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Introduction引言
Metabolic syndrome, as Cornier et al. (2008) defined, is the clusters of diseases and conditions that occur at the same time, driving up the risks of suffering from heart diseases, stroke and type 2 diabetes. The diseases and conditions in metabolic syndrome include the increased blood pressure, blood sugar and abdominal obesity, abnormal cholesterol and triglyceride levels. At present, metabolic syndrome becomes increasingly common around the world. In the United States alone, there are around 30% people found with metabolic syndromes, such as the large waist circumference, frequent fatigue and strong sense of weakness, blurred vision and increased thirst and urination. In Grundy’s study (2008), it is argued that once the above symptoms of metabolic syndrome are identified, people can seek to control and treat through aggressively changing lifestyles. According to Grundy (2008), the ultimate goal of treating metabolic syndrome is to cut down the risks of ischemic heart disease. Through changing lifestyle, people can lower the low-density lipoprotein (LDL) cholesterol and high blood pressure, hence manage diabetes and other conditions occurs simultaneously.
代謝綜合征，如Cornier等人。（2008）定義為同時發生的疾病和條件的集群，增加患心臟病、中風和2型糖尿病的風險。代謝綜合征的疾病和條件包括血壓升高、血糖和腹部肥胖、膽固醇和甘油三酯水平異常。目前，代謝綜合征在全世界越來越普遍。僅在美國，就有大約30%的人患有代謝綜合征，如腰圍過大、經常疲勞和虛弱感強、視力模糊以及口渴和排尿增多。在Grundy的研究（2008）中，有人認為一旦上述代謝綜合征的癥狀被發現，人們可以通過積極改變生活方式來尋求控制和治療。根據Grundy（2008），治療代謝綜合征的最終目標是降低缺血性心臟病的風險。通過改變生活方式，人們可以降低低密度脂蛋白（LDL）膽固醇和高血壓，從而控制糖尿病和其他疾病的同時發生。
Metabolic Health of Patients患者代謝健康
In Alberti et al.’s study (2005), metabolic health is defined as the state where people have an ideal level of blood sugar, triglycerides, high-density lipoprotein (HDL) cholesterol, blood pressure and waist circumference, without medical or therapies. However, in an empirical study conducted by the University of North Carolina at Chapel Hill during the period of 2009 to 2016, it was found that only 1 in 8 adults in the United States have optimal metabolic health (Healthline, 2019). This finding suggests that the decrease of metabolic health and the increase of metabolic syndrome is not uncommon to be found among the world population. Tom, the IT staff in an England company, is a typical example of metabolic syndrome.
在Alberti等人（2005年）的研究中，代謝健康被定義為人們在沒有醫療或治療的情況下，血糖、甘油三酯、高密度脂蛋白（HDL）膽固醇、血壓和腰圍達到理想水平的狀態。然而，在北卡羅來納大學教堂山分校（University of North Carolina at Chapel Hill）2009年至2016年進行的一項實證研究中發現，美國只有八分之一的成年人擁有最佳的代謝健康狀況（Healthline，2019年）。這一發現表明，在世界人口中，代謝健康的下降和代謝綜合征的增加并不少見。湯姆是一家英國公司的IT員工，他是代謝綜合征的典型例子。
According to the definition provided by the International Diabetes Federation (IDF), to diagnose an individual into metabolic syndrome, the person must meet two conditions: first, he or she is supposed to have central obesity with a particular ethnicity. Second, he or she must have two of the four health problems, including high triglycerides, decreased HDL cholesterol, increased blood pressure and increased fasting plasma glucose. Tom is a typical example of metabolic syndrome because he meets the two criterions: Coming from England, he is classified as Europids in terms of ethnicity. Després and Lemieux (2006) noted that the reference value of men’s waist circumference is 94cm, whereas Tom’s is 104cm. Therefore, Tom is classified as obesity. According to Després and Lemieux (2006), if men’s waist circumference is larger than 102cm, then they have higher risks of suffering from diabetes than those who have a smaller waist circumstance. In Weiss et al.’s study (2014), it is mentioned that larger waist circumference is a particular sign for type 2 diabetes. Based on the interpretation of Tom’s health indicators, it is argued that Tom has a raised fasting level of triglycerides because his triglyceride level is 1.9mmol/L, which is higher than the normal level of 1.7mmol/L. With this regard, Tom has a high possibility of type 2 diabetes and an above-normal fasting level of triglycerides, then he is diagnosed with metabolic syndrome.
