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martes, 30 de abril de 2019

Peptide exploits Achilles’ heel of Zika virus


- Science and Technology

Peptide exploits Achilles’ heel of Zika virus

https://www.patternhanging.com/2019/04/16/peptide-exploits-achilles-heel-of-zika-virus/?fbclid=IwAR2ZiIl9Z7ydYF2iu8kSKrOR0FqKZRAien7Tzn8TxgBPt0VnMtlvEKXU1es

Illustration of the research finding. Credit: NTU Singapore
Scientists at Nanyang Technological University, Singapore (NTU Singapore) have engineered an antiviral peptide that exploits the Zika virus at its Achilles’ heel—the viral membrane—hence stopping the virus from causing severe infections.
This new method of attacking the viral membrane focuses on directly stopping Zika virus particles rather than preventing the replication of new virus particles, and can potentially work against a wide range of membrane-enveloped viruses.
When administered in Zika-infected mice in the lab, the engineered peptide drug (a compound consisting of amino acids) reduced disease symptoms and the number of deaths. Importantly, the peptide was able to cross the nearly impenetrable blood-brain barrier to tackle viral infection in mouse brains and protect against Zika injury, a critical feature since Zika targets the brain and central nervous system.
The research team led by NTU Singapore’s Associate Professor Nam-Joon Cho published their findings in the peer-reviewed journal Nature Materials on 22 October 2018.
The study, done in collaboration with the Federal University of Minas Gerais (UFMG) in Brazil and Ghent University in Belgium, spanned over six years and combined materials engineering, antiviral drug development, and pharmacology.
“There are currently no vaccines for the Zika virus, while available medicines only alleviate symptoms such as fever and pain,” said Associate Professor Cho of NTU’s School of Materials Science and Engineering. “This newly created peptide holds great promise in becoming a future antiviral drug that can act directly on viral infections in the brain.”
The Zika virus is transmitted by Aedes mosquitoes and infections during pregnancy are linked to birth defects such as microcephaly, a condition in which a baby is born with an abnormally small head and brain. The World Health Organisation declared the Zika disease an international emergency in 2016, and it remains a large threat globally today.
How the engineered antiviral peptide works
In 2004, Associate Professor Cho developed the first antiviral peptide that works against viral membranes in laboratory tests. Since then, NTU scientists have studied how antiviral peptides can create pores that form in membranes made up of two layers of lipids (a component of fats).
Over the years, the team studied the peptide’s interactions with lipid membranes and engineered new peptides with greater potency and improved pharmacological properties. These findings led them to test a particularly promising peptide in Zika-infected mice and also showed that it ruptured other similar-sized enveloped viruses in the laboratory, such as dengue and chikungunya.
“The peptide differentiates between Zika viral membranes and mammalian cell membranes because the virus particles are much smaller and more curved, while the mammalian cells are larger and flatter. Like how a pin pricks a balloon, the peptide pricks a hole in the viral membrane. Prick enough holes, and the virus will be ruptured,” said Associate Professor Cho.
Lab tests showed that when the peptide was administered, 10 out of 12 infected mice survived. In comparison, all the mice in the control group died within a week post-infection. In addition, therapeutic concentrations of the peptide were able to cross the blood-brain-barrier, allowing it to inhibit viral infection in the brain.
“The exciting antiviral results validate the potential of this innovative therapeutic strategy and are further enhanced by the engineered peptide’s ability to cross the blood-brain barrier,” said Jeffrey S. Glenn, a professor of medicine, microbiology and immunology at Stanford University, who is not part of the study. Professor Glenn is also a former member of the US FDA Antiviral Drugs Advisory Committee.
Fresh approach in targeting viruses
In general, most antiviral drugs target the replication process of viruses. However, viruses often mutate quickly and antiviral drugs that target viral replication can become obsolete. Attacking the physical structure of enveloped viruses is a new approach to developing antiviral drugs. It offers promise for the peptide to be effective even if the Zika virus attempts to mutate.
Associate Professor Cho said, “There are instances where a virus mutation can lead to an epidemic in a short time, leaving communities unprepared. By targeting the lipid membrane of virus particles, scientists may devise more robust and effective ways to stop viruses.”
The Zika virus belongs to the Flaviviridae family and is related to other mosquito-borne viruses like dengue, chikungunya and yellow fever. As all flaviviruses have virus particles that are around 40-55 nanometres in diameter and are enveloped by a lipid membrane, the peptide engineered by the scientists from NTU Singapore has the potential to work against these viruses too.
Laboratory tests in this study confirm this potential and in future, the research team intends to study the effects of the peptide on diseases caused by these other viruses in greater detail. The team will also conduct trials in larger animals, and subsequently will plan to initiate human clinical trials, once relevant preclinical studies are completed and regulatory approvals obtained.
“This work represents a paradigm-changing breakthrough in the field of antiviral drug design,” commented Professor William C. Wimley, an antimicrobial peptide expert from Tulane University in the United States, who is not part of the study.
“It shows how the viral envelope, a novel target in antiviral drug design, can specifically be targeted by a peptide. It also shows that a peptide targeting the viral envelope can effectively inhibit virus in the body, and even in the brain, an organ that actively excludes many therapeutics. Given the vast potential of peptides as antibacterial and antifungal agents, this may be a game-changing discovery that will be broadly applicable to the design of anti-infective drugs against many classes of pathogens.”
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https://www.patternhanging.com/2019/04/16/peptide-exploits-achilles-heel-of-zika-virus/?fbclid=IwAR2ZiIl9Z7ydYF2iu8kSKrOR0FqKZRAien7Tzn8TxgBPt0VnMtlvEKXU1es
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lunes, 29 de abril de 2019

