scholarly journals Weather temperature and the incidence of hospitalization for cardiovascular diseases in an aging society

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kihei Yoneyama ◽  
Michikazu Nakai ◽  
Takumi Higuma ◽  
Kanako Teramoto ◽  
Mika Watanabe ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Regression Models ◽  
Primary Outcome ◽  
Limited Information ◽  
Older Individuals ◽  
Linear Regression Models ◽  
Temperature Changes ◽  
Patient Demographics ◽  
Aging Society ◽  
Incidence Of Hospitalization

AbstractWeather temperatures affect the incidence of cardiovascular diseases (CVD), but there is limited information on whether CVD hospitalizations are affected by changes in weather temperatures in a super-aging society. We aimed to examine the association of diurnal weather temperature changes with CVD hospitalizations. We included 1,067,171 consecutive patients who were admitted to acute-care hospitals in Japan between April 1, 2012 and March 31, 2015. The primary outcome was the number of CVD hospitalizations per day. The diurnal weather temperature range (DTR) was defined as the minimum weather temperature subtracted from the maximum weather temperature on the day before hospitalization. Multilevel mixed-effects linear regression models were used to estimate the association of DTR with cardiovascular hospitalizations after adjusting for weather, hospital, and patient demographics. An increased DTR was associated with a higher number of CVD hospitalizations (coefficient, 4.540 [4.310–4.765]/°C change, p < 0.001), with greater effects in those aged 75–89 (p < 0.001) and ≥ 90 years (p = 0.006) than among those aged ≤ 64 years; however, there were no sex-related differences (p = 0.166). Greater intraday weather temperature changes are associated with an increased number of CVD hospitalizations in the super-aging society of Japan, with a greater effect in older individuals.

scholarly journals Medication Intake Is Associated with Lower Plasma Carotenoids and Higher Fat-Soluble Vitamins in the Cross-Sectional MARK-AGE Study in Older Individuals

2020 ◽  
Vol 9 (7) ◽  
pp. 2072
Author(s):  
Daniela Weber ◽  
Bastian Kochlik ◽  
Wolfgang Stuetz ◽  
Martijn E. T. Dollé ◽  
Eugène H. J. M. Jansen ◽  
...  
Keyword(s):  
Regression Models ◽  
Plasma Concentrations ◽  
Older Individuals ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Medication Intake ◽  
The One ◽  
Fat Soluble Vitamins ◽  
The Impact ◽  
Β Carotene

The regular use of medication may interfere with micronutrient metabolism on several levels, such as absorption, turnover rate, and tissue distribution, and this might be amplified during aging. This study evaluates the impact of self-reported medication intake on plasma micronutrients in the MARK-AGE Project, a cross-sectional observational study in 2217 subjects (age- and sex-stratified) aged 35–75 years from six European countries that were grouped according to age. Polypharmacy as possible determinant of micronutrient concentrations was assessed using multiple linear regression models adjusted for age-group, dietary fruit, vegetables, and juice intake, and other confounders. Younger participants reported taking fewer drugs than older participants. Inverse associations between medication intake and lutein (−3.31% difference per increase in medication group), β-carotene (−11.44%), α-carotene (−8.50%) and positive associations with retinol (+2.26%), α-tocopherol/cholesterol (+2.89%) and γ-tocopherol/cholesterol (+1.36%) occurred in multiple adjusted regression models. Combined usage of a higher number of medical drugs was associated with poorer status of carotenoids on the one hand and higher plasma concentrations of retinol, α- and γ-tocopherol on the other hand. Our results raise concerns regarding the safety of drug combinations via the significant and surprisingly multifaceted disturbance of the concentrations of relevant micronutrients.

scholarly journals Childlessness, parenthood and subjective wellbeing: The relevance of conceptualizing parenthood and childlessness as a continuum.

2018 ◽  
Author(s):  
Marco Albertini ◽  
Bruno Arpino
Keyword(s):  
Life Satisfaction ◽  
Regression Models ◽  
Subjective Wellbeing ◽  
Later Life ◽  
Standard Errors ◽  
Intergenerational Solidarity ◽  
Older Individuals ◽  
Linear Regression Models ◽  
Number Of Children ◽  
The Continuum

The objective of the paper is to show the theoretical and practical relevance of conceptualizing and operationalizing parenthood and childlessness as a continuum – instead of a dichotomy - when evaluating the consequences of kinless-ness in later life. It is suggested that information on the number of children, structural and associational intergenerational solidarity can be utilized to operationalize the continuum. Subjective wellbeing is utilized as outcome of interest. Data from waves 2, 4, 5 and 6 of the Survey of Health, Ageing and Retirement in Europe are used. The sample includes 183,545 respondents from 21 countries. Linear regression models with clustered standard errors are used. Childless older individuals report lower levels of life satisfaction than parents. However, the largest difference is observed between those with one and two children. Using a measure of associational intergenerational solidarity to weight the degree of parenthood it is shown that parents who have infrequent contact with children report significantly lower levels of life satisfaction than childless individuals.Kinless-ness is not only a demographic but also a social condition. When studying the consequences of ageing alone it is essential to consider not only the presence and “quantity” of kin, but also its “quality”.

scholarly journals Critical Care Medical Centers May Play an Important Role in Reducing the Risk of COVID-19 Death in Japan

