**3. Results**

Figure 1 shows the chemical moieties, related abbreviations and the adopted labelling scheme; Figure 2 reports the GC-FID profile referring to the CSO extracted in our laboratory and Figure 3 represents the 13C-NMR profile of EVOO and CSO in the unsaturated region (127–131 ppm) along with the relative assignment witnessing the presence of the *cis*-vaccenic ester. As easily foreseeable, other NMR spectral regions also clearly showed *cis*-vaccenic resonances; however, a total assignment of 18 13C carbon atoms was challenged by the many overlaps. Previous pioneering studies pointed out the challenging quantitative decoding of the mono-unsaturated fatty esters mixture in EVOOs [23]. Specifically, other minor mono-unsaturated fatty esters (MUFE) were taken into account; beyond the oleic (O) are also considered cis-vaccenic (V), eicosenoic (E) and palmitoleic (PO) [24,25]. On the other hand, data coming from known EVOOs compositions, limit the quantitative contribution of E and PO below 1% [9] and it is consistently witnessed by the lack of defined resonances in the regions where these esters should not have overlap with other similar constructs. The Multiple Assignment Recovered Analysis (MARA-NMR) takes advantage of any spectral section also overcoming the overlap issues hampering, so far, the independent quantification of mono-unsaturated fatty esters. Specifically, in this case, MARA-NMR processing definitely led to the detection and quantification of the V esters (consistently all over the recorded spectral span). Among the 20 variables feed out from MARA-NMR whose code is reported in Table 1, we herein have restricted our considerations to the most meaningful 11 variables reported in Table 2 along with the relative standard deviation.

With respect to the other studies [24,25] the new information remarkably smooths discrepancies between 1H and 13C-NMR as the mono-unsaturated fatty esters contribution in 1H-NMR matches the contribution of O and V esters, which actually should be also somewhat enhanced by the minor PO and E esters' contribution. Because of the tricky GC-FID resolution between V and O, also referred to in the European regulation (which suggests to report the whole V+O contribution), it is not always possible to compare GC and NMR data. However, the new available data, display the best fitting so far obtainable (Figure 4) concerning the measurements of mono-unsaturated (O + V + PO), saturated (P + S), di-unsaturated (L) and tri-unsaturated (Ln) fatty esters. The average V contribution is around 3% and it is consistent with previous NMR [23] and GC-FID [26] analyses; on the other hand, we think that MARA-NMR is the most versatile method suitable for serial processing of several samples and data. We think that this remarkable parameter in EVOOs cannot be ignored, since it is not constant by shifting from sample to sample, therefore it could assess specific features of different food products. The V quantification is not a marker for this study according to Table 2; however, it will trigger many important statistical considerations.

**Figure 1.** Chemical scheme of the fatty esters commonly found in olive oils with relative abbreviation. Usually these acyl residues are esters of the glycerol moiety. The labelling scheme of carbon atoms is adopted in this paper for assignments and discussion.

This enlightened an important piece of information concerning the *cis*-vaccenic ester as main compound in CSO but also as relevant ester contributing to the EVOO mixture. This last element was incredibly ignored so far. Table S1 (Supplementary Materials) reports the extended panel of 20 quantitative variables considered in the study for 33 samples (see details in Supplementary Materials). These values are obtained by MARA-NMR—a post-processing algorithm working over the two experiments A and B type.

**Figure 2.** Expanded region of interest in the gas-chromatographic flame ionization detection (GC-FID) profile for *Capparis spinosa* oil; oleic (O) and *cis*-vaccenic (V) methyl esters are resolved for the quantification. In the case of extra-virgin oil the O peak is around 20 times more than V. Other labelled signals are linolenic (Ln), linoleic (L) and stearic (S) esters

**Figure 3.** 13C-NMR profiles for olive oil (EVOO) in gray and capparis seed oil (CSO) in black. All the assignments for oleic (O), linoleic (L) linolenic (Ln) and *cis*-vaccenic (V), with the number representing carbon atom position respect to the 1 carboxyl position, are pretty known and coherent with quantitative and literature data.

