Relevant bibliographies by topics / Android obesity

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Android obesity'

Author: Grafiati
Published: 4 June 2025
Last updated: 23 June 2025

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Journal articles on the topic "Android obesity"

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Cota, Cecília Cristina, Stefani Miranda-Castro, Antônio Felipe Souza-Gomes, et al. "Associations Between Pain Intensity and Inflammatory Profile in Women with Android and Gynoid Obesity Diagnosed with Chronic Pain: An Observational Study." Journal of Clinical Medicine 14, no. 12 (2025): 4170. https://doi.org/10.3390/jcm14124170.

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Background: There are different types of obesity, and the metabolic conditions associated with these phenotypes are also heterogeneous. Overweight and obesity are not only associated with pain but are also identified as risk factors for the development of pain. Objective: This study aimed to compare the levels of inflammatory biomarkers, counting of immune cells, and chronic pain between android and gynoid female patients with obesity. Method: Thirty (n = 30) women took part in this study (18 androids, age: 50.61 ± 9.41 and 12 gynoids, age: 50.67 ± 9.45). The participants underwent anamnesis, Visual Numeric Scale (VNS), dual-energy X-ray absorptiometry, and blood sampling for the analysis of leukocytes, C-reactive protein (CRP), and interleukin (IL)-6. Results: The number of total leukocytes in the blood was not different when comparing the android group (6045 µL) with the gynoid group (5230 µL). No differences were observed for neutrophils (3440 µL in android and 3017 µL in gynoid), lymphocytes (2208 µL in android and 2115 µL in gynoid), for monocytes (429.7 µL in android and 392.8 µL in gynoid), and basophils (17.27 µL in android and 15.41 µL in gynoid). However, there was a significant difference between the number of eosinophils when comparing the android group (137.6 µL) with the gynoid group (204.9 µL), p = 0.04. Although both groups presented CRP values above 0.3 mg/dL—indicative of low-grade inflammation—no statistically significant difference was observed. Similarly, no difference was found in pain intensity between groups, as measured by the Visual Numeric Scale (VNS). Conclusions: Although most inflammatory and pain markers did not differ between groups, the higher eosinophil count in the gynoid phenotype suggests immunological distinctions between obesity types. These findings underline the importance of considering body fat distribution in clinical assessments of inflammation and chronic pain in women with obesity.
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Orbetzova, Maria M., Daniela I. Koleva, Mitko D. Mitkov, et al. "Adipocytokines, Neuropeptide Y and Insulin Resistance in Overweight Women with Gynoid and Android Type of Adipose Tissue Distribution." Folia Medica 54, no. 3 (2012): 22–29. http://dx.doi.org/10.2478/v10153-011-0093-7.

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ABSTRACT The AIM of the study was to compare the levels of certain adipose tissue hormones in women with the two main morphological types of obesity - android and gynoid obesity. MATERIALS AND METHODS: The study included 2 groups of age- and weight-matched women with android (n = 32) and gynoid (n = 27) type of obesity, and a group of age-matched healthy women (n = 24) with normal weight and body constitution. Leptin, resistin, tumour necrosis factor α (TNFα), neuropeptide Y (NPY), glucose and insulin were measured.HOMA index was calculated. RESULTS: Leptin levels in the women with gynoid obesity did not differ significantly from those in the controls and the women with android obesity. The controls had significantly lower leptin levels compared with the android obesity women. NPY was significantly higher in the control women compared to the women with android obesity and did not differ significantly between the two groups of obese women. TNFα levels in all groups were very similar. Resistin did not show significant differences between all groups but tended to have the lowest levels in the controls. In the women with android obesity, insulin was significantly higher than that in the women with gynoid obesity and the controls. Insulin resistance was found in the women with android obesity only. Basal insulin and HOMA index in the women with gynoid obesity did not differ significantly from the values in the control group. CONCLUSION: The results from this study contribute to understanding the association of adipose tissue hormones and insulin resistance in obesity. When adipose tissue is predominantly distributed in the abdominal area at similar amount and percentage of body fats, leptin production is higher and insulin resistance develops. In the gynoid type of adipose tissue predisposition, overt insulin resistance is not found, leptin levels does not differ significantly from those in the control group.
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Doi, Rafiah, and Sweety Shah. "Anthropometric Measurements of Android and Gynoid Obesity and Their Association with Cardiovascular Diseases Risk Factors in Obese Young Adults." International Journal of Science and Healthcare Research 8, no. 3 (2023): 291–95. http://dx.doi.org/10.52403/ijshr.20230340.

