Association between socio-economic factors and the risk of overweight and obesity among Chinese adults: a retrospective cross-sectional study from the China Health and Nutrition Survey

Abstract

Background With the rising prevalence of obesity and overweight, increasing number of scholars paid attention to the negative effects on human health and life. Recent years, many studies have focused on the relation of socio-economic factors with the risk of overweight or obesity, but findings have been inconsistent. This study investigated the relationship between socio-economic factors and the risk of overweight and obesity among Chinese adults. Methods This study was based on the survey of the China Health and Nutrition Survey in 2015, with 9245 Chinese adults aged 18–65 years old. Overweight and obesity were assessed by physical measurements of weight, height, and waist circumference. Multiple logistic models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of the association. Results Overall, the prevalence rates of general obesity and abdominal obesity were 15.5% and 22.6%, respectively. We found that education and per capita household income were positively associated with overweight and obesity risk in men. However, the association between education and obesity status was negative in women [general obesity: OR = 0.64, 95% CI (0.50–0.81); abdominal obesity: OR = 0.62, 95% CI (0.51–0.76)]. Occupational status was only associated with general overweight in men. Conclusions Results suggested that higher education and per capita household income were associated with an increased risk of overweight and obesity among Chinese men, whereas the associations were negative for women. We recommended that men with high levels of education and income, women with low levels of education, can engage in some physical activity, modify dietary, and adopt a new way of life to maintain their weight and general health.

Effects of green space on physical activity and body weight status among Chinese adults: a systematic review

“…China is rapidly urbanizing, modernizing, and growing economically. However, physical inactivity, sedentary behavior, being overweight, and obesity are prevalent among Chinese adults in the urbanizing and modernizing Chinese society ( 29 , 30 ). From 1991 to 2006, PA levels among Chinese adults declined at an unprecedented rate, with average weekly PA declining by 32%, and the largest percentage decline in PA in China compared to the United States, United Kingdom, India, and Brazil ( 31 ).…”

Correlation of dietary mineral intake and malnutrition in cancer patients: A multicenter cross-sectional study

“…The results suggest that dietary minerals, particularly P, Se, and Mn, may have a protective effect against the development of nutritional risk in patients with malignant tumors. In addition, [11] 204 (42.4) 72 (18.7) <0.001 KPS score, mean ± SD 90.31 ± 9.40 73.12 ± 19.53 <0.001 Appetite score, [14] mean ± SD 7.92 ± 1.55 5.71 ± 2.25 <0.001 Dietary intake score, [15] patients should maintain appropriate levels of Ca and Zn, which also appear to have an association with the nutritional status. However, the results showed no correlation between dietary mineral intake and malnutrition diagnosed based on the GLIM criteria.…”

“…The requirements for Mn can typically be satisfied by a normal diet, and deficiency is rare. However, because cancer patients often have reduced food intake, they may [11] 262 (44.9) 14 (4.9) <0.001 KPS score, mean ± SD 85.74 ± 14.52 72.95 ± 20.11 <0.001 Appetite score, [14] mean ± SD 7.60 ± 1.89 5.95 ± 2.34 <0.001 Dietary intake score, [15] develop Mn deficiency. The results of this cross-sectional study suggest that moderate to high levels of Mn intake may be protective against nutritional risk in patients with malignant tumors.…”

“…The levels of dietary mineral intake in the malnourished group were lower than those in the nonmalnourished group. [11] 157 (30.5) 119 (33.8) 0.3 NRS 2002 score (≥3), n (%) [12] 242 (47.1) 143 (40.6) 0.06 GLIM score (≥2), n (%) [13] 170 (33.1) 113 (32.1) 0.8 KPS score, mean ± SD 82.61 ± 17.5 82.76 ± 16.45 0.9 Appetite score, [14] mean ± SD 6.99 ± 2.20 6.87 ± 2.18 0.5 Dietary intake score, [15] Logistic regression analysis of the associations between the NRS 2002 and GLIM with the intake of dietary minerals Table 2 shows the results of a multivariable logistic regression analysis of the associations of the NRS 2002 and GLIM with the dietary mineral intake after controlling for relevant confounders. Forest plots based on the regression analysis are shown in Figure 1 and Figure 2.…”

Health-related quality of life among patients with knee osteoarthritis in Guangzhou, China: a multicenter cross-sectional study

“…Body mass index (BMI, in kg/m 2 ) was calculated using height and weight for each patient. According to the guidelines of the Working Groups on Obesity in China [ 47 ], BMI was divided into the following four categories: underweight (<18.5), normal weight (18.5-23.9), overweight (24.0-27.9), and obese (≥ 28).…”