Test results of cross-sectional dependence.
\r\n\t
",isbn:"978-1-83881-017-7",printIsbn:"978-1-83881-016-0",pdfIsbn:"978-1-83881-024-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"d5ac3a7054e526666a89271cef6ee869",bookSignature:"Dr. Ahmed Mourtada Elseman",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9924.jpg",keywords:"Photons, Semiconducting Materials, Photocurrent Density, Dye-Sensitized Cells, Perovskite Cells, Perovskite/Si Tandem, CIGS, CdTe, Single Crystal, Thin-Film Crystal, Single Crystal, Multicrystalline",numberOfDownloads:440,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 25th 2020",dateEndSecondStepPublish:"June 15th 2020",dateEndThirdStepPublish:"August 14th 2020",dateEndFourthStepPublish:"November 2nd 2020",dateEndFifthStepPublish:"January 1st 2021",remainingDaysToSecondStep:"7 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Dr. Elseman holds two diplomas, first one from Inner Mongolia Institute of Science and Technology and the second one from the Institute of New Energy, Wuhan. During his work at Southwest University, where he is currently also active, Dr. Elseman received funds from Central Universities for a project on efficient perovskite solar cells, a topic on which his research is mainly focused.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"221890",title:"Dr.",name:"Ahmed Mourtada",middleName:null,surname:"Elseman",slug:"ahmed-mourtada-elseman",fullName:"Ahmed Mourtada Elseman",profilePictureURL:"https://mts.intechopen.com/storage/users/221890/images/system/221890.jpg",biography:"Ahmed Mourtada Elseman obtained his B.Sc., M.Sc., and Ph.D. in Inorganic and Analytical Chemistry from the Faculty of Science, Al-Azhar University, Egypt. He earned his Ph.D. in perovskite solar cells in February 2017. He obtained two diplomas, first one from Inner Mongolia Institute of Science and Technology, Hohhot, China 2015, and the second one from the Institute of New Energy, Wuhan, China, 2017. He currently works as Research Assistant Professor at the Department of Electronic and Magnetic Materials, Central Metallurgical Research and Development Institute (CMRDI), Egypt. \nHe was awarded the Talent Young Scientific (TYSP) Postdoctoral Research Fellow position funded by the Chinese Ministry of Science and Technology (MOST) and organized by North China Electric Power University, Beijing, China, 2017-2018. After that, he received a lecturer position in the School of Materials and Energy, Southwest University, Chongqing. China (2018 – 2020). During his work at Southwest University, he received a project funded by Central Universities for efficient perovskite solar cells (ID: XDJK2019C005). He was also awarded the CMRDI prize for excellence scientific publication (2018). His current research focuses on understanding the mechanisms, fundamental properties, and developing scalable protocols for high-efficiency perovskite solar cells. 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ROS can harm different types of cells and tissues through protein damage, lipid peroxidation, and DNA damage. Excessive ROS production plays a role in the pathogenesis of various chronic inflammatory diseases, including periodontal disease [2] (Figure 1). Cells and tissues require antioxidants to prevent the tissue damage caused by overproduction of ROS [3].
\nIt is shown that ROS has a key role in tissue injury occurred during reacting against periodontal pathogens and occurrence of chronic inflammation [2]. MMP, matrix metalloproteinase; TIMP, matrix metalloproteinase tissue inhibitor; NF-κB, nuclear factor-kappa B; AP-1, activator protein-1; PDL, periodontal ligament; TNF, tumor necrotizing factor; IL, interleukin; GM CSF, granulocyte-macrophage colony stimulating factor; LPS, lipopolysaccharide; and ROS, reactive oxygen species.
Antioxidants (AOs) are compounds that prevent the initiation or progression of oxidation reactions by trapping oxygen in the environment [4]. They play an important role in preserving the structural integrity of cells and tissues, by maintaining their normal functions and ensuring the maintenance of balance between oxidant and antioxidant mechanisms [2] (Figure 2). Antioxidants show their effects against oxidative stress in four different ways:
by acting on the free radical producing steps, such as chain-forming lipid peroxidation; α-tocopherol
reducing the concentration of ROS directly; glutathione
by neutralizing the primary radicals that initiate free radical production; superoxide dismutase
forming a chelate with transition metals; lactoferrin, transferrin, ferritin, ceruloplasmin, and albumin [5].
The biological effects of small and large shifts on the balance of activity between reactive oxygen species (ROS) and antioxidant (AO) species [2].
Antioxidants, such as vitamins, minerals, enzymes, and hormones, are molecules that could be obtained from exogenous and endogenous sources, in addition to nutrients and herbal supplements. Antioxidants such as vitamin E, vitamin C, ceruloplasmin, glutathione peroxidase, and superoxide dismutase protect cells and tissues from tissue damage caused by free radicals [6].
\nEndogenous antioxidants are classified as enzymatic and nonenzymatic antioxidants.
\nGSH-Px is a tetrameric enzyme found in the cytosol and contains four selenium (Se) atoms. It shows its effect by reducing hydroperoxides and hydrogen peroxide (H2O2). Essentially, GSH-Px acts on lipid hydroperoxides released by phospholipase A2 (PLA2), which is a membrane phospholipid. It also has important effects on phagocytic cells. The decrease in GSH-Px activity leads to hydrogen peroxide accumulation and cell damage. GSH-Px prevents lipid peroxidation and enables the metabolism of lipid hydroperoxides that are the products of lipid peroxidation [7, 8]. The gingival and serum GSH-Px levels were shown to be higher in periodontitis patients compared to healthy people and gingivitis patients [9].
\nGlutathione reductase, a flavoprotein, catalyzes the reduction of oxidized glutathione (GSSG) to glutathione with the help of NADPH. For the successful maintenance of many antioxidant enzyme activities, it is important that glutathione stays at the reduced state [10]. Increased GSH-Red salivary concentrations have been shown to be a strong/independent prognostic indicator of the amount and extent of oxidative stress-related periodontal injury in both chronic periodontitis (CP) and aggressive periodontitis (AgP) [11].