**Figure 4.** Comparison between MARA-NMR and GC-FID measured quantitative parameters referred to: (**A**) mono-unsaturated (MUFA), (**B**) saturated (SFA), (**C**) Linoleic (L) and (**D**) Linolenic (Ln) esters in relative percent ratio.


*Edited by Theodore V. Hromadka II and Prasada Rao*

In this book, an attempt is made to highlight the recent advances in Hydrology. The several topics examined in this book form the underpinnings of larger-scale considerations, including but not limited to topics such as large-scale hydrologic processes and the evolving field of Critical Zone Hydrology. Computational modeling, data collection, and visualization are additional subjects, among others, examined in the set of topics presented.

Published in London, UK © 2021 IntechOpen © LamiadLamai / iStock

Hydrology

Hydrology

*Edited by Theodore V. Hromadka II and Prasada Rao*


**3. Cardiometabolic research**

#### **3.1 Strides**

*Cardiac Diseases - Novel Aspects of Cardiac Risk, Cardiorenal Pathology and Cardiac Interventions*

phenotypes that appear protected from some of the adverse metabolic effects of excess body fat [28]. Disease risk may not be uniform across all obese phenotypes. The classification of an individual as "metabolically healthy" is not clearly defined, with 5 to more than 30 definitions documented across studies [28, 29]. In 2009, a harmonized definition for metabolic syndrome (MetS) was derived by The International Diabetes Federation Task Force on Epidemiology and Prevention, the National Heart, Lung, and Blood Institute, American Heart Association, World Heart Federation, International Atherosclerosis Society, and the International Association for the Study of Obesity [30]. According to this definition, participants who met ≥3 of the 5 abnormal criteria, excluding WC, were classified as having MetS and thus metabolically unhealthy and obese (MUO). These five components include high fasting blood glucose, high systolic and diastolic BP, elevated plasma triglyceride levels, low high-density lipoprotein cholesterol levels, and obesity (particularly central adiposity) [28, 30]. Obese participants who met 0, 1, or 2 of these criteria were classified as metabolically healthy but obese (MHO) [28, 31]. A classification of MHO should not be mistaken for metabolically unhealthy normal weight (MUN). These individuals are not phenotypically obese but share a metabolic profile similar to an overt obese person, including hyperinsulinemia, insulin resistance, and a predisposition to type 2 diabetes and premature CVD [32]. Studies suggest that MHO is a transient state and only a precursor to MUO [25, 33]. Data from longitudinal studies suggest that approximately 30% to nearly half of people with MHO transition back to MUO after 4 to 20 years of follow-up [28]. Indeed, in the absence of regular, systematic, and supervised diet and exercise programs, obese individuals with MHO profiles experience subsequent declines in

Differences in metabolic profiles of those with MHO versus MUO could be due to phenotypic characteristics that lower risk of MetS, such as lower visceral adiposity, higher birth weight, adipose cell size characteristics, and genetic markers of adipose cells [35]. Alternatively, differentiation of these metabolic profiles has been attributed to variations in physical activity and cardiorespiratory fitness levels [28, 31], diet (e.g., lower intake of sugar, sugar-sweetened beverages, and saturated fat in MHO than MUO), and lower adiponectin concentrations in MUO than MHO [28].

Recent studies have suggested that MHO profiles may not indicate a lower risk for mortality, particularly when compared to metabolically healthy normal weight [33], and lifestyle interventions (e.g., weight management and physical activity) should continue to be recommended to reduce total mortality in all obese individuals [35].

