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. 2021 Jan 9;19(1):26. doi: 10.3390/md19010026

Effectiveness of Chitosan as a Dietary Supplement in Lowering Cholesterol in Murine Models: A Meta-Analysis

Sung-Il Ahn 1, Sangbuem Cho 1, Nag-Jin Choi 1,*
PMCID: PMC7827691  PMID: 33435383

Abstract

This study presents a meta-analysis of studies that investigate the effectiveness of chitosan administration on lifestyle-related disease in murine models. A total of 34 published studies were used to evaluate the effect of chitosan supplementation. The effect sizes for various items after chitosan administration were evaluated using the standardized mean difference. Using Cochran’s Q test, the heterogeneity of effect sizes was assessed, after which a meta-ANOVA and -regression test was conducted to explain the heterogeneity of effect sizes using the mixed-effect model. Publication bias was performed using Egger’s linear regression test. Among the items evaluated, blood triglyceride and HDL-cholesterol showed the highest heterogeneity, respectively. Other than blood HDL-cholesterol, total cholesterol, and triglyceride in feces, most items evaluated showed a negative effect size with high significance in the fixed- and random-effect model (p < 0.0001). In the meta-ANOVA and -regression test, administering chitosan and resistant starch was revealed to be most effective in lowering body weight. In addition, chitosan supplementation proved to be an effective solution for serum TNF-α inhibition. In conclusion, chitosan has been shown to be somewhat useful in improving symptoms of lifestyle-related disease. Although there are some limitations in the results of this meta-analysis due to the limited number of animal experiments conducted, chitosan administration nevertheless shows promise in reducing the risk of cholesterol related metabolic disorder.

Keywords: meta-analysis, chitosan, lifestyle-related disease, cholesterol lowering

1. Introduction

Lifestyle-related diseases, including obesity, hyperlipidemia, atherosclerosis, type II diabetes, and hypertension, are widespread in industrialized countries, and are major threats to cardiovascular health. The syndrome is related to a combination of metabolic disorders, including abdominal obesity, hypertriglyceridemia, high-density lipoprotein (HDL) cholesterol decrease, hypertension, and high blood glucose, which lead to increased cardiovascular morbidity and mortality [1]. Unnatural blood lipid levels such as high levels of total cholesterol (TC) or triglyceride (TG), high low-density lipoprotein (LDL) level, or low HDL-cholesterol level are correlated with heart disease and stroke. Hypertension is one of the harmful risk factors for stroke and is a key factor in heart attacks. Moreover, obesity acts as a significant risk factor for cardiovascular disease and susceptibility to diabetes [2]. Thus, there has been an urgent need for effective methods of controlling these health-related parameters, including food additives.

Chitosan is one of the polymers containing acetyl glucosamine and glucosamine. It may be obtained by hydrolyzing and converting chitin with alkali from crabs, shrimps, insects, mushrooms, and the cell walls of microorganisms. Chitosan manufacture by deacetylation of chitin has been utilized in wastewater treatment and the agricultural sector. As the safety of chitin or chitosan has become increasingly recognized, it has recently-been used in a variety of fields, including medical supplies, food additives, and cosmetics [3,4]. Chitosan is also known among food additives of which the effects include lowering blood or liver cholesterol and triglyceride by combining with lipids [5]. It even shows an anti-inflammatory effect by TNF-α inhibition [6,7,8,9]. Nauss et al. [10] assume that chitosan binds lipid micelle in the small intestine after the ingestion of a fatty meal, while Kanauchi et al. [11] propose a more specific mechanism by which chitosan inhibits fat digestion in the gastrointestinal tract. In the stomach, chitosan is dissolved in acidic gastric juice. In this aqueous phase, it acts as an emulsifier on fat globules. It also mixes with fat to form an emulsion. Once transferred into the intestine, the chitosan in the emulsion turns into an insoluble gel-like form trapped fat, which cannot be decomposed by enzymes such as pancreatin or other intestinal enzymes. As a result, fat excretion in feces is increased (Figure 1). In this connection, [12] have confirmed that in one animal study chitosan administration led to fecal fat excretion approximately 7.5 times higher compared to that of a cellulose-fed group.

Figure 1.

Figure 1

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Schematic representation of cholesterol adsorption of chitosan in gastrointestinal tracts.

Meta-analysis is a method of statistical analysis that combines results from various scientific studies to obtain a quantified synthesis [13]. Meta-analysis increases the power of statistical analysis by pooling the results from multiple available studies. Therefore, this study summarizes the results of various animal experiments and provides integrated technical data for clinical trials so that clinical trials can proceed more accurately.

Studies of lifestyle diseases in murine models suggest that they may be improved by administering chitosan. However, few comprehensive studies have been conducted to date on the effect of chitosan supplementation on improving lifestyle diseases. Accordingly, the objective of the present study was to perform a meta-analysis of the effects of chitosan on factors in lifestyle-related diseases in adults.

2. Results

2.1. Data Set

Table 1 shows the data sets and experimental conditions for the 34 published studies used in the meta-analysis. The publication years of the studies ranged between 1978 and 2020. The animals most frequently used in the data set were rat strains such as Sprague-Dawley and Wistar, experiment duration was distributed between 2.8 and 21 weeks, and experimental diet most used for inducing hyperlipidemia in the data set was a high fat/cholesterol diet. In the case of Liu et al. [14], a high-fructose diet was used to induce hyperlipidemia. Furthermore, in the study of Gallaher et al. [12], blood total cholesterol (TC) was observed in all studies. In addition to total triglyceride (TG), low-density lipoprotein (LDL)- and high-density lipoprotein (HDL)-cholesterol in the blood, TC and TG in the liver, and fecal TC and TG were investigated. The levels of chitosan administered to hyperlipidemia-induced animals ranged from 0.045 to 7.5% of the diet. The chitosan administration period varied between 3 and 21 weeks.

Table 1.

Studies used in the data set and their information for meta-analysis.

