-
摘要:
目的 研究老年人肠道菌群α多样性的影响因素。 方法 对社区老年人肠道菌群16Sr-DNA测序并分析菌群α多样性。按照四分位数将α多样性分为“高”和“低”两组,利用logistic回归分析模型分析肠道菌群α多样性的影响因素。 结果 多因素logistic回归分析模型分析结果显示,与最低三分位数组相比,精制谷物和水果摄入量最高三分位数组肠道菌群“高”Shannon指数OR(95% CI)值分别为0.57(0.36~0.89)和1.86(1.15~3.02);较高频次酸菜/泡菜摄入者肠道菌群“高”Shannon指数OR(95% CI)值为0.47(0.27~0.81)。与Shannon指数类似,精制谷物、酸菜/泡菜和水果也是Simpson指数的影响因素,此外,性别也是Simpson指数的影响因素(P=0.028)。 结论 增加水果摄入有助于增加老年人肠道菌群α多样性,而精制谷物、酸菜/泡菜的摄入则可能不利于α多样性的增加。 Abstract:Objective To explore factors influencing α diversity of gut micro-biota in the older people. Methods Stool samples were collected to extract gut microbiota DNA, 16Sr-DNA sequencing was conducted, and gut microbiota α diversity was analyzed. α diversity was categorized as 'High' or 'Low' according to the quantile of every indicator. Logistic regression models were run to analyze the potential factors that influencing gut microbiota diversity. Results Multivariate logistic regressions showed, compared with the lowest tertile group, OR(95% CI) of high Shannon index in the higher tertile group of refined grain and fruit intake was 0.57(0.37-0.88) and 2.03(1.27-3.24), respectively. Compared with the low group, the possibility of high Shannon index in the high group of pickle intake frequency declined, with OR of 0.45(0.26-0.78). Similarly with Shannon index, refined grain, pickles intake frequency, and fruit intake were all factors influencing the Simpson's index, as well as sex (P=0.028). Conclusions Increasing fruit intake may be beneficial for α diversity of gut microbiota, while intake of refined grain and pickles may be harmful in the older people. -
Key words:
- Gut microbiota /
- α diversity /
- Influencing factors /
- Older people
-
表 1 研究对象基本特征与肠道菌群α多样性(x±s)
Table 1. Characterics and gut microbiota α diversity of participants(x±s)
特征 合计 男 女 t/χ2值 P值 例数 648 302 346 年龄[(x±s), 岁] 72.02±4.47 72.10±4.51 71.95±4.43 0.440 0.659 饮酒[n(%)] ≥1次/月 85(13.12) 72(23.84) 13(3.76) 57.072 < 0.001 < 1次/月 563(83.88) 230(76.16) 347(96.24) 体育锻炼[n(%)] 是 468(72.22) 223(73.84) 245(70.81) 0.739 0.390 否 180(27.78) 79(26.16) 101(29.19) 精制谷物摄入量[M(P25, P75), g] 200.00(110.71, 300.00) 200.00(114.29, 300.00) 200.00(107.14, 255.00) 3.322 0.068 新鲜蔬菜摄入量[M(P25, P75), g] 200.00(100.00, 205.00) 200.00(100.00, 300.00) 200.00(100.00, 200.00) 1.193 0.275 酸菜/泡菜摄入频率[n(%)] ≥1次/周 123(18.98) 53(17.55) 70(20.23) 0.754 0.385 < 1次/周 525(81.02) 249(82.45) 276(79.77) 水果摄入量[M(P25, P75), g] 42.86(14.29, 100.00) 42.86(14.28, 100.00) 42.86(14.29, 100.00) 0.285 0.593 红肉摄入量[M(P25, P75), g] 28.57(13.33, 50.00) 28.57(14.29, 57.14) 25.71(11.43, 42.86) 6.482 0.011 牛奶摄入量[M(P25, P75), g] 42.86(0.00, 180.00) 67.85(1.37, 200.00) 28.57(0.00, 114.29) 9.812 < 0.001 酸奶摄入量[M(P25, P75), g] 0.00(0.00, 28.57) 2.00((0.00, 28.57) 0.00(0.00, 28.57) 0.851 0.356 蛋类摄入量[M(P25, P75), g] 50.00(15.00, 55.00) 50.00(17.14, 55.00) 50.00(14.29, 55.00) 1.582 0.208 Shannon指数 5.77±0.76 5.78±0.76 576±0.74 0.370 0.708 Simpson指数 0.93±0.06 0.93±0.07 0.93±0.06 -0.260 0.791 Chao1指数 800.42±244.33 795.40±226.60 804.80±259.00 0.490 0.625 观察菌种数 678.21±197.41 672.00±175.30 683.70±215.00 -0.447 0.453 注:1.年龄和4项α多样性的指标均以(x±s)表示;2.表中食物摄入量呈偏态分布,故利用[M(P25, P75)]表示,男女两组差异检验用秩和检验(Kruskal-Wallis检验)。 表 2 肠道菌群高α多样性单因素logistic回归分析