\nGlutathione transferases, a multienzyme family, are responsible for the detoxification process. They produce an antioxidant defense mechanism by showing selenium-independent GSH-Px activity against lipid hydroperoxides, especially arachidonic acid and linoleic acid hydroperoxides. They have been shown to have increased activity in periodontal diseases [12].
\nCatalase, which catalyzes the conversion of H2O2 to molecular oxygen and water, is a protein that is found in both peroxisomes and cytosol and contains heme [7]. The lowered level of catalase is associated with hyper lipid peroxidation in periodontal disease [13].
\nSuperoxide dismutases are found in the cytosol and mitochondria of all aerobic cells. These enzymes eliminate the effects of superoxide radicals and protect the cells against the harmful effects of these radicals. This enzyme plays a role in the intracellular destruction of phagocytosed bacteria and is important for granulocyte function [14]. Gingival SOD activity was found to be higher in patients with chronic periodontitis [15].
\nMitochondrial cytochrome oxidase is the last enzyme in the respiratory chain and detoxifies superoxide (O2−) [16]. Maeda et al. [17] have suggested that mitochondrial cytochrome oxidase is a useful marker enzyme for demonstrating sensory receptors in the periodontal ligament.
\nIt is found in foods such as sour cherries, almonds, hazelnuts, chamomile tea, and St. John’s wort [18]. Because it has lipophilic properties, melatonin can be found in almost all cells. It exerts its antioxidant effect by quenching hydroxyl and superoxide radicals. Melatonin shows strong antioxidant properties in the inflammatory process and oxidative injuries. Melatonin was found to be lower in gingival crevicular fluid and saliva of individuals with periodontitis compared to healthy individuals. It has also been reported to enhance bone formation [19, 20]. Melatonin is released with saliva to the oral cavity and protects the mucosa and gingival tissues from radical damage [21].
\nCeruloplasmin oxidizes Fe2+ to Fe3+ to prevent the Fenton reaction and hydroxyl radical formation [22]. In CP and AgP patients, the serum ceruloplasmin level increases, especially in AgP patients, it may be a potential marker for diagnosis of periodontitis [23].
\nTransferrin prevents the Fenton reaction by binding free iron ions [22]. There was an inverse relationship between transferrin serum levels and chronic periodontitis [24].
\nLactoferrin binds to iron ions in low pH environments [25]. Lourenço et al. [26] indicated that lactoferrin (Lf) is a possible marker for periodontal diseases in immunocompetent and immunocompromised subjects.
\nGlutathione, which eliminates the effects of harmful compounds in the body, is found in all cells. GSH is reduced glutathione and serves as a substrate for antioxidant enzymes by acting as a radical scavenger during radical cell damage. Glutathione is a very important molecule, especially for the activities of peroxidase and reductase enzymes. GSSG is produced by the oxidation of GSH. During oxidative stress, GSH levels are decreased, and the GSSG levels are increased. H2O2 and organic hydroperoxides, which are produced during oxidative stress, are removed by the action of glutathione peroxidase and glutathione reductase [25].
\nGSH plays a critical role in keeping enzymes and other cellular components from being reduced. Most of the GSH is synthesized in the liver, and approximately 40% of GSH is excreted through bile. It is suggested that the GSH in the bile protects the body against dietary xenobiotics, prevents lipid peroxidation in the lumen of the intestine, and defends the intestinal epithelium against oxygen radicals [27]. Glutathione is the most important redox regulator that controls inflammatory processes, thus damaging the periodontium [28].
\nCysteine is a superoxide and hydroxyl radical scavenger [29]. The measurement of salivary cysteine may be useful for identifying periodontitis patients with hopeless teeth [30].
\nUric acid, which is synthesized as the final product of purine metabolism, functions as an endogenous free radical scavenger and antioxidant. It is found in body fluids at a concentration of approximately 0.5 mmol/L [31]. In a recent study, uric acid levels in periodontitis patients have been found to be higher than in gingivitis patients. Moreover, uric acid has many roles in periodontitis than in gingivitis as an antioxidant agent [32].
\nGlucose is a hydroxyl radical scavenger [33]. The relationship between the periodontal disease and the blood glucose level among type II diabetic patients has been demonstrated [34].
\nCarotenoids are recognized as substances that give color to vegetables and fruits, and their antioxidant effects as vitamin A precursors are well-known. Most important carotenoids are α-carotene, β-carotene, lycopene, crocetin, canthaxanthin, and fucoxanthin. β-carotene is a combination of two molecules of vitamin A (also known as retinol). When dietary β-carotene is absorbed by the small intestinal mucosa, it is converted into retinol [5, 38]. Retinol and other retinoids have potential hormone-like effects on cell growth and differentiation [39]. It has been reported that in the case of retinol deficiency, predisposition to some types of cancer including oral cavity cancer is increased [40].
\nVitamin A is an important vitamin involved in vision. Vitamin A is soluble in fat, helps maintaining healthy tissues and skin, strengthens the immune system, and is necessary for a healthy bone structure. It also acts as an antioxidant, protects cells against cancer and other diseases, slows down the aging process, and helps to store fat. In vitamin A deficiency, dermatological, mucosal, and ocular changes may occur [41].
\nVitamin C is a water-soluble antioxidant, which is found in citrus fruits, potatoes, tomatoes, and green leafy vegetables [5]. Since it is water soluble, it is not stored in the body, and its excess amounts are excreted through sweat and urine. Therefore, it must be taken daily [42]. Vitamin C is necessary for biosynthesis, structural integrity, and stability of many components in the connective tissue [43]. The function of vitamin C is particularly important in wound healing and tissue regeneration due to its role in collagen synthesis. Vitamin C acts as a coenzyme for many enzymes involved in the synthesis of collagen, carnitine, and neurotransmitters [2].
