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WHO Asian-BMI classification
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Background:
Obesity is a complex, multi-factorial chronic disease. Overweight and obesity are the fifth leading risk for global deaths.
Objectives:
To find the prevalence and risk factors for obesity in women aged 20-60 years in Ludhiana city.
Methods:
The present study is a community based cross sectional study carried out in an urban area of...
Context in source publication
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Citations
... Women are much more prone to obesity compared to men [2]. National Family Health Survey (NFHS)-3 of India reports approximately 13% of the women as obese between age 15-59 years [3]. The exponential increase in the risk of diabetes [4], hypertension [5], cardiovascular diseases [6], and cancer [7] makes obesity one of the huge disease burdens. ...
Background
Obesity is a rising risk factor for various diseases including cardiovascular diseases and Cancer. The limitations of targeted obesity-treatment approaches employed in the clinic presently underscore the importance of developing integrative management strategies for identification of specific biomarkers of obesity. Objectives: Given the specificity of exosome/extracellular vesicle (EV) biomarkers, we aimed here to identify the EV biomarkers of Ayurveda treatment – Lekhana Basti – for Obesity.
Methodology
A total of eighteen 24-h urine samples from 6 participants with BMI>30 kg/m² were used in this study, collected over 3 time-points during the Lekhana basti (medicated enema for obesity) treatment. Urine EV were isolated using Polyethylene Glycol (PEG). The proteins were resolved by 1-d gel electrophoresis and identified using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and quantified by label-free methods. Significant Protein-Protein Interactions, KEGG pathway analysis and enrichment, functional gene ontology (GO) annotation were identified and shortlisted in comparison to Obesity reference genes from DisGeNET.
Results
With UniProt as a reference subsequent to LC-MS/MS-identification, a total of 210 exosome proteins were identified. Seventy-three proteins were overexpressed in pathway enrichment analysis. Further, GO functional annotation identified 15 common proteins involved. Finally, the 8 hub proteins associated with obesity were identified and their differential expression profile compared between three different time-points during Lekhana Basti treatment. Six protein markers overexpressed during obesity were downregulated post Lekhana Basti treatment, while 2 markers increased in abundance post-treatment.
Conclusion
To our knowledge, this is the first study to isolate and identify urine EV protein abundance profiles from obese female participants of India. The study results indicate significant changes in the differential expression profile of 8 hub proteins involved in obesity, after Lekhana Basti treatment. The biomarker signature of the pilot study indicates the role of Ayurveda treatment and the possible pathways involved in the treatment of Obesity. Further, this study underlines the specificity of urine exosomes/EV as diagnostic markers as well as the potential of Ayurveda treatment in effective management of obesity.
... BMI was classified according to WHO Asian-BMI classification. 16 7. Random Blood Sugar (RBS) was tested for high-risk individuals i.e. individuals with risk score of >60, using a Digital Glucometer. 8. Indian Diabetes Risk Score: The risk of diabetes was assessed using The Indian Diabetes Risk Score (IDRS) which consisted of 4 components and each one has it's scoring: ...
Background: Diabetes mellitus is one of the leading causes of long term morbidity and is a major health hazard in a developing country like India. Because of the disease’s growing burden, its iceberg nature, its consequences, and the ability to prevent the complications through early identification and treatment, strong efforts for early diabetes diagnosis are essential. Early identification of the high risk individuals would help in taking appropriate intervention thus helping to prevent, or at least delay, the onset of diabetes. Indian Diabetes Risk Score (IDRS) is a cost-effective tool for screening of undiagnosed diabetic individuals in the community. Methods: A community based cross sectional study was conducted in the urban field practice area of Indira Gandhi Government Medical College, Nagpur, Maharashtra among 360 participants above 18 years of age. Indian Diabetes Risk Score (IDRS) was used to assess risk of diabetes. Chi-square test was applied to determine association between variables. Results: Out of the 360 study participants, 86 (23.89%), 156 (43.33%) and 118 (32.78%) participants were in low risk, moderate risk and high risk categories respectively. Risk of diabetes was significantly associated with age, socioeconomic status, physical activity, adequate fruit and vegetable intake, high consumption of sweet foods, history of hypertension, family history of diabetes, body mass index and waist circumference. Conclusions: Risk assessment using IDRS is useful for screening of individuals. This would help to take necessary interventions for their early diagnosis and treatment.
