scholarly journals Association between dietary intake and anthropometric and metabolic profile in Brazilian adult women

2020 ◽  
Vol 23 (2) ◽  
pp. 136-153
Author(s):  
Ana Gabriella Pereira Alves ◽  
Beatriz Assis Carvalho Cruvinel ◽  
Maria Sebastiana Silva ◽  
Ana Cristina Silva Rebelo
Keyword(s):  
Waist Circumference ◽  
Protein Intake ◽  
Metabolic Profile ◽  
Glycated Hemoglobin ◽  
Positive Association ◽  
Hdl Cholesterol ◽  
Adult Women ◽  
Fat Percentage ◽  
Anthropometric Parameters ◽  
Cross Sectional

Introduction: Alterations in the lipid, glycemic and hemodynamic profile may increase the risk of developingchronic diseases and mortality. Objective: Associate the metabolic and anthropometric parameters and foodintake of Brazilian adult women. Methods: A cross-sectional study was conducted with 34 Brazilian womenaged 20-59 years old. Alcohol consumption, smoking, physical exercise, blood pressure, anthropometric and foodintake data were collected. Glycated hemoglobin and lipid fractions were also evaluated. Results: There was apositive association between energy consumption and body mass ( = 0.377, p = 0.028) and waist circumference(ß = 0.373, p = 0.030), and between protein intake and body fat percentage (ß = 0.368, p = 0.032). There was alsoa positive association between waist circumference and the values of glycated hemoglobin (ß = 0.401, p = 0.019),and HDL-cholesterol was influenced directly by protein intake (ß = 0.573, p = 0.013) and inversely by lipid intake(ß = -0.597, p = 0.010). Conclusion: Anthropometry, metabolic profile and food intake were associated amongthe Brazilian adult women evaluated.

Relationship Among Adherence to The Mediterranean Diet and Anthropometric and Metabolic Parameters in Subjects with Obesity

2020 ◽  
Vol 20 ◽  
Author(s):  
Luisa Lampignano ◽  
Roberta Zupo ◽  
Rossella Donghia ◽  
Vito Guerra ◽  
Fabio Castellana ◽  
...  
Keyword(s):  
Mediterranean Diet ◽  
Hdl Cholesterol ◽  
Fat Distribution ◽  
Serum Levels ◽  
Overweight And Obesity ◽  
Height Ratio ◽  
Anthropometric Parameters ◽  
Cross Sectional ◽  
Waist To Height Ratio ◽  
The Mediterranean

Background: There is moderate-to-high evidence that the Mediterranean diet prevents increases in body weight and waist circumference in non-obese individuals but less is known about its effects in subjects with overweight and obesity. The present study was focused on exploring the cross-sectional association among the adherence to Mediterranean diet and the most commonly used variables of metabolic and cardiovascular risk factors in a cohort of overweight subjects from a typical Mediterranean region, Apulia, in Southern Italy. Methods:: The study was performed in a cohort of 1214 individuals, all with overweight or obesity but no other clinical condition. We investigated the association among adherence to Mediterranean diet, assessed with the PREDIMED score, and anthropometric parameters [namely body mass index (BMI), WC, waist to height ratio (WHtR) and neck circumference (NC)], fasting serum levels of glucose, insulin, uric acid and lipids (triglycerides, total cholesterol, HDL cholesterol and LDL cholesterol), and blood pressure and insulin resistance, measured by HOMA-IR. Results:: The waist to height ratio was negatively associated to a PREDIMED score ≥7 (p<0.04), whereas HDL cholesterol was positively associated to a PREDIMED score ≥7 (p<0.04) Conclusion: This study suggests that body fat distribution and HDL-cholesterol are the parameters most strongly influenced by MedDiet in Apulian subjects.

scholarly journals Metabolic syndrome in patients with prostate cancer

2008 ◽  
Vol 126 (5) ◽  
pp. 274-278 ◽  
Author(s):  
Iúri Amorim de Santana ◽  
Gustavo Souza Moura ◽  
Nivaldo Farias Vieira ◽  
Rosana Cipolotti
Keyword(s):  
Prostate Cancer ◽  
Metabolic Syndrome ◽  
Body Mass ◽  
Specific Antigen ◽  
Density Lipoprotein ◽  
Positive Association ◽  
Serum Glucose ◽  
Anthropometric Parameters ◽  
Cross Sectional ◽  
Waist To Hip Ratio

