scholarly journals 447 - Risk factors associated with sleep disturbance in a general elderly Japanese population: The Arao Cohort Study

2020 ◽  
Vol 32 (S1) ◽  
pp. 167-167
Author(s):  
Kazuki Honda ◽  
Tomohisa Ishikawa ◽  
Ryuji Fukuhara ◽  
Seiji Yuki ◽  
Yusuke Miyagawa ◽  
...  

[Background]Sleep disturbance is a common symptom in elderly people. However, the associated risk factors have not been completely clarified. We examined possible risk factors associated with sleep disturbance in a community-based Japanese cohort study.[Methods]1521 community-dwelling individuals aged 65 years or older were selected from a consecutive series at a cohort study from 2016 to 2018 in Arao city, where located at south part of Japan. In this survey, the clinical valuables were collected as follows: age, sex, occupational status, education, lifestyle information, medical history, EuroQoL(EQ)-5D (a score of health-related quality of life [QOL]), Barthel index (a score of performance in activities of daily living), a score of Geriatric Depression Scale (GDS) and a score of Mini-Mental State Examination (MMSE). Sleep disturbance was assessed by the Pittsburgh Sleep Quality Index (when the global score was 6 or over, sleep disturbance was determined to be present). Multiple logistic regression analysis was used to examine the association between clinical valuables and sleep disturbance. This research was supported by AMED (Japan Agency for Medical Research and Development) under Grant Number JP18dk0207025h0003 and has been approved by the research ethics committee of Kumamoto University. Informed consent was obtained from all participants and their family members.[Results]Multiple logistic regression analysis revealed that Parkinson disease (Odds ratio[OR]=5.59), living alone (OR=1.93), liver disease (OR=1.89), hyperlipidemia (OR=1.36), higher score of GDS (OR=1.14), lower scores of both EQ-5D index (OR=1.11) and Barthel index (OR=1.03) were significantly associated as risk factors with sleep disturbance. Unexpectedly, lower score of MMSE was not a significant risk factor.[Conclusion]These results suggest that several physical illnesses, solitude, depressive symptoms and lower QOL, but not cognitive impairment, might be crucial risk factors associated with sleep disturbance in elderly population.

2020 ◽  
Vol 27 (5) ◽  
pp. 130-140
Author(s):  
Asraf Ahmad Qamruddin ◽  
Reza Qamruddin ◽  
Ayu Malik

Objectives: To determine the incidence rate of measles and the factors associated with confirmed measles cases in Larut, Matang and Selama districts. Methods: Cross-sectional analysis was carried out looking at all suspected and laboratoryconfirmed measles cases in Larut, Matang and Selama districts between 2015 and 2019. Multiple logistic regression analysis was used to determine the associated factors for laboratory-confirmed measles cases. Results: The incidence rate for suspected measles showed an increasing trend from 2015–2019. For laboratory-confirmed measles cases, the incidence rate showed more variation with an increase to 36.11 per million population in 2017 from 5.67 per million population in 2015. The incidence rate later decreased to 10.99 per million population in 2018 and increased again to 24.47 per million population in 2019. From multiple logistic regression analysis, cases that fulfilled the case definition of measles were more likely to be laboratory-confirmed measles. On the other hand, a prior history of measles immunisation was a protective factor. Conclusion: Measles incidence is increasing in trend. Any suspected measles cases that fulfilled the clinical case definitions need to be further investigated. Immunisation should be promoted as they are effective in preventing and eliminating measles.


2019 ◽  
Vol 24 (S1) ◽  
pp. 39-47 ◽  
Author(s):  
Shyam Sundar Budhathoki ◽  
Amit Bhandari ◽  
Rejina Gurung ◽  
Abhishek Gurung ◽  
Ashish KC

Abstract Introduction The nutritional status in the first 5 years of life has lifelong and inter-generational impacts on individual’s potential and development. This study described the trend of stunting and its risk factors in children under 5 years of age between 2001 and 2016 in Nepal. Methods The study used datasets from the 2001, 2006, 2011 and 2016 Nepal Demographic Health Surveys to describe the trend of stunting in under 5-year children. Multiple logistic regression analysis was carried out to assess the risk factors for stunting at the time of the four surveys. Results The nutritional status of under 5-year children improved between 2001 and 2016. Babies born into poorer families had a higher risk of stunting than those born into wealthier families (AOR 1.51, CI 95% 1.23–1.87). Families residing in hill districts had less risk of stunting than those in the Terai plains (AOR 0.75, CI 95% 0.61–0.94). Babies born to uneducated women had a higher risk of stunting than those born to educated women (AOR 1.57, CI 95% 1.28–1.92). Discussion Stunting among under-5-year children decreased in the years spanning 2001–2016. This study demonstrated multiple factors that can be addressed to decrease the risk of stunting, which has important implications for neurodevelopment later in life. We add literature on risk factors for stunting in under-5-year children.


2021 ◽  
Vol 5 (1) ◽  
pp. 29
Author(s):  
Eka Suci Wulandari ◽  
Ernawati Ernawati ◽  
Djohar Nuswantoro

 Abstract.Background : The maternal mortality rate in Indonesia is dominated by preeclampsia as the second highest cause after bleeding. Several predictors can be categorized as risk factors that can be used to increase alertness in the care of pregnant women with severe preeclampsia to avoid complications. The purpose of this study was to study the relationship between risk factors for severe preeclampsia and its complications. Methods: This study used an observational analytic method with a case control design. The sampling technique is simple random sampling. The number of samples in this study were 80 samples, with 40 samples in each group. The case group was severe preeclampsia with one complication and the control group was severe preeclampsia without complications. Statistical analysis used was chi square and multiple logistic regression analysis. Results: The results showed that there was a significant relationship between age variables (p value = 0.001 < 0.05; OR = 5.318; CI = 2.118 – 13,356), BMI (p value = 0.002 < 0.05; OR = 6.000; CI = 1.958 – 18.384 ) and gestational age (p value = 0.039 < 0.05; OR = 2.636; CI = 1.040 – 6.685). Multiple logistic regression analysis showed that BMI (p = 0.003), age (p = 0.001) and gestational age (p = 0.048) were variables included in the final modeling of the regression analysis with the incidence of severe preeclampsia complications. Conclusion: BMI is the variable that has the strongest relationship with the incidence of severe preeclampsia complications.  


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