Evidence for an alternation strategy in a daily time-place task

This study aimed to examine the daily time use by activity and identified factors related to health management time (HMT) use among 195 older adults (mean age = 77.5, SD = 6.28 years; 70.8% women) attending a Korean senior center. Descriptive statistics were analyzed and gamma regression analyses were performed. Participants used the most time on rest, followed by leisure, health management, daily living activities, and work. The mean duration of HMT was 205.38 min/day. The mean score for the subjective evaluation of health management (SEHM) was 13.62 and the importance score for SEHM was 4.72. Factors influencing HMT included exercise, number of chronic conditions, fasting blood sugar level, low density lipoprotein level, and cognitive function. HMT and frailty significantly predicted SEHM. HMT interventions focus on promoting exercise and acquiring health information to improve health outcomes among older adults in senior centers.

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Assessing Early Heterogeneity in Doubling Times of the COVID-19 Epidemic across Prefectures in Mainland China, January–February, 2020

Epidemiologia ◽

10.3390/epidemiologia2010009 ◽

2021 ◽

Vol 2 (1) ◽

pp. 95-113 ◽

Cited By ~ 1

Author(s):

Isaac Chun-Hai Fung ◽

Xiaolu Zhou ◽

Chi-Ngai Cheung ◽

Sylvia K. Ofori ◽

Kamalich Muniz-Rodriguez ◽

...

Keyword(s):

Regression Models ◽

Doubling Time ◽

Metropolitan Areas ◽

Mainland China ◽

Linear Regression Models ◽

Case Count ◽

Daily Time Series ◽

The Mean ◽

Doubling Times ◽

Daily Time

To describe the geographical heterogeneity of COVID-19 across prefectures in mainland China, we estimated doubling times from daily time series of the cumulative case count between 24 January and 24 February 2020. We analyzed the prefecture-level COVID-19 case burden using linear regression models and used the local Moran’s I to test for spatial autocorrelation and clustering. Four hundred prefectures (~98% population) had at least one COVID-19 case and 39 prefectures had zero cases by 24 February 2020. Excluding Wuhan and those prefectures where there was only one case or none, 76 (17.3% of 439) prefectures had an arithmetic mean of the epidemic doubling time <2 d. Low-population prefectures had a higher per capita cumulative incidence than high-population prefectures during the study period. An increase in population size was associated with a very small reduction in the mean doubling time (−0.012, 95% CI, −0.017, −0.006) where the cumulative case count doubled ≥3 times. Spatial analysis revealed high case count clusters in Hubei and Heilongjiang and fast epidemic growth in several metropolitan areas by mid-February 2020. Prefectures in Hubei and neighboring provinces and several metropolitan areas in coastal and northeastern China experienced rapid growth with cumulative case count doubling multiple times with a small mean doubling time.

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