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. 2022 Oct 17;19:201. doi: 10.1186/s12978-022-01509-4

Global prevalence of congenital anencephaly: a comprehensive systematic review and meta-analysis

Nader Salari 1, Behnaz Fatahi 2, Reza Fatahian 3, Payam Mohammadi 4, Adibeh Rahmani 5, Niloofar Darvishi 2, Mona Keivan 6, Shamarina Shohaimi 7, Masoud Mohammadi 8,✉
PMCID: PMC9575217  PMID: 36253858

Abstract

Background

Anencephaly is a fatal congenital anomaly characterized by the absence of brain hemispheres and cranial arch. Timely preventive measures can be taken by knowing the exact prevalence of this common neural tube defect; thus, carried out through systematic review and meta-analysis, the present study was conducted to determine the worldwide prevalence, incidence and mortality of anencephaly.

Methods

Cochran’s seven-step instructions were used as the guideline. Having determined the research question and inclusion and exclusion criteria, we studied MagIran, SID, Science Direct, WoS, Web of Science, Medline (PubMed), Scopus, and Google Scholar databases. Moreover, the search strategy in each database included using all possible keyword combinations with the help of “AND” and “OR” operators with no time limit to 2021. The I2 test was used to calculate study heterogeneity, and Begg and Mazumdar rank correlation tests were employed to assess the publication bias. Data were analyzed by Comprehensive Meta-Analysis software (Version 2).

Results

In this study, the statements of Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) were used. In the first stage, 1141 articles were found, of which 330 duplicate studies were omitted. 371 articles were deleted based on the inclusion and exclusion criteria by reviewing the title and abstract of the study. 58 articles were removed by reviewing the full text of the article because it was not relevant to the research. 360 studies with a sample size of 207,639,132 people were considered for the meta-analysis. Overall estimate of the prevalence, incidence and attenuation of anencephaly worldwide were 5.1 per ten thousand births (95% confidence interval 4.7–5.5 per ten thousand births), 8.3 per ten thousand births (95% confidence interval 5.5–9.9 per ten thousand births), 5.5 per ten thousand births (95% confidence interval 1.8–15 per ten thousand births) respectively the highest of which according to the subgroup analysis, belonged to the Australian continent with 8.6 per ten thousand births (95% confidence interval 7.7–9.5 per ten thousand births).

Conclusion

The overall prevalence of anencephaly in the world is significant, indicating the urgent need for preventive and treating measures.

Keywords: Prevalence, Neural tube defects, Anencephaly, Systematic review and meta-analysis

Plain Language summary

Anencephaly is a fatal congenital anomaly characterized by the absence of brain hemispheres and cranial arch. Cochran’s seven-step instructions were used as the guideline. Having determined the research question and inclusion and exclusion criteria, we studied MagIran, SID, Science Direct, WoS, Web of Science, Medline (PubMed), Scopus, and Google Scholar databases. Moreover, the search strategy in each database included using all possible keyword combinations with the help of “AND” and “OR” operators with no time limit to 2021. Out of 1141 initial articles found, and after excluding repetitive ones in various databases and those irrelevant to inclusion criteria, 360 studies with a sample size of 207,639,132 people were considered for the meta-analysis. Overall estimate of the prevalence, incidence and attenuation of anencephaly worldwide were 5.1 per ten thousand births (95% confidence interval 4.7–5.5 per ten thousand births), 8.3 per ten thousand births (95% confidence interval 5.5–9.9 per ten thousand births), 5.5 per ten thousand births (95% confidence interval 1.8–15 per ten thousand births) respectively the highest of which according to the subgroup analysis, belonged to the Australian continent with 8.6 per ten thousand births (95% confidence interval 7.7–9.5 per ten thousand births). The overall prevalence of anencephaly in the world is significant, indicating the urgent need for preventive and treating measures.

Background

Neural Tube Defects (NTDs) are considered the most common congenital anomalies of the central nervous system (CNS) [1], and the second most serious ones after inborn heart defects [2]. Non-spontaneous neural tube closure between the 3rd and 4th weeks of intrauterine growth is considered as the leading cause of this defect [1]. Regarding the etiology of these defects, most cases are attributed to the interaction between different genes and environmental factors, known as a multifactorial inheritance [3]. Studies indicate that immediate family members are more at risk compared to others; in other words, if a child is born with NTD, the risk of recurrence in future pregnancies is between 25 and 50 times higher than in general cases [4, 5, 6]. Moreover, diabetes mellitus, using valproic acid to treat epilepsy during pregnancy, obesity, zinc deficiency, hyperthermia, and folate deficiency are all predisposing factors for neural tube defects [7, 8].

Though being significantly various in different geographical areas, the incidence of NTD is generally around 1 in 1000 live births or (NTD affects about 1 in 1000 live births on average, however this varies greatly by area.) [4, 9]. Pathologically, neural tube defects vary from a small, uncomplicated opening in the posterior canal of the vertebrae to the failure of the entire neural tube to close, leading to the most severe type of defect that is craniorachischisis [10]. The most recurring cases include anencephaly, spina bifida, and encephalocele [10].

Anencephaly is a fatal congenital malformation characterized by the absence of hemispheres of the brain and cranial arch [11]. Anencephaly is the most common CNS disorder in the Western world, occurring 37 times more frequently in women than men [12]. Babies born with such defects generally die at birth or shortly thereafter while newborns with spina bifida and encephalocele require special medical care and surgery to survive [13]. Prevalence of anencephaly mortality (100%), compared to Spina bifida (7%) and encephalocele (46%), is significantly higher [14]; thus, anencephaly is considered as a taxing burden on public health worldwide that may lead to significant human resources loss [15].

Frog-like appearance, short neck, bulging eyes, and large tongue are characteristic features of infants with anencephaly [16]. About 12% of cases of anencephaly are associated with other structural abnormalities [17], including Cleft lip, cleft palate, clubfoot and omphalocele (Anencephaly is linked to additional structural abnormalities in around 12% of cases [17], such as cleft lip, cleft palate, clubfoot, and omphalocele) [16]. Anencephaly was the first congenital anomaly to be detected by ultrasound, and it can be diagnosed at weeks 12–13 of pregnancy while preventive measures include controlling known risk factors and offering medical counseling to couples about termination of pregnancy [16]. Previous studies have demonstrated that anencephaly is a multifactorial process that is controlled by genes and numerous other environmental factors. However, recent studies reveal that folic acid supply before and in the early stages of pregnancy (1 to 3 months before pregnancy and up to 12 weeks of gestation) can dramatically prevent anencephaly and reduce its prevalence by 50–70% [18]. The U.S. Public Health Service and the Food and Nutrition Council of the Institute of Medicine, along with the National Research Council, recommend that all women of childbearing potential can take 0.4 mg of folic acid daily to reduce the risk of developing neural tube defects [19, 20].