Obesity has a profound impact on the cost of health care. Direct costs refer to money consumed to treat obesity-related health problems such as hospitalization, medical consultations in outpatient clinics, and obesity-related medications [36]. Obesity is associated with increases in annual health-care costs of 36% and medication costs of 77% compared with being of normal weight [37]. In 2014, a pooled estimate of annual medical costs attributable to obesity was \$1901 in USD (ranging from \$1239–\$2582), accounting for approximately \$150 billion nationally, with variations in costs primarily driven by age and severity of obesity-related comorbid condition [6]. There are long-term negative economic consequences and indirect costs of obesity. Indirect costs refer to lost productivity or costs to the economy outside of the health sector. Childhood obesity is associated with truancy from school, even after controlling for key covariates [37]. According to the National Longitudinal Survey on Youth 1979 data, higher BMI in late-teen years was associated with 3.5% lower hourly wages for men and women [38]. Obese adolescents were also more likely to

**82**

cardiometabolic health [34].

**2.6 Other considerations of obesity**

Over the last 40 years, the decline in mortality from CVD in the U.S. has been a public health success story. In the U.S., coronary heart disease as a leading cause of death has fallen 60% from its peak in the mid-1960s, with similar declines observed in nearly all regions of the world, especially in high-income countries [41]. However, if we place a narrower focus on racial/ethnic subgroups, or select populations from developing countries, we find that progress has not been equally shared [41, 42].

The sharp decline in mortality rates has been fueled by swift progress in prevention and treatment efforts. These efforts include rapid declines in cigarette smoking, improved methods for treating and controlling HTN, the use of statins to lower circulating cholesterol levels, and limiting or preventing infarction through the use of sophisticated methods [43]. Other factors have resulted in decreases in the rate of CVD despite increases in BMI, such as improved treatment or changes in other risks [26]. Clinical interventions have also proven effective in treating and controlling major risk factors of CVD, such as high systolic BP, cholesterol, and fasting plasma glucose [26].

#### **3.2 Setbacks**

#### *3.2.1 Medicalizing obesity*

The medical profession and social constructionists profess different concepts of illness. The medical model approaches disease as a biological condition, universal and unchanging, independent of time or place; in contrast, social constructionists define illness as the social and cultural meaning of that condition [44].

The idea of obesity as a social and cultural construct has contributed to its shift from being viewed as a comorbidity that ultimately leads to more complex diseases to its own treatment as a chronic disease with a complex etiology. In 2013, the American Medical Association officially recognized obesity as a complex chronic or non-communicable disease requiring medical attention [5, 13, 45]. The medicalization of obesity has presented a setback in the progress toward combating obesity and its resulting morbidities. Treating obesity as a health outcome rather than a comorbid condition leading to a chronic disease influences policies to focus on medical solutions (e.g., gastric bypass surgeries or pharmacological treatment of obesity-related comorbidities) rather than social and environmental factors as primary drivers of obesity, such as health illiteracy, the role of nutrition-deficient product promotion by the food industry, or healthy food access in areas with high rates of OW/obesity [44]. Other observers have raised similar concerns, not only emphasizing medicalization's overexpansion of medicine's domain, but also proclaiming it to be a mechanism by which the pharmaceutical industry can increase markets [46]. These medical policy changes will thus further contribute to rising health care costs. The Food and Drug Administration similarly expresses concern that proposed obesity drugs themselves increase cardiovascular or other risks and may require changes to clinical research protocols [46]. By treating the medical and social narratives of obesity as mutually exclusive, we may indeed see a resurgence of CVD in the near future.

#### *3.2.2 Constructionist view of the obesity pandemic*

The concept of health, illness, and disease are defined differently based on various factors in society. A medical practitioner may define health in very different terms than social or cultural definitions. However, all modern concepts of health recognize health as more than the absence of disease, pointing toward a greater capacity of the individual for self-realization and self-fulfillment [47].

