{"paper_id":"41bb0731-5cb1-4f78-8cf4-53e640a90c07","body_text":"Prevalence and associated factors of Self-medication in worldwide pregnant women: Systematic Review and Meta-Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence and associated factors of Self-medication in worldwide pregnant women: Systematic Review and Meta-Analysis Afaf BOUQOUFI, Laila LAHLOU, Said BOUJRAF, Fatima AIT EL HADJ, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2791845/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jan, 2024 Read the published version in BMC Public Health → Version 1 posted 9 You are reading this latest preprint version Abstract Background: Self-medication during pregnancy is of great interest. The use of drugs during pregnancy requires a careful reflection on the benefits to the mother and the risks to the fetus. It is a difficult medical situation for clinicians to select the drug because of the various pharmacokinetic and physiological changes encountered in pregnant women this study aimed to estimate the pooled prevalence of self-medication and associated factors in worldwide pregnant women by a systematic review and a meta-analysis of the published studies on self-medication during pregnancy. Methods: Searches were carried out at PubMed, Science Direct, Web of Science, and Google Scholar. The quality of the studies and the risk of bias were analyzed using the Joanna Briggs Critical Appraisal Checklist for Analytical Cross-Sectional Studies instrument. The extracted data were tabulated and analyzed qualitatively and quantitatively through meta-analysis. Results: The overall prevalence of self-medication among pregnant women was 44.50% (95% CI: 38.92-50.23). The subgroup analysis has shown a difference in the prevalence of self-medication which is influenced by region, Income of countries, and study design. The Heterogeneity, assessed by the statistical test I2 varied from 96% to 99% and was statistically significant. The result of this funnel plot showed that the funnel plot was symmetry with p-value = 0.36, and there is no publication bias. Conclusion: The results obtained from this study showed that the prevalence of self-medication among pregnant women is relatively high. This requires effective measures and interventions to reduce self-medication. Systematic Review Registration: https://www.crd.york.aa.uk/prospero/display_record.php?RecordID=312333 ID=CRD42022312333. Systematic Review Pregnancy Women’s Health Self-medication Pregnant women Public Health Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background The World Health Organization (WHO) defines self-medication as a practice that leads individuals to treat their illnesses with authorized medicines. Self-medication can be defined as \"the act of the subject, on his initiative, to consume a drug without consulting a doctor, and whether the drug is already in his possession or whether he obtains it from a pharmacy or from another person (1). It is a very prevalent practice, and the majority of medicines consumed by the population are available without a doctor's prescription (2). The practice of self-medication is common throughout the world, both in developing and developed countries (3). The number of people who self-medicate varies significantly by country, for example, in a study conducted in the United States about 71% of men and 82% of women had used self-medication at least once(4). In the United Kingdom of Britain and Northern Ireland, 41.5% of people had used medicines without a prescription(5). The use of drugs during pregnancy requires a careful reflection on the benefits to the mother and the risks to the fetus. It is a difficult medical situation for clinicians to select the drug because of the various pharmacokinetic and physiological changes encountered in pregnant women (6,7). Self-medication during pregnancy is of great interest; it carries serious risks of drug interactions, misdiagnosis, use of excessive doses of drugs, and prolonged use of drugs. (8,9). In Europe, a survey of 740 pregnant women conducted in France revealed that 41.5% of the participants in the study practiced self-medication (3). In Africa, a systematic review conducted in Ethiopia revealed a prevalence of self-medication of 12.8–77.1%(7). The studies are contradictory some of them report a high prevalence and others show the opposite. Also, no meta-analysis of the prevalence of self-medication in pregnant women has been carried out in the world. The goal of this study was to estimate the pooled prevalence of self-medication in worldwide pregnant women through a systematic review and a meta-analysis of published studies on self-medication during pregnancy. Methods The steps of this systematic review complied with the recommendations in the PRISMA (Preferred Reporting for Systematic Reviews and Meta-Analysis) grid. A systematic review protocol was registered by PROSPERO.55 with ID = CRD42022312333. In this study, the focused research question was: “What is the prevalence of self-medication in pregnant women in the world?” (10). Inclusion and exclusion criteria We included all published articles between January 2011 and December 2021. We also included all original studies published in English and French and human studies of pregnant or postnatal women. Studies or scientific medical literature were also included if they described the prevalence of self-medication. Only observational studies of cross-sectional type were included, as well as cohort studies if they mentioned the prevalence of self-medication in pregnant women. We excluded non-English studies (Persian and Spanish) if they didn’t contain the requested data. We also excluded unpublished reports, pilot studies, conference abstracts, opinion articles, editorial reports, seminal work, systematic reviews, and animal research. Data sources and search strategy To collect the maximum of data, we performed an exhaustive bibliographic search in PubMed, Science Direct, Google Scholar, and Web of Science databases started in December 2021. It was performed to identify all relevant studies available from January 2011 to December 2021. The search was performed using Boolean operators AND or OR that narrowed the search and also using a combination of terms and medical subject heading (MeSH). For example, the search strategy in PubMed was as follows: (((self care[MeSH Terms])) OR (self medication[MeSH Terms])) AND (pregnan*[MeSH Terms]) All stages of the search were performed by 2 independent researchers (B.A) and (L.L). Any disagreements were resolved by a third researcher (K.Y). Study selection A screening strategy was implemented to identify all relevant studies. We used Covidence, software that was developed by an Australian in 2015, it’s the primary screening and data extraction tool for Cochrane authors conducting standard intervention reviews. Covidence is designed to perform the following functions to make review production more efficient. Initially, duplicates were eliminated by the software. Then secondly, the initial selection was made according to the abstract and title. This was followed by reading the full text to identify eligible studies. In case of disagreement, a third reviewer (K.Y) was asked to make a clean agreement. Finally, the articles included in this review were downloaded and the references of each article were manually searched to determine whether other studies met the criteria. Quality Assessment The quality assessment of eligible studies was reviewed by two independent reviewers (B.A) and (L.L). This process was conducted using a recent version of the Joanna Briggs Institute's critical appraisal tools (Checklist for Analytical Cross-Sectional Studies and Cohort studies) (11,12). Joanna Briggs Institute (JBI) is an international research organization based in the Faculty of Medical and Health Sciences at the University of Adelaide in South Australia. (13). The purpose of this process is to assess the methodological quality and risk of bias in included studies. This checklist is divided into eight items for cross-sectional studies and ten items for cohort studies. Each item is scored with one point. A study was considered low quality if it had 0–4 points, moderate quality if it had 5–6 points, and high quality if it had 7–8 points. A third reviewer (Y.K.) was consulted if a consensus could not be reached. When information was missing from the studies, we tried to contact the authors by e-mail. All cross-sectional and cohort studies were included, regardless of their quality score. Articles with missing data were included as long as they reported the prevalence of self-medication. The results of the quality assessment of eligible studies are presented in Fig. 2 . Data extraction Data covering author, country, year of publication, sample size, age of participants, and prevalence of self-medication were extracted and collated in an Excel table. We also extracted the associated factors of self-medication including the reason for use, source of information, illness of drug used, type of drugs used, and finally sociodemographic characteristics of pregnant women. Any disagreements were resolved by consensus with a third reviewer (K.Y). For non-English studies, we extracted data from the abstracts available in English Statistical Analysis To calculate the pooled prevalence, we used a random-effects model, calculating effect sizes with a confidence interval (CI). Heterogeneity between studies was assessed using the Cochrane Q test with the I2 index. I2 values equal to 25%, 50%, and 75% were synonymous with low, moderate, and high heterogeneity respectively. Publication bias was assessed using a funnel plot and Egger and Begg’s test. We conduct also the trim-and-fill method aims at estimating potentially missing studies due to publication bias in the funnel plot and adjusting the overall effect estimate. To investigate the effect of variables on heterogeneity, we performed a subgroup analysis by ranking eligible studies by income (based on the country in which the study was conducted). This was done by consulting the World Bank website (14), study region, sample size, and study quality. The R software was used for the statistical analysis. In the R4.1.2 version, we used the Meta and Metafor packages for the metanalysis. Sensitivity Analysis To identify and reduce the source of heterogeneity, We conducted sensitivity analysis based on studies with small sample sizes (≥ 500 participants), and studies with a high risk of bias in any methodological domain (studies that have a low-quality score). Outcome measurement What is the prevalence of self-medication? The Prevalence is the proportion of pregnant women who have self-medicated or taken drugs without a doctor’s prescription during their pregnancy period. Results Study selection The flow chart of the studies included in this systematic review is shown in Fig. 1 . The search generated 4475 articles, 151 of which were duplicates and subsequently deleted. We examined the titles and abstracts of 4324 articles. In addition, 4202 were excluded as ineligible based on the inclusion and exclusion criteria of the analysis. Then we examined the full text of the remaining 122 articles for eligibility. We, therefore, excluded 61 studies with the reason (False target population (32), false study design (22), non-English articles (5), and Thesis(2)), therefore 59 studies were eligible and they proceeded to the data extraction after adding four articles from the manual search. Finally, 65 studies were eligible and included in the present systematic review. Characteristics of included studies The total sample size analyzed included 42615 pregnant women. The studies were published between 2011 and 2021. All included studies were cross-sectional observational studies except three studies were Cohort (15–17). The