Annually, about 300,000 babies are born with neural tube defects, resulting in 88,000 deaths and 8.6 million lifelong disabilities [21]. The occurrence of anencephaly varies over time and geographically. For instance, the prevalence of this defect in northern Iran in 1998–2005 was estimated at 12 per 10,000 births [22] while In Texas, the United States, 2.81 per 10,000 births during 1999–2003 were reported [23]. The prevalence of anencephaly based on data collected from (EUROCAT) member countries during the years 2000 and 2010, was estimated at 3.52 per 10,000 births [24].

Considering the importance of anencephaly as the most severe type of neural tube defect, and its detrimental effects on the quantity and quality of patients’ and parents’ life, and regarding the serious health, psychological, social and economic costs for the individual and society, accurate identification of patients is of great importance to organize health care services and implement preventive measures. In addition, because of various statistics on the prevalence of anencephaly and the worldwide absence of a comprehensive investigation capable of analyzing the outcomes of these studies, the present research was conducted through a systematic review and meta-analysis to shed light on the prevalence, incidence and mortality of anencephaly worldwide.

Methods

The present systematic review and meta-analysis was conducted based on the Cochrane 7-step approach, including: research question selection, inclusion and exclusion criteria, article identification, study selection, study quality evaluation, data extraction, and analysis and interpretation of findings [25]. In this study, the statements of Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) were used [26].

Research question and keyword determination

According to the research question “How has the prevalence, incidence and mortality of anencephaly changed worldwide?” the following were defined:

The study population (Population) included patients with anencephaly, result (Outcome) comprised the prevalence of anencephaly, date of publishing the first related article until March 23, 2021 was specified as the time range (Time or Duration), and type of study (study design) included cross-sectional studies (descriptive, descriptive-analytical). Keywords were extracted from the MeSH browser. Keywords related to the studied population (P): Anencephaly, Congenital Absence of Brain, Anencephalus, Anencephalia, Incomplete Anencephaly, Partial Anencephaly, Hemicranial Anencephaly, Aprosencephaly and Keywords related to outcome were (O), Prevalence, outbreak.

Inclusion and exclusion criteria according to the research question

Cross-sectional population-based studies (descriptive, descriptive-analytical) that reported the prevalence of anencephaly in different parts of the world, published in Persian and English with full texts available included in the study. Analytical, interventional, conferential, and group-case studies irrelevant to the research question and studies that were not in English or did not have English abstracts were excluded from the investigation.

Article identification

To review the literature, two Persian databases, including MagIran and SID, and four international ones, Science Direct, Web of Science (WoS), Medline (PubMed), and Scopus, were selected. The Google Scholar scientific search engine was considered for final review while no time limit was set for the search to retrieve relevant results; thus, all articles published up to March 23, 2021 were reviewed. Searching was limited to studies published in Persian and English and strategy in each database was determined using Advanced Search (Advance Search) with the help of all possible keyword combinations with the help of AND and OR operators. For example, searching strategy in the PubMed database was determined as follows:

(prevalence [Title/Abstract] OR outbreak [Title/Abstract]) AND (Anencephaly [Title/Abstract] OR Congenital Absence of Brain [Title/Abstract] OR Anencephalus [Title/Abstract] OR Anencephalia [Title/Abstract] OR Incomplete Anencephaly [Title/Abstract] OR Partial Anencephaly [Title/Abstract] OR Hemicranial Anencephaly [Title/Abstract] OR Aprosencephaly [Title/Abstract]).

In order to access the latest published studies, an alert was created on a number of important databases, including PubMed and Scopus, to check if new articles were published during the study. Also, in order to access all related studies, the sources of articles that met the inclusion criteria were manually reviewed. To avoid error, all steps of article search, study selection, qualitative evaluation and data extraction were performed independently by two researchers (BF and ND). If there was a difference of opinion among the researchers regarding the inclusion of the article in the study, in order to avoid the risk of biased selections for specific studies, first a final agreement was reached through discussion and in some cases with the participation and opinion of a third party (MM).

Selection of studies based on inclusion and exclusion criteria

The information of all articles found in each database was transferred to EndNote X8 software. After completing the search in all the databases, duplicate articles were excluded. Then, in order to avoid the risk of prejudice in selecting studies, the names of the authors and the titles of the journals of the articles were removed and a checklist was prepared based on the titles and abstracts of the studies. In the next step, two authors (N.D. and B.F.) independently examined the title and abstract of the research and eliminated irrelevant papers based on the inclusion and exclusion criteria. Studies with no full text were not considered for the systematic review and meta-analysis process. The full text of all remaining articles was then evaluated. Studies that did not meet the inclusion criteria based on the research question were out listed.

Qualitative evaluation of studies

Qualitative evaluation of studies was performed using the Newcastle–Ottawa Scale, the NOS assigns a maximum of 9 points for the three areas of study group selection, group comparison, and exposure and outcome for the case and group studies [27]. Based on this, articles were classified as high quality (≥ 5) and low quality (< 5).

Extracting the data

After selecting the studies to enter the systematic review and meta-analysis process, the data were extracted and the studies were summarized. An electronic checklist was prepared for this purpose. The various items on the checklist included: the surname of the first author, year of publication and year of the report, sample size, number of patients, prevalence, incidence and mortality of patients.

Statistical analysis

To analyze and combine the results of different studies, in each study, the prevalence of anencephaly was considered as the probability of two-sentence distribution and its variance was calculated through two-sentence distribution. Heterogeneity of studies was assessed using I2 test. A Random effect model was used in case of I2 index above 50%. In this model, parameter changes between studies are also considered in the calculations, so it can be said that the results of this model in heterogeneous conditions can be more generalized than the model with a fixed effect. Due to the large sample size investigated in the study, Begg and Mazumdar rank correlation test was used at a significance level of 0.1 to check the publication bias. Data were analyzed using Comprehensive Meta-Analysis (Version 2) software.