... In recent years, rates of obesity and overweight are increasing in lowand middle-income countries. The rise in these risk factors has been linked to the increase in high-calorie nutritional choices, processed snacks, and sugary beverages, along with a reduction in physical activity related to technological advances (Akande et al., 2015;Girdhar et al., 2016;Msyamboza et al., 2013;Neupane et al., 2016). People with obesity and overweight are two to three times more likely to suffer from noncommunicable diseases (NCDs), including type 2 diabetes mellitus (T2DM) and hypertension (Hernández-Hernández et al., 2010). ...
... The body mass index (BMI) has been categorized according to Asian parameters. Underweight is categorized as a BMI less than 18.5 kg/m 2 ; normal weight, a BMI from 18.5 to 22.9 kg/m 2 ; overweight, a BMI from 23.0 to 24.9 kg/m 2 ; and obesity, a BMI of more than 25 kg/m 2 [3]. The recommended ranges of weight gain for pregnancy are 12.5 to 18.5 kg for women with underweight, 11.5 to 16 kg for women with normal weight, 7 to 11.5 kg for women with overweight, and 5 to 9 kg for women with obesity [4]. ...
Background
Obesity is described as excessive fat accumulation. Almost 47% of pregnant women gain more weight than recommended. The prevalence of obesity doubled from 2007 to 2018 (10.5% to 21.8%) in Indonesia. An increase in body mass index (BMI) before pregnancy is associated with delayed labor and vaginal delivery failure. Women with overweight or obesity in pregnancy are at increased risk of developing gestational hypertension and gestational diabetes, resulting in the induction of labor or elective cesarean section. This study aimed to investigate the correlation between pre-pregnancy BMI and outcomes from induction of labor in 248 women during 1 year at a hospital in Purwokerto, Indonesia.
Material/Methods
The study was conducted at Margono Soekarjo General Hospital and involved all pregnant women delivered between 2023 and 2024. Inclusion and exclusion criteria were applied. Total number of pregnant women was 248, BMI used Asian parameters, induction of labor was performed with oxytocin or misoprostol, and outcomes were according to the International Federation of Gynecology and Obstetrics. The design was a case-control study. Statistical analysis performed using IBM SPSS Statistics version 29.0.1.0 was used to analyze odds ratio and chi-square test.
Results
This research study revealed pregnant women with obesity had statistically significant higher odds, with an odds ratio of 3.78 (95% CI 1.53–9.31, P=0.002), of labor induction failure than did those without obesity.
Conclusions
The findings from this study showed that increased BMI in pre-pregnancy significantly increased the risk of failure of labor induction.
... In addition, BMI cut-offs used in this study are in line with the World Health Organization Asian-BMI classification for the South Asian population [16]. ...
Background
The saphenous nerve, a sensory branch of the femoral nerve, is not commonly included in routine lower extremity nerve conduction studies due to a high frequency of non-recordable responses in healthy subjects. However, saphenous nerve conduction studies are sometimes utilized for the diagnostic assessment of isolated lumbosacral plexus, femoral, or saphenous mononeuropathies. Our study aims to determine normative saphenous nerve response values in a healthy Pakistani population and to investigate their associations with patient body mass index, age, and gender.
Methods
This cross-sectional descriptive study was undertaken over a 3‑month period (May to July 2021) at a neurophysiology department of a tertiary care center in Pakistan. Healthy subjects underwent neurological examination, anthropometric measurements, and bilateral SN nerve conduction studies, with recording of peak-latency, peak-to-peak amplitude and conduction velocity. Statistical analyses and linear regression were conducted to evaluate associations between nerve conduction study variables and patient characteristics. Statistical analyses were also run to assess patient characteristics affecting recordability of saphenous nerve responses. A p-value < 0.05 was considered statistically significant.
Results
Among 117 subjects, 79.5% (n = 93) had recordable saphenous nerve responses. Median peak-latency, amplitude, and conduction velocity were 3.2 (3.0-3.3) m/s, 7.7 (5.8–9.9) uV, and 44.0 (42.0–47.0) m/s, respectively. Bilaterally absent responses were observed in 20.5% (n = 24) of subjects. Obese participants had a significantly higher number of absent saphenous responses (p = 0.033). Females had shorter peak-latency (p = 0.006) and higher conduction velocity (p = 0.012).
Conclusions
Saphenous nerve responses can be used to assess unilateral femoral and saphenous nerve pathologies, provided they are recordable on the asymptomatic side for comparison. Absent bilateral saphenous nerve responses should be interpreted with caution given their prevalence in healthy individuals. Patient characteristics should be taken into consideration when interpreting recordable and nonrecordable saphenous nerve responses.
