Review Article Effects of Panax ginseng on Obesity in ...

Hindawi Evidence-Based Complementary and Alternative Medicine Volume 2018, Article ID 2719794, 16 pages https://doi.org/10.1155/2018/2719794

Review Article Effects of Panax ginseng on Obesity in Animal Models: A Systematic Review and Meta-Analysis Hye-Sung Park, Jae-Heung Cho, Koh-Woon Kim Won-Seok Chung , and Mi-Yeon Song

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Department of Korean Rehabilitation Medicine, College of Korean Medicine, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 130-701, Republic of Korea Correspondence should be addressed to Mi-Yeon Song; [email protected] Received 24 November 2017; Accepted 5 February 2018; Published 15 May 2018 Academic Editor: Juntra Karbwang Copyright © 2018 Hye-Sung Park et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. To determine the antiobesity effects of Panax ginseng in animals. Methods. We conducted a systematic search for all controlled trials (up to March 2017) that assessed the antiobesity effects of P. ginseng in animal obesity models in the PubMed, EMBASE, Cochrane library, Web of Science, and Scopus databases. The primary outcome was final body weight measured at the longest follow-up time after administration of the intervention. The secondary outcome was the lipid profile. We assessed methodological quality using the SYRCLE risk of bias tool, and RevMan 5.3 was used to perform a meta-analysis. Finally, a subgroup analysis of parameters including intervention duration, animal models, and type of ginseng was performed. Result. We identified 16 studies that met the inclusion criteria. Data from the meta-analysis indicated that the intervention group had a significantly lower body weight than the control group (SMD: −1.50, 95% CI: −1.90 to −1.11, 𝜒2 : 78.14, 𝑃 < 0.0001, 𝐼2 = 58%). Final body weight was lower in an animal obesity model induced by high-fat diet than in genetic models. Also the intervention group had a significantly higher serum HDL level and lower serum LDL, TG, and TC level than the control group. Conclusion. Our meta-analysis indicated that oral administration of P. ginseng significantly inhibits weight gain and improves serum lipid profiles in animal obesity models. However, causes of obesity and type of ginseng may affect treatment effects.

1. Introduction The worldwide prevalence of obesity has increased significantly in recent decades [1]. Obesity is associated with not only the development of various chronic diseases [2], but also the increased risk of mortality [3]. As a result, obesity is considered a human health priority and a critical health issue requiring both prevention and treatment [4]. The treatment of obesity using conventional medication has numerous limitations, including adverse effects of medication and the potential for drug abuse [5, 6]. Therefore, interest in complementary and alternative therapies for the treatment of obesity has been increasing globally [7, 8]. The Greek word panax means “cure-all” [9]. As its name implies, Panax ginseng has been shown to exert several pharmacological and physiological effects. These include beneficial effects against cancer [10], hypertension [11], diabetes

[12], nociception [13], and stroke [14], as well as reported improvements in chronic fatigue [15]. Furthermore, it has also been reported to exert antiobesity effects [16, 17]. Previous studies have reported various mechanisms for the antiobesity effect of P. ginseng in animal models. These mechanisms include the reduction of the intestinal absorption of dietary fat via inhibition of pancreatic lipase activity [18], regulation of the hypothalamic expression of orexigenic neuropeptide Y and anorexigenic cholecystokinin [19, 20], facilitation of lipoprotein lipase, and regulation of the PPAR𝛾 signaling pathway [21, 22]. However, the complex relationship between P. ginseng and its antiobesity effects has not yet been established under in vivo conditions. Although P. ginseng and its components have been shown to exert antiobesity effects by modulating physiological lipid metabolism in vivo or via intracellular signaling in numerous preclinical studies [23], the results are far from conclusive.

2 Furthermore, although P. ginseng has been shown to exert antiobesity effects in several animal studies, there have been relatively few studies investigating its effects in human obesity [17, 24, 25]. Systematic reviews and meta-analyses of animal studies can yield useful information for the design of subsequent human clinical studies [26]. Several recent studies [17, 27, 28] have reviewed the antiobesity effect of ginseng, but reported only descriptive outcomes and mechanism of action without quantitatively analyzing the data. Therefore, a systematic review and meta-analysis are required to comprehensively examine the antiobesity effects of ginseng in animal models, which, to the best of our knowledge, has not been reported to date. We therefore conducted a systematic review and meta-analysis to determine the antiobesity effects of P. ginseng in animals.

2. Methods We conducted a systematic review according to the Cochrane method [29] and SYRCLE guideline [30]. The results are reported in accordance with PRISMA guidelines [31]. The protocol for this review was registered on the Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies website (http://www.camarades.info). 2.1. Inclusion Criteria for Studies 2.1.1. Types of Studies. We included controlled comparative studies assessing the effect of P. ginseng in preclinical models of obesity in vivo. Review articles, observational studies, human studies, and in vitro studies were excluded. Studies published in English were included. There were no restrictions on publication date or publication status. 2.1.2. Types of Subjects. Genetic, physiological, epigenetic, and environmental animal models of obesity [32–36] were included in this study. Each model represented at least one of the diverse pathophysiological characteristics of obesity. With consideration to our proposed future clinical trials on adult obesity, neonatal animal models of obesity were excluded due to the existence of potential differences in the underlying mechanisms and the response to a specific treatment between adults and neonates. For the same reason, animal models with other diseases, such as cancer and type I diabetes, were excluded. The comparison groups included sham-controlled animals or animals with preclinically induced obesity without any intervention. 2.1.3. Types of Interventions. The intervention group included animals from studies that investigated the antiobesity effect of P. ginseng. Although numerous variants of gichonseng have many of the same compounds and medicinal properties, we focused on P. ginseng C.A. Meyer (Korean ginseng). Other types of ginseng, such as Panax quinquefolius (American ginseng), Panax japonicas, Panax notoginseng, and Panax trifolius, were excluded. Studies using roots of P. ginseng were included, but those using berries or leaves were excluded. Only oral administrations of ginseng were included, while administration by other routes such as intravenous, intramuscular, and intraperitoneal was excluded. Furthermore,

Evidence-Based Complementary and Alternative Medicine studies using only individual substances extracted from ginseng, such as ginsenosides or compound K, were excluded. The majority of processing or extractions methods routinely used in clinical practice were included, such as white ginseng, red ginseng, fermented red ginseng, black ginseng, water extraction, ethanol extraction, vinegar extraction, powdered, and high-pressure extraction. Other processing or extracting methods not commonly used, such as those employing pectin, enzymes, or carbon dioxide, were excluded. Cointervention studies including coadministration with other compounds, herbs, formula, or nonoral preparations and studies in combination with exercise were excluded to avoid confounding factors. For inclusion in our analysis, P. ginseng must have been administered during or following the induction of experimental obesity. Experiments using P. ginseng without the induction of obesity were excluded, as our objective was to identify preventive or treatment effects for obesity. [37] 2.1.4. Types of Outcome Measurements (1) Primary Outcome. The primary outcome was final body weight (BW) measured at the longest follow-up time after administration of the intervention. (2) Secondary Outcomes. Secondary outcome measures included lipid profiles such as triacylglycerol (TG), total cholesterol (TC), high-density lipoprotein (HDL), and lowdensity lipoprotein (LDL). For inclusion in the meta-analysis, the exact animal numbers in each group, the mean effect size, and the variance of the outcomes were required to have been reported. 2.2. Search Methods for Identification of Studies. We identified studies on the antiobesity effect of P. ginseng in animal models from the following databases in consultation with an experienced medical information-scientist or librarian: PubMed, Embase, Web of Science, Cochrane Library, and Scopus. Searches were performed until March 2017. There was no language restriction. A search strategy for PubMed (Table 1) was developed with guidance [29, 38]. Animal filters validated for PubMed/MEDLINE and Embase were used to enhance the search efficiency with respect to identifying all animal studies [39, 40]. 2.3. Data Collection and Analysis 2.3.1. Study Selection. Two reviewers independently reviewed and determined the eligibility of studies. Disagreements between investigators were resolved by consensus after discussion. Duplicates and nonexperimental studies were removed by screening the titles and abstracts. Reviewers carefully examined the full text of studies where it was unclear whether the studies met the inclusion criteria. Studies were excluded if they involved any unqualified interventions. Study selection is summarized in a PRISMA flow diagram [31] (Figure 1). 2.3.2. Data Extraction and Management. We extracted the following data from selected studies: study characteristics

Evidence-Based Complementary and Alternative Medicine

3

Table 1: PubMed search strategy. History

Search string

#1

obesity [MeSH terms] obes∗ [tiab] OR adipos∗ [tiab] OR body mass index [tiab] OR BMI[tiab] OR Overweight[tiab] OR Body weight[tiab] OR Body size[tiab] OR Body constitution[tiab] OR weight gain[tiab] OR Fat mass[tiab] OR percent fat[tiab] OR Leptin[tiab] OR Grehlin[tiab] OR energy expenditure[tiab] #1 OR #2 panax [MeSH terms] Panax ginseng[tiab] OR ginseng[tiab] OR panax[tiab] OR red ginseng[tiab] OR Korean red ginseng[tiab] OR ginsan[tiab] OR “jen shen”[tiab] OR shinseng[tiab] OR “ren shen”[tiab] OR schinseng[tiab] OR ninjin[tiab] #4 OR #5 “animal experimentation” [MeSH terms] animals filter (Hooijmans et al. [40]) #7 OR #8 #3 AND #6 AND #9

#2 #3 #4 #5

Identification

#6 #7 #8 #9 #10

1041 of records identified through database searching

0 of additional records identified through other sources

Screened

534 of records after duplicates removed

461 of records excluded after abstract screening to clear irrelevant content

73 of full-text articles assessed for eligibility

57 of full-text articles excluded due to not fulfilling inclusion criteria or inadequate reporting data necessary to calculate summary effect measure

Included

Eligibility

534 of records screened

16 of studies included in quantitative synthesis (meta-analysis)

Figure 1: PRISMA flow diagram for study search process.