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Background- Obesity is the leading risk-factor of cardiovascular-diseases, which accounts for 23% of Ischemic Heart-Diseases burden. Several studies are done to correlate the effect of BMI on cardiovascular risk-factors. But only few studies are done to compare the effect of obesity on cardiovascular risk-factors. Therefore, this study is to identify the effect of android & gynoid-type of obesity on CVD risk-factors. Method- Study conducted on 60 obese-adults; Age:20-45 years; BMI 25-29.9kg/m2 (Obese-class Ⅰ WHO-Asian Classification) Demographic and anthropometric data regarding WC, HC, and WHR were recorded. CVD risk-factors by ATP-III definition: High-BP, Low-HDL-C, High-triglycerides, Fasting-glucose. Thus, to observe association of CVD risk-factors between android-obesity & gynoid-obesity. Result- Result has been obtained from SPSS20. Mean-age & Mean-BMI in Android-obesity were (33.06+7.8) (27.33+1.24) and in Gynoid-obesity were (33.9+7.54) (27.26+1.15) respectively. Comparison between two groups found using independent t-tests. There was significant difference of Triglycerides, Fasting-glucose, Blood-pressure & HDL-C between both groups. Triglycerides (M=158.27), Fasting-glucose (M=121.30), Blood-pressure (SBP; M=132.69, DBP; M=89.03) were higher while HDL-C (M=35.10) is lower in Android-obesity than that of Gynoid(M=110.53), (M=95.77), (SBP; M=116.97, DBP; M=75.50) and (M=46.03), having significant difference p<0.05 Conclusion & Clinical-implications- This study concludes that CVD risk-factors are significantly associated with Android-obesity as compared to Gynoid-obesity. Keywords: Android-Obesity, Gynoid-obesity, CVD risk-factors, waist-hip-ratio
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Shah, Shruti, and Pratibha Gaikwad. "Comparison of Peak Expiratory Flow Rate between Android and Gynoid Pattern Obesity in Females." International Journal of Health Sciences and Research 11, no. 4 (2021): 236–54. http://dx.doi.org/10.52403/ijhsr.20210429.

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Aim: To assess comparison of PEFR between Android and Gynoid Pattern Obesity in Females. Objectives: To assess Peak Expiratory Flow Rate in Android Pattern, Gynoid Pattern of Obesity in Females and compare Peak Expiratory Flow Rate between Android and Gynoid Pattern Obesity in Females. Methodology: 100 Female Obese Subjects with BMI> 30 in the Age Group between 20-40 yrs living a sedentary lifestyle were recruited with incidental sampling over the period of 1 year duration and allocated to Android (n = 50) and Gynoid (n = 50) groups on the basis of Adiposity Markers like BMI, Height, Weight, Waist Circumference (WC), Hip Circumference (HC), WHR - Waist Hip Ratio (WHR) and Waist to Height Ratio (WtHR). PEFR was recorded by taking 3 readings and the highest among them chosen. Results: Pearson correlation test and Linear Regression was done between PEFR & BMI, PEFR & WHR and PEFR & WHtR. Using an Unrelated t Test, results were found to be Significant (p < 0.05) between PEFR in Both the Groups. Conclusion: The study establishes that there is a difference in PEFR between Android and Gynoid Pattern of Obesity in Females and PEFR in Gynoid Pattern is 5% better than PEFR in the Android Pattern Obesity in Females. Key words: Obesity, Android, Gynoid, PEFR, BMI, WHR, WtHR, WC, HC.
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Mohanty, Charchika, and Roopa Desai. "Will Carrying Angle Have an Impact on Different Types of Obesity and Dominance? A Correlational Study." International Journal of Health Sciences and Research 15, no. 1 (2025): 8–13. https://doi.org/10.52403/ijhsr.20250102.