\nVitamin C (also known as ascorbic acid) has many functions such as strengthening the immune system and development of bone and teeth. It enables protection against cancer and heart diseases. Unlike many other antioxidant vitamins, it is a water-soluble vitamin. It functions with glutathione in vitamin E regeneration. A negative correlation was found between plasma vitamin C and clinical attachment loss levels [44].
\nVitamin E is a name given to identify a group of eight natural compounds consisting of various tocopherols and tocotrienols, such as α, β, and δ. The form of vitamin E with the highest biological activity is α-tocopherol [45]. Vitamin E (also known as tocopherol) is the most important oil-soluble antioxidant found in nature [46]. It contains alpha, beta, gamma, and delta tocopherols. It is stored in the liver and has many functions in the immune system. It is found in cell membranes and as a component of lipoproteins [47]. Vitamin E is a major chain-breaking antioxidant and is the first line of defense against lipid peroxidation by protecting cell membranes during the early stages of free radical attack [48]. Its function as an antioxidant is mainly to inhibit peroxidation of membrane phospholipids and prevent damage to cell membranes. Lipid peroxidation is common in membranes, erythrocytes, lipoproteins, brain, and other tissues where polyunsaturated fatty acids (PUFAs) are abundant [47].
\nIn an experimental study in rats, vitamin E has been shown to be important in preventing alveolar bone destruction. The effect of vitamin E in reducing periodontal inflammation can be explained by the fact that it is a prostaglandin inhibitor [6, 49].
\nPolyphenols are composed of 4000 compounds in 13 classes (flavonoids, phenolic acids, anthocyanins, catechins, flavones, flavonols, flavanones, isoflavones, lignans, proanthocyanidins, procyanidins, resveratrol, and tannins). They are abundant in green tea, grape, and soy. They have anti-inflammatory, antiallergic, antiviral, antiaging, anticarcinogenic, and antioxidant properties [50].
\nFlavonoids are free radical scavengers and are sub-grouped into flavanones, flavanols (e.g., Luteolin), flavanols (e.g., quercetin and kaempferol), flavan-3-ols (e.g., catechin), anthocyanins, and isoflavones according to their chemical structure. Flavonoids are polyphenolic compounds found in vegetables (onion, parsley, etc.), fruits (berry, blackberry, apple, etc.), and beverages (green tea, cocoa, etc.). Due to their antioxidant, anti-inflammatory, antiallergic, antiviral, antibacterial, antiplatelet, and antitumor properties, they are widely used in medicine. Foods containing high amounts of flavonoids help protect blood vessels from rupture or leakage, protect cells from oxygen damage, and prevent inflammation in various tissues and organs [51, 52].
\nCoenzyme Q10, also known as ubiquinone, is a naturally occurring substance and is found in all living cells. It is abundant in veal, fish, and chicken [53]. It constitutes an important part of the energy production system of the body. Coenzyme Q10 strengthens the immune system by increasing immune resistance. It also protects the body against free radicals. It is especially important for the correct functioning of the heart muscle. It is a nutritional supplement that is soluble in fat and has an effect similar to vitamin E. In addition to its antioxidant effect, it is involved in the proper functioning of the circulatory system [54].
\nCoenzyme Q10 levels have been shown to be relatively low in gingival tissues of individuals with periodontitis. Local or systemic administration of Coenzyme Q10 during treatment helps reduce inflammation in periodontal tissues [55].
\nSelenium is found in the structure of selenoproteins and glutathione peroxidase, which is an important antioxidant enzyme. Selenoproteins help to regulate thyroid function and have a role in the immune system. Although selenium is a basic mineral required for a healthy body, the body only needs trace amounts of this mineral [56].
\nPeriodontal diseases are inflammatory diseases characterized by inflammation and loss of periodontal tissues. Periodontopathogenic bacteria and their products are important in its etiology. The course of the disease is determined by the interaction between the periodontopathogenic bacteria and the host immune response. Reactive oxygen species play a role in these interactions in favor of tissue destruction [57]. Oxidative stress plays an important role in the pathogenesis of many diseases such as rheumatoid arthritis and atherosclerosis, and it has also been reported to affect the pathogenesis of periodontal diseases [58]. In the case of periodontal disease, the increased PMN count and activity cause a high rate of ROS release. This causes increased oxidative stress in periodontal tissues [6]. ROS produced on the surfaces of osteoclasts may play an important role in alveolar bone resorption [59]. Periodontal tissues require adequate levels of antioxidants to prevent tissue damage caused by reactive oxygen species. Therefore, some studies have focused on the effects of antioxidant use in addition to SRP (scaling and root planning) on periodontal tissue destruction [60]. Natural antioxidants protect the tissues against tissue damage caused by free radicals and play a critical role in maintaining the tissue health [61]. Due to the likely benefits of antioxidants against periodontitis, the intake of such nutrients is recommended [60]. Figure 3 shows the possible oxidative stress-mediated inflammatory pathways related to periodontal tissue breakdown [62].
\nPossible oxidative stress-mediated inflammatory pathways related to periodontal tissue breakdown. LPS, lipopolysaccharide; GM-CSF, granulocyte-macrophage colony-stimulating factor; IL8, interleukin-8; TNF-α, tumor necrosis factor-alpha; PDL, periodontal ligament; NF-κβ, nuclear factor-kappa B; ROS, reactive oxygen species; PMNL, polymorphonuclear leukocyte; TIMP, tissue inhibitor of metalloproteinases; and MMP, matrix metalloproteinase.
In a study, a positive correlation was found between the improvement in sulcus bleeding scores and the intake of grapefruit that leads to an increase in plasma vitamin C levels [63]. In an 8-month follow-up study on individuals with periodontitis, encapsulated fruit and vegetable powder concentrate was reported to reduce the periodontal pocket depth compared to placebo [64].
\nMain antioxidant sources in a diet are cereals, fruits, vegetables, chocolates, oils, and beverages such as tea, coffee, wine, and fruit juices [65].