Authors Animal
(Strain)		 n Week Experimental Diet Analytical Items 1
Liu et al. (2018) [15] Rat
(Sprague–Dawley)		 8 8 High fat TC *, TG *, LDL-C *, HDL-C *, TNF-α *
Abozaid et al. (2015) [16] Rat
(white Albino)		 10 6 High fat TC *, TG *, LDL-C *, HDL-C *, TNF-α *
Bahijri et al. (2017) [17] Rat
(Wistar)		 10 12 High fat TC *, TG *, LDL-C *, HDL-C *
Chiu et al. (2015) [18] Rat
(Sprague–Dawley)		 8 7 High fat TC *, TG *, TC ‡, TG ‡
Park et al. (2010) [19] Rat
(Sprague–Dawley)		 8 8 High fat TC *, TG *, LDL-C *, HDL-C *, TC †, TG †, TC ‡
Sivakumar et al. (2007) [20] Rat
(Wistar)		 6 8.5 High fat TC *, TG *, LDL-C *, HDL-C *
Sugano et al. (1978) [21] Rat
(Wistar)		 6 2.8 High fat TC *, TG *, TC †, TG †, TC ‡
Tao et al. (2011) [22] Rat
(Sprague–Dawley)		 8 4 High fat TC *, TG *, LDL-C *, HDL-C *
Zacour et al. (1992) [23] Rat
(Wistar)		 6 6 High fat TC *, TG *, TC †, TG †, TC ‡, TG ‡
Yao and Chiang (2006) [24] Hamster 9 8 High fat TC *, TG *, LDL-C *, HDL-C *, TC †, TG †, TC ‡
Moon et al. (2007) [25] Rat
(Sprague–Dawley)		 8 4 High fat TC *, TG *, LDL-C *, HDL-C *, TC †
Chiu et al. (2017) [26] Rat
(Sprague−Dawley)		 8 5 High fat TC *, TG*, HDL-C *, TC ‡, TG ‡
Liu et al. (2015) [14] Rat
(Sprague–Dawley)		 8 21 High fructose TC *, TG *, HDL-C *, TC †, TG †, TC ‡, TG ‡
Ardakani et al. (2009) [27] Rat
(Wistar)		 5 2 High fat TC *, TG *, LDL-C *, HDL-C *
Jung et al. (2016) [28] Rat
(Sprague–Dawley)		 8 6 High fat TC *, TG *, LDL-C *, HDL-C *
Hsieh et al. (2012) [29] Rat
(Sprague–Dawley)		 9.5 10 High fat TC †, TG †, TNF-α *
Han et al. (1999) [30] Mouse
(ICR)		 13 9 High fat TC *, TG, TC †, TG †, body weight
Chiang et al. (2000) [31] Rat
(Sprague–Dawley)		 6 4 Normal diet + cellulose 5% TC *, LDL-C *, HDL-C *, TC †, TG †, TC ‡, TG ‡
Shang et al. (2017) [32] Rat
(Sprague–Dawley)		 8 6 High fat TC *, TG *, LDL-C *, HDL-C *, body weight
Zhang et al. (2011) [33] Rat
(Sprague–Dawley)		 8 4 High fat TC *, TG *, LDL-C *, HDL-C *
van Bennekum et al. (2005) [34] Mouse
(C57BL/6)		 6 3 High fat TC *, TC †
Zhou et al. (2008) [35] Rat
(Sprague–Dawley)		 12 8 High fat TC *, TG *, LDL-C *, HDL-C *, TNF-α *, glucose *
Kumar et al. (2009) [36] Mouse
(C57BL/6)		 6 4 High fat TC *, TG *
Kim et al. (2009) [37] Rat
(Sprague–Dawley)		 5 8 High fat TC *, body weight
Zong et al. (2012) [38] Mouse
(C57BL/6)		 6 6 High fat TC *, TG *, LDL-C *, HDL-C *, body weight,
Liu et al. (2012) [39] Rat
(Sprague–Dawley)		 9 16 High sucrose TC *, TG *, HDL-C *, TNF-α *, glucose *
Zhang et al. (2012) [40] Rat
(Sprague–Dawley)		 8 8 High fat TC *, TG *, LDL-C *, HDL-C *, TC †, TG †
Zhang et al. (2012) [41] Rat
(Sprague–Dawley)		 10 4 High fat TC *, TG *, LDL-C *, HDL-C *
Zhang and Xia (2015) [42] Rat
(Sprague–Dawley)		 8 8 High fat TC *, TG *, LDL-C *, HDL-C *, TC †, TG †, TC ‡, body weight
Si et al. (2017) [43] Rat
(Wistar)		 8 6 High fat TC *, TG *, LDL-C *, HDL-C *, body weight, glucose *
Do et al. (2018) [44] Mouse
(C57BL/6)		 10 12 High fat TC *, TG *, HDL-C *, TC †, TG †, TC ‡, TG ‡, body weight
Wang et al. (2019) [45] Rat
(Sprague–Dawley)		 8 4.2 High fat TC *, TG *, LDL-C *, HDL-C *, TC †, TG †, TC ‡, body weight
Chiu et al. (2020) [46] Rat
(Sprague–Dawley)		 6 8 High fat TC *, TC †, TC ‡, TNF-α *
Wang et al. (2011) [47] Rat
(Wistar)		 8 3 High fat TG *, LDL-C *, HDL-C *
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1 TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TNF-α, tumor necrosis factor-α; *, blood; †, liver; ‡, feces.

2.2. Effect Size and Heterogeneity

The effect sizes of chitosan administration on hyperlipidemia in murine models using fixed and random effect models are listed in Table 2. Most items other than HDL-cholesterol in blood, total cholesterol, and triglyceride in feces showed negative effect size and high significance (p < 0.0001) in both effect models. These results mean that chitosan administration results in decreased levels of TC, TG, and LDL-C in blood, TC and TG in the liver, serum TNF-α and glucose in blood and body weight, and increased levels of blood HDL-C, fecal TC and TG.

Table 2.

Effect size of chitosan administration on hyperlipidemia in murine model.

Items df Fixed Effect Model Random Effect Model Heterogeneity
ES 1 p-Value ES p-Value Q (p-Value) I2 (%) τ2
Total cholesterol (blood) 65 −1.5457 <0.0001 −2.2248 <0.0001 376.43 (<0.0001) 82.7 2.1388
Triglyceride (blood) 63 −0.5852 <0.0001 −1.2366 <0.0001 525.93 (<0.0001) 88.0 2.6610
LDL-cholesterol (blood) 46 −1.6121 <0.0001 −2.5212 <0.0001 294.88 (<0.0001) 84.4 2.5182
HDL-cholesterol (blood) 49 0.1318 0.1363 0.1532 0.5704 431.89 (<0.0001) 88.7 3.0718
Total cholesterol (liver) 30 −2.3101 <0.0001 −3.3734 <0.0001 187.28 (<0.0001) 84.0 3.2403
Triglyceride (liver) 22 −2.1172 <0.0001 −3.2648 <0.0001 172.75 (<0.0001) 87.3 3.8731
Total cholesterol (feces) 22 1.8491 <0.0001 2.6038 <0.0001 113.25 (<0.0001) 80.6 2.2198
Triglyceride (feces) 9 2.0168 <0.0001 2.4130 <0.0001 35.30 (<0.0001) 74.5 1.5050
TNF-α (blood) 12 −1.4885 <0.0001 −1.8355 <0.0001 66.72 (<0.0001) 82.0 1.8174
Body weight 21 −1.5974 <0.0001 −2.4442 <0.0001 162.18 (<0.0001) 87.1 3.1836
Glucose (blood) 12 −0.7512 <0.0001 −0.8958 0.0096 61.64 (<0.0001) 80.5 1.2356
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1 ES: effect size.