(study title, journal published, author, and publication date); study population (animal age, gender, strain, and type of obesity model); intervention and comparison (dose and duration of intervention, description of preparation and suspension of P. ginseng, and number of animals); and outcome measures

(final body weight and lipid profiles including TG, TC, LDL, and HDL). Information not available from the manuscript was requested from the first or corresponding author by email. Data were independently assessed and extracted by two

4 reviewers using standardized extraction forms. Extracted data were reviewed by a third researcher, and discrepancies were adjudicated by the arbitrator. 2.3.3. Assessment of Risk of Bias in Included Studies. The methodological quality of individual studies was assessed according to the SYRCLE risk of bias (RoB) tool for animal studies [41]. Two authors independently assessed the risk of bias of the included studies according to SYRCLE RoB tool, which evaluates the following domains with three outcomes (“low risk,” “high risk,” or “unclear risk”): sequence generation (selection bias), baseline characteristics (selection bias), allocation concealment (selection bias), random housing (performance bias), blinding of personnel and outcome assessors (performance and detection bias), random outcome assessment (detection bias), incomplete outcome data (attrition bias), and selective outcome reporting (reporting bias). A third author was consulted to resolve discrepancies related to risk of bias. 2.3.4. Measures of Treatment Effect. As outcomes were measured in diverse species, the standardized mean difference (SMD) was used to measure treatment effect with 95% confidence intervals (CIs). The meta-analysis focused not on precise estimates, but on the direction of the outcome because of the expected heterogeneity in animal study characteristics (e.g., significant variations in species or intervention protocols). 2.3.5. Handling Missing Data. The reviewers attempted to obtain the pertinent information by contacting the first or corresponding authors by email where relevant data were missing. If the required data were not obtained, the study was excluded from the analysis. 2.3.6. Assessment of Heterogeneity. To determine whether the included studies had sufficient homogeneity for metaanalysis, we determined between-study heterogeneity by calculating 𝐼2 inconsistency values. We analyzed the statistical heterogeneity using a 𝜒2 test (𝑃 value < 0.10) and quantified it using 𝐼2 and 𝑇2 statistics. Heterogeneity was regarded as substantial where 𝐼2 > 50%, 𝑇2 > 0, or the 𝑃 value < 0.10. Heterogeneity was defined according to the 𝐼2 range: 0%–40% indicated no important heterogeneity, 40%–60% moderate heterogeneity, 60%–90% substantial heterogeneity, and >90% considerable heterogeneity [42]. 2.3.7. Assessment of Publication Bias. A graphical funnel plot was used to investigate whether publication bias was present in the studies included in the review [43]. 2.3.8. Data Synthesis. A meta-analysis was performed using Review Manager 5.3 software. A random-effects model was used in the analysis because of the expected diversity among animal studies If the number of treatment groups was more than two, control groups were shared and represented more than once in the summary estimates calculation. To avoid this, the number of animals in the control group was adjusted by

Evidence-Based Complementary and Alternative Medicine dividing the total number of control animals by the number of comparisons (N of total/N of treatment group) [44]. 2.3.9. Subgroup Analysis and Investigation of Heterogeneity. Subgroup analysis, including analysis of the intervention duration, animal models, and type of ginseng, was performed.

3. Results 3.1. Description of Studies 3.1.1. Search Results. A flow chart of the study selection process is presented in a PRISMA flow diagram (Figure 1). We identified 1041 publications. After duplicates were removed, 534 studies remained. Based on the inclusion criteria, 461 studies were excluded following the screening of titles and abstracts. The full texts of the remaining 73 publications were reviewed, and 40 that did not meet the inclusion criteria were excluded. As a result, 33 studies that met the inclusion criteria were reviewed. A further 17 studies were excluded for inadequate reporting of data necessary to calculate the summary effect. Finally, 16 studies were included in the meta-analysis, all of which had been published between 2004 and 2016. 3.1.2. Included Studies. Data pertaining to 426 animals from 16 studies were analyzed. The characteristics of the included studies are shown in Table 2. Twelve studies used acquired obesity animal models induced by a high-fat diet (HFD): four were in Sprague-Dawley (SD) rats, three were in C57BL/6J mice, one was in Wistar rats, and four were in Institute for Cancer Research (ICR) mice. For genetic obesity models, three studies used leptin receptor-deficient (db/db) mice and one study used Otsuka Long Evans Tokushima Fatty (OLEFT) rats. Sample size per group ranged from 5 to 10 animals. The duration of administration of P. ginseng ranged from 8 to 14 weeks. Various methods of extraction and processing were described: red ginseng (RG), fermented red ginseng (FRG), white ginseng (WG), black ginseng (BG), ginsam; vinegar extracted (GS, VE), water extracted (WE), high-pressure extracted (PE), and ethanol extracted (EE). 3.1.3. Excluded Studies. Following the full-text manuscript review, 57 studies were excluded for failing to fulfill the inclusion criteria or having inadequate reporting data necessary to calculate the summary effect. 3.2. Risk of Bias in Included Studies. The SYRCLE RoB tool for animal studies [41] was used to assess the risk of bias in the included 16 studies. The risk of bias for each study is summarized in Figure 2. As for most animal studies [60], the studies included in this review contained insufficient reporting of the experimental details. As a result, several studies were judged as having an “unclear risk of bias.” Allocation concealment; blinding of caregivers, investigators, or outcome assessors; and random outcome assessment were incompletely described in most studies. However, baseline characteristics, incomplete outcome data, and selective reporting were factors associated with a low risk of bias. Baseline characteristics, such as sex, age, and initial weight,


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Table 2: Summary of included studies. Study

Chung et al. 2016 [45]

Material (extraction method) (1) RG (WE) (2) WG (WE) (3) AG4 (WE) (4) AG5(WE)

Animal model

Sex

Age (weeks)

Weight (g)

𝑁 per group

C57BL/6N mice with HFD

M

4

12

8

M

5

25-26

5

GS (VE)

Dose or concentration

Duration (weeks)

Outcome

Unknown

8

BW, HDL, TC, TG

8

BW, HDL

8

BW, HDL

Han et al. 2008 db/db mice [46] Hong et al. 2013 db/db mice [47] Jung et al. 2014 SD rat [48] with HFD Jung et al. 2015 SD rat [49] with HFD Kho et al. 2016 SD rat [50] with HFD

M

8

25-26

10

RG (WE)

M

3

78–110

10

(1) WG (PE) (2) WG (WE)

(1) 300 mg/kg (2) 500 mg/kg (1) 100 mg/kg (2) 200 mg/kg (1) 1500 mg/kg (2) 1500 mg/kg

M

Unknown

80–110

8

RG (PE)

1500 mg/kg

M

7

270–280

10

(1) FRG (WE) (2) RG (WE)

Kim et al. 2013 [51]

ICR mice with HFD

F

6

80–110

10

(1)∼(3) FRG (WE) (4) RG (WE)

(1) 250 mg/kg (2) 250 mg/kg (1) 125 mg/kg (2) 250 mg/kg (3) 500 mg/kg (4) 250 mg/kg

Lee et al. 2014 [52]

Aged SD rat with HFD C57BL/6N mice with HFD ICR mice with HFD

M

8

200–250

8

RG (WE)

M

6

12

8

BG (EE)

4

23-24

8

WG (EE)

5

78–110

8

GS (VE)

8

200–250

10

WG (unknown)

100 mg/kg

8

BW, HDL, LDL, TC, TG

4

20–30

10

RG (P)

0.5%

12

BW, TG

4

200–250

10

RG (EE)

13


5

approx. 25

8

WG (EE)

5

18–20

8

(1) GS (VE) (2) WG (EE)

Lee et al. 2013 [53]