... In affluent families, sedentary lifestyle and less labour-intensive work led to maternal obesity [39][40][41]. Further, children from wealthier families were used to consumption of processed junk food leading to malnutrition [42][43][44]. On the contrary, lower socioeconomic status families would have a limit on food with labour intense work led to malnutrition [45]. ...
Introduction
Improper consumption of food leads to various forms of malnutrition such as undernutrition, overnutrition and micronutrient deficiency. The coexistence of various malnutrition forms in the same household is a public health concern in developing countries. Very little research has been done on exploring the burden and risk factors associated with double (DBM) and triple burden of malnutrition (TBM).
Methods
Secondary analysis was done using data from India's National Family Health Survey-5 (NFHS-5), 2019-21. Mothers and under-five children were paired at the household level as a unit of analysis. DBM and TBM were interpreted from children's height-for-age, weight-for-height, weight-for-age and anaemia status and mothers' body-mass-index. Stratification and clustering in the sample design were accounted for during the analysis in STATA v14.2. DBM and TBM were summarized as weighted proportions with 95 % confidence interval (CI) and the risk factors associated were reported as adjusted odds ratio (aOR) with 95%CI using mixed effects logistic regression.
Results
We included 167,380 mother-child pairs for analysis. In India, the prevalence of DBM was 7.7 % (95 % CI: 7.5–7.9 %) and TBM was 5.1 % (5.0–5.3 %) at the household level among mother-child dyads. Mothers' age, age at first birth, educational levels, current breastfeeding habits, mode of delivery, child's age, gender, twin birth, birth weight, geographical region, residence, caste and religion, and wealth index were associated with both DBM and TBM.
Conclusion
Both DBM and TBM are public health concerns in India. Thus, scaling-up of health intervention, effective implementation of nutritional programmes and life-course approach are needed to control malnutrition.
... There are two World Health Organization (WHO) classifications of BMI: an individual is categorized as obese if the BMI is greater than or equal to 30 (kg/m 2 ) 1 or if the BMI is greater than or equal to 25 (kg/m 2 ) according to the WHO Asia-Pacific classification. 2 Obesity has become an epidemic with severe consequences for the global health and economy, with the increasing prevalence of obesity contributing to the decline in the quality and life expectancy of future generations. 3 According to WHO, in 2022, 8 billion of the world's population were obese. ...
Obesity is a condition in which there is an accumulation of excess body fat leading to a weight far above the normal range that poses significant health risks. According to WHO, 8 billion people in the world were obese in 2022. Consequently, obesity has become a pandemic with negative impacts on both global health and economies. Obesity is influenced by various factors including environmental influences, lifestyle choices, gut microbiota, genetic factors, and epigenetic mechanisms such as DNA methylation. DNA methylation can affect an individual’s phenotype and condition without altering their DNA sequence. It is the most extensively studied epigenetic alteration and it plays an important part in controlling gene activity associated with obesity. Numerous studies have indicated that DNA methylation is implicated in obesity, thus this review aims to elaborate the roles of DNA methylation to inform the development of preventive measures for obesity.
... kg/m 2 ), obese 1 (25-29.9 kg/m 2 ), and obese 11 (≥ 30 kg/m 2 ) [19]. A waist-to-hip ratio (WHR) ≥ 94.0 centimeters for males and ≥ 80.0 centimeters for females was classified as an unhealthy waist-to-hip ratio [20]. ...
Background
Suboptimal glycemic control of type 2 diabetes mellitus (T2DM) which is defined as having HbA1c greater than 7% is a major public health problem in several countries, including the Maldives. The study aimed to estimate the prevalence and determine factors associated with suboptimal glycemic control among T2DM patients.
Methods
A hospital-based cross-sectional was applied to collect data from T2DM patients who attended public hospitals in the Greater Male’ Region, Maldives where were one of the highest reports of T2DM and suboptimal glycemic control cases in the country between January to March 2023 by a validated questionnaire and anthropometric measurements. Five (5) ml blood specimens were collected to measure the glycated hemoglobin (HbA1c) level. Univariable and multivariable logistic regressions were employed to determine factors associated with suboptimal glycemic control of T2DM at a significant level of α = 0.05.
