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Objective: To analyze the short-term effect of individual atmospheric PM2.5 exposure on the diversity, enterotype, and community structure of gut microbiome in healthy elderly people in Jinan, Shandong province. Methods: The present panel study recruited 76 healthy elderly people aged 60-69 years old in Dianliu Street, Lixia District, Jinan, Shandong Province, and followed them up five times from September 2018 to January 2019. The relevant information was collected by questionnaire, physical examination, precise monitoring of individual PM2.5 exposure, fecal sample collection and gut microbiome 16S rDNA sequencing. The Dirichlet multinomial mixtures (DMM) model was used to analyze the enterotype. Linear mixed effect model and generalized linear mixed effect model were used to analyze the effect of PM2.5 exposure on gut microbiome α diversity indices (Shannon, Simpson, Chao1, and ACE indices), enterotype and abundance of core species. Results: Each of the 76 subjects participated in at least two follow-up visits, resulting in a total of 352 person-visits. The age of 76 subjects was (65.0±2.8) years old with BMI (25.0±2.4) kg/m2. There were 38 males accounting for 50% of the subjects. People with an educational level of primary school or below accounted for 10.5% of the 76 subjects, and those with secondary school and junior college or above accounting for 71.1% and 18.4%. The individual PM2.5 exposure concentration of 76 subjects during the study period was (58.7±53.7) μg/m3. DMM model showed that the subjects could be divided into four enterotypes, which were mainly driven by Bacteroides, Faecalibacterium, Lachnospiraceae, Prevotellaceae, and Ruminococcaceae. Linear mixed effects model showed that different lag periods of PM2.5 exposure were significantly associated with a lower gut α diversity index (FDR<0.05 after correction). Further analysis showed that PM2.5 exposure was significantly associated with changes in the abundances of Firmicutes (Megamonas, Blautia, Streptococcus, etc.) and Bacteroidetes (Alistipes) (FDR<0.05 after correction). Conclusion: Short-term PM2.5 exposure is significantly associated with a decrease in gut microbiome diversity and changes in the abundance of several species of Firmicutes and Bacteroidetes in the elderly. It is necessary to further explore the underlying mechanisms between PM2.5 exposure and the gut microbiome, so as to provide a scientific basis for promoting the intestinal health of the elderly.
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Anciano , Humanos , Masculino , Persona de Mediana Edad , Femenino , Heces/microbiología , Microbioma Gastrointestinal , Material Particulado , ARN Ribosómico 16S/genéticaRESUMEN
To understand the current status of BMI of the elderly and related factors in longevity areas in China, and provide scientific evidence for the control of BMI level in elderly population. Data used in this study were obtained from Healthy Aging and Biomarkers Cohort Study, a sub-cohort of the Chinese Longitudinal Healthy Longevity Survey. A total of 2 825 elderly in 8 longevity areas in China were surveyed and measured in 2017. The BMI levels of 2 217 elderly aged 65 years and older were calculated and in follow up. The ordered classification logistic regression model was used to analyze the influencd factors for the BMI in the elderly. The BMI of the elderly in 8 longevity areas in China was (22.36±3.87) kg/m(2), and it was (22.76±3.58) kg/m(2) for males and (21.75±3.98) kg/m(2) for females. The BMI levels were normal in 1 165 elderly persons. The prevalence of underweight, overweight and obesity were 15.8, 24.0 and 7.7, respectively. Multivariate analysis showed that the main factors affecting the BMI of people under 100- years old were age (65-: =2.78, 95: 1.87-4.15; 80-: =1.47, 95: 1.00-2.17), smoking status (=0.46, 95: 0.32-0.66), annual household income (<30 000 Yuan: =1.26, 95: 1.07-1.47; 30 000-70 000 Yuan: =1.52, 95: 1.12-1.86), and frequency of tea intake(=1.36, 95: 1.01-1.71), while the factor in people aged ≥100 years was gender (=3.68, 95: 1.32-10.36). The prevalence of underweight, overweight and obesity were high in the elderly from longevity areas in China. It is necessary to pay attention to the trend of overweight and obesity due to smoking, higher annual household income and regular tea drinking in the elderly men.
