Obesity and visceral fat in Indonesia: An unseen epidemic? A study using iDXA and surrogate anthropometric measures

Smith, Marc; Christianto, Erwin; Staynor, Jonathan

doi:10.1016/j.orcp.2020.11.003

Cited by 9 publications

(11 citation statements)

References 25 publications

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“…Risk may also vary among different Asian countries 37 and for different ethnic groups, even those living in similar environments within the same country. 38 Thus, in Asian populations, lower BMI cut points should be used for overweight and obesity, to improve the identification of people at risk of cardiometabolic disease.…”

Section: Resultsmentioning

confidence: 99%

“…This difference in cardiovascular (CV) risk profile is seen for both men and women across weight categories and is most extreme in the normal weight range (BMI ranging from 18.5 to 24.9 kg/m 2 ). 36 Risk may also vary among different Asian countries 37 and for different ethnic groups, even those living in similar environments within the same country. 38 Thus, in Asian populations, lower BMI cut points should be used for overweight and obesity, to improve the identification of people at risk of cardiometabolic disease.…”

Section: Bmimentioning

confidence: 99%

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Obesity in South and Southeast Asia—A new consensus on care and management

Tham¹,

Ghani²,

Sioksoan

et al. 2022

Obesity Reviews

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Summary Obesity is a chronic disease in which the abnormal or excessive accumulation of body fat leads to impaired health and increased risk of mortality and chronic health complications. Prevalence of obesity is rising rapidly in South and Southeast Asia, with potentially serious consequences for local economies, healthcare systems, and quality of life. Our group of obesity specialists from Bangladesh, Brunei Darussalam, India, Indonesia, Malaysia, Philippines, Singapore, Sri Lanka, Thailand, and Viet Nam undertook to develop consensus recommendations for management and care of adults and children with obesity in South and Southeast Asia. To this end, we identified and researched 12 clinical questions related to obesity. These questions address the optimal approaches for identifying and staging obesity, treatment (lifestyle, behavioral, pharmacologic, and surgical options) and maintenance of reduced weight, as well as issues related to weight stigma and patient engagement in the clinical setting. We achieved consensus on 42 clinical recommendations that address these questions. An algorithm describing obesity care is presented, keyed to the various consensus recommendations.

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Section: Resultsmentioning

confidence: 99%

Section: Bmimentioning

confidence: 99%

Obesity in South and Southeast Asia—A new consensus on care and management

Tham¹,

Ghani²,

Sioksoan

et al. 2022

Obesity Reviews

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“…First, this study analyzed the cutoff for central obesity based on CT scan measurement of VAT area, which is a high-precision method and the gold standard for quantitative assessment of VAT [10]. Previous studies that assessed VAT in Indonesian population used bio-impedance analysis and Dual energy X-ray Absorptiometry (DXA) [31][32][33][34], which are not as accurate as CT or MRI [10]. Second, the formulas we developed to predict VAT only require two anthropometric parameters, rendering it a more practical substitute to the calculation by imaging methods which may not be available in rural areas of Indonesia.…”

Section: Plos Onementioning

confidence: 99%

Simple anthropometric measures to predict visceral adipose tissue area in middle-aged Indonesian men

et al. 2023

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The diagnosing of central obesity requires ethnic-specific cut-offs of waist circumference (WC) and body mass index (BMI). This study aims to develop formulas to predict visceral adipose tissue (VAT) area based on WC and BMI to determine the cut-off points of central obesity in Indonesia. We conducted a cross-sectional study among 32 middle-aged Indonesian men. VAT area was measured using an abdominal CT scan, whereas WC and BMI were assessed through anthropometric measurements. Linear regression analysis was performed to define the formulas to predict VAT area using WC and BMI. Next, the optimal cut-off values of WC and BMI were determined using ROC curve analysis. Strong positive correlations were found between WC and VAT as well as BMI and VAT (r = 0.78; r = 0.67, p <0.001). The formula to predict VAT area from WC was −182.65 + (3.35 × WC), whereas the formula to predict VAT area from BMI was −57.22 + (6.95 × BMI). These formulas predicted WC of 88.5 cm and BMI of 23.9 kg/m2 as the optimal cut-off values for central obesity in middle-aged Indonesian men.

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“…Hence, the study suggested using WC in clinical settings to identify individuals with high visceral adipose tissue that might lead to an increase in chronic diseases. [13] Another recent study among the Indonesian population that included 24,660 adult participants also delineated that when compared to BMI, WC (men = 76, women = 80) would be a better predictor for measuring central obesity to identify T2DM. [7]…”

Section: Diagnosis and Clinical Evaluationmentioning

confidence: 99%

“…[14] A recent study showed that the obesity prevalence in Indonesia is underestimated when using BMI (obese ≥ 27.0), since it misclassified 40% of obese people as normal or overweight. [13] Despite having a lower obesity prevalence than developed countries, increased chronic disease may be explained by Indonesia’s obesity levels being underestimated. [1,3,15,16] Another recent study on the Indonesian population depicted the new proposed cutoff of WC cutoff (76 cm for men and 80 cm for women), which is lower than the World Health Organization (WHO) standard.…”

Section: Introductionmentioning

confidence: 99%

The urgency in proposing the optimal obesity cutoff value in Indonesian population: A narrative review

et al. 2022

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In developing nations such as Indonesia, obesity and central obesity have emerged as major public health issues. Many studies have revealed that morbidity and death from obesity-related diseases are already significant in some “Asian” communities at low body mass index (BMI) levels. A recent study showed that the obesity prevalence in Indonesia is underestimated when using the current BMI cutoff (obese ≥ 27.0). Indonesia faced an increase in obesity-related chronic diseases despite having a lower obesity prevalence than developed countries, which may be explained by the underestimation of obesity levels in Indonesia. This creates a huge global health problem, as well as an economic burden. Another recent study on the Indonesian population depicted the new proposed cutoff of waist circumference (WC), which is lower than the World Health Organization (WHO) standard for detecting the early detection of type 2 diabetes mellitus (T2DM), one of the comorbidities and a strong correlation with obesity. An analysis of 58 studies in 2021 that included Indonesian adult subjects revealed enormous differences and ambiguities in defining obesity cutoffs values among Indonesian researchers. Additionally, we advocate adding the Edmonton Obesity Staging System (EOSS) staging to the anthropometric classification for a better clinical evaluation of obesity. Considering the urgency of obesity determination in Indonesia for clinical application and study purposes, this review highlights the need to revise the optimal cutoff value for obesity to warrant early prevention and control of diabetes complications.

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Obesity and visceral fat in Indonesia: An unseen epidemic? A study using iDXA and surrogate anthropometric measures

Cited by 9 publications

References 25 publications

Obesity in South and Southeast Asia—A new consensus on care and management

Obesity in South and Southeast Asia—A new consensus on care and management

Simple anthropometric measures to predict visceral adipose tissue area in middle-aged Indonesian men

The urgency in proposing the optimal obesity cutoff value in Indonesian population: A narrative review

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