2.3. Moderator Analysis

Since heterogeneity analysis in this study revealed a high level of heterogeneity between the studies analyzed, moderator analysis was performed to account for this. For this, meta-ANOVA and meta-regression were conducted. To perform the meta-ANOVA test, Q statistics between the subgroups (Qb) calculated under assessing that between subgroups (τ2) was the same. First of all, a meta-ANOVA analysis was performed on most items except fecal TG, as shown in Table 3 and Table 4. Chitosan and resistant starch (CTS + RS) showed the highest effect size in blood TC and TG, body weight, blood glucose and blood HDL-C, CTS showed the largest effect size in blood LDL-C and TNF-α, and the cholestyramine (CSR) and water-soluble chitosan (WSC) showed the greatest effect size in liver TC and liver TG, respectively (Table 3). However, none of these items were statistically significant (p < 0.05). Table 4 shows the results of meta-ANOVA in analyzing the effect of chitosans administration period on biological indices (p > 0.05). Other than fecal TC, body weight, and blood glucose, most items showed significant differences (p < 0.05). In the case of TC, the Q statistics between the groups (Qb) was 31.94 (df = 13, p = 0.0025); the effect size between groups was assumed to be significantly different.

Table 3.

Meta-ANOVA analysis of effect of chitosan type on biological indices.

Biological Index 1 Analysis Item 2 K 3 Fixed Effect Model Random Effect Model Q 6 τ2 7 I2 8 Qb 9 df 10 p
SMD 4 95%-CI 5 SMD 95%-CI
Lower Upper Lower Upper
TC (blood) CTS 42 −1.5720 −1.7639 −1.3801 −2.0640 −2.5645 −1.5635 194.29 2.2266 78.9 12.60 7 0.0826
WSC 17 −1.5434 −1.9066 −1.1801 −2.7620 −3.6088 −1.9153 145.47 2.2266 89.0
RS 2 −1.7624 −2.6836 −0.8412 −2.3197 −4.6315 −0.0080 6.88 2.2266 85.5
CE 1 −2.1859 −3.7413 −0.6305 −2.1859 −5.4984 1.1266 0.00 -11 -
CTS + RS 1 −8.9998 −12.7228 −5.2769 −8.9998 −13.7341 −4.2655 0.00 - -
WSC + RS 1 −1.4835 −4.6243 1.6572 −1.4835 −4.6243 1.6572 0.00 - -
CTS + VitC 1 0.2823 −0.7041 1.2688 0.2823 −2.8042 3.3688 0.00 - -
CSR 1 −1.9182 −3.3870 −0.4494 −1.9182 −5.1910 1.3545 0.00 - -
TG (blood) CTS 39 −0.4142 −0.6035 −0.2249 −1.0874 −1.6614 −0.5135 378.70 2.8583 90.0 5.50 6 0.4819
WSC 17 −1.1778 −1.4773 −0.8782 −1.9030 −2.7835 −1.0224 86.48 2.8583 81.5
RS 2 −0.8491 −1.6483 −0.0499 −1.1971 −3.6866 1.2924 7.64 2.8583 86.9
CE 1 1.1106 0.0996 2.1216 1.1106 −2.3538 4.5750 0.00 - -
CTS + RS 1 −3.4066 −5.0825 −1.7307 −3.4066 −7.1199 0.3067 0.00 - -
WSC + RS 1 −1.4338 −2.5685 −0.2990 −1.4338 −4.9363 2.0688 0.00 - -
CTS + VitC 1 −0.8606 −1.8990 0.1778 −0.8606 −4.3331 2.6119 0.00 - -
LDL-C
(blood)		 CTS 28 −2.1800 −2.4471 −1.9129 −2.8041 −3.4238 −2.1843 100.39 1.9848 73.1 6.27 3 0.0990
WSC 13 −1.6760 −2.0564 −1.2956 −2.8831 −3.8113 −1.9550 100.21 1.9848 88.0
RS 2 −0.2492 −0.9457 0.4474 −0.2492 −2.3222 1.8238 0.00 1.9848 0.0
CTS + RS 2 −1.6799 −2.5327 −0.8270 −1.7721 −3.9089 0.3647 1.49 1.9848 32.9
HDL-C
(blood)		 CTS 36 0.1332 −0.0704 0.3368 0.3816 −0.2696 1.0329 315.19 3.3880 88.9 3.63 4 0.4585
WSC 10 −0.0158 −0.4449 0.4132 −0.7968 −2.0465 0.4528 107.00 3.3880 91.6
RS 2 −0.1120 −0.8081 0.5842 −0.1134 −2.7577 2.5308 0.34 3.3880 0.0
CTS + RS 1 1.9999 0.7360 3.2638 1.9999 −1.8227 5.8225 0.00 - -
WSC + RS 1 0.2293 −0.7549 1.2135 0.2293 −3.5102 3.9688 0.00 - -
TC
(liver)		 CTS 26 −2.5523 −2.8603 −2.2442 −3.6571 −4.4528 −2.8614 157.12 3.2800 84.1 4.50 3 0.2122
WSC 3 −1.0529 −1.7573 −0.3485 −1.5068 −3.6972 0.6837 11.05 3.2800 81.9
CE 1 −1.5873 −2.9588 −0.2158 −1.5873 −5.3927 2.2181 0.00 - -
CSR 1 −4.7470 −7.3259 −2.1682 −4.7470 −9.1346 −0.3595 0.00 - -
TG
(liver)		 CTS 19 −1.9028 −2.2234 −1.5823 −3.0600 −4.0045 −2.1154 153.33 3.5904 88.3 0.91 1 0.3410
WSC 4 −3.9955 −4.9445 −3.0466 −4.1792 −6.2803 −2.0781 2.65 3.5904 0.0
TC
(feces)		 CTS 20 1.8847 1.5660 2.2034 2.6479 1.8759 3.4200 97.07 2.3783 80.4 0.04 1 0.8341
WSC 3 1.6188 0.8072 2.4304 2.4194 0.4258 4.4131 15.82 2.3783 87.4
Body weight CTS 11 −2.4795 −2.9132 −2.0458 −3.4586 −4.5418 −2.3755 78.81 2.5667 87.3 18.75 4 0.0009
WSC 7 −0.5100 −0.9616 −0.0584 −0.5950 −1.8669 0.6769 22.98 2.5667 73.9
RS 2 −1.7624 −2.6836 −0.8412 −2.3356 −4.7858 0.1147 6.88 2.5667 85.5
CTS + RS 1 −8.9998 −12.7228 −5.2769 −8.9998 −13.8702 −4.1295 0.00 - -
WSC + RS 1 −1.4835 −2.6285 −0.3386 −1.4835 −4.8258 1.8588 0.00 - -
TNF-α CTS 12 −1.6953 −2.0508 −1.3398 −2.0430 −2.8184 −1.2676 49.88 1.4116 77.9 19.84 3 0.0002
WSC 1 0.9843 −0.2451 2.2137 0.9843 −1.6489 3.6175 0.00 - -
Glucose
(blood)		 CTS 10 −0.7573 −1.0898 −0.4247 −0.9044 −1.6869 −0.1218 48.68 1.2809 81.5 2.49 3 0.4765
RS 1 −1.6688 −2.8537 −0.4840 −1.6688 −4.1837 0.8460 0.00 - -
CTS + RS 1 −1.7693 −2.9772 −0.5615 −1.7693 −4.2951 0.7564 0.00 - -
CTS + VitC 1 0.7144 −0.3062 1.7350 0.7144 −1.7274 3.1562 0.00 - -
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1 TC, total cholesterol; TG, triglyceride, LDL-C, low-density lipoprotein; HDL-C, high-density lipoprotein, TNF-α; Tumor necrosis factor alpha; 2 CTS, chitosan; WSC, water-soluble chitosan; RS, resistant starch; CE, cellulose; CTS + RS, chitosan and resistant starch; WSC + RS, water-soluble chitosan and resistant starch; CTS + VitC, chitosan and vitamin C; CSR, cholestyramine; 3 k: number of treatments; 4 SMD: standardized mean difference; 5 CI: confidence interval; 6 Q: chi-squared statistic; 7 τ2: true heterogeneity; 8 I2: Higgin’s I2 statistic; 9 Qb: Q statistics between groups; 10 df: degrees of freedom of Q statistic; 11 –: no data.