Table 2. Univariate logistic regression analysis for gut microbiota high α diversity
特征 高Shannon指数 高Simpson指数 高Chao1指数 高观察菌种数 OR (95% CI)值 Wald值 P值 OR (95% CI)值 Wald值 P值 OR (95% CI)值 Wald值 P值 OR (95% CI)值 Wald值 P值 年龄(岁) 65~<75 1.00 1.00 1.00 1.00 ≥75 0.89(0.59~1.33) 0.311 0.577 1.33(0.91~1.95) 2.136 0.144 0.93(0.62~1.39) 0.126 0.723 1.01(0.68~1.50) 0.003 0.960 性别 男 1.00 1.00 1.00 1.00 女 0.76(0.53~1.08) 2.383 0.123 0.67(0.48~0.96) 4.791 0.029 1.08(0.76~1.55) 0.207 0.649 1.20(0.84~1.72) 0.999 0.318 饮酒 否 1.00 1.00 1.00 1.00 是 1.06(0.63~1.78) 0.041 0.840 1.21(0.73~2.01) 0.562 0.453 0.78(0.45~1.36) 0.759 0.383 0.85(0.49~1.46) 0.365 0.546 运动 否 1.00 1.00 1.00 1.00 是 1.23(0.82~1.86) 1.023 0.312 1.40(0.92~2.09) 2.505 0.114 1.04(0.70~1.55) 0.041 0.840 0.92(0.62~1.37) 0.164 0.686 精制谷物 T1 1.00 1.00 1.00 1.00 T2 0.57(0.32~0.87) 6.562 0.01 0.82(0.54~1.25) 0.862 0.353 0.53(0.34~0.83) 7.589 0.006 0.67(0.43~1.04) 3.165 0.075 T3 0.57(0.37~0.88) 6.421 0.011 0.62(0.40~0.96) 4.537 0.033 0.84(0.56~1.28) 0.631 0.427 1.04(0.68~1.58) 0.028 0.867 新鲜蔬菜 T1 1.00 1.00 1.00 1.00 T2 0.94(0.62~1.43) 0.083 0.774 1.01(0.67~1.53) 0.005 0.945 0.68(0.45~1.05) 3.093 0.079 0.84(0.55~1.30) 0.603 0.438 T3 1.00(0.63~1.58) 0.001 0.993 0.92(0.59~1.46) 0.119 0.729 1.07(0.69~1.68) 0.108 0.742 1.25(0.80~1.95) 0.946 0.331 酸菜泡菜 < 1次/周 1.00 1.00 1.00 1.00 ≥1次/周 0.45(0.26~0.78) 8.373 0.004 0.49(0.29~0.82) 7.366 0.007 0.96(0.61~1.52) 0.029 0.863 0.81(0.51~1.30) 0.751 0.386 水果 T1 1.00 1.00 1.00 1.00 T2 1.69(1.06~2.69) 4.853 0.027 1.92(1.21~3.05) 7.674 0.006 1.08(0.70~1.68) 0.133 0.716 1.38(0.88~2.15) 1.973 0.160 T3 2.03(1.27~3.24) 8.844 0.003 2.08(1.30~3.31) 9.432 0.002 1.06(0.67~1.65) 0.055 0.814 1.35(0.86~2.13) 1.654 0.198 红肉 T1 1.00 1.00 1.00 1.00 T2 1.26(0.82~1.95) 1.129 0.288 0.88(0.57~1.35) 0.353 0.553 1.13(0.73~1.74) 0.278 0.598 1.02(0.66~1.58) 0.008 0.928 T3 1.00(0.64~1.57) 0.001 0.989 0.88(0.58~1.36) 0.316 0.574 1.05(0.68~1.64) 0.053 0.817 1.08(0.70~1.67) 0.116 0.738 牛奶 低 1.00 1.00 1.00 1.00 高 1.06(0.74~1.51) 0.101 0.751 1.30(0.91~1.85) 2.146 0.143 1.13(0.79~1.62) 0.463 0.496 1.29(0.90~1.85) 1.973 0.160 酸奶 低 1.00 1.00 1.00 1.00 高 1.36(0.92~2.02) 2.383 0.123 1.41(0.96~2.08) 3.089 0.078 1.21(0.81~1.79) 0.860 0.354 1.26(0.85~1.86) 1.284 0.257 蛋类 T1 1.00 1.00 1.00 1.00 T2 1.27(0.79~2.06) 0.923 0.337 1.22(0.76~1.97) 0.695 0.404 0.92(0.58~1.46) 0.121 0.728 1.15(0.72~1.85) 0.351 0.554 T3 1.60(1.03~2.49) 4.451 0.035 1.51(0.98~2.33) 3.566 0.059 0.88(0.58~1.35) 0.331 0.565 1.21(0.78~1.86) 0.736 0.391 注:T1、T2、T3分别为食物摄入量最低三分位数组、中间三分位数组和最高三分位数组。 表 3 肠道菌群高α多样性多因素logistic回归分析
Table 3. Multiple logistic regression analysis for gut microbiota high α diversity