Nutrition and Health – The Association between Eating Behavior and Various Health Parameters: A Matched Sample Study

Carnívoros más saludables que vegetarianos: estudio

https://www.uni-graz.at/en/university/

https://www.eluniversal.com.mx/menu/carnivoros-mas-saludables-que-vegetarianos-estudio?fbclid=IwAR3_RGB1ggOLBWYBdrHulw5e95MkYrwcbdNtakETbXzsgc8iQIjGALhxsx4

Nutrition and Health – The Association between Eating Behavior and Various Health Parameters: A Matched Sample Study

Population-based studies have consistently shown that our diet has an influence on health. Therefore, the aim of our study was to analyze differences between different dietary habit groups in terms of health-related variables. The sample used for this cross-sectional study was taken from the Austrian Health Interview Survey AT-HIS 2006/07. In a first step, subjects were matched according to their age, sex, and socioeconomic status (SES). After matching, the total number of subjects included in the analysis was 1320 (N = 330 for each form of diet – vegetarian, carnivorous diet rich in fruits and vegetables, carnivorous diet less rich in meat, and carnivorous diet rich in meat). Analyses of variance were conducted controlling for lifestyle factors in the following domains: health (self-assessed health, impairment, number of chronic conditions, vascular risk), health care (medical treatment, vaccinations, preventive check-ups), and quality of life. In addition, differences concerning the presence of 18 chronic conditions were analyzed by means of Chi-square tests. Overall, 76.4% of all subjects were female. 40.0% of the individuals were younger than 30 years, 35.4% between 30 and 49 years, and 24.0% older than 50 years. 30.3% of the subjects had a low SES, 48.8% a middle one, and 20.9% had a high SES. Our results revealed that a vegetarian diet is related to a lower BMI and less frequent alcohol consumption. Moreover, our results showed that a vegetarian diet is associated with poorer health (higher incidences of cancer, allergies, and mental health disorders), a higher need for health care, and poorer quality of life. Therefore, public health programs are needed in order to reduce the health risk due to nutritional factors.
Citation: Burkert NT, Muckenhuber J, Großschädl F, Rásky É, Freidl W (2014) Nutrition and Health – The Association between Eating Behavior and Various Health Parameters: A Matched Sample Study. PLoS ONE 9(2): e88278. https://doi.org/10.1371/journal.pone.0088278
Editor: Olga Y. Gorlova, Geisel School of Medicine at Dartmouth College, United States of America
Received: May 17, 2013; Accepted: January 9, 2014; Published: February 7, 2014
Copyright: © 2014 Burkert et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no support or funding to report.
Competing interests: The authors have declared that no competing interests exist.

Introduction

Our diet has an impact on our well-being and on our health. Studies have shown a vegetarian diet to be associated with a lower incidence of hypertension, cholesterol problems, some chronic degenerative diseases, coronary artery disease, type II diabetes, gallstones, stroke, and certain cancers [1]–[7]. A vegetarian diet is characterized by a low consumption of saturated fat and cholesterol, due to a higher intake of fruits, vegetables and whole-grain products [3], [4], [8]. Overall, vegetarians have a lower body mass index [1], [4], [5], [7], [9]–[12], a higher socioeconomic status [13], and better health behavior, i.e. they are more physically active, drink less alcohol, and smoke less [9], [13], [14]. On the other hand, the mental health effects of a vegetarian diet or a Mediterranean diet rich in fruits, vegetables, whole-grain products and fish are divergent [9], [15]. For example, Michalak et al. [16] report that a vegetarian diet is associated with an elevated prevalence of mental disorders. A poor meat intake has been shown to be associated with lower mortality rates and higher life expectancy [17], and a diet which allows small amounts of red meat, fish and dairy products seems to be associated with a reduced risk of coronary heart disease as well as type 2 diabetes [18]. Additionally, evidence concerning lower rates of cancer, colon diseases including colon cancer, abdominal complaints, and all-cause mortality is, however, inconsistent [5]–[7], [19]–[22].
Not only is the intake of certain nutrients, like red meat, associated with an increased health risk [18], [23]–[26], high-caloric intake also plays a crucial role [23], [27]. Moreover, there seems to be proof that lifestyle factors like physical activity may be more crucial in lowering disease rates than individual dietary habits [20], [28]–[29]. While, generally speaking, diets based on plants, like vegetarian diets, seem to be associated with a certain health benefit, a lower risk to contract certain chronic diseases [30], and the ability to improve health [31]–[32], restrictive and monotonous vegetarian diets include the risk of nutritional deficits [2], [18], [19], [30], [33]. Baines et al. [9] report that vegetarians take more medication than non-vegetarians.
To summarize, a number of studies have shown vegetarian diets and diets with poor meat intake to be associated with lower mortality rates for certain diseases. Research about the dietary habits in Austria is, however, rather sparse and mainly focused on genetic factors [33]–[36]. Therefore, the aim of this study was to investigate health differences between different dietary habit groups among Austrian adults.