Results
A total of 341 participants were recruited for the study: 65.7% were female, 42.5% were aged 40–60 years, and 42.2% were married. The overall prevalence of suboptimal glycemic control was 50.7%. Ten variables were found to be associated with suboptimal glycemic control in multivariable logistic regression. Those aged 40–60 years (AOR = 3.35, 95% CI = 1.78–6.30), being single (AOR = 2.53, 95% CI = 1.21–5.30), preparation of food using more than three tablespoons of cooking oil (AOR = 2.78, 95% CI = 1.46–5.28), preparation of food with more than three tablespoons of sugar (AOR = 2.55, 95% CI = 1.31–4.93), no exercise (AOR = 2.04, 95% CI = 1.15–3.61), DM diagnosed with more than twenty years prior (AOR = 2.59, 95% CI = 1.34–4.99), obese body mass index (BMI) (AOR = 3.82, 95% CI = 1.75–8.32), high total cholesterol (AOR = 2.43, 95% CI = 1.36–4.35), high triglycerides (AOR = 3.43, 95% CI = 1.93–6.11), and high-level stress (AOR = 2.97, 95% CI = 1.48–5.93) were having a greater odds of having suboptimal glycemic control than those who did not have these characteristics.
Conclusion
A large proportion of T2DM patients in the Greater Male’ Region fail to control their blood glucose. Effective public health interventions should be introduced, especially interventions focused on reducing cooking oil and sugar in daily cooking practices, encouraging regular exercise, and maintaining cholesterol levels, particularly for those diagnosed with diabetes mellitus for more than 20 years prior.
... kg/m 2 , overweight 23-24.9 kg/m 2 , obesity I: 25-29 kg/m 2 , obesity II:>30 kg/m 2 [13]. ...
Objectives: To measure the Body Mass Index (BMI) and Blood pressure (BP) of newly enrolled undergraduate students in a medical university in Karachi, Pakistan, and to assess any association between BMI and BP levels among them. Methods: A cross-sectional study was conducted on pre-existing three-year data of 1403 students. The age, gender, BMI, and BP were recorded. The BMI of students was classified according to the Asian cutoff and BP was categorized using the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC) classification. Data was analyzed using SPSS version 24. Descriptive statistics were used to present quantitative and qualitative variables. The association was measured using the Chi-square test of significance. A p-value of < 0.05 was taken as significant. Results: Total 1403 students with a mean age of 19 + 1.4 years students were enrolled including 397 (28.3%) males and 1006 (71.7%) females. A total of 667 (47.5%) students had a normal weight while 216 (15.4%) students were underweight, and 512 (36.5%) were either overweight or obese. Mean systolic BP was 111.42 + 10.7 mmHg and mean diastolic BP was 73.45 + 7.96 mmHg. Most students had normal systolic BP 901 (64.2%) while 501 (35.7%) had prehypertension or stage-I or II hypertension (HTN). The majority of the students had normal diastolic BP 1357 (96.7%) and 45 (3.3%) had stage-I or II HTN. There was a significant association between BMI and BP (p<0.001). Conclusion: A significant number of the students are either under or overweight. There is a significant relationship between BMI and BP levels.
... 10 Body mass index (BMI) ≥25 kg/m 2 was considered obese. 11 For the Asian population central or abdominal obesity was defined as a WC≥90 cm for males and ≥80 cm for females. 4 ...
Background: The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is increasingly drawing worldwide attention. Among multiple risk factors, obesity is one of the factors that can influence the disease severity. This study aimed to explore the impact of obesity on the severity of COVID-19 infection. Methods: This cross-sectional study was conducted in the Department of Respiratory Medicine, Bangabandhu Sheikh Mujib Medical University, Dhaka from September 2020 to February 2021. The Adult (Aged ≥18 years) patients of both genders, who were COVID-19 positive, were included in this study. Ninety-one COVID-19 patients with BMI≥25 kg/m2 were set as case and another ninety-one patients with BMI<25 kg/m2 were selected as control. The patient's BMI and waist circumference (WC) were recorded. Disease severity was evaluated by the management of COVID-19 disease guidelines by the World Health Organization (WHO) 2020. Results: The maximum patients were male (65.38%), in the sixth and seventh decades. The proportion of severe illness was higher in the obese group 69.2% compared to the non-obese 47.3%. Patients with obesity require more ICU support (15.4% versus 5.5%) and invasive mechanical ventilation (9.9% versus 2.2%) compared to non-obese patients. In multivariate logistic regression analysis, after adjusting age, diabetes mellitus, and hypertension, obesity (BMI>25 kg/m2) was an independent risk factor for severe illness. Conclusions: Obese patients are associated with severe COVID-19 pneumonia. As BMI increases, disease severity increases, needs more ICU support, and needs more invasive mechanical ventilation.
