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      Comparison of lipid accumulation product and body mass index as indicators of diabetes diagnosis among 215,651 Chinese adults

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          Abstract

          Purpose

          We aimed to assess if lipid accumulation product (LAP) could outperform body mass index (BMI) as a marker for diabetes diagnosis.

          Methods

          We analyzed the results of a national physical examination project in Urumqi, China. This project was conducted in 442 community clinics in Urumqi from October 2016 to February 2017.

          Results

          LAP was highly correlated with diabetes. The subjects with higher amounts of LAP had a higher risk of diabetes, and the prevalence of diabetes in the fourth quartile of LAP was dramatically higher than in the first quartile (5.72% vs. 21.76%). The adjusted odds ratios (AOR) associated with diabetes in the fourth quartile of LAP was significantly higher than the AOR associated with diabetes in the first quartile, and when BMI ≥ 28 kg/m 2 was compared with BMI < 28 kg/m 2 (3.24 (3.11, 3.37) vs. 1.65 (1.60, 1.70)). The LAP’s area under the curve (AUC) was significantly higher than the BMI’s AUC when based on diabetes (0.655 vs. 0.604). In the normal BMI group, 34% of participants had a LAP value higher than the cutoff point found during ROC analysis. In this subgroup, we observed a significantly higher prevalence of diabetes that was similar to that of the subgroup with a BMI ≥ 28 kg/m 2, and both of their LAP values were higher than the cutoff point.

          Conclusion

          When use as a tool for diabetes diagnosis, LAP performed better than BMI, implying that LAP could be a preferable anthropometry assessment.

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          Most cited references17

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          Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults--study on optimal cut-off points of body mass index and waist circumference in Chinese adults.

          Bei-Fan Zhou (2002)
          For prevention of obesity in Chinese population, it is necessary to define the optimal range of healthy weight and the appropriate cut-off points of BMI and waist circumference for Chinese adults. The Working Group on Obesity in China under the support of International Life Sciences Institute Focal point in China organized a meta-analysis on the relation between BMI, waist circumference and risk factors of related chronic diseases (e.g., high diabetes, diabetes mellitus, and lipoprotein disorders). 13 population studies in all met the criteria for enrollment, with data of 239,972 adults (20-70 year) surveyed in the 1990s. Data on waist circumference was available for 111,411 persons and data on serum lipids and glucose were available for more than 80,000. The study populations located in 21 provinces, municipalities and autonomous regions in mainland China as well as in Taiwan. Each enrolled study provided data according to a common protocol and uniform format. The Center for data management in Department of Epidemiology, Fu Wai Hospital was responsible for statistical analysis. The prevalence of hypertension, diabetes, dyslipidemia and clustering of risk factors all increased with increasing levels of BMI or waist circumference. BMI at 24 with best sensitivity and specificity for identification of the risk factors, was recommended as the cut-off point for overweight, BMI at 28 which may identify the risk factors with specificity around 90% was recommended as the cut-off point for obesity. Waist circumference beyond 85 cm for men and beyond 80 cm for women were recommended as the cut-off points for central obesity. Analysis of population attributable risk percent illustrated that reducing BMI to normal range ( or = 28) with drugs could prevent 15%-17% clustering of risk factors. The waist circumference controlled under 85 cm for men and under 80 cm for women, could prevent 47%-58% clustering of risk factors. According to these, a classification of overweight and obesity for Chinese adults is recommended.
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            Waist circumference and not body mass index explains obesity-related health risk.