Methods

Study Design and Study Population

The sample for this cross-sectional study was taken from the Austrian Health Interview Survey (AT-HIS) which ran from March 2006 to February 2007 [37]. The AT-HIS is a standardized survey which is conducted at regular intervals in Austria (currently every eight years). The subjects included in the survey form a representative sample of the Austrian population. They were chosen from the central population register and are distributed across the different geographic regions of Austria. The AT-HIS is part of the European Health Interview Survey (E-HIS; http://www.euhsid.org), an important high-quality survey. The interviews were conducted by free-lancers engaged by the Austrian Statistic Agency. To ensure that all interviews were conducted in the same way, interviewers had to participate in a training day where they were instructed on how to conduct the survey. Time measurement, non-response analyses, and analyses of error dialogs were performed in order to ensure consistency between interviewers. Additionally, all interviewers were supervised by field supervisors. Overall, 15474 individuals, aged 15 years and older, were questioned in computer-assisted personal interviews (CAPI; 54.7% female; response rate: 63.1%).
While 0.2% of the interviewees were pure vegetarians (57.7% female), 0.8% reported to be vegetarians consuming milk and eggs (77.3% female), and 1.2% to be vegetarians consuming fish and/or eggs and milk (76.7% female). 23.6% reported to combine a carnivorous diet with lots of fruits and vegetables (67.2% female), 48.5% to eat a carnivorous diet less rich in meat (60.8% female), and 25.7% a carnivorous diet rich in meat (30.1% female). Since the three vegetarian diet groups included a rather small number of persons (N = 343), they were analyzed as one dietary habit group. Moreover, since the vegetarian group was the smallest, we decided to match each of the vegetarians (1) with an individual of each other dietary habit group (carnivorous diet rich in fruits and vegetables (2), carnivorous diet less rich in meat (3) and a carnivorous rich in meat (4)).

Matching Process

In a first step, subjects consuming a vegetarian diet were identified (N = 343). All vegetarians were categorized according to their sex, age (in age-groups spanning 5 years, e.g. 20- to 24-year-olds), and socioeconomic status (SES). Each such vegetarian was then matched with one subject consuming a carnivorous diet rich in fruits and vegetables, one individual eating a carnivorous diet less rich in meat, and one subject consuming a carnivorous diet rich in meat. Only 96.2% of the vegetarians were included in the analyses, since not all of them corresponded to a subject of the same sex, age, and SES from a different dietary habit group. Therefore, the total number of analyzed subjects was 1320 (comprising 330 vegetarians, 330 subjects consuming a carnivorous diet rich in fruits and vegetables, 330 individuals eating a carnivorous diet less rich in meat, and 330 subjects consuming a carnivorous diet rich in meat). Each dietary habit group was set-up according to the demographic characteristics shown in Table 1.
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Table 1. Data definition and structure for each of the four dietary habit groups.
https://doi.org/10.1371/journal.pone.0088278.t001

Ethical Approval

The study was carried out in compliance with the principles laid down in the Helsinki Declaration. No minors or children were included in the study. Verbal informed consent was obtained from all subjects, witnessed, and formally recorded. The Ethics Committee of the Medical University of Graz approved the consent procedure as well as the conductance of this study (EK-number: 24–288 ex11/12).