Results

Summary of how articles entered the meta-analysis

In this study, the statements of Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) were used [26]. In the first stage, 1141 articles (1104 articles in international, 9 articles in Persian databases and 28 studies in reviewing article sources) were found, of which 330 duplicate studies were omitted. 811 studies entered the screening stage and 371 articles were deleted based on the inclusion and exclusion criteria by reviewing the title and abstract of the study. In the next stage (competency assessment), out of the remaining 440 studies from the screening stage, 58 articles were removed by reviewing the full text of the article because it was not relevant to the research. The quality evaluation of 382 articles included in this study was performed using the STROBE checklist, of which 22 studies had poor methodological quality and were deleted. Thus, 360 related studies entered the process of systematic review and meta-analysis (Fig. 1) [28].

Fig. 1.

Fig. 1

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Preferred reporting items for systematic reviews and meta-analyses (PRISMA 2020) flow diagram

General characteristics of the studies:

The total sample size of the prevalence studies was 169,407,738 people. The studies were published between 1969 and March 23, 2021. The lowest sample size was related to the study of Castilla-17 et al. (1985) with 1623 people in [29] Colombia and the highest sample size was related to the study of James et al. (1993) with 15,487,449 people in the USA [30]. The surname of the first author, year of publication and year of reporting, place of study, maternal age, sample size, number of cases, prevalence, incidence and attenuation of anencephaly reported in Tables 1, 2 and 3.

Table 1.

Summary of study specifications (prevalence of anencephaly)