In addition, health indicators of Tom suggest that he has a decreased fasting HDL cholesterol, which is 0.6mmol/L. According to IDF, the normal range of HDL cholesterol for male adult should be no less than 1.03mmol/L. Therefore, the decreased fasting HDL cholesterol is a problem for Tom. Except these abnormal indicators, Tom’s blood pressure is 115/78 mmHg, falling into the normal range recommended by IDF, which is 130/85 mmHg. Tom’s fasting blood glucose is 6.9 mmol/L, which is also within the normal range of 5.6 mmol/L recommended by IDF. From these two indicators, it can be found that Tom shows no particular signs for high blood pressure or increased fasting plasma glucose.
From the interpretation of Tom’s health indicators, in addition to the four factors of metabolic syndrome, it is found that Tom’s body mass index (BMI) is 33.9, which, according to the standard released by IDF, should be classified as class 1. In American Diabetes Association’s study (2014), it is argued that a BMI at 25kg/m2 or higher is a risk factor for type 2 diabetes. This finding further confirms that Tom is under the risk of type 2 diabetes. Another important health indicator or body fat. Currently, Tom’s body fat is 35%, which is less to be ideal, because based on his anthropometric measurement, a recommended body fat is 22%. Therefore, the high body fat could be a trigger for potential health problems.
Advice
First, Tom is suggested to take physical exercises more often. In the study conducted by Eckel et al. (2005), it is noted that being physically inactive is a significant reason for people to suffer from cardiovascular diseases and type 2 diabetes. As discussed earlier, Tom is classified into obese class 1 for his large waist circumference and high BMI. Therefore, it is highly recommended that Tom should increase the frequency of physical exercise, not only for the purpose of losing weight and cutting down waist circumference, but also to reduce the risks of developing type 2 diabetes and various cardiovascular diseases. One recommendation regarding physical exercise is increasing the daily step counts or take moderate-intensity exercise every week. In the study conducted by Isomaa et al. (2001), it is argued that an extra 3,000 steps contribute to driving down the risks for suffering from cardiovascular disease. This can also be replaced by taking a minimum of 2 hours and a half’s moderate-intensity physical exercise on a weekly basis, which can be broken down into 30 minutes per day and 5 days a week. According to Isomaa et al. (2001), by taking such physical exercises, people can increase heart rate and energy expenditure. In the case of Tom, it is recommended that he can either increase the daily step counts to 7,000 to 8,000, or, taking moderate-intensity exercises such as brisk walking. If Tom has limited time for long-time exercise, he is recommended to take vigorous aerobic exercise, such as jogging and spinning. However, considering the potential risks of injury, Tom should take such vigorous aerobic exercises under the guidance of professional coach and proceed with these exercises gradually.
Second, Tom is recommended to adjust his diets and eating habits. This is not only to help Tom control weight and waist circumference, but also to gain health and nutrition benefits from daily food intake. According to Kim, Newton and Knopp (2002), the most effective and fundamental way to lose weight is to ensure the daily intake of energy is lower than the energy expenditure. Based on the understanding of Tom’s current intake and the recommended intake level of IDF (2006), he is suggested to reduce 500 to 600 calories per day, so as to 5% to 10% of the body weight in the following one year. In other words, every day, Tom should cut off snacks between meals and the high-energy food in three meals a day.
