Informal caregivers in Germany - who are they and which risks and resources do they have?

Background

The aim of this study is to describe the social characteristics, the health and living situation and the prevalence of behavioral risk factors of adult informal caregivers compared to non-caregivers in Germany.

Methods

We used data from the German Health Update (GEDA 2019/2020-EHIS survey) which is a cross-sectional population-based health interview survey conducted between 04/2019 and 09/2020. The sample comprised 22,646 adults living in private households. Three mutually exclusive groups of providing informal care or assistance were differentiated: intense caregivers (informal care ≥10 h/week), less-intense caregivers (informal care<10 h/week) and non-caregivers. For the three groups weighted prevalences of social characteristics, health status (self-perceived health, health-related activity limitations, chronic diseases, low back disorder or other chronic back defect, depressive symptoms), behavioral risk factors (at-risk drinking, current smoking, insufficient physical activity, non-daily fruit and vegetable consumption, obesity) and social risk factors (single household, low social support) were calculated and stratified by gender. Separate regression analyses adjusted for age-group were conducted to identify significant differences between intense and less-intense caregivers vs. non-caregivers, respectively.

Results

Overall, 6.5% were intense caregivers, 15.2% less-intense caregivers and 78.3% non-caregivers. Women provided care more often (23.9%) than men (19.3%). Informal care was most frequently provided in the age group of 45 to 64 years. Intense caregivers reported worse health status, were more often current smokers, physical inactive, obese and lived less often alone than non-caregivers. However, in age-group adjusted regression analyses only few significant differences were seen: Female and male intense caregivers had more often a low back disorder and lived less often alone compared to non-caregivers. In addition, male intense care-givers reported more often worse self-perceived health, health-related activity limitation, and the presence of chronic diseases. In contrast, less-intense caregivers and non-caregivers differed in favor of the less-intense caregivers.

Discussion

A substantial proportion of the adult German population provides informal care regularly, especially women. Intense caregivers are a vulnerable group for negative health outcomes, especially men. In particular measures to prevent low back disorder should be provided. As the necessity of providing informal care will probably increase in the future, this will be important for the society and public health.

Survival study on deep learning techniques for IoT enabled smart healthcare system

Purpose

The paper is to study a review of the employment of deep learning (DL) techniques inside the healthcare sector, together with the highlight of the strength and shortcomings of existing methods together with several research ultimatums. Our study lays the foundation for healthcare professionals and government with present-day inclinations in DL-based data analytics for smart healthcare.

Methods

A deep learning-based technique is designed to extract sensor displacement effects and predict abnormalities for activity recognition via Artificial Intelligence (AI). The presented technique minimizes the vanishing gradient issue of Recurrent Neural Networks (RNN), thereby reducing the time for detecting abnormalities with consideration of temporal and spatial factors. Proposed Moran Autocorrelation and Regression-based Elman Recurrent Neural Network (MAR-ERNN) introduced.

Results

Experimental results show the feasibility of the proposed method. The results show that the proposed method improves accuracy by 95% and reduces execution time by 18%.

Conclusion

MAR-ERNN performs well in the activity recognition of health status. Collectively, this IoT-enabled smart healthcare system is utilized by enhancing accuracy, and minimizing time and overhead reduction.

Socioeconomic Correlates and Determinants of Cardiorespiratory Fitness in the General Adult Population: a Systematic Review and Meta-Analysis

BACKGROUND

This review aims to (1) consolidate evidence regarding the association between socioeconomic status (SES) and cardiorespiratory fitness (CRF), (2) conduct a meta-analysis of the association between SES and CRF using methodologically comparable data, stratified by sex, and (3) test whether the association varies after adjustment for physical activity (PA).

METHODS

A systematic review of studies from MEDLINE, EMBASE, Latin American and Caribbean Health Sciences (LILACS), Scientific Electronic Library Online (ScIELO), and Cochrane Library without time or language restrictions, which investigated associations between SES and CRF. Risk of bias within studies was assessed using a customized quality assessment tool. Results were summarized in table format and methodologically similar studies were synthesized using meta-analysis of Hedges' g effect sizes. Synthesized results were appraised for cross-study bias. Results were tested for the impact of PA adjustment using meta-regression.

RESULTS

Compared to individuals with low education, both men and women showed higher CRF among individuals with high education (men 0.12 [0.04-0.20], women 0.19 [0.02-0.36]), while participants with medium education showed no significant difference in CRF (men 0.03 [- 0.04-0.11], women 0.09 [- 0.03-0.21]). Adjustment for PA did not significantly impact the association between education and CRF.

CONCLUSIONS

There is fair evidence for an association between high levels of education and increased CRF. This could have implications for monitoring, of health target compliance and of chronic disease risk among higher risk populations, to detect and prevent non-communicable diseases (NCDs) and to diminish social health inequalities.

