Analysis of the Status of Agricultural Communities and Location Quotient (LQ) using Regional Survey Data in 2015 Census of Agriculture, Forestry, and Fisheries

이, 지민

doi:10.7851/ksrp.2020.26.2.083

Cited by 2 publications

(1 citation statement)

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“…Considering the overall population distribution of Jeju province in which 73.4% resides in Jeju city and 26.6% in Seogwipo city [14], the higher proportion of Seogwipo residence in this study may have contributed to the greater proportion of the elderly and the agricultural workers. Data of Korean National Statistics demonstrated high proportion of elderly and agricultural households in Seogwipo city [15].…”

Section: Discussionmentioning

confidence: 97%

Establishment of a qualified integrated care system after total knee arthroplasty as a role of regional rheumatoid and degenerative arthritis centers

et al. 2022

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Background The geriatric population and advanced knee osteoarthritis are rapidly increasing in Korea, and the socioeconomic burden of total knee arthroplasty (TKA) is increasing. This study aimed to analyze the demographic, clinical and socioeconomic characteristics of patients who underwent TKA and to differentiate the factors affecting participation in inpatient-intensive rehabilitation programs after TKA in the Jeju regional rheumatoid and degenerative arthritis center established by the government. Methods This retrospective cohort study included 845 patients (735 females; 72.0 ± 5.8 years) diagnosed with primary osteoarthritis (OA) of the knee who underwent elective unilateral primary TKA between January 2013 and June 2016. Demographic, clinical, and socioeconomic characteristics, including age, body mass index, obesity, length of stay, OA severity, underlying disease, education level, occupation, and location of residence were reviewed. Patients were allocated to the TKA-only group (home discharge) and to the TKA + rehab group (participation in post-TKA rehabilitation). The variables were analyzed and compared before and after the establishment of the center and according to participation in intensive rehabilitation. Results Patients who underwent TKA were mostly female, in the 60 s, and had a high prevalence of comorbidities and obesity. After the rehabilitation center's establishment, the intensive post-TKA participation increased profoundly from 3% to 59.2%. Participants after the center establishment had lower mean BMI and a higher proportion of K-L grade 4 compared to those before the center establishment. The location of residence was the only factor differentiating the participation in the intensive rehabilitation. Conclusion The regional rheumatoid and degenerative arthritis center was appropriate to satisfy the high unmet need for participating in the intensive rehabilitation after TKA and to execute the qualified integrated post-TKA care system. Policy support should ensure the early rehabilitation and a qualified integrated care system and prepare for the increased burden of revision. Future longitudinal studies should be conducted to assess the long-term effect of the integrated post-TKA rehabilitation program on functional outcomes and patient survivorship free from revision.

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Section: Discussionmentioning

confidence: 97%

Establishment of a qualified integrated care system after total knee arthroplasty as a role of regional rheumatoid and degenerative arthritis centers

et al. 2022

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Analysis of Factors Influencing Forest Loss in South Korea: Statistical Models and Machine-Learning Model

Jeongmook

Lim

Lee

2021

Forests

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Analyzing the current status of forest loss and its causes is crucial for understanding and preparing for future forest changes and the spatial pattern of forest loss. We investigated spatial patterns of forest loss in South Korea and assessed the effects of various factors on forest loss based on spatial heterogeneity. We used the local Moran’s I to classify forest loss spatial patterns as high–high clusters, low–low clusters, high–low outliers, and high–low outliers. Additionally, to assess the effect of factors on forest loss, two statistical models (i.e., ordinary least squares regression (OLS) and geographically weighted regression (GWR) models) and one machine-learning model (i.e., random forest (RF) model) were used. The accuracy of each model was determined using the R2, RMSE, MAE, and AICc. Across South Korea, the forest loss rate was highest in the Seoul–Incheon–Gyeonggi region. Moreover, high–high spatial clusters were found in the Seoul–Incheon–Gyeonggi and Daejeon–Chungnam regions. Among the models, the GWR model was the most accurate. Notably, according to the GWR model, the main factors driving forest loss were road density, cropland area, number of households, and number of tertiary industry establishments. However, the factors driving forest loss had varying degrees of influence depending on the location. Therefore, our findings suggest that spatial heterogeneity should be considered when developing policies to reduce forest loss.

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Analysis of the Status of Agricultural Communities and Location Quotient (LQ) using Regional Survey Data in 2015 Census of Agriculture, Forestry, and Fisheries

Cited by 2 publications

References 0 publications

Establishment of a qualified integrated care system after total knee arthroplasty as a role of regional rheumatoid and degenerative arthritis centers

Establishment of a qualified integrated care system after total knee arthroplasty as a role of regional rheumatoid and degenerative arthritis centers

Analysis of Factors Influencing Forest Loss in South Korea: Statistical Models and Machine-Learning Model

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