Table 4.

Meta-ANOVA analysis of effect of chitosans administration period on biological indices.

Item 1 Administration Period (Week) K 2 Fixed Effect Model Random Effect Model Q 5 τ2 6 I2 7 Qb 8 Df 9 p
SMD 3 95%-CI 4 SMD 95%-CI
Lower Upper Lower Upper
TC (blood) 2 1 −2.4519 −4.3072 −0.5966 −2.4519 −5.6070 0.7668 0.00 -10 - 31.94 13 0.0025
2.8 1 −5.4530 −8.3456 −2.5605 −5.4530 −9.3626 −1.5435 0.00 - -
3 3 −1.7388 −2.5626 −0.9149 −1.7849 3.5161 −0.0536 0.84 1.8009 0.0
4 15 −2.4145 −2.7809 −2.0482 3.0386 −3.8429 −2.2343 58.25 1.8009 76.0
4.2 4 −1.4345 −2.0713 −0.7978 −2.1531 −3.6612 −0.6451 19.86 1.8009 84.9
5 1 −2.1630 −3.4689 −0.8570 −2.1630 −5.0996 0.7736 0.00 - -
6 13 −0.8035 −1.1424 −0.4645 −1.3554 −2.1863 −0.5246 73.20 1.8009 83.6
7 3 0.1396 −0.4290 0.7082 0.1408 −1.4807 1.7624 0.48 1.8009 0.0
8 13 −1.9919 −2.3823 −1.6016 −2.4673 −3.3262 −1.6083 45.48 1.8009 73.6
8.5 1 −2.6715 −4.3982 −0.9449 −2.6715 −5.8178 0.4748 0.00 - -
9 3 −3.9353 −4.8325 −3.0381 −5.3277 −7.2274 −3.4280 26.07 1.8009 92.3
12 4 −1.1933 −1.8028 −0.5839 −1.8238 −3.3133 −0.3343 31.08 1.8009 90.3
16 3 −1.1877 −1.7836 −0.5919 −1.2240 −2.8565 0.4085 1.48 1.8009 0.0
21 1 −1.2794 −2.3845 −0.1744 −1.2794 −4.1324 1.5735 0.00 - -
TG (blood) 2 1 −1.7652 −3.3540 −0.1764 −1.7652 −4.6864 1.1560 0.00 - - 96.55 13 <0.0001
2.8 1 1.5689 0.2025 2.9353 1.5689 −1.2375 4.3754 0.00 - -
3 2 −1.1789 −1.9477 −0.4101 −1.1794 −3.0756 0.7168 0.01 1.5643 0.0
4 15 −0.6150 −0.9114 −0.3186 −1.1423 −1.8601 −0.4246 115.66 1.5643 87.9
4.2 4 −3.0564 −3.8949 −2.2179 −3.6529 −5.1879 −2.1179 12.50 1.5643 76.0
5 1 −0.5418 −1.5454 0.4617 −0.5418 −3.1906 2.1070 0.00 - -
6 13 −0.9085 −1.2282 −0.5889 −1.0837 −1.8397 −0.3276 38.28 1.5643 68.6
7 3 1.1330 0.5098 1.7563 1.1336 −0.4129 2.6800 0.02 1.5643 0.0
8 10 −0.8028 −1.1722 −0.4333 −1.3193 −2.1969 −0.4417 68.52 1.5643 86.9
8.5 1 −2.5453 −4.2258 −0.8647 −2.5453 −5.5173 0.4268 0.00 - -
9 3 −9.3202 −10.9958 −7.6445 −9.5824 −11.8082 −7.3566 4.23 1.5643 52.7
12 3 −1.6964 −2.3414 −1.0515 −2.0228 −3.5934 −0.4521 10.45 1.5643 80.9
16 4 1.3087 0.7842 1.8333 1.3374 0.0031 2.6716 1.33 1.5643 0.0
21 1 1.3630 0.2421 2.4838 1.3630 −1.3324 4.0584 0.00 - -
LDL-C
(blood)		 2 1 −1.7162 −3.2878 −0.1445 −1.7162 −4.3664 0.9341 0.00 - - 59.48 7 <0.0001
3 2 −0.2574 −0.9554 0.4407 −0.2590 −1.9216 1.4036 0.18 1.1854 0.0
4 15 −2.2993 −2.6446 −1.9539 −2.5700 −3.2315 −1.9085 33.05 1.1854 57.6
4.2 4 −11.5502 −13.9253 −9.1751 −11.6010 −14.2147 −8.9872 1.53 1.1854 0.0
6 11 −1.4658 −1.8446 −1.0870 −1.7983 −2.5618 −1.0348 32.11 1.1854 68.9
8 10 −1.7590 −2.1810 −1.3371 −2.5968 −3.4802 −1.7134 60.61 1.1854 85.2
8.5 1 −5.2140 −7.9995 −2.4285 −5.2140 −8.7229 −1.7050 0.00 - -
12 1 −2.6102 −3.8684 −1.3520 −2.6102 −5.0875 −0.1329 0.00 - -
HDL-C
(blood)		 2 1 1.0239 −0.3431 2.3910 1.0239 −2.2340 4.2819 0.00 - - 69.79 10 <0.0001
3 2 0.5630 −0.6456 1.7715 0.5824 −1.8350 2.9998 0.18 2.2766 0.0
4 13 −2.0684 −2.4694 −1.6673 −2.9457 −3.883.7 −2.0077 106.17 2.2766 88.7
4.2 4 0.0038 −0.4905 0.4981 0.0015 −1.5576 1.5606 1.69 2.2766 0.0
5 1 0.4126 −0.5811 1.4064 0.4126 −2.7071 3.5324 0.00 - -
6 13 0.5061 0.1888 0.8233 0.9245 0.0276 1.8213 63.04 2.2766 81.0
8 8 1.3101 0.9108 1.7093 1.5747 0.4469 2.7025 21.96 2.2766 68.1
8.5 1 5.6757 2.6829 8.6686 5.6757 1.4683 9.8832 0.00 - -
12 3 0.2234 −0.6859 1.1328 4.0812 1.8229 6.3396 66.29 2.2766 97.0
16 3 0.4824 −0.1859 1.1506 0.4850 −1.3486 2.3185 0.14 2.2766 0.0
21 1 0.6661 −0.3493 1.6815 0.6661 −2.4607 3.7928 0.00 - -
TC
(liver)		 2.8 1 −9.3712 −14.0837 −4.6586 −9.3712 −14.5605 −4.1818 0.00 - - 62.17 9 <0.0001
3 3 −2.2552 −3.2123 −1.2980 −2.5488 −4.1731 −0.9244 4.50 1.2291 55.6