First author, year, References Report year Continent Country Sample size Number of patients with Anencephaly
Gong-1, 2017, [1] 2006 Asia China 306,734 227
Gong-2, 2017, [1] 2007 Asia China 341,432 244
Gong-3, 2017, [1] 2008 Asia China 330,414 186
Gong-4, 2017, [1] 2009 Asia China 321,353 166
Gong-5, 2017, [1] 2010 Asia China 307,826 168
Gong-6, 2017, [1] 2011 Asia China 304,079 158
Gong-7, 2017, [1] 2012 Asia China 353,108 145
Gong-8, 2017, [1] 2013 Asia China 321,171 141
Gong-9, 2017, [1] 2014 Asia China 364,400 108
Gong-10, 2017, [1] 2015 Asia China 298,437 55
PEI, 2009, [2] 2004–2006 Asia China 4175 28
Afshar, 2006, [3] 1997–2001 Asia Iran 16,785 23
Golalipour-1, 2007, [4] 1998–2003 Asia Iran 37,951 43
Li, 2006, [5] 2003 Asia China 11,534 76
LIAN, 1987, [6] 1970–1984 Asia China 208,801 461
Golalipour-2, 2010, [7] 1998–2005 Asia Iran 30,639 35
Xie, 2020, [8] 2015–2018 Asia China 705,395 188
Khattak, 2010, [9] 2007 Asia SWAT 5560 63
Golalipour-3, 2010, [10] 1998–2005 Asia Iran 49,534 56
Zhang-1, 2012, [11] 2005–2008 Asia China 62,443 43
Jung-1, 1999, [12] 1993 Asia Korea 601,376 156
Jung-2, 1999, [12] 1994 Asia Korea 601,459 255
Jaruratanasirikul, 2014, [13] 2009–2012 Asia Thailand 148,759 12
Zhu-1, 2012, [14] 2006 Asia China 643,987 407
Zhu-2, 2012, [14] 2007 Asia China 777,397 454
Zhu-3, 2012, [14] 2008 Asia China 843,920 465
Jin-1, 2017, [15] 2006 Asia China 22,559 16
Jin-2, 2017, [15] 2007 Asia China 26,874 13
Jin-3, 2017, [15] 2008 Asia China 28,291 19
Jin-4, 2017, [15] 2009 Asia China 27,916 20
Jin-5, 2017, [15] 2010 Asia China 26,973 12
Jin-6, 2017, [15] 2011 Asia China 28,424 9
Jin-7, 2017, [15] 2012 Asia China 32,489 13
Kant, 2017, [16] 2001–2014 Asia India 26,946 33
Liu, 2007, [17] 1996–2004 Asia China 99,888 42
Ebrahimi, 2013, [18] 2005–2011 Asia Iran 14,034 59
Ghavami, 2011, [19] 2005–2008 Asia Iran 22,500 18
Kondo-1, 2019, [20] 2014 Asia Japan 156,791 13
Kondo-2, 2019, [20] 2015 Asia Japan 158,347 13
Tiwari, 2020, [21] 2014 Asia India 14,681 19
IMAIZUMI-1, 1991, [22] 1948–1958 Asia Japan 27,891 27
IMAIZUMI-2, 1991, [22] 1959–1969 Asia Japan 40,715 22
IMAIZUMI-3, 1991, [22] 1970–1980 Asia Japan 39,506 28
IMAIZUMI-4, 1991, [22] 1981–1990 Asia Japan 23,884 17
Zhang-2, 2017, [23] 2006–2015 Asia China 3,248,954 1600
Seto-1, 2003, [24] 1981–1990 Asia Japan 136,846 39
Seto-2, 2003, [24] 1991–2000 Asia Japan 117,332 7
Fakheri, 2004, [25] 1996–2001 Asia Iran 81,538 106
PourIsa, 2005, [26] 1997–2003 Asia Iran 21,074 29
Golalipour-4, 2004, [27] 1997–2001 Asia Iran 26,280 39
Stoll-1, 2006, [28] 1988–1992 Europe France 68,326 9
Stoll-2, 2006, [28] 1993–1995 Europe France 39,286 4
Stoll-3, 2006, [28] 1996–2002 Europe France 95,058 10
RICHARDS, 1972, [31] 1964–1966 Europe Wales 92,980 2145
Stoll-4, 2011, [32] 1979–2008 Europe France 402,532 182
Szabó-1, 2013, [33] 1980–1991 Europe Hungary 209,762 64
Szabó-2, 2013, [33] 1994–2005 Europe Hungary 155,978 29
Pietrzyk-1, 1983, [34] 1970–1972 Europe Poland 33,766 9
Pietrzyk-2, 1983, [34] 1979- 1981 Europe Poland 46,818 11
McDonnell-1, 1999, [35] 1980–1994 Europe East Ireland 320,750 322
Boyd-1, 2000, [36] 2000 Europe Denmark 8788 2
Boyd-2, 2000, [36] 2000 Europe Netherlands 81,980 18
Boyd-3, 2000, [36] 2000 Europe Austria 29,026 3
Boyd-4, 2000, [36] 2000 Europe Croatia 10,718 2
Boyd-5, 2000, [36] 2000 Europe France 60,705 15
Boyd-6, 2000, [36] 2000 Europe Germany 18,280 7
Boyd-7, 2000, [36] 2000 Europe Italy 204,178 34
Boyd-8, 2000, [36] 2000 Europe Lithuania 95,469 29
Boyd-9, 2000, [36] 2000 Europe Spain 38,166 14
Boyd-10, 2000, [36] 2000 Europe Ukraine 44,761 11
Boyd-11, 2000, [36] 2000 Europe UK 78,695 31
Salvador, 2011, [37] 1992–2006 Europe Spain 197,003 87
DOLK-1, 1991, [38] 19,980–1987 Europe UK& Ireland 577,989 739
DOLK-2, 1991, [38] 19,980–1986 Europe Europe & Malta 378,849 184
Khoshnood-1, 2015, [39] 1991–2009 Europe Austria 216,196 40
Khoshnood-2, 2015, [39] 1991–2011 Europe Belgium 601,565 182
Khoshnood-3, 2015, [39] 2000–2009 Europe Czech Republic 1,029,247 245
Khoshnood-4, 2015, [39] 1991–2010 Europe Croatia 131 525 18
Khoshnood-5, 2015, [39] 1991–2011 Europe Denmark 115 846 44
Khoshnood-6, 2015, [39] 1993–2010 Europe Finland 1,070,940 314
Khoshnood-7, 2015, [39] 1991–2011 Europe France 666,353 347
Khoshnood-8, 2015, [39] 1991–2011 Europe Germany 360,801 95
Khoshnood-9, 2015, [39] 1998–2010 Europe Hungary 1,260,719 256
Khoshnood-10, 2015, [39] 1991–2011 Europe Ireland 702,747 244
Khoshnood-11, 2015, [39] 1991–2011 Europe Italy 1,215,306 217
Khoshnood-12, 2015, [39] 1991–2010 Europe Malta 88,573 25
Khoshnood-13, 2015, [39] 1991–2011 Europe Netherlands 401,404 108
Khoshnood-14, 2015, [39] 1999–2011 Europe Norway 775,060 282
Khoshnood-15, 2015, [39] 1999–2010 Europe Poland 440,163 71
Khoshnood-16, 2015, [39] 1991–2010 Europe Portugal 316,853 62
Khoshnood-17, 2015, [39] 1991–2010 Europe Spain 361,416 189
Khoshnood-18, 2015, [39] 1991–2011 Europe Switzerland 159,273 62
Khoshnood-19, 2015, [39] 1991–2011 Europe UK 2,556,075 1361
Loane, 2009, [40] 2000–2004 Europe UK 1,740,718 40
Peake, 2021, [41] 2006–2011 Europe UK 1,351,405 673
Boyd-12, 2011, [42] 2005–2006 Europe UK 601,545 366
Poretti, 2008, [43] 2001–2007 Europe Switzerland 10,769,230 22
Obeid-1, 2015, [44] 2000–2010 Europe Europe 9,161,189 3221
Obeid-2, 2015, [44] 2000–2010 Europe Germany 227,781 56
GARNE, 2005, [45] 1995–1999 Europe 17 European regions 1,198,519 498
CADAS, 1978, [46] 1955–1965 Europe Greece 74,390 49
Loncarek-1, 2001, [47] 1963 Europe Croatia 2946 1
Loncarek-2, 2001, [47] 1966 Europe Croatia 2988 1
Loncarek-3, 2001, [47] 1967 Europe Croatia 2974 2
Loncarek-4, 2001, [47] 1971 Europe Croatia 3582 1
Loncarek-5, 2001, [47] 1972 Europe Croatia 3522 1
Loncarek-6, 2001, [47] 1973 Europe Croatia 3580 1
Loncarek-7, 2001, [47] 1974 Europe Croatia 3612 1
Loncarek-8, 2001, [47] 1975 Europe Croatia 3692 1
Loncarek-9, 2001, [47] 1979 Europe Croatia 4174 1
Loncarek-10, 2001, [47] 1980 Europe Croatia 4242 1
Loncarek-11, 2001, [47] 1983 Europe Croatia 4042 3
Loncarek-12, 2001, [47] 1988 Europe Croatia 3655 1
Loncarek-13, 2001, [47] 1989 Europe Croatia 3504 2
Loncarek-14, 2001, [47] 1992 Europe Croatia 3647 1
Loncarek-15, 2001, [47] 1993 Europe Croatia 3468 1
Loncarek-16, 2001, [47] 1994 Europe Croatia 3326 1
Loncarek-17,2001, [47] 1996 Europe Croatia 3412 1
Loncarek-18, 2001, [47] 1998 Europe Croatia 3017 1
EUROCAT GROUP-1, 1991, [48] 1980–1986 Europe Republic of Ireland 183,278 242
EUROCAT GROUP-2, 1991, [48] 1980–1986 Europe UK 467,437 597
EUROCAT GROUP-3, 1991, [48] 1980–1986 Europe Belgium 57,352 31
EUROCAT GROUP-4, 1991, [48] 1980–1986 Europe Netherlands 50,437 33
EUROCAT GROUP-5, 1991, [48] 1980–1986 Europe Denmark 32,648 17
EUROCAT GROUP-6, 1991, [48] 1980–1986 Europe France 349,737 143
EUROCAT GROUP-7, 1991, [48] 1980–1986 Europe Italy 63,261 28
EUROCAT GROUP-8, 1991, [48] 1980–1986 Europe Malta 22,225 13
EUROCAT GROUP-9, 1987, [49] 1980–1983 Europe Republic of Ireland 109,276 168
EUROCAT GROUP-10, 1987, [49] 1980–1983 Europe UK 244,955 309
EUROCAT GROUP-11, 1987, [49] 1980–1983 Europe Denmark 18,533 8
EUROCAT GROUP-12, 1987, [49] 1980–1983 Europe Netherlands 23,150 13
EUROCAT GROUP-13, 1987, [49] 1980–1983 Europe Belgium 60,034 25
EUROCAT GROUP-14, 1987, [49] 1980–1983 Europe France 143,878 69
EUROCAT GROUP-15, 1987, [49] 1980–1983 Europe Luxembourg 9148 3
EUROCAT GROUP-16, 1987, [49] 1980–1983 Europe Germany 21,985 9
EUROCAT GROUP-17, 1987, [49] 1980–1983 Europe Italy 135,662 28
Smithells, 1989, [50] 1985–1986 Europe UK 97,101 67
Corona-Rivera-1, 2021, [51] 1991–2002 Europe Mexico 95,454 21
Corona-Rivera-2, 2021, [51] 2003–2019 Europe Mexico 171,795 67
Stone-1, 1988, [52] 1974 Europe Scotland 14,880 33
Stone-2, 1988, [52] 1975 Europe Scotland 14,398 39
Stone-3, 1988, [52] 1976 Europe Scotland 12,889 34
Stone-4, 1988, [52] 1977 Europe Scotland 12,487 28
Stone-5, 1988, [52] 1978 Europe Scotland 12,491 30
Stone-6, 1988, [52] 1979 Europe Scotland 13,339 29
Stone-7, 1988, [52] 1980 Europe Scotland 13,438 24
Stone-8, 1988, [52] 1981 Europe Scotland 13,491 19
Stone-9, 1988, [52] 1982 Europe Scotland 12,884 19
Stone-10, 1988, [52] 1983 Europe Scotland 12,661 19
Stone-11, 1988, [52] 1984 Europe Scotland 12,783 14
Stone-12, 1988, [52] 1985 Europe Scotland 13,089 15
CARSTAIRS-1, 1984, [53] 1971 Europe Scotland 87,883 224
CARSTAIRS-2, 1984, [53] 1972 Europe Scotland 79,603 185
CARSTAIRS-3, 1984, [53] 1973 Europe Scotland 75,265 181
CARSTAIRS-4, 1984, [53] 1974 Europe Scotland 70,943 156
CARSTAIRS-5, 1984, [53] 1975 Europe Scotland 68,708 140
CARSTAIRS-6, 1984, [53] 1976 Europe Scotland 65,524 89
CARSTAIRS-7, 1984, [53] 1977 Europe Scotland 62,895 66
CARSTAIRS-8, 1984, [53] 1978 Europe Scotland 64,819 57
CARSTAIRS-9, 1984, [53] 1979 Europe Scotland 68,841 47
CARSTAIRS-10, 1984, [53] 1980 Europe Scotland 69,355 32
CARSTAIRS-11, 1984, [53] 1981 Europe Scotland 69,490 19
CARSTAIRS-12, 1984, [53] 1982 Europe Scotland 66,582 13
Rankin-1, 2000, [54] 1984 Europe UK 39,357 27
Rankin-2, 2000, [54] 1985 Europe UK 41,175 33
Rankin-3, 2000, [54] 1986 Europe UK 40,541 27
Rankin-4, 2000, [54] 1987 Europe UK 40,700 35
Rankin-5, 2000, [54] 1988 Europe UK 40,428 33
Rankin-6, 2000, [54] 1989 Europe UK 39,411 36
Rankin-7, 2000, [54] 1990 Europe UK 40,966 30
Rankin-8, 2000, [54] 1991 Europe UK 41,484 26