oldest study in terms of publication year (2011) is (18). The most recent studies published in 2021 are (2,19–24) (Table 1 ). One study used the largest sample size of 9,459 parturient. This was a multinational study conducted in Europe (western, northern, and eastern), North and South America, and Australia (25). While the study carried out in France recruited only 68 participants(26). The age of the participants ranged from 15 to 60 years. Regarding the region where the studies were conducted, 26 (31.32%) studies were conducted in Africa, 25 (30.12%) in Asia and 21 (25.30%) in Europe, 10 (12.04%) in America, 1 (1.20%) in Australia. Of most of the studies 29 (34.93%) were conducted in high-income countries, 28 (33.73%) in low-middle-income countries, 14 (16.86%) in low-income countries, and 12 (14%.45) in upper-middle-income countries. Regarding the quality of the studies, 42 (50.60%) articles were high quality (score of 7–8), 33 (39.75%) medium quality (6 − 5), and 8 studies (9.63%) low quality (4 − 0). Table 1 Main characteristics of the included studies References Country Year of publication Study design Sample size Prevalence Age Atif (41) Pakistan 2018 cross sectional 351 37.9 26.28 ± 10.4 Abasiubong(42) Nigeria 2012 cross sectional 518 72.40 < 20 8,7% Abduelkarem (43) United Arab Emirates 2017 Cross sectional 140 40.0 15–20 (2.1%) 21–25 (25%) Abeje(44) Ethiopia 2015 Cross sectional 510 2510 26.5 (± 6.0). Adanikin(31) Nigeria 2016 Cross sectional 346 31.50 < 20 (1.4) Afshary(45) Iran 2015 cross-sectional 801 30.60 Less than 25 37,8% Seid Mussa Ahmed(46) Ethiopia 2020 cross-sectional 1117 27 18–45 years old, with a median age 25 years Ake(19) Nigeria 2021 cross-sectional 359 40.40 26.92 years (SD = + 5.057 Alonso-Castro(47) Mexico 2018 A cross-sectional 1798 21.90 < 25 37,6% Alsous (48) Jordan 2020 cross-sectional 1313 33.10 31.11 ± 5.71 Araujo (49) Brazil 2013 cross sectional 78 28.2 NR Atmadani (50) Indonesia 2020 cross-sectional 333 11.7 16–27 41% Befekadu (51) Ethiopia 2014 cross-sectional 315 20.10 Mean = 22.58 SD = 4.298 Beza (52) Ethiopia 2018 cross-sectional 617 26.6 18–24 (31.4) BiBintsene (53) Congo 2018 cross-sectional 350 46.24 67 + 6,3 Bobga (20) Cameron 2021 cross-sectional 500 67.40 15–20 23.0% Bohio (54) Pakistan 2016 cross-sectional 351 36.5 26.19 ± 4.82 Malihe Botyar (55) Iran 2018 cross-sectional 210 34.8 > 20 0% Bulabula (56) South Africa 2019 cross-sectional 301 16.60 29 (6.1) years Cabut (26) France 2017 A cross-sectional 68 72 [30.2 ± 3.9] Navaro (57) Italy 2018 cross-sectional 503 59.6 NR Ebrahimi (58) Iran 2017 cross-sectional 384 43.5 26.33 ± 4.60 Gbagbo (59) Ghana 2020 cross-sectional 136 69 29 ± 5 Grover (60) USA 2019 cross-sectional 138 53% Nr Haque (61) Bangladesh 2016 cross-sectional 650 12.2 15–20 35.4% 21–25 30.4% ,26–30 24.1%, 31–35 7.6%,36–40 2.5%,>40 0% Barhamji (62) France 2014 cross sectional 330 46 29,7 ± 5,3 ans Ibrahim,(21) United Arab Emirates 2021 cross-sectional 434 41 < 20 2% ,20–29 31.3%, 30–39 37.6%,40–60 29.1% Jambo (63) Ethiopia 2018 cross-sectional 244 69.4 25 ± 4.68 Kabamba (64) Congo 2014 cross sectional 145 75 16–20 15,1%, 21–30 57,9% Karami Matin (65) Iran 2016 cross-sectional 308 29.3 19–43 29.16 ± 6.44 Leke (66) Cameroon 2018 cross-sectional 795 73.2 13–17 5.2% 18–25 47.8%, 285 75.0%,26–35 42.1% Liao (67) China 2015 cross-sectional 422 2.6 20–42 ,29.57 ± 3.966 Lutz (15) Brazil 2015 Cohort 4270 27.7 NR Marwa (68) Tanzania 2018 cross-sectional 372 46.24 18–27 47.06% 28–37 45.32% 38–47 45.45% > 47 0% Mbarambara (69) Congo 2016 A cross-sectional 920 59.9 15–19 28.0%,20–24 38.6%, 25–29 19.3% 30–35 11.0%, > 35 3.0% Mehmood (70) Pakistane 2018 A cross-sectional 351 63.5 18–45 26.28 ± 10.42 Niriayo (22) Ethiopia 2021 A cross-sectional 250 40.8 < 18 0.8% 19–25 46%,26–30 33%, 31–35 13.6%, > 35 6.4% Odalovic (17) Serbia 2012 cohort 218 34.7 NR Ojo (71) Nigeria 2020 cross-sectional 343 48.9 15–20 3.2% 21–26 29.7%,27–32 43.4%, 33 and above 23.6% Pakseresht (72) Iran 2020 cross-sectional 598 8.7 16–25 24.4%, 26–35 59.7%, 36–45 15.4%, > 46 0.5% Pereira (23) Brazil 2021 cross-sectional study 297 36.0 < 30 43.9%,30–39 52%, > 40 7.4% Pisa (16) Italy 2015 Cohort 767 39.8 NR Rafiee (73) Iran 2018 cross-sectional 400 25.8 < 25 20.5% 25–30 30.4% >30 72.6% Raheel (74) Saudi Arabia 2017 cross-sectional 354 32 < 20 2.5%,20–30 67%, 31–41 25.5%, > 40 5% Sah (2) Nepal 2020 this cross-sectional 225 41.3 24–29 41.3% Sema (75) Ethiopia 2020 this cross-sectional 400 44.8 28–37 27.83 ± 4.27 Sina (24) Ghana 2021 cross-sectional 367 74.1 18–24 19,6%, 25–34 68.9%, 35–45 11.5 Tefera (76) Ethiopia 2020 cross-sectional 423 18.2 27.22 ± 5.5 Tuha A (77) Ethiopia 2020 cross-sectional 223 26.9 15–19 26% 20–24 10.8%, 25–29 31.8%, 30–34 16.6% 35–39 10.8% 40–49 4% Verstappen (78) Pays bas 2013 cross-sectional 1246 12.5 18–35 23%, > 35 15.1% Wakjira (79) Ethiopia 2019 cross-sectional 195 21.5 30.4 + 3.45 Yusuff (18) Nigeria 2011 cross-sectional 1594 63.8 NR Zaki (80) Saudi Arabia 2013 cross-sectional 760 40 20–30 34.2%, 30–40 44.7%, 40–50 21.1% Zewdie (81) ethiopia 2018 cross-sectional 323 15.5 15–24 29.1%, 25–34 63.8% Andy Emmanuel(82) Nigeria 2014 cross-sectional 120 85 15–20 16.6%, 21–25 37.5%,26–30 18.3%, 31–35 15%, 36–40 9.16%, > 40 3.33% M. Sarani, S. Saravani (83) Iran 2017 cross-sectional 350 46.6 31.4 ± 7.3 M. J. Twigg1 (84) UK 2016 cross-sectional 856 76.4 30.5 (5.2) D. Courrier (6) france 2015 cross-sectional 740 41,5 30,4 (± 4,6) Lupattelli (25) Ausralia 2014 cross-sectional 217 77.4 NR Italy 926 44 austria 82 62.2 Switzerland 618 72.5 france 374 71.9 Pays bas 81 85.2 UK 1120 82.1 Norway 1288 70.4 Sweden 877 79.3 Finland 574 84.8 Iceland 71 81.7 Russia 1008 66.4 Poland 679 57.1 Croatia 286 39.7 Serbia 220 45.5 Slovenia 149 52.3 USA 297 60.6 Canada 236 68.6 South America 346 45.1 Lunardi-Maia (85) Brazil 2014 cross-sectional 212 46.7 NR Maslakpak (86) Iran 2013 cross-sectional 116 27.6 NR Shah (87) Pakistan 2021 cross-sectional 205 79 NR Rahbar (88) Iran 2017 cross-sectional 226 74.3 NR Baghianimoghadam (89) Iran 2013 cross-sectional 180 35 NR Miní E (90) Peru 2012 cross-sectional 400 10.5 NR Risk of bias in studies The findings of the quality appraisal of eligible studies were reported in Fig. 2 . The tool is used to indicate the methodological quality and appropriateness of the observational studies, including cross-sectional and cohort studies that were reviewed in this study. We determined the score by counting the asterisks (*) that we gave to each answer to the items in the grids, where a high score (11 − 8) indicates a higher quality of a study, a Middle score (6 − 5) indicates middle quality and Low Score (4 − 0) indicates low quality. The sex of the sixty-five studies was evaluated by the abstract since these articles are in Spanish and Persian language and we have no response from their authors to retrieve the full text. Two reviewers completed this process, and where there were discrepancies, a team of reviewers intervened to resolve them. Meta-analysis of the prevalence of self-medication in pregnant women The overall prevalence of self-medication among pregnant women was 44.50% (95% CI: 38.92–50.23). Overall the prevalence ranged from 2.61–85%, as shown in the forest plot (Fig. 3 ). The I2 test revealed a high statistically significant heterogeneity of 99%. Results of the subgroup analysis are shown in Fig. 4 (A, B, C, D, E). Analysis was based on income level, geographic region, quality of publication study, sample size, and study design. Heterogeneity, assessed by the statistical test I2 was high, statistically significant for all subgroup analyses, and ranging from 96–99%. By region, the highest prevalence of self-medication was 77.42% (95% CI: 77.27–82.80%) in Australia and the lowest was 33.17% (95% CI: 25.22–42.22%) in Asia (Fig. 4 B). Stratifying by a score of the quality assessment of the studies, the prevalence of self-medication was 33.95% (95% CI: 27.72–40.80%) in studies with high scores. 58.95% (95% CI: 52.03–65.53%), and 42.68% (95% CI: 23.28–64.63%), in middle and low quality respectively. For the cohort studies, the prevalence was lower 33.52% (95% CI: 27.68–39.91%), and 44.93%(95% CI: 39.14–50.86%) for the cross-sectional studies. To assess publication bias, we applied the funnel plot (Fig. 5 ). The result of this funnel plot showed that the funnel plot was symmetry with p-value = 0.36, and there is no publication bias. We did the trim and fill analysis to see the number of missed studies and found that the estimated number of missing studies was 0. The distribution of the published studies displayed in the funnel plot is consistent with the foregoing observation. Sensitivity Analysis Due to the high heterogeneity of the results, sensitivity analysis was done after excluding studies with a high risk of bias (Fig. 6 A) and studies with small sample sizes (Fig. 6 B). The sensitivity analysis showed the stability of the results. The overall prevalence of self-medication based on the random effect model was determined to be 43.70% and 47.34% for the studies with a low score and small sample size, respectively. The results showed that the prevalence of self-medication did not generally change confirming the robustness and reliability of our findings. The reason and motivation for self-medication practice The time is taken in deciding on self-medication differed considerably and it’s depending on women’s health needs, information available, and preference. Some studies discovered women’s personal preferences motivated the choices and decisions made. There are many factors responsible for self–medication practice among pregnant women. The majority of the respondents pointed that drugs are easily available in drug stores or pharmacies or by the availability of old prescription that helps themes to purchase drugs. Others think that they have better knowledge about the disease and the treatment, they knew that the medication is safe during pregnancy. This report is logical when the respondents see that the illness as minor diseases will definitely not worry themselves to visit the health facility for professional care and will therefore prefer to buy non-prescribed drug from the patent medicine shop for treatment. Especially when costly medical are expensive and the Lack of healthcare insurance, then women considerate self-medication as a cheaper practice. Others reported that the previous medication good experiences are one of the reason for self-medication. Self-medication for health problem treatments Most of pregnant women practice self-medication on the given health condition/diagnosis and accompanying treatment plans, and the desire to get over the pain, the complication, or if infertility persisted over time. Pregnant women practice self-medication to alleviate pregnancy associated symptom. Antiemetics, antiacids and antipain are the most frequently drugs used to treat gastrointestinal disorders such as nausea, vomiting, abdominal pain, bloating, flatulence and stomach aches followed by Antibiotics and Analgesics to treat cold and flu symptoms. Other women treat Anemia and Weakness with Vitamins, Calcium supplement, antianemia, folic acid and Iron. Some African studies reported that pregnant women self-medicate with Antimalaria to treat Malaria (Table 2 ). Whereas others reported self-medication practices with Anti-inflammatory antirheumatic, anthelminthic, and antiepyliptics. Other uses were specifically for the stimulation of labor or facilitation of labor and delivery. Finally, skin problems, Sleep disorders, and weight loss is the fewer reasons that we have marked among some users. Illness drugs used for and family therapeutics of drugs are reported in Table 2 . The source and quality of the information received The choice of treatment for maternal illness was influenced partly by the source and quality of information