pregnancy experience. Among the 49 recommendations listed therein, 14 pertained to nutritional interventions. According to the WHO, maintaining a healthy lifestyle during pregnancy is crucial, and dietary counselling may support preventive strategies against potential pregnancy complications [1]. Conditions such as gestational diabetes mellitus, pre-term delivery [2], small-for-gestational-age babies [3], and pre-eclampsia [4], are associated with increased levels of oxidative stress (OS) during pregnancy. Although OS physiologically increases due to changes in maternal tissues and fetal growth [2,5], higher OS levels may be involved in several pathological conditions affecting both mothers and babies [5]. The adoption of a healthy and balanced diet is an affordable and natural way for humans to effectively increase the intake of large quantities of exogenous antioxidants [6]. Thus, effective primary prevention can also be achieved through a healthy and balanced diet, especially if rich in antioxidants. Dietary patterns are defined as the quantities, proportions, variety, and combination of different foods, as well as their consumption frequency [7,8]. Although traditional approaches used to investigate the impact of nutrition on health encompassed the analysis of a single or a few nutrients [9], nowadays the overall dietary model is applied to overcome some inherent limitations of the single-nutrient approach (e.g., the effect of a single nutrient can be too small to be detected) [8]. For this reason, the literature on this topic has increased in recent years and become fundamental for public health. Maternal nutrition during pregnancy is a major determinant of birth outcomes and, consequently, offspring health outcomes later in life. Moreover, diet can represent a useful, cost-effective and safe intervention to prevent most of the aforementioned OS-related conditions, during a time in which many pharmaceutical interventions are limited [10]. The association between maternal dietary patterns and infant birth outcomes has been summarized in previous reviews, with a specific focus on the relationship between dietary patterns and inflammatory state [11,12]. However, the relationship between maternal adherence to specific dietary patterns, maternal macronutrient intake and OS levels during pregnancy has not been eval‎uated yet [13]. Therefore, the aim of this work is to sum up the existing knowledge to fill the literature gap herein identified, and to verify the extent of the impact that diet can have on OS during pregnancy. Diet is a fundamental actor in the development of the fetus, and nutritional education should be introduced in the routine talk during pregnancy interviews.

1. 서론

2016년, 세계보건기구(WHO)는 긍정적인 임신 경험을 위한 글로벌 가이드라인을 제공했습니다. 이 가이드라인에 포함된 49개의 권고사항 중 14개는 영양 관련 개입에 관한 것이었습니다. WHO에 따르면, 임신 중 건강한 생활 방식을 유지하는 것이 매우 중요하며, 식이 상담은 임신 합병증에 대한 예방 전략을 지원할 수 있습니다 [1].

임신성 당뇨병,

조산 [2],

임신 연령에 비해 작은 아기 [3],

자간전증 [4]과 같은 조건은

임신 중 산화 스트레스(OS) 수준 증가와 관련이 있습니다.

산모 조직의 변화와 태아의 성장으로 인해

생리적으로 산화 스트레스가 증가하지만 [2,5],

산모와 아기 모두에게 영향을 미치는 여러 병리학적 조건에

더 높은 산화 스트레스 수준이 관여할 수 있습니다 [5].

건강하고 균형 잡힌 식단을 채택하는 것은

인간이 대량의 외인성 항산화제 섭취를 효과적으로 늘릴 수 있는

저렴하고 자연스러운 방법입니다 [6].

따라서,

특히 항산화제가 풍부한 경우,

건강하고 균형 잡힌 식단을 통해 효과적인 1차 예방을 달성할 수도 있습니다.

식이 패턴은

다양한 음식의 양, 비율, 종류, 조합, 그리고

섭취 빈도로 정의됩니다 [7,8].

영양이 건강에 미치는 영향을 조사하는 전통적인 접근 방식은

단일 영양소 또는 몇 가지 영양소를 분석하는 것이었지만[9],

오늘날에는

단일 영양소 접근 방식의 본질적인 한계(예: 단일 영양소의 효과가 너무 작아서 감지할 수 없음)를 극복하기 위해

전체적인 식이 모델을 적용하고 있습니다[8].

이러한 이유로

최근 몇 년 동안 이 주제에 관한 문헌이 증가했으며,

공중 보건의 기초가 되었습니다.

임신 중 산모의 영양 상태는

출산 결과와 그 결과로 나타나는 자녀의 건강 결과에 큰 영향을 미칩니다.

또한,

식이요법은

많은 제약적 개입이 제한되는 시기에

앞서 언급한 OS 관련 질환의 대부분을 예방하는 데 유용하고

비용 효율적이며 안전한 개입이 될 수 있습니다 [10].

산모의 식습관과 유아의 출산 결과 사이의 연관성은

식습관과 염증 상태 사이의 관계에 초점을 맞춘 이전의 리뷰에서 요약되어 있습니다 [11,12].

그러나,

특정 식이 패턴에 대한 산모의 준수,

산모의 다량 영양소 섭취,

임신 중 OS 수준 사이의 관계는 아직 평가되지 않았습니다 [13].

따라서,

이 연구의 목적은

기존 지식을 요약하여 문헌에서 확인된 격차를 메우고,

식단이 임신 중 OS에 미칠 수 있는 영향의 정도를 검증하는 것입니다.

식단은

태아 발달의 기본 요소이며,

임신 상담 중 일상적인 대화에서 영양 교육이 도입되어야 합니다.

2. Materials and Methods

This review was conducted according to the recommendations from Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA [14] and based on the registered PROSPERO protocol (Protocol n. CRD42023387270). Due to the prioritization of COVID-19 protocol registrations, the current submission passed a basic automated check and was published automatically.

2.1. Search Strategy

The search was conducted considering only original research. A preliminary search in PubMed, Embase and Web of Science supported the definition of specific keywords and gold-standard articles to be included in the review. Clinical trial registries, such as The World Health Organization International Clinical Trials Registry Platform (WHO-ICTRP), Clinicaltrial.gov (accessed on 14 December 2022) and the International Standard Randomized Controlled Trial Numbers (ISRCTN) registry, were also considered in this phase. This preliminary research enabled us to exclude randomized clinical trials and focus solely on observational studies due to a lack of suitable results for our work. In fact, the identified results were a small number and only single food were administered (e.g., yogurt or salmon), which was not in line with our goal. Additionally, we chose to avoid combined intervention with supplementation, as they can influence the biological results [15]. The search strategy was specifically tailored to each electronic database and was conducted on 22 December 2022. Four databases, PubMed Central, Embase, Web of Science and Food Sciences and Technology Abstracts (FSTA) were searched. The full search string is available in Appendix A.

2.2. Eligibility Criteria

The inclusion criteria for the studies were as follows: (1) original observational research; (2) involving pregnant women at any stage of gestation, (≥16 years); (3) measuring OS biomarkers in urine and/or blood; (4) including diet and/or nutritional habits as the main intervention/exposure; (5) published in English with a full text available. Systematic reviews, scoping reviews, expert opinions, editorials, conference abstracts and primary research reporting non-quantitative data, based on animal or in vitro experiments, were excluded. Additionally, studies involving any kind of antioxidant supplementation, pathological condition (e.g., gestational diabetes, pre-eclampsia, and hypertension,) or combined intervention (e.g., diet and physical exercise) including multiple pregnancies were excluded. Two independent reviewers carried out the screening process of titles, abstracts and full texts.

2.3. Data Extraction

Data were extracted and recorded in a customized Excel spreadsheet. The extracted information includes study design data (e.g., study type, study duration, aim, country, and main findings), population and sample information (e.g., sample size, age, Body Mass Index (BMI), and gestational age), details on diet (dietary pattern, nutritional habits, specific nutrients, and dietary assessment tool), and information about OS/antioxidant biomarkers (including units of measure, collection time, analytical method, and biological matrix). A particular focus was placed on extracting data regarding the association between diet and OS biomarkers. If different time points during the pregnancy were reported in the original paper, all the time points were extracted. Similarly, if different OS biomarkers or measurements at different time points were available, all of them were extracted. After the extraction process, a second reviewer checked data and all eventual discrepancies were discussed.