Lee et al. 2010 F [54] Lim et al. 2009 OLETF rat M [55] de MirandaWistar rat Unknown Henriques et al. with HFD 2014 [56] Park et al. 2005 db/db mice M [57] C57BL/6J Song et al. 2012 mice with M [23] HFD Yun et al. 2004 ICR mice M [58] with HFD Yun et al. 2007 ICR mice M [59] with HFD

200 mg/kg (1) 1% (2) 3% (3) 5% (1) 0.8% (2) 1.6% (1) 300 mg/kg(/day) (2) 500 mg/kg(/day)

(1) 500 mg/kg (2) 1000 mg/kg (3) 3000 mg/kg (1) 250 mg/kg (2) 500 mg/kg (1) 500 mg/kg (2) 500 mg/kg

14 14 8

BW, HDL, LDL, TC, TG BW, HDL, LDL, TC, TG BW, HDL, LDL, TC, TG

12


8


12

BW, HDL, TC, TG

8 8

8 8

BW, HDL, TC, TG BW, HDL, LDL, TC, TG

BW, HDL, LDL, TC, TG BW, HDL, LDL, TC, TG

FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high pressure extracted, P: powdered, VE: vinegar extracted, AG4: 4-year-old fresh ginseng, AG5: 5-year-old fresh ginseng BW: body weight, HDL: high-density lipoprotein, LDL: low-density lipoprotein, 𝑁: number, and db/db mice: the leptin receptor-deficient mouse. Lepdb /Lepdb mouse, the “diabetic” mouse, ICR mice: Institute for Cancer Research mice, OLEFT rat: Otsuka Long Evans Tokushima Fatty rat, SD rats: Sprague-Dawley rats, HFD: high-fat diet, TC: total cholesterol, and TG: triacylglycerol.

were described and revealed to have no significant difference between the intervention and control groups. Compared with human randomized controlled trials, randomization, concealment of allocation, and blinding of investigators and outcome assessors are not yet standardized in animal studies [60]. 3.3. Effects of Interventions 3.3.1. Primary Outcome: Final Body Weight. The effect of P. ginseng on final BW was evaluated, and 16 studies reported

this outcome. The mean final BW of groups treated with P. ginseng administration was significantly less than that of control groups (SMD = −1.50, 95% CI −1.90 to −1.11; Figure 3). The heterogeneity was determined as moderate (𝜒2 = 78.14, 𝑃 < 0.0001, 𝐼2 = 58%). (1) P. ginseng Processing and Extraction Method. Subgroup analysis according to the type of P. ginseng preparation was performed (Figures 3 and 6(f)). The nine subgroup variables were GS (VE), WG (EE), WG (WE), RG (WE), RG (EE), FRG

Baseline Characteristics (selection bias)

Allocation concealment (selection bias)

Random housing (performance bias)

Blinding (performance bias)

Blinding of participants and personnel (performance bias)

Random outcome assessment (detection bias)

Blinding of outcome assessment (detection bias)

Incomplete outcome data (attrition bias)

Selective reporting (reporting bias)

Other bias


Random sequence generation (selection bias)

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Chung et al. 2016

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Han et al. 2008

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Hong et al. 2013

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Kho et al. 2016

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Kim et al. 2013

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Figure 2: Risk of bias summary for the 16 included studies.

(WE), RG (PE), WG (PE), and VG (EE). Heterogeneity was found to be partially decreased. Furthermore, subgroup analysis for processing and extracting methods for P. ginseng were performed independently (Figures 6(d) and 6(e)), with the former being shown to affect heterogeneity while extraction method did not significantly affect heterogeneity. (2) Animal Obesity Models. Subgroup analysis was performed according to the animal obesity models used in the selected studies (Figures 4 and 6). The subgroup variables included aged SD rats, SD rats, C57BL/6J mice, ICR mice, Wistar rats, db/db mice, and OLEFT rats, and the type of animal obesity model was found to be a factor affecting heterogeneity.

Following subgroup analysis according to animal model, the treatment effect size was found to be significantly higher in acquired obesity animal models induced by HFD (SMD = −1.79, 95% CI −2.23 to −1.34, 𝐼2 = 52%) than in genetic animal obesity models (SMD = −0.55, 95% CI −1.12 to 0.03, 𝐼2 = 35%). Particularly for the db/db mouse genetic model of obesity, no significant treatment effect was observed (SMD = −0.21, 95% CI = −1.80 to −1.04, 𝐼2 = 0%). (3) Duration of P. ginseng Administration. Subgroup analysis was performed according to the duration of treatment with P. ginseng (Figures 5 and 6(c)), grouped by interventions for 8 weeks, or more than 8 weeks. However, no significant

Evidence-Based Complementary and Alternative Medicine Study or Subgroup

Experimental (Ginseng) Total SD Mean

7 Weight

Std. Mean Difference IV, Random, 95% CI

3 3 4 4 4 18

3.2% 3.2% 3.1% 2.9% 2.0% 14.5%

−0.05 [−1.48, 1.38] −0.12 [−1.55, 1.31] −1.68 [−3.14, −0.23] −2.06 [−3.63, −0.50] −3.86 [−6.10, −1.63] −1.40 [−2.61, −0.19]

3.36 3.36 2.8 2.8 2.8

4 4 4 4 4 20

3.3% 3.5% 3.2% 2.5% 2.8% 15.3%

−1.45 [−2.84, −0.06] −0.80 [−2.07, 0.46] −1.49 [−2.89, −0.08] −2.96 [−4.83, −1.08] −2.27 [−3.91, −0.64] −1.61 [−2.29, −0.93]

3.3 3.3 3.3 31.305 16.45

2 2 2 5 10

1.7% 1.4% 2.5% 3.7% 2.7%

−3.59 [−6.14, −1.05] −4.39 [−7.31, −1.47] −1.75 [−3.59, 0.08] −0.95 [−2.10, 0.19] −4.24 [−5.95, −2.53]

21

12.0%

−2.79 [−4.34, −1.23]

Mean

Control SD

5 5 8 8 8 34

46.9 46.9 678.3 678.3 49

6.4086 6.4086 20.7 20.7 2.8

8 8 8 8 8 40

37.01 37.01 49 49 49

8 8 8 10 10

35.86 35.86 35.86 539.69 405.2

Total


1.1.1 GS(VE) 7.6026 46.5 Han et al. 2008 - GS(VE)300 10.5095 45.6 Han et al. 2008 - GS(VE)500 21.5 639.5 Lim et al. 2009 - GS(VE)300 18.6 635.3 Lim et al. 2009 - GS(VE)500 2.2627 38.8 Yun et al. 2007 - GS(VE) Subtotal (95% CI) Heterogeneity: 2 = 1.24; 2 = 11.70, ＞＠ = 4 (P = 0.02); I2 = 66% Test for overall effect: Z = 2.26 (P = 0.02) 1.1.2 WG(EE) 32.45 Lee et al. 2010 - WG(EE) 1.6% 33.08 Lee et al. 2010 - WG(EE)0.8% 43.8 Yun et al. 2004 - WG(EE)250 41.2 Yun et al. 2004 - WG(EE)500 43 Yun et al. 2007 - WG(EE) Subtotal (95% CI) Heterogeneity: 2 = 0.04; 2 = 4.25, ＞＠ = 4 (P = 0.37); I2 Test for overall effect: Z = 4.64 (P < 0.00001) 1.1.3 WG(WE) Chung et al. 2016 - AG4(WE) Chung et al. 2016 - AG5(WE) Chung et al. 2016 - WG(WE) Jung et al. 2014 - WG(WE) de Miranda-Henriques et al. 2014

29.1 29.8 30.95 502.67 350

2.687 4.9215 3.3941 2.2627 2.2627 = 6%

1.32 0.47 2.4 38.5798 6.3

Subtotal (95% CI) Heterogeneity: 2 = 2.11; 2 = 13.56, ＞＠ = 4 (P = 0.009); I2 = 71% Test for overall effect: Z = 3.51 (P < 0.0005) 1.1.4 RG(WE) 2.34 29.96 Chung et al. 2016 - RG(WE) 7.2732 65 Hong et al. 2013 - RG(WE) 100 5.0596 66.9 Hong et al. 2013 - RG(WE) 200 33.2039 405.8 Kho et al. 2016 - RG(WE) 9.23 44.54 Kim et al. 2013 - RG(WE)250 15.86 597.59 Lee et al. 2014 - RG(WE) 6.1 46.72 Park et al. 2005 - RG(P) 0.5% Subtotal (95% CI) Heterogeneity: 2 = 0.81; 2 = 18.09, ＞＠ = 6 (P = 0.006); I2 = 67% Test for overall effect: Z = 2.10 (P = 0.04) 1.1.5 RG(EE) 3.1 44.6 Song et al. 2012 - RG(EE)500 mg/kg 43.7 3 Song et al. 2012 - RG(EE)1000 mg/kg 4.9 42.9 Song et al. 2012 - RG(EE)3000 ＧＡ Subtotal (95% CI) Heterogeneity: 2 = 0.00; 2 = 0.13, ＞＠ = 2 (P = 0.94); I2 = 0% Test for overall effect: Z = 2.75 (P = 0.006) 1.1.6 FRG(WE) 20.2386 393.9 Kho et al. 2016 - FRG(WE) 7.83 42.56 Kim et al. 2013 - FRG(WE)125 5.81 44.31 Kim et al. 2013 - FRG(WE)250 9.48 39.28 Kim et al. 2013 - FRG(WE)500 Subtotal (95% CI) 2 2 2 Heterogeneity:  = 0.00;  = 0.45, ＞＠ = 3 (P = 0.93); I = 0% Test for overall effect: Z = 2.84 (P = 0.005) 1.1.7 RG(PE) Jung et al. 2015 - RG(PE) Subtotal (95% CI) Heterogeneity: Not applicable Test for overall effect: Z = 1.54 (P = 0.12) 1.1.8 WG(PE) Jung et al. 2014 - WG(PE)/1500/14 Subtotal (95% CI) Heterogeneity: Not applicable Test for overall effect: Z = 2.21 (P = 0.03)