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To investigate the relationship of sleep duration and sleep quality with anxiety in the elderly aged 60 years and older in China. The elderly aged 60 years and older were selected from the China Short-term Health Effects of Air Pollution Study conducted between July 18, 2017 and February 7, 2018. Multivariate logistic regression models were used to analyze the association of sleep duration and sleep quality with anxiety. A total of 3 897 elderly aged 60 years and older were included in the study. The age of the elderly was (73.4±8.0) years old. Among the elderly surveyed, 6.5 were defined with anxiety, and 18.7 reported poor sleep quality. Multivariate logistic regression models showed shorter sleep duration was the risk factor for anxiety in the elderly that after adjusting for factors such as general demographics, socioeconomic factors, lifestyle, health status, social support and ambient fine particulates exposure. Compared with the elderly with 7 hours of sleep duration daily, the (95) of anxiety for those with sleep duration ≤ 6 hours was 2.09 (1.49-2.93). Compared with those with good sleep quality, the (95) of anxiety for those with poor sleep quality was 5.12 (3.88-6.77). We also found statistically significant correlations of the scores of subscales of Pittsburgh sleep quality index with anxiety, in which the effects of sleep disturbance, subjective sleep quality and daytime dysfunction scores were most obvious, the (95) were 4.63 (3.55-6.04), 2.75 (2.33-3.23) and 2.50 (2.19-2.86), respectively. Subgroup analysis showed that the association of sleep duration and sleep quality with anxiety was more obvious in males and in those aged <80 years. Shorter sleep duration and poor sleep quality are associated with anxiety in the elderly in China.
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To establish a prediction model for 6-year incidence risk of chronic kidney disease (CKD) in the elderly aged 65 years and older in China. In this prospective cohort study, we used the data of 3 742 participants collected during 2008/2009-2014 and during 2012-2017/2018 from Healthy Aging and Biomarkers Cohort Study, a sub-cohort of the Chinese Longitudinal Healthy Longevity Survey. Two follow up surveys for renal function were successfully conducted for 1 055 participants without CKD in baseline survey. Lasso method was used for the selection of risk factors. The risk prediction model of CKD was established by using Cox proportional hazards regression models and visualized through nomogram tool. Bootstrap method (1 000 resample) was used for internal validation, and the performance of the model was assessed by C-index and calibration curve. The mean age of participants was (80.8±11.4) years. In 4 797 person years of follow up, CKD was found in 262 participants (24.8). Age, BMI, sex, education level, marital status, having retirement pension or insurance, hypertension prevalence, blood uric acid, blood urea nitrogen and total cholesterol levels and estimated glomerular filtration rate in baseline survey were used in the model to predict the 6-year incidence risk of CKD in the elderly. The corrected C-index was 0.766, the calibration curve showed good consistence between predicted probability and observed probability in high risk group, but relatively poor consistence in low risk group. The incidence risk prediction model of CKD established in this study has a good performance, and the nomogram can be used as visualization tool to predict the 6-year risk of CKD in the elderly aged 65 years and older in China.
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To investigate the association between estimated glomerular filtration rate (eGFR) and all-cause mortality in the elderly aged 65 years and older in longevity areas in China. Data used in this study were obtained from Healthy Aging and Biomarkers Cohort Study, a sub-cohort of the Chinese Longitudinal Healthy Longevity Survey, 1 802 elderly adults were collected in the study during 2012-2017/2018. In this study, the elderly were classified into 4 groups, moderate-to-severe group [<45 ml·min(-1)·(1.73 m(2))(-1)], mild-to-moderate group [45- ml·min(-1)·(1.73 m(2))(-1)], mild group [60- ml·min(-1)·(1.73 m(2))(-1)] and normal group [≥90 ml·min(-1)·(1.73 m(2))(-1)] according to their eGFR levels. After 6 years of follow-up, 852 participants died, with a mortality rate of 47.3. Multivariate Cox regression analysis showed that the levels of eGFR were negatively correlated with all-cause mortality risk in the elderly (the of elderly was 0.993 and the 95 was 0.989-0.997 for every unit of eGFR increased, =0.001), while compared with the group with normal eGFR, the (95) of the elderly in the moderate-to-severe group, mild-to-moderate group, and mild group were 1.690 (1.224-2.332, =0.001), 1.312 (0.978-1.758, =0.070), 1.349 (1.047-1.737, =0.020) respectively [trend test <0.001]. The decrease in eGFR was associated with higher mortality risk among the elderly in longevity areas in China.