2.4. Quality Assessment

The quality of the included articles was assessed based on the study design using appropriate checklists to eval‎uate the risk of bias (RoB) of the included articles. Specifically, the employed tools were: the National Institutes of Health (NIH) Quality Assessment Tool [16], for observational cohort, cross-sectional and case–control studies, and the NUtrition QUality Eval‎uation Strengthening Tools (NUQUEST) [17], a specific tool for eval‎uating RoB in nutritional studies. Two reviewers independently conducted the quality assessment and any discrepancies were discussed. Since the tools use different ratings, we expressed our eval‎uation as a percentage, and the final score was recoded based on tertiles (1st tertile 0–33% = poor quality; 2nd tertile 34–66% = medium quality; 3rd tertile 67–100% = high quality).

3. Results

A total of 4162 studies were initially identified from the databases used. After removing 1426 duplicates, the titles and abstracts of the remaining 2736 articles were screened based on the inclusion and exclusion criteria defined in the PROSPERO protocol. After the screening phase, 2667 studies that did not meet the inclusion criteria were excluded. At the end of the selection process, 69 papers were examined, and of these, 13 were included in this review. Figure 1 presents the entire process. The main reasons for exclusion relied on the absence of OS biomarkers and/or nutrition data, while other studies did not meet other eligibility criteria (e.g., age range, antioxidant supplementation, full text not available in English, studies conducted only on subjects suffering from a diagnosed disease).

3. 결과

처음에 사용된 데이터베이스에서 총 4162건의 연구가 확인되었습니다. 1426건의 중복을 제거한 후, PROSPERO 프로토콜에 정의된 포함 및 제외 기준에 따라 나머지 2736건의 논문의 제목과 초록을 심사했습니다. 심사 단계가 끝난 후, 포함 기준을 충족하지 못한 2667건의 연구는 제외되었습니다. 선정 과정이 끝날 무렵, 69편의 논문이 검토되었고, 그 중 13편이 이 리뷰에 포함되었습니다. 그림 1은 전체 과정을 보여줍니다. 제외된 주요 이유는 OS 바이오마커 및/또는 영양 데이터가 없기 때문이었고, 다른 연구들은 다른 자격 기준(예: 연령 범위, 항산화제 보충, 영어로 된 전문이 없는 경우, 진단받은 질병을 앓고 있는 피험자만을 대상으로 한 연구)을 충족하지 못했기 때문입니다.

Figure 1.

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PRISMA flow diagram (Modified from: [15]). Abbreviations: FSTA: Food Science and Technology Abstracts; OS: oxidative stress.

3.1. Study and Participant Characteristics

Table 1 summarizes the characteristics of the studies. They were mainly conducted in the USA (n = 4), Mexico (n = 4), and Korea (n = 3). Only one study was located in Europe (Spain) and one in Japan, for a total of three continents and four countries. The publication dates range from 2001 to 2022. The majority of the studies used a cohort study design (69%) [13,18,19,20,21,22,23,24,25], while 23% employed a cross-sectional design [26,27,28], and only one study had a case–control design [4]. The study sample sizes ranged from 33 to 1158, totaling 5088 healthy women included in this systematic review, aged between 19 and 40 years. Only five articles (38%) reported the detailed educational distribution of the participants [13,18,19,22,24]. Among them, 84% achieved a middle/high education level. Participants’ BMI ranged between 18 and 35, and they were enrolled between 0 and 39 weeks of gestation. Two studies were omitted to report the gestational age of the participants at enrolment [23,28].

3.1. 연구와 참가자 특성

표 1은 연구의 특성을 요약한 것입니다. 주로 미국(n = 4), 멕시코(n = 4), 한국(n = 3)에서 실시되었습니다. 유럽(스페인)과 일본에서 각각 1건의 연구가 실시되었으므로, 총 3개 대륙과 4개 국가에서 연구가 실시되었습니다. 출판 연도는 2001년부터 2022년까지입니다. 대부분의 연구가 코호트 연구 설계(69%)를 사용했습니다[13,18,19,20,21,22,23,24,25], 23%는 횡단면 설계를 사용했습니다[26,27,28], 단 한 건의 연구만이 사례-대조군 설계를 사용했습니다[4]. 연구 표본의 규모는 33명에서 1,158명까지 다양했으며, 이 체계적 문헌고찰에 포함된 건강한 여성은 총 5,088명이었습니다. 참가자의 상세한 교육 수준을 보고한 논문은 5개(38%)에 불과했습니다[13,18,19,22,24]. 그 중 84%가 중등/고등 교육 수준을 달성했습니다. 참가자들의 BMI는 18에서 35 사이였고, 임신 0주에서 39주 사이에 등록되었습니다. 등록 당시 참가자들의 임신 기간을 보고하기 위해 두 개의 연구가 생략되었습니다

Table 1.

Study characteristics as reported by the original studies included in the systematic review. The risk of bias was firstly assessed using the National Institutes of Health (NIH) [16] Quality Assessment Tool and the NUtrition QUality Eval‎uation Strengthening Tools (NUQUEST) [17] checklist and then reported as average scoring among them.

Study ReferenceCountryStudy DesignSample SizeMaternal Age (Mean ± s.d.)Dietary Exposure/Assessment MethodOS BiomarkersMain FindingsRisk of Bias

Ballesteros-Guzmán, A.K. 2019 [28]	Mexico	Cross-sectional	33	30.1 ± 3.6	Average macro and micronutrients/FFQ	MDA/TAC	No significant associations between maternal diet and MDA, TAC. ↑Vit C significantly associated with ↑MDA	Medium
Chen, X. 2003 [21]	USA	Cohort	408	29.6 ± 3.8	Dietary fat intake/24 h recall	GPx	↑PUFA, n-3 and n-6 FA significantly associated with ↑GPx activity	High
Diaz-Garcia, H. 2022 [23]	Mexico	Cohort	90	24.4 ± 5.5	Daily nutrients intake/FFQ	8OHdG	↑Vit A intake significantly related to ↓8OHdG levels	Medium
Hwang, J. 2021 [24]	Korea	Cohort	1158	32.7 ± 4.5	Dietary pattern 1, 2, 3/SFFQ	MDA	Dietary pattern 1 significantly associated to ↓MDA in urine	Medium
Kim, H. 2011 [18]	South Korea	Cohort	715	29.52 ± 4.97	Fruits and vegetables intake/SFFQ	MDA	Significant correlation between ↑fruit and vegetable intake and ↓MDA	Medium
Kim, Y. J. 2005 [26]	Korea	Cross-sectional	235	NA	Meat and vegetables consumption/Questionnaire	MDA/ 8OHdG	No significant differences between patterns and their association with OS	Medium
Lopez-Yañez Blanco A. 2022 [27]	Mexico	Cross-sectional	238	22.9 ± 0.78	Fruits and vegetables intake/FFQ	MDA/NO	↑ Fruit and vegetables intake significantly associated to ↓OS	Medium
Matsuzaki, M. 2014 [25]	Japan	Cohort	49	26.3 ± 5.4	PUFA intake/BDHQ	Biopyrrin/ CoQ10	↑ PUFA intake during the 3rd trimester significantly associated with ↑ biopyrrin	High
Morales, E. 2022 [13]	Spain	Cohort	665	20 to 40	Mediterranean diet, DASH diet, AHEI/FFQ	8OHdG/Isoprostane	↑ Adherence to rMED significantly associated with ↓8OHdG levels, ↑ adherence to DASH diet marginally associated to ↓ Isop	Medium
Rodriguez-Cano A. M. 2022 [19]	Mexico	Cohort	119	21.86 ± 0.23	Ultra-processed food consumption/24 h recall	TAC/MDA/PC	↓UPF intake significantly associated to ↑ TAC, UPF negatively associated with MDA	High
Scholl, T. O. 2001 [4]	USA	Case–control	52	24.1 ± 5.2	Dietary fat, vitamins intake/24 h recall	8OHdG	Significant correlation between ↑SFA and ↑8OHdG	High
Scholl, T. O. 2005 [20]	USA	Cohort	307	NA	Daily nutrients intake/24 h recall	Isoprostane/TAC	Maternal diet significantly associated with ↑Isop, ↑PUFA significantly associated with ↑Isop	Medium
Tylavsky, F. A. 2022 [22]	USA	Cohort	1019	31	OBS/FFQ	Isoprostane	↑ OBS significantly associated with ↓ Isop	Medium

