Associations between disorders in activities of daily living and heavy metal concentrations in elderly people
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摘要:背景
重金属可能在老年人日常生活活动能力(ADL)障碍的环境危险因素中起重要作用。
目的本研究旨在探讨老年人血浆中锌、砷、镉、铅、锰和铜6种重金属的含量与ADL障碍的关联。
方法2018—2019年对广西壮族自治区恭城瑶族自治县
1412 名农村老年人进行了一项横断面调查,采用电感耦合等离子体质谱法(ICP-MS)检测血浆金属浓度,根据三分位数分为3组(T1~T3),以T1组为参照。采用ADL量表评估调查对象ADL障碍情况。采用logistic回归和限制立方样条模型(RCS)估计优势比(OR)和95%置信区间(CI)来评估重金属与ADL障碍患病率之间的关联。结果研究对象平均年龄为(68.52±5.92)岁,女性825人(58.4%),男性587人(41.6%)。其中372人(26.34%)存在ADL障碍,ADL障碍者多为女性(74.3%)。总人群logistic回归分析结果显示,与T1组(≤0.15 µg·L−1)相比,镉水平T2组(0.15~0.25 µg·L−1)发生ADL障碍的风险较高(OR=1.552,95%CI:1.086~2.134)。按性别分层后,与T1组(≤868.12 µg·L−1)相比,男性血浆铜水平T3组(>
1019.58 µg·L−1)发生ADL障碍的风险较低(OR=0.481,95%CI:0.232~0.998)。与T1组(≤0.15 µg·L−1)相比,女性血浆镉水平T2组(0.15~0.25 µg·L−1)发生ADL障碍的风险较高(OR=1.758,95%CI:1.182~2.616)。RCS分析结果表明,男性ADL障碍风险与铜呈非线性相关(P 非线性=0.011,P 整体<0.05)。结论高浓度的镉与ADL障碍的发生风险呈正相关,而高浓度的铜与男性ADL障碍的发生风险呈负相关。
Abstract:BackgroundHeavy metals may play an important role in environmental risk factors associated disorders of activities of daily living (ADL) in older adults.
ObjectiveTo investigate the associations between plasma levels of six heavy metals (zinc, arsenic, cadmium, lead, manganese, and copper) and ADL disorders in older adults.
MethodsA cross-sectional survey was conducted from 2018 to 2019 among
1412 rural elderly people in Gongcheng Yao Autonomous County, Guangxi Zhuang Autonomous Region. The plasma metal concentrations were detected by inductively coupled plasma mass spectrometry (ICP-MS), and subsequently classified into three groups (T1-T3) based on tertiles, with the T1 group as the reference. The samples were assessed for ADL disorders using the ADL scale. Logistic regression and restricted cubic spline model (RCS) were used to estimate the odds ratio (OR) and 95% confidence interval (CI) to assess the associations between heavy metals and the prevalence of reporting ADL disorders.ResultsThe mean age of the study population was (68.52 ± 5.92) years, 825 (58.4%) female and 587 (41.6%) male. Of these, 372 (26.34%) subjects reported ADL disorders, and most of them were female (74.30%). The results of logistic regression showed that the participants in the cadmium T2 group (0.15-0.25 µg·L−1) had a higher risk of ADL disorders compared to the T1 group (≤0.15 μg·L−1) (OR=1.552, 95%CI: 1.086, 2.134). After stratification by sex, the relative risk of ADL disorders was lower in the plasma copper T3 group (>
1019.58 µg·L−1) compared to the T1 group (≤868.12 μg·L−1) in men (OR=0.481, 95%CI: 0.232, 0.998). The relative risk of ADL disorders was higher in the plasma cadmium T2 group (0.15-0.25 µg·L−1) compared to the T1 group (≤0.15 μg·L−1) in women (OR=1.758, 95%CI: 1.182, 2.616). The RCS results showed that the risk of ADL disorders in men was nonlinearly associated with copper (P nonlinear=0.011,P overall<0.05).ConclusionHigh levels of cadmium are positively associated with the risk of reporting ADL disorders, while high levels of copper are negatively associated with the risk of reporting ADL disorders in men.