Variables and Measurements

Face-to-face interviews were conducted by questioning the subjects about their socio-demographic characteristics, health-related behavior, diseases, medical treatments, and also psychological aspects.
The independent variable in this study was the dietary habit of individuals. Concerning eating behavior, the respondents were given a list of six different dietary habits and asked which one describes their eating behavior best (1 = vegan, 2 = vegetarian eating milk/eggs, 3 = vegetarian eating fish and/or milk/eggs, 4 = carnivorous diet rich in fruits and vegetables, 5 = carnivorous diet less rich in meat, 6 = carnivorous diet rich in meat). Participants described their dietary habit, without interviewers giving a clear definition of the various eating categories. Since, overall, only 2.2% of all participants consumed a vegetarian diet, these individuals were analyzed as one dietary habit group. We created a scale that would reflect the animal fat intake for each dietary habit (1 = vegetarian diet, 2 = carnivorous diet rich in fruits and vegetables, 3 = carnivorous diet less rich in meat, 4 = carnivorous diet rich in meat).
Since age, sex, and the socioeconomic background of subjects all have an influence on health [38]–[41], we matched the subjects according to these variables in order to control for their influence. The SES of the subjects (ranging between 3 and 15) was calculated using the following variables: net equivalent income, level of education, and occupation. Net equivalent income was calculated based on an equivalence scale provided by the OECD [42], and divided by quintiles. Level of education was measured by an ordinal variable, distinguishing between (1) basic education (up to 15 years of age), (2) apprenticeship/vocational school, (3) secondary education without diploma, (4) secondary education with diploma, and (5) university education. The occupation of the subjects was differentiated into the following five levels: (1) unskilled worker, (2) apprentice/skilled worker, (3) self-employed/middle job, (4) qualified job/academic, (5) executive position. To verify the combination of variables that served to calculate the SES, correlations with the different variables were calculated. They ranged between r = .70 and r = .80.
The body mass index (BMI) and lifestyle factors (physical activity, smoking, and alcohol consumption) were included as covariates in all analyses. The BMI was calculated by dividing the weight of a person in kilograms by the square of their height in meters (kg/m2) [43]. Physical exercise was measured using the short version of the International Physical Activity Questionnaire (IPAQ), a self-reported instrument, which asks for an estimate of the total weekly physical activity (walking, moderate- and vigorous-intensity activity) performed during the last week. The short version of the IPAQ does not discriminate between leisure-time and non-leisure time physical activity. The total MET score was calculated by weighting the reported minutes per week within each activity by a MET energy expenditure estimate that was assigned to each category [44]. Smoking behavior was measured as the number of cigarettes smoked per day. Alcohol consumption was surveyed as the number of days on which alcohol was consumed during the last 28 days.
The dependent variables focusing on ill-health included self-perceived health, ranging from 1 (very good) to 5 (very bad), and impairment to health, ranging from 1 (very impaired) to 3 (not impaired). We further assessed the presence of 18 specific chronic conditions (asthma, allergies, diabetes, cataract, tinnitus, hypertension, cardiac infarction, apoplectic stroke, bronchitis, arthritis, sacrospinal complaints, osteoporosis, urinary incontinence, gastric or intestinal ulcer, cancer, migraine, mental illness (anxiety disorder or depression), and any other chronic condition). Each condition was coded as present (1) or absent (0). We calculated a total frequency score by summing up the chronic conditions present (0–18, sum index). Additionally, a vascular risk score was calculated by summing up the variables “hypertension”, “enhanced blood cholesterol level”, “diabetes”, and “smoking” (0–4, sum index). Each variable was coded as present (1) or absent (0).
A dependent variable concerning health care was created as the sum index of the number of doctors consulted in the last 12 months (0–8, sum index). Each of the 8 medical treatments (general practitioner, gynecologist, urologist, dermatologist, ophthalmologist, internist, orthopedist, and ENT physician) was coded as “consulted” (1) or “not consulted” (0). The number of vaccinations was analyzed by calculating a sum index combining 8 different vaccinations (influenza, tetanus, diphtheria, polio, FSME, pneumococci, hepatitis A and B; 0–8, sum index). Each vaccination was coded as present (1) or absent (0). In addition, preventive health care was analyzed by calculating a sum index of the variables “preventive check-ups”, “mammography”, “prostate gland check-up”, and “Papanicolaou test” (0–4, sum index). Each variable was coded as present (1) or absent (0).
The dependent variable concerning quality of life was measured using the short version of the WHOQOL (WHOQOL-BREF) [45]. Four domain scores (physical health, psychological health, social relationships, and environment) were calculated. These domain scores ranged between 4 and 20.

Statistical Analysis

In a first step subjects with different dietary habits (vegetarian, carnivorous diet rich in fruits and vegetables, carnivorous diet less rich in meat, carnivorous diet rich in meat) were matched according to their sex, age, and SES. Differences in lifestyle factors (BMI, total MET score, number of cigarettes smoked per day, and alcohol consumption in the last four weeks) between the different dietary habit groups were calculated by multivariate analysis of variance.
In order to analyze the differences between the dietary habit groups, multivariate analyses of variance were calculated for the three domains: (1) health (self-reported health, impairment due to health problems, number of chronic conditions, vascular risk), (2) health care (number of visits to the doctor, number of vaccinations, number of used preventive care offers), and (3) quality of life (physical and psychological health, social relationships, and environment). To address the bias of lifestyle factors impacting health, analyses of variance were calculated, controlling for the aforementioned lifestyle variables (BMI, physical activity, smoking behavior, and alcohol consumption).
In the domain of “health”, the two variables “self-reported health” and “impairment due to health problems” were originally assessed using an ordinal scale. Therefore, we controlled the results using non-parametric tests (Kruskal Wallis Test). Since the results were the same, only results of the analyses of variance are reported.
In addition, Chi-square tests were calculated for the aforementioned 18 chronic conditions in order to establish which one occurs significantly more often, depending on the form of nutrition. p-values <.050 were considered as statistically significant. All analyses were calculated using IBM SPSS software (version 20.0) for Windows.

