Body Mass Index, Sleep Quality, Stress Conditions Determine Menstrual Cycles Among Female Adolescents

Menstrual cycles are an important indicator of women's health. Menstrual cycles can be affected by body mass index (BMI), sleep quality, and stress. This study aimed to analyse the relationship between BMI, sleep quality, stress and the menstrual cycle. The subjects of this research were the female adolescents at the age of at least 15 years old that had experienced menstruation for at least 2 years. The dependent variable is the menstrual cycle while the independent variables are BMI, sleep quality, and stress conditions. Observational analytic research method with Cross sectional design was used in this research. The subjects were 148 female students. The BMI data were obtained through the anthropometric measurement. The sleep quality data were taken with PSQI questionnaire, and the stress condition data obtained from PSS-10 questionnaire which were then analysed using Chi-Square test and Logistic Regression. Results of study showed that there is a significant relationship between BMI, sleep quality, stress conditions and the adolescent menstrual cycle. The results of the multivariate analysis showed that the female adolescents with abnormal BMI are at risk of having menstrual cycle disorders 1.91 times. The adolescents with poor sleep quality are at risk experiencing menstrual cycle disorders 2.05 times, and the adolescents with stress conditions at risk of the menstrual cycle disorders 2.26 times. There is a relationship between BMI, sleep quality, stress conditions and the menstrual cycle. Stress conditions most influence the regularity of the menstrual cycle

Rethinking the Body Mass Index Initiative

In February 2005, the Office for Education Policy published a fact sheet detailing Arkansans’ attitudes toward the Body Mass Index initiative (BMI) and found that the state was roughly divided on the issue. Since 2005, the results of BMI screening have been chronicled in a pair of government reports, and the General Assembly has acted to modify how BMI testing is undertaken. In this policy brief we outline what the research indicates after three years of BMI testing, and how the laws surrounding BMI have changed

The Association between Body Mass Index, Religion Index, Media, and Body Image in Adolescents

BACKGROUND: Adolescents experience bio-psychosocial change in their developmental stages. These changes influence their perception about their body look. Some start to dislike their appearance. Someone‟s religiosity may protect them from the negative impact of the environment. Meanwhile, the mass media campaign about “slim ideal” for women and “shape and muscle” for men, is massive. This study aimed to examine the association between body mass index (BMI), religiosity, mass media, and body image in adolescents. SUBJECT AND METHODS: This was a cross sectional study. A sample of 116 students was selected at random for this study from one public and one private senior high school in Surakarta, Indonesia. The dependent variable was negative body image. The independent variables included body mass index (BMI), religiosity, and exposure to “slim ideal” mass media. Body image was measured using Body Shape Questionnaire. Religi-osity was measured using Duke University Religion Index Questionnaire. The data was analyzed using linear regression model. RESULTS: BMI (b=3.22; 95%CI 2.08 to 4.36; p<0.001) and exposure to “slim ideal” mass media (b=16.35; 95%CI 1.92 to 30.78; p=0.027) had positive association with negative body image, and it was statistically signi-ficant. Religiosity (b=-3.10; 95%CI -11.86 to 5.64; p=0.483) had negative association but statistically not significant with negative body image. CONCLUSION: BMI and exposure to “slim ideal” mass media have positive association with negative body image in adolescents. Keywords: body image, adolescents, Body Mass Index, religion index, media

Aplikasi Simulasi Body Mass Index Berbasis Web dengan Menggunakan Metode Fuzzy Logic

Memiliki badan yang ideal merupakan dambaan daripada setiap orang baik itu orang tua maupun orang muda. Badan yang ideal sangat berpengaruh pada penampilan fisik dan kesehatan setiap orang. Terkait hal tersebut, suatu aplikasi simulasi Body Mass Index dengan menerapkan konsep Kecerdasan buatan didalamnya terlebih khusus menggunakan metode Fuzzy Logic berhasil dikembangkan. Aplikasi ini dapat membantu setiap orang untuk dapat mengetahui keadaan badan mereka pada saat ini, apakah ideal ataukah tidak ? Pada aplikasi ini tinggi badan dan berat badan menjadi input, yang kemudian diolah dengan menggunakan metode Fuzzy Logic dan menghasilkan 4 buah output yang berupa kategori kondisi badan yaitu : tidak sehat, agak sehat, sehat dan sangat sehat. Keempat kategori tersebut sudah dilengkapi dengan autosuggesstion yaitu berupa rekomendasi apa yang dapat dilakukan oleh user untuk selanjutnya. User dapat menggunakan aplikasi ini untuk mengevaluasi keseimbangan dan merubah gaya hidup lebih baik lagi. Kata kunci : Body Mass Index, Artificial Intelligence, Fuzzy Logic, Suggesstio

Association between Body Mass Index, Type of Occupation, History of Chronic Illness, and Poor Occupational Posture

Background: Good posture is important for an individual health as well as appearance. Poor occupational posture may cause negative impacts such as soreness & pain, poor circulation, negative mood, increased stress, carpal tunnel synd¬rome, less motivation, poor digestion, and fatigue. The purpose of this study was to determine the association between body mass index, type of occupation, his¬tory of chronic illness, and poor occupational posture. Subjects and Method: This was a cross-sectional study conducted at Dr. Moewar¬di hospital, Surakarta, Central Java, from April to May 2018. A sample of 116 patients was selected for this study by fixed disease sampling. The dependent va¬ri¬able was occupational posture. The independent variables were body mass index, type of occupation, and history of chronic illness. Occupational posture da¬ta were measured by Rapid Entry Body Assessment (REBA) questionnaire. The other variables were measured by questionnaire. The data were analyzed by a mul¬¬tiple logistic regression. Results: Poor occupational posture was associated with body mass index ≥25 (OR= 0.99; 95% CI= 0.02 to 1.96; p= 0.044), heavy occupational type (OR= 2.24; 95% CI= 1.34 to 3.14; p<0.001), and history of chronic illness (OR= 0.78; 95% CI= -0.10 to 1.67; p= 0.084). Conclusion: Poor occupational posture is associated with body mass index ≥25, heavy occupational type, and history of chronic illness. Keywords: occupational posture, body mass index, occupational type, history of ill¬nes

The sitting-height index of build, (body mass)/(sitting height)³, as an improvement on the body mass index for children, adolescents and young adults

The body mass index (BMI) is unsatisfactory in being affected by both relative leg length and height, and, for use with children and adolescents, therefore needs to be interpreted in relation to age. The sitting-height index of build (body mass)/(sitting height)3, is largely free of these disadvantages. Furthermore, because that index is independent of relative leg length, the latter can be treated as a separate indicator of nutritional history and health risks. Past studies on white children and adults have shown body mass to be approximately proportional to (sitting height)3. Moreover, multiple regression of (body mass)1/3 on sitting height and leg length, using year-by-year averages, has indicated that leg length is an insignificant predictor of body mass. The present study used data for individuals, namely 2–20 years old males and females, black as well as white. Regression analysis as above again showed leg length to be an insignificant predictor of body mass, but only above the age of about nine years. However, sitting height is still a stronger predictor of body mass than leg length at all ages. The advantages of the sitting-height index of build for use with young people are confirmed