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Keywords:
- activity of daily living /
- plasma /
- heavy metal /
- elderly /
- restricted cubic spline
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日常生活活动能力(activities of daily living, ADL)障碍是衡量老年人整体健康状况的指标之一,指不能独立进行吃饭、穿衣、上厕所、洗澡、打电话、购物等任何一项活动,这严重影响老年人生活质量[1]。ADL障碍不仅是预测老年人不良健康事件的指标,如跌倒、骨折等[2],也是人口老龄化过程中的一个突出问题,它加重了老年人家庭和社会的照护负担以及经济压力[3]。据估计,到2050年,全球80岁及以上人口将达到4亿,其中70%生活在欠发达地区[4]。在美国,有报告指出发生ADL障碍的成年人口已达
6100 万,占比25.7%[5]。根据中国第七次人口普查数据,2020年,60岁及以上老年人口已达2.64亿,占总人口的18.7%[6];同时,失能老人规模已达618万人,老年人口失能率为2.34%[7]。与城市相比,文化和经济相对落后的农村地区正面临环境恶化、日常生活活动减少和慢性病的多重威胁[8–9]。因此,现阶段农村老年人口的健康状况和养老保障负担必须予以重点关注。在公共卫生学中,关注ADL相关因素可以帮助更好地了解和照顾老年人群的健康需求,从而提高整个社会的健康水平和生活质量。ADL的影响因素包括个体因素和环境因素。个体因素包括年龄、性别、健康状况、身体功能、认知能力等。环境因素是指个体所处的物理和社会环境,包括居住条件、家庭支持、文化背景等。环境因素在ADL中发挥重要作用,它与个体因素相互作用,共同影响着个体的日常生活能力和生活质量。重金属污染是一个关键的环境问题,因为重金属离子具有难以降解、易于积累的特性[10]。重金属暴露可通过空气污染、水和危险职业(如在金属工业和电镀加工中工作)发生[11]。饮食等不同的生活习惯也可导致重金属污染的产生[12–13]。重金属砷、镉、铜、锰、铅和锌可能与ADL障碍的发生有关。研究表明,镉和铅的暴露会对美国老年人的ADL障碍产生有害影响,并导致功能依赖[14]。铅通过干扰神经递质和钙释放,扰乱胆碱能功能,抑制N-甲基-D-天冬氨酸受体离子通道,损伤神经系统,并刺激活性氧的形成,加速细胞死亡[15–16]。镉通过增加乙酰胆碱酯酶的活性,降低乙酰胆碱的浓度[17],引起认知损害[18],最终导致老年人功能状态的限制[19–20]。锰、锌也被指出可能导致ADL障碍[21–22]。有研究发现淀粉样蛋白-蛋白聚集是其与铜等金属相互作用的结果[23],提示铜可能导致神经变性[24–26],甚至ADL障碍的发生[27]。然而,最近的一项流行病学研究结果发现铜在老年人ADL障碍风险中可能发挥保护作用[28]。目前,关于重金属元素与ADL障碍关系的研究较少,两者关系仍不明确。
不同的重金属暴露水平可能导致重金属与ADL障碍之间的关系不一致。并且,重金属和ADL的关联受到性别等个体差异因素的影响。因此,本研究团队开展了一项在广西壮族自治区恭城瑶族自治县的横断面研究,旨在评估农村老年人血浆重金属水平与ADL障碍风险之间的关联。研究采用电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)测定人体血浆6种重金属元素含量,并进一步评估了血浆重金属水平与ADL障碍风险的关系。
1. 对象与方法
1.1 研究对象
本研究在2018至2019年间对中国西南地区广西壮族自治区恭城瑶族自治县的农村成年人进行了一项横断面调查。选择符合以下标准的研究对象:1)居住在研究区域;2)年龄在60岁及以上。初步纳入
1701 名研究对象,根据以下标准排除受试者:1)未完成问卷或问卷中缺少协变量数据;2)使用精神药物,有精神障碍;3)被诊断出患有严重的器质性疾病,如心力衰竭和恶性肿瘤;4)金属值异常的参与者(定义为第99百分位数的3倍)。共排除289人后,对符合条件的1412 名受试者的数据进行了分析。研究方案已获得桂林医学院伦理委员会的批准(编号:20180702-3)。每位参与者均提供书面知情同意书。1.2 血浆金属浓度测量