4 4 −1.1782 −1.8149 −0.5415 −1.6315 −2.9484 −0.3146 11.98 1.2291 75.0
4.2 4 −1.4115 −2.0064 −0.8165 −1.6940 −2.9526 −0.4353 9.42 1.2291 68.1
6 1 −1.6407 −3.0270 −0.2543 −1.6407 −4.2182 0.9368 0.00 - -
8 10 −2.4940 −2.9903 −1.9978 −2.9111 −3.7901 −2.0320 32.45 1.2291 72.3
9 3 −9.3634 −11.0438 −7.6830 −9.5728 −11.6968 −7.4488 3.86 1.2291 48.2
10 2 −2.7055 −3.6429 −1.7681 −2.7400 −4.5432 −0.9368 0.52 1.2291 0.0
12 2 −6.7401 −8.5025 −4.9776 −6.7503 −9.0902 −4.4104 0.11 1.2291 0.0
21 1 −3.0412 −4.6012 −1.4813 −3.0412 −5.7161 −0.3664 0.00 - -
TG
(liver)		 2.8 1 −5.1384 −7.8902 −2.3866 −5.1384 −9.5841 −0.6927 0.00 - - 18.28 8 0.0192
4 2 0.6597 −0.1879 1.5072 0.7060 −1.9059 3.3180 1.18 3.1738 15.0
4.2 4 −2.8029 −3.5742 −2.0316 −3.1371 −5.0651 −1.2092 6.82 3.1738 56.0
6 1 −3.2107 −5.1438 −1.2775 −3.2107 −7.2018 0.7804 0.00 - -
8 7 −2.5754 −3.2000 −1.9508 −4.0563 −5.5980 −2.5146 47.21 3.1738 87.3
9 3 −3.3928 −4.2013 −2.5842 −4.7613 −7.0104 −2.5123 24.84 3.1738 91.9
10 2 −0.9960 −1.6800 −0.3120 −0.9970 −3.5590 1.5650 0.03 3.1738 0.0
12 2 −5.0743 −6.5083 −3.6403 −5.6019 −8.5208 −2.6830 4.14 3.1738 75.8
21 1 −1.8937 −3.1313 −0.6562 −1.8937 −5.5982 1.8108 0.00 - -
TC
(feces)		 2.8 1 5.3232 2.4889 8.1575 5.3232 1.3385 9.3079 0.00 - - 10.86 8 0.2098
4 2 0.5976 −0.2454 1.4405 0.6403 −1.5136 2.7943 1.26 2.0420 20.6
4.2 4 1.6887 0.9671 2.4103 3.0580 1.3721 4.7439 30.95 2.0420 90.3
5 1 1.0557 −0.0110 2.1224 1.0557 −1.9414 4.0527 0.00 - -
6 1 1.7250 0.3145 3.1356 1.7250 −1.4109 4.8609 0.00 - -
7 3 3.0554 2.1511 3.9596 3.0669 1.2132 4.9206 0.18 2.0420 0.0
8 8 1.5481 1.0714 2.0247 2.2101 1.0727 3.3475 33.38 2.0420 79.0
12 2 4.1314 2.9406 5.3221 4.1879 1.8709 6.5048 0.59 2.0420 0.0
21 1 5.0436 2.8049 7.2823 5.0436 1.4581 8.6292 0.00 - -
TG (feces) 4 2 2.0809 1.0028 3.1590 2.0809 1.0028 3.1590 0.17 0.0000 0.0 34.97 5 <0.0001
5 1 0.1343 −0.8472 1.1157 0.1343 −0.8472 1.1157 0.00 - -
6 1 2.3328 0.7274 3.9382 2.3328 0.7274 3.9382 0.00 - -
7 3 1.9419 1.2198 2.6640 1.9419 1.2198 2.6640 0.16 0.0000 0.0
12 2 5.2475 3.8224 6.6726 5.2475 3.8224 6.6726 0.00 0.0000 0.0
21 1 2.7213 1.2585 4.1841 2.7213 1.2585 4.1841 0.00 - -
Body weight 4.2 4 −1.7969 −2.4141 −1.1796 −1.8690 −3.7561 −0.0360 3.13 3.1917 4.1 8.74 4 0.0679
6 9 −0.9479 −1.3802 −0.5155 −1.8184 −3.1069 −0.5299 56.45 3.1917 85.8
8 3 −1.4852 −2.2513 −0.7191 −1.8393 −4.0223 0.3436 9.29 3.1917 78.5
9 3 −3.9353 −4.8325 −3.0381 −5.6255 −7.9722 −3.2789 26.07 3.1917 92.3
12 3 −1.7793 −2.6526 −0.9059 −2.8871 −5.1625 −0.6117 31.84 3.1917 93.7
TNF-α 6 1 −8.0454 −10.9625 −5.1282 −8.0454 −11.4788 −4.6119 0.00 - - 19.84 3 0.0002
8 7 −1.0126 −1.4568 −0.5683 −1.0557 −1.8732 −0.2382 27.60 0.8535 78.3
10 2 −3.4666 −4.5486 −2.3845 −3.4672 −5.1437 −1.7908 0.01 0.8535 0.0
16 3 −1.4696 −2.0976 −0.8416 −1.5301 −2.7528 −0.3075 2.46 0.8535 18.6
Glucose
(blood)		 6 5 −0.4178 −0.9320 0.0963 −0.4410 −1.5333 0.6513 30.43 1.2036 86.9 8.51 5 0.1304
8 1 −4.5622 −6.1849 −2.9395 −4.5622 −7.2560 −1.8684 0.00 - -
10 2 −1.2618 −1.9991 −0.5246 −1.2927 −2.9841 0.3987 0.83 1.2036 0.0
12 1 −0.1355 −1.0133 0.7423 −0.1355 −2.4580 2.1870 0.00 - -
16 3 −0.6143 −1.1747 −0.0522 −0.6727 −2.0368 0.6914 3.57 1.2036 43.9
21 1 −0.8705 −1.9103 0.1692 −0.8705 −3.2590 1.5179 0.00 - -
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1 TC, total cholesterol; TG, triglyceride, LDL-C, low-density lipoprotein; HDL-C, high-density lipoprotein, TNF-α; Tumor necrosis factor alpha; 2 k: number of treatments; 3 SMD: standardized mean difference; 4 CI: confidence interval; 5 Q: chi-squared statistic; 6 τ2: true heterogeneity; 7 I2: Higgin’s I2 statistic; 8 Qb: Q statistics between groups; 9 df: degrees of freedom of Q statistic; 10 –: no data.