2020 ◽  
Vol 2 (11) ◽  
pp. 2147-2150
Author(s):  
Yohei Ishikawa ◽  
Toru Hifumi ◽  
Mitsuyoshi Urashima
Keyword(s):  
Critical Care ◽  
Regression Models ◽  
Primary Outcome ◽  
Simple Linear Regression ◽  
Linear Regression Models ◽  
Positive Ratio ◽  
Medical Centers ◽  
Number Of Patients ◽  
Polymerase Chain ◽  
Positive Results

AbstractMarked differences in COVID-19 mortalities have been observed among 47 prefectures in Japan. Here, we explored associations between COVID-19 mortalities and medical and public health capacities in individual prefectures. The following data by prefecture were abstracted from open resources provided by the Ministry of Health, Labour and Welfare in Japan as of May 24, 2020: total number of COVID-19 deaths; polymerase chain reaction (PCR)-positive ratio (i.e., number of patients with PCR-positive results/number of patients aiming diagnosis of COVID-19 or individuals in close contacted with COVID-19 patients); number of call centers, outpatient centers, and hospital beds specifically for patients diagnosed with COVID-19; and others. The primary outcome was COVID-19 mortality per million population. Multiple and simple linear regression models were applied. Two variables were significantly associated with COVID-19 mortality: PCR-positive ratio (P < 0.001) and number of critical care medical centers per million population (P = 0.001). PCR-positive ratio was positively associated with COVID-19 mortality (aR-sqr = 0.522). Low PCR-positive ratio, especially ≤ 4%, was associated with low COVID-19 mortality. Critical care medical centers may also play an important role in reducing the risk of COVID-19 death.

scholarly journals Effects of temperature and humidity on acute myocardial infarction hospitalization in a super-aging society

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Takumi Higuma ◽  
Kihei Yoneyama ◽  
Michikazu Nakai ◽  
Toshiki Kaihara ◽  
Yoko Sumita ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Primary Outcome ◽  
Weather Conditions ◽  
Linear Regression Models ◽  
Average Temperature ◽  
Aging Society ◽  
Temperature And Humidity ◽  
Effects Of Temperature ◽  
Spring Coefficient

AbstractWeather conditions affect the incidence of acute myocardial infarction (AMI). However, little is known on the association of weather temperature and humidity with AMI hospitalizations in a super-aging society. This study sought to examine this association. We included 87,911 consecutive patients with AMI admitted to Japanese acute-care hospitals between April 1, 2012 and March 31, 2015. The primary outcome was the number of AMI hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of the average temperature and humidity, 1 day before hospital admission, with AMI hospitalizations, after adjusting for weather, hospital, and patient demographics.Lower temperature and humidity were associated with an increased number of AMI hospitalizations (coefficient − 0.500 [− 0.524 to − 0.474] per °C change, p < 0.001 and coefficient − 0.012 [− 0.023 to − 0.001] per % change, p = 0.039, respectively). The effects of temperature and humidity on AMI hospitalization did not differ by age and sex (all interaction p > 0.05), but differed by season. However, higher temperatures in spring (coefficient 0.089 [0.025 to 0.152] per °C change, p = 0.010) and higher humidity in autumn (coefficient 0.144 [0.121 to 0.166] per % change, p < 0.001) were risk factors for AMI hospitalization. Increased average temperatures and humidity, 1 day before hospitalization, are associated with a decreased number of AMI hospitalizations.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

scholarly journals Anticipated help-seeking for cancer symptoms before and after the coronavirus pandemic: results from the Onco-barometer population survey in Spain

2021 ◽  
Author(s):  
Dafina Petrova ◽  
Marina Pollán ◽  
Miguel Rodriguez-Barranco ◽  
Dunia Garrido ◽  
Josep M. Borrás ◽  
...  
Keyword(s):  
Poisson Regression ◽  
Help Seeking ◽  
Regression Models ◽  
Population Survey ◽  
Waiting Times ◽  
Perceived Barriers ◽  
Older Individuals ◽  
Cancer Symptoms ◽  
Before And After ◽  
Diagnostic Delays

Abstract Background The patient interval—the time patients wait before consulting their physician after noticing cancer symptoms—contributes to diagnostic delays. We compared anticipated help-seeking times for cancer symptoms and perceived barriers to help-seeking before and after the coronavirus pandemic. Methods Two waves (pre-Coronavirus: February 2020, N = 3269; and post-Coronavirus: August 2020, N = 1500) of the Spanish Onco-barometer population survey were compared. The international ABC instrument was administered. Pre–post comparisons were performed using multiple logistic and Poisson regression models. Results There was a consistent and significant increase in anticipated times to help-seeking for 12 of 13 cancer symptoms, with the largest increases for breast changes (OR = 1.54, 95% CI 1.22–1–96) and unexplained bleeding (OR = 1.50, 1.26–1.79). Respondents were more likely to report barriers to help-seeking in the post wave, most notably worry about what the doctor may find (OR = 1.58, 1.35–1.84) and worry about wasting the doctor’s time (OR = 1.48, 1.25–1.74). Women and older individuals were the most affected. Conclusions Participants reported longer waiting times to help-seeking for cancer symptoms after the pandemic. There is an urgent need for public interventions encouraging people to consult their physicians with symptoms suggestive of cancer and counteracting the main barriers perceived during the pandemic situation.

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