According to the WHO, health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity [48]. Other definitions of health can be found in three main models that include social, biomedical, and functional aspects. The social model places its focus on the social determinants of health and illness and argues that the way society is structurally organized affects the etiology of health and illness [49]. It highlights changes that need to be made by society, including health disparities by social class, occupation, race/ethnicity, gender, and income, in order to make the population healthier [49]. The biomedical model of health, currently dominant in medical practice, focuses on biological determinants playing a key role in explaining disease as a condition, primarily caused by external (e.g., physical, chemical, and microbiologic factors) or internal (e.g., vascular, immunologic, and metabolic) factors [50]. In this model, the physical or biological aspects of disease and illness serves as the focal endpoint and is associated with the diagnosis, cure, and treatment of disease. Lastly, functional medicine model focuses more on the dynamic functional processes that result in a person's disease and less with disease as the endpoint [51].

There are skeptics, primarily influenced by the social model of health, who assert the obesity epidemic, and even the idea of health itself, is socially constructed. Holland et al. view obesity as a construct propagated by scientific discourse, which functions within a context of social surveillance and bio-power, even though they acknowledge obesity rates as "social facts" and being obese as a reality [52]. The Association for Size Diversity and Health, an international professional organization and strong proponent of the HAES® movement, asserts that, "health exists on a continuum that varies with time and circumstance for each

**85**

*Obesity Acceptance: Body Positivity and Clinical Risk Factors*

individual. Health should be conceived as a resource or capacity available to all regardless of health condition or ability level, and not as an outcome or objective

Natalie Boero characterizes the obesity epidemic as a "postmodern epidemic," or "epidemics in which unevenly medicalized phenomena lacking a clear pathological basis get cast in the language and moral panic of "traditional" epidemics [54]." The "postmodern" and constructed labels given to the obesity epidemic are said to be justified due to there being no known discrete cause of obesity, having been attributed to a wide range of factors, from genetic predisposition, to socioeconomic factors (e.g., food quality/scarcity), to the built environment. Adding to this argument is the idea that obesity research tends to conflate overweight and obesity, largely attributable to a critical reliance on a fluid metric (due to its changing categories) to diagnose health [54] and issues with participant selection

The constructionist view of obesity, largely endorsed by sociologists and members

Body image involves a person's perceptions, thoughts, behaviors, and feelings regarding his or her appearance. There are several aspects of body image that can be explored: perceptual, attitudinal, and psychological [56]. Perceptual body image investigates the accuracy of body size estimations relative to its actual size. Attitudinal body image assesses an overall subjective satisfaction of the body, personal feelings and beliefs about the body, and avoidance of exposure of the body to others [56]. Finally, psychological measures combine one or more of these components. In all aspects, body image is a subjective concept and experience. Any aspect of body image an individual has of his or her body is pivotally determined by interactions within obesogenic environments [57], (social) media [58], fitness imagery [59], and sociocultural experiences [59–61]. For example, in a study examining the impact of different forms of inspirational fitness ("fitspiration") images on women's image of their bodies, the authors found that exposure to "fitspiration" images led to decreased body satisfaction and increased negative

Body image satisfaction also exhibits elasticity and can change throughout developmental periods. For example, adolescents display body image elasticity as they undergo the significant physical and psychological changes of puberty [56]. Other examples of groups who may pay special attention to body-related imagery and display sensitivity to media cues are pregnant women, bodybuilders, athletes, and people with eating disorders. Research suggests there are also qualitative differences in body image that vary between men and women, by age group, sexual

of fat activism, and those that treat obesity as a biomedical fact and health risk, undoubtedly occupy two poles of obesity scholarship. Both hold influence on how the public views and treats OW/obesity. Yet, how can we continue our public health campaign of reducing obesity while avoiding what members of the fat acceptance movement label as "fat shaming"? Is there still a platform wherein OW/obesity and its health ramifications can be publicly discussed from a biomedical perspective while also avoiding weight stigmatization? Until these questions are addressed, the contention between these two groups will remain and the growing popularity of body positivity and fat activism, without regard for the health risks that accompany obesity, will render the public health message of the health advantages of preventing

*DOI: http://dx.doi.org/10.5772/intechopen.93540*

of living [53]."

in study populations [55].

or treating obesity largely ignored.