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To understand the relationship between visual impairment and risk of all-cause mortality in the elderly aged 65 years and older in 8 longevity areas in China. The data of the elderly aged 65 years and older in the project in 2012 were obtained from Healthy Aging and Biomarkers Cohort Study, a sub-cohort of the Chinese Longitudinal Healthy Longevity Survey, including physical measurement and survival status, and a follow-up for survival outcomes were conducted in 2014 and 2017 respectively. Cox proportional hazard regression model was used to analyze the influence of visual impairment on mortality. Gender and age specific analysis was conducted. A total of 1 736 elderly adults were included. A total of 943 deaths occurred during the 5-year follow-up period with a 5-year mortality rate of 54.3. The 5-year mortality rate was 76.7 in the group with visual impairment, and 47.6 in the group without visual impairment (<0.001). After adjusting for demographic information, life style and some disease factors, the risk of 5-year mortality in the group with visual impairment group was 1.30 times higher than that in the group without visual impairment (=1.30, 95: 1.09-1.55). In the females, the risk for mortality in the group with visual impairment was 1.48 times higher than that in the group without visual impairment (=1.48, 95:1.20-1.84). However, vision status was not associated with the risk for mortality in males (=1.02, 95: 0.72-1.43). The risk for mortality in the group with visual impairment was 1.39 times higher than that in the group without visual impairment in the elderly aged over 90 years (=1.39, 95: 1.13-1.70). Vision status was not associated with mortality risk in the elderly aged 65-79 years and 80-89 years (=1.37, 95: 0.61-3.07; =0.95, 95: 0.61-1.48). In the elderly people in China, visual impairment is a risk factor for mortality.
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To analyze influencing factors for depressive symptoms in the elderly aged 65 years and older in 8 longevity areas in China. We recruited 2 180 participants aged 65 years and older in 8 longevity areas from Healthy Aging and Biomarkers Cohort Study, a sub-cohort of the Chinese Longitudinal Healthy Longevity Survey in 2017. Multivariate logistic regression analysis was performed to evaluate the relationships of socio-demographic characteristics, behavioral lifestyle, chronic disease prevalence, functional status, family and social support with depressive symptoms in the elderly. The detection rate of depression symptoms was 15.0 in the elderly aged 65 years and older in 8 longevity areas of China, and the detection rate of depression symptoms was 11.5 in men and 18.5 in women. Multivariate logistic regression analysis results showed that the detection rate of depressive symptoms was lower in the elderly who had regular physical exercises (=0.44, 95: 0.26-0.74), frequent fish intakes (=0.57, 95: 0.39-0.83), recreational activities (=0.65, 95: 0.44-0.96), social activities (=0.28, 95: 0.11-0.73) and community services (=0.68, 95: 0.50-0.93). The elderly who were lack of sleep (=2.04, 95: 1.49-2.80), had visual impairment (=1.54, 95: 1.08-2.18), had gastrointestinal ulcer (=2.97, 95: 1.53-5.77), had arthritis (=2.63, 95: 1.61-4.32), had higher family expenditure than income (=1.80, 95: 1.17-2.78) and were in poor economic condition (=4.58, 95: 2.48-8.47) had higher detection rate of depressive symptoms. The status of doing physical exercise, fish intake in diet, social activity participation, sleep quality or vision, and the prevalence of gastrointestinal ulcers and arthritis were associated with the detection rate of depressive symptoms in the elderly.