The authors have declared that no competing interests exist.
Conceived and designed the experiments: XH WJ. Performed the experiments: XH JL JW LJ ZS JL HT QJ DZ JG LL LC XG Z. Zhou QL Z. Zhao GS ZY WY WJ. Analyzed the data: XH ZY. Contributed reagents/materials/analysis tools: JL JW LJ ZS JL HT QJ DZ JG LL LC XG Z. Zhou QL Z. Zhao GS ZY WY WJ. Wrote the paper: XH WJ.
¶ Members of the China National Diabetes and Metabolic Disorders Study Group are listed in Appendix S1
We updated the prevalence of obesity and evaluated the clinical utility of separate and combined waist circumference (WC) or body mass index (BMI) category increments in identifying cardiometabolic disorder (CMD) and cardiovascular disease (CVD) risk in Chinese adults.
46,024 participants aged ≥20 years, a nationally representative sample surveyed in 2007–2008, were included in this analysis. Taking the cutoffs recommended by the Chinese Joint Committee for Developing Chinese Guidelines (JCDCG) and the Working Group on Obesity in China (WGOC) into account, the participants were divided into four WC and four BMI groups in 0.5-SD increments around the mean, and 16 cross-tabulated combination groups of WC and BMI. 27.1%, 31.4%, and 12.2% of Chinese adults are centrally obese, overweight, or obese according to JCDCG and WGOC criteria. After adjustment for confounders, after a 1-SD increment, WC is associated with a 1.7-fold or 2.2-fold greater risk of having DM or DM plus dyslipidemia than BMI, while BMI was associated with a 2.3-fold or 1.7-fold higher hypertension or hypertension plus dyslipidemia risk than WC. The combination of WC and BMI categories had stronger association with CMD risk, i.e., the adjusted ORs (95% CI) of having DM, hypertension, and dyslipidemia for the combined and separate highest WC and BMI categories were 2.19 (1.96–2.44) vs 1.88 (1.67–2.12) and 1.12 (0.99–1.26); 5.70 (5.24–6.19) vs 1.51 (1.39–1.65) and 1.69 (1.57–1.82); and 3.73 (3.42–4.07) vs 2.16 (1.98–2.35) and 1.33 (1.25–1.40), respectively. The combination of WC and BMI categories was more likely to identify individuals with lower WC and lower BMI at CVD risk, even after the effects of CMD were controlled (all
Central obesity, overweight, and obesity are epidemic in Chinese adults. The combination of WC and BMI measures is superior to the separate indices in identifying CMD and CVD risk.
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the world
Although they are not perfect measures of body fat, body mass index (BMI) and waist circumference (WC) are the most practical indices for identifying obesity in clinical practice and epidemiologic research. It is known that specific BMI values can reflect different body compositions across genders and races; eg, in some Asian populations a given BMI value indicates a higher percentage of body fat than in European populations
As part of the China National Diabetes and Metabolic Disorders Study, the goal of this analysis was to assess the prevalence of obesity in Chinese adults and to evaluate the clinical utility of separate and combined WC and BMI categories and category increments in identifying the risk of CMD and CVD in this population. To our knowledge, there has not been any systematic assessment based upon a large representative sample reported for Chinese adults.
This current paper is one of a series of reports on different themes from the China National Diabetes and Metabolic Disorders Study, which was a representative cross-sectional survey of Chinese adults from June 2007 to May 2008. This study was designed to provide up-to-date prevalence figures for diabetes mellitus (DM) and related metabolic disorders in Chinese adults. Three papers from the study have been published and have been referred to in the present manuscript
Our current report focused on evaluating the clinical utility of separate and combined waist circumference (WC) and body mass index (BMI) categories within the same increment in assessing presence of cardiometabolic and cardiovascular diseases in Chinese adults, while at the same time, we also reported the prevalence of overweight, obesity and central obesity identified by China diagnostic criteria.