\nLeggott et al. [66] showed that ascorbic acid deficiency is not associated with the mucosal pathoses or changes in plaque accumulation or probing depths. In another study, the same researchers showed that vitamin C was not associated with plaque accumulation, pocket depth, and attachment loss [67]. But, in both studies, ascorbic acid status was found directly related to the measures of gingival inflammation [66, 67]. Nishida et al. [68] found a weak but statistically significant inverse relationship between the vitamin C-rich diet and the periodontal disease. Chapple et al. [2] found a strong inverse relationship between the serum vitamin C levels and the prevalence of periodontitis. Jacob et al. [69] found that normal and high doses of vitamin C intake reduced gingival inflammation and sulcus bleeding. Rai et al. [70] found a strong relationship between the low concentrations of vitamin C in serum and saliva and the risk of periodontal disease. In other studies, vitamin C levels in the gingival fluid were found to be 3-folds higher than that of plasma [71], and vitamin C was found to inhibit neutrophil collagenase activation [72]. In an experimental periodontitis study on rats, vitamin C intake decreased interleukin-1a and interleukin-1β gene expression by more than twofolds compared to the control group [73]. In the same study, an increase in plasma vitamin C levels by 175% was found to result in a significant decrease in gingival 8-hydroxydeoxyguanosine levels and a significant increase in reduced oxidized glutathione amounts [73].
\nIn a study on rats, Sanbe et al. [74] showed that vitamin C decreased high cholesterol diet-induced alveolar bone resorption and decreased periodontal tissue damage.
\nVitamin C has been shown to decrease the cytotoxic and apoptotic effects of Porphyromonas gingivalis (P. gingivalis) on gingival fibroblasts in vitro [75].
\nAkman et al. [76] showed that the administration of vitamin C with or without alpha lipoic acid was associated with a significant decrease in serum myeloperoxidase levels, increased bone alkaline phosphatase levels, decreased alveolar bone resorption, and decreased RANKL-positive cell count. In individuals with chronic periodontitis, vitamin C intake in addition to nonsurgical periodontal treatment has been shown to decrease the gingival bleeding index levels [77]. Furthermore, it was reported that low serum levels of vitamin C and vitamin E may be risk factors for periodontal disease in elderly individuals [78].
\nResearch on the relationship between vitamin E and periodontal diseases showed conflicting results. Cohen et al. [79] reported that 5% topical vitamin E gel, in addition to SRP, did not positively affect the formation of plaque and healing of the periodontal tissues. In another study, same researchers showed that vitamin E has a protective role against bone loss [49]. Another study reported that there was no statistically significant difference between the periodontitis patients and the healthy group in terms of serum vitamin E levels [80]. These contradictory results may be related to the study design, the dose of vitamin E, and the investigated different parameters.
\nIn a study on rats, the combination of vitamin E and selenium has been shown to reduce collagen degradation [81]. In addition, vitamin E supplementation has been found to accelerate gingival wound healing [82].
\nA negative correlation was found between serum α-tocopherol levels and the severity of periodontitis. While the level of α-tocopherol increases, the severity of periodontitis decreases [83]. The use of vitamin E in addition to nonsurgical periodontal treatment has been shown to have positive effects on periodontal parameters [84].
\nCarotenoids are highly potent antioxidants. Linden et al. [85] showed that α-carotene, β-carotene, β-cryptoxanthin, and zeaxanthin levels were significantly lower in patients with moderate to severe periodontitis.
\nIt has been shown that β-cryptoxanthin stimulates bone formation and may stop bone resorption by inhibiting gene expression of osteoclastic enzymes associated with bone resorption [86]. Therefore, it has been suggested that β-cryptoxanthin may reduce the risk of osteoporosis [87]. This may mean that it can slow and/or stop the alveolar bone destruction in periodontal diseases.
\nSystemic supplementation of 8 mg/day of lycopene was reported to decrease the gingival index in patients with gingivitis [88]. In individuals with chronic periodontitis, it was reported that the supplementation of 4 mg/day of oral lycopene in addition to SRP for 2 weeks resulted in a reduction in clinical attachment loss [89]. Arora et al. [90] found that, in individuals with CP, 8 mg/day of oral lycopene intake for 2 months in addition to SRP had positive effects in plaque index, modified gingival index, probing bleeding, and saliva IL-1β compared to the control group but reported that there was no significant difference in terms of a reduction in pocket depth, clinical attachment, and serum TNF-α levels.
\nIn an animal study, vitamin A deficiency was shown to cause hyperkeratosis in the gingival epithelium, periodontal pocket formation, cement resorption, and osseous changes [91]. In another study, vitamin A deficiency was found to result in thickening of the cement, contraction of the periodontal ligament, irregularities in the periodontal ligament, thickening of the alveolar bone, and labial alveolar periosteum, and these results were shown to be reversible with replacement therapy [92]. In a study analyzing the relationship between the periodontal status and the serum antioxidant levels, it was shown that there was a relationship between the prevalence of increased periodontitis and the low serum levels of β cryptoxanthin and β carotene in men between the age of 60–70 years [85].
\nIn periodontal disease, the amount of Coenzyme Q10 decreases in both blood and gingival tissues [93]. Oral intake of Coenzyme Q10 was found to cause an increase in the density of the gingiva and a decrease in the periodontal inflammation and microorganism amounts [94, 95, 96]. In another study, coadministration of Coenzyme Q10 and vitamin E orally was found to result in a decrease in plaque index, gingival index, sulcus bleeding index, and pocket depth [97].
\nPolyphenols can increase the antioxidant activity of oral fluids. It has been reported that keeping green tea in the mouth for 2–5 minutes increases the antioxidant capacity of saliva [98], and the consumption of two grapefruits per day for 2 weeks increases the phagocytic capacity of the gingival crevicular fluid neutrophils [99]. Furthermore, in vitro studies have shown the antibacterial effect of polyphenols against periodontal pathogens [100].