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↑ increase; ↓ decrease. Abbreviations: SFA: saturated fatty acids; PUFA: polyunsaturated fatty acids; FFQ: food frequency questionnaire; SFFQ: semi-quantitative food frequency questionnaire; BDHQ: Brief Diet History Questionnaire; OBS: oxidative balance score; MDA: malondialdehyde; NA: Not Available; TAC: total antioxidant capacity; PC: protein carbonylation; GPx: glutathione peroxidase; 8OHdG: 8-hydroxy-2′-deoxyguanosine; CoQ10: Coenzyme Q10; NO: nitric oxide, Vit: vitamin. Pattern 1: high consumption of grains, light-colored vegetables, legumes, fruits, meat, eggs, fish, and nuts. Pattern 2: low consumption of white rice, poultry, meat, and red meat by-products. Pattern 3: high consumption of grains, milk, and yogurt and low consumption of rice cake, legumes, snacks, bony fish, and tofu/soy milk. DASH: Dietary Approaches to Stop Hypertension; AHEI: Alternate Healthy Index; rMED: relative Mediterranean Diet; aMED: alternative Mediterranean Diet; UPF: ultra-processed food. Data on biomarkers with no significant associations with diet were not reported unless differently indicated.

3.2. Biomarkers of OS

The main characteristics of the OS biomarkers and biological matrix are summarized in Table 2.

Table 2.

Oxidative stress biomarkers and biological matrices of the included studies.

Study ReferenceBiological MatrixOS BiomarkerAnalytical Method

Kim, H. 2011 [18]	Urine *	MDA [µmol/g creatinine]	HPLC
Kim, Y. J. 2005 [26]		MDA [µmol/g creatinine]	HPLC
Kim, Y. J. 2005 [26]		8OHdG [µg/g creatinine]	ELISA
Scholl, T. O. 2001 [4]		8OHdG	ELISA
Tylavsky, F. A. 2022 [22]		Isoprostane	MS
Hwang, J. 2021 [24]		MDA [µmol/g creatinine]	HPLC
Matsuzaki, M. 2014 [25]		Biopyrrin [µmol/g creatinine]	ELISA
Matsuzaki, M. 2014 [25]		CoQ10 [ng/mL]	HPLC
Diaz-Garcia, H. 2022 [23]	Blood (Plasma)	8OHdG [ng/mL]	ELISA
Lopez-Yañez Blanco A. 2022 [27]		MDA [µmol/L]	Colorimetric (TBARS)
Lopez-Yañez Blanco A. 2022 [27]		NO [µmol/L]	Colorimetric (Griess assay)
Ballesteros-Guzmán, A.K. 2019 [28]		MDA [µmol/L]	Colorimetric (TBARS)
Ballesteros-Guzmán, A.K. 2019 [28]	Blood (Serum)	TAC [nmol/µL/µg protein]	Colorimetric
Rodriguez-Cano A. M. 2022 [19]	Blood (Serum and Plasma)	MDA [nmol/mg dry weight]	Colorimetric (Gérard-Monnier)
Rodriguez-Cano A. M. 2022 [19]		TAC [nmol/mg protein]	Colorimetric (CUPRAC)
Rodriguez-Cano A. M. 2022 [19]		PC [pmol trolox equivalent/mg protein]	DNPH method
Chen, X. 2003 [21]		GPx [mU/mg Hb]	Colorimetric
Morales, E. 2022 [13]	Urine * and Blood (Serum and Plasma)	Isoprostane [ng/mg creatinine]	ELISA
Morales, E. 2022 [13]		8OHdG [ng/mL]	ELISA
Scholl, T. O. 2005 [20]		Isoprostane [ng/mg creatinine]	ELISA
Scholl, T. O. 2005 [20]		TAC [µmol/L]	ELISA

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* Urine samples are always spot urine. Abbreviations: OS: oxidative stress; MDA: malondialdehyde; HPLC: High-Performance Liquid Chromatography; 8OHdG: 8-hydroxy-2′-deoxyguanosine; ELISA: enzyme-linked immunosorbent assay; MS: Mass Spectrometry; CoQ10: Coenzyme Q10; TBARS: thiobarbituric acid reactive substances; NO: nitric oxide; TAC: total antioxidant capacity; CUPRAC: CUPric Reducing Antioxidant Capacity; PC: protein carbonylation; DNPH: dinitropenylhydrazine; GPx: glutathione peroxidase.

Overall, 46% of the studies measured OS biomarkers in spot urine, a non-invasively collected matrix, while 38% used blood. Only two studies (15%) used both blood and urine. In all the studies, a spot of urine was collected [4,13,18,20,22,24,25,26]; and in seven articles, a blood sample was collected. Among these, 57% used plasma, 29% used serum and in one study, whole blood was collected. A variety of analytical techniques has been used for the detection of OS biomarkers: Enzyme-linked immunosorbent assay (ELISA) (46%), colorimetric assays (31%), and High-Performance Liquid Chromatography (HPLC) (31%). Other techniques include Mass Spectrometry, CUPric Reducing Antioxidant Capacity (CUPRAC) and dinitropenylhydrazine (DNPH) (respectively [19,22]). The two most investigated biomarkers in relation to diet were malondialdehyde (MDA) (46%) and the DNA oxidation product, namely 8-hydroxy-2-deoxyguanosine (8OHdG) (31%). Considering the biological matrices, the most investigated OS markers in urine were MDA [18,24,26] and isoprostane [13,20,22], followed by 8OHdG. Only one study [25] investigated Biopyrrin and Coenzyme Q10 (CoQ10). In plasma, MDA and total antioxidant capacity (TAC) were the two most analyzed biomarkers, while 8OHdG, protein carbonylation (PC), and nitric oxide (NO) were only analyzed in one study, respectively. In serum and whole blood, the analyzed biomarkers were 8OHdG, glutathione peroxidase (GPx), and TAC. Only 23% of the studies collected more than one biological sample at different time points to measure the OS levels.

전체적으로,

연구의 46%가

비침습적으로 수집된 매트릭스인 소변의 OS 바이오마커를 측정했고,

38%는 혈액을 사용했습니다.

단 두 개의 연구(15%)만이 혈액과 소변을 모두 사용했습니다.

모든 연구에서 소변 샘플을 채취했습니다 [4,13,18,20,22,24,25,26];

그리고 7개의 논문에서 혈액 샘플을 채취했습니다.

이 중 57%는 혈장을, 29%는 혈청을 사용했고, 한 연구에서는 전혈을 채취했습니다.

OS 바이오마커의 검출을 위해 다양한 분석 기법이 사용되었습니다. 효소결합 면역흡착 분석법(ELISA) (46%), 비색 분석법(31%), 고성능 액체 크로마토그래피(HPLC) (31%). 다른 기술로는 질량 분석법, CUPRAC(CUPric Reducing Antioxidant Capacity), DNPH(dinitropenylhydrazine) 등이 있습니다(각각 [19,22]).