The multi-stage sampling process used in the survey, including sampling size, sampling scheme, and several other features, has been described in detail previously
This study was approved by the institutional review boards of 17 participating institutions, which are the institutional review board of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, the institutional review board of Chinese People’s Liberation Army General Hospital, the institutional review board of Sun Yat-sen University Third Hospital, the institutional review board of Peking University People’s Hospital, the institutional review board of First Affiliated Hospital of Chinese Medical University, the institutional review board of Shanxi Province People’s Hospital, the institutional review board of West China Hospital of Sichuan University, the institutional review board of Xijing Hospital of Fourth Military Medical University, the institutional review board of the Affiliated Drum Tower Hospital of Nanjing University Medical School, the institutional review board of Xinjiang Uygur Autonomous Region’s Hospital, the institutional review board of Fujian Provincial Hospital, the institutional review board of Qilu Hospital of Shandong University, the institutional review board of Peking University First Hospital, the institutional review board of Henan Province People’s Hospital, the institutional review board of Second Affiliated Hospital of Harbin Medical University, the institutional review board of Xiangya Second Hospital, and the institutional review board of China–Japan Friendship Hospital. Written informed consent was obtained from each participant before the survey. The 17 institutional review boards’ approvals covered every participant in the study.
An oral glucose tolerance test was performed on all subjects. After subjects underwent at least 10 hours of overnight fasting, venous blood samples were drawn at 0, 30, and 120 minutes following ingestion of a 75-gram oral glucose load (for participants without a prior diagnosis of DM) or ingestion of a steamed bun containing approximately 80 g of complex carbohydrates (for participants with a self-reported history of DM).
Plasma glucose, serum cholesterol, and triglyceride levels were determined by enzymatic assay at the clinical biochemical laboratories of each province. All laboratory measurements met a standardization and certification program. Serum insulin levels were measured by a radioimmunoassay, and homeostatic model assessment of insulin resistance (HOMA-IR) was calculated using the formula HOMA-IR = fasting serum insulin (FINS, mIU/L)×FPG (mmol/L)/22.5
Trained staff administered a standardized questionnaire to each subject. Demographic data, lifestyle, smoking/drinking habits, family history, and medical history were collected during the survey.
For smoking and drinking habits, the subjects were divided into two categories (according to the information at the time of the survey): current smokers/drinkers and non-current smokers/drinkers. Current smokers were defined as those who had smoked ≥1 cigarette/day for at least 1 year. Current drinkers were defined as those who had consumed ≥30 g of alcohol/week on average for at least 1 year. Regular leisure-time physical activity was defined as participation in moderate or vigorous activity for 30 minutes or more per day at least 3 days a week. Educational level was also recorded and categorized into three groups: low (illiteracy, primary, and secondary education), medium (high school education) and high (college or university education). The questionnaire included family history of obesity, DM, hypertension, dyslipidemia, coronary heart disease (CHD), and stroke for first-degree relatives (biological mother, father, brothers, or sisters).
Blood pressure, body weight, and height were measured according to standard protocol
Central obesity was defined as WC ≥90 cm in men and ≥85 cm in women according to the Chinese Joint Committee for Developing Chinese Guidelines (JCDCG) Guidelines on Prevention and Treatment of Dyslipidemia in Adults (2007)