on drugs received. Differences in over-the-counter drug use patterns and drug prescribing systems that differ from one country to another. For example, in some African countries, all medicines can be purchased without a prescription. However, Pharmacies or drug stores that were authorized to vend and supply drugs and relevant information left significant adverse implications on the overall health outcomes of users. This means that women who practice self-medication were most likely influenced by the source they originated, from and the quality of the information about the drugs. Most of the studies indicated the source and quality of information, first, some women decided in person to use drugs during pregnancy through past prescriptions and family storage boxes. Second, some of the pregnant women received recommendations from family (Mothers), friends, and neighbors. Healthcare workers (physicians and nurses) and internet pharmacies also influence women’s decisions to use drugs and finally other users had recommendations from the internet, social media, newspaper, radio, and television. Discussion The results of the present study showed that the global prevalence of self-medication among pregnant women in the world is 44.55% although the results show a high heterogeneity. This rate is similar to the results of a systematic review and meta-analysis that investigated self-medication among Iranian pregnant women (38.46%)(27). Despite the prevalence of self-medication being higher in pregnant women, due to the complications of pregnancy, Our results compared to the results of other studies showed that self-medication in pregnant women was relatively low in comparison with other groups in general. (28,29). A meta-analysis conducted in Iran among students showed a very high prevalence of 70.1% (30). The results of the subgroup analysis in our study showed that the prevalence of self-medication varies by region, this finding is attributable to the difference in health-related socio-cultural knowledge, beliefs, attitudes, and behaviors among pregnant women from different geographical areas. The large difference in prevalence rates of self-medication in different regions of the world may be due to differences in over-the-counter drug use patterns and drug prescribing systems that differ from one country to another. For example, in some African countries, all medicines can be purchased without a prescription (31). Other reasons that may influence self-medication include the high cost of medical visits and limited health insurance coverage. Women with unplanned pregnancies are also more likely to self-medicate(18). The low prevalence rate noted in Asian countries may be due to the cultural and social habits of using complementary and alternative medicine. The prevalence of the use of herbal medicines among pregnant women varied from 22.3–82.3%, this was reported in a systematic review conducted on Middle East (32). Other studies conducted in Iran, Palestine, and Saudi Arabia reported a higher prevalence of herbal use among pregnant, 89.9%, 88.4%, and 66% respectively (33–35). Most pregnant women believe that herbal medicine is more effective than conventional medicine (36). Others think that are safe and secure for the mother and her fetus and have fewer side effects than conventional medicine during pregnancy (37–39). Stratifying by score of the quality assessment of the studies, the prevalence of self-medication was 33.95% (95% CI: 27.72–40.80%) in studies with high score. 58.95% (95% CI: 52.03–65.53%), and 42.68% (95% CI: 23.28–64.63%), in middle and low quality respectively. This can be explained by the fact that high-quality studies have a low risk of bias and therefore the prevalence approaches the pooled prevalence (44.50%). But the low quality studies probably overestimated the prevalence because of the low recruited sample size. For the cohort studies, the prevalence was lower 33.52% (95% CI: 27.68–39.91%), and 44.93%(95% CI: 39.14–50.86%) for the cross sectional studies this can be explained by the fact that research methodology of the cohort studies are very rigorous with a best evidence (40). In recent years, several initiatives and interventions, such as improving the knowledge of pregnant women about the consequences of self-medication, as well as the provision of brochures and catalogs, have been planned and implemented, which could be very effective in combating this practice. In addition, the continuous training of health professionals on the prescription of drugs and the advice given when dispensing drugs to pregnant women could reduce the prevalence of self-medication. Despite the efforts made by countries to reduce self-medication among pregnant women, this practice is still on the rise, it is, therefore, urgent to adopt new and more effective prevention measures. Strengths and limitations of the study The strengths of our study are the large sample size, sample size analysis, and subgroup analysis. All these analyses reflect the methodological rigor of our systematic review and meta-analysis. On the other hand, the included articles provide large and profound information on various aspects of self-medication in pregnant women (prevalence, groups of drugs most used by pregnant women, groups of diseases most often treated by self-medication, and the most common reasons for self-medication) that can be used by health professionals to make decisions and organize effective interventions to prevent self-medication in pregnant women. The limitation of this study was the fact that we included only articles in English and French, while we excluded some studies of Spanish and Farsi languages after exploiting their abstracts if only it reports the prevalence of self-medication. Another limitation of the present study was the high possibility of publication bias and heterogeneity in the results, which could be due to methodological differences in the different studies. In addition, the quality of the included studies was different and the inclusion of some studies of poor quality may affect the final estimate. Conclusion The results obtained from this study showed that the prevalence of self-medication among pregnant women is relatively high. This requires effective measures and interventions to reduce self-medication. We recommend that health professionals consider implementing programs on the risks of self-medication, and strengthening the control and monitoring of over-the-counter sales of drugs. Physicians and pharmacists should also be made more sensitive to prescribing the appropriate medication and avoiding the provision of medication without a prescription Declarations Availability of Data and Materials All data generated or analyzed during this study are included in the article . Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials Not applicable Competing interests The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest Funding None Author Contributions AB, LL conceived of the study and compiled the data used in analyses and conducted analyses, and drafted the manuscript. FA, SB, YK assisted within perpetration of the data and provided feedback for this manuscript, RR, RA supervised the findings of this work. All authors read and approved the final manuscript. Acknowledgment The authors would like all the researchers whose works were used in the present study. Authors' information (optional) References WHO_EDM_QSM_00.1_eng.pdf [Internet]. [cité 25 sept 2022]. 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Archives of Iranian medicine. 2013;16(10):0‑0. Miní E, Varas R, Vicuña Y, Lévano M, Rojas L, Medina J, et al. [Self-medication behavior among pregnant women user of the Instituto Nacional Materno Perinatal, Peru 2011]. Rev Peru Med Exp Salud Publica. juin 2012;29(2):212‑7. Table Table 2 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table2GeneraldescriptionofAssociatedFactorsofselfmedicationamongworldwidepregnantwomen.docx Table 2 : General description of Associated Factors of self-medication among worldwide pregnant women Cite Share Download PDF Status: Published Journal Publication published 27 Jan, 2024 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Major revision 28 Jun, 2023 Reviews received at journal 12 Jun, 2023 Reviewers agreed at journal 01 Jun, 2023 Reviewers agreed at journal 31 May, 2023 Reviewers invited by journal 28 May, 2023 Editor assigned by journal 18 May, 2023 Editor invited by journal 18 Apr, 2023 Submission checks completed at journal 18 Apr, 2023 First submitted to journal 08 Apr, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":201449,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eForest Plot of the prevalence of self-medication among pregnant women\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2791845/v1/96a5d3402f26b94b2b4e39fa.png\"},{\"id\":36088662,\"identity\":\"835e8824-5d71-496f-9bbf-0a480095b753\",\"added_by\":\"auto\",\"created_at\":\"2023-04-20 21:44:08\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1125312,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eForest Plot of subgroups analysis based on Income Level (Fig.4.A), Region (Fig.4.B), Quality of studies (Fig.4.C), Sample size (Fig.4.D), and Study Design (Fig.4.E).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2791845/v1/be3b8c7836cf3d2bed9a8e2c.png\"},{\"id\":36088663,\"identity\":\"eaa19aa9-a15d-472d-9885-09f9929b93eb\",\"added_by\":\"auto\",\"created_at\":\"2023-04-20 21:44:08\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":95520,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFunnel Plot to evaluate the publications Bias before (panel A) and after (panel B) applying the trim and fill methods.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2791845/v1/50b4c971415dfbd04d745ada.png\"},{\"id\":36089208,\"identity\":\"9af3b56f-7437-4421-af9a-2b43fc27ebe8\",\"added_by\":\"auto\",\"created_at\":\"2023-04-20 21:52:08\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":352976,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSensitivity analysis of the stability of the results of panel A studies with a high risk of bias and panel B studies with small sample size.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2791845/v1/8c6a3d7fad3a97b4128bce01.png\"},{\"id\":50314408,\"identity\":\"f2d6424b-02ed-4efa-9129-b3aab33443b4\",\"added_by\":\"auto\",\"created_at\":\"2024-01-29 15:30:27\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1666936,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2791845/v1/835a7d71-666f-4292-b1b7-3fffa5b77e4d.pdf\"},{\"id\":36088659,\"identity\":\"9e5b5eda-dc41-40aa-9044-556a3f4bfa01\",\"added_by\":\"auto\",\"created_at\":\"2023-04-20 21:44:07\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":60128,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 2\\u003c/strong\\u003e : General description of Associated Factors of self-medication among worldwide pregnant women\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table2GeneraldescriptionofAssociatedFactorsofselfmedicationamongworldwidepregnantwomen.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2791845/v1/998f8278af93873e4029692c.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Prevalence and associated factors of Self-medication in worldwide pregnant women: Systematic Review and Meta-Analysis \",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eThe World Health Organization (WHO) defines self-medication as a practice that leads individuals to treat their illnesses with authorized medicines. Self-medication can be defined as \\\"the act of the subject, on his initiative, to consume a drug without consulting a doctor, and whether the drug is already in his possession or whether he obtains it from a pharmacy or from another person (1). It is a very prevalent practice, and the majority of medicines consumed by the population are available without a doctor's prescription (2). The practice of self-medication is common throughout the world, both in developing and developed countries (3). The number of people who self-medicate varies significantly by country, for example, in a study conducted in the United States about 71% of men and 82% of women had used self-medication at least once(4). In the United Kingdom of Britain and Northern Ireland, 41.5% of people had used medicines without a prescription(5).