scholarly journals Effect of Body Weight Change on Blood Pressure in a Japanese General Population with a Body Mass Index ≥ 22 kg/m2

2019 ◽  
Vol 60 (6) ◽  
pp. 1381-1386 ◽  
Author(s):  
Hidetaka Itoh ◽  
Hidehiro Kaneko ◽  
Hiroyuki Kiriyama ◽  
Koki Nakanishi ◽  
Yoshiko Mizuno ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
Body Weight ◽  
General Population ◽  
Body Mass ◽  
Weight Change ◽  
Body Weight Change ◽  
Japanese General Population

Association Between Body Weight Change Before and After Delivery and Development of Nonmetabolic Syndrome: A Prospective Study

2018 ◽  
Vol 50 (01) ◽  
pp. 17-22
Author(s):  
Zhao Ya ◽  
Zeng Yue ◽  
Liu Dan ◽  
Lin Neng-bo ◽  
Luo Yi ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Body Weight ◽  
Confidence Interval ◽  
Body Mass ◽  
Weight Change ◽  
Body Weight Change ◽  
Relative Risks ◽  
Delivery Times ◽  
Before And After

AbstractThe aim of the work was to investigate the association between body weight change before and after delivery and development of nonmetabolic syndrome in Chinese females aged ≥40 years. We selected 789 participants without metabolic syndrome randomly from a baseline survey performed in Luzhou, China in 2011. We took the group with decreasing or no increasing body mass index difference during a pregnancy as “R-Body Mass Index 1” (n=286) and divided the group with increasing body mass index difference during a pregnancy into “R-Body Mass Index 2” (n=254) and “R-Body Mass Index 3” (n=249) based upon P50. All study participants were followed up every year, and a questionnaire, physical examination, and biochemical detection were administered after 3 years. Of 789 participants, 82 nonmetabolic syndrome women developed metabolic syndrome during 3-year follow-up. The morbidity of metabolic syndrome in the R-BMI1, R-BMI2, and R-BMI3 groups was 5.2%, 11.8%, and 14.9%, respectively. Compared to the R-BMI1 group, the relative risk for R-BMI2 was 1.92 (95% confidence interval: 1.03–3.58, p=0.040) and for R-BMI3 was 2.20 (95% confidence interval: 1.20–4.03, p=0.011). After adjusting for age, BMI, WHR, baseline blood glucose, HbA1c, TG, HDL-C, SBP, DBP, age of menarche and menopause, and delivery times, the relative risks were similar to the unadjusted relative risks. In conclusion, body weight change after delivery was associated with metabolic syndrome: the higher the weight gain, the higher the risk of metabolic syndrome.

scholarly journals A Prevalent Polymorphism in the Promoter of theUCP3Gene and Its Relationship to Body Mass Index and Long Term Body Weight Change in the Danish Population1

2001 ◽  
Vol 86 (3) ◽  
pp. 1398-1402 ◽  
Author(s):  
Louise T. Dalgaard ◽  
Thorkild I. A. Sørensen ◽  
Thomas Drivsholm ◽  
Knut Borch-Johnsen ◽  
Teis Andersen ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Body Mass ◽  
Weight Change ◽  
Body Weight Change

scholarly journals Relationship between Body Mass Index, Blood Pressure, and Visual Acuity in Residents of Esan West Local Government Area of Edo State, Nigeria

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
I. O. Ernest-Nwoke ◽  
M. O. Ozor ◽  
U. Akpamu ◽  
M. O. Oyakhire
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
Visual Acuity ◽  
Body Weight ◽  
Local Government ◽  
Body Mass ◽  
Local Government Area ◽  
Cross Sectional ◽  
Snellen Chart ◽  
Edo State

Aim. To study the relationship between body mass index (BMI) and blood pressure (BP) on visual acuity among apparently healthy residents of Ekpoma, Esan West Local Government Area of Edo State, Nigeria. Methodology. This is a cross-sectional descriptive study among 225 subjects (ages of 18–35 years) from whom BP, body weight, and height were collected. Visual acuity was measured using the Snellen chart following standard procedures of number of letters seen at 6-metre distance. The data were then analyzed using SPSS version 17. Results. The sampled population consists of 112 male and 113 female (mean age 31.72±14.2 years). Majority (180) of the respondents had normal visual acuity. However, compared with the respondents with normal BMI (R19.61±1.5; L19.67±1.70), visual acuity of underweight (R18.53±2.30; L18.53±2.70) and obese (R15.68±4.79; L17.73±1.70) were more deviated. Similarly, compared with respondent with normal BP (120–125/80–85 mmHg; R18.00±2.53; L18.07±3.11), hypotensive (R15.5±7.35; L15.00±10.20), and hypertensive (R15.01±21.25; L15.00±11.91) respondents had deviated visual acuity. Conclusion. Abnormal body weight (underweight and obese) and BP (hypotension and hypertension) have potential negative impacts on visual acuity. Based on the observed relationship between weights, BP, and visual acuity, eye examinations can be included as regular screening exercise for abnormal BMI and BP conditions.

scholarly journals Effect of Metformin Therapy on Clinical and Hormonal Indices of Patients with Polycystic Ovary Syndrome