Considering Tom’s high risks of developing type 2 diabetes, it is recommended that he should introduce cardioprotective diets. In the study conducted by Liu et al. (2010), it is recommended that although cutting down the overall intake of energy is contributable to prevent cardiovascular diseases, the level of saturated fat contained in daily diets should be reduced. Liu et al. (2010) proposed that this can be achieved through replacing part of the meat and diary products with around 20g soya protein. Liu et al. (2010) argued that this eating habit can also help people control the LDL cholesterol through curbing the generation of liver LDL cholesterol and improving the level of HDL cholesterol. In terms of staple food, Tom is suggested to replace wheat flour and rice with coarse food grain, such as oats, wholegrain bread and coarse rice with various beans, quinoa and black rice. In Hsu et al.’s study (2015), it is mentioned that taking less-processed staple food that contains high soluble fiber helps control coronary heart disease and diabetes risks. Therefore, the above staple foods should be considered by Tom.
Use of IDF (2006) Metabolic Syndrome Criteria
According to the IDF (2006), the increase of insulin protection is a significant trigger for various cardiovascular diseases, because the increased insulin protection makes the body vulnerable to beta-cells. In Cornier et al.’s study (2008), it is mentioned that insulin resistance usually takes place when hormones are generated by the cells that contributing to the excessive glucose that cannot be absorbed, but these glucoses still exist in bloodstreams and have the demand for insulin. Once the pancreas is less capable of producing insulin, type 2 diabetes are developed. From these findings, it is not hard to find that insulin resistance is closely-related to metabolic syndrome. This relationship is also confirmed in Kho et al.’s study (2011). According to them, obesity is associated with metabolic syndrome, as well as insulin resistance, because obesity leads to a higher level of blood pressure, then driving up the risk for developing type 2 diabetes. Therefore, insulin resistance is a criterion for metabolic syndrome.
As discussed earlier, abdominal obesity and large waist circumference increase the risk for type 2 diabetes, which are also signs of metabolic syndrome. According to IDF (2006), in the lack of physical activities and long-time indoor stay increase the likelihood of developing metabolic syndrome. From this perspective, the excessive body fat caused by the lack of physical activity is a useful clue used to diagnose metabolic syndrome.
In terms of the dentification of type 2 diabetes, several approaches and alternatives have been outlined in IDF (2006) and other medical studies. For example, in Grundy’s study (2008), it is argued that the fasting plasma glucose level can be used to diagnose type 2 diabetes. According to Grundy (2008), through taking the sample of fasting plasma glucose from blood, doctors can directly identify type 2 diabetes without referring to independent factors, including age, cholesterol level and triglycerides. In addition, blood test of glycated hemoglobin is also an approach to identify type 2 diabetes, as it helps doctors to identify the mean blood glucose level for the past few months, hence determine whether the diabetes have been effectively controlled.
Critique of Anthropometric Assessment
BMI is an indicator widely used in anthropometric assessment, because it provides a convenient access for people to measure obesity. Nevertheless, BMI is criticized for being ungrounded to claim that there are distinct categories of underweight, ideal weight and overweight. According to Lindström and Tuomilehto (2003), such sharp boundaries outlined based on BMI is ungrounded because BMI does not consider the distinction between fat and fat-free mass, it also does not consider other dependent variables, including age and ethnics. With this regard, in anthropometric assessment, BMI alone can hardly be used to determine whether an individual is subject to type 2 diabetes or metabolic syndrome.
Waist circumference, as discussed earlier, is an essential sign indicating whether a person has abdominal obesity. In most cases, the larger the waist circumference is, the greater level of visceral adipose tissue is. However, similar to the role of BIM in anthropometric assessment, waist measurement alone is insufficient to indicate type 2 diabetes or metabolic health of a person. After all, a large waist circumference is a strong indicator of general obesity; to identify type 2 diabetes and metabolic syndrome, assessing the fat distribution pattern is a more reliable approach.
Compared with BMI and waist circumference, body fat is an indicator that shows the ratio of body mass to body weight (Hsu et al. 2015). Therefore, in anthropometric assessment, body fat percentage is often used to identify whether the person is under the risk of type 2 diabetes and metabolic syndrome. It is widely believed that a high body fat percentage indicates a higher risk for cardiovascular diseases (Billings and Florez, 2010). Nevertheless, high body fat does not necessarily equal to high BMI; a high BMI also does not completely equal to high body fat (Hsu et al. 2015). To make propose use of the role that body fat plays in anthropometric assessment, Billings and Florez (2010) suggested that body fat percentage should be referred together with an in-depth analysis of BMI.