Results

Participant Characteristics and Lifestyle Differences between the Dietary Habit Groups

In total, we analyzed the data of 1320 individuals (330 in each dietary habit group). Each dietary habit group was set-up according to the demographic characteristics shown in Table 1. Overall, 23.6% of all subjects were male and 76.4% female. 40.0% of the individuals were younger than 30 years, 17.8% between 30 and 39 years, 17.6% between 40 and 49 years, 9.4% between 50 and 59 years, 8.4% between 60 and 69 years, 4.4% between 70 and 79 years, and 2.4% than 80 years or older. 30.3% of the subjects had a low SES (they had an SES score of ≤6), 48.8% a middle one (SES between >6 and ≤10), and 20.9% had a high SES (SES>10).
Our multivariate analysis regarding lifestyle showed a significant main effect for the dietary habit of individuals (p = .000), showing that the different dietary habit groups differ in their overall health behavior. However, results of the univariate analyses showed that the dietary habit groups only differ concerning their BMI and their alcohol consumption.
Concerning BMI: vegetarians have the lowest mean BMI (M = 22.9), followed by subjects eating a carnivorous diet less rich in meat (M = 23.4), rich in fruits and vegetables (M = 23.5), and rich in meat (M = 24.9). Heavy meat eaters differ significantly from all other groups in terms of their BMI (p = .000).
Concerning physical exercise: no significant difference was found in the total MET score between the various dietary habit groups (p = .631).
Concerning smoking behavior: the number of cigarettes smoked per day did not differ between the various dietary habit groups (p = .302).
Concerning alcohol consumption: Subjects following a vegetarian diet (M = 2.6 days in the last 28 days) or a carnivorous diet rich in fruits and vegetables (M = 3.0 days) consume alcohol significantly less frequently than those eating a carnivorous diet less rich in meat (M = 4.4 days) or rich in meat (M = 4.8 days; p = .000).

Health Differences between the Dietary Habit Groups

In the domain of health, the multivariate analysis of variance showed a significant main effect for the dietary habit of individuals (p = .000). Overall, vegetarians are in a poorer state of health compared to the other dietary habit groups. Concerning self-reported health, vegetarians differ significantly from each of the other groups, toward poorer health (p = 000). Moreover, these subjects report higher levels of impairment from disorders (p = .002). Vegetarians additionally report more chronic diseases than those eating a carnivorous diet less rich in meat (p = .000; Table 2). Significantly more vegetarians suffer from allergies, cancer, and mental health ailments (anxiety, or depression) than the other dietary habit groups (Table 3). Subjects who eat a carnivorous diet rich in meat more often report urinary incontinence (p = .023). No differences between individuals consuming different forms of diet were found regarding their vascular risk (p = .150; Table 2).
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Table 2. Differences in health and health care between the different dietary habit groups.
https://doi.org/10.1371/journal.pone.0088278.t002
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Table 3. Differences in suffering from various chronic conditions between the different dietary habit groups.
https://doi.org/10.1371/journal.pone.0088278.t003

Differences in Health Care between the Dietary Habit Groups

Our multivariate analysis regarding health care has shown a significant main effect for dietary habits (p = .000) and confirmed that, overall, subjects with a lower animal fat intake demonstrate worse health care practices. Vegetarians and subjects eating a carnivorous diet rich in fruits and vegetables consult doctors more often than those eating a carnivorous diet less rich in meat (p = .003). Moreover, vegetarians are vaccinated less often than all other dietary habit groups (p = .005) and make use of preventive check-ups less frequently than subjects eating a carnivorous diet rich in fruits and vegetables (p = .033; Table 2).