CONTEXT AND OBJECTIVE: Prostate cancer (PCa) is the second most common cancer among men in Brazil. Recently, several studies have hypothesized a relationship between PCa and metabolic syndrome (MS). The aim here was to identify an association between MS and PCa. DESIGN AND SETTING: Cross-sectional study, Fundação de Beneficência Hospital de Cirurgia (FBHC) and Universidade Federal de Sergipe. METHODS: Laboratory and anthropometric parameters were compared between PCa patients (n = 16) and controls (n = 16). RESULTS: The PCa patients showed significantly greater frequency of MS than did the controls (p = 0.034). Serum glucose was higher and high-density lipoprotein-cholesterol was lower than in the controls, although without significant differences. There were significant differences in blood pressure (p = 0.029) and waist-to-hip ratio (p = 0.004). Pearson linear correlation showed a positive association between waist-to-hip ratio and prostate specific antigen (r = 0.584 and p = 0.028). Comparing subgroups with and without MS among the PCa patients, significant differences (p < 0.05) in weight, height, body mass index, hip circumference and lean body mass were observed, thus showing higher central obesity in those with MS. The serum glucose values were also higher in MS patients (p = 0.006), thus demonstrating that insulin resistance has a role in MS physiopathology. CONCLUSIONS: Our study suggests that MS may exert an influence on the development of PCa. However, it would be necessary to expand the investigation field with larger sample sizes and cohorts studied, to test the hypothesis generated in this study.

scholarly journals The Association of Serum Lipid and Lipoprotein Levels with Total and Differential Leukocyte Counts: Results of a Cross-sectional and Longitudinal Analysis of the UK Biobank

2020 ◽  
Author(s):  
Bradley Tucker ◽  
Sonia Sawant ◽  
Hannah McDonald ◽  
Kerry-Anne Rye ◽  
Sanjay Patel ◽  
...  
Keyword(s):  
Longitudinal Analysis ◽  
Positive Association ◽  
Hdl Cholesterol ◽  
Uk Biobank ◽  
Cross Sectional ◽  
Lipoprotein A ◽  
Valid Data ◽  
Leukocyte Counts ◽  
The Uk ◽  
Relationship Of

Background and aims: There is some evidence of a cross-sectional, and possibly causal, relationship of lipid levels with leukocyte counts in mice and humans. This study investigates the cross-sectional and longitudinal relationship of blood lipid and lipoprotein levels with leukocyte counts in the UK Biobank cohort. Methods: The primary cross-sectional analysis included 417,132 participants with valid data on lipid measures and leukocyte counts. A subgroup analysis was performed in 333,668 participants with valid data on lipoprotein(a). The longitudinal analysis included 9,058 participants with valid baseline and follow-up data on lipid and lipoprotein levels and leukocyte counts. The association of lipid and lipoprotein levels with leukocyte counts was analysed by multivariable linear regression. Results: Several relationships were significant in both cross-sectional and longitudinal analysis. After adjustment for demographic, socioeconomic and other confounding factors a higher eosinophil count was associated with lower HDL cholesterol and apolipoproteinA-I concentration (p<0.001). Higher triglycerides levels were associated with higher total leukocyte, basophil, eosinophil, monocyte and neutrophil counts (all p<0.01). A higher lymphocyte count was associated with a higher apolipoprotein B level (p<0.001). In the longitudinal analysis lipoprotein(a) was inversely associated with basophil count in men but not women (p<0.001). Conclusion: Triglyceride levels demonstrate a robust positive association with total and differential leukocyte counts suggesting they may be directly involved in leuokogenesis. However, unlike in murine models, the remainder of these relationships are modest which suggests that cholesterol and lipoproteins are minimally involved in leukogenesis in humans.

scholarly journals PO-236 Associations between sleep quality of college students and different measures of obesity: A cross-sectional study

