Objective: To investigate the association between urinary arsenic levels and anemia among older adults in nine longevity areas of China. Methods: A total of 1 896 subjects aged 65 years and above who participated in the Healthy Aging and Biomarkers Cohort Study (HABCS) in 2017-2018 were included. A self-made questionnaire was used to collect demographic characteristics, lifestyle and other information from the subjects. Through physical examination, data including height, weight and blood pressure were determined and body mass index (BMI) was calculated. Blood and urine samples were collected for the detection of hemoglobin (Hb), blood glucose, blood lipids, plasma vitamin B12 and urinary arsenic concentrations. The urinary arsenic levels were divided into four groups according to the quartiles of urinary arsenic concentrations (μg/g creatinine): Q1 (<18.7), Q2 (18.7-34.5), Q3 (34.6-69.5) and Q4(≥69.6). Multivariate logistic regression model and restricted cubic spline fitting logistic regression model were used to analyze the association between urinary arsenic levels and anemia. Results: The age of the 1 896 subjects (M (Q1, Q3)) was 83 (74, 92) years, including 952 females (50.21%), and the concentration of Hb (M (Q1, Q3)) was 135 (124, 147)g/L. The prevalence of anemia was 24.89% (472 cases). The geometric mean and M (Q1, Q3) of urinary arsenic concentrations were 37.5 and 34.6 (18.7, 69.6)μg/g creatinine, respectively. Multivariate logistic regression model analysis showed that after adjusting for age, gender, BMI, education level, smoking and drinking status, residence, economic level, ethnicity, the status of vitamin B12 deficiency, consumption frequency of aquatic products and meat, the prevalence of hypertension, diabetes and dyslipidemia, urinary arsenic levels were positively associated with anemia (Taking group Q1 as a reference, OR (95%CI) values in Q2, Q3 and Q4 groups were 1.73 (1.20-2.50), 2.08 (1.43-3.02) and 1.52 (1.02-2.28), respectively). The results of restricted cubic spline fitting logistic regression analysis showed a non-linear association between urinary arsenic concentrations and anemia (P<0.001). Subgroup analysis showed there was a negative multiplicative interaction between the prevalence of chronic diseases and urinary arsenic levels with OR (95%CI) was 0.55 (0.30-0.99), while no multiplicative interaction was found between age, gender, residence, smoking status, drinking status and urinary arsenic levels (P>0.05). There was a positive association between urinary arsenic levels and anemia in participants who were absence of chronic diseases,male, living in rural, smoking and drinking with OR (95%CI) values of 3.62 (1.30-10.06),2.46 (1.34-4.52), 1.70 (1.03-2.80), 2.21 (1.01-4.82) and 2.79 (1.23-6.33), respectively. Conclusion: There is a positive association between urinary arsenic levels and anemia among older adults in nine longevity areas of China.
目的： 探讨中国9个长寿地区老年人尿砷水平与贫血的关系。 方法： 以2017—2018年参与老年健康生物标志物队列研究的1 896名65岁及以上老年人为对象，采用自制问卷收集人口学特征和生活方式等资料，通过体格检查测定身高、体重、血压并计算体质指数（BMI），采集血液和尿液标本后分别检测血红蛋白（Hb）、血糖、血脂、血浆维生素B12和尿砷等指标。将尿砷水平（μg/g 肌酐）按四分位数分为Q1（<18.7）、Q2（18.7~34.5）、Q3（34.6~69.5）和Q4（≥69.6）等不同尿砷水平，分别采用多因素logistic回归模型和限制性立方样条拟合logistic回归模型分析尿砷水平与贫血的关系。 结果： 研究对象年龄［M（Q1，Q3）］为83（74，92）岁，其中女性952名（50.21%），Hb含量［M（Q1，Q3）］为135（124，147）g/L，贫血患病率为24.89%（472例），尿砷水平几何均数和［M（Q1，Q3）］分别为37.5和34.6（18.7，69.6）μg/g肌酐。多因素logistic回归模型分析显示：调整年龄、性别、BMI、教育水平、吸烟、饮酒情况、居住地、经济水平、民族、维生素B12缺乏情况、水产品和肉类食用频率、高血压、糖尿病和血脂异常患病情况等因素后，尿砷水平与贫血均呈正向关联［以Q1组为参照，Q2、Q3和Q4组的OR（95%CI）分别为1.73（1.20~2.50）、2.08（1.43~3.02）和1.52（1.02~2.28）］。限制性立方样条拟合logistic回归分析结果显示：尿砷水平与贫血存在非线性关联（P<0.001）。亚组分析显示：慢性病患病情况与尿砷水平具有负相乘交互作用［OR（95%CI）：0.55（0.30~0.99）］，未发现年龄、性别、居住地、吸烟和饮酒情况等与尿砷水平之间的相乘交互作用（均P>0.05）。未患慢性病、男性、乡村居住、吸烟和饮酒对象的尿砷水平与贫血呈正向关联［OR（95%CI）值分别为3.62（1.30~10.06）、2.46（1.34~4.52）、1.70（1.03~2.80）、2.21（1.01~4.82）和2.79（1.23~6.33）］。 结论： 中国9个长寿地区老年人尿砷水平与贫血呈正向关联。.