Differences in Quality of Life between the Dietary Habit Groups

Regarding quality of life, the main effect of the multivariate analysis of variance showed no significant difference between the dietary habit groups (p = .291). The results obtained in the univariate analyses of variance, however, revealed that vegetarians have a lower quality of life in the domains of “physical health” (p = .026) and “environment” (p = .037) than subjects consuming a carnivorous diet less rich in meat. Moreover, vegetarians have a lower quality of life regarding “social relationships” than individuals eating a carnivorous diet rich in fruits and vegetables, or those with a carnivorous diet less rich in meat (p = .043). All results are shown in Table 4.
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Table 4. Differences in quality of life between the different dietary habit groups.
https://doi.org/10.1371/journal.pone.0088278.t004

Discussion

Overall, our findings reveal that vegetarians report poorer health, follow medical treatment more frequently, have worse preventive health care practices, and have a lower quality of life. Concerning the variable “eating behavior”, we tried to generate a variable that would reflect the animal fat intake (1 = vegetarian, 2 = carnivorous diet rich in fruits and vegetables, 3 = carnivorous diet less rich in meat, 4 = carnivorous diet rich in meat). The mean BMI of subjects is coupled in nearly linear progression with the amount of animal fat intake. This is in line with previous studies showing vegetarians to have a lower body mass index [1], [4], [5], [7], [9]–[12].
Our results have shown that vegetarians report chronic conditions and poorer subjective health more frequently. This might indicate that the vegetarians in our study consume this form of diet as a consequence of their disorders, since a vegetarian diet is often recommended as a method to manage weight [10] and health [46]. Unfortunately, food intake was not measured in more detail, e.g. caloric intake was not covered. Hence, further studies will be necessary to analyze health and its relationship with different forms of dietary habits in more detail.
When analyzing the frequency of chronic diseases, we found significantly higher cancer incidence rates in vegetarians than in subjects with other dietary habits. This is in line with previous findings, reporting that evidence about cancer rates, abdominal complaints, and all-cause mortality in vegetarians is rather inconsistent [5]–[7], [19]–[22]. The higher cancer incidence in vegetarians in our study might be a coincidence, and is possibly related to factors other than the general amount of animal fat intake, such as health-conscious behavior, since no differences were found regarding smoking behavior and physical activity in Austrian adults as reported in other studies for other countries [9], [13], [14]. Therefore, further studies will be required in Austria in order to analyze the incidence of different types of cancer and their association with nutritional factors in more depth.
Several studies have shown the mental health effects of a vegetarian diet to be divergent [9], [15], [16]. Vegetarians in our study suffer significantly more often from anxiety disorder and/or depression. Additionally, they have a poorer quality of life in terms of physical health, social relationships, and environmental factors.
Moreover, the use of health care differs significantly between the dietary habit groups in our study. Vegetarians need more medical treatment than subjects following another form of diet. However, this might be due to the number of chronic conditions, which is higher in subjects with a vegetarian diet.
Among the strengths of our study are: the large sample size, the matching according to age, sex, and socioeconomic background, and the standardized measurement of all variables. Other strengths of our study include considering the influence of weight and lifestyle factors on health, e.g. physical exercise and smoking behavior.
Potential limitations of our results are due to the fact that the survey was based on cross-sectional data. Therefore, no statements can be made whether the poorer health in vegetarians in our study is caused by their dietary habit or if they consume this form of diet due to their poorer health status. We cannot state whether a causal relationship exists, but describe ascertained associations. Moreover, we cannot give any information regarding the long-term consequences of consuming a special diet nor concerning mortality rates. Thus, further longitudinal studies will be required to substantiate our results. Further limitations include the measurement of dietary habits as a self-reported variable and the fact that subjects were asked how they would describe their eating behavior, without giving them a clear definition of the various dietary habit groups. However, a significant association between the dietary habit of individuals and their weight and drinking behavior is indicative for the validity of the variable. Another limitation concerns the lack of detailed information regarding nutritional components (e.g. the amount of carbohydrates, cholesterol, or fatty acids consumed). Therefore, more in-depth studies about nutritional habits and their effects on health are required among Austrian adults. Further studies should e.g. investigate the influence of the various dietary habits on the incidence of different cancer types. To our knowledge this is the first study ever in Austria to analyze differences in terms of dietary habits and their impact on health. We admit that the large number of participants made it necessary to keep the questions simple, in order to cover the large sample. Overall, we feel that our results are of specific interest and contribute to extant scientific knowledge, notwithstanding some limitations regarding causes and effects.

Conclusions

Our study has shown that Austrian adults who consume a vegetarian diet are less healthy (in terms of cancer, allergies, and mental health disorders), have a lower quality of life, and also require more medical treatment. Therefore, a continued strong public health program for Austria is required in order to reduce the health risk due to nutritional factors. Moreover, our results emphasize the necessity of further studies in Austria, for a more in-depth analysis of the health effects of different dietary habits.

Author Contributions

Conceived and designed the experiments: NTB WF. Performed the experiments: NTB. Analyzed the data: NTB JM FG ER WF. Contributed reagents/materials/analysis tools: NTB JM FG WF. Wrote the paper: NTB ER WF.