2018 ◽  
Vol 1 (5) ◽  
Author(s):  
Guangyu Wang ◽  
Mei Zhen Zhang
Keyword(s):  
Physical Activity ◽  
Waist Circumference ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Body Fat ◽  
Positive Association ◽  
Female Students ◽  
Male Students ◽  
Body Fat Percentage ◽  
Fat Percentage

Objective The majority studies focused on obesity prevention on physical activity and eating behavior. However, epidemiological studies have shown that sleep duration and sleep quality could be an adjustable risk factor for obesity. The aim of this study was to examine the associations of sleep quality with different measurement of obesity in Chinese university students. Methods A total of 481 college students aged 18-25 years volunteered to participate in this study. Sleep quality was assessed by Pittsburgh Sleep Quality Index （PSQI）questionnaire. International Physical Activity Questionnaire （IPAQ）was used to determine the physical activity, Psychological status was assessed by Self-Rating Depression Scale （SDS） and Self-Rating Anxiety Scale (SAS). Body height, weight and waist circumference are measured by a trained researcher. Body composition was evaluated by a bio-impedance device (InBody 230, South Korea). Independent sample t test was applied to compare the sleep characteristics, physical activity, obesity, depression and anxiety in different gender students. The associations among the dependent variables BMI, body fat percentage, and the independent variables age, sleep quality and sleep durations was examined using Multiple linear regression models. SPSS 22.0 (IMB SPSS Inc) was used for all statistical. Results The BMI (22.9±3.4 vs 21.6±3.2, p＜0.001) of male students were significantly higher than that of female, but the percentage of body fat (18.7±6.9 vs 29.7±7.0, p＜0.001) was lower than that of female. We observed a positive association between sleep quality and body fat percentage (β = 0.166, P = 0.037), and a negative association with age (β = -0.166, P = 0.008) in female students. Sleep quality was associated positively with BMI (β = 0.360, P＜0.001), body fat percentage (β = 0.260, P＜0.001), and age (β = 0.215, P＜0.001) in male students; An inverse correlation between sleep duration and BMI (β = -0.141, P = 0.015), body fat percentage (β = -0.134, P = 0.022) was found, and a positive relationship with  anxiety scores (β = 0.331, P＜0.001) in male students. while an inverse relationship was found with WHR (β = -0.236, P = 0.001), waist circumference (β = -0.169, P = 0.007), and a positive association between sleep duration with anxiety scores (β = 0.331, P＜0.001) and depression scores (β = 0.415, P＜0.001) in female students. Conclusions The obesity of male and female students goes up with the increase of total score of sleep quality, anxiety and depression, and goes down with the increase of sleep duration, physical activity time and energy consumption. Male obesity increases with age, but female obesity decreases with age. Among the importance of males' sleep duration and sleep quality in the obesity risk assessment, BMI and body fat percentages are more accurate, while for females, BMI and waist circumference is of no statistical significance.  

scholarly journals Neck Circumference, a Novel Predictor of Overweight/ Obesity in School Children in Pokhara

Med Phoenix ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 32-39
Author(s):  
Manisha Maskey ◽  
KK Dutta Gupta ◽  
Meraj Ahmed
Keyword(s):  
Waist Circumference ◽  
School Children ◽  
Good Predictor ◽  
Central Obesity ◽  
Characteristic Curve ◽  
Cross Sectional Study ◽  
Neck Circumference ◽  
Anthropometric Parameters ◽  
Cross Sectional ◽  
High Bmi

Background: Calculating BMI in an individual is a standard anthropometric procedure to estimate overweight/obesity. But it has been observed to be a bad predictor of central obesity. On the other hand, waist circumference, in many studies, has been found to be a good predictor of central obesity but not so frequently used because of tendency to vary throughout the day. In the recent years, NC has been found to have a good correlation with both BMI and WC. The aim of this study was to find out whether neck circumference is a good predictor of Overweight/Obesity or not. Methods: This was a cross sectional study carried out among the school children, aged 12 to 15 years, in Pokhara city, Nepal. In total, 408 students, 238 males and 170 females were screened. Anthropometric markers of obesity measured: included body mass index (BMI), waist circumference (WC), and compared with neck circumference (NC) of the same subjects. Pearson’s correlation test was used to see the correlation between NC with BMI and WC, and receiver operating characteristic curve analysis was used to determine the best cut off value of neck circumference in predicting high BMI. Results: Among 408 students, 238 (58.3%) were male and 170 (41.7%) were female. Among them 37 (9.1%) were overweight and 32 (7.8%) were obese. All the anthropometric parameters were significantly higher in cases, except height in male, than in controls. NC was significantly correlated with age, BMI, and waist circumference in both boys and girls. The best cut-off value of neck circumference by ROC to identify boys with a high BMI was 29.5 with sensitivity of (76%), specificity (54%), and for girls was 28.5 with sensitivity of (97%), specificity (48%). Conclusion: Statistically significant positive correlation was found between NC with BMI and WC. The value of NC as a screening tool has been found comparably lower in compare to WC.