\nCatechin is an effective antioxidant found in green tea and was found to have protective effects against cancer and cardiovascular diseases. Catechins have also been shown to inhibit the growth of periodontal pathogens and prevent the periodontal tissue destruction [101].
\nIn green tea users, the gingival bleeding index is decreased significantly [102]. Also, it was shown that green tea has an inverse relationship with average pocket depth, levels of bleeding during probing, and clinical attachment level [103]. In another study, it has been reported that green tea inhibits the activity of gingival crevicular fluid collagenase in aggressive periodontitis patients [104]. In an experimental periodontitis model in rats, flavonoids have been shown to prevent inflammatory bone resorption by lipopolysaccharides [105]. Chopra et al. [106] reported that green tea supplement in addition to the nonsurgical periodontal treatment resulted in improvements in the plaque index, gingival index, bleeding during probing, and clinical attachment loss parameters, and the gingival crevicular fluid antioxidant capacity was eight times higher than the control group. In contrast to these studies, in a study conducted in adults, it was found that the consumption of less than one cup of green tea per day was associated with a decrease in the prevalence of periodontal disease, and the consumption of one or more cups of green tea per day resulted in an increase in the prevalence of moderate and severe periodontitis [107].
\nCocoa also contains flavonoids, and in an experimental study conducted in rats, a diet rich in cocoa has been shown to reduce periodontal disease-associated oxidative stress and periodontal destruction [108].
\nCoffee, which is a rich source of antioxidants due to its caffeine, caffeic acid, and chlorogenic acid content, has a modulating effect in natural and acquired immune response [109, 110]. In a study on adult males, coffee consumption has been shown to reduce alveolar bone loss [111]. Among periodontitis patients at the periodontal maintenance phase, there was a negative correlation between the coffee consumption [≥1 cup/day] and the prevalence of severe periodontitis [112]. Han et al. [113] suggested that coffee consumption is higher in men with periodontitis, and it may be an independent risk factor for periodontal disease.
\nQuercetin is one of the most common flavonoids in dietary foods. It is a free radical scavenger found in many vegetables, fruits, olive oil, red wine, and tea. It has anti-inflammatory, antiallergic, antiviral, antithrombotic, antimutagenic, antineoplastic, and cytoprotective effects. In an experimental periodontitis study conducted on rats, 75 mg/kg/day oral quercetin administration was reported to decrease lipopolysaccharide-induced osteoclast formation, bone loss, and periodontal inflammation [114].
\nCurcumin also has antioxidant properties due to the phenolic compounds in its content. It has antitumor and anti-inflammatory properties [115]. Bakir et al. [116] reported that oral curcumin application reduced alveolar bone loss in rats.
\nKaempferol is one of the flavonoids in vegetables (leek, cucumber, etc.), fruits, and tea. It has an immunomodulatory effect and has been suggested to be used as a host modulator agent in periodontal therapy [117]. In a study on rats, the administration of 10 mg/kg/day of oral kaempferol was reported to decrease the alveolar bone loss, attachment loss, and gingival tissue MMP-1 and MMP-8 levels [118].
\nThe active ingredients of propolis are also flavonoids. In addition, it contains magnesium, calcium, iodine, potassium, sodium, copper, zinc, manganese and iron minerals, and vitamins B1, B2, B6, C, and E. The content that gives most of its antioxidant properties is the caffeic acid, which has phenolic properties. In an experimental periodontitis study performed in rats, it was shown that systemic propolis administration of 100 mg/kg/day for 21 days reduced alveolar bone loss [119]. In addition to SRP, 400 mg of daily propolis supplementation for 6 months was reported to significantly decrease HbA1C levels and pocket depth at 3 and 6 months compared to the control groups and to increase clinical attachment gain [120].
\nProanthocyanidin is a potent antioxidant found in grape seed and red fruits like cranberries, blueberries, etc. In an experimental periodontitis model in rats, 30 mg/kg of proanthocyanidin was given for 30 days, and a decrease in reactive oxygen species in blood and a decrease in histopathologic inflammatory cell infiltration were reported [121].
\nOlive oil contains a large number of polyphenols, a high concentration of α-tocopherols, and low concentrations of carotene and acts as a chain-breaking antioxidant through its oleuropein content. In a 24-month study conducted in rats, it was shown that alveolar bone loss was lower in the group that used olive oil compared to the groups that used sunflower oil and fish oil in addition to their regular diet [122].
\nNo significant difference was shown between saliva and plasma melatonin levels of healthy subjects and CP patients; however, melatonin levels were significantly lower in gingival tissues of individuals with CP [123]. It was reported that the levels of saliva melatonin increased after nonsurgical periodontal treatment and salivary melatonin levels correlated negatively with bleeding during probing [21].
\nSerum selenium, glutathione, and catalase levels in diabetic individuals with periodontitis have been reported to be negatively correlated with the severity of periodontal inflammation and tissue destruction [124].
\nSome systemic diseases and conditions that affect periodontal diseases including, cardiovascular disease, diabetes, dyslipidemia, hypertension, obesity, osteoporosis, and pregnancy are associated with antioxidants. Also, periodontitis is associated with low serum/plasma micronutrient levels. Nowadays, actual studies that investigate the effects of antioxidants on periodontal diseases have shown that antioxidants have anti-inflammatory properties. Although numerous studies demonstrated the relationship between antioxidants and periodontal diseases, and the number of studies in humans is limited. There are only a few cross-sectional studies that support the potential to improve periodontal outcomes by antioxidants. This chapter will discuss the possible role of antioxidants in the etiology and therapy of periodontal diseases.
\nThe author has no conflicts of interest to disclose.