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The carrying angle represents the angle developed when the forearm is fully extended and supinated in between lateral obliquity and the median axis of both the arms, and shoulder externally rotated. The carrying angle measurement is conducted on genders having android and gynoid obesity in the age category of 20–45 years. In this research we evaluated carrying angle and analyzed its prevalence in both genders with different types of obesity. A total of 100 obese participants, consisting 26 obese men and 74 obese women took part in the study. Simultaneously, their dominant and non-dominant hands were used to measure the carrying angle using a goniometer and body mass index was measured using a stadiometer, an electronic weight machine including a measuring tape for the waist to hip ratio. The statistical analysis was done using Microsoft Excel and the statistical package for social sciences (SPSS) version 21 software. The average carrying angle in the right hand of an obese android is 19.87 ± 2.72, whereas that of a gynoid is 19.83 ± 2.41. The carrying angle of an android's left hand is 17.67 ± 2.67. on average, compared to 17.60 ± 2.50 are obese gynoid individuals. It has been discovered that gynoid obesity is more common in women than android obesity in men. The study concluded that increase in body mass index and waist hip ratio can affect the carrying angle in both male and female obese individuals, but gynoid and android obesity has no effect on the carrying angle. Hence, there is no significant correlation between carrying angle with android and gynoid obesity in both genders. Key words: Android, Carrying Angle, Gynoid, Obesity, Waist to hip ratio
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Filatova, O., S. Polovinkin, E. Baklanova, I. Plyasova, and Yu Burtsev. "Constitutional features of females with different types of obesity." Ukrainian Journal of Ecology 8, no. 2 (2018): 371–79. http://dx.doi.org/10.15421/2018_356.

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<p>We investigated 214 females aged 35-73 years. We divided them into groups of reproductive and menopausal age. We used methods of anthropometry and bioimpedanceometry. We performed somatotyping according to the schemes of Rees-Eisenck, Tanner. The proportion of obese individuals significantly increased in the menopausal period. The body mass index was higher in the group of menopausal females with android obesity. The higher body weight in the same group was caused by the higher fat mass of the body in both absolute and relative magnitudes. The index of normalized basal metabolism based on bioimpedanceometry was lower in women with android obesity. The groups studied did not differ in the proportion of somatotypes according to the Tanner classification. The percentage of pyknic bodies was higher in females with android obesity. The trend of obesity risk in pyknics was 1.5 times higher (p = 0.182). The risk of developing android obesity in pyknics was higher by 4.7 times (p <0.001).</p><p> </p>
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Susindra, Yoswenita, and Riasyah Al Waja Permatasari. "Pengaruh Media Pembelajaran Infografis Berbasis Aplikasi Android Terhadap Tingkat Pengetahuan Mengenai Obesitas Pada Remaja Putri." ARTERI : Jurnal Ilmu Kesehatan 4, no. 2 (2023): 81–86. http://dx.doi.org/10.37148/arteri.v4i2.269.

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Obesity is still an epidemic health problem worldwide. Obesity is a condition in which a person is overweight due to abnormal fat tissue deposits. The cause of obesity is a diet that has been consumed in excess of the need for unbalanced nutrients. Obesity is also caused by various factors related to changes in one's lifestyle that lead to a sedentary lifestyle. The level of knowledge about obesity is one of the factors that influence the formation of an attitude in preventing overweight and obesity. The purpose of this study was to determine the effect of infographic media based on android applications regarding obesity on knowledge of obesity in young women. This research is a quantitative study using a pre-experimental design method with a one group pre- test post-test design. The number of subjects in this study were 74 female students using the simple random sampling technique. The results showed that female adolescents experienced an increase in knowledge from 84.27 to 99.03 after being given an android application media intervention regarding obesity. This proves the influence of the android application regarding obesity on knowledge in young women, with a p-value = 0.000 <0.05.
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Tyshko, К., and О. Gnatko. "Peculiarities of hormonal balance and metabolic profile in pregnant women with different obesity types." HEALTH OF WOMAN, no. 4(150) (May 30, 2020): 67–72. http://dx.doi.org/10.15574/hw.2020.150.67.