식이 요법과 관련하여 가장 많이 연구된 바이오마커는

말론디알데히드(MDA)(46%)와

DNA 산화 생성물인 8-하이드록시-2-데옥시구아노신(8OHdG)(31%)이었습니다.

생물학적 매트릭스를 고려할 때,

소변에서 가장 많이 연구된 OS 마커는

MDA[18,24,26]와 이소프로스타네[13,20,22]였으며,

그 다음으로 8OHdG가 뒤를 이었습니다.

단 한 건의 연구[25]만이

바이오피린과 코엔자임 Q10(CoQ10)을 조사했습니다.

혈장에서는 MDA와 총 항산화 능력(TAC)이 가장 많이 분석된 두 가지 바이오마커였고, 8OHdG, 단백질 카르보닐화(PC), 산화질소(NO)는 각각 한 건의 연구에서만 분석되었습니다. 혈청과 전혈에서 분석된 바이오마커는 8OHdG, 글루타티온 퍼옥시다아제(GPx), TAC입니다. OS 수준을 측정하기 위해 서로 다른 시점에 두 가지 이상의 생물학적 샘플을 수집한 연구는 23%에 불과했습니다.

3.3. Dietary Assessment

Three main tools were used for the assessment of dietary intake of food and nutrients. The most frequently used was the 24 h recall method (38%), followed by the food frequency questionnaire (FFQ) (31%). Two studies (15% [13]) utilized a semi-quantitative FFQ, and another two studies used other questionnaires ([25,26]). Almost all the researchers that used a FFQ or one of its derivatives (SFFQ: semi-quantitative food frequency questionnaire; BDHQ: Brief Diet History Questionnaire) explained in detail the number of items that compose the questionnaire, the diet type, and the reference period during which it was administered. Only Ballesteros-Guzmán et al. [28] did not mention the number of items, diet type, and reference period. The items number of the FFQ and similar questionnaires, ranged from 62 [25] to 138 [24]. As per the 24 h recall method, Kim et al. [18] used a single recall, while all the other studies utilized three recalls [4,19,20,21]. The majority of the questionnaires have been administered during each trimester [4,19,20,21,25], three studies took into consideration the second trimester [13,22,26], and two studies referred to the third trimester [23,25,27]. Three studies did not specify the reference period of the questionnaire [26,28]. Overall, only 38% of the studies included in the present review applied multiple dietary measurements over time. The questionnaires were used mainly to assess the Mexican diet (23%) [19], the Korean diet (15%) [18,24], and the Western diet (31%) [4,20,21,22].

3.3. 식이 평가

식사와 영양소 섭취량 평가를 위해 세 가지 주요 도구가 사용되었습니다.

가장 빈번하게 사용된 방법은

24시간 회상법(38%)이고,

그 다음으로 음식 빈도 설문지(FFQ)가 사용되었습니다(31%).

두 연구(15% [13])에서는 반정량적 FFQ를 활용했고, 다른 두 연구에서는 다른 설문지를 사용했습니다([25,26]). FFQ 또는 그 파생 질문지(SFFQ: 준정량적 식품 빈도 설문지, BDHQ: 간단한 식이 이력 설문지)를 사용한 거의 모든 연구자들은 설문지를 구성하는 항목의 수, 식이 유형, 설문지를 시행한 기준 기간을 자세히 설명했습니다. Ballesteros-Guzmán et al. [28]만이 항목 수, 식이 유형, 기준 기간을 언급하지 않았습니다. FFQ 및 유사한 설문지의 항목 수는 62 [25]에서 138 [24]까지 다양했습니다. 24시간 회상법에 따라, Kim et al. [18]은 단일 회상을 사용했고, 다른 모든 연구는 3회 회상을 사용했습니다 [4,19,20,21]. 설문지의 대부분은 각 임신 기간에 실시되었습니다 [4,19,20,21,25], 3개의 연구는 임신 후기 [13,22,26]를 고려했으며, 2개의 연구는 임신 후기 [23,25,27]를 언급했습니다. 세 가지 연구는 설문지의 참조 기간을 명시하지 않았습니다 [26,28]. 전반적으로, 본 연구에 포함된 연구 중 38%만이 시간에 따른 여러 가지 식습관 측정을 적용했습니다. 설문지는 주로 멕시코 식습관(23%) [19], 한국 식습관(15%) [18,24], 서양 식습관(31%) [4,20,21,22]을 평가하는 데 사용되었습니다.

3.4. Dietary Patterns and Dietary Exposure Assessment

Dietary exposure was assessed using a questionnaire in all the included studies. Five of them [13,19,22,24,26] were able to identify dietary patterns starting from the questionnaire, while the others [4,18,20,21,23,25,27,28] assessed the consumption of fruit and vegetable, fat, and vitamins, expressed as g/day or g/1000 kcal.

Among the five studies that calculated dietary patterns only one [24] used a posteriori approach, based on the reduced-rank regression (RRR) method, to establish and define the patterns, starting from the data collected with the SFFQ. Morales et al. [13] used a priori-defined dietary index, which includes relative Mediterranean Diet (rMED), alternative Mediterranean Diet (aMED), Dietary Approach to Stop Hypertension (DASH), Alternate Healthy Index (AHEI), and AHEI-2010. Finally, Kim et al. [26] eval‎uated the frequency of meat and vegetables consumption, while Rodriguez-Cano et al. [19] appraised the ultra-processed food (UPF) consumption starting from the data collected according to the NOVA definition [29]. Tylavsky et al. [22] decided to eval‎uate the antioxidant power of the diet in relation with the OS levels, using an a priori method composed of the HEI score employed to validate the efficacy of the oxidative balance score they wanted to test.

Three studies [18,26,27] analyzed the impact of fruit and vegetable consumption on OS levels during pregnancy. Among them, Kim et al. decided to analyze the weekly frequency of consumption of vegetables, while in [27] and [18] was taken into account the daily consumption of both fruits and vegetables.

Another type of dietary exposure considered from five studies [4,19,20,21,25] was the consumption of total fats and polyunsaturated fatty acids (PUFA). All the articles except for Matsuzaki et al. [25], took into consideration the total fat intake and the fatty acid composition. [25] analyzed only the correlation between PUFA and OS. In particular, 40% of the studies took into account the total fat composition, the amount of PUFA, saturated fatty acids (SFA), and ω-3 and ω-6 daily intake. The 80% estimate PUFA intake, of this percentage, 75% consider the total daily intake of ω-3 and ω-6. A single study [4] estimates only the SFA consumption in addition to total fats without considering PUFA quantity.

Among the thirteen included studies, four [4,20,23,28] also reported the influence of vitamin intake on OS biomarkers. All of them measured the daily intake of vitamins A, C, and E.

3.4. 식습관 패턴과 식습관 노출 평가

모든 연구에서 식이 노출은 설문지를 사용하여 평가되었습니다. 그 중 5개 연구[13,19,22,24,26]는 설문지를 통해 식이 패턴을 확인할 수 있었지만, 나머지 연구[4,18,20,21,23,25,27,28]는 과일과 채소, 지방, 비타민 섭취량을 g/일 또는 g/1000kcal로 평가했습니다.

식습관 패턴을 계산한 5개의 연구 중 단 한 건[24]만이 SFFQ로 수집한 데이터를 바탕으로 패턴을 설정하고 정의하기 위해 감소 순위 회귀(RRR) 방법을 기반으로 한 후후적 접근 방식을 사용했습니다.

Morales et al. [13]은

상대적 지중해식(rMED),

대안적 지중해식(aMED),

고혈압 예방을 위한 식이요법(DASH),

대체 건강 지수(AHEI), AHEI-2010을 포함하는 사전 정의된 식이 지수를 사용했습니다.