The MetS was defined according to the criteria established by the Chinese Joint Committee for Developing Chinese Guidelines on Prevention and Treatment of Dyslipidemia in Adults (JCDCG). The JCDCG-Mets was defined as three or more of the following abnormalities: 1. Central obesity (WC ≥90 cm for men and ≥85 cm for women); 2. Elevated TG (TG ≥1.7 mmol/L), or specific treatment for this lipid abnormality; 3. Reduced HDL-C (HDL-C <1.03 mmol/l), or specific treatment for this lipid abnormality; 4. Elevated BP (BP≥130/85 mmHg or current treatment for hypertension), or previously diagnosed hypertension; and 5. Elevated plasma glucose (FPG ≥6.1 mmol/L or 2 h PG ≥7.8 mmol/L) or previously diagnosed DM
Cardiometabolic disorder (CMD) is defined as a clustering of disorders which includes DM, hypertension, and dyslipidemia (elevated TG, reduced HDL-C, and elevated LDL-C), but not obesity. DM was defined as FPG ≥7.0 mmol/L or 2 hPPG ≥11.1 mmol/L, or having been previously diagnosed with DM and receiving therapy
Hypertension was diagnosed as systolic blood pressure (SBP) ≥140 mmHg or diastolic blood pressure (DBP) ≥90 mmHg, or having been diagnosed with hypertension and receiving antihypertensive therapy
Dyslipidemia was defined as (1) elevated triglycerides (TG): TG ≥1.7 mmol/L, or drug treatment for this lipid abnormality; (2) reduced high-density lipoprotein cholesterol (HDL-C): HDL-C <1.03 mmol/L in men and <1.29 mmol/L in women; (3) elevated low-density lipoprotein cholesterol (LDL-C): LDL-C ≥3.37 mmol/L; or (4) use of cholesterol-lowering medication
Non-fatal CVD (non-fatal CHD and non-fatal stroke) was determined according to a patient’s self-report. Incident of non-fatal CHD events were identified by a history of hospitalization for myocardial infarction or a surgical history of coronary balloon angioplasty, or coronary stent implantation or coronary artery bypass graft surgery. Non-fatal stroke events were identified by a history of language or physical dysfunction continuing for more than 24 h and ischemic or hemorrhagic stroke. These diagnostic criteria are wholly consistent with our previously published paper
For men and women, the mean (SD) WC and BMI were 85.5 (10.5) cm and 79.4 (10.2) cm, and 24.5 (3.6) kg/m2 and 23.9 (3.7) kg/m2, respectively. Taking into account the gender-specific mean (SD) of each of the indices and the cut-offs recommended by JCDCG and WGOC, the participants were divided into four WC and four BMI groups: WC Group I (WC <85 cm in men and <80 cm in women), WC Group II (85–90 cm in men and 80–85 cm in women), WC Group III (90–95 cm in men and 85–90 cm in women), and WC Group IV (≥95 cm in men and ≥90 cm in women); BMI Group I (BMI <24 kg/m2), BMI Group II (24–26 kg/m2), BMI Group III (26–28 kg/m2), and BMI Group IV (≥28 kg/m2), respectively. These WC and BMI categories were cross-tabulated to form 16 combination WC and BMI (WC * BMI) groups.
These categories allowed us to evaluate the clinical utility of separate and combined WC and BMI cut-off points, at 0.5-SD increments (∼2 kg/m2 for BMI and 5 cm for WC) above the mean (BMI: 24 kg/m2; WC: 85 cm for men and 80 cm for women), in predicting risk for adverse CMD and CVD outcomes.
Descriptive statistics were presented as mean with a 95% confidence interval (CI) or proportion (95% CI). Differences in mean were tested by
Considering the study sampling scheme and differences between the sample surveyed and the total population, the prevalence data was corrected for several features of the survey
Binary or multinominal multivariable logistic regression was conducted to assess the association of separate and joint WC and BMI categories with CMD and CVD using the Entry method; adjusted odds ratios (ORs) and the 95% CIs are given.
The dependent variables were CMD (DM, hypertension, elevated TG, reduced HDL-C, elevated LDL-C, or dyslipidemia) and CVD (CHD, stroke, and CVD) in binary logistic regression, and the dependent variables were the category variable of different CMD combinations with the group without any CMD as the referent in multinominal logistic regression.
The independent variables were mutually adjusted WC and BMI categories, shown in
Binary or multinominal multivariable logistic regression was conducted to assess the association of separate WC and BMI categories with CMD (
Binary multivariable logistic regression was conducted to assess the association of combined WC and BMI categories with CMD
Adjustment variables included age, education level, smoking status, drinking status, physical activity, and family history of disease (identified as the dependent variables). Additionally, CMD (DM, hypertension, and dyslipidemia) and gender were also considered as confounding factors as appropriate.