Limitations
In a word, metabolic syndrome is a combination of symptoms and diseases that drive up the possibility of developing type 2 diabetes and cardiovascular diseases. Based on the review of IDF metabolic syndrome criteria and the evaluation of roles that various health indicators play, it is summarized that BMI, waist circumference and body fat are insufficient to be used alone in anthropometric assessment, because in some situations, external and internal factors, such as a recent diet, change of muscle mass and fat mass can affect these index hence affect their meanings in body assessment (Kim, Newton and Knopp, 2002).
It is recommended that in anthropometric assessment, various indicators and criteria, such as waist circumference, body fat and BMI, should be correlated and analyzed in-depth, so as to correctly identify health risks.
References
Alberti, K.G.M., Zimmet, P. and Shaw, J., 2005. The metabolic syndrome—a new worldwide definition. The Lancet, 366(9491), pp.1059-1062.
American Diabetes Association, 2004. Screening for type 2 diabetes. Diabetes care, 27(suppl 1), pp.s11-s14.
Billings, L.K. and Florez, J.C., 2010. The genetics of type 2 diabetes: what have we learned from GWAS?. Annals of the New York Academy of Sciences, 1212(1), pp.59-77.
Cornier, M. A., Dabelea, D., Hernandez, T. L., Lindstrom, R. C., Steig, A. J., Stob, N. R., ... & Eckel, R. H. (2008). The metabolic syndrome. Endocrine reviews, 29(7), 777-822.
Després, J.P. and Lemieux, I., 2006. Abdominal obesity and metabolic syndrome. Nature, 444(7121), p.881.
Eckel, R.H., Grundy, S.M. and Zimmet, P.Z., 2005. The metabolic syndrome. The lancet, 365(9468), pp.1415-1428.
Grundy, S.M., 2008. Metabolic syndrome pandemic. Arteriosclerosis, thrombosis, and vascular biology, 28(4), pp.629-636.
Healthline (2019). Only 12% of Americans are Metabolically Healthy. [online] Healthline. Available at: https://www.healthline.com/health-news/what-does-it-mean-to-be-metabolically-healthy [Accessed 31 Mar. 2019].
Hsu, W.C., Araneta, M.R.G., Kanaya, A.M., Chiang, J.L. and Fujimoto, W., 2015. BMI cut points to identify at-risk Asian Americans for type 2 diabetes screening. Diabetes care, 38(1), pp.150-158.
International Diabetes Federation (2006). myhealthywaist.org - IDF. [online] Myhealthywaist.org. Available at: http://www.myhealthywaist.org/evaluating-cmr/metabolic-syndrome-and-type-2-diabetescvd-risk/idf/page/2/index.html [Accessed 31 Mar. 2019].
Isomaa, B.O., Almgren, P., Tuomi, T., Forsén, B., Lahti, K., Nissen, M., Taskinen, M.R. and Groop, L., 2001. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes care, 24(4), pp.683-689.
Kim, C., Newton, K.M. and Knopp, R.H., 2002. Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes care, 25(10), pp.1862-1868.
Kho, A.N., Hayes, M.G., Rasmussen-Torvik, L., Pacheco, J.A., Thompson, W.K., Armstrong, L.L., Denny, J.C., Peissig, P.L., Miller, A.W., Wei, W.Q. and Bielinski, S.J., 2011. Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study. Journal of the American Medical Informatics Association, 19(2), pp.212-218.
Lindström, J. and Tuomilehto, J., 2003. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes care, 26(3), pp.725-731.
Liu, Y., Liu, Z., Song, Y., Zhou, D., Zhang, D., Zhao, T., Chen, Z., Yu, L., Yang, Y., Feng, G. and Li, J., 2010. Meta‐analysis added power to identify variants in FTO associated with type 2 diabetes and obesity in the Asian population. Obesity, 18(8), pp.1619-1624.
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