采集至少禁食12 h的研究对象的空腹静脉血,通过离心处理分离出血浆,并于−80 ℃超低温储存,用于测量金属浓度。本研究使用电感耦合等离子体质谱仪(赛默飞世尔公司,美国)测量血浆中的6种金属(锌、砷、镉、铅、锰和铜)质量浓度(简称浓度),使用含有0.01% Triton X-100、0.5%正丁醇(丹麦Across)和1%硝酸(超纯)的酸性溶液将0.1 mL血浆稀释至2.0 mL。标准对照中的金属含量(ClinChek,德国)用于质量控制。每25份样本测定1次2种标准试剂,本研究测得的金属浓度均在试剂规格的参考值范围内,完成质控。血浆金属的测定内变异系数和测定间变异系数均低于10%。所有样品标准添加的加标回收率为80.16%~114.65%。锌、砷、镉、铅、锰和铜的检出限分别为0.071、0.005、0.002、0.015、0.021和0.004 µg·L−1。所有等离子体金属均在检出限(limit of detection, LOD)以上测量。
1.3 ADL测量
ADL量表由14个项目组成,用于评估障碍,分为两部分:日常生活体力活动(physical activities of daily living, PADL)和日常生活工具活动(instrumental activities of daily living, IADL)。PADL的6个项目是吃饭、如厕、穿衣、梳洗、走路和洗澡,IADL的8个项目是做饭、购物、打电话、做家务、洗衣服、开车、吃药、处理金钱和物品。每项有4个选项,得分范围从1到4:1—我完全可以做;2—我有一些困难;3—我需要帮助;4—我根本不会做。总分14~56分,14分为正常水平,15分及以上为ADL障碍。单项评分1分为正常,2~4分为障碍。在本研究中,如果个体自我报告在14种日常活动的任何领域需要帮助或依赖,则确定ADL障碍。
该量表在农村地区适用性较好,Cronbach’s冗余系数为0.811[29]。
1.4 协变量的测定
调查人员接受了统一的培训,从每个参与者的问卷中收集性别(男性或女性)、年龄、民族(汉族、瑶族或其他)、文化程度(小学或中学及以上)、吸烟(是否吸烟)、饮酒(是否饮酒)、空腹血糖、静息血压(收缩压/舒张压)和体重指数(body mass index, BMI)等信息。每天至少抽1支烟的参与者被定义为吸烟者。饮酒者被定义为每月至少1次饮酒超过50 g的人。长期(每周≥3晚,持续3个月以上)异常无法获得充足和不间断睡眠的人被定义为失眠症患者。空腹血糖浓度≥7.0 mmol·L−1或正在服用降糖药的受试者被认为是高血糖。血压≥140/90 mmHg或正在服用降压药的参与者被认为是高血压[30]。BMI分为正常体重(BMI<24.0 kg·m−2)、超重(24.0 kg·m−2≤BMI<28.0 kg·m−2)和肥胖(BMI≥28.0 kg·m−2)[31]。
1.5 统计学分析
对研究对象的所有人口统计学和临床特征进行了描述性统计。连续变量表示为平均值或中位数。分类变量以数字和百分比的形式呈现。金属水平经过log10变换以减小它们的偏斜度。根据重金属浓度的三分位数将其分为T1、T2与T3三组,具体划分切点为33.3%和66.7%。本研究的非正态分布资料使用Mann Whitney U检验;分类变量采用卡方检验进行分析。采用Spearman相关分析探讨金属之间的相关性。对不同调整模型采用logistic回归分析。模型1作单因素分析,模型2以性别、年龄作为协变量,模型3以性别、年龄、民族、受教育程度、吸烟、饮酒、失眠、高血压、高血糖和BMI作为协变量,根据金属浓度分为3组(T1至T3),以T1组为参照。6种金属暴露水平与ADL障碍之间的关系根据校正优势比(odds ratio, OR)估计。
此外,采用限制立方样条模型(restricted cubic spline, RCS)检验重金属与ADL障碍的线性假设,描述重金属水平与ADL障碍风险之间的暴露-反应关系,并最大程度地减小混杂因素的影响[32]。共4个节点,位置分别为0.05,0.35,0.65,0.95。所有分析均采用SPSS 25.0和R 4.0.0进行。检验水准α=0.05。
2. 结果
2.1 研究对象的基本情况
大多数研究对象为女性(约58.4%),平均年龄为(68.50±5.92)岁,其中372人(26.3%)存在ADL障碍。民族以瑶族最多,占67.3%,56.4%的参与者文化程度为小学。研究对象的平均血糖和BMI分别为(5.24±1.49)mmol·L−1和(22.1±3.36)kg·m−2。与正常组相比,ADL障碍者年龄更高(P<0.05),女性、文化程度为小学文化、不吸烟、不饮酒、患高血压者比例更高(P<0.05),见表1。
表 1 研究对象的基本情况[例数(构成比/%)]Table 1. Basic information on the study population [n (proportion/%)]变量(Varaible) 总人群
