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1.
Zhonghua Yu Fang Yi Xue Za Zhi ; (12): 641-648, 2023.
Artigo em Chinês | WPRIM | ID: wpr-985456

RESUMO

Objective: To investigate the association of mixed exposure to greenness and nitrogen dioxide(NO2) and hypertension among the older adults aged 65 years and over in China. Methods: The study subjects were from the Chinese Longitudinal Healthy Longevity Survey from 2017 to 2018. A total of 15 423 older adults aged 65 years and over meeting the criteria were finally included in the study. A questionnaire survey was used to collect information on demographic characteristics, lifestyle habits and self-reported prevalence of hypertension. Blood pressure values were obtained through physical examination. The level of normalized difference vegetation index(NDVI) was measured by the Medium-resolution Imaging Spectral Radiator(MODIS) of the National Aeronautics and Space Administration(NASA). The concentration of NO2 was from China's surface air pollutant data set. Meteorological data was from NASA MERRA-2. The exposure to NDVI and NO2 for each study subject was calculated based on the area within a 1 km radius around their residence. The association between mixed exposure of NDVI and NO2 as well as their interaction and hypertension in older adults was analyzed by using the multivariate logistic regression model. The restrictive cubic spline(RCS) function was used to explore the exposure-response relationship between greenness and NO2 and the risk of hypertension in study subjects. Results: The mean age of 15 423 older adults were (85.6±11.6). Women accounted for 56.3%(8 685/15 423) and 55.6%(8 578/15 423) lived in urban areas. The mean time of residence was (60.9±28.5) years. 59.8% of participants were with hypertension. The mean NDVI level was 0.41±0.13, and the mean NO2 concentration was (32.18±10.36) μg/cm3. The results of multivariate logistic regression analysis showed that NDVI was inversely and linearly associated with the hypertension in older adults, with the OR(95%CI) value of 0.959(0.928-0.992). Compared with the T1 group of NDVI, the risk of hypertension was lower in the T3 group, with the OR(95%CI) value of 0.852(0.769-0.944), and the trend test was statistically significant(P<0.05). Compared with the T1 group of NO2, the risk of hypertension was higher in the T2 and T3 groups, with OR(95%CI) values of 1.160(1.055-1.275) and 1.244(1.111-1.393), and the trend test was statistically significant (P<0.05). The result of the RCS showed that NDVI was inversely and linearly associated with hypertension in older adults. NO2 was nonlinearly associated with hypertension in older adults. The interaction analysis showed that NDVI and NO2 had a negative multiplicative interaction on the risk of hypertension, with OR(95%CI) value of 0.995(0.992-0.997). Conclusion: Exposure to greenness and NO2 are associated with hypertension in older adults.


Assuntos
Idoso , Humanos , Feminino , Dióxido de Nitrogênio , Poluição do Ar , Prevalência , Hipertensão/epidemiologia , China/epidemiologia , Material Particulado/análise
2.
Chinese Journal of Epidemiology ; (12): 855-861, 2023.
Artigo em Chinês | WPRIM | ID: wpr-985604

RESUMO

Objective: To investigate body mass index (BMI) level, identify the main type of nutritional problem, and describe the population distribution characteristics of BMI among Chinese people aged 80 years or above. Methods: The data of 9 481 oldest-old individuals were obtained from the 2017-2018 Chinese Longitudinal Healthy Longevity Survey. The Lambda-Mu-Sigma method, weighted estimates of BMI, and comparisons by BMI quintiles were used to describe the BMI level and distribution characteristics among the oldest-old. Results: The average age of the participants was (91.9±7.7) years, with P50 of the weighted BMI at 21.9 (95%CI: 21.8-22.0) kg/m2. The result of BMI level showed a decreasing trend with age, with a rapid decline before age 100, and then the trend became slower. There are about 30% of the oldest-old classified as undernutrition, but the prevalence of overnutrition is only about 10%. The population distribution characteristics by BMI quintiles showed the oldest-old with lower BMI levels were likely to have the following characteristics: sociodemographically, to be older, female, ethnic minority, unmarried/divorced/widowed, rural residents, illiterate, with inadequate living expenses, located in Central, South, or Southwest China; regarding lifestyles, lower BMI levels were observed for participants who were smoking, not exercising, lack of leisure activities, or with poor dietary diversity; considering functional status, participants with lower BMI levels were those who have poor chewing ability, disability in activities of daily living, cognitive impairment, hearing loss, visual impairment, or poor self-rated health status. The oldest-old with higher BMI levels were likely to have heart disease, hypertension, cerebrovascular disease, and diabetes. Conclusions: The overall BMI level was low among the Chinese oldest-old and it showed a downward trend with age. Currently, the main nutritional problem among the Chinese oldest-old was undernutrition rather than overweight or obesity. Management of healthy lifestyles, functional status, and diseases would be helpful to reduce the risk of undernutrition among the oldest-old.


Assuntos
Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Atividades Cotidianas , Índice de Massa Corporal , População do Leste Asiático , Etnicidade , Desnutrição , Grupos Minoritários , Centenários , Nonagenários
3.
Artigo em Chinês | WPRIM | ID: wpr-969890

RESUMO

Objective: To examine the association of greenness exposure with waist circumference (WC) and central obesity in older adults in China. Methods: Based on the cross-sectional data from the Chinese Longitudinal Healthy Longevity Survey in 2017-2018, 14 056 participants aged 65 years and over were included. Demographic characteristics, lifestyle, WC, and other information were collected through a questionnaire and physical examination. Based on the satellite monitoring data of moderate-resolution imaging spectroradiometer (MODIS) provided by NASA, the annual mean of normalized difference vegetation index (NDVI) within a radius of 1 000 meters was obtained as the measurement value of greenness exposure. Multivariate linear regression model, multivariate logistic regression model, and restricted cubic splines (RCS) model were used to analyze the association and dose-response relationship between greenness exposure and WC and central obesity in older adults in China. Results: A total of 14 056 participants were enrolled with a median age of 84.0 years [IQR: 75.0-94.0 years]. About 45.0% (6 330) of them were male and 48.6% (5 853) were illiterate. There were 10 964 (78.0%) participants from rural. The mean of WC was (84.4±10.8) cm. Central obesity accounted for 60.2% (8 465), and the NDVI range was (-0.06, 0.78). After adjusting for confounding factors, the multivariate linear regression model showed that the change value of WC in the urban group [β (95%CI):-0.49 (-0.93, -0.06)] was smaller than that in the rural [-0.78 (-0.98, -0.58)] for every 0.1 unit increase in NDVI (Pinteraction=0.022). Compared with the Q1 group in NDVI, WC of Q2 and Q3 groups in rural decreased, and the β (95%CI) values were-1.74 (-2.5, -0.98) and-2.78 (-3.55, -2.00), respectively. The multivariate logistic regression model showed that after adjusting for confounding factors, the risk of central obesity decreased for urban and rural older adults with an increase of 0.1 unit in NDVI, and the OR (95%CI) values were 0.87 (0.80, 0.95) and 0.86 (0.82, 0.89), respectively (Pinteraction=0.284). Compared with the Q1 group in NDVI, the risk of central obesity in the Q2 and Q3 groups in rural was lower, and the OR (95%CI) values were 0.68 (0.58, 0.80) and 0.57 (0.49, 0.68), respectively. The results of the multivariate regression model with RCS showed that there was a non-linear association of NDVI with WC (Pnonlinear=0.006) and central obesity (Pnonlinear=0.025). Conclusion: Greenness exposure is negatively associated with WC and central obesity in older adults in China.

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