Next, meta-regression was performed to evaluate the effect size between the type of chitosan used and the administration period (Table 5). Only CTS + RS was significant (p = 0.0208), and it was revealed to use to decrease blood TC. In the case of WSC, it was significantly effective in lowering of serum TNF-α and body weight (p = 0.0307 and 0.0008, respectively). With regard to the administration period, this was significantly relevant to blood HDL-C and liver TC with p = 0.0004 and 0.0358, respectively.

Table 5.

Meta-regression analysis of effect of chitosan on lowering cholesterol.

Item Item 1 Estimate SE p-Value 2 ci. lb ci. ub
TC
(blood)		 Type Intercept −2.1859 1.6901 0.1959 −5.4884 1.1266
CTS 0.1219 1.7093 0.9431 −3.2282 3.4720
WSC −0.5761 1.7444 0.7412 −3.9952 2.8429
RS −0.1338 2.0610 0.9482 −4.1733 3.9056
CTS + RS −6.8139 2.9481 0.0208 * −12.5920 −1.0358
WSC + RS 0.7024 2.3290 0.7630 −3.8624 5.2671
CSR 0.2677 2.3758 0.9103 −4.3889 4.9242
Administ-ration period Intercept −2.7155 0.4412 <0.0001 *** −3.5802 −1.8509
Period 0.0701 0.0561 1.2503 −0.0398 0.1800
TG
(blood)		 Type Intercept 1.1106 1.7676 0.5298 −2.3538 4.5750
CTS −2.1980 1.7917 0.2199 −5.7097 1.3136
WSC −3.0136 1.8238 0.0985 −6.5881 0.5610
RS −2.3077 2.1766 0.2890 −6.5738 1.9584
CTS + RS −4.5172 2.5911 0.0813 −9.5957 0.5613
WSC + RS −2.5444 2.5135 0.3114 −7.4708 2.3821
CTS + VitC −1.9712 2.5027 0.4309 −6.8764 2.9340
Administ-ration period Intercept −2.0619 0.4644 <0.0001 *** −2.9721 −1.1516
Period 0.1108 0.0586 0.0586 −0.0040 0.2257
LDL-C
(blood)		 Type Intercept −1.7721 1.0902 0.1041 −3.9089 0.3647
CTS −1.0320 1.1352 0.1041 −3.9089 0.3647
WSC −1.1110 1.1886 0.3499 −3.4407 1.2186
RS 1.5229 1.5190 0.3161 −1.4542 4.5000
Administ-ration period Intercept −2.3459 0.7447 0.0016 ** −3.8056 −0.8863
Period −0.0554 0.1258 0.6595 −0.3021 0.1912
HDL-C
(blood)		 Type Intercept 0.3816 0.3323 0.2507 −0.2696 1.0329
WSC −1.1785 0.7190 0.1012 −2.5877 0.2307
RS −0.4951 1.3894 0.7216 −3.2183 2.2282
CTS + RS 1.6183 1.9784 0.4134 −2.2594 5.4959
WSC + RS −0.1523 1.9366 0.9373 −3.9481 3.6434
Administ-ration period Intercept −1.4886 0.5323 0.0052 ** −2.5319 −0.4453
Period 0.2432 0.0684 0.0004 *** 0.1091 0.3773
TC(liver) Type Intercept −1.5873 1.9416 0.4136 −5.3927 2.2181
WSC 0.0805 2.2402 0.9713 −4.3102 4.4713
CTS −2.0698 1.9835 0.2967 −5.9575 1.8179
CSR −3.1597 2.9633 0.2869 −8.9676 2.6481
Administ-ration period Intercept −1.9173 0.7594 0.0116 −3.4057 −0.4289
Period −0.1982 0.0944 0.0358 −0.3872 −0.0132
TG(blood) Type Intercept −3.0600 0.4819 <0.0001 *** −4.0045 −2.1154
WSC −1.1192 1.1754 0.3410 −3.4229 1.1845
Administ-ration period Intercept −2.7837 1.0596 0.0086 ** −4.8606 −0.7068
Period −0.0620 0.1197 0.6045 −0.2967 0.1727
TC
(feces)		 Type Intercept 2.6479 0.3939 <0.0001 *** 1.8759 3.4200
WSC −0.2285 1.0908 0.8341 −2.3664 1.9094
Administ-ration period Intercept 1.3488 0.7729 0.0810 −0.1661 2.8637
Period 0.1637 0.0958 0.0808 −0.0205 0.3552
TG
(feces)		 Administ-ration period Intercept 1.2205 0.8155 0.1345 −0.3778 2.8189
Period 0.1409 0.0847 0.0961 −0.2510 0.3069
TNF-α Type Intercept −2.0430 0.3956 <0.0001 *** −2.8184 −1.2676
WSC 3.0273 1.4005 0.0307 * 0.2823 5.7723
Administ-ration period Intercept −2.4611 1.3793 0.0744 −5.1646 0.2423
Period 0.0599 0.1285 0.6413 −0.1920 0.3117
Body weight Type Intercept −3.4586 0.5526 <0.0001 *** −4.5418 −2.3755
WSC 2.8636 0.8524 0.0008 *** 1.1930 4.5342
RS 1.1231 1.3669 0.4113 −1.5559 3.8021
CTS + RS −5.5412 2.5456 0.0295 * −10.5305 −0.5519
WSC + RS 1.9751 1.7926 0.2705 −1.5383 5.4885
Administ-ration period Intercept −0.5489 1.3274 0.6793 −3.1506 2.0529
Period −0.2678 0.1770 0.1303 −0.6148 0.0792
Glucose
(blood)		 Type Intercept −0.9044 0.3993 0.0235 * −1.6869 −0.1218
RS −0.7644 1.3438 0.5694 −3.3982 1.8694
CTS + RS −0.8650 1.3491 0.5214 −3.5092 1.7793
CTS + VitC 1.6188 1.3082 0.2159 −0.9453 4.1829
Administ-ration period Intercept −1.0118 0.8754 0.2477 −2.7275 0.7039
Period 0.0103 0.0736 0.8887 −0.1339 0.1545
Open in a new tab

1 CTS, chitosan; WSC, water-soluble chitosan; RS, resistant starch; CTS + RS, chitosan and resistant starch; WSC + RS, water-soluble chitosan and resistant starch; CTS + VitC, chitosan and vitamin C; CSR, cholestyramine; 2 Means marked with *, **, and *** differ significantly (p < 0.05, 0.01 and 0.001, respectively).