scholarly journals Heritability of the risk factors characteristic for the metabolic syndrome: a twin study

2011 ◽  
Vol 152 (32) ◽  
pp. 1265-1271 ◽  
Author(s):  
György Jermendy ◽  
Levente Littvay ◽  
Rita Steinbach ◽  
Ádám Jermendy ◽  
Ádám Tárnoki ◽  
...  
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Waist Circumference ◽  
Environmental Factors ◽  
Fasting Blood Glucose ◽  
Hdl Cholesterol ◽  
Anthropometric Parameters ◽  
Serum Triglycerides ◽  
The Metabolic Syndrome ◽  
Genetic And Environmental Factors

Both genetic and environmental factors play role in the pathogenesis of the metabolic syndrome. The magnitude of genetic and environmental influences on the components of metabolic syndrome may vary in different populations. Aims: The present study was aimed to determine the effects of genetic and environmental factors on risk factors characteristic for the metabolic syndrome. Methods: A total of 101 (63 monozygotic and 38 dizygotic) adult twin pairs (n = 202; mean age: 43.3±15.8 years) were investigated. Medical history was recorded and physical examination was carried out for each subject. Fasting venous blood samples were used for measuring laboratory parameters. The presented estimates include the heritability structural equation (A-C-E) model results. In Model-1, all presented parameters are age- and gender- corrected. In Model-2, parameters were corrected for age, gender, body mass index and waist circumference. Results: Heritability in waist circumference (as well as in other anthropometric parameters such as weight and height) was high (Model-1: 71.0–88.1%). Similarly, genetic factors had the highest proportion of total phenotypic variance in systolic and diastolic blood pressure (Model-2: 57.1% and 57.7%, respectively). Based on the results of Model-2, unique environmental factors dominate alterations in serum triglycerides values (55.9%) while shared environmental factors proved to be substantial in alterations of HDL-cholesterol and fasting blood glucose values (58.1% and 57.1%, respectively). Comparing the results of Model-1 and Model-2, the difference in A-C-E model varied from 0.0% to 17.1%, indicating that only a minor proportion of genetic and environmental influences can be explained by the effects of anthropometric parameters. Conclusions: Among adult Hungarian healthy people, genetic factors have substantial influence on waist circumference and blood pressure values while environmental factors dominate alterations in serum triglycerides, HDL-cholesterol and fasting blood glucose values. The different heritability of individual risk factors challenges the original unifying concept of the metabolic syndrome. The results may be useful for establishing and implementing primary cardiovascular prevention both at individual and population levels. Orv. Hetil., 2011, 152, 1265–1271.

scholarly journals Knowledge of nutrition and physical activity in apparently healthy Indian adults

2018 ◽  
Vol 21 (9) ◽  
pp. 1743-1752 ◽  
Author(s):  
Deepa Pandit-Agrawal ◽  
Anuradha Khadilkar ◽  
Shashi Chiplonkar ◽  
Vaman Khadilkar
Keyword(s):  
Physical Activity ◽  
Leafy Vegetables ◽  
Dietary Intakes ◽  
Residential Areas ◽  
Fat Percentage ◽  
Anthropometric Parameters ◽  
Cross Sectional ◽  
Nutrition And Physical Activity ◽  
Cross Sectional Design ◽  
The Relationship