References

  1. 1. American Dietetic Association, Dietitians of Canada (2003) Position of the American Dietetic Association and Dietitians of Canada: vegetarian diets. Can J Diet Pract Res 64(2): 62–81.
  2. 2. Craig WJ (2009) Health effects of vegan diets. Am J Clin Nutr 89(5): 1627s–1633s.
  3. 3. Craig WJ (2010) Nutrition concerns and health effects of vegetarian diets. Nutr Clin Pract 25(6): 613–20.
  4. 4. Craig WJ, Mangels AR (2009) American Dietetic Association (2009) Position of the American Dietetic Association: vegetarian diets. J Am Diet Assoc 109(7): 1266–82.
  5. 5. Dwyer JT (1988) Health aspects of vegetarian diets. Am J Clin Nutr 48: 712–38.
  6. 6. Key TJ, Appleby PN, Davey GK, Allen NE, Spencer EA, et al. (2003) Mortality in British vegetarians: review and preliminary results from EPIC-Oxford. Am J Clin Nutr 78: 533s–58s.
  7. 7. Key TJ, Appleby PN, Rosell MS (2006) Health effects of vegetarian and vegan diets. Proc Nutr Soc 65(1): 35–41.
  8. 8. Deriemaeker P, Alewaeters K, Hebbelinck M, Lefvre J, Philippaerts R, et al. (2010) Nutritional status of Flemish vegetarians compared with non-vegetarians: a matched sample study. Nutrients 2(7): 770–80.
  9. 9. Baines S, Powers J, Brown WJ (2007) How does the health and well-being of young Australian vegetarian women compare with non-vegetarians? Public Health Nutr 10(5): 436–42.
  10. 10. Farmer B, Larson BT, Fulgoni VL, Rainville AJ, Liepa GU (2011) A vegetarian dietary pattern as a nutrient-dense approach to weight management: an analysis of the national health and nutrition examination survey 1999–2004. J Am Diet Assoc 111(6): 819–27.
  11. 11. Rizzo NS, Sabaté J, Jaceldo-Siegl K, Fraser GE (2011) Vegetarian dietary patterns are associated with a lower risk of metabolic syndrome: the adventist health study 2. Diabetes Care 34(5): 1225–27.
  12. 12. Tonstad S, Butler T, Yan R, Fraser GE (2009) Type of vegetarian diet, body weight, and prevalence of type 2 diabetes. Diabetes care 32(5): 791–96.
  13. 13. Pollard J, Greenwood D, Kirk S, Cade J (2001) Lifestyle factors affecting fruit and vegetable consumption in the UK women’s cohort study. Appetite 37(1): 71–79.
  14. 14. Gacek M (2010) Selected lifestyle and health condition indices of adults with varied models of eating. Rocz Pantsw Zakl Hig 61(1): 65–69.
  15. 15. Low Dog T (2010) The role of nutrition in mental health. Altern Ther Health Med 16(2): 42–46.
  16. 16. Michalak J, Zhang XC, Jacobi F (2012) Vegetarian diet and mental disorders: results from a representative community survey. Int J Behav Nutr Phys Act 9: 67.
  17. 17. Singh PN, Sabaté J, Fraser GE (2003) Does low meat intake increase life expectancy in humans? Am J Clin Nutr 78(3): 526s–32s.
  18. 18. McEvoy CT, Temple N, Woodside JV (2012) Vegetarian diets, low-meat diets and health: a review. Public Health Nutr 15: 2287–2294.
  19. 19. Appelby PN, Thorogood M, Mann JI, Key TJA (1999) The Oxford vegetarian study: an overview. Am J Clin Nutr 70: 525s–31s.
  20. 20. Frentzel-Beyme R, Chang-Claude J (1994) Vegetarian diets and colon cancer: the German experience. Am J Clin Nutr 59: 143s–52s.
  21. 21. Burkert NT, Großschädl F, Muckenhuber J, Rásky É, Stronegger WJ, et al. (2012) Gastro-intestinal complaints related to various eating behaviours. J Nutr Therapeutics 1: 19–23.
  22. 22. Tantamango-Bartley Y, Jaceldo-Siegl K, Fan J, Fraser G (2013) Vegetarian Diets and the Incidence of Cancer in a Low-risk Population. Cancer Epidemiol Biomarkers Prev 22(2). DOI:https://doi.org/10.1158/1055-9965.EPI-12.1060.
  23. 23. Flood A, Velie AM, Sinha R, Chaterjee N, Lacey JV, et al. (2003) Meat, fat, and their subtypes as risk factors for colorectal cancer in a prospective cohort study in women. Am J Epidemiol 158: 59–68.
  24. 24. Mathew A, Peters U, Chatterjee N, Kulldorff M, Sinha R (2004) Fat, fiber, fruits, vegetables, and risk of colorectal adenomas. Int J Cancer 108: 287–292.
  25. 25. Seow A, Quah SR, Nyam D, Straughan PT, Chua T, et al. (2002) Food groups and the risk of colorectan carcinomas in an Asian population. Cancer 95: 2390–2396.
