Medication and fall injury in the elderly population; do individual demographics, health status and lifestyle matter?

Abstract Objectives Though Bangladesh is passing through demographic, epidemiologic and nutritional transitions, national estimates on nutrition and health status of the elderly population are largely unknown. We aimed to determine the status of selected health and nutrition indicators among the elderly population in Bangladesh. Methods For the first time in Bangladesh, we included elderly population (≥60 years old females and males) as a separate population group in the national food security and nutrition surveillance round 2018–2019. We collected data on dietary diversity, nutritional status, behavioral risk factors of non-communicable diseases, blood pressure, and self-reported chronic diseases from 4,818 elderly people (48% female) living in 82 clusters (57 rural, 15 non-slums urban, and 10 slums) randomly selected from eight administrative division of Bangladesh. Results Majority (59% in rural, 53% in non-slum urban, and 69% in slums) of elderly people were consuming an inadequately diverse (4 or less food groups out of 10) diet. Overall, 89% of elderly people were malnourished (20%) or at risk of malnutrition (69%). The highest prevalence of malnutrition was in Mymensingh division (37%) followed by Sylhet division (27%). The prevalence of obesity was 5%, 16%, and 11%, in rural, non-slum urban, and slums, respectively. The national prevalence of smoking, smokeless tobacco consumption, physical inactivity was 18%, 52%, and 38%, respectively. There was a high burden of hypertension (49% in rural, 53% in non-slum urban, and 39% in slums). Overall, 16% of elderly people had heart diseases, 14% had chronic respiratory diseases, 3% had kidney diseases, 9% had diabetes, 8% had stroke, 0.5% had cancer and 1.4% had mental health problems. Conclusions The government of Bangladesh should design and implement health and nutrition programs among the elderly population. The regional differences in the prevalence of health and nutrition indicators should be considered while designing such programs. Funding Sources Ministry of Health and Family Welfare, Government of Bangladesh

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The Future of the Elderly Population Health Status: Filling a Knowledge Gap

SSRN Electronic Journal ◽

10.2139/ssrn.3753614 ◽

2020 ◽

Author(s):

Vincenzo Atella ◽

Federico Belotti ◽

Daejung Kim ◽

Dana Goldman ◽

Tadeja Gracner ◽

...

Keyword(s):

Health Status ◽

Population Health ◽

Elderly Population ◽

The Elderly ◽

Knowledge Gap ◽

The Future

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The Health Status Transition and Medical Expenditure Evaluation of Elderly Population in China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18136907 ◽

2021 ◽

Vol 18 (13) ◽

pp. 6907

Author(s):

Lianjie Wang ◽

Yao Tang ◽

Farnaz Roshanmehr ◽

Xiao Bai ◽

Farzad Taghizadeh-Hesary ◽

...

Keyword(s):

Health Care ◽

Health Status ◽

Elderly Population ◽

The Elderly ◽

Severe Disability ◽

Medical Expenditures ◽

Medical Expenditure ◽

Population Increase ◽

Health Transition ◽

Status Transition

(1) Background: Because of the rapid expansion of the aging population in China, their health status transition and future medical expenditure have received increasing attention. This paper analyzes the health transition of the elderly and how their health transition impacts medical expenditures. At the same time, feasible policy suggestions are provided to respond to the rising medical expenditure and the demand for social care. (2) Methods: The data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015 and analyzed using the Markov model and the Two-Part model (TPM) to forecast the size of the elderly population and their medical expenditures for the period 2020–2060. (3) Results: The study indicates that: (1) for the elderly with a mild disability, the probability of their health improvement is high; in contrast, for the elderly with a moderate or severe disability, their health deterioration is almost certain; (2) the frequency of the diagnosis and treatments of the elderly is closely related to their health status and medical expenditure; alternatively, as the health status deteriorates, the intensity of the elderly individuals’ acceptance of their diagnosis and treatment increases, and so does the medical expense; (3) the population of the elderly with mild and moderate disability demonstrates an inverted “U”-shape, which reaches a peak around 2048, whereas the elderly with severe disability show linear growth, being the target group for health care; (4) with the population increase of the elderly who have severe disability, the medical expenditure increases significantly and poses a huge threat to medical service supply. Conclusions: It is necessary to provide classified and targeted health care according to the health status of the elderly. In addition, improving the level of medical insurance, establishing a mechanism for sharing medical expenditure, and adjusting the basic demographic structure are all important policy choices.

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The future of the elderly population health status: Filling a knowledge gap

Health Economics ◽

10.1002/hec.4258 ◽

2021 ◽

Author(s):

Vincenzo Atella ◽

Federico Belotti ◽

Daejung Kim ◽

Dana Goldman ◽

Tadeja Gracner ◽

...

Keyword(s):

Health Status ◽

Population Health ◽

Elderly Population ◽

The Elderly ◽

Knowledge Gap ◽

The Future

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Construction of a risk prediction model for Alzheimer’s disease in the elderly population

BMC Neurology ◽

10.1186/s12883-021-02276-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Lingling Wang ◽

Ping Li ◽

Ming Hou ◽

Xiumin Zhang ◽

Xiaolin Cao ◽

...