(Total)
(n=1412)正常组
(Normal group)
(n=1040)ADL障碍组
(ADL disorder group)
(n=372)P 性别(Sex) <0.001 男性(Male) 587(41.6) 492(47.2) 95(25.7) 女性(Female) 825(58.4) 551(52.8) 274(74.3) 年龄/岁(Age, years),x̄±s 68.5±5.92 67.5±5.30 71.5±6.55 <0.001 民族(Ethnic group) 0.052 汉族(Han) 395(28.0) 274(26.3) 121(32.8) 瑶族(Yao) 950(67.3) 720(69.0) 230(62.3) 其他(Others) 67(4.7) 49(4.7) 18(4.9) 文化程度(Education) <0.001 小学文化(Primary school) 797(56.4) 526(50.4) 271(73.4) 中学及以上(Middle
school and above)615(43.6) 517(49.6) 98(26.6) 吸烟(Smoking) <0.001 是(Yes) 285(20.2) 240(23.0) 45(12.2) 否(No) 1127(79.8) 803(77.0) 324(87.8) 饮酒(Drinking) <0.001 是(Yes) 518(36.7) 423(40.6) 95(25.7) 否(No) 894(63.3) 620(59.4) 274(74.3) 失眠(Insomnia) 0.240 是(Yes) 648(45.9) 469(45.0) 179(48.5) 否(No) 764(54.1) 574(55.0) 190(51.5) 高血压(Hypertension) 0.046 是(Yes) 708(50.1) 507(48.6) 201(54.5) 否(No) 704(49.9) 536(51.4) 168(45.5) 高血糖(Hyperglycemia) 0.820 是(Yes) 422(29.9) 310(29.7) 112(30.4) 否(No) 990(70.1) 733(70.3) 257(69.6) BMI 0.130 正常(Normal) 911(64.5) 650(62.3) 261(70.7) 超重(Overweight) 422(29.9) 333(31.9) 89(24.1) 肥胖(Obese) 79(5.6) 60(5.8) 19(5.1) 2.2 血浆金属浓度及相关性
所有研究对象的血砷、镉、铜、锰、铅和锌浓度的M(P25,P75)分别为1.23(0.95,2.00)、0.19(0.13,0.29)、937.31(827.91,
1069.88 )、1.95(1.48,2.86)、5.08(3.32,8.55)和993.59(746.26,2400.53 )μg·L−1。血浆金属浓度在对照组和ADL障碍组之间的差异无统计学意义(P﹥0.05),见表2。表 2 不同人群血浆重金属的分布特征Table 2. Distribution characteristics of plasma heavy metals by groups单位(Unit):μg·L−1 变量(Variable) 正常组(Normal group)
M(P25,P75)ADL障碍组(ADL disorder group)
M(P25,P75)P 总人群(Total) 砷(Arsenic) 1.22(0.94,1.97) 1.23(0.95,2.17) 0.45 镉(Cadmium) 0.18(0.12,0.28) 0.19(0.13,0.29) 0.57 铜(Copper) 933.39(817.96,1075.83) 952.16(849.96,1056.83) 0.20 锰(Manganese) 1.96(1.49,2.84) 1.88(1.44,2.89) 0.44 铅(Lead) 5.04(3.34,8.49) 5.14(3.25,8.66) 0.59 锌(Zinc) 993.01(752.41,2505.93) 997.62(733.61,2362.93) 0.32 男性(Male) 砷(Arsenic) 1.24(0.95,1.93) 1.27(0.91,1.72) 0.72 镉(Cadmium) 0.19(0.12.0.29) 0.19(0.12,0.35) 0.82 铜(Copper) 900.85(780.96,1013.83) 907.43(815.96,986.44) 