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Maternal obesity has become one of the main factors influencing obstetric and perinatal outcomes. Obesity in pregnant women increases the risk of complications during pregnancy, childbirth and the postpartum period. The newborns of obese women also have higher rates of perinatal morbidity and an increased risk of long-term health problems. The objective: to learn hormonal and metabolic peculiarities in pregnant women with different obesity types during full-term pregnancy. Materials and methods. We examined 61 pregnant women with android type and 57 pregnant women with gynoid type of obesity at 39.6–40.6 weeks of gestation and 57 pregnant women without obesity and overweight. The concentration of estradiol, free estriol, insulin, placental lactogen, free testosterone, cortisol, dehydroepialdosterone sulfate (DHEA sulfate), and serum progesterone by enzyme-linked immunosorbent method and glucose rate by glucose-oxydase method were determined. The HOMA index was determined. Results. In pregnant women with gynoid obesity type, the level of progesterone was 41.15 (34.6–48) ng/ml, with android type – 35.7 (32.6–40.6) ng/ml and with physiological body weight 35.4 (33.2–40) ng/ml (p<0.05). While determining the concentration of placental lactogen in three groups there were no significant differences. There was a decrease (p<0,05) in the level of free estriol in groups of pregnant women with android and gynoid type of obesity in comparison with the control group, respectively 13.9 (13.1–14.9) ng/ml, 13.6 (12, 4–15.4) ng/ml and 14.7 (13.6–15.8) ng/ml. The concentration of estradiol in second group was 24 925.3 (20 206.6–30 400.5) pg/ml, which is 1.2 times (p<0.05) higher as in the control group and 1.4 times higher as in first group. In pregnant women with android-type obesity, estradiol levels were 1.2 times lower (p<0.05) compared with the control group. The concentration of cortisol in pregnant women with android type was 812.1 (599–1235.15) nmol/l, which is 2.7 times higher (p<0.05) compared to the women with gynoid type of obesity and 1.5 times higher (p<0.05) than in the control group. In pregnant women with gynoid type of obesity, 1.7 times lower (p<0.05) cortisol levels were observed in comparison with control group. The level of free testosterone was 2.4 (1.7–3.1) nmol/l in pregnant women of first group, what was higher (p<0.05) than in second group and in control group, respectively 1 (0.8–1.5) nmol/l and 1.9 (1.6–2.3) nmol/l. Pregnant women in group 1 had 2.4 times higher (p<0.05) testosterone levels compared to group 2 and 1.2 times higher (p<0.05) than in control group. In women with android type, the concentration of DHEA sulfate was 2.4 times higher (p<0.05) than in pregnant women with gynoid type and 2.1 times higher (p<0.05) compared with the control group. Pregnant women with android type of obesity have a significantly higher (p<0.05) serum insulin concentration of 67 (40–94.5) μIU / ml compared to women with gynoid type of obesity 33.3 (25.6–43) μIU/ml. When determining the glucose concentration no significant difference between three groups was found. The HOMA index in pregnant women with android type of obesity was 2.1 times higher than in pregnant women with gynoid type and 2.3 times higher than in control group (p<0.05). Conclusions. The results of a study indicate that the type of distribution of adipose tissue is important during pregnancy and childbirth because the hormonal and metabolic activity of adipose tissue in android and gynoid obesity types are different. Keywords: android type of obesity, pregnancy, gynoid type of obesity, hormonal balance, metabolic profile.
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Wassef, N., G. Sidhom, Z. El-Khayat, and M. El-Kholy. "Lipoprotein(a) in Android Obesity and NIDDM." Diabetes Care 20, no. 11 (1997): 1693–96. http://dx.doi.org/10.2337/diacare.20.11.1693.

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10

Ghannem, H., and A. Hadj Fredj. "Epidemiology of hypertension and other cardiovascular disease risk factors in the urban population of Soussa, Tunisia." Eastern Mediterranean Health Journal 3, no. 3 (1997): 472–79. http://dx.doi.org/10.26719/1997.3.3.472.