AbstractObjectiveTo assess knowledge of nutrition and physical activity; examine associations of knowledge with sociodemographic and anthropometric parameters; and evaluate the relationship between knowledge and practice in adults.DesignIn a cross-sectional design, 720 adults were selected using random sampling. Data on anthropometry, body fat, diet, physical activity, and nutrition and physical activity knowledge were collected using standardized questionnaires. Tertiles were used to categorize nutrition knowledge (NK) and physical activity knowledge (PK).SettingsSubjects selected through routine health checks from hospitals, housing societies and residential areas.SubjectsA total of 720 adults (361 men) aged 35–50 years participated.ResultsMean age was 42·7 (sd 9·4) years and mean BMI was 25·8 (sd 5·0) kg/m2. Mean energy intake was 64 %, protein was 68 % and fat was 144 % of the RDA. Mean NK and PK scores were 10·2 (sd 2·9) and 6·5 (sd 1·7), respectively, and were similar across genders (P>0·05). Individuals with higher education exhibited significantly higher NK and PK. Individuals with high fat had significantly higher NK and PK (P<0·05) than participants with normal fat percentage. Overweight and obese individuals had significantly higher PK (P<0·05). Multivariate regression modelling indicated that NK was positively associated with dietary intakes of leafy vegetables, salads and sprouts but negatively associated with fruit intake. BMI, television and reading time were positively associated with PK, even after adjusting for sociodemographic status.ConclusionsThere is a need for increased efforts towards developing health education programmes focusing on transforming nutrition and physical activity knowledge into practice and adherence to guidelines.

scholarly journals Protein Intake and Human Health: Implications of Units of Protein Intake

2020 ◽  
Author(s):  
Adela Hruby ◽  
Paul F Jacques
Keyword(s):  
Protein Intake ◽  
Observational Studies ◽  
Estimated Glomerular Filtration Rate ◽  
Protein Quality ◽  
Fasting Glucose ◽  
Hdl Cholesterol ◽  
Cardiometabolic Health ◽  
Cross Sectional ◽  
Number Of Factors ◽  
Heart Study

ABSTRACT Understanding the health effects of protein intake is bedeviled by a number of factors, including protein quality and source. In addition, different units, including grams, grams per kilogram body weight (g/kg BW), and percent energy, may contribute to confusion about protein's effects on health, especially BW-based units in increasingly obese populations. We aimed to review the literature and to conduct a modeling demonstration of various units of protein intake in relation to markers of cardiometabolic health. Data from the Framingham Heart Study Offspring (n = 1847; 60.3 y; 62.5% women) and Third Generation (n = 2548; 46.2 y; 55.3% women) cohorts and the NHANES 2003–04 (n = 1625; 46.2 y; 49.7% women) and 2005–06 (n = 1347; 43.7 y; 49.5% women) cycles were used to model cross-sectional associations between 7 protein units (grams, percent energy, g/kg ideal BW, g/kg actual BW, BW-adjusted g/kg actual BW, g/kg lean BW, and g/kg fat-free BW) and 9 cardiometabolic outcomes (fasting glucose, systolic and diastolic blood pressure, total and HDL cholesterol, triglycerides, BMI, waist circumference, and estimated glomerular filtration rate). The literature review indicated the use of myriad units of protein intake, with differential results on cardiometabolic outcomes. The modeling demonstration showed units expressed in BW were confounded by BW, irrespective of outcome. Units expressed in grams, percent energy, and ideal BW showed similar results, with or without adjustment for body size. After adjusting for BW, results of units expressed in BW aligned with results of grams, percent energy, and ideal BW. In conclusion, protein intake in cardiometabolic health appears to depend on protein's unit of expression. Authors should be specific about the use of WHO (g/kg ideal BW) compared with US (g/kg actual BW) units, and ideally use gram or percent energy in observational studies. In populations where overweight/obesity are prevalent, intake based on actual BW should be reevaluated.