\\u003c/p\\u003e \\u003cp\\u003eThe use of drugs during pregnancy requires a careful reflection on the benefits to the mother and the risks to the fetus. It is a difficult medical situation for clinicians to select the drug because of the various pharmacokinetic and physiological changes encountered in pregnant women (6,7). Self-medication during pregnancy is of great interest; it carries serious risks of drug interactions, misdiagnosis, use of excessive doses of drugs, and prolonged use of drugs. (8,9). In Europe, a survey of 740 pregnant women conducted in France revealed that 41.5% of the participants in the study practiced self-medication (3). In Africa, a systematic review conducted in Ethiopia revealed a prevalence of self-medication of 12.8\\u0026ndash;77.1%(7). The studies are contradictory some of them report a high prevalence and others show the opposite. Also, no meta-analysis of the prevalence of self-medication in pregnant women has been carried out in the world. The goal of this study was to estimate the pooled prevalence of self-medication in worldwide pregnant women through a systematic review and a meta-analysis of published studies on self-medication during pregnancy.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003eThe steps of this systematic review complied with the recommendations in the PRISMA (Preferred Reporting for Systematic Reviews and Meta-Analysis) grid. A systematic review protocol was registered by PROSPERO.55 with ID\\u0026thinsp;=\\u0026thinsp;CRD42022312333. In this study, the focused research question was: \\u0026ldquo;What is the prevalence of self-medication in pregnant women in the world?\\u0026rdquo; (10).\\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eInclusion and exclusion criteria\\u003c/h2\\u003e \\u003cp\\u003eWe included all published articles between January 2011 and December 2021. We also included all original studies published in English and French and human studies of pregnant or postnatal women. Studies or scientific medical literature were also included if they described the prevalence of self-medication. Only observational studies of cross-sectional type were included, as well as cohort studies if they mentioned the prevalence of self-medication in pregnant women.\\u003c/p\\u003e \\u003cp\\u003eWe excluded non-English studies (Persian and Spanish) if they didn\\u0026rsquo;t contain the requested data. We also excluded unpublished reports, pilot studies, conference abstracts, opinion articles, editorial reports, seminal work, systematic reviews, and animal research.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData sources and search strategy\\u003c/h2\\u003e \\u003cp\\u003eTo collect the maximum of data, we performed an exhaustive bibliographic search in PubMed, Science Direct, Google Scholar, and Web of Science databases started in December 2021. It was performed to identify all relevant studies available from January 2011 to December 2021. The search was performed using Boolean operators AND or OR that narrowed the search and also using a combination of terms and medical subject heading (MeSH). For example, the search strategy in PubMed was as follows: (((self care[MeSH Terms])) OR (self medication[MeSH Terms])) AND (pregnan*[MeSH Terms])\\u003c/p\\u003e \\u003cp\\u003eAll stages of the search were performed by 2 independent researchers (B.A) and (L.L). Any disagreements were resolved by a third researcher (K.Y).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStudy selection\\u003c/h2\\u003e \\u003cp\\u003eA screening strategy was implemented to identify all relevant studies. We used Covidence, software that was developed by an Australian in 2015, it\\u0026rsquo;s the primary screening and data extraction tool for Cochrane authors conducting standard intervention reviews. Covidence is designed to perform the following functions to make review production more efficient. Initially, duplicates were eliminated by the software. Then secondly, the initial selection was made according to the abstract and title. This was followed by reading the full text to identify eligible studies. In case of disagreement, a third reviewer (K.Y) was asked to make a clean agreement. Finally, the articles included in this review were downloaded and the references of each article were manually searched to determine whether other studies met the criteria.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eQuality Assessment\\u003c/h2\\u003e \\u003cp\\u003eThe quality assessment of eligible studies was reviewed by two independent reviewers (B.A) and (L.L). This process was conducted using a recent version of the Joanna Briggs Institute's critical appraisal tools (Checklist for Analytical Cross-Sectional Studies and Cohort studies) (11,12). Joanna Briggs Institute (JBI) is an international research organization based in the Faculty of Medical and Health Sciences at the University of Adelaide in South Australia. (13). The purpose of this process is to assess the methodological quality and risk of bias in included studies. This checklist is divided into eight items for cross-sectional studies and ten items for cohort studies. Each item is scored with one point. A study was considered low quality if it had 0\\u0026ndash;4 points, moderate quality if it had 5\\u0026ndash;6 points, and high quality if it had 7\\u0026ndash;8 points.\\u003c/p\\u003e \\u003cp\\u003eA third reviewer (Y.K.) was consulted if a consensus could not be reached. When information was missing from the studies, we tried to contact the authors by e-mail. All cross-sectional and cohort studies were included, regardless of their quality score. Articles with missing data were included as long as they reported the prevalence of self-medication.\\u003c/p\\u003e \\u003cp\\u003eThe results of the quality assessment of eligible studies are presented in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData extraction\\u003c/h2\\u003e \\u003cp\\u003eData covering author, country, year of publication, sample size, age of participants, and prevalence of self-medication were extracted and collated in an Excel table. We also extracted the associated factors of self-medication including the reason for use, source of information, illness of drug used, type of drugs used, and finally sociodemographic characteristics of pregnant women. Any disagreements were resolved by consensus with a third reviewer (K.Y). For non-English studies, we extracted data from the abstracts available in English\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical Analysis\\u003c/h2\\u003e \\u003cp\\u003eTo calculate the pooled prevalence, we used a random-effects model, calculating effect sizes with a confidence interval (CI). Heterogeneity between studies was assessed using the Cochrane Q test with the I2 index. I2 values equal to 25%, 50%, and 75% were synonymous with low, moderate, and high heterogeneity respectively. Publication bias was assessed using a funnel plot and Egger and Begg\\u0026rsquo;s test. We conduct also the trim-and-fill method aims at estimating potentially missing studies due to publication bias in the funnel plot and adjusting the overall effect estimate. To investigate the effect of variables on heterogeneity, we performed a subgroup analysis by ranking eligible studies by income (based on the country in which the study was conducted). This was done by consulting the World Bank website (14), study region, sample size, and study quality. The R software was used for the statistical analysis. In the R4.1.2 version, we used the Meta and Metafor packages for the metanalysis.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSensitivity Analysis\\u003c/h2\\u003e \\u003cp\\u003eTo identify and reduce the source of heterogeneity, We conducted sensitivity analysis based on studies with small sample sizes (\\u0026ge;\\u0026thinsp;500 participants), and studies with a high risk of bias in any methodological domain (studies that have a low-quality score).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e\\u003cem\\u003eOutcome measurement\\u003c/em\\u003e\\u003c/h2\\u003e \\u003cp\\u003eWhat is the prevalence of self-medication? The Prevalence is the proportion of pregnant women who have self-medicated or taken drugs without a doctor\\u0026rsquo;s prescription during their pregnancy period.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eStudy selection\\u003c/h2\\u003e\\n \\u003cp\\u003eThe flow chart of the studies included in this systematic review is shown in Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. The search generated 4475 articles, 151 of which were duplicates and subsequently deleted. We examined the titles and abstracts of 4324 articles. In addition, 4202 were excluded as ineligible based on the inclusion and exclusion criteria of the analysis. Then we examined the full text of the remaining 122 articles for eligibility. We, therefore, excluded 61 studies with the reason (False target population (32), false study design (22), non-English articles (5), and Thesis(2)), therefore 59 studies were eligible and they proceeded to the data extraction after adding four articles from the manual search. Finally, 65 studies were eligible and included in the present systematic review.\\u003c/p\\u003e\\n \\u003ch2\\u003e\\u003cem\\u003eCharacteristics of included studies\\u003c/em\\u003e\\u003c/h2\\u003e\\n \\u003cp\\u003eThe total sample size analyzed included 42615 pregnant women. The studies were published between 2011 and 2021. All included studies were cross-sectional observational studies except three studies were Cohort (15\\u0026ndash;17). The oldest study in terms of publication year (2011) is (18). The most recent studies published in 2021 are (2,19\\u0026ndash;24) (Table \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cp\\u003eOne study used the largest sample size of 9,459 parturient. This was a multinational study conducted in Europe (western, northern, and eastern), North and South America, and Australia (25). While the study carried out in France recruited only 68 participants(26). The age of the participants ranged from 15 to 60 years. Regarding the region where the studies were conducted, 26 (31.32%) studies were conducted in Africa, 25 (30.12%) in Asia and 21 (25.30%) in Europe, 10 (12.04%) in America, 1 (1.20%) in Australia.\\u003c/p\\u003e\\n \\u003cp\\u003eOf most of the studies 29 (34.93%) were conducted in high-income countries, 28 (33.73%) in low-middle-income countries, 14 (16.86%) in low-income countries, and 12 (14%.45) in upper-middle-income countries. Regarding the quality of the studies, 42 (50.60%) articles were high quality (score of 7\\u0026ndash;8), 33 (39.75%) medium quality (6\\u0026thinsp;\\u0026minus;\\u0026thinsp;5), and 8 studies (9.63%) low quality (4\\u0026thinsp;\\u0026minus;\\u0026thinsp;0).