44

8 10 10 10 8 8 10 64

35.86 65.9 65.9 421.2 50.2 698.67 50.33

3.3 4.2485 4.2485 13.4164 10.44 29.1 4.6

2 5 5 5 2 8 10 37

2.3% 3.9% 3.9% 3.9% 2.9% 2.4% 4.2% 23.6%

−2.15 [−4.11, −0.18] −0.13 [−1.21, 0.94] 0.20 [−0.88, 1.27] −0.51 [−1.60, 0.59] −0.54 [−2.12, 1.04] −4.08 [−5.98, −2.18] −0.64 [−1.54, 0.26] −0.90 [−1.73, −0.06]

10 10 10 30

47.9 47.9 47.9

2.4 2.4 2.4

3 3 3 9

3.3% 3.2% 3.3% 9.8%

−1.03 [−2.40, 0.35] −1.35 [−2.78, 0.08] −1.02 [−2.40, 0.35] −1.13 [−1.93, −0.32]

10 8 8 8 34

421.2 50.2 50.2 50.2

13.4164 10.44 10.44 10.44

5 2 2 2 11

3.6% 2.9% 2.9% 2.8% 12.1%

−1.40 [−2.62, −0.17] −0.84 [−2.46, 0.78] −0.81 [−2.42, 0.81] −1.03 [−2.68, 0.63] −1.08 [−1.82, −0.33]

514.67

32.3572

8 8

546.94

42.3981

8 8

4.0% 4.0%

−0.81 [−1.84, 0.22] −0.81 [−1.84, 0.22]

490.56

34.3107

10 10

539.69

32.6466

5 5

3.6% 3.6%

−1.37 [−2.58, −0.15] −1.37 [−2.58, −0.15]

8 8 8 24

39.6 39.6 39.6

1.16 1.16 1.16

3 3 3 9

2.1% 1.9% 1.1% 5.1%

−3.19 [−5.32, −1.06] −3.72 [−6.07, −1.37] −5.83 [−9.15, −2.51] −3.87 [−5.29, −2.45]

138

100.0%

−1.50 [−1.90, −1.11]

1.1.9 BG(EE) 1.74 33.92 Lee et al. 2013 - BG(EE)1% 1.28 34.5 Lee et al. 2013 - BG(EE)3% 1.1 32.5 Lee et al. 2013 - BG(EE)5% Subtotal (95% CI) 2 2 2 Heterogeneity:  = 0.00;  = 1.75, ＞＠ = 2 (P = 0.42); I = 0% Test for overall effect: Z = 5.32 (P < 0.00001)

Total (95% CI) 288 Heterogeneity: 2 = 0.75; 2 = 78.14, ＞＠ = 33 (P < 0.0001); I2 = 58% Test for overall effect: Z = 7.42 (P < 0.00001) Test for subgroup differences: 2 = 18.77, ＞＠ = 8 (P = 0.02); I2 = 57.4%

−10

−5

Favours [experimental]

0

5

10

Favours [control]

Figure 3: Forest plot and subgroup analysis comparing body weight between the treatment and control groups according to P. ginseng processing status and extraction method. FRG: fermented red ginseng; RG: red ginseng; BG: black ginseng; GS: ginsam (vinegar extracted ginseng); WG: white ginseng; EE: ethanol extracted; WE: water extracted; PE: high-pressure extracted; P: powdered; VE: vinegar extracted.

8

Evidence-Based Complementary and Alternative Medicine Experimental (Ginseng)

Study or Subgroup

Control Weight

Std. Mean Difference


IV, Random, 95% CI

IV, Random, 95% CI

Mean

SD

Total

Mean

SD

Total

597.59

15.86

8

698.67

29.1

8

2.4%

−4.08 [−5.98, −2.18]

8

2.4%

−4.08 [−5.98, −2.18]

5 5 8 5 5

3.6% 3.7% 4.0% 3.6% 3.9%

−1.37 [−2.58, −0.15] −0.95 [−2.10, 0.19] −0.81 [−1.84, 0.22] −1.40 [−2.62, −0.17] −0.51 [−1.60, 0.59]

28

18.8%

−0.97 [−1.48, −0.46]

2 2 2 2 4 4 4 4 4 4

2.9% 2.9% 2.8% 2.9% 3.3% 3.5% 3.2% 2.5% 2.0% 2.8%

−0.84 [−2.46, 0.78] −0.81 [−2.42, 0.81] −1.03 [−2.68, 0.63] −0.54 [−2.12, 1.04] −1.45 [−2.84, −0.06] −0.80 [−2.07, 0.46] −1.49 [−2.89, −0.08] −2.96 [−4.83, −1.08] −3.86 [−6.10, −1.63] −2.27 [−3.91, −0.64]

32

28.8%

−1.44 [−2.01, −0.87]

2 2 2 2 3 3 3 3 3 3

1.7% 1.4% 2.3% 2.5% 2.1% 1.9% 1.1% 3.3% 3.2% 3.3%

−3.59 [−6.14, −1.05] −4.39 [−7.31, −1.47] −2.15 [−4.11, −0.18] −1.75 [−3.59, 0.08] −3.19 [−5.32, −1.06] −3.72 [−6.07, −1.37] −5.83 [−9.15, −2.51] −1.03 [−2.40, 0.35] −1.35 [−2.78, 0.08] −1.02 [−2.40, 0.35]

26

22.8%

−2.34 [−3.20, −1.48]

10

2.7%

−4.24 [−5.95, −2.53]

10

2.7%

−4.24 [−5.95, −2.53]

3 3 5 5 10

3.2% 3.2% 3.9% 3.9% 4.2%

−0.05 [−1.48, 1.38] −0.12 [−1.55, 1.31] −0.13 [−1.21, 0.94] 0.20 [−0.88, 1.27] −0.64 [−1.54, 0.26]

26

18.4%

−0.21 [−0.71, 0.30]

4 4 8

3.1% 2.9% 6.1%

−1.68 [−3.14, −0.23] −2.06 [−3.63, −0.50] −1.86 [−2.93, −0.79]

138

100.0%

−1.50 [−1.90, −1.11]

1.4.1 Aged SD rat with HFD Lee et al. 2014 - RG(WE) Subtotal (95% CI)

8

Heterogeneity: Not applicable Test for overall effect: Z = 4.21 (P < 0.0001) 1.4.2 SD rats with HFD Jung et al. 2014 - WG(PE)/1500/14 Jung et al. 2014 - WG(WE) Jung et al. 2015 - RG(PE) Kho et al. 2016 - FRG(WE) Kho et al. 2016 - RG(WE)

490.56 502.67 514.67 393.9 405.8

34.3107 38.5798 32.3572 20.2386 33.2039

Subtotal (95% CI)

10 10 8 10 10

539.69 539.69 546.94 421.2 421.2

32.6466 31.305 42.3981 13.4164 13.4164

48

Heterogeneity: 2 = 0.00; 2 = 1.66, ＞＠ = 4 (P = 0.80); I2 = 0% Test for overall effect: Z = 3.75 (P = 0.0002) 1.4.3 ICR mice with HFD Kim et al. 2013 - FRG(WE)125 Kim et al. 2013 - FRG(WE)250 Kim et al. 2013 - FRG(WE)500 Kim et al. 2013 - RG(WE)250 Lee et al. 2010 - WG(EE) 1.6% Lee et al. 2010 - WG(EE)0.8% Yun et al. 2004 - WG(EE)250 Yun et al. 2004 - WG(EE)500 Yun et al. 2007 - GS(VE) Yun et al. 2007 - WG(EE)