Benefits of pedometer-measured habitual physical activity in healthy women

2012 ◽  
Vol 37 (1) ◽  
pp. 149-156 ◽  
Author(s):  
Scheila Karen Graff ◽  
Bruna Cherubini Alves ◽  
Mariana Kirjner Toscani ◽  
Poli Mara Spritzer
Keyword(s):  
Physical Activity ◽  
Metabolic Profile ◽  
Skinfold Thickness ◽  
Cross Sectional Study ◽  
Habitual Physical Activity ◽  
Reproductive Age ◽  
Fat Percentage ◽  
Cross Sectional ◽  
Class I Obesity ◽  
Healthy Women

This cross-sectional study aimed at (i) characterizing pedometer-determined physical activity and (ii) examining its associations with dietary intake and anthropometric and metabolic profile in healthy women. Anthropometric and metabolic profile was evaluated in 68 healthy women of reproductive age. Habitual physical activity was assessed using a pedometer for 6 consecutive days, including weekends. Participants were stratified into active and inactive according to the mean steps·day–1(≥6000 and <6000, respectively). Food consumption was evaluated by 24-h recall in a subsample of 35 participants. Thirty-eight women were defined as active and had significantly lower body mass index (BMI), fat percentage, waist circumference, sum of skinfold thickness, insulin, and HOMA than the sedentary group. Mean BMI was 27 kg·m–2(overweight) in active participants and 31 kg·m–2(class I obesity) in inactive participants. Active women consumed more carbohydrates (55.5% ± 9.4% vs. 46.3% ± 7.6%) and calories (2138 ± 679 vs. 1664 ± 558 kcal), and less protein (15.4% ± 4.2% vs. 19.9% ± 5.8%) and lipids (29.0% ± 7.2% vs. 33.8% ± 6.2%) than inactive individuals (p < 0.05). Fiber, cholesterol, and fatty acid intake was similar in both groups. The number of steps was lower on Sunday than on weekdays for the overall group. Using a pedometer for 3 days was sufficient to determine habitual physical activity (sensitivity: 94%; specificity 91% vs. 6 days of pedometer use). In the present study, nonstructured physical activity was associated with more adequate dietary consumption and contributed toward a healthier anthropometric and metabolic profile in young women, despite the high prevalence of overweight.

scholarly journals Clustering of lifestyle characteristics and their association with cardio-metabolic health: the Lifestyles and Endothelial Dysfunction (EVIDENT) study

2015 ◽  
Vol 114 (6) ◽  
pp. 943-951 ◽  
Author(s):  
Maria C. Patino-Alonso ◽  
José I. Recio-Rodríguez ◽  
José Felix Magdalena-Belio ◽  
María Giné-Garriga ◽  
Vicente Martínez-Vizcaino ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Waist Circumference ◽  
Endothelial Dysfunction ◽  
Adult Population ◽  
Healthy Diet ◽  
Fat Percentage ◽  
Cross Sectional ◽  
Multi Centre Study ◽  
Lifestyle Behaviours ◽  
Cholesterol Levels

AbstractLittle is known about the clustering patterns of lifestyle behaviours in adult populations. We explored clusters in multiple lifestyle behaviours including physical activity (PA), smoking, alcohol use and eating habits in a sample of adult population. A cross-sectional and multi-centre study was performed with six participating groups distributed throughout Spain. Participants (n 1327) were part of the Lifestyles and Endothelial Dysfunction (EVIDENT) study and were aged between 20 and 80 years. The lifestyle and cardiovascular risk (CVR) factors were analysed using a clustering method based on the HJ-biplot coordinates to understand the variables underlying these groupings. The following three clusters were identified. Cluster 1: unhealthy, 677 subjects (51 %), with a slight majority of men (58·7 %), who were more sedentary and smokers with higher consumption of whole-fat dairy products, bigger waist circumference as well as higher TAG levels, systolic blood pressure (SBP) and CVR. Cluster 2: healthy/PA, 265 subjects (20 %), including 24·0 % of males with high PA. Cluster 3: healthy/diet, including 29 % of the participants, with a higher consumption of olive oil, fish, fruits, nuts, vegetables and lower alcohol consumption. Using the unhealthy cluster as a reference, and after adjusting for age and sex, the multiple regression analysis showed that belonging to the healthy/PA cluster was associated with a lower waist circumference, body fat percentage, SBP and CVR. In summary, the three clusters were identified according to lifestyles. The ‘unhealthy’ cluster had the least favourable clinical parameters, the ‘healthy/PA’ cluster had good HDL-cholesterol levels and low SBP and the ‘healthy/diet’ cluster had lower LDL-cholesterol levels and clinical blood pressure.

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