Rankin-9, 2000, [54] 1992 Europe UK 40,316 41
Rankin-10, 2000, [54] 1993 Europe UK 38,960 26
Rankin-11, 2000, [54] 1994 Europe UK 35,380 21
Rankin-12, 2000, [54] 1995 Europe UK 34,487 32
Rankin-13, 2000, [54] 1996 Europe UK 34,024 21
Fleurke-Rozema, 2015, [55] 2008–2013 Europe Netherlands 203,703 110
Sever-1, 1982, [56] 1966 America USA 124,467 66
Sever-2, 1982, [56] 1967 America USA 124,441 55
Sever-3, 1982, [56] 1968 America USA 126,637 61
Sever-4, 1982, [56] 1969 America USA 131,343 82
Sever-5, 1982, [56] 1970 America USA 134,045 65
Sever-6, 1982, [56] 1971 America USA 117,324 59
Sever-7, 1982, [56] 1972 America USA 107,094 60
Limb-1, 1994, [57] 1972–1974 America USA 18,155 17
Limb-2, 1994, [57] 1979–1981 America USA 21,436 10
Limb-3, 1994, [57] 1982–1984 America USA 25,218 11
Limb-4, 1994, [57] 1985–1987 America USA 30,217 16
Limb-5, 1994, [57] 1988–1990 America USA 31,290 20
Groisman-1, 2019, [58] 2016 America Argentina 305,452 57
Rowland, 2006, [59] 1968–2002 America USA 1,164,865 431
Krajewski, 2021, [60] 2007–2010 America USA 1,610,709 433
Bronberg, 2020, [61] 2010–2016 America Argentina 228,208 111
Carmichael, 2004, [62] 1989–1997 America USA 2,234,846 535
Shaw, 2002, [63] 1985–1997 America USA 1,303,306 197
Estevez-Ordonez, 2017, [64] 2010–2015 America Honduras 123,903 30
Biggar-1, 1976, [65] 1918 America USA 7199 3
Biggar-2, 1976, [65] 1919 America USA 6973 1
Biggar-3, 1976, [65] 1920 America USA 7153 10
Biggar-4, 1976, [65] 1921 America USA 7272 4
Biggar-5, 1976, [65] 1922 America USA 6905 3
Biggar-6, 1976, [65] 1923 America USA 7256 7
Biggar-7, 1976, [65] 1924 America USA 5967 3
Biggar-8, 1976, [65] 1925 America USA 6925 2
Biggar-9, 1976, [65] 1926 America USA 6393 3
Biggar-10, 1976, [65] 1927 America USA 6717 8
Biggar-11, 1976, [65] 1928 America USA 6370 5
Biggar-12, 1976, [65] 1929 America USA 6116 7
Biggar-13, 1976, [65] 1930 America USA 5872 2
Biggar-14, 1976, [65] 1931 America USA 5632 8
Biggar-15, 1976, [65] 1932 America USA 5574 6
Biggar-16, 1976, [65] 1933 America USA 5065 7
Biggar-17, 1976, [65] 1934 America USA 5127 10
Biggar-18, 1976, [65] 1935 America USA 5101 6
Biggar-19, 1976, [65] 1936 America USA 5056 8
Biggar-20, 1976, [65] 1937 America USA 5314 8
Biggar-21, 1976, [65] 1938 America USA 5613 7
Sargiotto, 2015, [66] 2009–2013 America Argentina 703,325 212
Pacheco, 2009, [67] 2000–2006 America Brasil 161,341 34
Janerich-1, 1973, [68] 1945–1947 America USA 407,326 463
Janerich-2, 1973, [68] 1948–1950 America USA 454,206 476
Janerich-3, 1973, [68] 1951–1953 America USA 510,601 397
Janerich-4, 1973, [68] 1954–1956 America USA 565.391 398
Janerich-5, 1973, [68] 1957–1959 America USA 601,196 375
Janerich-6, 1973, [68] 1960–1962 America USA 605,336 392
Janerich-7, 1973, [68] 1963–1965 America USA 574,662 376
Janerich-8, 1973, [68] 1966–1968 America USA 506,706 337
Janerich-9, 1973, [68] 1969–1971 America USA 499,131 248
Jorde, 1984, [69] 1940–1979 America USA 979,873 374
Castilla-1, 1985, [29] 1967 America South America 12,430 7
Castilla-2, 1985, [29] 1968 America South American 33,874 8
Castilla-3, 1985, [29] 1969 America South American 42,874 7
Castilla-4, 1985, [29] 1970 America South American 51,535 11
Castilla-5, 1985, [29] 1971 America South American 47,156 9
Castilla-6, 1985, [29] 1972 America South American 50,786 13
Castilla-7, 1985, [29] 1973 America South American 65,009 13
Castilla-8, 1985, [29] 1974 America South American 84,961 31
Castilla-9, 1985, [29] 1975 America South American 65,214 11
Castilla-10, 1985, [29] 1976 America South American 77,992 22
Castilla-11, 1985, [29] 1977 America South American 67,432 19
Castilla-12, 1985, [29] 1978 America South American 72,231 21
Castilla-13, 1985, [29] 1979 America South American 68,645 20
Castilla-14, 1985, [29] 1980–1982 America Argentina 70,768 38
Castilla-15, 1985, [29] 1980–1982 America Bolivia 8,514 5
Castilla-16, 1985, [29] 1980–1982 America Brazil 43,702 26
Castilla-17, 1985, [29] 1980–1982 America Colombia 1,623 0
Castilla-18, 1985, [29] 1980–1982 America Chile 25,634 23
Castilla-19, 1985, [29] 1980–1982 America Ecuador 19,463 10
Castilla-20, 1985, [29] 1980–1982 America Paraguay 3,443 2
Castilla-21, 1985, [29] 1980–1982 America Peru 15,943 4
Castilla-22, 1985, [29] 1980–1982 America Uruguay 10,916 11
Castilla-23, 1985, [29] 1980–1982 America Venezuela 55,828 35
Groisman-2, 2017, [70] 2009–2013 America Argentina 703,422 212
Forrester-1, 1998, [71] 1987–1996 America USA 150,000 75
Parks, 2011, [72] 1999—2005 America USA 2,594,295 677
Cragan-1, 2009, [73] 1995–2004 America USA 470,802 81
Besser, 2007, [74] 1968–2003 America USA 398,165 434
de Souza, 2020, [75] 2012–2017 America Brazil 30,761 9
James, 1993, [30] 1970–1987 America USA 15,487,449 6040
Parker-1, 2010, [76] 2004–2006 America USA 3,120,605.00 697
Parker-2, 2010, [76] 2004–2006 America USA 2,075,973 211
Parker 3, 2010, [76] 2004–2006 America USA 2,145,287 192
Feuchtbaum, 1999, [77] 1990–1994 America USA 1,618,279 770
Windham-1, 1982, [78] 1966–1972 America USA 865,351 447
Aguiar, 2003, [79] 1999–2000 America Latin-America 18,807 24
Poletta, 2018, [80] 1990–2013 America Venezuela 353,956 155
Castilla-24, 2003, [81] 1999 America Chile 10,740 10
Castilla-25, 2003, [81] 2000 America Chile 12,977 5
Castilla-26, 2003, [81] 2001 America Chile 11,462 7
Forrester-2, 2000, [82] 1986–1997 America USA 246,189 89
Winsor, 1986, [83] 1980–1984 America Canada 61,500 43
Bidondo, 2015, [84] 2009–2013 America Argentina 703 325 164
De Wals, 2007, [85] 1993–2002 America Canada 1,909,741 830
Yang, 2004, [86] 1989–2000 America USA 2,615,197 617
Boulet-1, 2011, [87] 1995–2005 America USA 522,315 29
McBride, 1979, [88] 1952–1970 America Columbia 686,326 466
Siffel, 2005, [89] 1978–2001 America USA 874,100 243
Mathews-1, 2002, [90] 1991 America USA 3,564,453 655
Mathews-2, 2002, [90] 1992 America USA 3,572,890 457
Mathews-3, 2002, [90] 1993 America USA 3,562,723 481
Mathews-4, 2002, [90] 1994 America USA 3,527,482 387
Mathews-5, 2002, [90] 1995 America USA 3,484,539 408
Mathews-6, 2002, [90] 1996 America USA 3,478,723 416
Mathews-7, 2002, [90] 1997 America USA 3,469,667 434
Mathews-8, 2002, [90] 1998 America USA 3,519,240 349
Mathews-9, 2002, [90] 1999 America USA 3,533,565 382
Mathews-10, 2002, [90] 2000 America USA 3,640,376 376
Mathews-11, 2002, [90] 2001 America USA 3,649,061 343
Cragan-2, 1995, [91] 1985–1994 America USA 211,024 268
Canfield, 2009, [92] 1999–2003 America USA 1,827,317 514
Feldman, 1982, [93] 1968–1976 America USA 173,655 89
Naggan-1, 1969, [94] 1930–1933 America USA 14,052 38
Naggan-2, 1969, [94] 1934–1937 America USA 16,179 28
Naggan-3, 1969, [94] 1938–1941 America USA 18,206 34
Naggan-4, 1969, [94] 1942–1945 America USA 22,059 25
Naggan-5, 1969, [94] 1946–1949 America USA 28,097 25
Naggan-6, 1969, [94] 1950–1953 America USA 43,441 37
Naggan-7, 1969, [94] 1954–1957 America USA 52,032 32
Naggan-8, 1969, [94] 1958–1961 America USA 57,639.00 35
Naggan-9, 1969, [94] 1962–1965 America USA 60,002 51
Windham-2, 1982, [95] 1966–1979 America USA & Norway 1,656,116 802
Boulet-2, 2008, [96] 1999–2000 America USA 3,165,992 782
Boulet-3, 2008, [96] 2001–2002 America USA 3,218,605 692
Boulet-4, 2008, [96] 2003–2004 America USA 3,242,424 642
Bupp, 2015, [97] 1992–2012 America USA 1,116,289 240
Nasri, 2014, [98] 1991–2011 Africa Tunisia 3,803,889 174
Berihu, 2018, [99] 2018 Africa Ethiopia 14,903 99
Forci, 2020, [100] 2011–2016 Africa Morocco 43,923 22
Buccimazza, 1994, [101] 1973–1992 Africa South Africa 516,252 164
Omer, 2016, [102] 2014–2015 Africa Sudan 36,785 18
Riley, 1998, [103] 1983–1995 Australia Australia 825,051 452
Owen, 2000, [104] 1983–1997 Australia Australia 949,914 550
Chan-1, 1993, [105] 1966 Australia Australia 20,556 24
Chan-2, 1993, [105] 1967 Australia Australia 20,597 8
Chan-3, 1993, [105] 1968 Australia Australia 21,424 27
Chan-4, 1993, [105] 1969 Australia Australia 22,185 25
Chan-5, 1993, [105] 1970 Australia Australia 22,817 13
Chan-6, 1993, [105] 1971 Australia Australia 23,246 27
Chan-7, 1993, [105] 1972 Australia Australia 22,073 25
Chan-8, 1993, [105] 1973 Australia Australia 20,651 22
Chan-9, 1993, [105] 1974 Australia Australia 20,417 22
Chan-10, 1993, [105] 1975 Australia Australia 20,175 17
Chan-11, 1993, [105] 1976 Australia Australia 19,157 15
Chan-12, 1993, [105] 1977 Australia Australia 19,438 15
Chan-13, 1993, [105] 1978 Australia Australia 18,736 17
Chan-14, 1993, [105] 1979 Australia Australia 18,641 19
Chan-15, 1993, [105] 1980 Australia Australia 18,638 20
Chan-16, 1993, [105] 1981 Australia Australia 19,052 12
Chan-17, 1993, [105] 1982 Australia Australia 19,128 19
Chan-18, 1993, [105] 1983 Australia Australia 19,800 15
Chan-19, 1993, [105] 1984 Australia Australia 20,281 17
Chan-20, 1993, [105] 1985 Australia Australia 19,833 14
Chan-21, 1993, [105] 1986 Australia Australia 19,800 16
Chan-22, 1993, [105] 1987 Australia Australia 19,395 16
Chan-23, 1993, [105] 1988 Australia Australia 19,530 14
Chan-24, 1993, [105] 1989 Australia Australia 19,823 17
Chan-25, 1993, [105] 1990 Australia Australia 19,988 23
Chan-26, 1993, [105] 1991 Australia Australia 19,749 20
Barry Borman, 1986, [106] 1978 Australia New Zealand 52,143 51
BORMAN, 1993, [107] 1978–1982 Australia New Zealand 262,821 205
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Table 2.