2021 ◽  
Vol 15 (5) ◽  
pp. 1522-1525
Author(s):  
S. Inayat ◽  
H. F. Khattak ◽  
M. G. Muhammad ◽  
K. Robeen ◽  
A. Inayat ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
Body Weight ◽  
Polycystic Ovary Syndrome ◽  
Blood Sugar ◽  
Body Mass ◽  
Polycystic Ovary ◽  
Fasting Blood Sugar ◽  
Ovary Syndrome ◽  
Group Ii

Objective: The main objective of this study is to determine the efficacy of metformin therapy on clinical and hormonal indices of patients with polycystic ovary syndrome. Study Design: Randomized control trial Place and Duration: Study was conducted at Obstetrics & Gynaecology department of Northwest General Hospital and Research Center, Peshawar and Mian Rashid Hussain Shaheed Memorial Hospital, Pabbi for duration of nine months from March 2020 to November 2020. Methods: Total 100 patients of polycystic ovary syndrome were presented in this study. Patients were aged between 18 to 45years. Patients detailed demographics including age, body mass index and socio-economicstatus were recorded after taking informed written consent. Patients were divided into 2-groups, group I had 50 patients and received metformin (500 mg) three times a day and group II had 50 patients and received pioglitazone (30 mg) three times a day for 3months.Clinical (body weight, blood pressure (BP), and body mass index) and indices fasting blood sugar (FBS), serum triglyceride (TG), cholesterol, low-density lipoprotein, high-density lipoprotein, insulin, testosterone, and dehydroepiandrosterone (DHEA) were measured before and after therapy. Complete data was analyzed by SPSS 22.0 version. Results: Mean age of the patients in group I was 29.18 ± 2.25 years with mean BMI 26.14 ± 8.86 kg/m2 and in group II mean age was 29.8 ± 2.52 years with mean BMI 27.64 ± 7.68 kg/m2.Significantly decrease in blood pressure (systolic 105.41±8.57, diastolic 67.19±8.9), hair loss 20 (40%),oligomenorrhea 23 (46%), body weight 74.45±9.72, waist circumference and dehydroepiandrosterone (DHEA) 2.35±0.67 and as compared to group II. Only triglycerides gave results of reduction in group II 115.39±64.11. Among both groups serum insulin, acne, menstrual disturbance and fasting blood sugar were controlled after treatment. Conclusion: We concluded in this study that use of metformin in patients with polycystic ovary syndrome resulted in to decrease clinical body weight, blood pressure (BP), body mass index and hormonal indices with reduction of serum insulin, acne, menstrual disturbance and fasting blood sugar but pioglitazone was an alternative effective and reliable method in PCOS patients. Keywords: Polycystic ovary syndrome, Insulin resistance, Metformin, Pioglitazone

scholarly journals Metabolic risk factor profile in patients on treatment with second generation antipsychotics

2016 ◽  
Vol 41 (3) ◽  
pp. 144-150
Author(s):  
Tahmina Zahan ◽  
Nargis Akhter ◽  
Mohammad Sayadul Islam Mullick ◽  
Zasmin Fauzia
Keyword(s):  
Diabetes Mellitus ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Bipolar Disorder ◽  
Body Weight ◽  
Adverse Effects ◽  
Body Mass ◽  
Second Generation ◽  
Density Lipoprotein ◽  
Second Generation Antipsychotics

The second generation antipsychotic agents, although exhibit superior safety profile, is associated with metabolic adverse effects including weight gain, diabetes mellitus and hyperlipidaemia. These adverse effects are not only the risk factors for cardiovascular disease and diabetes mellitus but may also impair patient’s adherence to treatment. However, different member of second generation antipsychotics differ in their extent of metabolic adverse effects. The aim of the study was to evaluate the association between olanzapine, risperidone or quetiapine treatment and body mass index, blood pressure, diabetes mellitus and hyperlipidaemia in patients with Schizophrenia and Bipolar Disorder. Forty-four cases of Schizophrenia and Bipolar Disorder diagnosed with DSM-IV criteria were selected according to inclusion and exclusion criteria. Body weight, body mass index and blood pressure were measured at baseline, at the end of 4th, 8th and 12th weeks of treatment. Blood samples were collected to measure blood glucose and serum lipid profile at baseline and at the end of 4th, 8th and 12th weeks in the study group receiving treatment (olanzapine 20-30 mg/day, risperidone 4-16 mg/day and quetiapine 300-800 mg/day) after overnight fasting. Therapeutic use of olanzapine and risperidone in Schizophrenia and Bipolar Disorder for a period of 4th, 8th and 12th weeks was associated with significant increase in body weight and body mass index. Quetiapine did not cause significant changes in body weight and body mass index after 4 and 8 weeks. However, after 12 weeks treatment, body mass index increased significantly. Olanzapine, risperidone and quetiapine increased the blood glucose level significantly after 8 and 12 weeks treatment. Olanzapine and risperidone elevated the serum cholesterol, triglyceride and low density lipoprotein levels significantly after 4, 8 and 12 weeks. But quetiapine showed no significant change in lipid profile. However, olanzapine and risperidone significantly increased triglyceride level after 8 and 12 weeks. Amongst three drugs, quetiapine treatment increased high density lipoprotein level. Our study revealed that quetiapine treatment is associated with less risk of dyslipidaemia.

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