마지막으로,

Kim et al. [26]은

육류와 채소 섭취 빈도를 평가했고,

Rodriguez-Cano et al. [19]은 NOVA 정의에 따라 수집된 데이터를 바탕으로

초가공식품(UPF) 섭취량을 평가했습니다 [29].

Tylavsky et al. [22]은

그들이 테스트하고자 하는 산화 균형 점수의 유효성을 검증하기 위해 사용된

HEI 점수로 구성된 선험적 방법을 사용하여,

OS 수준과 관련하여 식단의 항산화력을 평가하기로 결정했습니다.

세 가지 연구[18,26,27]는

임신 기간 동안 과일과 채소 섭취가 OS 수준에 미치는 영향을 분석했습니다.

그 중에서도 김 외.는

채소 섭취 빈도를 주 단위로 분석하기로 결정한 반면, [27]과 [18]은

과일과 채소 모두의 일일 섭취량을 고려했습니다.

다섯 가지 연구[4,19,20,21,25]에서 고려된

또 다른 유형의 식이 노출은

총 지방과 다중불포화지방산(PUFA)의 섭취였습니다.

Matsuzaki et al. [25]을 제외한 모든 논문은

총 지방 섭취량과 지방산 구성을 고려했습니다.

[25]은 PUFA와 OS 간의 상관관계만을 분석했습니다. 특

히, 연구의 40%는 총 지방 구성, PUFA의 양, 포화 지방산(SFA), 그리고 매일 섭취하는 ω-3와 ω-6의 양을 고려했습니다. 이 중 80%는 PUFA 섭취량을 추정했고, 이 중 75%는 매일 섭취하는 ω-3와 ω-6의 총량을 고려했습니다. 한 연구[4]는 PUFA의 양을 고려하지 않고 총 지방과 SFA 섭취량만을 추정했습니다.

포함된 13개의 연구 중 4개[4,20,23,28]는 비타민 섭취가 OS 바이오마커에 미치는 영향에 대해서도 보고했습니다.

이들 모두 비타민 A, C, E의 일일 섭취량을 측정했습니다.

3.5. Dietary Patterns, Nutrient Intakes and OS Biomarkers

3.5.1. OS and Dietary Patterns

Overall, 39% of the studies considered dietary patterns as exposure exploring the association between OS reduction and a healthy diet (i.e., rich in fruits, vegetables, legumes, cereals, fish and olive oil with low consumption of red meat and alcohol, comparable to a Mediterranean pattern) [13,19,22,24,26]. Among them, 60% eval‎uated MDA. One study identifies a significant reduction in MDA levels in the presence of a “healthy diet” (p = 0.001) [24]. Another study [19] found controversial result: a significant decrease in MDA was detected in women consuming a UPF-rich diet (β = −0.0052, −0.007, −0.003, p < 0.0001), and a decrease in TAC in relation to UPF consumption was observed (β = −0.0005, −0.001, −0.000, p = 0.002). Daily higher intakes of fruits and vegetables, fiber, grain, nuts, and legumes were associated with significant lower levels of MDA (Spearman’s rho = −0.061, p < 0.01) [18], (Kruskal–Wallis test, p < 0.05) [27]. No significant associations were found between dietary patterns characterized by high consumption of meat and vegetables, and MDA levels [26]. The association between dietary patterns and 8OHdG was assessed by [13,26], but only [13] identified a significant result for the Mediterranean diet (β = −8.02, CI −15.4, −0.64, p for trend = 0.026). Tylavsky et al. [22], identified a significant decrease in isoprostane levels as the antioxidant power of the diet increase (p for trend = 0.0003).

3.5. 식습관, 영양소 섭취량, OS 바이오마커

3.5.1. OS와 식습관 패턴

전체적으로, 연구의 39%가

OS 감소와 건강한 식습관(과일, 채소, 콩류, 곡물, 생선, 올리브 오일을 많이 섭취하고,

적색육과 알코올 섭취를 줄이는 지중해식 식습관)의 연관성을 조사하는 데

식습관 패턴을 노출로 간주했습니다 [13,19,22,24,26].

그 중 60%가

MDA를 평가했습니다.

한 연구에서는

“건강한 식단”이 있을 때

MDA 수치가 현저하게 감소한다는 사실을 확인했습니다(p = 0.001) [24].

또 다른 연구[19]에서는 논란의 여지가 있는 결과를 발견했습니다: UPF가 풍부한 식단을 섭취하는 여성에서 MDA가 유의미하게 감소하는 것으로 나타났습니다(β = −0.0052, −0.007, −0.003, p < 0.0001). 그리고 UPF 섭취와 관련하여 TAC의 감소가 관찰되었습니다(β = −0.0005, −0.001, −0.000, p = 0.002).

매일 과일과 채소, 섬유질, 곡물, 견과류, 콩류를 많이 섭취할수록

MDA 수치가 현저히 낮아졌습니다(스피어만 상관계수 = −0.061, p < 0.01) [18], (크루스칼-월리스 검정, p < 0.05) [27].

육류와 채소를 많이 섭취하는 식습관과 MDA 수치 사이에는

유의미한 연관성이 발견되지 않았습니다 [26].

--> truth reflex 검사상 '아니다'

식습관과 8OHdG 사이의 연관성은 [13,26]에 의해 평가되었지만, 지중해식 식습관(β = -8.02, CI -15.4, -0.64, p for trend = 0.026)에 대해서만 유의미한 결과가 확인되었습니다. Tylavsky et al. [22]은 식이 항산화 능력이 증가함에 따라 이소프로스테인 수치가 현저하게 감소하는 것을 확인했습니다(추세에 대한 p = 0.0003).

3.5.2. OS and Fruit and Vegetable

Kim et al. [18], Kim et al. [26] and Lopez-Yañez Blanco et al. [27] investigated the impact of fruit and vegetable intake on OS levels. All of them explored the association with MDA and two of them [18,27] identified also an inverse correlation between a higher intake of fruits and vegetables and a decrease in MDA levels (r = −0.061, p < 0.01) [18] (p < 0.05) [27]. NO decreased, which was inversely correlated with high fruit and vegetables intake (p < 0.05) [27], while 8OHdG showed no significant association with frequent consumption of vegetables (p = 0.323) [26].

3.5.2. OS와 과일과 채소

김 외. [18], 김 외. [26], 로페즈-야네즈 블랑코 외. [27]은 과일과 채소 섭취가 OS 수준에 미치는 영향을 조사했습니다. 그들 모두는 MDA와의 연관성을 조사했고, 그 중 두 연구[18,27]에서는

과일과 채소의 섭취량이 많을수록

MDA 수치가 낮아지는 역상관관계도 확인했습니다(r = −0.061, p < 0.01) [18] (p < 0.05) [27].

NO는 감소했는데,

이는 과일과 채소 섭취량이 많을수록 감소하는 것과 반비례하는 것으로 나타났습니다(p < 0.05) [27],

반면 8OHdG는 채소 섭취 빈도와 유의미한 상관관계가 없었습니다(p = 0.323) [26].

3.5.3. OS and Dietary Fats

Total fat and PUFA consumption was explored by five [4,19,20,21,25] out of the thirteen included studies. Four [4,20,21,25] over five studies observed a significant association between fat and PUFA amount in the diet, and OS biomarkers. Both [20,21] found that high levels of total fat, PUFA, ω6, and ω3 in the maternal diet were associated with OS increase. More specifically, they registered an increase in isoprostane excretion (p for trend (total fat and ω6) <0.05, p for trend (PUFA and ω3) <0.001) and GPx activity (Total fat: β = 0.045 ± 0.012, p < 0.001, PUFA: β = 0.104 ± 0.04, p < 0.03, ω3: β = 0.820 ± 0.022, p < 0.03, and ω6: β = 0.106 ± 0.05, p < 0.03), respectively. Similarly, 8OHdG was positively correlated with SFA levels (Pearson’ r = 0.38, p = 0.007) [4], and Biopyrrin, was higher in response to high intake of PUFA (β = −0.44, p < 0.001) [25]. Noteworthy, 75% of the studies that found a significant association observed it during the third trimester of pregnancy. Rodriguez-Cano et al. [19] did not identify any significant association with the three biomarkers analyzed (MDA, TAC, and PC).