**4. Body image**

mood over time [59].

orientation, and race/ethnicity [56, 62].

*Obesity Acceptance: Body Positivity and Clinical Risk Factors DOI: http://dx.doi.org/10.5772/intechopen.93540*

individual. Health should be conceived as a resource or capacity available to all regardless of health condition or ability level, and not as an outcome or objective of living [53]."

Natalie Boero characterizes the obesity epidemic as a "postmodern epidemic," or "epidemics in which unevenly medicalized phenomena lacking a clear pathological basis get cast in the language and moral panic of "traditional" epidemics [54]." The "postmodern" and constructed labels given to the obesity epidemic are said to be justified due to there being no known discrete cause of obesity, having been attributed to a wide range of factors, from genetic predisposition, to socioeconomic factors (e.g., food quality/scarcity), to the built environment. Adding to this argument is the idea that obesity research tends to conflate overweight and obesity, largely attributable to a critical reliance on a fluid metric (due to its changing categories) to diagnose health [54] and issues with participant selection in study populations [55].

The constructionist view of obesity, largely endorsed by sociologists and members of fat activism, and those that treat obesity as a biomedical fact and health risk, undoubtedly occupy two poles of obesity scholarship. Both hold influence on how the public views and treats OW/obesity. Yet, how can we continue our public health campaign of reducing obesity while avoiding what members of the fat acceptance movement label as "fat shaming"? Is there still a platform wherein OW/obesity and its health ramifications can be publicly discussed from a biomedical perspective while also avoiding weight stigmatization? Until these questions are addressed, the contention between these two groups will remain and the growing popularity of body positivity and fat activism, without regard for the health risks that accompany obesity, will render the public health message of the health advantages of preventing or treating obesity largely ignored.

#### **4. Body image**

*Cardiac Diseases - Novel Aspects of Cardiac Risk, Cardiorenal Pathology and Cardiac Interventions*

The idea of obesity as a social and cultural construct has contributed to its shift from being viewed as a comorbidity that ultimately leads to more complex diseases to its own treatment as a chronic disease with a complex etiology. In 2013, the American Medical Association officially recognized obesity as a complex chronic or non-communicable disease requiring medical attention [5, 13, 45]. The medicalization of obesity has presented a setback in the progress toward combating obesity and its resulting morbidities. Treating obesity as a health outcome rather than a comorbid condition leading to a chronic disease influences policies to focus on medical solutions (e.g., gastric bypass surgeries or pharmacological treatment of obesity-related comorbidities) rather than social and environmental factors as primary drivers of obesity, such as health illiteracy, the role of nutrition-deficient product promotion by the food industry, or healthy food access in areas with high rates of OW/obesity [44]. Other observers have raised similar concerns, not only emphasizing medicalization's overexpansion of medicine's domain, but also proclaiming it to be a mechanism by which the pharmaceutical industry can increase markets [46]. These medical policy changes will thus further contribute to rising health care costs. The Food and Drug Administration similarly expresses concern that proposed obesity drugs themselves increase cardiovascular or other risks and may require changes to clinical research protocols [46]. By treating the medical and social narratives of obesity as mutually exclusive, we may indeed see a resurgence of

The concept of health, illness, and disease are defined differently based on various factors in society. A medical practitioner may define health in very different terms than social or cultural definitions. However, all modern concepts of health recognize health as more than the absence of disease, pointing toward a greater capacity of the individual for self-realization and self-fulfillment [47]. According to the WHO, health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity [48]. Other definitions of health can be found in three main models that include social, biomedical, and functional aspects. The social model places its focus on the social determinants of health and illness and argues that the way society is structurally organized affects the etiology of health and illness [49]. It highlights changes that need to be made by society, including health disparities by social class, occupation, race/ethnicity, gender, and income, in order to make the population healthier [49]. The biomedical model of health, currently dominant in medical practice, focuses on biological determinants playing a key role in explaining disease as a condition, primarily caused by external (e.g., physical, chemical, and microbiologic factors) or internal (e.g., vascular, immunologic, and metabolic) factors [50]. In this model, the physical or biological aspects of disease and illness serves as the focal endpoint and is associated with the diagnosis, cure, and treatment of disease. Lastly, functional medicine model focuses more on the dynamic functional processes that result in a person's