            Ian Janssen, Peter Katzmarzyk, Robert Ross (2004)
            The addition of waist circumference (WC) to body mass index (BMI; in kg/m(2)) predicts a greater variance in health risk than does BMI alone; however, whether the reverse is true is not known. We evaluated whether BMI adds to the predictive power of WC in assessing obesity-related comorbidity. Subjects were 14 924 adult participants in the third National Health and Nutrition Examination Survey, grouped into categories of BMI and WC in accordance with the National Institutes of Health cutoffs. Odds ratios for hypertension, dyslipidemia, and the metabolic syndrome were compared for overweight and class I obese BMI categories and the normal-weight category before and after adjustment for WC. BMI and WC were also included in the same regression model as continuous variables for prediction of the metabolic disorders. With few exceptions, overweight and obese subjects were more likely to have hypertension, dyslipidemia, and the metabolic syndrome than were normal-weight subjects. After adjustment for WC category (normal or high), the odds of comorbidity, although attenuated, remained higher in overweight and obese subjects than in normal-weight subjects. However, after adjustment for WC as a continuous variable, the likelihood of hypertension, dyslipidemia, and the metabolic syndrome was similar in all groups. When WC and BMI were used as continuous variables in the same regression model, WC alone was a significant predictor of comorbidity. WC, and not BMI, explains obesity-related health risk. Thus, for a given WC value, overweight and obese persons and normal-weight persons have comparable health risks. However, when WC is dichotomized as normal or high, BMI remains a significant predictor of health risk.
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              Beyond body mass index.

              A Prentice, S. Jebb (2001)
              Body mass index (BMI) is the cornerstone of the current classification system for obesity and its advantages are widely exploited across disciplines ranging from international surveillance to individual patient assessment. However, like all anthropometric measurements, it is only a surrogate measure of body fatness. Obesity is defined as an excess accumulation of body fat, and it is the amount of this excess fat that correlates with ill-health. We propose therefore that much greater attention should be paid to the development of databases and standards based on the direct measurement of body fat in populations, rather than on surrogate measures. In support of this argument we illustrate a wide range of conditions in which surrogate anthropometric measures (especially BMI) provide misleading information about body fat content. These include: infancy and childhood; ageing; racial differences; athletes; military and civil forces personnel; weight loss with and without exercise; physical training; and special clinical circumstances. We argue that BMI continues to serve well for many purposes, but that the time is now right to initiate a gradual evolution beyond BMI towards standards based on actual measurements of body fat mass.
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                Author and article information

                Contributors
                Hua Yao
                Dai Jianghong
                Journal
                Journal ID (nlm-ta): PeerJ
                Journal ID (iso-abbrev): PeerJ
                Journal ID (pmc): PeerJ
                Journal ID (publisher-id): PeerJ
                Title: PeerJ
                Publisher: PeerJ Inc. (San Diego, USA )
                ISSN (Electronic): 2167-8359
                Publication date (Electronic): 10 February 2020
                Publication date Collection: 2020
                Volume: 8
                Electronic Location Identifier: e8483
                Affiliations
                [1 ]School of Public Health, Xinjiang Medical University , Urumqi, China
                [2 ]School of Health Management, Xinjiang Medical University , Urumqi, China
                Author information
                http://orcid.org/0000-0002-6103-1666
                Article
                Publisher ID: 8483
                DOI: 10.7717/peerj.8483
                PMC ID: 7017788
                PubMed ID: 32095339
                SO-VID: 1470f1c8-4344-4534-9cb1-48cabcda3b95
                Copyright © © 2020 Tian et al.
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                Date received : 20 September 2019
                Date accepted : 29 December 2019
                Funding
                Funded by: Xinjiang Multi-Ethnic Natural Population Cohort Construction and Health Follow-up Study
                Award ID: 2017YFC0907203
                Funded by: Xinjiang Uygur Autonomous Region “13th Five-Year” Key Discipline (Plateau discipline)—Public Health and Preventive Medicine
                This work was supported by the national key research and development plan “precise medical research” key special sub-project “Xinjiang multi-ethnic natural population cohort construction and health follow-up study” (2017YFC0907203) and Xinjiang Uygur Autonomous Region “13th Five-Year” Key Discipline (Plateau discipline)—Public Health and Preventive Medicine. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Epidemiology
                Subject: Public Health

                Keywords: type 2 diabetes,body mass index,lipid accumulation product
                Data availability:
                Keywords: type 2 diabetes, body mass index, lipid accumulation product

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