2.4. Publication Bias

Publication bias was conducted using an Egger’s linear regression test (Table 6) on blood TC and TG, blood LDL-C and HDL-C, liver TG and TC, fecal TC, and body weight. As the results from the Egger’s linear regression test show, significance was detected in all items (p < 0.05) indicating that the relationship between effect size and standard error was statistically significant and confirming the presence of bias [48]. Thus, the trim-and-fill technique was used to correct asymmetry due to publication bias in all items, with the resulting compensated effect sizes being shown in Table 7. Other than blood HDL-C, most of the effects showed significance (p < 0.05).

Table 6.

Egger’s linear regression test for publication bias.

Items Bias Se 1. bias Slope t df 2 p-Value
Total cholesterol (blood) −6.9521793 0.5168551 2.8826324 −13.451 64 <2.2 × 10−16
Triglyceride (blood) −7.4780606 0.9998057 3.7716108 −7.4795 67 2.087 × 10−10
LDL-cholesterol (blood) −6.1250126 0.4715822 2.2442145 −12.988 46 <2.2 × 10−16
HDL-cholesterol (blood) 0.51543585 1.43323094 −0.07605097 0.35963 52 <0.0001
Total cholesterol (liver) −6.5468325 0.5461543 2.4287577 −11.987 30 5.732 × 10−13
Triglyceride (liver) −6.7370699 0.9014982 2.5785977 −7.4732 21 2.411 × 10−07
Total cholesterol (feces) 6.5339622 0.4235035 −2.6905774 15.428 24 5.871 × 10−14
Triglyceride (feces) 8.411555 1.070048 −3.8220945 7.8609 8 4.953 × 10−05
TNF-α (blood) −8.347186 2.266406 3.647681 −3.683 11 0.003607
Body weight −7.798456 1.192187 3.513530 −6.5413 20 2.249 × 10−06
Open in a new tab

1 Se: standard error; 2 df: degrees of freedom of Q statistic.

Table 7.

Trimmed effect size of probiotics on inflammatory bowel disease in murine model.

Items df Fixed Effect Model Random Effect Model Heterogeneity
ES p-Value ES p-Value Q (p-Value) I2 (%) τ2
Total cholesterol (blood) 86 −1.1096 <0.0001 −1.2079 <0.0001 686.36 (<0.0001) 87.5 3.6291
Triglyceride (blood) 78 −0.2142 0.0029 −0.2935 0.2360 878.84 (<0.0001) 91.1 4.2254
LDL-cholesterol (blood) 64 −1.1291 <0.0001 −1.2373 <0.0001 551.97 (<0.0001) 88.4 4.2350
HDL-cholesterol (blood) 52 0.0607 0.4912 −0.1870 0.5174 521.81 (<0.0001) 90.0 3.7407
Total cholesterol (liver) 42 −1.7190 <0.0001 −1.8509 <0.0001 367.01 (<0.0001) 88.6 5.8208
Triglyceride (liver) 31 −1.4703 <0.0001 −1.6805 0.0004 314.64 (<0.0001) 90.1 6.2275
Total cholesterol (feces) 31 1.2437 <0.0001 1.3796 0.0004 226.78 (<0.0001) 86.3 3.9640
Triglyceride (feces) 13 1.4815 <0.0001 1.5692 0.0011 71.66 (<0.0001) 81.9 2.5666
TNF-α (blood) 14 −1.2869 <0.0001 −1.3743 0.0026 96.71 (<0.0001) 85.5 2.5645
Body weight 27 −1.1740 <0.0001 −1.2547 0.0079 284.88 (<0.0001) 90.5 5.3068
Glucose (blood) 12 −0.7512 <0.0001 −0.8958 0.0096 61.64 (<0.0001) 80.5 1.2356
Open in a new tab

3. Discussion

In the results of Table 2, most items showed negative effect size and high significance (p < 0.0001) in both effect models. These results mean that chitosan administration results in decreased levels of TC, TG, and LDL-C in blood, TC and TG in the liver, TNF-α and glucose in blood and body weight, and increased levels of blood HDL-C, fecal TC and TG.

The bioavailability of dietary fat in the intestine decreased after chitosan administration. After this, reverse cholesterol transport, which is delivered from peripheral tissues to the liver, is accelerated by excretion of surplus dietary fat, resulting in an increase in the ratio of HDL-cholesterol [49]. Similarly, [50] have reported that the addition of chitosan to an animal diet caused a decrease in LDL-cholesterol content. Generally, HDL-cholesterol may decrease cardiovascular disease by converting cholesterol condensed on peripheral tissues or blood vessel walls into an ester compound. The ester compound is then transferred to the liver, excreted by bile-salt, and cholesterol content in blood is lowered. By contrast, LDL-cholesterol, which is the most general delivery type of blood cholesterol, accumulates easily on artery walls, causing arteriosclerosis. For this reason, it is known as the leading risk factor for arteriosclerosis and cardiovascular [51]. In this result, increased HDL-cholesterol, fecal total cholesterol, and triglyceride after chitosan administration are related to the factors mentioned above. According to Jeon and Kim [52], when chitosan is cationized (–NH3+), its viscosity is increased by the formation of poly cations and gels. In high viscosity of the intestine, dietary fiber lower blood cholesterol by delaying cholesterol diffusion from micelle to mucosa, inhibiting bile acid metabolism, delaying micelle forming, and reducing cholesterol absorption rate in the intestine [19,53]. Based on this result, chitosan exhibits an excellent anti-hypercholesterolemic effect and is thought to be effective in mitigating cardiovascular disease caused by excessive fat intake.

Cytokines are secreted by activated lymphocytes and macrophages, and regulate the function of the cells related to immune response. They are also recognized as playing an essential role in the inflammatory response [54]. Yemak et al. [8] report that TNF-α generation was lower in lipopolysaccharide (LPS) and chitosan-injected mice than in LPS-injected mice. Similarly, Seo et al. [7] observed that TNF-α was increased by the application of special stimulants in a human mast cell line (HMC−1), but decreased by the use of chitosan. TNF-α is one of the pro-inflammatory cytokines synthesized by adipose tissue [55,56], and high TNF-α levels are one of the critical risk factors for diabetes [57]. In a similar vein, Yoon et al. [58] state that chitosan is associated with an anti-inflammatory response to TNF-α gene expression. According to Zhu et al. [59], chitosan has an anti-inflammatory effect on active molecules, for example TNF-α and IL-1β via the NF-κB pathway. Activated macrophages secrete numerous pro-inflammatory cytokines, including IL-1β and TNF-α, to intermediate the inflammatory response [60]. However, overproduction of these pro-inflammatory mediators causes excessive inflammation [61]; thus, regulation of the release of pro-inflammatory mediators may be important in mitigating the inflammatory response.