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To illustrate the distribution of hypertension in the community, an epidemiological survey was conducted based on a representative sample of 957 adults aged >/= 20 years resident in Soussa, Tunisia in 1995. The prevalence of hypertension according to the new World Health Organization criteria [systolic blood pressure >140 mmHg and/or diastolic blood pressure >90 mmHg] was 28.9%. Hypertension was significantly higher in cases with obesity, android obesity and for persons aged >40 years. History of diabetes was found in 10.2% of cases, obesity in 27.7%, overweight in 56.7%, android obesity in 36.0% and smoking in 61.4% of men and 4.2% of women
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Dissertations / Theses on the topic "Android obesity"

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Briand, Sophie. "Rôle du stress et de la détresse psychologique dans les anomalies endocrino-métaboliques de l'obésité androïde." Bordeaux 2, 2001. http://www.theses.fr/2001BOR2M015.

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Book chapters on the topic "Android obesity"

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Revathy, N., S. Vasanth, M. Thenmozhi, T. Guhan, and K. Padmavathi. "Diabetes Prediction Using Support Vector Machine With Android Applications." In Shaping the Digital Future: From Algorithms to Intelligence. QTanalytics India, 2025. https://doi.org/10.48001/978-81-980647-6-9-2.

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Diabetes Mellitus is a critical disease affecting millions globally, with its prevalence rising alarmingly due to lifestyle changes and environmental factors. Key contributors to diabetes include age, obesity, lack of exercise, hereditary diabetes, poor dietary habits, and high blood pressure. Patients diagnosed with diabetes face a heightened risk of severe complications, including heart disease, kidney failure, and stroke, which can significantly impact their quality of life. Current diagnostic practices in healthcare often involve extensive testing, which is not only time-consuming but also resource-intensive, leading to delays in treatment. In recent years, Machine Learning (ML) and Big Data Analytics have emerged as transformative tools in healthcare, enabling the extraction of meaningful insights from vast datasets. This paper proposes a streamlined machine learning-based approach for diabetes prediction, aimed at improving accuracy and efficiency. By utilizing a Support Vector Machine (SVM) classifier, undersampling techniques for class balance, and deployment through FastAPI, this work delivers a deployable pipeline with high prediction accuracy and real-time application capabilities.
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Moulos Ioannis, Maramis Christos, Mourouzis Alexandros, and Maglaveras Nicos. "Designing the User Interfaces of a Behavior Modification Intervention for Obesity & Eating Disorders Prevention." In Studies in Health Technology and Informatics. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-512-8-647.

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The recent immense diffusion of smartphones has significantly upgraded the role of mobile user interfaces in interventions that build and/or maintain healthier lifestyles. Indeed, high-quality, user-centered smartphone applications are able to serve as advanced front-ends to such interventions. These smartphone applications, coupled with portable or wearable sensors, are being employed for monitoring day to day health-related behaviors, including eating and physical activity. Some of them take one step forward by identifying unhealthy behaviors and contributing towards their modification. This work presents the design as well as the preliminary implementation of the mobile user interface of SPLENDID, a novel, sensor-oriented intervention for preventing obesity and eating disorders in young populations. This is implemented by means of an Android application, which is able to monitor the eating and physical activity behaviors of young individuals at risk for obesity and/or eating disorders, subsequently guiding them towards the modification of those behaviors that put them at risk. Behavior monitoring is based on multiple data provided by a set of communicating sensors and self-reported information, while guidance is facilitated through a feedback/encouragement provision and goal setting mechanism.
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Arantes, Joicy Guerra, Geovana Pires, Éveny Gonçalves Moura, et al. "Metabolic syndrome: a review and clinical case." In DEVELOPMENT AND ITS APPLICATIONS IN SCIENTIFIC KNOWLEDGE. Seven Editora, 2023. http://dx.doi.org/10.56238/devopinterscie-026.