42.56 44.31 39.28 44.54 32.45 33.08 43.8 41.2 38.8 43

7.83 5.81 9.48 9.23 2.687 4.9215 3.3941 2.2627 2.2627 2.2627

Subtotal (95% CI)

8 8 8 8 8 8 8 8 8 8

50.2 50.2 50.2 50.2 37.01 37.01 49 49 49 49

10.44 10.44 10.44 10.44 3.36 3.36 2.8 2.8 2.8 2.8

80

Heterogeneity: 2 = 0.19; 2 = 11.57, ＞＠ = 9 (P = 0.24); I2 = 22% Test for overall effect: Z = 4.97 (P < 0.00001) 1.4.4 C57BL/6J mice with HFD Chung et al. 2016 - AG4(WE) Chung et al. 2016 - AG5(WE) Chung et al. 2016 - RG(WE) Chung et al. 2016 - WG(WE) Lee et al. 2013 - BG(EE)1% Lee et al. 2013 - BG(EE)3% Lee et al. 2013 - BG(EE)5% Song et al. 2012 - RG(EE)500 mg/kg Song et al. 2012 - RG(EE)1000 mg/kg Song et al. 2012 - RG(EE)3000 ＧＡ

29.1 29.8 29.96 30.95 33.92 34.5 32.5 44.6 43.7 42.9

1.32 0.47 2.34 2.4 1.74 1.28 1.1 3.1 3 4.9

Subtotal (95% CI) Heterogeneity: 2 = 0.86; 2 = 17.20, ＞＠ = 9 (P = 0.05); I2 = 48% Test for overall effect: Z = 5.35 (P < 0.00001) 1.4.5 Wistar rat with HFD de Miranda-Henriques et al. 2014

350

6.3

Subtotal (95% CI)

8 8 8 8 8 8 8 10 10 10

35.86 35.86 35.86 35.86 39.6 39.6 39.6 47.9 47.9 47.9

3.3 3.3 3.3 3.3 1.16 1.16 1.16 2.4 2.4 2.4

86

10

405.2

16.45

10

Heterogeneity: Not applicable Test for overall effect: Z = 4.87 (P < 0.00001) 1.4.6 db/db mice Han et al. 2008 - GS(VE)300 Han et al. 2008 - GS(VE)500 Hong et al. 2013 - RG(WE) 100 Hong et al. 2013 - RG(WE) 200 Park et al. 2005 - RG(P) 0.5%

46.5 45.6 65 66.9 46.72

7.6026 10.5095 7.2732 5.0596 6.1

Subtotal (95% CI)

5 5 10 10 10

46.9 46.9 65.9 65.9 50.33

6.4086 6.4086 4.2485 4.2485 4.6

40

Heterogeneity: 2 = 0.00; 2 = 1.50, ＞＠ = 4 (P = 0.83); I2 = 0% Test for overall effect: Z = 0.80 (P = 0.42) 1.4.7 OLEFT rat Lim et al. 2009 - GS(VE)300 Lim et al. 2009 - GS(VE)500

639.5 635.3

21.5 18.6

Subtotal (95% CI)

8 8 16

678.3 678.3

20.7 20.7

Heterogeneity: 2 = 0.00; 2 = 0.12, ＞＠ = 1 (P = 0.73); I2 = 0% Test for overall effect: Z = 3.42 (P = 0.0006) Total (95% CI)

288

Heterogeneity: 2 = 0.75; 2 = 78.14, ＞＠ = 33 (P < 0.0001); I2 = 58% Test for overall effect: Z = 7.42 (P < 0.00001) Test for subgroup differences: 2 = 45.65, ＞＠ = 6 (P < 0.00001); I2 = 86.9%

−10

−5


0

5

10

Favours [control]

Figure 4: Forest plot and subgroup analysis comparing body weight between the treatment and control groups according to animal obesity model. FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, VE: vinegar extracted, AG4: 4-year-old fresh ginseng, AG5: 5-year-old fresh ginseng, and db/db mice: the leptin receptor-deficient mouse. Lepdb /Lepdb mouse, the “diabetic” mouse, ICR mice: Institute for Cancer Research mice, OLEFT rat: Otsuka Long Evans Tokushima Fatty rat, SD rats: Sprague-Dawley rats, and HFD: high-fat diet.


Study or Subgroup

Experimental (Ginseng)

9

Control

Weight



IV, Random, 95% CI

IV, Random, 95% CI

Mean

SD

Total

Mean

SD

Total

29.1 29.8 29.96 30.95 46.5 45.6 65 66.9 393.9 405.8 597.59 32.45 33.08 639.5 635.3 350 43.8 41.2 38.8 43

1.32 0.47 2.34 2.4 7.6026 10.5095 7.2732 5.0596 20.2386 33.2039 15.86 2.687 4.9215 21.5 18.6 6.3 3.3941 2.2627 2.2627 2.2627

8 8 8 8 5 5 10 10 10 10 8 8 8 8 8 10 8 8 8 8

35.86 35.86 35.86 35.86 46.9 46.9 65.9 65.9 421.2 421.2 698.67 37.01 37.01 678.3 678.3 405.2 49 49 49 49

3.3 3.3 3.3 3.3 6.4086 6.4086 4.2485 4.2485 13.4164 13.4164 29.1 3.36 3.36 20.7 20.7 16.45 2.8 2.8 2.8 2.8

2 2 2 2 3 3 5 5 5 5 8 4 4 4 4 10 4 4 4 4

1.7% 1.4% 2.3% 2.5% 3.2% 3.2% 3.9% 3.9% 3.6% 3.9% 2.4% 3.3% 3.5% 3.1% 2.9% 2.7% 3.2% 2.5% 2.0% 2.8%

−3.59 [−6.14, −1.05] −4.39 [−7.31, −1.47] −2.15 [−4.11, −0.18] −1.75 [−3.59, 0.08] −0.05 [−1.48, 1.38] −0.12 [−1.55, 1.31] −0.13 [−1.21, 0.94] 0.20 [−0.88, 1.27] −1.40 [−2.62, −0.17] −0.51 [−1.60, 0.59] −4.08 [−5.98, −2.18] −1.45 [−2.84, −0.06] −0.80 [−2.07, 0.46] −1.68 [−3.14, −0.23] −2.06 [−3.63, −0.50] −4.24 [−5.95, −2.53] −1.49 [−2.89, −0.08] −2.96 [−4.83, −1.08] −3.86 [−6.10, −1.63] −2.27 [−3.91, −0.64]

84

58.0%

−1.71 [−2.31, −1.10]

5 5 8 2 2 2 2 3 3 3 10 3 3 3

3.6% 3.7% 4.0% 2.9% 2.9% 2.8% 2.9% 2.1% 1.9% 1.1% 4.2% 3.3% 3.2% 3.3%

−1.37 [−2.58, −0.15] −0.95 [−2.10, 0.19] −0.81 [−1.84, 0.22] −0.84 [−2.46, 0.78] −0.81 [−2.42, 0.81] −1.03 [−2.68, 0.63] −0.54 [−2.12, 1.04] −3.19 [−5.32, −1.06] −3.72 [−6.07, −1.37] −5.83 [−9.15, −2.51] −0.64 [−1.54, 0.26] −1.03 [−2.40, 0.35] −1.35 [−2.78, 0.08] −1.02 [−2.40, 0.35]

Subtotal (95% CI) 124 Heterogeneity: 2 = 0.23; 2 = 18.65, ＞＠ = 13 (P = 0.13); I2 = 30% Test for overall effect: Z = 5.10 (P < 0.00001)

54

42.0%

−1.21 [−1.67, −0.74]

Total (95% CI) 288 Heterogeneity: 2 = 0.75; 2 = 78.14, ＞＠ = 33 (P < 0.0001); I2 = 58% Test for overall effect: Z = 7.42 (P < 0.00001) Test for subgroup differences: 2 = 1.64, ＞＠ = 1 (P = 0.20); I2 = 38.9%

138

100.0%

−1.50 [−1.90, −1.11]

1.2.1 8 wk Chung et al. 2016 - AG4(WE) Chung et al. 2016 - AG5(WE) Chung et al. 2016 - RG(WE) Chung et al. 2016 - WG(WE) Han et al. 2008 - GS(VE)300 Han et al. 2008 - GS(VE)500 Hong et al. 2013 - RG(WE) 100 Hong et al. 2013 - RG(WE) 200 Kho et al. 2016 - FRG(WE) Kho et al. 2016 - RG(WE) Lee et al. 2014 - RG(WE) Lee et al. 2010 - WG(EE) 1.6% Lee et al. 2010 - WG(EE)0.8% Lim et al. 2009 - GS(VE)300 Lim et al. 2009 - GS(VE)500 de Miranda-Henriques et al. 2014 Yun et al. 2004 - WG(EE)250 Yun et al. 2004 - WG(EE)500 Yun et al. 2007 - GS(VE) Yun et al. 2007 - WG(EE)