  26. 26. Vang A, Singh PN, Lee JW, Haddad EH, Brinegar CH (2008) Meats, processed meats, obesity, weight gain and occurrence of diabetes among adults: findings from Adventist Health Studies. Ann Nutr Metab 52(2): 96–104.
  27. 27. Boutron-Ruault MC, Senesse P, Meance S, Belghiti C, Faivre J (2001) Energy intake, body mass index, physical activity, and the colorectal adenoma-carcinoma sequence. Nutr Cancer 39: 50–57.
  28. 28. Appleby PN, Key TJ, Thorogood M, Burr ML, Mann J (2002) Mortality in British vegetarians. Public Health Nutr 5(1): 29–36.
  29. 29. Chang-Claude J, Hermann S, Eilber U, Steindorf K (2005) Lifestyle determinants and mortality in German vegetarians and health-conscious persons: results of a 21-year follow-up. Cancer Epidemiol Biomarkers Prev 14(4): 963–68.
  30. 30. Fraser GE (2009) Vegetarian diets: what do we know of their effects on common chronic diseases? Am J Clin Nutr 89: 1607s–12s.
  31. 31. Sabaté J (2003a) The contribution of vegetarian diets to health and disease: a paradigm shift? Am J Clin Nutr 78: 502s–7s.
  32. 32. Sabaté J (2003b) The contribution of vegetarian diets to human health. Forum Nutr 56: 218–20.
  33. 33. Karlic H, Schuster D, Varga F, Klindert G, Lapin A, et al. (2008) Vegetarian diet affects genes of oxidative metabolism and collagen synthesis. Ann Nutr Metab 53(1): 29–32.
  34. 34. Kornsteiner M, Singer I, Elmadfa I (2008) Very low n-3 long-chain polyunsaturated fatty acid status in Austrian vegetarians and vegans. Ann Nutr Metab 52(1): 37–47.
  35. 35. Majchrzak D, Singer I, Maenner M, Rust P, Genser D, et al. (2006) B-vitamin status and concentrations of homocysteine in Austrian omnivores, vegetarians and vegans. Ann Nutr Metab 50(6): 485–91.
  36. 36. Schumacher M, Eber B, Schallmoser K, Toplak H, Zweiker R, et al. (1993) Eating behavior of patients with metabolic diseases and metabolically healthy probands in Austria. Results of a questionnaire survey at the Graz Autumn Fair 1991. Wien Med Wochenschr 43(12): 329–23.
  37. 37. Klimont J, Kytir J, Leitner B (2007) Austrian Health Interview Survey 2006/07. (Oesterreichische Gesundheitsbefragung 2006/07. Hauptergebnisse und methodische Dokumentation.) Wien: Statistik Austria.
  38. 38. Bauer GF, Huber CA, Jenny GJ, Mueller F, Haemming O (2009) Socioeconomic status, working conditions and self-rated health in Switzerland: explaining the gradient in men and women. International J Pub Health 54: 23–30.
  39. 39. Volkert D (2006) The body mass index (BMI) – an important parameter to evaluate the nutritional status [Der Body-Mass-Index (BMI) – ein wichtiger Parameter zur Beurteilung des Ernährungszustandes]. Aktuel Ernaehr Med 31: 126–132.
  40. 40. Dorner TE, Rieder A (2010) Obesity paradox or reverse epidemiology: is hight body weight a protective factor for various chronic conditions? [Das Adipositasparadoxon oder Reverse Epidemiologie. Hohes Körpergewicht als protektiver Faktor bei bestimmten chronischen Bedingungen? ] Dtsch Med Wochenschr 135: 413–418.
  41. 41. Burkert NT, Rásky E, Freidl W (2012) Social inequalities regarding health and health behaviour in Austrian adults. Wien klin Wochenschr 7–8: 256–261.
  42. 42. OECD Social Policy Division (2009) “What are equivalence scales?” Available: http://www.oecd.org/els/social.
  43. 43. World Health Organization (2013) Global database on Body Mass Index. BMI classification. Available: http://apps.who.int/bmi/index.jsp?introPage=intro_3.html. Accessed 2013 September 17.
  44. 44. Craig CL, Marshall A, Sjostrom M, Bauman AE, Booth ML, et al. (2003) International Physical Activity Questionnaire: 12 country reliability and validity. Med Sci Sports Exerc 35(8): 1381–1395.
  45. 45. World Health Organization (1996) WHOQOL-BREF. Introduction, Administration, Scoring, and Generic Version of the Assessment. Geneva: WHO. Available: http://www.who.int/mental_health/media/en/76.pdf.
  46. 46. Leitzmann C (2005) Vegetarian diets: what are the advantages? Forum Nutr 57: 147–56.

 

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