Summary of study specifications (incidence of Anencephaly)

First author, year, references Report year Continent Country Sample size Number of patients with Anencephaly
Safdar, 2007, [108] 1997–2005 Asia Saudi Arabia 33,489 1
Al-Ani, 2010, [109] 2007–2008 Asia Iraq 10,016 9
Bener, 2012, [110] 1985–2009 Asia Qatar 302,049 102
Akar-1, 1988, [111] 1983 Europe Turkey 628 1
Akar-2, 1988, [111] 1984 Europe Turkey 563 1
Akar-3, 1988, [111] 1985 Europe Turkey 756 2
Akar-4, 1988, [111] 1986 Europe Turkey 1145 2
Akar-5, 1988, [111] 1987 Europe Turkey 600 6
Onrat, 2009, [112] 2003–2004 Europe Turkey 8631 12
SN ÍPEK, 2002, [113] 1961–1999 Europe Czech Republic 5,499,008 1812
McDonnell-2, 2015, [114] 2009–2011 Europe Republic of Ireland 226,923 106
Evans, 1979, [115] 1965–1976 Europe Wales 70,871 146
Van Allen-1, 2006, [116] 1997 America Columbia 44,734 17
Van Allen-2, 2006, [116] 1998 America Columbia 43,141 12
Van Allen-3, 2006, [116] 1999 America Columbia 42,040 28
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Table 3.