AgP | aggressive periodontitis |
AO | antioxidants |
CP | chronic periodontitis |
GSH and GSSG | glutathione |
GSH-Px | glutathione peroxidase |
GSH-Red | glutathione reductase |
GSH-Tr | glutathione transferase |
H2O2 | hydrogen peroxide |
Lf | lactoferrin |
GSSG | oxidized glutathione |
PLA2 | phospholipase A2 |
PUFA | polyunsaturated fatty acids |
P. gingivalis | Porphyromonas gingivalis |
ROS | reactive oxygen species |
SRP | scaling and root planning |
Se | selenium |
O2- | superoxide |
SO | superoxide dismutase |
Liquidity risk, which is an important measure of the bank’s success in the long run, is the ability to pay liabilities and swap debts when needed. Banks should keep optimal liquid assets to meet their loan activities, investments, and depositors’ demands on time and adequately. In this respect, banks try to balance this situation. As a result, the bank is exposed to liquidity risk. Thanks to the liquidity risk management, it is ensured that banks continue their effectiveness against new risks that may arise due to changes in the operating environment or increases in the current risk level [1]. On the other hand, credit is the debt given to real persons and corporations within the framework of contracts. It is one of the important financial instruments that cause economic growth by gaining investors’ savings to the economy and increasing private consumption expenditures [2].
\nTotal amount of credits given by the Turkish banking sector have been increasing rapidly in the last decade. This situation was shown in Figure 1. However, there is a risk that the bank loan client is not able to meet the obligations of the agreement. In this case, it is expected that there will be a decrease in the income and capital of banks and an increase in expenses and losses [3].
\nTotal amount of credits in the Turkish banking sector (million TL).
Banks should have liquid funds in their hands in order to meet their credit activities on time and adequately. If they do not hold this fund, the liquidity risk will increase. Increasing liquidity risk will increase financial vulnerability and economic instability. Therefore, in this study, the long-term relationship between credit expansion and liquidity risk is investigated with a panel cointegration analysis. The rest of this study is organized as follows. In the second section, literature on credit expansion is given. The third section introduces the data set and variables used in this study. The fourth section examines the results of the econometric method used, and the last section concludes.
\nCredits can have positive and negative effects on the economy. For this purpose, studies conducted on credit expansion in Turkey were examined. Orhangazi explored the relation between capital inflows and credit expansion by using logit model. According to the findings, net private capital flows effect positively credit expansion by controlling other determinants [4]. Kara et al. made a cross-country comparison of credit growth by calculating a ratio of net credit use with respect to national income. They suggested a stable ratio of net credit relative to GDP that decreases slowly credit growth in the long-term period [5]. Kılıç examined relation between consumer credits and current account deficit. Time series methodology was adopted in order to find long-run dynamics. The study’s results indicate one way Granger causality between consumer credits and current account deficit [6]. Karahan and Uslu analyzed relationship between credits extended by deposit banks to the private sector and current accounts deficit by using ARDL approach within time series framework. They found long-term relationship between variables [7]. Güneş and Yıldırım analyzed long-run relationship between credit expansion and current account deficit by using Johansen cointegration test. The results indicate existence of cointegration relation between vehicle and corporate loans and current account deficit [8]. Kılıç and Torun studied causality relation between consumer credits and inflation by using Granger causality test. The findings of the study gave evidence on two-way Granger causality relation between individual credit cards and inflation [9]. Köroğlu analyzed relation between credit expansion and current account deficit by using Granger causality test. He found one-way causality relation that credit expansion causes current account deficit [10]. Varlık investigated the effect of net and gross capital inflows and their components on credit boom by using logit model. The findings addressed that net and gross foreign direct investment inflows are negatively correlated with credit boom [11].
\nThere is an extensive literature in Turkey examining the impact of credit expansion on macroeconomic factors. However, there is no study investigating the effect of credit expansion on liquidity risk by directly considering banks. The aim of this study is to fill this gap in the literature by using the panel data approach.
\nThis study examines long-run relation among liquidity risk and credit expansion. For this purpose, quarterly panel data was used in order to conduct analysis. Selected variables of 20 Turkish banks from 2014.Q1 to 2017.Q4 were obtained from the database of The Banks Association of Turkey in order to calculate liquidity risk and credit expansion from banks’ balance sheet. The banks used in the study can be analyzed in three different groups. These are state-owned deposit banks, private-owned deposit banks, and foreign banks. Halkbank, Ziraat Bank, and Vakıf Bank were taken as state-owned deposit banks. Akbank, Fibabank, Şekerbank, Turkish Bank, Turkish Economy Bank, İş Bank, and Yapı Kredi Bank were used as private-owned deposit banks. Alternatif Bank, Arab Turkish Bank, Burgan Bank, Denizbank, ICBC Turkey Bank, ING Bank, QNB Finansbank, and Garanti BBVA Bank were taken as foreign banks. These banks constitute the units of the panel data set.
\nIn this study, the ratio of the difference of loans and receivables from deposits to total assets was used as a measure of liquidity risk (LR) [12].
\nThe increase in credits, which causes an increase in production, income, exports, and profits of the financial sector, is expressed as credit expansion. Credit expansion (CE) which is the other variable of interest was created using equation below [13].
\nThe main purpose of this study is to explore long-run relationship among liquidity risk and credit expansion in the Turkish banking sector. This study adopts dynamic panel econometric methodology. It consists of four steps. First, the cross-sectional dependence of the units (banks) is investigated with the Pesaran CDLM test developed by Pesaran [14]. Second, Delta tests are applied to analyze whether the parameters change according to the units. Third, CIPS panel unit root test developed by Pesaran [15] is used to determine order of the integration of the variables. Finally, panel cointegration test developed by Westerlund [16] is conducted in order to explore the existence of the long-run relationship among the variables. In this section, theoretical background of methodology is explained.
\nOne of the important concepts that affects the choice of method to be used in dynamic panel data analysis is inter-units correlation. The inter-units correlation, in other words, cross-sectional dependence is the simultaneous correlation of series that may occur due to excluded, observed common factors, spatial spillover effects, and all common effects observed or not observed [17].