\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003c/p\\u003e\\u0026nbsp;\\u003ctable id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eMain characteristics of the included studies\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eReferences\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCountry\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eYear of publication\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eStudy design\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSample size\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePrevalence\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAtif (41)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePakistan\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd 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\\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;20 8,7%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAbduelkarem (43)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eUnited Arab Emirates\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCross sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e140\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e40.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;20 (2.1%) 21\\u0026ndash;25 (25%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAbeje(44)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCross sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e510\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2510\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e26.5 (\\u0026plusmn;\\u0026thinsp;6.0).\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAdanikin(31)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNigeria\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCross sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e346\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e31.50\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;20 (1.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAfshary(45)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e801\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e30.60\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLess than 25 37,8%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eSeid Mussa Ahmed(46)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1117\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18\\u0026ndash;45 years old, with a median age 25 years\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAke(19)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNigeria\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e359\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e40.40\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e26.92 years (SD\\u0026thinsp;=\\u0026thinsp;+\\u0026thinsp;5.057\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAlonso-Castro(47)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMexico\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eA cross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1798\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e21.90\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;25 37,6%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAlsous (48)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eJordan\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1313\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e33.10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e31.11\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAraujo (49)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBrazil\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e78\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e28.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eAtmadani (50)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIndonesia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e333\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e11.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e16\\u0026ndash;27 41%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBefekadu (51)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e315\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e20.10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMean\\u0026thinsp;=\\u0026thinsp;22.58 SD\\u0026thinsp;=\\u0026thinsp;4.298\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBeza (52)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e617\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e26.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18\\u0026ndash;24 (31.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBiBintsene (53)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCongo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e350\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e46.24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e67\\u0026thinsp;+\\u0026thinsp;6,3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eBobga (20)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCameron\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e500\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e67.40\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;20 23.0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBohio (54)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePakistan\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e351\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e36.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e26.19\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eMalihe Botyar (55)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e210\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e34.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026gt;\\u0026thinsp;20 0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBulabula (56)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSouth Africa\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2019\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e301\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e16.60\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e29 (6.1) years\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eCabut (26)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFrance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eA cross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e68\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e[30.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.9]\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNavaro (57)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eItaly\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e503\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e59.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEbrahimi (58)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e384\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e43.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e26.33\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.60\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGbagbo (59)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGhana\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e136\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e69\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e29\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eGrover (60)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eUSA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2019\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e138\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e53%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHaque (61)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBangladesh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e650\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e12.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;20 35.4% 21\\u0026ndash;25 30.4% ,26\\u0026ndash;30 24.1%, 31\\u0026ndash;35 7.6%,36\\u0026ndash;40 2.5%,\\u0026gt;40 0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBarhamji (62)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFrance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e330\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e46\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e29,7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5,3 ans\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eIbrahim,(21)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eUnited Arab Emirates\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e434\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;20 2% ,20\\u0026ndash;29 31.3%, 30\\u0026ndash;39 37.6%,40\\u0026ndash;60 29.1%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eJambo (63)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e244\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e69.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.68\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eKabamba (64)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCongo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e145\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e16\\u0026ndash;20 15,1%, 21\\u0026ndash;30 57,9%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eKarami Matin (65)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e308\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e29.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e19\\u0026ndash;43 29.16\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.44\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLeke (66)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCameroon\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e795\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e73.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e13\\u0026ndash;17 5.2% 18\\u0026ndash;25 47.8%, 285 75.0%,26\\u0026ndash;35 42.1%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLiao (67)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eChina\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e422\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e20\\u0026ndash;42 ,29.57\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.966\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLutz (15)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBrazil\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCohort\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4270\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e27.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMarwa (68)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTanzania\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e372\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e46.24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18\\u0026ndash;27 47.06% 28\\u0026ndash;37 45.32% 38\\u0026ndash;47 45.45% \\u0026gt; 47 0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eMbarambara (69)\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCongo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eA cross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e920\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e59.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;19 28.0%,20\\u0026ndash;24 38.6%, 25\\u0026ndash;29 19.3% 30\\u0026ndash;35 11.0%, \\u0026gt; 35 3.0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMehmood (70)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePakistane\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eA cross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e351\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e63.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18\\u0026ndash;45 26.28\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;10.42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNiriayo (22)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eA cross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e250\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e40.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;18 0.8% 19\\u0026ndash;25 46%,26\\u0026ndash;30 33%, 31\\u0026ndash;35 13.6%, \\u0026gt;\\u0026thinsp;35 6.4%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOdalovic (17)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSerbia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecohort\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e218\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e34.