TRIAL REGISTRATION

PROSPERO, CRD42017055456.

Monitoring Daily Physical Conditions of Older Adults Using Acoustic Features: A Preliminary Result

Health monitoring in everyday situations has become important due to the rapid aging of many societies. Speech changes have been suggested as a means of measuring an individual's state, such as emotion and stress, and screening for neurodegenerative diseases. However, how speech features are associated with daily physical conditions remains unknown. In this study, we investigated whether acoustic features collected in everyday situations could be used for inferring the daily physical conditions of older adults. We analyzed speech data collected in two settings of monitoring the health of older adults: during phone calls with an actual service for regularly monitoring older adults and with a tablet-based monitoring system we developed. Through analyses, we suggest that acoustic features extracted from speech data in everyday situations may be used for detecting poor physical conditions.

Nurses views on accepting the creation of a nurses' health monitoring system

Background

Nurses’ health is often accompanied by various dangers due to the nature of their career. Therefore, it is required to monitor their health. Based on designing any system, users’ views should be investigated relative to the usefulness, necessity and acceptance of the system. Then, a designing and implementing process is conducted.

Objective

To investigate nurses’ views on accepting the creation of a Nurses’ Health Monitoring System.

Methods

This cross-sectional study was conducted in 2015. Sample size was 586 nurses of Shahid Beheshti University of Medical Sciences. Sampling was conducted using multi-stage random sampling method. Research tool was a two-section researcher-made questionnaire. In the first section, demographic data were studied and in the second section, a twelve-item questionnaire was presented based on technology acceptance model. Five-item questions were regulated on perceived usefulness (PU) and perceived ease of use (PEU) and views towards creating this system. Validity of the questionnaire was approved by content validity and content validity index and its reliability was approved by Cronbach’s alpha. Data were analyzed using SPSS16 and descriptive statistics (frequency distribution, percentage, mean).

Results

The majority of participants (75.3%) were females between 25–35 years of age (44.4%) and (58.2%) were married. Mean work experience was 11.5±8.19. Mean perceived usefulness (PU) (17.36±2.66) and perceived ease of use (PEU) (16.75±2.65) and views towards using a Nurses’ Health Monitoring System was (16.220±3.05).

Conclusion

Over two-thirds of nurses demonstrated perceived usefulness and perceived ease of use as well as positive views towards creating a nurses’ health monitoring system. It is recommended to design and implement a nurses’ health monitoring system based on local culture of Iranian nurses using IT in the health sector.

New Aging Index Using Signal Features of Both Photoplethysmograms and Acceleration Plethysmograms

OBJECTIVES

Acceleration plethysmograms (APGs) are obtained by taking the second derivative of photoplethysmograms (PPGs) and are noninvasive circulatory signals related to risk factors for atherosclerosis with age. There has been growing interest in the development of mobile devices to collect and analyze PPG single features for ambulatory health monitoring. The present study aimed to extract a new feature from the morphologies of APG and PPG signals to classify the dominant indices related to the pulsatile volume of blood in tissue according to age.

METHODS

Ten APG and 14 PPG indices were simultaneously extracted. All indices were compared via Pearson correlation coefficients (r) and a regression analysis. We introduced a combined index extracted from both the PPG and APG indices defined as the inflection point area plus the d_peak (IPAD). The participants included 93 healthy adults aged 36-86 years with a mean ± standard deviation age of 57.43 ± 11.99 years.

RESULTS

The d_peak and age index for the APG indices were significantly correlated with age (r = -0.408, p < 0.0001 and r = 0.296, p = 0.0039, respectively). Only the A1 time for PPG indices was moderately correlated with age (r = -0.247, p = 0.017). The stiffness index, including individual height information, was not related to age (r = -0.031, p = 0.7713). However, the combined IPAD index was significantly more correlated with age (r = 0.56, p < 0.001) than the other indices.

CONCLUSIONS

The proposed index outperformed the other 24 indices for evaluating vascular aging. We suggest that the IPAD is a significant factor related to the clinical information embedded in the PPG waveform.

eButton: A Wearable Computer for Health Monitoring and Personal Assistance

Recent advances in mobile devices have made profound changes in people's daily lives. In particular, the impact of easy access of information by the smartphone has been tremendous. However, the impact of mobile devices on healthcare has been limited. Diagnosis and treatment of diseases are still initiated by occurrences of symptoms, and technologies and devices that emphasize on disease prevention and early detection outside hospitals are under-developed. Besides healthcare, mobile devices have not yet been designed to fully benefit people with special needs, such as the elderly and those suffering from certain disabilities, such blindness. In this paper, an overview of our research on a new wearable computer called eButton is presented. The concepts of its design and electronic implementation are described. Several applications of the eButton are described, including evaluating diet and physical activity, studying sedentary behavior, assisting the blind and visually impaired people, and monitoring older adults suffering from dementia.