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The term "Metabolic Syndrome" (MS) refers to a cluster of risk factors for cardiovascular disease (CVD), most notably obesity, type 2 diabetes, dyslipidemia, and hypertension, whose pathophysiology is attributed to insulin resistance. Individuals with android-type obesity have high levels of plasma insulin, often associated with glucose intolerance, hypertriglyceridemia, and arterial hypertension, constituting an important metabolic condition, which is also strongly associated with hepatic steatosis. In addition, the increase in triglycerides and the reduction in HDL or drug treatment can be used as an alternative indicator of this syndrome, with a worldwide prevalence of 25%, accounting for 7% of mortality and 17% of deaths related to CVDs. The objective of this study is to analyze the clinical picture of a patient who has a diagnosis with MS, through bibliographic reviews, test results, and medical reports. The patient is a 40-year-old woman, diabetic, hypertensive, and obese, with a family history of diabetes, and her grandmother and mother being affected by The disease. We observed that MS does not refer to a specific disease, but to a set of risk factors, of metabolic origin, with a tendency to group, and that the main aggravating factor observed regarding the patient's health was the lack of preventive care with the health since he had a history of diabetes in his family, which led to the development of the syndrome.
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Conference papers on the topic "Android obesity"

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Rychkova, Lyubov, Ekaterina Sheneman, Tatyana Bairova, Vladimir Polyakov, and Aryuna Kosovtseva. "P519 Psychological interventions and motivation for weight loss in girls with android obesity." In Faculty of Paediatrics of the Royal College of Physicians of Ireland, 9th Europaediatrics Congress, 13–15 June, Dublin, Ireland 2019. BMJ Publishing Group Ltd and Royal College of Paediatrics and Child Health, 2019. http://dx.doi.org/10.1136/archdischild-2019-epa.854.

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Barbosa, Maria Lúcia Kroeff, Luciano Zancan, Mario Figueiró Zemor, Valter Roesler, Marcia Rosa Da Costa, and Sílvio César Cazella. "Sistema Emagreça@Saudável para controle da obesidade em adultos." In XXIV Simpósio Brasileiro de Sistemas Multimídia e Web. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/webmedia.2018.4584.

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This paper presents the Slim&Healthy system, focusing on the control of obesity in adults and aiming at the adoption of healthy habits. The system consists of two parts: a) an Android application on the client mobile device; b) an application on a server. The paper integrates different theories to increase user motivation, such as gamification, social networks, design heuristics for mobile devices and behavioral theories. It was performed an evaluation of the application interface through a questionnaire adherent to standards ISO 9241-11 and ABNT ISO/IEC 25062:2011, and the results are presented for discussion.
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Sheneman, Ekaterina, Tatyana Bairova, Ksenia Ievleva, Lyubov Rychkova, and Olga Bugun. "GP222 Clinical and metabolic parameters in girls-carriers of LEPR rs1137100 with android and gynoid obesity." In Faculty of Paediatrics of the Royal College of Physicians of Ireland, 9th Europaediatrics Congress, 13–15 June, Dublin, Ireland 2019. BMJ Publishing Group Ltd and Royal College of Paediatrics and Child Health, 2019. http://dx.doi.org/10.1136/archdischild-2019-epa.281.

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Kulikova, N. G., A. S. Tkachenko, and T. V. Konchugova. "Psychological Aspects of Evaluation of Women with Android Type of Obesity in their Early Postpartum Period." In IV научно-практическая конференция «Арбатские чтения». Знание-М, 2021. http://dx.doi.org/10.38006/907345-95-9.2021.45.54.

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: Проведена оценка психоэмоционального статуса и уровня реактивной тревожности у женщин с андроидным типом ожирения в раннем послеродовом периоде в динамике применения у них комплексного физиотерапевтического лечения. Данное исследование посвящено разработке новых методов реабилитационной физиотерапии, позволяющих корригировать психоэмоциональный статус женщин с андроидным типом ожирения в раннем послеродовом периоде. Предложены наиболее эффективные физиотерапевтические комплексы для коррекции локальных жировых отложений и психоэмоционального статуса.
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Umarova, Irina, Olga Balionis, and Alexander Gorelov. "The efficacy of noninvasive positive pressure ventilation in patients with obesity hypoventilation syndrome according to the android/gynoid fat ratio and position of ventilation." In Annual Congress 2015. European Respiratory Society, 2015. http://dx.doi.org/10.1183/13993003.congress-2015.oa4783.

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