The statistical analyses were performed using SUDAAN version 10 (RTI International, Research Triangle Park, NC, USA) and SPSS version 15.0 (SPSS Inc, Chicago, IL, USA). A value of
Characteristic | Mean (95% CI) |
|||||||
Men (n = 18,326) | Women (n = 27,698) | Urban vs Rural | Men vs Women | |||||
Urban (n = 11,355) | Rural (n = 6,971) | Urban (n = 18,001) | Rural (n = 9,697) | In Men | In Women | In Urban | In Rural | |
Age (years) | 45.0 (44.9–45.1) | 44.8 (44.7–44.9) | 44.7 (44.6–44.8) | 44.7 (44.6–44.8) | 0.022 | 0.834 | <0.001 | 0.355 |
Waist circumference (cm) | 85.5 (85.2–85.8) | 81.8 (81.4–82.2) | 77.9 (77.7–78.2) | 78.0 (77.7–78.3) | <0.001 | 0.753 | <0.001 | <0.001 |
BMI (kg/m2) | 24.6 (24.5–24.7) | 23.6 (23.4–23.7) | 23.5 (23.4–23.6) | 23.4 (23.2–23.5) | <0.001 | 0.126 | <0.001 | 0.026 |
FPG (mmol/L) | 5.39 (5.34–5.44) | 5.22 (5.18–5.27) | 5.30 (5.20–5.40) | 5.16 (5.11–5.20) | <0.001 | 0.011 | 0.102 | 0.035 |
2 h PG (mmol/L) | 7.18 (7.06–7.29) | 6.62 (6.51–6.72) | 7.01 (6.86–7.16) | 6.81 (6.72–6.91) | <0.001 | 0.029 | 0.079 | 0.007 |
FINS (µIU/mL) | 8.97 (8.77–9.16) | 7.93 (7.57–8.29) | 8.85 (8.48–9.21) | 7.69 (7.49–7.89) | <0.001 | <0.001 | 0.558 | 0.256 |
2 hINS (µIU/mL) | 40.24 (38.72–41.76) | 30.03 (27.89–32.16) | 42.54 (40.99–44.09) | 35.26 (33.86–36.66) | <0.001 | <0.001 | 0.038 | <0.001 |
TC (mmol/L) | 4.79 (4.76–4.82) | 4.63 (4.59–4.67) | 4.77 (4.75–4.80) | 4.67 (4.64–4.71) | <0.001 | <0.001 | 0.293 | 0.084 |
TG (mmol/L) | 1.82 (1.78–1.86) | 1.62 (1.58–1.67) | 1.39 (1.37–1.42) | 1.42 (1.39–1.45) | <0.001 | 0.134 | <0.001 | <0.001 |
HDL-C (mmol/L) | 1.22 (1.21–1.23) | 1.27 (1.25–1.28) | 1.37 (1.36–1.37) | 1.34 (1.32–1.35) | <0.001 | <0.001 | <0.001 | <0.001 |
LDL-C (mmol/L) | 2.82 (2.79–2.85) | 2.55 (2.52–2.58) | 2.77 (2.74–2.79) | 2.56 (2.53–2.60) | <0.001 | <0.001 | 0.007 | 0.633 |
SBP (mmHg) | 125.3 (124.8–125.9) | 122.0 (121.3–122.6) | 120.0 (119.6–120.4) | 119.8 (119.1–120.4) | <0.001 | 0.523 | <0.001 | <0.001 |
DBP (mmHg) | 80.5 (80.2–80.9) | 78.4 (78.0–78.8) | 76.0 (75.7–76.2) | 75.6 (75.2–76.0) | <0.001 | 0.113 | <0.001 | <0.001 |
HOMA–IR (mIU·mmol/L2) | 2.22 (2.15–2.29) | 1.91 (1.81–2.00) | 2.12 (2.04–2.21) | 1.81 (1.75–1.87) | <0.001 | <0.001 | 0.076 | 0.095 |
Current smoker (%) |
45.2 (43.6–46.8) | 53.6 (51.6–55.5) | 2.4 (2.1 –2.8) | 3.3 (2.8–4.0) | <0.001 | 0.011 | <0.001 | <0.001 |
Current drinker (%) |
41.9 (40.4–43.4) | 44.2 (42.3–46.2) | 4.1 (3.7–4.6) | 4.1 (3.5–4.8) | 0.063 | 0.914 | <0.001 | <0.001 |
Abbreviations: 2 hINS, 2-hour postprandial insulin; 2 hPPG, 2-hour postprandial plasma glucose; BMI, body mass index; CI, confidence interval; DBP, diastolic blood pressure; FINS, fasting insulin; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, Homeostasis Model Assessment – Insulin Resistance; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triglycerides.