Summary of study specifications (mortality of Anencephaly)

First author, year, references Report year Continent Country Sample size Number of deaths due to Anencephaly
Kancherla, 2018, [117] 2015 Asia India 25,794,000 64,485
Tanner, 2010, [118] 1999–2006 America USA 1,701,076 123
Wen-1, 2000, [119] 1981–1983 America Canada 580,000 116
Wen-2, 2000, [119] 1993–1995 America Canada 542,857 38
Dixon, 2019, [120] 2016 Africa Ethiopia 3,328,867 21,638
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The result of the I2 test for the prevalence of anencephaly in different parts of the world indicates a significant heterogeneity between studies (I2 = 99.9), so the data were analyzed by meta-analysis using a random effects model. Due to the high heterogeneity of the studies, sensitivity analysis was performed and the effect of each study on the final result and the degree of heterogeneity were evaluated. Based on Begg and Mazumdar rank correlation tests, the publication bias in the studies with less than 0.1% was not observed. (P = 0.105) (Table 4).

Table 4.

General analysis of the prevalence of anencephaly per 10,000 births worldwide and continents by sample size, heterogeneity, publication bias

Meta-analysis N Sample size I2 Begg and Mazumdar Prevalence (95% CI)
Overall prevalence 340 169,407,738 99.9 0.105 5.1 (95% CI 4.7–5.5)
Continent
 Asia 50 12,449,402 99.9 0.776 6.5 (95% CI 5.5–7.7)
 Europe 126 43,826,079 99.9 0.906 4.8 (95% CI 4.2–5.5)
 America 128 106,111,868 99.9 0.809 4.3 (95% CI 3.8–4.8)
 Africa 5 4,415,752 99.9 0.278 6.5 (95% CI 1–9.9)
 Australia 30 12,615,064 99.7 0.111 8.6 (95% CI 7.7–9.5)
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As a result of the combination of studies, the overall estimate of the prevalence of Anencephaly in the world will be 5.1 per ten thousand births (95% confidence interval 4.7–5.5) based on the random effects model (Table 4).