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOjo (71)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNigeria\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e343\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e48.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;20 3.2% 21\\u0026ndash;26 29.7%,27\\u0026ndash;32 43.4%, 33 and above 23.6%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePakseresht (72)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e598\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e16\\u0026ndash;25 24.4%, 26\\u0026ndash;35 59.7%, 36\\u0026ndash;45 15.4%, \\u0026gt;\\u0026thinsp;46 0.5%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePereira (23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBrazil\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional study\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e297\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e36.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;30 43.9%,30\\u0026ndash;39 52%, \\u0026gt;\\u0026thinsp;40 7.4%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePisa (16)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eItaly\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCohort\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e767\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e39.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRafiee (73)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e400\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;25 20.5% 25\\u0026ndash;30 30.4% \\u0026gt;30 72.6%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRaheel (74)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSaudi Arabia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e354\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e32\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;20 2.5%,20\\u0026ndash;30 67%, 31\\u0026ndash;41 25.5%, \\u0026gt;\\u0026thinsp;40 5%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSah (2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNepal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ethis cross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e225\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e41.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e24\\u0026ndash;29 41.3%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSema (75)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ethis cross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e400\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e44.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e28\\u0026ndash;37 27.83\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSina (24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGhana\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e367\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e74.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18\\u0026ndash;24 19,6%, 25\\u0026ndash;34 68.9%, 35\\u0026ndash;45 11.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTefera (76)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e423\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e27.22\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTuha A (77)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e223\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e26.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;19 26% 20\\u0026ndash;24 10.8%, 25\\u0026ndash;29 31.8%, 30\\u0026ndash;34 16.6% 35\\u0026ndash;39 10.8% 40\\u0026ndash;49 4%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eVerstappen (78)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePays bas\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1246\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e12.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e18\\u0026ndash;35 23%, \\u0026gt;\\u0026thinsp;35 15.1%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eWakjira (79)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEthiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2019\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e195\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e21.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e30.4\\u0026thinsp;+\\u0026thinsp;3.45\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eYusuff (18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNigeria\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1594\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e63.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eZaki (80)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSaudi Arabia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e760\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e40\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e20\\u0026ndash;30 34.2%, 30\\u0026ndash;40 44.7%, 40\\u0026ndash;50 21.1%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eZewdie (81)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eethiopia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e323\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;24 29.1%, 25\\u0026ndash;34 63.8%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAndy Emmanuel(82)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNigeria\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e120\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e85\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u0026ndash;20 16.6%, 21\\u0026ndash;25 37.5%,26\\u0026ndash;30 18.3%, 31\\u0026ndash;35 15%, 36\\u0026ndash;40 9.16%, \\u0026gt;\\u0026thinsp;40 3.33%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eM. Sarani,\\u0026nbsp;S. Saravani (83)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e350\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e46.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e31.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;7.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eM. J. Twigg1 (84)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eUK\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e856\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e76.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e30.5 (5.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eD. Courrier (6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003efrance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e740\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e41,5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e30,4 (\\u0026plusmn;\\u0026thinsp;4,6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"19\\\"\\u003e\\n \\u003cp\\u003eLupattelli (25)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAusralia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" rowspan=\\\"19\\\"\\u003e\\n \\u003cp\\u003e2014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"19\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e217\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e77.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"19\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eItaly\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e926\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e44\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eaustria\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e62.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSwitzerland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e618\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e72.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003efrance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e374\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e71.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePays bas\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e85.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eUK\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1120\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e82.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNorway\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1288\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e70.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSweden\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e877\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e79.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFinland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e574\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e84.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIceland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e81.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRussia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1008\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e66.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePoland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e679\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e57.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCroatia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e286\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e39.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSerbia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e220\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e45.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSlovenia\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e149\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e52.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eUSA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e297\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e60.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCanada\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e236\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e68.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSouth America\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e346\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e45.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLunardi-Maia (85)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBrazil\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e212\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e46.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMaslakpak (86)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e116\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e27.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eShah (87)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePakistan\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e205\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e79\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRahbar (88)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e226\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e74.