164 Subtotal (95% CI) Heterogeneity: 2 = 1.22; 2 = 58.71, ＞＠ = 19 (P < 0.00001); I2 = 68% Test for overall effect: Z = 5.54 (P < 0.00001) 1.2.2 above 8 wk Jung et al. 2014 - WG(PE)/1500/14 Jung et al. 2014 - WG(WE) Jung et al. 2015 - RG(PE) Kim et al. 2013 - FRG(WE)125 Kim et al. 2013 - FRG(WE)250 Kim et al. 2013 - FRG(WE)500 Kim et al. 2013 - RG(WE)250 Lee et al. 2013 - BG(EE)1% Lee et al. 2013 - BG(EE)3% Lee et al. 2013 - BG(EE)5% Park et al. 2005 - RG(P) 0.5% Song et al. 2012 - RG(EE)500 mg/kg Song et al. 2012 - RG(EE)1000 mg/kg Song et al. 2012 - RG(EE)3000 ＧＡ

490.56 502.67 514.67 42.56 44.31 39.28 44.54 33.92 34.5 32.5 46.72 44.6 43.7 42.9

34.3107 38.5798 32.3572 7.83 5.81 9.48 9.23 1.74 1.28 1.1 6.1 3.1 3 4.9

10 10 8 8 8 8 8 8 8 8 10 10 10 10

539.69 539.69 546.94 50.2 50.2 50.2 50.2 39.6 39.6 39.6 50.33 47.9 47.9 47.9

32.6466 31.305 42.3981 10.44 10.44 10.44 10.44 1.16 1.16 1.16 4.6 2.4 2.4 2.4

−10

−5


0

5

10

Favours [control]

Figure 5: Forest plot and subgroup analysis comparing body weight between the treatment and control groups according to duration of P. ginseng administration. AG4: 4-year-old ginseng, FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, P: powdered, and VE: vinegar extracted.

difference in effect size was observed between the two groups. 3.3.2. Secondary Outcomes

the experimental groups was significantly lower than that of the control groups (SMD = −3.16, 95% CI = −4.44 to −1.87; 𝑃 < 0.00001), with substantial heterogeneity (𝐼2 = 86%, 𝜒2 = 84.91, 𝑃 < 0.00001) (Figure 8).

(1) HDL. The effect of P. ginseng on HDL was evaluated among the 11 studies that reported this outcome. The mean final HDL in the experimental groups was significantly higher than that in the control groups (SMD = 1.78, 95% CI 1.14 to 2.42), with substantial heterogeneity (𝐼2 = 72%, 𝜒2 = 74.28, 𝑃 < 0.00001) (Figure 7).

(3) TG. The effect of P. ginseng on TG was evaluated among the 13 experiments reported this outcome. The mean TG of the experimental groups was significantly lower than that of the control groups (SMD = −2.00, 95% CI = −2.56 to −1.45; 𝑃 < 0.00001), with substantial heterogeneity (𝐼2 = 68%, 𝜒2 = 74.08, 𝑃 < 0.00001) (Figure 9).

(2) LDL. The effect of P. ginseng on LDL was evaluated among the 8 studies that reported this outcome. The mean LDL of

(4) TC. The effect of P. ginseng on TC was evaluated among the 13 experiments that reported this outcome. The mean TC


Environmental model

Aged SD rat with HFD

0 Gentic model

(a)

(b)

6 Effect size (SMD Final body weight)

Effect size (SMD Final body weight)

2.5 2 1.5 1 0.5 0

5 4 3 2 1 0

8 wk ↑

8 wk

WG

(c)

RG

FRG

BG

GS

(d)

3

6 Effect size (SMD Final body weight)


db/db mice

0.5

OLEFT rat

1

Wistar rat with HFD

1.5

C57BL/6J mice with HFD

2

7 6 5 4 3 2 1 0 ICR mice with HFD



2.5

SD rat with HFD

10

2.5 2 1.5 1 0.5 0

5 4 3 2 1 0

VE

EE

WE

PE

GS WG WG RG RG FRG RG WG BG (VE) (EE) (WE) (WE) (EE) (WE) (PE) (PE) (EE)

(e)

(f)

Figure 6: Estimated effect size of body weight between treatment and control groups stratified by (a) environmental/genetic model, (b) animal obesity model, (c) duration of intervention, (d) ginseng processing method, (e) ginseng extraction method, and (f) type of ginseng. SMD: standard mean difference, wk: week, FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, P: powdered, and VE: vinegar extracted.

of the experimental groups was significantly lower than that of the control groups (SMD = −36.64, 95% CI = −39.96 to −33.31; 𝑃 < 0.00001), with considerable heterogeneity (𝐼2 = 99%, 𝜒2 = 2448.74, 𝑃 < 0.00001) (Figure 10). 3.4. Publication Bias. The risk of publication bias is depicted on a funnel plot (Figure 11). The asymmetry observed in the graph may indicate the presence of publication bias. Studies reporting a negative treatment effect tend not to be published or may be selectively reported. Furthermore, as the funnel plot is based on SMD, the results can be skewed. One characteristic of animal studies is small sample size per group, which could influence the outcomes of included studies as the size of the overall effect can be over- or underestimated.

4. Discussion This review describes the experimental details of P. ginseng administration (including dose, duration, and processing and extraction method) in studies using different species and strains of animals. Variations in these procedures might have contributed to the heterogeneity in treatment outcome observed between the studies. Subgroup analysis was therefore conducted. Effect size was found to vary according to type of ginseng, animal model, and duration of administration. First, the processing method might have influenced the treatment effect. The compositions of active components of ginseng, such as ginsenosides, can differ considerably according to the extraction and processing method. For example, GS, a vinegar extract of P. ginseng, differs from regular white


Study or Subgroup Chung et al. 2016 - AG4(WE) Chung et al. 2016 - AG5(WE) Chung et al. 2016 - RG(WE) Chung et al. 2016 - WG(WE) Han et al. 2008 - GS(VE)300 Han et al. 2008 - GS(VE)500 Jung et al. 2014 - WG(PE)/1500/14 Jung et al. 2014 - WG(WE) Jung et al. 2015 - RG(PE) Kho et al. 2016 - FRG(WE) Kho et al. 2016 - RG(WE) Lee et al. 2014 - RG(WE) Lee et al. 2013 - BG(EE)1% Lee et al. 2013 - BG(EE)3% Lee et al. 2013 - BG(EE)5% Lim et al. 2009 - GS(VE)300 Lim et al. 2009 - GS(VE)500 de Miranda-Henriques et al. 2014 Yun et al. 2004 - WG(EE)250 Yun et al. 2004 - WG(EE)500 Yun et al. 2007 - GS(VE) Yun et al. 2007 - WG(EE)

Experimental Mean

SD

137.8 122.8 115.81 112.21 84.9 95.6 1.55 1.6 1.49 60.5 56 29 104.26 109.12 109.84 31 31 18.8 61 64 70 62

15.98 33.3 19.77 17.56 10.2859 7.6026 0.3795 0.253 0.198 13.914 9.8031 10.1823 6.04 2.08 2.52 2.4 2.4 1.9 5.6569 2.8284 2.8284 2.8284

Total (95% CI)

Control

Total Mean 8 8 8 8 5 5 10 10 8 10 10 8 8 8 8 8 8 10 8 8 8 8

78.99 78.99 78.99 78.99 73.9 73.9 1.46 1.46 1.46 45.2 45.2 22 94.99 94.99 94.99 27.6 26 18.8 39 39 39 39

11

Weight



IV, Random, 95% CI

IV, Random, 95% CI

SD

Total

19.17 19.17 19.17 19.17 16.9741 16.9741 0.2236 0.2236 0.2828 9.1679 9.1679 5.374 3.67 3.67 3.67 2.1 3 3.3 2 2 2 2

2 2 2 2 3 3 5 5 8 5 5 8 3 3 3 4 4 10 4 4 4 4

3.6% 4.8% 4.6% 4.6% 5.2% 4.6% 6.1% 6.0% 6.2% 5.9% 5.9% 6.1% 5.1% 2.8% 3.0% 5.5% 5.3% 6.4% 3.7% 1.6% 1.1% 1.8%

3.24 [0.84, 5.63] 1.24 [−0.46, 2.94] 1.69 [−0.13, 3.51] 1.69 [−0.13, 3.51] 0.74 [−0.78, 2.26] 1.63 [−0.19, 3.44] 0.25 [−0.83, 1.33] 0.54 [−0.56, 1.64] 0.12 [−0.86, 1.10] 1.14 [−0.03, 2.31] 1.06 [−0.10, 2.22] 0.81 [−0.22, 1.85] 1.51 [−0.03, 3.06] 5.12 [2.14, 8.11] 4.82 [1.98, 7.66] 1.36 [−0.01, 2.73] 1.78 [0.30, 3.26] 0.00 [−0.88, 0.88] 4.18 [1.81, 6.55] 8.85 [4.37, 13.33] 10.97 [5.48, 16.46] 8.14 [3.99, 12.29]

93

100.0%

1.78 [1.14, 2.42]

180

Heterogeneity: 2 = 1.46; 2 = 74.28, ＞＠ = 21 (P < 0.00001); I2 = 72% Test for overall effect: Z = 5.45 (P < 0.00001)

−10

−5

0


5

10

Favours [control]

Figure 7: Forest plot comparing serum HDL between the treatment and control groups. AG4: 4-year-old ginseng, FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, P: powdered, and VE: vinegar extracted.