According to Prabu and Naturajan [62], blood glucose levels decreased in streptozotocin-induced diabetic rats that were fed chitosan for 30 days. Other researchers suggest that the effectiveness of chitosan in lowering blood glucose may be due in part to the effect of total glyceride in lowering free fatty acids. Jo et al. [63] report that in an animal study, chitosan that was enzymatically treated and of low molecular weight (<1000 Da) was more effective in managing prandial glucose. Kim et al. [64] also report that chitosan that is low in molecular weight acted similarly to acarbose, a known anti-diabetic medication, in a murine model. They also note that chitosan administration inhibited sucrase and glucoamylase activities. It is recognized that chitosan binds with glucosidase in the intestinal brush border in a manner similar to acarbose (Hanefeld, [65]; Puls et al. [66]; Krentz and Bailey [67]). The inference of these reports is that body weight may be decreased by chitosan administration.

In the course of this process, heterogeneity is introduced as a result of methodological differences between studies. In general, a heterogeneity test is used to decide on methods for combining studies and to evaluate the consistency or inconsistency of findings (Petitti [68]; Higgins et al. [69]). To evaluate heterogeneity in relation to effect size in the present study, Q statistics and I2 values were computed. The highest among Q statistics was TG in blood, with high significance (p < 0.0001). The significance of the Q statistic implies that the studies used to calculate the overall effect (the effect size of fixed and random effect models) do not share the same effect size with one another (Cho et al. [70]). In this study, the Q statistics for all items were found to be significant (p < 0.0001). However, one limitation of this method is its dependence on the number of studies (Fleiss [71]). I2 and τ2 values are commonly used to overcome this limitation of Q statistics by providing a concrete indication of heterogeneity. The I2 value is used most frequently in meta-analysis to compare different numbers of studies and data types. Consequently, it offers a solution to the issue of the Q statistic when analyzing heterogeneity (Higgins et al. [72]). All items of I2 value in the present study were above 70%, which means that they all showed significant levels of heterogeneity [73]. The τ2 value indicates the absolute value of heterogeneity, representing variance in true effect sizes [74]. In addition, liver TG showed the highest τ2 value, which means that variance in the effectiveness of chitosan administration is great (Cho et al. [70]).

Cholestyramine (trade name: Questran, Questran Light, Cholybar or Olestyr) and cholestipol (trade name: Colestid or Cholestabyl) as an anion-exchanger are these days used mainly for reducing cholesterol [75]. These medications contain amino groups, are water-insoluble, and unlike chitosan are not absorbed in the intestine. Specifically, they form insoluble complexes with bile acids in the intestines, which are then excreted in the feces. As a result, more plasma cholesterol is converted into bile acids in the liver to normalize its levels. When cholesterol is converted into bile acids, plasma cholesterol levels are lowered (National Institute of Diabetes and Digestive and Kidney Diseases [76]). Consequently, they are known to inhibit cholesterol absorption in the gut and to promote bile salt excretion. However, they are also known to involve a number of issues, including gastrointestinal disturbance, constipation, and colon cancer [77,78]. Valhouny et al. [79] report that chitosan supplementation showed a similar inhibition effect to cholestyramine in cholesterol adsorption. Similarly, an animal study by Jennings et al. [78] showed that chitosan was similar to cholestyramine in lowering lipids without other harmful changes in intestinal mucosa. Currently, a total of 1832 patents related to chitosan are being searched in the field of hyperlipidemia and associated cardiovascular diseases. It can thus be concluded that chitosan supplementation may be useful in lowering cholesterol and offers a promising alternative treatment for lifestyle-related diseases.

4. Materials and Methods

4.1. Data Set

To perform a meta-analysis of published studies regarding the effect of chitosan administration on lowering cholesterol in murine models between 1978 to 2020, a literature search was conducted on Pubmed (US National Library of Medicine, Bethesda, MD, USA) and Science Direct (Elsevier B. V., Amsterdam, The Netherlands). The keywords used for searching studies for meta-analysis were “chitosan, cholesterol” in all databases. The results obtained included 450 citations from Science Direct and 303 from Pubmed (US National Library of Medicine, Bethesda, MD, USA). These results were then filtered by title, abstract, and full text. Among them, 4 review articles and 7 studies of clinical tests in human studies were removed. Also, the studies expressed with graphical data were eliminated. Following this, studies regarding changes in cholesterol levels after chitosan administration were collected. Ultimately, a total of 34 studies with 11 items (e.g., total cholesterol, triglyceride, LDL- and HDL-cholesterol, TNF-α, and so on) were selected to perform a meta-analysis of the effectiveness of chitosan in reducing cholesterol in murine models.

4.2. Data Analysis

Corrected standardized mean difference (Hedges’ g), and 95% confidence intervals (CI) were computed between control groups and treatment. The weight of the effect size was calculated using inverse-variance [80,81]. Effect-size analysis of fixed and random effect models was used to calculate overall effect due to differences in administration period, animal strain, and the type and dosage of chitosan used in each study. Cochran’s Q test was performed to assess the statistical heterogeneity of the effect size, and the ratio of true heterogeneity to total variation in observed effects was expressed by the I2 value. To confirm the heterogeneity of effect size using a mixed-effect model for the items in question, meta-ANOVA and regression analyses were also used. Meta-ANOVA and meta-regression analysis can evaluate the difference of Hedges’ g among subgroups herein administration periods or type of treatment. The periods were set as independent factors in meta-ANOVA and as continuous variables in meta-regression. Finally, publication bias analysis was conducted to ensure the validity of the meta-analysis results. Statistical analysis and visualization of the results were performed using the ‘meta’, and ‘metafor’ packages in the R statistics software application (ver. 3.5.3, R Foundation for Statistical Computing, Vienna, Austria).

5. Conclusions

The present study confirmed the effectiveness of chitosan administration on lifestyle-related diseases through meta-analysis. Chitosan was significantly effective in lowering total cholesterol and triglyceride of blood and liver and rising fecal total cholesterol and triglyceride. Based on our results, chitosan was demonstrated to be useful in improving the symptoms of lifestyle-related disease.

Acknowledgments

The authors would like to thank the Writing Center at Jeonbuk National University for their language assistance, which we think readers will agree has greatly enhanced the readability of the manuscript.

Author Contributions

S.C. and N.-J.C. designed the study. S.-I.A. performed the literature search and data extraction. S.C. contributed to the statistical analyses. S.-I.A. wrote the first draft of the manuscript and S.C. and N.-J.C. prepared the final draft. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (No. 2020R1C1C1010982).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are fully available in the main text of this article.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Data Availability Statement

The data presented in this study are fully available in the main text of this article.

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