3.5.3. OS와 식이 지방

총 지방과 PUFA 섭취량은 13개의 연구 중 5개[4,19,20,21,25]에서 조사되었습니다. 5개 연구 중 4개[4,20,21,25]는 식이 지방과 PUFA 섭취량과 OS 바이오마커 사이의 유의미한 연관성을 관찰했습니다.

두 연구 [20,21] 모두 산모의 식단에서

총 지방, 고도불포화지방, 오메가6, 오메가3의 함량이 높을수록

OS가 증가한다는 사실을 발견했습니다.

--> truth reflex 상 '아니다'

     다른 원인이다. 특히 글루텐, 유당, 과당, 설탕때문이다. yes

보다 구체적으로, 그들은 이소프로스타네 배설의 증가(추세에 대한 p(총 지방 및 ω6) <0.05, 추세에 대한 p(PUFA 및 ω3) <0.001)와 GPx 활성(총 지방: β = 0.045 ± 0.012, p < 0.001, PUFA: β = 0.104 ± 0.04, p < 0.03, ω3: β = 0.820 ± 0.022, p < 0.03, ω6: β = 0.106 ± 0.05, p < 0.03), 각각. 마찬가지로, 8OHdG는 SFA 수치와 양의 상관관계가 있었습니다(Pearson의 r = 0.38, p = 0.007) [4], 그리고 바이오피린은 PUFA의 높은 섭취에 대한 반응이 더 높았습니다(β = −0.44, p < 0.001) [25]. 주목할 만한 점은, 유의미한 연관성을 발견한 연구의 75%가 임신 3기에 이를 관찰했다는 것입니다. Rodriguez-Cano et al. [19]은 분석된 세 가지 바이오마커(MDA, TAC, PC)와 유의미한 연관성을 확인하지 못했습니다.

3.5.4. OS and Vitamins

Lastly, vitamins intake from food was examined by four studies [4,20,23,28]. Only two of them identified an association with OS. [28] found that maternal MDA was positively associated with vitamin C intake (p < 0.05). Diaz-Garcia et al. [23] highlighted that higher intake of dietary vitamin A is beneficial and can significantly reduce 8OHdG levels (Spearman’ rho = −0.445, p < 0.001). This result was not confirmed by Scholl [4], who analyzed vitamins A, C, and E, and did not find any significant reduction in DNA damage. Another study by Scholl et al. in 2005 [20] investigated the association of dietary vitamins intake and isoprostane and TAC levels. Again, they did not find any significant relationship. Two studies [4,20] verified also the impact of β-carotene and did not find any relation with OS. Table 3 reports results on the association between OS and dietary exposure. The most analyzed biomarker was MDA (46% of the studies). Of them, 83% identified a significant association between diet and MDA levels. Isoprostane was measured in 23% of the studies, with 67% of significant results, while 8OHdG was quantified in 31% of the studies, with 75% of significant results. TAC was assessed in 23% of studies and resulted to be the least correlated with diet (33%). Four studies used other biomarkers, 75% of them showed a significant result.

3.5.4. OS와 비타민

마지막으로, 음식에서 섭취한 비타민을 조사한 연구가 4개 있었습니다 [4,20,23,28]. 그 중 2개만이 OS와의 연관성을 확인했습니다. [28]은 산모의 MDA가 비타민 C 섭취량과 양의 상관관계가 있다는 것을 발견했습니다(p < 0.05). Diaz-Garcia et al. [23]은 식이성 비타민 A의 섭취량이 많을수록 유익하며, 8OHdG 수치를 상당히 감소시킬 수 있다고 강조했습니다(Spearman의 rho = −0.445, p < 0.001). 그러나 비타민 A, C, E를 분석한 Scholl [4]은 이 결과를 확인하지 못했으며, DNA 손상의 현저한 감소도 발견하지 못했습니다. Scholl 등의 2005년 연구 [20]에서는 식이 비타민 섭취와 이소프로스테인 및 TAC 수치 간의 연관성을 조사했습니다. 이 연구에서도 유의미한 상관관계가 발견되지 않았습니다. 두 연구 [4,20]에서도 β-카로틴의 영향을 검증했지만, OS와의 상관관계는 발견되지 않았습니다. 표 3은 OS와 식이 노출 간의 연관성에 대한 결과를 보여줍니다. 가장 많이 분석된 바이오마커는 MDA였습니다(연구의 46%). 그 중 83%가 식단과 MDA 수치 사이에 유의미한 상관관계를 확인했습니다. 이소프로스타네는 23%의 연구에서 측정되었으며, 67%에서 유의미한 결과가 나왔습니다. 한편, 8OHdG는 31%의 연구에서 정량화되었으며, 75%에서 유의미한 결과가 나왔습니다. TAC는 23%의 연구에서 평가되었으며, 식단과 가장 낮은 상관관계(33%)를 보였습니다. 4건의 연구에서 다른 바이오마커를 사용했는데, 그 중 75%에서 유의미한 결과가 나타났습니다.

Table 3.

Association between oxidative stress and dietary exposure.

BiomarkerQuantification Rate in Included StudiesSignificant Association between OS and Diet in the Included StudiesDietary Exposure

MDA	46%	83%	Dietary pattern/fruit and vegetables intake
Isoprostane	23%	67%	Antioxidant diet/fat and PUFA intake
8OHdG	31%	75%	Dietary pattern/fat and PUFA intake/vitamins intake
TAC	23%	33%	Dietary pattern
Others	31%	75%	Fat and PUFA intake/fruit and vegetables intake

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Abbreviations: MDA: malondialdehyde; PUFA: polyunsaturated fatty acids; 8OHdG: 8-hydroxy-2′-deoxyguanosine; TAC: total antioxidant capacity.

3.6. Risk of Bias (RoB) Assessment

The overall scoring was quite homogenous among the studies. The quality assessment according to NIH tool ranked 62% (n = 8) of the studies as “medium quality”, 31% as “high quality” (n = 4), and 8% as “poor quality” (n = 1) [28]. The NUQUEST scale instead classified 62% of the studies as “medium quality” (n = 8), 31% as “high quality”, and just one study classified as “poor quality” [26]. The mean score is in Table 1. We averaged the scoring from different tools obtaining 69% medium-quality studies, meaning that they could be affected by a certain degree of RoB, and 31% high-quality studies. The main weaknesses identified by both tools were a lack of multiple biomarker measures, and none of the studies provides a sample size justification or a power description. Only three studies provided information on the participation rate. These issues have been highlighted by both eval‎uation scales.

4. Discussion

This systematic review offers a summary of the current knowledge about the influence of diet on OS biomarkers during pregnancy. Different dietary habits and patterns were explored including the Mediterranean diet and the Western diet but also single-food and single-nutrient intakes such as fruits, vegetables, fats and vitamins. We observed that the contribution of dietary patterns on OS has been measured by different OS biomarkers. The most frequently measured biomarker was MDA, whose levels were significantly lower in association with patterns rich in fruit and vegetables. 8OHdG showed an increase in the presence of a diet rich in saturated fats and a decrease in relation to a Mediterranean pattern, which seems to be protective against DNA damage from free radicals, data already present in the literature [30]. Higher urinary isoprostane levels were associated with a Western diet, while in women who followed an antioxidant diet, isoprostane excretion was significantly lower. Biopyrrin increased considerably in relation to PUFA consumption, especially during the third trimester. Concerning the TAC and the enzymes involved in the antioxidant response, they were associated with UFP and high-fat consumption, respectively. NO was associated with higher intakes of fruit and vegetables consumption. No significant results were observed for other biomarkers such as PC and CoQ10.