\nModel for panel data analysis can be written as in Eq. (3) [18]:
\nwhere i = 1…N denotes cross section dimension, which is banks here, t = 1…T, is time series dimension which is the quarterly period. \n
The null hypothesis (\n
Rejecting the null hypothesis shows existence of the cross-sectional dependence. Pesaran [14] proposed a simple cross-sectional dependence test that can be applied to heterogeneous panel series with both stationary and unit roots [14]. The test statistic, CD, is the average of the pairwise correlation coefficients of the ordinary least squares residuals obtained from the individual regression coefficients. The test statistic is calculated as Eq. (4) [19]:
\nwhere \n
Homogeneity means that constant and slope parameters do not change according to the units. Delta test which is an extension of Swamy S test is used to test homogeneity of parameters in this study. The purpose of the Swamy S test is to explore whether there is a difference between OLS estimator and weighted average matrices of within estimator. OLS estimator does not take into account panel structure of units. Conversely, within estimator considers panel-specific estimates with weighted average of parameters.
\nThe null hypothesis of Swamy S test is \n
Test statistic of Swamy [21] can be written as Eq. (5):
\n\n\n
Pesaran and Yamagata [22] developed Swamy test by two different test statistics [22]. These two statistics differ according to the size of sample. They are delta (\n
in which \n
The first factor to be considered in panel unit root tests is whether the units forming the panel are correlated to each other. According to the existence of correlation between units, panel unit root tests are divided into two as first- and second-generation tests. Levin et al., Harris and Tzavalis, Breitung and Hadri are first-generation unit root tests that do not take into account cross-sectional dependence [24, 25, 26, 27]. In these tests, all units are assumed to have a common autoregressive parameter. However, an autoregressive parameter changing according to the units is a more realistic approach. The second-generation unit root tests have been developed for this purpose. They deal with cross-sectional dependence in three different ways. First, first-generation unit root tests were transformed by reducing the correlation between the units by taking the difference from the cross-sectional averages, but unable to eliminate some types of correlation. As a result, these versions of tests are not used much in the literature [28]. Second, there are panel unit root tests such as the multivariate augmented Dickey-Fuller (MADF) panel unit root test and seemingly unrelated augmented Dickey-Fuller (SURADF) panel unit root test based on system estimation [29, 30, 31, 32]. Third, there are panel unit root tests that eliminate cross-sectional dependence by modeling it via common factor [15, 33, 34, 35, 36, 37, 38, 39, 40].
\nIn this study, since the cross-sectional dependence was determined among the banks forming the panel, the stationarity of the series was tested by using the second-generation panel unit root tests. Cross-sectionally augmented Im, Pesaran, and Shin (CIPS) unit root test developed by Pesaran [15] was used to in order to determine stationarity of the series. CIPS unit root test is an extension of Im, Pesaran, and Shin (2003) unit root test. This method adds cross-sectional averages of the lagged series and first differences of series as factors to DF or ADF regression to eliminate correlation between units [15]. Dynamic heterogenous panel data model without autocorrelation is as Eq. (9).
\n\n\n
where \n
in which \n
The unit root hypothesis of interest is: \n
where \n
Cointegration is the long-run equilibrium relationship between the variables despite permanent shocks affecting the system. Panel cointegration tests were developed to investigate long-run relationship in the panel data. They can be divided into two according to the existence of cross-sectional dependence. First-generation panel cointegration tests (Kao (1999); Pedroni (1999, 2004); McCoskey and Kao (1998); [16]) do not take into account correlation between units, while second-generation tests [16] with bootstrapping critical values (Gengenbach, Urbain and Westerlund (2016)) do. In this study, Westerlund [16] cointegration test was used to investigate long-run relationship between variables.
\nWesterlund [16] is an error-correction based panel cointegration test. In the test, the presence of long-run relationship is explored by deciding whether each unit has its own error correction [16]. So rejecting hypothesis of interest shows that there is not error correction and it means absence of the long-run relationship between variables. Error correction model is shown in Eq. (14) [41]:
\n\nEq. (14) can be rewritten as below:
\nwhere \n
in which SE denotes the standard error of \n
The rejection of the hypothesis of interest (\n
where \n
The aim of this study is to examine the long-term relationship between liquidity risk and credit expansion for the period from 2014.Q1 to 2017.Q4 using data from 20 banks in the Turkish banking sector. Since biased results can be obtained due to correlation between units forming panel data, the presence of cross-sectional dependence should be tested first. In this context, the presence of cross-sectional dependence of residuals obtained from error correction model and cross-sectional dependence of the liquidity risk and credit expansion variables were tested by Pesaran [14] CD test. The test results are given in Table 1.
\n\n | LR | \nCE | \nModel | \n|||
---|---|---|---|---|---|---|
Statistic | \np-Value | \nStatistic | \np-Value | \nStatistic | \np-Value | \n|
CD [14] | \n3.88 | \n0.000 | \n3.84 | \n0.000 | \n0.54 | \n0.589 | \n
Test results of cross-sectional dependence.
According to the results represented in Table 1, the null hypothesis of cross-sectional dependence test states no correlation between units. There is enough evidence to reject the null hypothesis at 1% significance level for variables. It means that second-generation unit root tests are more appropriate in order to decide whether variables are stationary or not. However, test result for the residuals obtained from error correction model fails to reject the null hypothesis at any significance level. This result provides support for presence of cross-sectional independence in the error correction model. In this case, first-generation panel cointegration tests should be used. Westerlund [16] was chosen to explore long-run dynamics. However, Homogeneity tests should be realized before applying Westerlund [16]. If panel is homogenous then Westerlund’s [16] results are valid. For this purpose, Pesaran and Yamagata [22] homogeneity test was applied to error correction model. Test results are given in Table 2.
\n\n | Statistic | \np-Value | \n
---|---|---|
\n\n | \n−0.417 | \n0.676 | \n
\n\n | \n−0.590 | \n0.555 | \n
Test results of homogeneity tests.