According to different reports of Anencephaly prevalence in different parts of the world, subgroup analysis by different continents (Asia, Europe, USA, Africa and Australia) is reported in Table 2, which has the highest prevalence in Australia with 8.6 per ten thousand births (confidence interval). 95%: 7.7–9.5) (Table 4).

Incidence and mortality of Anencephaly were 8.3 per ten thousand births (95% confidence interval 5.5–9.9) and 5.5 per ten thousand births (95% confidence interval 1.8–15) respectively (Table 5).

Table 5.

General analysis of the incidence and mortality of anencephaly per 10,000 births worldwide and continents by sample size, heterogeneity, publication bias

Continent N Sample size I2 Begg and Mazumdar Prevalence (95% CI)
Incidence 15 6,284,594 99.9 0.766 8.3 (95% CI 5.5–9.9)
Mortality 5 31,946,800 99.9 0.462 5.5 (95% CI 1.8–15)
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Discussion

Neural tube defects (NTDs) are a major congenital structural disorder of the brain and spinal cord that occurs early in pregnancy as a result of defective neural tube closure [9], including abortion, stillbirth, and lifelong disability, as well as high emotional, psychological and economic consequences (138). Many factors, including radiation therapy, drugs, malnutrition, chemicals, and genetic determinants (mutations in folate-responsive or folate-dependent pathways) can adversely affect CNS growth during pregnancy and cause neural tube defects [12].

Anencephaly, which is the partial or complete absence of the brain and skull [3] is one of the most common forms of NTD. The fetus with anencephaly dies or will die in the first few hours after birth [9]. Exposure to methotrexate, aminopterin and valproic acid, maternal characteristics, race, ethnicity, geography, nutritional, biological and poor economic conditions are all risk factors for anencephaly [121, 122].

According to the present systematic review and meta-analysis, the overall prevalence of anencephaly in the world was 5.1 per ten thousand births. The highest prevalence of anencephaly was related to the study of RICHARDS et al. [57] with 230.69 infants with anencephaly per ten thousand births and the lowest prevalence was related to the study of Castilla et al. [31] with zero cases per ten thousand births. The most comprehensive study in terms of sample size was the study of James et al. (1993) with 15,487,449 people in the USA [32] that reported the prevalence of anencephaly at 3.89 per thousand births. Also, the present study estimated the risk of incidence and death due to anencephaly: 8.3 per ten thousand births and 5.5 per ten thousand births worldwide. Bhide et al. (2013) reported the prevalence of anencephaly in India at 2.1 per thousand births through 19 studies [123]. A meta-analysis and systematic review by Bitew et al. (2020) reported the prevalence of NTD in Ethiopia. 63.3 per ten thousand births [124]. Our study is almost in line with these studies and regarding the cause of minor differences between the present study and these studies, we can point out that the number of articles studied in the present study is more (121 articles in the present study versus 19 articles in the study of Bhide et al.) And also, the present study has examined patients with different races and geographical regions in the world.

Due to the change in population structure in different countries and different reports of the prevalence of anencephaly, the need for a detailed study of the prevalence of this defect in different continents in order to pay more attention to the process and its consequences seems inevitable. Therefore, according to the analysis of subgroups according to different continents, the highest prevalence of anencephaly is related to the continent of Australia with 8.6 per ten thousand births and the lowest belongs to the Americas with 4.3 per thousand births.

The results show that in addition to genetics, various environmental factors can also be involved in the development of anencephaly. So far, folic acid is the most important factor in preventing neural tube defects. Reports suggest the use of periovulation fulate supplements significantly reduces the risk of recurrence of anencephaly and other neural tube defects [125].

Regarding the serious nature of anencephaly and its high mortality, genetic counseling, folic acid supplements and prenatal diagnosis of neural tube defects are extremely important or (Given the seriousness of anencephaly and its high mortality rate, genetic counseling, folic acid supplements, and prenatal detection of neural tube abnormalities are critical.). This defect can be diagnosed by screening AFP (alpha-fetoprotein) with a combination of ultrasound and amniocentesis between 14 and 16 weeks of gestation [3, 5]. These studies can provide useful information to health care providers and enrich health care interventions and improve the quality of services and life [126].

Limitations

One of the limitations of this study is that some samples were not based on random selection. Also, non-homogeneous reporting of articles, non-homogeneous method of implementation, and unavailability of the full text of the papers presented at the conference can be added. Such conditions can justify the high heterogeneity reported in the studies, and therefore, if these limitations and differences in the studies did not exist, the heterogeneity analysis could be less.

Conclusion

The results of this study demonstrate that the prevalence of anencephaly in the world is high; therefore, it is necessary for physicians and specialists to emphasize the importance of preventive as well as control and treatment strategies.

Acknowledgements

This study is the result of research project No. 4000613 approved by the Student Research Committee of Kermanshah University of Medical Sciences. We would like to thank the esteemed officials of the center for financing this study.

Abbreviations

NTDs

Neural Tube Defects

SID

Scientific Information Database

MESH

Medical Subject Headings

WoS

Web of Science

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

STROBE

Strengthening the reporting of observational studies in epidemiology for cross-sectional study

Author contributions

NS and BF and ND contributed to the design, MM statistical analysis, participated in most of the study steps. MM and RF and PM and MK prepared the manuscript. MM and ND and BF and AR and PM and SHSH assisted in designing the study, and helped in the, interpretation of the study. All authors read and approved the final manuscript.

Funding

By Deputy for Research and Technology, Kermanshah University of Medical Sciences (IR) (4000613). This deputy has no role in the study process.

Availability of data and materials

Datasets are available through the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Ethics approval was received from the ethics committee of deputy of research and technology, Kermanshah University of Medical Sciences (IR.KUMS.REC.1400.504).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no conflict of interest.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Nader Salari, Email: n_s_514@yahoo.com.

Behnaz Fatahi, Email: behnaz.fatahi.ir@gmail.com.

Reza Fatahian, Email: r_fatahian@kums.ac.ir.

Payam Mohammadi, Email: payammohamadi142@gmail.com.

Adibeh Rahmani, Email: adibeh.rahmani@charite.de.

Niloofar Darvishi, Email: darvishi.niloufar@gmail.com.

Mona Keivan, Email: dr.Monakeivan@gmail.com.

Shamarina Shohaimi, Email: shamarina@upm.edu.my.

Masoud Mohammadi, Email: Masoud.mohammadi1989@yahoo.com.

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Data Availability Statement

Datasets are available through the corresponding author upon reasonable request.

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