4. 토론

이 체계적인 검토는 임신 중 OS 바이오마커에 대한 식단의 영향에 대한 현재의 지식을 요약하여 제공합니다. 지중해식 식단과 서양식 식단을 포함한 다양한 식습관과 식습관 패턴뿐만 아니라 과일, 채소, 지방, 비타민과 같은 단일 식품 및 단일 영양소 섭취도 조사되었습니다. 우리는 OS에 대한 식습관 패턴의 기여도가 다양한 OS 바이오마커에 의해 측정되었음을 관찰했습니다. 가장 빈번하게 측정된 바이오마커는 MDA였으며, 과일과 채소가 풍부한 식습관과 연관되어 그 수치가 현저히 낮았습니다. 8OHdG는 포화지방이 풍부한 식단의 존재가 증가하고, 자유 라디칼에 의한 DNA 손상을 방지하는 것으로 보이는 지중해식 식단과 관련하여 감소하는 것으로 나타났습니다. 이는 이미 문헌에 발표된 데이터입니다 [30]. 요로 이소프로스타네 수치가 높을수록 서양식 식단과 관련이 있는 반면, 항산화 식단을 따르는 여성의 경우 이소프로스타네 배설이 현저히 낮았습니다. 바이오피린은 특히 임신 3분기 동안, PUFA 섭취와 관련하여 상당히 증가했습니다. TAC와 항산화 반응에 관여하는 효소들은 각각 UFP와 고지방 섭취와 관련이 있었습니다. NO는 과일과 채소 섭취량 증가와 관련이 있었습니다. PC와 CoQ10과 같은 다른 바이오마커에 대해서는 유의미한 결과가 관찰되지 않았습니다.

Although the analysis of the overall diet could provide a better understanding of the effect of diet on OS and health, many studies still focus on single-nutrient analysis. In recent years, nutritional epidemiology moved to dietary pattern analysis and tried to buck the trend, but there is still a lack of trials and observational studies regarding overall pattern effects [31]. It is possible that the absence of a unique and validated method of pattern assessment led authors to focus on the single-nutrient approach. We observed that the most frequently used method was a priori, based on index calculations created from dietary recommendations. This approach can be useful to reduce the bias determined by the subjective reporting of the FFQ and 24 h recalls but is limited by the current knowledge behind index construction [8]. Another option is the a posteriori approach, which is dependent on what the subject declared in the questionnaire. In fact, the construction of the statistical model strictly depends on dietary data obtained on the basis of eating behavior. Questionnaires such as FFQ or 24 h dietary recall are the most common tools used to collect dietary information from people, but they have some limitations; people tend to underestimate the amount and quality of the foods that they consume, and the report is subjective [32]. Therefore, also in a posteriori-derived method, results might be biased. An example is the result obtained by Rodriguez-Cano and colleagues [19] about MDA levels in relation to UPF consumption. Their controversial result can be attributed to this phenomenon, along with the effect modification played by BMI (i.e., women with higher BMI and higher exposure to UPF could be expected to exhibit higher levels of MDA.) [33,34]. The dietary assessment method can expose to methodological issues able to produce biased results. To date many more studies on the relationship between UPF and MDA are required to clarify this point. A possible strategy to limit some methodological problem is to assess dietary consumption at different time points during the observation [32]. Another option could be combining different dietary assessment methods and, possibly, integrating them with a biological measure, (e.g., nutritional biomarkers) [35]. Hwang et al. [24] applied this method, by using some nutritional biomarkers such as serum folate, iron and zinc as intermediate response variables to derive the patterns by applying the RRR method. They observed a relation between dietary pattern 1 (balanced and rich in fruits, vegetables, grains and legumes), nutritional biomarkers and OS biomarkers. A similar approach has been applied by Tylavsky et al. [22], who derived an oxidative balance score (OBS), calculated on the basis of dietary anti and pro-oxidant power.

Another fundamental aspect of the study design is the choice of the OS biomarkers and the timing of biological sample collection. The use of a single measurement may produce pitfalls, as biomarkers quantified only at the beginning of gestation, are not representative of the overall trend of the pregnancy. Conversely, sample collection during the third trimester without a baseline measure does not consider that OS during the third trimester is physiologically higher [2]. The lack of repeated biological measurement can constitute an important source of bias. Repeated measures are essential to reduce measurement errors and flatten the physiological OS fluctuations during pregnancy. Despite all these possible methodological problems, the quality assessment suggested that most of the studies have medium or low risk of bias. We used different RoB tools with the aim of partly overcoming a potential RoB underestimation. Although the NUQUEST scale is specifically created to eval‎uate nutritional studies, we observed almost no difference between the scoring derived from NIH and the NUQUEST. This can be attributed to the fact that some studies did not have the eval‎uation of diet with respect to OS as the main outcome of the study.

In addition to the analysis of overall patterns, the eval‎uation of fruit and vegetables consumption can be considered similarly important, since they are the main source of antioxidants (vitamins and non-nutrient sources) and fibers, and they are related to lower levels of OS [36]. The WHO recommendations for a healthy and balanced diet suggest to eat at least 400 g of fruit and vegetables per day, in order to assume all the essential micronutrients, and fibers [37,38]. Moreover, guidelines from Harvard University recommends a new way to make a healthy eating plate (Figure 2), in which fruit and vegetables represent half of the meal. Despite these recommendations, fruit and vegetables consumption during pregnancy is generally low [38,39]. Fruit and vegetables intake was assessed by three studies [18,26,27], and in two of them, a positive correlation was identified with the reduction in MDA. The only study that found no association with vegetables was [26], probably because it considered only the frequency of consumption per week, and fruit was not considered. Two groups [18,27] studied the impact of fruit and vegetable intake on MDA, in order to assess the possible relationship with OS. In both studies, a positive association was found, meaning that a significant reduction in MDA was detected in subjects who consume higher quantities of fruit and vegetables.

Figure 2.

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Healthy eating plate.

With regard to dietary fat intake, three [20,21,25] out of four studies identified a significant association with OS during the third trimester. The increase in OS, due to fat catabolism, and the release of free fatty acids during the third trimester is in line with previous studies [2,40,41]. In addition, the influence of a diet rich in fats could contribute to this increase [42,43]. One of the main methods used to measure OS-derived damage in vivo is the assessment of lipid peroxidation products. PUFAs are susceptible to oxidative damage [44], so it is reasonable to expect that a high-fat diet, rich in PUFA, may contribute to OS increase by offering substrates for lipid peroxidation product creation such as MDA and isoprostane [45]. Hence, MDA and isoprostane can be useful OS biomarkers as suggested by the mechanism depicted in Figure 3. Although this phenomenon is theoretically plausible, many studies did not confirm‎ our hypothesis [45,46]. Of the five studies that analyzed the association between dietary fats and OS, only two [19,20] quantify the lipid peroxidation products MDA and isoprostane, respectively. Isoprostane was positively associated with dietary fats intake [20], meaning that with the increase in total fat and PUFA consumption, an increase in urinary isoprostane was observed. Lipid peroxidation products can be used as OS biomarkers to assess the oxidative damage of a high-fat diet, but further studies are required, to clarify dietary fat role in their metabolism. TAC showed no significant correlation in both the studies that eval‎uated it [19,20] probably because both populations’ diets were characterized by UPF consumption or, broadly, we can assume they followed a Western diet model. The Western diet is typically associated with low consumption of high-quality and nourishing foods, such as non-refined carbohydrates (fruits and vegetables) and legumes proteins, essential for vitamins, minerals, nutrients, and antioxidants supply [43]. Therefore, the lack of antioxidants from the diet could have been balanced by the activation of enzymatic antioxidant defence. This latter hypothesis seems to be confirmed by Chen et al. [21], who quantified GPx and found a significant correlation between the increase in total fat, PUFA consumption, and increase in GPx activity during the third trimester. The last biomarker with a significant correlation with PUFA intake is byopirrin. Biopyrrin is an oxidized metabolite of bilirubin. Bilirubin is able to scavenge ROS, and the reaction products (biopyrrins) are excreted in urine [47]. Biopyrrin shows a significant increase with a high level of PUFA intake. The same study also suggested the possible influence of dietary PUFA on CoQ10. CoQ10 can be considered a marker of OS due to its strong antioxidant activity [25], but the association with diet was found not significant. Finally, Scholl et al. [4], analyzed the impact of SFA intake on DNA damage by using 8OHdG as a biomarker. The result is a significant correlation between the intake of SFA and DNA damage. In conclusion, from the included studies the most interesting OS biomarkers to eval‎uate the impact of high-fat diets are lipid peroxidation products, byopirrins, and GPx activity in relation to PUFA intake, while for the eval‎uation of the damage operated by SFA, 8OhdG seems to be effective. Further studies are required to clarify the impact of a high-fat diet on OS and to confirm‎ the role of the aforementioned biomarkers.