0.95 锰(Manganese) 1.95(1.49,2.83) 1.89(1.41,3.12) 0.96 铅(Lead) 5.37(3.54,8.98) 5.96(3.56,8.71) 0.50 锌(Zinc) 976.24(723.41,2359.93) 1030.63(727.2539.93) 0.33 女性(Female) 砷(Arsenic) 1.20(0.94,2.08) 1.20(0.96,2.41) 0.44 镉(Cadmium) 0.19(0.12,0.28) 0.19(0.13,0.28) 0.47 铜(Copper) 977.68(853.96,1100.83) 974.81(860.87,1076.83) 0.94 锰(Manganese) 2.02(1.49,2.88) 1.88(1.48,2.72) 0.33 铅(Lead) 4.75(3.17,7.93) 4.43(3.11,8.58) 0.90 锌(Zinc) 998.27(764.66,2517.93) 972.62(738.61,1999.93) 0.30 6种金属之间的相关性分析结果如图1所示。总人群中,除砷与铅、锌以外,其余金属之间的相互关联均具有统计学意义(P<0.05),相关系数为0.07到0.48。男性人群中,除了砷与铅、锌和镉,铜与锰以外,其余金属之间的相互关联均具有统计学意义(P<0.05),相关系数为从0.10到0.47。女性人群中,除了砷与铅、锌以外,其余金属之间的相互关联均具有统计学意义(P<0.05),相关系数为从0.08到0.49。
2.3 ADL障碍与重金属浓度的关联
如图2所示,在模型1中,与最低三分位数的参与者相比,镉T2组的参与者发生ADL障碍的风险增加至1.388倍(95%CI:1.038~1.857,P<0.05)。在模型2中调整性别、年龄后,镉与ADL障碍风险发生的关联仍具有统计学意义(OR=1.485,95%CI:1.085~2.032,P<0.05)。男性人群中,锰T2组的OR为0.527(95%CI:0.290~0.958,P<0.05)。在模型3中调整了性别、年龄、民族、教育程度、吸烟、饮酒、失眠、高血压、高血糖和BMI后,镉水平与ADL障碍有关,T2组OR值为1.522(95%CI:1.086~2.134,P<0.05)。性别分层后,女性镉T2组的OR值为1.758(95%CI:1.182~2.616,P<0.05),男性铜T3组的OR值为0.481(95%CI:0.232~0.998,P<0.05)。提示在男性中,ADL障碍的发生与铜的浓度有关。
图 2 6种金属与ADL障碍的相关性Model 1未调整因素;Model 2调整因素为性别、年龄;Model 3调整因素为性别、年龄、民族、文化程度、吸烟、饮酒、失眠、高血压、高血糖和BMI。Figure 2. Correlations of six metals with ADL disordersModel 1 does not adjust factors; Model 2 adjusts for sex and age; Model 3 adjusts for sex, age, ethnic group, education, smoking, drinking, insomnia, hypertension, hyperglycemia, and BMI.2.4 金属与ADL障碍之间的暴露-反应关系
在调整性别、年龄、民族、教育程度、吸烟、饮酒、失眠、高血压、高血糖和BMI后,RCS分析结果表明,男性ADL障碍风险与铜呈非线性相关(P非线性=0.011,P整体<0.05)。见图3。
3. 讨论
这项以恭城县60岁以上成年人为研究对象的人群研究显示,26.3%的参与者存在ADL障碍,高于广西河池市(21.8%)[21]和韩国首尔市(7.2%)[33]。本次研究发现,在总人群中,镉与增加患病风险相关。在男性人群中,铜与降低男性患病风险相关。铜与男性ADL障碍之间存在非线性相关关系。
一般人群接触镉的途径主要是饮食,比如食用贝类、肝脏[34]。吸烟也是常见的镉暴露来源[34–35]。目前许多证据表明,与年龄相关的疾病的患病率增加与镉有关,如心血管、神经和代谢疾病[36–37]。一项对