Data are expressed as mean (95% CI) unless otherwise indicated.
Data are expressed as percentage (95% CI).
The mean and percentage values were weighted and standardized to represent Chinese adults (aged ≥20 years) according to the Chinese population structure in 2006.
Population | Central Obesity |
Overweight |
Obesity |
JCDCG-MetS |
WC ≥90 cm in men, ≥85 cm in women (n = 46,024) | BMI ≥24 to <28 kg/m2(n = 46,024) | BMI ≥28 kg/m2 (n = 46,024) | (n = 45,172) | |
Overall |
27.1 (26.4–27.8) | 31.4 (30.6–32.2) | 12.2 (11.7–12.7) | 21.9 (21.2–22.5) |
Men |
29.0 (27.9–30.0) | 33.7 (32.6–34.8) | 13.7 (12.9–14.5) | 25.8 (24.8–26.9) |
Women |
25.2 (24.3–26.2) | 29.2 (28.1–30.2) | 10.7 (10.1–11.4) | 18.0 (17.2–18.9) |
<0.001 | <0.001 | <0.001 | <0.001 | |
DM | ||||
with | 45.4 (42.3–48.6) | 41.0 (37.8–44.2) | 24.3 (21.5–27.2) | 58.7 (55.6–61.8) |
without | 25.5 (24.7–26.2) | 30.7 (29.9–31.5) | 11.2 (10.7–11.7) | 18.1 (17.4–18.8) |
<0.001 | <0.001 | <0.001 | <0.001 | |
Hypertension | ||||
with | 44.4 (42.6–46.2) | 39.4 (37.1–41.7) | 26.0 (24.4–27.6) | 45.0 (43.2–46.9) |
without | 20.6 (19.8–21.5) | 28.3 (27.4–29.2) | 7.8 (7.3–8.3) | 12.8 (12.1–13.6) |
<0.001 | <0.001 | <0.001 | <0.001 | |
Urban |
30.0 (29.1–30.9) | 34.4 (33.4–35.3) | 13.2 (12.6–13.8) | 24.6 (23.7–25.5) |
Men |
34.9 (33.5–36.3) | 39.1 (37.6–40.6) | 15.9 (14.8–17.0) | 30.7 (29.4–32.1) |
Women |
25.2 (24.0–26.4) | 29.7 (28.5–30.9) | 10.5 (9.9–11.2) | 18.6 (17.6–19.7) |
<0.001 | <0.001 | <0.001 | <0.001 | |
Rural |
24.7 (23.7–25.7) | 28.9 (27.8–30.1) | 11.3 (10.6–12.1) | 19.5 (18.5–20.5) |
Men |
24.0 (22.6–25.6) | 29.1 (27.5–30.7) | 11.8 (10.7–13.1) | 21.5 (20.0–23.1) |
Women |
25.3 (23.9–26.7) | 28.8 (27.2–30.4) | 10.9 (10.0–11.9) | 17.5 (16.2–18.8) |
0.252 | 0.779 | 0.240 | <0.001 | |
Sex– and age–specific | ||||
Men, age, y | ||||
20–29 | 17.5 (15.1–20.0) | 22.4 (19.8–25.1) | 10.3 (8.4–12.5) | 12.9 (10.7–15.5) |
30–39 | 27.9 (25.8–30.0) | 34.1 (31.8–36.5) | 15.1 (13.4–16.9) | 21.4 (19.4–23.5) |
40–49 | 31.5 (29.5–33.7) | 38.8 (36.5–41.1) | 14.4 (13.0–16.0) | 28.5 (26.4–30.6) |
50–59 | 33.6 (31.2–36.0) | 37.0 (34.5–39.5) | 15.6 (13.9–17.6) | 31.3 (29.0–33.8) |
60–69 | 31.8 (29.1–34.7) | 35.8 (32.8–38.8) | 11.6 (9.8–13.7) | 33.9 (30.9–37.0) |
≥70 | 36.0 (30.6–41.8) | 32.3 (27.1–38.0) | 12.9 (9.3–17.5) | 36.3 (30.8–40.3) |
<0.001 | 0.001 | 0.756 | <0.001 | |
Women, age, y | ||||
20–29 | 8.4 (7.2–9.7) | 15.0 (12.6–17.6) | 3.5 (2.8–4.2) | 3.0 (2.4–3.7) |
30–39 | 13.3 (12.0–14.7) | 24.5 (22.7–26.3) | 7.7 (6.6–8.9) | 6.0 (5.2–6.9) |
40–49 | 24.6 (23.1–26.2) | 34.6 (32.9–36.4) | 13.0 (11.8–14.2) | 15.8 (14.5–17.2) |
50–59 | 38.4 (36.4–40.5) | 38.1 (36.1–40.2) | 15.2 (13.8–16.7) | 30.3 (28.4–32.4) |
60–69 | 42.6 (39.8–45.4) | 37.7 (34.9–40.6) | 14.5 (12.9–16.3) | 37.6 (34.8–40.4) |
≥70 | 48.5 (40.9–56.1) | 29.2 (22.9–36.5) | 15.2 (11.4–19.9) | 40.9 (33.7–48.5) |
<0.001 | <0.001 | <0.001 | <0.001 |
Abbreviation: BMI, body mass index; WC, Waist Circumference.
Central obesity was identified as waist circumference ≥90 cm in men and ≥85 cm.
Overweight was identified as BMI ≥24 to <28 kg/m2.
Obesity was BMI ≥28 kg/m2.
The JCDCG-MetS was defined as three or more of the following abnormalities: 1. Central obesity (WC ≥90 cm for men and ≥85 cm for women); 2. Elevated TG (TG ≥1.7 mmol/L), or specific treatment for this lipid abnormality; 3. Reduced HDL-C (HDL-C <1.03 mmol/l), or specific treatment for this lipid abnormality; 4. Elevated BP (BP≥130/85 mmHg or current treatment for hypertension), or previously diagnosed hypertension; and 5. Elevated plasma glucose (FPG ≥6.1 mmol/L or 2 h PG ≥7.8 mmol/L) or previously diagnosed DM.