There are skeptics, primarily influenced by the social model of health, who assert the obesity epidemic, and even the idea of health itself, is socially constructed. Holland et al. view obesity as a construct propagated by scientific discourse, which functions within a context of social surveillance and bio-power, even though they acknowledge obesity rates as "social facts" and being obese as a reality [52]. The Association for Size Diversity and Health, an international professional organization and strong proponent of the HAES® movement, asserts that, "health exists on a continuum that varies with time and circumstance for each

**84**

CVD in the near future.

*3.2.2 Constructionist view of the obesity pandemic*

disease and less with disease as the endpoint [51].

Body image involves a person's perceptions, thoughts, behaviors, and feelings regarding his or her appearance. There are several aspects of body image that can be explored: perceptual, attitudinal, and psychological [56]. Perceptual body image investigates the accuracy of body size estimations relative to its actual size. Attitudinal body image assesses an overall subjective satisfaction of the body, personal feelings and beliefs about the body, and avoidance of exposure of the body to others [56]. Finally, psychological measures combine one or more of these components. In all aspects, body image is a subjective concept and experience.

Any aspect of body image an individual has of his or her body is pivotally determined by interactions within obesogenic environments [57], (social) media [58], fitness imagery [59], and sociocultural experiences [59–61]. For example, in a study examining the impact of different forms of inspirational fitness ("fitspiration") images on women's image of their bodies, the authors found that exposure to "fitspiration" images led to decreased body satisfaction and increased negative mood over time [59].

Body image satisfaction also exhibits elasticity and can change throughout developmental periods. For example, adolescents display body image elasticity as they undergo the significant physical and psychological changes of puberty [56]. Other examples of groups who may pay special attention to body-related imagery and display sensitivity to media cues are pregnant women, bodybuilders, athletes, and people with eating disorders. Research suggests there are also qualitative differences in body image that vary between men and women, by age group, sexual orientation, and race/ethnicity [56, 62].


**9. Conclusions**

This review provides an efficient summary of multilevel inverters to emphasize the necessity for new or modified multilevel inverters for grid-connected sustainable solar PV systems. Firstly, this review presented a detailed survey of reduced switch count multilevel inverter (RSC-MLI) topologies, including their designs, typical features, limitations, assessment parameters, and selection for particular applications. Secondly, this review presented a comprehensive analysis of MLIs and a classification of the existing MLI topologies, along with their merits and demerits. Thirdly, this review also included a survey of SC-MLI topologies with a qualitative assessment to aid in the direction of future research due to their variety of applications such as inductor-less or transformer-less operation, enhanced voltage output, improved voltage regulation, low cost, reduced circuit components, size, and less electromagnetic interference. Lastly, this review serves as a valuable resource for

engineers and researchers because it provides a detailed look at parametric comparisons of the total number of power semiconductor switches, DC sources, passive elements, total standing voltage, reliability assessment, applications, challenges, and recommendations.

**Author Contributions:** Conceptualization and methodology, S.N.; validation, D.C.; formal analysis, S.N.; investigation, D.C.; resources, D.C.; data curation, S.N.; writing—original draft preparation, S.N.; writing—review, S.N.; editing, D.C.; visualization, D.C.; supervision, D.C.; project administration, D.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Data Availability Statement:** This review has no information related to it.

**Acknowledgments:** The authors further thank the Vellore Institute of Technology in Vellore, India, for their assistance and also the authors wish to thank the particular copyright holders for allowing approval to use the pictures, graphics, tables, and figures in this work.

**Conflicts of Interest:** The authors declare no conflict of interest.