5513 名老年人的横断面研究发现血液镉水平升高与ADL下降相关[14]。这与本研究的结果一致。一项基因组甲基化研究结果表明,镉通过引起表皮生长因子受体和磷脂酰肌醇3-激酶信号通路上的基因甲基化改变,导致ADL障碍[38–39],此结果提示镉暴露可以通过调控氧化应激反应和甲基化,从而影响ADL。一项为期3年的随访研究提示,认知障碍(包括执行功能障碍、失用症和记忆问题)与ADL障碍有关[40]。镉暴露被认为是美国成年人神经认知能力下降的原因之一[41]。动物研究也出现了类似结果,镉通过诱导细胞凋亡、抑制增殖,损害大脑皮层和海马体神经元,导致认知障碍[42]。因此,镉可能是ADL障碍的危险因素。一项大鼠的实验研究发现镉暴露特异性损伤大鼠的学习认知功能,并且损伤效应存在性别差异,该差异的毒理作用机制为负向调控神经元突起生长的磷脂酶β4(PLCβ4)在雄性大鼠中特异性高表达(上调6.79倍)[43]。然而,尚未有研究证明镉对ADL障碍的影响与性别差异相关。因此,性别对镉与ADL障碍关系的影响有待进一步研究。
铜暴露的主要途径是食物和饮用水[44]。关于铜与ADL障碍的研究较少。伊朗北部的一项流行病学研究结果表明,铜与ADL障碍存在正相关关联[40]。而本研究发现铜与ADL障碍呈负相关,与前人研究不一致。相互矛盾的结果可能是因为铜既是促氧化剂又是抗氧化剂,铜蓝蛋白、铜依赖性超氧化物歧化酶等多种与代谢和氧化应激相关的酶促反应都与铜相关[45–46]。有家兔实验表明,过量的铜摄入会增加动脉粥样硬化的易感性,这反映了铜与动脉粥样硬化的双相关系[47]。并且各观察性研究所研究的种群和种群所处环境存在差异,从而导致研究结果不同。此外,有2011—2014年美国国家健康和营养检查调查(NHANES)的数据发现,老年人较高的血清铜浓度与认知表现测试呈负相关[48–49]。而在约旦老年人中,血清铜与认知能力下降之间没有发现实质性的相关性[50]。铜与ADL障碍的关系仍存在争议,研究人员需要找到更多的实验和流行病学证据来阐明铜与ADL障碍的关系。
既往研究报道铜可能通过影响激素相关的神经发育,造成性别差异[51]。例如,铜的增加可以显著改变男性神经发育相关的激素,如游离甲状腺素的水平[52],然而这项研究并未证明性别-重金属相互作用与ADL障碍之间存在显著关联。因此,性别对铜与ADL障碍关系的影响有待进一步研究。
砷暴露的主要原因是摄入含有无机砷的防腐剂,以及受到工业或农业废物污染的饮用水[53]。铅暴露的主要来源包括油漆、工业污水排放、电子垃圾、中药制品等[54]。锰和锌的主要途径是食物和饮用水[43]。然而,在本研究中,并没有发现铅、锌、锰和砷4种重金属元素与ADL障碍之间存在显著关联。关于人体血液中重金属浓度与ADL障碍之间关系的研究很少。2011—2012年和2013—2014年全国健康与营养调查发现ADL障碍的风险与血锌水平显著相关(0.81 µg·mL−1)[55],且性别、文化程度与血清锌水平有交互作用。2001—2006年全国健康与营养检查调查显示铅含量与ADL显著相关(2.20 μg·dL−1)。中国广西红水河流域居民的ADL障碍风险与血浆锰(22.10 µg·L−1)和砷(2.25 µg·L−1)水平升高显著相关[21]。上述研究中锰、砷和铅的暴露水平高于本研究。成人血液中锌的指定安全水平为<1.10 µg·mL−1[56]。在本研究中,受试者血浆中的锌浓度低于上述研究,且在安全标准范围内。重金属浓度的差异可能是导致研究结果不一致的原因。
本研究尚存若干不足之处。首先,鉴于ADL的保护与危险因素繁多且作用机制错综复杂,由于纳入的病例对照样本量相对有限,导致结果呈现上存在一定的局限性。其次,本研究主要基于横断面研究设计,因此在探究重金属与ADL之间的因果关系时,其推断能力相对较弱。最后,本研究样本规模较小,且主要聚焦于瑶族人群,这可能导致研究结果的外推性和代表性受限。未来研究应进一步扩大样本量,并考虑采用纵向研究设计,以更准确地揭示重金属与ADL之间的关联机制。
综上,高浓度的镉与ADL障碍的发生风险呈正相关,而高浓度的铜与男性ADL障碍的发生风险呈负相关。
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图 2 6种金属与ADL障碍的相关性
Model 1未调整因素;Model 2调整因素为性别、年龄;Model 3调整因素为性别、年龄、民族、文化程度、吸烟、饮酒、失眠、高血压、高血糖和BMI。
Figure 2. Correlations of six metals with ADL disorders
Model 1 does not adjust factors; Model 2 adjusts for sex and age; Model 3 adjusts for sex, age, ethnic group, education, smoking, drinking, insomnia, hypertension, hyperglycemia, and BMI.
