Ke Zheng1, Wenjing Gao1, Weihua Cao1, Jun Lv1, Canqing Yu1, Shengfeng Wang1, Tao Huang1, Dianjianyi Sun1, Chunxiao Liao1, Yuanjie Pang1, Zengchang Pang2, Min Yu3, Hua Wang4, Xianping Wu5, Zhong Dong6, Fan Wu7, Guohong Jiang8, Xiaojie Wang9, Yu Liu10, Jian Deng11, Lin Lu12, Liming Li1. 1. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China. 2. Qingdao Center for Disease Control and Prevention, Qingdao, China. 3. Zhejiang Center for Disease Control and Prevention, Hangzhou, China. 4. Jiangsu Center for Disease Control and Prevention, Nanjing, China. 5. Sichuan Center for Disease Control and Prevention, Chengdu, China. 6. Beijing Center for Disease Control and Prevention, Beijing, China. 7. Shanghai Center for Disease Control and Prevention, Shanghai, China. 8. Tianjin Center for Disease Control and Prevention, Tianjin, China. 9. Qinghai Center for Disease Control and Prevention, Xining, China. 10. Heilongjiang Center for Disease Control and Prevention, Harbin, China. 11. Handan Center for Disease Control and Prevention, Handan, China. 12. Yunnan Center for Disease Control and Prevention, Kunming, China.
Abstract
OBJECTIVE: This study aimed to examine the association of socioeconomic status with obesity. METHODS: A total of 39,262 twin individuals were included from the Chinese National Twin Registry (CNTR). Generalized estimating equation models for unmatched twin individual analyses and conditional logistic regression for the co-twin matched design were used. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was used to explore the evidence of a causal relationship. RESULTS: In general estimating equation models, high education level and income were associated with lower risk of obesity (odds ratio [OR] = 0.74 [95% CI: 0.65 to 0.84] and 0.86 [95% CI: 0.77 to 0.96]). In conditional logistic regression analysis, the association with education was significant (OR = 0.50 [95% CI: 0.34 to 0.74]) but the association with income was insignificant (OR = 0.74 [95% CI: 0.48 to 1.15]). From the ICE FALCON analysis, a twin's obesity was associated with the co-twin's education and income. After adjusting for the twin's own education, the association disappeared ( β co - twin ' = -0.10 [95% CI: -0.26 to 0.07]), whereas the twin's obesity was still associated with the co-twin's income but attenuated toward the null ( β co - twin ' = -0.21 [95% CI: -0.36 to -0.06]). CONCLUSIONS: Socioeconomic status is negatively associated with obesity. Education may have a causal effect on obesity, whereas the association between income and obesity is confounded by familial factors.
OBJECTIVE: This study aimed to examine the association of socioeconomic status with obesity. METHODS: A total of 39,262 twin individuals were included from the Chinese National Twin Registry (CNTR). Generalized estimating equation models for unmatched twin individual analyses and conditional logistic regression for the co-twin matched design were used. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was used to explore the evidence of a causal relationship. RESULTS: In general estimating equation models, high education level and income were associated with lower risk of obesity (odds ratio [OR] = 0.74 [95% CI: 0.65 to 0.84] and 0.86 [95% CI: 0.77 to 0.96]). In conditional logistic regression analysis, the association with education was significant (OR = 0.50 [95% CI: 0.34 to 0.74]) but the association with income was insignificant (OR = 0.74 [95% CI: 0.48 to 1.15]). From the ICE FALCON analysis, a twin's obesity was associated with the co-twin's education and income. After adjusting for the twin's own education, the association disappeared ( β co - twin ' = -0.10 [95% CI: -0.26 to 0.07]), whereas the twin's obesity was still associated with the co-twin's income but attenuated toward the null ( β co - twin ' = -0.21 [95% CI: -0.36 to -0.06]). CONCLUSIONS: Socioeconomic status is negatively associated with obesity. Education may have a causal effect on obesity, whereas the association between income and obesity is confounded by familial factors.