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBaghianimoghadam (89)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIran\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e180\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMin\\u0026iacute; E (90)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePeru\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ecross-sectional\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e400\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003cp\\u003e\\u003c/p\\u003e\\n \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section3\\\"\\u003e\\n \\u003ch2\\u003eRisk of bias in studies\\u003c/h2\\u003e\\n \\u003cp\\u003eThe findings of the quality appraisal of eligible studies were reported in Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e. The tool is used to indicate the methodological quality and appropriateness of the observational studies, including cross-sectional and cohort studies that were reviewed in this study. We determined the score by counting the asterisks (*) that we gave to each answer to the items in the grids, where a high score (11\\u0026thinsp;\\u0026minus;\\u0026thinsp;8) indicates a higher quality of a study, a Middle score (6\\u0026thinsp;\\u0026minus;\\u0026thinsp;5) indicates middle quality and Low Score (4\\u0026thinsp;\\u0026minus;\\u0026thinsp;0) indicates low quality. The sex of the sixty-five studies was evaluated by the abstract since these articles are in Spanish and Persian language and we have no response from their authors to retrieve the full text. Two reviewers completed this process, and where there were discrepancies, a team of reviewers intervened to resolve them.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section3\\\"\\u003e\\n \\u003ch2\\u003eMeta-analysis of the prevalence of self-medication in pregnant women\\u003c/h2\\u003e\\n \\u003cp\\u003eThe overall prevalence of self-medication among pregnant women was 44.50% (95% CI: 38.92\\u0026ndash;50.23). Overall the prevalence ranged from 2.61\\u0026ndash;85%, as shown in the forest plot (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). The I2 test revealed a high statistically significant heterogeneity of 99%.\\u003c/p\\u003e\\n \\u003cp\\u003eResults of the subgroup analysis are shown in Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e (A, B, C, D, E). Analysis was based on income level, geographic region, quality of publication study, sample size, and study design. Heterogeneity, assessed by the statistical test I2 was high, statistically significant for all subgroup analyses, and ranging from 96\\u0026ndash;99%. By region, the highest prevalence of self-medication was 77.42% (95% CI: 77.27\\u0026ndash;82.80%) in Australia and the lowest was 33.17% (95% CI: 25.22\\u0026ndash;42.22%) in Asia (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eB). Stratifying by a score of the quality assessment of the studies, the prevalence of self-medication was 33.95% (95% CI: 27.72\\u0026ndash;40.80%) in studies with high scores. 58.95% (95% CI: 52.03\\u0026ndash;65.53%), and 42.68% (95% CI: 23.28\\u0026ndash;64.63%), in middle and low quality respectively.\\u003c/p\\u003e\\n \\u003cp\\u003eFor the cohort studies, the prevalence was lower 33.52% (95% CI: 27.68\\u0026ndash;39.91%), and 44.93%(95% CI: 39.14\\u0026ndash;50.86%) for the cross-sectional studies.\\u003c/p\\u003e\\n \\u003cp\\u003eTo assess publication bias, we applied the funnel plot (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The result of this funnel plot showed that the funnel plot was symmetry with p-value\\u0026thinsp;=\\u0026thinsp;0.36, and there is no publication bias. We did the trim and fill analysis to see the number of missed studies and found that the estimated number of missing studies was 0. The distribution of the published studies displayed in the funnel plot is consistent with the foregoing observation.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section3\\\"\\u003e\\n \\u003ch2\\u003eSensitivity Analysis\\u003c/h2\\u003e\\n \\u003cp\\u003eDue to the high heterogeneity of the results, sensitivity analysis was done after excluding studies with a high risk of bias (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eA) and studies with small sample sizes (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eB). The sensitivity analysis showed the stability of the results. The overall prevalence of self-medication based on the random effect model was determined to be 43.70% and 47.34% for the studies with a low score and small sample size, respectively. The results showed that the prevalence of self-medication did not generally change confirming the robustness and reliability of our findings.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eThe reason and motivation for self-medication practice\\u003c/h2\\u003e\\n \\u003cp\\u003eThe time is taken in deciding on self-medication differed considerably and it\\u0026rsquo;s depending on women\\u0026rsquo;s health needs, information available, and preference. Some studies discovered women\\u0026rsquo;s personal preferences motivated the choices and decisions made. There are many factors responsible for self\\u0026ndash;medication practice among pregnant women. The majority of the respondents pointed that drugs are easily available in drug stores or pharmacies or by the availability of old prescription that helps themes to purchase drugs. Others think that they have better knowledge about the disease and the treatment, they knew that the medication is safe during pregnancy. This report is logical when the respondents see that the illness as minor diseases will definitely not worry themselves to visit the health facility for professional care and will therefore prefer to buy non-prescribed drug from the patent medicine shop for treatment. Especially when costly medical are expensive and the Lack of healthcare insurance, then women considerate self-medication as a cheaper practice. Others reported that the previous medication good experiences are one of the reason for self-medication.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eSelf-medication for health problem treatments\\u003c/h2\\u003e\\n \\u003cp\\u003eMost of pregnant women practice self-medication on the given health condition/diagnosis and accompanying treatment plans, and the desire to get over the pain, the complication, or if infertility persisted over time. Pregnant women practice self-medication to alleviate pregnancy associated symptom. Antiemetics, antiacids and antipain are the most frequently drugs used to treat gastrointestinal disorders such as nausea, vomiting, abdominal pain, bloating, flatulence and stomach aches followed by Antibiotics and Analgesics to treat cold and flu symptoms. Other women treat Anemia and Weakness with Vitamins, Calcium supplement, antianemia, folic acid and Iron. Some African studies reported that pregnant women self-medicate with Antimalaria to treat Malaria (Table \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Whereas others reported self-medication practices with Anti-inflammatory antirheumatic, anthelminthic, and antiepyliptics. Other uses were specifically for the stimulation of labor or facilitation of labor and delivery. Finally, skin problems, Sleep disorders, and weight loss is the fewer reasons that we have marked among some users. Illness drugs used for and family therapeutics of drugs are reported in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eThe source and quality of the information received\\u003c/h2\\u003e\\n \\u003cp\\u003eThe choice of treatment for maternal illness was influenced partly by the source and quality of information on drugs received. Differences in over-the-counter drug use patterns and drug prescribing systems that differ from one country to another. For example, in some African countries, all medicines can be purchased without a prescription. However, Pharmacies or drug stores that were authorized to vend and supply drugs and relevant information left significant adverse implications on the overall health outcomes of users. This means that women who practice self-medication were most likely influenced by the source they originated, from and the quality of the information about the drugs. Most of the studies indicated the source and quality of information, first, some women decided in person to use drugs during pregnancy through past prescriptions and family storage boxes. Second, some of the pregnant women received recommendations from family (Mothers), friends, and neighbors. Healthcare workers (physicians and nurses) and internet pharmacies also influence women\\u0026rsquo;s decisions to use drugs and finally other users had recommendations from the internet, social media, newspaper, radio, and television.\\u003c/p\\u003e\\n \"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThe results of the present study showed that the global prevalence of self-medication among pregnant women in the world is 44.55% although the results show a high heterogeneity. This rate is similar to the results of a systematic review and meta-analysis that investigated self-medication among Iranian pregnant women (38.46%)(27). Despite the prevalence of self-medication being higher in pregnant women, due to the complications of pregnancy, Our results compared to the results of other studies showed that self-medication in pregnant women was relatively low in comparison with other groups in general. (28,29). A meta-analysis conducted in Iran among students showed a very high prevalence of 70.1% (30). The results of the subgroup analysis in our study showed that the prevalence of self-medication varies by region, this finding is attributable to the difference in health-related socio-cultural knowledge, beliefs, attitudes, and behaviors among pregnant women from different geographical areas. The large difference in prevalence rates of self-medication in different regions of the world may be due to differences in over-the-counter drug use patterns and drug prescribing systems that differ from one country to another. For example, in some African countries, all medicines can be purchased without a prescription (31). Other reasons that may influence self-medication include the high cost of medical visits and limited health insurance coverage. Women with unplanned pregnancies are also more likely to self-medicate(18). The low prevalence rate noted in Asian countries may be due to the cultural and social habits of using complementary and alternative medicine. The prevalence of the use of herbal medicines among pregnant women varied from 22.3\\u0026ndash;82.3%, this was reported in a systematic review conducted on Middle East (32). Other studies conducted in Iran, Palestine, and Saudi Arabia reported a higher prevalence of herbal use among pregnant, 89.9%, 88.4%, and 66% respectively (33\\u0026ndash;35). Most pregnant women believe that herbal medicine is more effective than conventional medicine (36). Others think that are safe and secure for the mother and her fetus and have fewer side effects than conventional medicine during pregnancy (37\\u0026ndash;39). Stratifying by score of the quality assessment of the studies, the prevalence of self-medication was 33.95% (95% CI: 27.72\\u0026ndash;40.80%) in studies with high score. 58.95% (95% CI: 52.03\\u0026ndash;65.53%), and 42.68% (95% CI: 23.28\\u0026ndash;64.63%), in middle and low quality respectively. This can be explained by the fact that high-quality studies have a low risk of bias and therefore the prevalence approaches the pooled prevalence (44.50%). But the low quality studies probably overestimated the prevalence because of the low recruited sample size. For the cohort studies, the prevalence was lower 33.52% (95% CI: 27.68\\u0026ndash;39.91%), and 44.93%(95% CI: 39.14\\u0026ndash;50.86%) for the cross sectional studies this can be explained by the fact that research methodology of the cohort studies are very rigorous with a best evidence (40). In recent years, several initiatives and interventions, such as improving the knowledge of pregnant women about the consequences of self-medication, as well as the provision of brochures and catalogs, have been planned and implemented, which could be very effective in combating this practice. In addition, the continuous training of health professionals on the prescription of drugs and the advice given when dispensing drugs to pregnant women could reduce the prevalence of self-medication. Despite the efforts made by countries to reduce self-medication among pregnant women, this practice is still on the rise, it is, therefore, urgent to adopt new and more effective prevention measures.