Association of Waist Circumference Gain and Incident Prediabetes Defined by Fasting Glucose: A Seven-Year Longitudinal Study in Beijing, China

Abstract

The risk of incident prediabetes with gain in waist circumference (WC) has not been addressed among Chinese adults. A total of 7951 participants who underwent health check-ups at the Beijing Physical Examination Center and Beijing Xiaotangshan hospital were recruited in 2009 and followed up in 2016. Participants were classified into four groups according to categories of percent WC gain: ≤−2.5%, −2.5–2.5%, 2.5–5%, and >5%. The effect of WC gain on prediabetes was evaluated using modified Poisson regression models. Over seven years of follow-up, we identified 1034 prediabetes cases (413 women). Compared with a WC gain of ≤−2.5%, participants with a WC gain of >5% have a higher risk of prediabetes, be they male (non-abdominal obesity at baseline group: RR = 1.57, 95% CI: 1.10–2.24, abdominal obesity at baseline group: RR = 1.66, 95% CI: 1.20–2.30) or female (non-abdominal obesity at baseline group: RR = 1.74, 95% CI: 1.14–2.64, abdominal obesity at baseline group: RR = 2.47, 95% CI: 1.43–4.28). In conclusion, the risk of prediabetes increased significantly with increasing WC for both genders in the Chinese population. Lifestyle interventions aiming at preventing abdominal obesity are urgently needed to reduce the increasing burden of prediabetes, diabetes, and its complications.

Comparison of Different Anthropometric Indices to Predict Prediabetes in North China, Beijing: a 7-year Prospective Study

“…The study of Manju Bala [26] found that WHR is positively correlated with HbA1c, which means that a decrease in WHR is effective for the prevention of prediabetes. The previous ndings regarding the association between the WHR and prediabetes [27,28] were consistent with the results of our study.…”

Effectiveness of Anthropometric Measurements for Identifying Diabetes and Prediabetes among Civil Servants in a Regional City of Northern Ethiopia: A Cross-Sectional Study

“…Another study from Indonesia revealed that WtHR predicts prediabetes [39]. Another study from Chinese population showed that the risk of prediabetes increased significantly with increasing WC for both genders [14].…”

“…e distribution of fat in the body is measured by using simple, most practical, at a low cost, and widely used markers of obesity index like anthropometric measurements, such as body mass index (BMI), waist circumference (WC), waistto-hip ratio (WHR), and waist-to-height ratio (WHtR) [7,8]. Different previous studies showed varied prediction abilities of anthropometric measurements to predict prediabetes and diabetes [9][10][11][12][13][14][15][16][17][18][19][20][21]. A study conducted in Ethiopia indicated that WC was a predictor of CVD risk [22].…”

Influence of Health Behaviors and Occupational Stress on Prediabetic State among Male Office Workers

“…According to a 10-year cohort analysis of office workers in large corporations [ 3 ], the OR of those who worked for over 20 years, compared to those who worked 1 to 2 years, were 2.70 (95% CI = 1.63–4.45) in waist circumference (male ≥90 cm), and the risk of contracting diabetes was 3.7 times, which was the highest. In addition, previous studies [ 28 , 37 ] reported that it was important to monitor and prevent increases in waist circumference to reduce the increasing burden of prediabetes, diabetes, and its complications. These are similar to the results of the present study and highlight the need for further studies to consider working years and maintaining waist circumference.…”

“…To identify the influencing factors of prediabetic state, stepwise multiple logistic regression was performed using regression models. Among the statistically significant variables in the descriptive statistical analysis and risk analysis, working years, marital status, waist circumference, systolic blood pressure, and diastolic blood pressure were included to perform multiple logistic regression, but age, body weight, and BMI were excluded, since working years were highly correlated with age and waist circumference were highly related with body weight and BMI, and working years and waist circumference were important factors for office workers [ 3 , 28 ].…”