特征 高Shannon指数 高Simpson指数 高Chao1指数 高观察菌种数 OR (95% CI)值 Wald值 P值 OR (95% CI)值 Wald值 P值 OR (95% CI)值 Wald值 P值 OR (95% CI)值 Wald值 P值 性别 男 1.00 1.00 1.00 1.00 女 0.71(0.48~1.05) 2.478 0.116 0.68(0.46~0.99) 4.833 0.028 1.06(0.72~1.55) 0.130 0.718 1.22(0.85~1.76) 1.182 0.276 精制谷物 T1 1.00 1.00 1.00 1.00 T2 0.56(0.36~0.88) 6.215 0.013 0.85(0.55~1.32) 0.522 0.470 0.53(0.34~0.84) 7.200 0.007 0.67(0.43~1.07) 2.840 0.092 T3 0.57(0.36~0.89) 6.058 0.014 0.62(0.40~0.98) 4.259 0.039 0.86(0.56~1.32) 0.471 0.492 1.07(0.70~1.65) 0.106 0.744 酸菜泡菜 < 1次/周 1.00 1.00 1.00 1.00 ≥1次/周 0.47(0.27~0.81) 7.424 0.006 0.50(0.29~0.84) 6.836 0.009 0.98(0.62~1.55) 0.011 0.916 0.81(0.50~1.30) 0.786 0.375 水果 T1 1.00 1.00 1.00 1.00 T2 1.63(1.01~2.65) 3.869 0.048 1.98(1.23~3.22) 7.807 0.005 1.03(0.65~1.61) 0.011 0.917 1.32(0.83~2.10) 1.398 0.237 T3 1.86(1.15~3.02) 6.406 0.011 2.01(1.24~3.25) 8.113 0.004 1.03(0.65~1.63) 0.011 0.917 1.27(0.79~2.03) 1.003 0.316 蛋类 T1 1.00 1.00 1.00 1.00 T2 1.19(0.71~1.98) 0.440 0.507 1.12(0.68~1.84) 0.185 0.667 0.89(0.55~1.45) 0.210 0.647 1.06(0.65~1.74) 0.061 0.806 T3 1.55(0.98~2.46) 3.478 0.062 1.38(0.88~2.16) 1.961 0.161 0.96(0.62~1.49) 0.038 0.846 1.25(0.80~1.96) 0.964 0.326 注:T1、T2、T3分别为食物摄入量最低三分位数组、中间三分位数组和最高三分位数组。 -
[1] Agustí A, García-Pardo MP, López-Almela I, et al. Interplay between the gut-brain axis, obesity and cognitive function[J]. Front. Neurosci, 2018, 12: 155. DOI: 10.3389/fnins.2018.00155. [2] 周起, 孙亮, 齐海梅, 等. 肠道菌群与老龄健康的研究进展[J]. 中华老年医学杂志, 2018, 37 (12): 1428-1432. DOI: 10.3760/cma.j.issn.0254-9026.2018.12.033.Zhou Q, Sun L, Qi HH, et al. Relationship between gut microbiota and healthy aging: Research process and future prospective[J]. Chin J Geriatr, 2018, 37(12): 1428-1432. DOI: 10.3760/cma.j.issn.0254-9026.2018.12.033. [3] Shuai M, Zuo LS, Miao Z, et al. Multi-omics analyses reveal relationships among dairy consumption, gut microbiota and cardiometabolic health[J]. EBioMedicine, 2021, 66: 103284. DOI: 10.1016/j.ebiom.2021.103284. [4] Yu D, Nguyen SM, Yang Y, et al. Long-term diet quality is associated with gut microbiome diversity and composition among urban Chinese adults[J]. Am J Clin Nutr, 2021, 113(3): 684-694. DOI: 10.1093/ajcn/nqaa350. [5] Jiang Z, Sun TY, He Y, et al. Dietary fruit and vegetable intake, gut microbiota, and type 2 diabetes: results from two large human cohort studies. [J]. BMC Med, 2020, 18(1): 371. DOI: 10.1186/s12916-020-01842-0. [6] Wang Y, Yu M, Shi Y, et al. Effects of a fermented beverage of Changbai mountain fruit and vegetables on the composition of gut microbiota in mice[J]. Plant Foods Hum Nutr, 2019, 74(4): 468-473. DOI: 10.1007/s11130-019-00761-7. [7] Sugimoto T, Shima T, Amamoto R, et al. Impacts of habitual diets intake on gut microbial counts in healthy Japanese adults[J]. Nutrients, 2020, 12(8): 2414. DOI: 10.3390/nu12082414. [8] Kim YS, Unno T, Kim BY, et al. Sex differences in gut microbiota[J]. World J Mens Health, 2020, 38(1): 48-60. DOI: 10.5534/wjmh.190009. [9] Le Roy CI, Wells PM, Si J, et al. Red wine consumption associated with increased gut microbiota α-diversity in 3 independent cohorts[J]. Gastroenterology, 2020, 158(1): 270-272. e2. DOI: 10.1053/j.gastro.2019.08.024. [10] Zhong F, Wen X, Yang M, et al. Effect of an 8-week exercise training on gut microbiota in physically inactive older women[J]. Int J Sports Med. 2021, 42(7): 610-623. DOI: 10.1055/a-1301-7011.