Figure 3.

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Suggested mechanism of dietary fats contribution to lipid peroxidation. Dietary fats may represent a source of substrates for lipid peroxidation products. ROS: reactive oxygen species; PUFA: polyunsaturated fatty acids (figure Created with BioRender.com).

Vitamins, and more specifically, vitamin C and E, are acknowledged for their antioxidant properties. Vitamin C is mostly present in fruit and vegetables and can exert its antioxidant role in aqueous environments. Despite all the evidence about their antioxidant actions, many trials report controversial information about their effectiveness in the reduction of OS [48]. More in depth, vitamin C has been reported as having a pro-oxidant effect that depends strongly on iron availability [49]. The pro-oxidant activity consists mainly in promoting DNA damage under pathological conditions. Despite this controversial function, vitamin C more often plays an antioxidant role [50] as proposed in Figure 4. Ballesteros-Guzmán et al. [28] found a positive correlation between vitamin C intake and MDA, confirm‎ing the pro-oxidant role of ascorbic acid. It is noteworthy that they did not give us some essential information about the dietary pattern that was taken into consideration, or about the timing of biological sample collection, so it is difficult to make any assumption about their results.

Figure 4.

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Dietary antioxidant mechanism of action of vitamin A, vitamin E and vitamin C (figure Created with BioRender.com). Abbreviations: ROS: reactive oxygen species; sMaf: small musculoaponeurotic fibrosarcoma proteins; ARE: antioxidant response element; ATRA: all-trans-retinoic acid; RAR: retinoic acid receptors; RXR: retinoid X receptor; RARE: retinoic acid response elements; α-TO∙: α-tocopheroxyl radical; α-TOH: α-tocopherol; LOOH: lipid hydroperoxide; LOO∙: lipid peroxyl radicals; PUFA: polyunsaturated fatty acids; AA: ascorbic acid; DHAA: dehydroascorbic acid.

Vitamin A has an important antioxidant action too, but different from that of vitamins C and E. In particular, all-trans-retinol, which is the active metabolite of vitamin A acts as an indirect antioxidant, regulating the transcription of some genes involved in antioxidant response (e.g., NRF2 pathway) (Figure 4). Since this action is more complex than that of vitamins C and E which have a direct antioxidant activity (by quenching ROS, and preventing lipid peroxidation, respectively), this can explain why only one out of four studies identified a correlation between vitamin A intake and OS regulation. Another possible explanation of the lack of results could be that very often vitamin A is mistakenly considered a direct antioxidant vitamin, with a function similar to that of vitamins C and E. The only direct antioxidant activity of vitamin A, can be searched in provitamin A carotenoids such as β-carotene [51]. Both [4,20] quantified β-carotene, but did not find any significant relationship with OS biomarkers (isoprostane and TAC, and 8OHdG, respectively), as for vitamin A. [23] looks for a correlation between vitamin A and DNA damage operated by free radicals, through 8OhdG quantification, finding a significant association between them (A higher tertile of vitamin A consumption corresponds to a lower 8OhdG excretion). Given the all-trans-retinol regulatory function, we can expect to see a long-term effect compared to that of direct antioxidants. Thus, it would be useful to quantify the activity of enzymes such as GPx, SOD, and CAT in addition to the DNA damage.

Vitamin E (α-tocopherol) is an important antioxidant thanks to its ability in preventing lipid peroxidation, and as a ROS scavenger [51] (Figure 4). [4,20] eval‎uated vitamin E intake in an American population, characterized by the Western type of diet acknowledged for its pro-oxidant properties and high consumption of ultra-processed foods able to increase the OS and inflammatory state of the body. Hence, it is possible that the antioxidant effect of vitamins was covered by the pro-oxidant effect of the high fat consumption. In [23,28], the population was Mexican; from the literature, we know that the Mexican diet is similar to a Mediterranean pattern [52], but they failed in the identification of a correlation with OS too. Overall, the reason for the lack of significant results in vitamin influence on OS need to be searched in the fact that micronutrients effect could be too small to be detected. The positive results of Diaz-Garcia [23] can be due also to the fact that the global consumption of fruit and vegetables in their populations is higher than the American one.

From a broader point of view, we also need to keep in mind that people do not eat isolated nutrients, but all the nutrients assumed through diet can interact and can have a collaborative function inside our organism. The low percentage of significant results regarding OS and vitamins is more likely to be attributed to the overall effect that multiple nutrients of the meal have on the oxidative balance, rather than an actual lack of effectiveness of vitamins as antioxidants.

Strength and Limitations

One of the main strengths is that the present systematic review followed a rigorous method. An a priori protocol has been established to ensure transparency and scientific rigor. Two reviewers carried out independently the screening phases, as well as the quality assessment of the studies. To the best of our knowledge, this is the first work that revises all the existing articles about the relationship of OS and diet during pregnancy. Another strength is the use of two different tools for the RoB assessment. By using the NUQUEST scale, we tried to overcome a critical issue, which is the lack of criteria to eval‎uate nutritional interventions in human nutrition studies. The main limitations of our study are the heterogeneity of the biomarkers and of the dietary patterns, which precluded us from conducting a meta-analysis. Moreover, the analysis of studies focused on single nutrients should be considered a limitation too, due to their aforementioned collaborative function inside our body.

5. Conclusions

Among many different biomarkers analyzed by the studies in this review, blood and urinary MDA seems to be the most influenced by both dietary patterns and micronutrients. As expected, a high intake of fruit and vegetables is protective from MDA increase, while a controversial result was found regarding diets rich in ultra-processed foods. Concerning other biomarkers, diets rich in fruit and vegetables seemed correlated with NO decrease. Some significant results have been obtained for isoprostane urine levels, which drops in the presence of an antioxidant diet and increases in the presence of the Western diet with high consumption of fats. DNA damage quantified by 8OHdG (in both blood and urine) shows an increase in correlation with a diet rich in saturated fats, and a decrease in relation to a Mediterranean pattern and vitamin A consumption. Another biomarker that shows a significant increase in relation to high fat consumption is biopyrrin. In terms of antioxidant capacity and antioxidant enzymatic response, only two studies gave positive results, respectively, in correlation to ultra-processed-food consumption and high fat ingestion. The remaining biomarkers, namely PC and CoQ10, show no correlation with diet. In conclusion, despite the heterogeneity of biomarkers analyzed in this review, diet is confirmed as an important factor in the modulation of OS during pregnancy. Further studies with an appropriate methodology and appropriate OS biomarker eval‎uation are required.

Acknowledgments

We would like to thank the Biblioteca Federata di Medicina Ferdinando Rossi of the University of Turin, for their precious support.

Appendix A

Search strategy used for each database.