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eStrengths and limitations of the study\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe strengths of our study are the large sample size, sample size analysis, and subgroup analysis. All these analyses reflect the methodological rigor of our systematic review and meta-analysis. On the other hand, the included articles provide large and profound information on various aspects of self-medication in pregnant women (prevalence, groups of drugs most used by pregnant women, groups of diseases most often treated by self-medication, and the most common reasons for self-medication) that can be used by health professionals to make decisions and organize effective interventions to prevent self-medication in pregnant women.\\u003c/p\\u003e \\u003cp\\u003eThe limitation of this study was the fact that we included only articles in English and French, while we excluded some studies of Spanish and Farsi languages after exploiting their abstracts if only it reports the prevalence of self-medication. Another limitation of the present study was the high possibility of publication bias and heterogeneity in the results, which could be due to methodological differences in the different studies. In addition, the quality of the included studies was different and the inclusion of some studies of poor quality may affect the final estimate.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThe results obtained from this study showed that the prevalence of self-medication among pregnant women is relatively high. This requires effective measures and interventions to reduce self-medication. We recommend that health professionals consider implementing programs on the risks of self-medication, and strengthening the control and monitoring of over-the-counter sales of drugs. Physicians and pharmacists should also be made more sensitive to prescribing the appropriate medication and avoiding the provision of medication without a prescription\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAvailability of Data and Materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data generated or analyzed during this study are included in the article\\u003cstrong\\u003e.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNone\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor Contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAB, LL conceived of the study and compiled the data used in analyses and conducted analyses, and drafted the manuscript. FA, SB, YK assisted within perpetration of the data and provided feedback for this manuscript, RR, RA supervised the findings of this work. All\\u003c/p\\u003e\\n\\u003cp\\u003eauthors read and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgment\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors would like all the researchers whose works were used in the present study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; information (optional)\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eWHO_EDM_QSM_00.1_eng.pdf [Internet]. [cit\\u0026eacute; 25 sept 2022]. Disponible sur: https://apps.who.int/iris/bitstream/handle/10665/66154/WHO_EDM_QSM_00.1_eng.pdf?sequence=1\\u0026amp;isAllowed=y\\u003c/li\\u003e\\n\\u003cli\\u003eSah AK, Giri A, Palikhey A, Chaurasiya RK, Yadav SK. Self-medication among pregnant women attending antenatal clinic at Tertiary Care Center of Nepal. Janaki Medical College Journal of Medical Science. 2020;8(2):5‑10.\\u003c/li\\u003e\\n\\u003cli\\u003eOcan M, Obuku EA, Bwanga F, Akena D, Richard S, Ogwal-Okeng J, et al. Household antimicrobial self-medication: a systematic review and meta-analysis of the burden, risk factors and outcomes in developing countries. BMC Public Health. 1 ao\\u0026ucirc;t 2015;15:742.\\u003c/li\\u003e\\n\\u003cli\\u003eHong SH, Spadaro D, West D, Tak SH. Patient valuation of pharmacist services for self care with OTC medications. J Clin Pharm Ther. juin 2005;30(3):193‑9.\\u003c/li\\u003e\\n\\u003cli\\u003eSingh I, Bard I, Jackson J. Robust Resilience and Substantial Interest: A Survey of Pharmacological Cognitive Enhancement among University Students in the UK and Ireland. PLoS One. 30 oct 2014;9(10):e105969. \\u003c/li\\u003e\\n\\u003cli\\u003eCourrier D, Villier C, Jourdan S, Hoffmann P. Autom\\u0026eacute;dication et grossesse : enqu\\u0026ecirc;te aupr\\u0026egrave;s de 740 femmes enceintes dans le r\\u0026eacute;seau p\\u0026eacute;rinatal Alpes-Is\\u0026egrave;re. La Revue Sage-Femme. sept 2015;14(4):131‑41.\\u003c/li\\u003e\\n\\u003cli\\u003eAyalew MB. Self-medication practice in Ethiopia: a systematic review. Patient Prefer Adherence. 1 mars 2017;11:401‑13.\\u003c/li\\u003e\\n\\u003cli\\u003eLoebstein R, Lalkin A, Koren G. Pharmacokinetic changes during pregnancy and their clinical relevance. Clin Pharmacokinet. nov 1997;33(5):328‑43.\\u003c/li\\u003e\\n\\u003cli\\u003eDawes M, Chowienczyk PJ. Drugs in pregnancy. Pharmacokinetics in pregnancy. Best Pract Res Clin Obstet Gynaecol. d\\u0026eacute;c 2001;15(6):819‑26.\\u003c/li\\u003e\\n\\u003cli\\u003eMartin J. \\u0026copy; Joanna Briggs Institute 2017 Critical Appraisal Checklist for Analytical Cross Sectional Studies. 2017;7.\\u003c/li\\u003e\\n\\u003cli\\u003eChecklist_for_Analytical_Cross_Sectional_Studies (2).pdf.\\u003c/li\\u003e\\n\\u003cli\\u003eChecklist_for_Cohort_Studies.pdf.\\u003c/li\\u003e\\n\\u003cli\\u003eLiberati A, Altman DG, Tetzlaff J, Mulrow C, G\\u0026oslash;tzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 18 ao\\u0026ucirc;t 2009;151(4):W65-94.\\u003c/li\\u003e\\n\\u003cli\\u003eWorld Bank Country and Lending Groups \\u0026ndash; World Bank Data Help Desk [Internet]. [cit\\u0026eacute; 25 f\\u0026eacute;vr 2022]. Disponible sur: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups\\u003c/li\\u003e\\n\\u003cli\\u003eLutz B, Miranda V, Silveira M, Dal Pizzol T, Mengue S, da Silveira M, et al. Medication Use among Pregnant Women from the 2015 Pelotas (Brazil) Birth Cohort Study. International Journal Of Environmental Research And Public Health. 2020;17(3).\\u003c/li\\u003e\\n\\u003cli\\u003ePisa F, Casetta A, Clagnan E, Michelesio E, Brumatti L, Barbone F. Medication use during pregnancy, gestational age and date of delivery: agreement between maternal self-reports and health database information in a cohort. BMC PREGNANCY AND CHILDBIRTH. 2015;15.\\u003c/li\\u003e\\n\\u003cli\\u003eOdalovic M, Kovacevic S, Ilic K, Sabo A, Tasic L. Drug use before and during pregnancy in Serbia. INTERNATIONAL JOURNAL OF CLINICAL PHARMACY. 2012;34(5):719‑27.\\u003c/li\\u003e\\n\\u003cli\\u003eYusuff KB, Omarusehe LD. Determinants of self medication practices among pregnant women in Ibadan, Nigeria. Int J Clin Pharm. 2011;33(5):868‑75.\\u003c/li\\u003e\\n\\u003cli\\u003eAke SF, Yimam GN, Bekele NA. Self-Medication and its Predictors among Pregnant Women in Gedeo Zone, South Ethiopia. 2021;\\u003c/li\\u003e\\n\\u003cli\\u003eBobga TP, Ngwa SB, Ambe NF, Ketum AS, Agbor AN, Kanla WJ, et al. The Prevalence of Auto-Medication among Pregnant Women in a Conflict Affected, North West Region, Cameroon. Journal of Biosciences and Medicines. 2021;9(04):122.\\u003c/li\\u003e\\n\\u003cli\\u003eIbrahim O, Ibrahim R, Al-Tameemi N, Ebaed S, AlMazrouei N, Riley K. Evaluation of the use and attitudes of pregnant and postpartum women towards medicine utilisation during pregnancy in the United Arab Emirates: A national cross-sectional study. International Journal Of Clinical Practice. 2021;75(9).\\u003c/li\\u003e\\n\\u003cli\\u003eNiriayo Y, Mohammed K, Asgedom S, Demoz G, Wahdey S, Gidey K. 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Journal Of Gynecology Obstetrics And Human Reproduction. 2017;46(2):167‑73.\\u003c/li\\u003e\\n\\u003cli\\u003eRahmani A, Hamanajm SA, Fallahi A, Gheshlagh RG, Dalvand S. Prevalence of self-medication among pregnant Women: A systematic review and meta-analysis. Nursing and Midwifery Studies. 10 janv 2019;8(4):169.\\u003c/li\\u003e\\n\\u003cli\\u003eMortazavi SS, Shati M, Khankeh HR, Ahmadi F, Mehravaran S, Malakouti SK. Self-medication among the elderly in Iran: a content analysis study. BMC Geriatrics. 1 sept 2017;17(1):198. \\u003c/li\\u003e\\n\\u003cli\\u003eJim\\u0026eacute;nez E, Bosch F, L\\u0026oacute;pez A, Costa J, Cos R, Ba\\u0026ntilde;os JE. Patterns of regular drug use in Spanish childbearing women: changes elicited by pregnancy. Eur J Clin Pharmacol. oct 1998;54(8):645‑51.\\u003c/li\\u003e\\n\\u003cli\\u003eBehzadifar M, Behzadifar M, Aryankhesal A, Ravaghi H, Baradaran HR, Sajadi HS, et al. 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Journal of Arak University of Medical Sciences. 10 mai 2017;20(2):33‑45.\\u003c/li\\u003e\\n\\u003cli\\u003eBaghianimoghadam MH, Mojahed S, Baghianimoghadam M, Yousefi N, Zolghadr R. Attitude and practice of pregnant women regarding self-medication in Yazd, Iran. Archives of Iranian medicine. 2013;16(10):0‑0. \\u003c/li\\u003e\\n\\u003cli\\u003eMin\\u0026iacute; E, Varas R, Vicu\\u0026ntilde;a Y, L\\u0026eacute;vano M, Rojas L, Medina J, et al. [Self-medication behavior among pregnant women user of the Instituto Nacional Materno Perinatal, Peru 2011]. Rev Peru Med Exp Salud Publica. juin 2012;29(2):212‑7.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Table\",\"content\":\"\\u003cp\\u003eTable 2 is available in the Supplementary Files section.\\u003c/p\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-public-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"pubh\",\"sideBox\":\"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/pubh/default.aspx\",\"title\":\"BMC Public Health\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Systematic Review, Pregnancy, Women’s Health, Self-medication, Pregnant women, Public Health\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-2791845/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-2791845/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground:\\u003c/strong\\u003e Self-medication during pregnancy is of great interest. The use of drugs during pregnancy requires a careful reflection on the benefits to the mother and the risks to the fetus. It is a difficult medical situation for clinicians to select the drug because of the various pharmacokinetic and physiological changes encountered in pregnant women this study aimed to estimate the pooled prevalence of self-medication and associated factors in worldwide pregnant women by a systematic review and a meta-analysis of the published studies on self-medication during pregnancy.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e Searches were carried out at PubMed, Science Direct, Web of Science, and Google Scholar. The quality of the studies and the risk of bias were analyzed using the Joanna Briggs Critical Appraisal Checklist for Analytical Cross-Sectional Studies instrument. The extracted data were tabulated and analyzed qualitatively and quantitatively through meta-analysis.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e The overall prevalence of self-medication among pregnant women was 44.50% (95% CI: 38.92-50.23). The subgroup analysis has shown a difference in the prevalence of self-medication which is influenced by region, Income of countries, and study design. The Heterogeneity, assessed by the statistical test I2 varied from 96% to 99% and was statistically significant. The result of this funnel plot showed that the funnel plot was symmetry with p-value = 0.36, and there is no publication bias.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion:\\u003c/strong\\u003e The results obtained from this study showed that the prevalence of self-medication among pregnant women is relatively high. 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