表 1 研究对象的基本情况[例数(构成比/%)]
Table 1 Basic information on the study population [n (proportion/%)]
变量(Varaible) 总人群
(Total)
(n=1412)正常组
(Normal group)
(n=1040)ADL障碍组
(ADL disorder group)
(n=372)P 性别(Sex) <0.001 男性(Male) 587(41.6) 492(47.2) 95(25.7) 女性(Female) 825(58.4) 551(52.8) 274(74.3) 年龄/岁(Age, years),x̄±s 68.5±5.92 67.5±5.30 71.5±6.55 <0.001 民族(Ethnic group) 0.052 汉族(Han) 395(28.0) 274(26.3) 121(32.8) 瑶族(Yao) 950(67.3) 720(69.0) 230(62.3) 其他(Others) 67(4.7) 49(4.7) 18(4.9) 文化程度(Education) <0.001 小学文化(Primary school) 797(56.4) 526(50.4) 271(73.4) 中学及以上(Middle
school and above)615(43.6) 517(49.6) 98(26.6) 吸烟(Smoking) <0.001 是(Yes) 285(20.2) 240(23.0) 45(12.2) 否(No) 1127(79.8) 803(77.0) 324(87.8) 饮酒(Drinking) <0.001 是(Yes) 518(36.7) 423(40.6) 95(25.7) 否(No) 894(63.3) 620(59.4) 274(74.3) 失眠(Insomnia) 0.240 是(Yes) 648(45.9) 469(45.0) 179(48.5) 否(No) 764(54.1) 574(55.0) 190(51.5) 高血压(Hypertension) 0.046 是(Yes) 708(50.1) 507(48.6) 201(54.5) 否(No) 704(49.9) 536(51.4) 168(45.5) 高血糖(Hyperglycemia) 0.820 是(Yes) 422(29.9) 310(29.7) 112(30.4) 否(No) 990(70.1) 733(70.3) 257(69.6) BMI 0.130 正常(Normal) 911(64.5) 650(62.3) 261(70.7) 超重(Overweight) 422(29.9) 333(31.9) 89(24.1) 肥胖(Obese) 79(5.6) 60(5.8) 19(5.1) 表 2 不同人群血浆重金属的分布特征
Table 2 Distribution characteristics of plasma heavy metals by groups
单位(Unit):μg·L−1 变量(Variable) 正常组(Normal group)
M(P25,P75)ADL障碍组(ADL disorder group)
M(P25,P75)P 总人群(Total) 砷(Arsenic) 1.22(0.94,1.97) 1.23(0.95,2.17) 0.45 镉(Cadmium) 0.18(0.12,0.28) 0.19(0.13,0.29) 0.57 铜(Copper) 933.39(817.96,1075.83) 952.16(849.96,1056.83) 0.20 锰(Manganese) 1.96(1.49,2.84) 1.88(1.44,2.89) 0.44 铅(Lead) 5.04(3.34,8.49) 5.14(3.25,8.66) 0.59 锌(Zinc) 993.01(752.41,2505.93) 997.62(733.61,2362.93) 0.32 男性(Male) 砷(Arsenic) 1.24(0.95,1.93) 1.27(0.91,1.72) 0.72 镉(Cadmium) 0.19(0.12.0.29) 0.19(0.12,0.35) 0.82 铜(Copper) 900.85(780.96,1013.83) 907.43(815.96,986.44) 0.95 锰(Manganese) 1.95(1.49,2.83) 1.89(1.41,3.12) 0.96 铅(Lead) 5.37(3.54,8.98) 5.96(3.56,8.71) 0.50 锌(Zinc) 976.24(723.41,2359.93) 1030.63(727.2539.93) 0.33 女性(Female) 砷(Arsenic) 1.20(0.94,2.08) 1.20(0.96,2.41) 0.44 镉(Cadmium) 0.19(0.12,0.28) 0.19(0.13,0.28) 0.47 铜(Copper) 977.68(853.96,1100.83) 974.81(860.87,1076.83) 0.94 锰(Manganese) 2.02(1.49,2.88) 1.88(1.48,2.72) 0.33 铅(Lead) 4.75(3.17,7.93) 4.43(3.11,8.58) 0.90 锌(Zinc) 998.27(764.66,2517.93) 972.62(738.61,1999.93) 0.30 -
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