Keyword(s):

Regression Analysis ◽

Health Status ◽

Prediction Model ◽

Genetic Risk ◽

Elderly Population ◽

Economic Status ◽

The Elderly ◽

Predictor Variables ◽

Lasso Regression ◽

Validation Set

Abstract Background Dementia is one of the greatest global health and social care challenges of the twenty-first century. The etiology and pathogenesis of Alzheimer’s disease (AD) as the most common type of dementia remain unknown. In this study, a simple nomogram was drawn to predict the risk of AD in the elderly population. Methods Nine variables affecting the risk of AD were obtained from 1099 elderly people through clinical data and questionnaires. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis was used to select the best predictor variables, and multivariate logistic regression analysis was used to construct the prediction model. In this study, a graphic tool including 9 predictor variables (nomogram-see precise definition in the text) was drawn to predict the risk of AD in the elderly population. In addition, calibration diagram, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to verify the model. Results Six predictors namely sex, age, economic status, health status, lifestyle and genetic risk were identified by LASSO regression analysis of nine variables (body mass index, marital status and education level were excluded). The area under the ROC curve in the training set was 0.822, while that in the validation set was 0.801, suggesting that the model built with these 6 predictors showed moderate predictive ability. The DCA curve indicated that a nomogram could be applied clinically if the risk threshold was between 30 and 40% (30 to 42% in the validation set). Conclusion The inclusion of sex, age, economic status, health status, lifestyle and genetic risk into the risk prediction nomogram could improve the ability of the prediction model to predict AD risk in the elderly patients.

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Evaluation of the Criteria for Quality of Life of Elderly Health Care Centers in Tehran Province, Iran

Global Journal of Health Science ◽

10.5539/gjhs.v8n7p68 ◽

2015 ◽

Vol 8 (7) ◽

pp. 68 ◽

Cited By ~ 4

Author(s):

Fereshteh Farzianpour ◽

Mohammad Arab ◽

Abbas Rahimi Foroushani ◽

Esmaeil Morad Zali Mehran

Keyword(s):

Quality Of Life ◽

Health Status ◽

Elderly Population ◽

Short Form ◽

Age Distribution ◽

The Elderly ◽

Financial Problems ◽

Cross Sectional ◽

The Mean

BACKGROUND & OBJECTIVES: The objective of this study was to evaluate the elderly quality of life of people covered by the healthcare centers in Tehran and its influencing demographic and background factors.METHOD: This is a cross-sectional study of quality of life of the elderly population covered by healthcare centers and bases in Tehran, as well as the influential background and demographic factors. Sampling was performed using simple random stratified sampling proportionate to the size of strata. Data were collected using the Iranian version of the standard questionnaire Short Form Health Survey (SF-36).RESULTS: According to the findings, 240 (60%) of the cases were men and 160 (40%) were women. Regarding age distribution, 76.3% fell in the 60-69 age range and 87.2% were illiterate. 18% of the elderly stated that they have financial problems and 19.5% did not express any financial problems. While studying the relationship between financial status and health status with the mean scores of quality of life, statistically significant differences were observed in all domains (p=0.032<0.001). The mean quality of life was lower in women compared to men. CONCLUSIONS: The findings of the present study indicate that the health-related quality of life in the elderly population is influenced by their health status and demographic and background variables.

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Elderly Health Inequality in China and its Determinants: A Geographical Perspective

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16162953 ◽

2019 ◽

Vol 16 (16) ◽

pp. 2953 ◽

Cited By ~ 5

Author(s):

Chenjing Fan ◽

Wei Ouyang ◽

Li Tian ◽

Yan Song ◽

Wensheng Miao

Keyword(s):

Health Status ◽

Health Inequalities ◽

Health Inequality ◽

Elderly Population ◽

Hot Spot ◽

Good Health ◽

The Elderly ◽

Multilevel Regression ◽

Health Differences ◽

Elderly Health

Inter-regional health differences and apparent inequalities in China have recently received significant attention. By collecting health status data and individual socio-economic information from the 2015 fourth sampling survey of the elderly population in China (4th SSEP), this paper uses the geographical differentiation index to reveal the spatial differentiation of health inequality among Chinese provinces. We test the determinants of inequalities by multilevel regression models at the provincial and individual levels, and find three main conclusions: 1) There were significant health differences on an inter-provincial level. For example, provinces with a very good or good health rating formed a good health hot-spot region in the Yangtze River Delta, versus elderly people living in Gansu and Hainan provinces, who had a poor health status. 2) Nearly 2.4% of the health differences in the elderly population were caused by inter-provincial inequalities; access (or lack of access) to economic, medical and educational resources was the main reason for health inequalities. 3) At the individual level, inequalities in annual income served to deepen elderly health differences, and elderly living in less developed areas were more vulnerable to urban vs. rural-related health inequalities.

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The health status of the elderly population of Iran in 2012

Archives of Gerontology and Geriatrics ◽

10.1016/j.archger.2015.01.004 ◽

2015 ◽

Vol 60 (2) ◽

pp. 281-287 ◽

Cited By ~ 16

Author(s):

Parisa Taheri Tanjani ◽

Mohammad Esmaeil Motlagh ◽

Mehdi Moradi Nazar ◽

Farid Najafi

Keyword(s):

Health Status ◽

Elderly Population ◽

The Elderly

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