Study or Subgroup Jung et al. 2014 - WG(PE)/1500/14 Jung et al. 2014 - WG(WE) Jung et al. 2015 - RG(PE) Kho et al. 2016 - FRG(WE) Kho et al. 2016 - RG(WE) Lee et al. 2014 - RG(WE) Lim et al. 2009 - GS(VE)300 Lim et al. 2009 - GS(VE)500 de Miranda-Henriques et al. 2014 Yun et al. 2004 - WG(EE)250 Yun et al. 2004 - WG(EE)500 Yun et al. 2007 - GS(VE) Yun et al. 2007 - WG(EE) Total (95% CI)

Control Experimental Mean SD Total Mean SD 1.27 1.57 1.37 22.2 26 153 40.5 46.7 350 128 116 96 124

0.2846 0.253 0.1697 5.3759 5.0596 43.5578 9.1 8.5 6.3 11.3137 11.3137 8.4853 11.3137

10 10 8 10 10 8 8 8 10 8 8 8 8

1.6 0.246 1.6 0.246 4.6 0.3111 30 5.8138 30 5.8138 320 113.4199 50.8 12.02 50.8 12.2 405.2 16.45 233 10 233 10 233 10 233 10

114

Weight


5 5 8 5 5 8 4 4 10 4 4 4 4

10.1% 10.3% 4.2% 10.1% 10.2% 10.0% 9.9% 10.1% 9.2% 4.7% 4.2% 2.6% 4.5%

−1.14 [−2.31, 0.04] −0.11 [−1.19, 0.96] −12.19 [−17.15, −7.23] −1.33 [−2.54, −0.12] −0.71 [−1.82, 0.40] −1.84 [−3.06, −0.61] −0.94 [−2.23, 0.34] −0.39 [−1.60, 0.83] −4.24 [−5.95, −2.53] −8.86 [−13.35, −4.37] −9.88 [−14.84, −4.91] −14.10 [−21.09, −7.11] −9.20 [−13.85, −4.55]

70

100.0%

−3.16 [−4.44, −1.87]

Total



−20

−10


0

10

20

Favours [control]

Figure 8: Forest plot comparing serum LDL between the treatment and control groups. AG4: 4-year-old ginseng, FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, P: powdered, and VE: vinegar extracted.

ginseng in ginsenoside concentration and exerts a greater effect on metabolic syndrome [59]. In this study, BG exerted the greatest effect among the interventions on inhibition of weight gain. BG, which is prepared from raw P. ginseng by nine cycles of steaming at 98∘ C for 3 hours followed by drying, exerted a higher biological activity than red ginseng or white ginseng [61]. However, in this review, the extraction method of ginseng did not significantly influence heterogeneity or treatment effect.

Second, the type of animal model of obesity was shown to influence heterogeneity, indicating that P. ginseng has a potential role in preventing weight gain induced by HFD. In contrast, P. ginseng had no significant effect in db/db mice, which are a leptin receptor-deficient model characterized by marked hyperglycemia, hyperphagia, and reduced energy expenditure [34]. In studies using db/db mice, ginseng exerted no significant effect on BW but did modulate plasma glucose level, insulin resistance, plasma adiponectin level,

12


Study or Subgroup

Experimental Control Weight Total SD Total Mean SD Mean

Chung et al. 2016 - AG4(WE) Chung et al. 2016 - AG5(WE) Chung et al. 2016 - RG(WE) Chung et al. 2016 - WG(WE) Han et al. 2008 - GS(VE)300 Han et al. 2008 - GS(VE)500 Jung et al. 2014 - WG(PE)/1500/14 Jung et al. 2014 - WG(WE) Jung et al. 2015 - RG(PE) Kho et al. 2016 - FRG(WE) Kho et al. 2016 - RG(WE) Lee et al. 2014 - RG(WE) Lee et al. 2013 - BG(EE)1% Lee et al. 2013 - BG(EE)3% Lee et al. 2013 - BG(EE)5% Lee et al. 2010 - WG(EE) 1.6% Lee et al. 2010 - WG(EE)0.8% Lim et al. 2009 - GS(VE)300 Lim et al. 2009 - GS(VE)500 de Miranda-Henriques et al. 2014 Park et al. 2005 - RG(P) 0.5% Yun et al. 2004 - WG(EE)250 Yun et al. 2004 - WG(EE)500 Yun et al. 2007 - GS(VE) Yun et al. 2007 - WG(EE)

130.68 131.33 140.57 147.34 109 101 0.68 0.8 0.81 169 180.3 141 72.76 82.08 81.54 96.37 100.98 151.9 101.8 350 124.4 162 153 140 160

6.39 11.93 8.65 17.11 15.4289 16.3233 0.1265 0.1581 0.1414 79.3732 103.0903 37.0524 5.37 3.16 4.76 24.1548 29.4156 57.4 39.7 6.3 7.67 5.6569 5.6569 5.6569 5.6569

8 8 8 8 5 5 10 10 8 10 10 8 8 8 8 8 8 8 8 10 10 8 8 8 8

175.2 175.2 175.2 175.2 132.2 132.2 0.96 0.96 0.96 243.6 243.6 187 95.82 95.82 95.82 150.62 150.62 149.5 149.5 405.2 150.4 181 181 181 181

206

Total (95% CI) 2

2

7.6 7.6 7.6 7.6 47.6314 47.6314 0.2683 0.2683 0.3394 61.4919 61.4919 56.512 8.28 8.28 8.28 25.28 25.28 80.7 80.7 16.45 3.68 6 6 6 6


2 2 2 2 3 3 5 5 8 5 5 8 3 3 3 4 4 4 4 10 10 4 4 4 4

1.6% 2.8% 2.7% 3.9% 4.4% 4.3% 4.9% 5.1% 5.3% 5.1% 5.1% 5.3% 3.2% 3.7% 3.9% 4.3% 4.5% 5.0% 4.9% 4.0% 4.1% 3.7% 2.8% 1.9% 3.5%

−6.14 [−9.92, −2.35] −3.45 [−5.94, −0.97] −3.67 [−6.25, −1.09] −1.55 [−3.33, 0.23] −0.67 [−2.17, 0.84] −0.89 [−2.44, 0.67] −1.45 [−2.68, −0.21] −0.76 [−1.88, 0.36] −0.55 [−1.55, 0.46] −0.94 [−2.09, 0.20] −0.65 [−1.75, 0.46] −0.91 [−1.96, 0.13] −3.44 [−5.67, −1.21] −2.62 [−4.52, −0.71] −2.28 [−4.06, −0.50] −2.04 [−3.61, −0.48] −1.62 [−3.06, −0.18] 0.03 [−1.17, 1.23] −0.80 [−2.06, 0.47] −4.24 [−5.95, −2.53] −4.14 [−5.82, −2.46] −3.04 [−4.95, −1.13] −4.49 [−6.98, −1.99] −6.57 [−9.99, −3.14] −3.36 [−5.40, −1.33]

111

100.0%

−2.00 [−2.56, −1.45]


2

Heterogeneity:  = 1.26;  = 74.08, ＞＠ = 24 (P < 0.00001); I = 68% Test for overall effect: Z = 7.04 (P < 0.00001)

−10

−5


0

5

10

Favours [control]

Figure 9: Forest plot comparing serum TG between the treatment and control groups. AG4: 4-year-old ginseng, FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, P: powdered, and VE: vinegar extracted.