The percentage values were standardized by the direct method according to the Chinese population structure in 2006,
adjusted for age and sex,
adjusted for age.
The demographic and clinical characteristics of the 46,024 subjects by gender and region are presented in
Standardized mean BMI and waist circumference by gender and age group are shown in
Association of WC/BMI categories with CMD and CVD are shown in
Furthermore, the total study population was divided into eight subgroups with different CMD combinations according the presence of cardiometabolic disorders, i.e. (1) the control group, without any cardiometabolic disorder (n = 11234, 27.1%); (2) the three groups with only one cardiometabolic disorder: the DM group (n = 501, 1.2%), the hypertension group (n = 2648, 6.4%), or the dyslipidemia group (n = 15915, 38.4%); (3) the three groups with two cardiometabolic disorders: the DM plus hypertension group (n = 403, 1.0%), the DM plus dyslipidemia group (n = 1529, 3.7%), and the hypertension plus dyslipidemia group (n = 7159, 17.3%); and (4) the one group with three cardiometabolic disorders: the DM plus hypertension and dyslipidemia group (n = 2104, 5.1%). Then, the associations of combinations of CMD with the BMI and WC categories were analyzed in multinomial regressions
Compared to the lowest group of WC/BMI, the highest BMI group (BMI ≥28 kg/m2) was associated with a 1.9-fold greater risk of CHD in men, and the highest WC group (WC ≥90 cm) was associated with a 2.1-fold greater risk of CHD in women, even when the effects of CMD were controlled (
Bar graphs of ORs for CMD and CVD among the combination groups of WC and BMI categories in all participants are shown in
In addition, when compared to the highest separate WC and BMI categories, the highest combination of WC and BMI categories (BMI ≥28 kg/m2 and WC ≥95 cm in men and ≥90 cm in women) was associated with greater DM, hypertension, and dyslipidemia risk. The ORs (95% CI) in all participants were 2.19 (1.96–2.44) vs 1.88 (1.67–2.12) and 1.12 (0.99–1.26); 5.70 (5.24–6.19) vs 1.51 (1.39–1.65) and 1.69 (1.57–1.82); and 3.73 (3.42–4.07) vs 2.16 (1.98–2.35) and 1.33 (1.25–1.40), respectively (data for joint WC and BMI categories shown in
With the effects of CMD controlled, the ORs of CHD and CVD significantly increased 0.9-fold and 0.5-fold, respectively, even in those combination groups with a BMI of 24–26 kg/m2 and WC of 90–95 cm in men or 85–90 cm in women, and the ORs (95% CIs) of stroke and CVD in the group with a BMI ≥28 kg/m2 and WC <85 cm in men or WC <80 cm in women increased 2.2-fold and 1.5-fold, respectively
This report is one of a series of reports from the large 2007–2008 China National Diabetes and Metabolic Disorders Study
Our results indicate that 27.1% (approximately 258.2 million) of Chinese adults are centrally obese according to the the JCDCG standards
The relationship of WC/BMI with CMD and CVD vary in a variety of epidemiologic studies, depending on the sample size, the sample’ representativeness, the scale for measurement of variables, and the confounding factors considered. Our results show that, after a 1-SD increment, WC is associated with a 1.7-fold or 2.2-fold greater risk of having DM or DM plus dyslipidemia than BMI, while BMI was associated with a 2.3-fold or 1.7-fold higher hypertension or hypertension plus dyslipidemia risk than WC. These findings are supported by previous studies