There is not enough evidence to reject the null hypothesis of homogeneity tests at any significance level with respect to results presented in Table 2. The results indicate strong evidence for homogeneity of slope coefficients. Therefore, Westerlund [16] is suitable to explore cointegration relation if variables are nonstationary. Pesaran [15] CIPS unit root test was used in order to examine stationarity of variables. Table 3 reports results of the CIPS unit root test for level and first difference of variables.
\nVariables | \nDeterministic term | \nPesaran CIPS statistic [15] | \n
---|---|---|
LR | \nIntercept only | \n−2.198 | \n
\n\n | \nIntercept only | \n−4.421\n***\n\n | \n
CE | \nIntercept only | \n−1.780 | \n
\n\n | \nIntercept only | \n−3.991\n***\n\n | \n
Test results of CIPS unit root test.
Indicates that the results can reject the null hypothesis at 1% significance level. The relevant 1% critical value for the cross-sectionally augmented Dickey-Fuller (CADF) statistic suggested by Pesaran is −2.1 [15].
Note: Deterministic term was chosen by exploring graphs by panel.
\n\n
The test results in Table 3 fail to reject the null hypothesis of CIPS unit root test in level of all variables. This result gives evidence of non-stationarity of variables. It means that a shock in the economy has permanent effect on liquidity risk and credit expansion. However, the results provide support for stationarity of variables after differencing them. Liquidity risk and credit expansion are integrated of order 1 (I(1)). Due to integration level of variables, panel cointegration relation can be analyzed. Selection of appropriate panel cointegration method depends on cross-sectional dependence and homogeneity of residuals. Westerlund [16] cointegration test was chosen due to homogeneity and cross-sectional independence of residuals. Westerlund’s [16] null hypothesis indicates that there is not long-term relation between variables. Four statistics were calculated in Westerlund [16]. Test results were given in Table 4.
\nTest statistic | \nTest value | \nz-Value | \np-Value | \n
---|---|---|---|
\n\n | \n−2.943 | \n−5.785 | \n0.000 | \n
\n\n | \n−14.235 | \n−5.804 | \n0.000 | \n
\n\n | \n−10.502 | \n−3.857 | \n0.000 | \n
\n\n | \n−7.343 | \n−2.912 | \n0.002 | \n
Test results of Westerlund [16] cointegration test.
Westerlund [16] cointegration test results show rejection of the null hypothesis for all statistics. It points out that there is a long-term relationship between liquidity risk and credit expansion. Since the variables are cointegrated, long-run relationship can be estimated. Eq. (18) was estimated by the PDOLS estimation method developed by Kao and Chiang [42] in order to investigate the effect of credit expansion on liquidity risk in the long run. The estimation results were given in Table 5.
\nLR | \nCoefficient | \nz-Value | \n
---|---|---|
CE | \n1.31 (0.133) | \n9.82\n***\n\n | \n
\n\n | \n96.50\n***\n\n | \n\n |
Estimation results of long-run relation model.
Indicates significant at 1% level.
Note: Standard error is given in brackets.
The Wald statistics in Table 5 is significant at 1% level. It means that model is generally significant. The estimated parameter is the long-term parameter and it is statistically significant at 1% level. Therefore, the credit expansion affects the liquidity risk in the long run. This means that 1% increase in credit expansion increases liquidity risk by 1.31%.
\nBanks convert short-term assets received from depositors to long-term debt for borrowers. Therefore, banks try to maximize their expected profits by considering the risks that may arise from their activities. The concept of risk here is the state of uncertainty, which is uncertain but effective on institutional goals. Liquidity risk is one of the important risks faced by banks. Therefore, many studies on liquidity risk have been conducted in the literature. However, while assets and liabilities are two important components that constitute a bank’s balance sheet, a panel study investigating long-run relation between credit expansion and liquidity risk has not been conducted in Turkey. This study aims to fill this gap in the literature. Panel cointegration approach was adopted in order to explore long-run dynamics. First, two important factors in panel methodology which are cross-sectional dependence and homogeneity were investigated properly. Pesaran [14] CD test was applied to the variables and error correction model in order to decide whether there is a cross-sectional dependence between units. The null hypothesis of Pesaran [14] CD test which states that there is a dependence between units was rejected for the variables, while it was not rejected for the model. It indicates that there is no cross-sectional dependence in the residuals of error correction model. Similarly, Delta test for large and small samples were conducted in order to determine homogeneity. The null hypothesis of homogeneity was not rejected. It indicates homogeneity of constant and slope coefficients. This result shapes dynamic panel methodology structure of the study. While there is an evidence on cross-sectional dependence in the variables, cross-sectionally augmented Im-Pesaran-Shin panel unit root test was used to determine integration level of variables. One of the strengths of this test is that it takes the cross-sectional averages of the lagged levels and first differences of the individual series instead of taking difference from the estimated common factors. According to the test results, variables were found to be nonstationary. Since the first order difference of both variables was stationary, existence of the long-run relation between two variables were explored by using Westerlund’s [16] paper. Four test statistics were calculated in order to decide whether there is a cointegration relation or not. The null hypothesis which shows long-run relation between variables was rejected according to the test statistics. It allows us to estimate long-run effects. Long-run relation model was estimated by using PDOLS estimator. Model was found statistically significant at 1% level. Also, coefficient of explanatory variable which is credit expansion is found statistically significant at 1% level. Sign of the coefficient is positive. It indicates positive correlation between variables. According to this correlation relation, a growth in credit expansion leads an increase in liquidity risk which affects the costs and returns of banks. This result shows importance of credit expansion on risk management. Because, uncontrolled credit expansion leads to the financial fragility of banks. This study’s findings suggest that the banks may limit their credit growth strategy in order to control liqudity risk [43].
\nAll Works published by IntechOpen prior to October 2011 are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported license (CC BY-BC-SA 3.0). Works published after October 2011 are licensed under a Creative Commons Attribution 3.0 Unported license (CC BY 3.0), the latter allowing for the broadest possible reuse of published material.
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