and AMPK activity [46, 47, 57]. Ginseng thus has a significant effect on insulin sensitivity and may exert preventive and treatment effects in type 2 diabetes and hyperglycemia in db/db mice despite the absence of a significant effect on weight loss. However, this outcome is inconsistent with the results of some previous studies [62]. Given that the number of studies included in this analysis was small, the possibility cannot be ruled out that the dosage or duration of ginseng administration of included studies was not large enough to demonstrate a significant treatment effect. The duration of the intervention was also found to be a major cause of heterogeneity. More than half of the studies had an intervention period of 8 weeks. One study with an 11week intervention period showed that the greatest difference in BW between the control group and the experimental group was at 8 weeks [51]. The subgroup analysis was therefore conducted based on an 8-week treatment period. However, no significant difference in treatment effect and heterogeneity was observed. Unexpectedly, the duration of intervention and extraction method did not significantly affect the magnitude of the treatment effect. Unlike meta-analyses of clinical studies, sources of bias and heterogeneity are not independent in meta-analyses of animal studies. Further studies are therefore required to determine the effects of administration period on treatment outcome. Despite being generally considered a major cause of heterogeneity, subgroup analysis according to ginseng dose

was not performed. Several previous studies have reported dose-dependent effects of ginseng [53, 58]. However, studies included in this review used different units of dosage, such as mg/kg (body weight), mg/kg (food intake), % (density), or mg/day. Furthermore, depending on the extraction or processing method, the quantity of active substance can differ even at the same dose [45, 50, 51]. Therefore, the actual administered dose cannot be regarded as equivalent where the same dose is given but processing or extraction method differs. These factors limit the ability to stratify groups based on dose. Therefore, subgroup analysis according to ginseng dose was not performed, despite its importance. To date, various hypotheses have been suggested to explain the mechanisms underlying the antiobesity effects of P. ginseng. Ginseng is reported to affect appetite and the levels of related hormones including leptin, adiponectin, and ghrelin. It also attenuates HFD-induced chronic inflammation of the hypothalamus, improving leptin resistance and reducing the secretion of neuropeptide Y [53, 59]. Furthermore, it is suggested that ginseng inhibits the digestion and absorption of carbohydrate and fat by inhibiting the activity of pancreatic lipase, and reports of reduced blood glucose and increased fecal weight support this hypothesis [18, 53]. Ginseng may also exert an antiadipogenic effect and increase fat oxidation and energy expenditure by regulating PAR-𝛾/C/EBP-𝛼, AMPK, and PPAR-𝛼 [17, 21, 22, 27]. The results of several studies are contradictory, so these proposed mechanisms remain controversial.


13

Study or Subgroup

Control Experimental Weight Mean SD Total Mean SD Total

Chung et al. 2016 - AG4(WE) Chung et al. 2016 - AG5(WE) Chung et al. 2016 - RG(WE) Chung et al. 2016 - WG(WE) Han et al. 2008 - GS(VE)300 Han et al. 2008 - GS(VE)500 Jung et al. 2014 - WG(PE)/1500/14 Jung et al. 2014 - WG(WE) Jung et al. 2015 - RG(PE) Kho et al. 2016 - FRG(WE) Kho et al. 2016 - RG(WE) Lee et al. 2014 - RG(WE) Lee et al. 2013 - BG(EE)1% Lee et al. 2013 - BG(EE)3% Lee et al. 2013 - BG(EE)5% Lee et al. 2010 - WG(EE) 1.6% Lee et al. 2010 - WG(EE)0.8% Lim et al. 2009 - GS(VE)300 Lim et al. 2009 - GS(VE)500 de Miranda-Henriques et al. 2014 Yun et al. 2004 - WG(EE)250 Yun et al. 2004 - WG(EE)500 Yun et al. 2007 - GS(VE) Yun et al. 2007 - WG(EE)

156.72 157.78 29.96 194.09 130.9 133 2.47 2.66 2.45 70.6 80 219 168.15 179.48 181.53 117.56 118.81 98.4 93 350 221 210 193 218

6.02 5.71 2.34 6.36 14.3108 6.261 0.253 0.253 0.198 22.4522 12.9653 61.6597 13.07 14.97 10.11 26.1912 24.4942 6.7 12.9 6.3 8.4853 5.6569 5.6569 5.6569

Total (95% CI)

8 8 8 8 5 5 10 10 8 10 10 8 8 8 8 8 8 8 8 10 8 8 8 8

227.27 227.27 35.86 227.27 121.8 121.8 2.68 2.68 2.68 104.2 104.2 384 197.74 197.74 197.74 135.73 135.73 111.7 111.7 405.2 308 308 308 308

6.59 6.59 3.3 6.59 17.4937 17.4937 0.3354 0.3354 0.4243 25.7148 25.7148 48.3661 8.17 8.17 8.17 21.16 21.16 12.1 12.1 16.45 8 8 8 8

196

Mean Difference

Mean Difference

IV, Random, 95% CI

IV, Random, 95% CI

2 2 2 2 3 3 5 5 8 5 5 8 3 3 3 4 4 4 4 10 4 4 4 4

4.8% 4.8% 7.2% 4.7% 1.6% 2.0% 8.5% 8.5% 8.5% 1.3% 1.6% 0.4% 3.7% 3.4% 4.2% 1.2% 1.3% 3.8% 3.2% 4.4% 4.9% 5.3% 5.3% 5.3%

−70.55 [−80.59, −60.51] −69.49 [−79.44, −59.54] −5.90 [−10.75, −1.05] −33.18 [−43.32, −23.04] 9.10 [−14.34, 32.54] 11.20 [−9.34, 31.74] −0.21 [−0.54, 0.12] −0.02 [−0.35, 0.31] −0.23 [−0.55, 0.09] −33.60 [−60.09, −7.11] −24.20 [−48.13, −0.27] −165.00 [−219.30, −110.70] −29.59 [−42.53, −16.65] −18.26 [−32.16, −4.36] −16.21 [−27.81, −4.61] −18.17 [−45.73, 9.39] −16.92 [−43.72, 9.88] −13.30 [−26.03, −0.57] −18.70 [−33.55, −3.85] −55.20 [−66.12, −44.28] −87.00 [−96.80, −77.20] −98.00 [−106.77, −89.23] −115.00 [−123.77, −106.23] −90.00 [−98.77, −81.23]

101

100.0%

−36.64 [−39.96, −33.31]


−200

−100


0

100

200

Favours [control]

Figure 10: Forest plot comparing serum TC between the treatment and control groups. AG4: 4-year-old ginseng, FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, P: powdered, and VE: vinegar extracted.

0

SE(SMD)

0.5

1

1.5

2

−10 Subgroups GS(VE) WG(EE) WG(WE)

−5

0 SMD RG(WE) RG(EE) FRG(WE)

5

10

RG(PE) WG(PE) BG(EE)

Figure 11: Funnel plot for publication bias FRG: fermented red ginseng, RG: red ginseng, BG: black ginseng, GS: ginsam (vinegar extracted ginseng), WG: white ginseng, EE: ethanol extracted, WE: water extracted, PE: high-pressure extracted, P: powdered, and VE: vinegar extracted.

To our knowledge, this is the first systematic review and meta-analysis of the antiobesity effect of P. ginseng in animal experiments. Our findings indicate that P. ginseng inhibits

weight gain in animal obesity models and that LDL, TG, and TC were significantly lower in ginseng-treated groups than in control groups, while HDL was significantly higher. P. ginseng can therefore be considered to exert a positive effect on improving serum lipid profiles. There were some limitations to our review, however. The total number of studies and the sample size were too small for the results to be considered reliable. Furthermore, there was a risk of publication bias, given that studies reporting negative results tend to remain unpublished, thus contributing to an overestimation of the effect size. The inclusion of articles written only in English might also have caused a language bias. In general, the quality of included studies was low because of the poor reporting, which is a common feature of animal studies. Despite the fact that the risk of bias has been increasingly emphasized in animal studies, reporting experimental details is still very insufficient in most animal studies [60]. This might have had a significant impact on the outcome of the metaanalysis. Further well-designed and well-reported studies on antiobesity effects in animal models are therefore required. Although multiple studies on the antiobesity effects of P. ginseng in animals have been published to date, relatively few clinical trials in humans have been reported and are limited by the absence of placebo, small sample size, and an overly specific study population [17, 24, 25]. Therefore, this systematic analysis of experimental studies was necessary to evaluate feasibility prior to conducting future clinical trials.

14


The information reported in our review may contribute significantly to the information required for transitioning from preclinical studies to clinical trials [26, 63]. Additional studies and the verification of outcomes using longitudinal human studies are therefore required to elucidate the antiobesity effects of ginseng in humans. Before conducting clinical trials, however, an appropriate dosage and treatment period to show a significant treatment effect should be established. These parameters may differ according to the ginseng processing or extraction method, or the cause of obesity, whether innate or acquired.

5. Conclusions (1) P. ginseng administration significantly inhibits weight gain in animal obesity models. (2) The processing method of ginseng may cause differences in the observed antiobesity effects, although there is insufficient evidence that the duration of administration and ginseng extraction method may affect the outcome. (3) The treatment effect was higher in animal obesity models induced by HFD than in genetic db/db models. (4) The administration of P. ginseng may significantly lower the serum TC, TG, and LDL levels but may elevate the serum HDL level. (5) Sample sizes of included studies were generally small, and the risk of bias was generally low as a result of poor reporting. Further well-designed and wellreported studies are therefore needed. (6) Further clinical studies should be conducted to verify the antiobesity effects of ginseng in humans, with consideration given to dose, treatment period, and ginseng processing method during study design.

Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this paper.

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