Additionally, significant heterogeneity across genders was observed in association of the three lipoprotein markers with WC/BMI. Stronger associations of WC with elevated TG and reduced HDL-C than BMI were found in women but not in men. The exact mechanisms involved in these associations are unclear.
Although an established link between WC/BMI and CVD has been documented, the debate remains about whether the link is mediated through the other CMD and which anthropometric indices are most closely associated with CVD
Compared with previous studies
The combination of WC and BMI categories was more likely to identify individuals having CVD risk with lower WC but the highest BMI (even <85 cm in men or <80 cm in women but BMI ≥28 kg/m2) and lower BMI but the highest WC (BMI of 24–26 kg/m2 but WC ≥90 cm in men or ≥85 cm in women) than separate WC or BMI categories (WC ≥95 cm in men or ≥90 cm in women, or BMI ≥28 kg/m2), even when controlling for the effect of CMD. We also noted that although WC reflects a measure of central fat distribution, while BMI reflects a combination of both fat mass and lean mass, the two parameters share almost the same information of obesity, r(Pearson correlation) = 0.775 (
This study has notable strengths. First, the large size of the population studied gives our analyses good statistical power and broad generalizability to the Chinese adult population. Secondly, taking the measurement scale and cut-offs recommended for Chinese adults into consideration, we evaluated the utility of separate and combined WC and BMI categories across matched increments in identifying risk of CMD and CVD.
Limitations of this study included oversampling of urban residents and a lower response rate among men than women. In view of this, all BMI and WC means and obesity prevalence figures were weighted to represent Chinese adults (≥20 years old) based on Chinese population data in 2006. Note taht a cross-sectional survey may preclude a causal relationship. In our study, in the case of participants reporting a non-fatal CVD event, the participant’s BMI and WC before or at the time of the presence of CMD or the incident CVD event is unknown. Any secondary causes of stroke (such as clotting disorders, atrial fibrillation, atrial septal defect) were not used to exclude participants.
In conclusion, central obesity, overweight, and obesity are epidemic in Chinese adults. WC and BMI add to the predictive power of each other, and a combination of the two indexes is superior to the separate indicators in identifying risk of CMD and CVD. This study shows that prevention and control of obesity in Chinese adults should be an urgent public health priority. A combination measurement of WC and BMI may help identify those who are most at risk for adverse cardiometabolic and cardiovascular outcomes. We also found that the cut-offs of WC and BMI recommended by Chinese JCDCG and WGOC are of clinical significance for this population.
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We thank all the members of the China National Diabetes and Metabolic Disorders Study Group for their contribution to the study, as listed in