Alcohol Drinking and Health in Ageing: A Global Scale Analysis of Older Individual Data through the Harmonised Dataset of ATHLOS

Tyrovolas, Stefanos; Panaretos, Dimitris; Daskalopoulou, Christina; Gine-Vazquez, Iago; Sánchez-Niubò, Albert; Olaya, Beatriz; Bobák, Martin; Prince, Martin; Prina, Matthew; Ayuso-Mateos, José Luís; Caballero, Francisco Félix; García‐Esquinas, Esther; Arndt, Holger; Scherbov, Sergei; Sanderson, Warren C.; Gheno, Ilenia; Koupil, Ilona; Bickenbach, Jerome; Chatterji, Somnath; Koskinen, Seppo; Raggi, Alberto; Pająk, Andrzej; Tobiasz–Adamczyk, Beata; Haro, Josep María; Panagiotakos, Demosthenes B.

doi:10.3390/nu12061746

Cited by 10 publications

(4 citation statements)

References 28 publications

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“…The positive correlation between the highest level of alcohol consumption and SRH in women was surprising. However, some evidence indicates that alcohol consumption may carry some health benefits for older women in terms of survival and quality of life, possibly mediated through a healthier drinking pattern than men and cardio-protective effects [ 16 , 49 – 51 ]. On the other hand, some studies have found that having a very good health status is a predictor of alcohol consumption, and not the other way around [ 52 , 53 ].…”

Section: Discussionmentioning

confidence: 99%

The effects of exceeding low-risk drinking thresholds on self-rated health and all-cause mortality in older adults: the Tromsø study 1994–2020

et al. 2023

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Background Based on findings of increasing alcohol consumption in older adults, it is important to clarify the health consequences. Using data from the Tromsø study, we aimed to investigate the relationship between different levels of alcohol consumption in old adulthood and self-rated health trajectories and all-cause mortality. Methods This is an epidemiological study utilizing repeated measures from the Tromsø study cohort. It allows follow-up of participants from 1994 to 2020. A total of 24,590 observations of alcohol consumption were made in older adults aged 60–99 (53% women). Primary outcome measures: Self-rated health (SRH) and all-cause mortality. SRH was reported when attending the Tromsø study. Time of death was retrieved from the Norwegian Cause of Death Registry. The follow-up time extended from the age of study entry to the age of death or end of follow-up on November 25, 2020. Predictor: Average weekly alcohol consumption (non-drinker, < 100 g/week, ≥100 g/week). We fitted two-level logistic random effects models to examine how alcohol consumption was related to SRH, and Cox proportional hazards models to examine its relation to all-cause mortality. Both models were stratified by sex and adjusted for sociodemographic factors, pathology, biometrics, smoking and physical activity. In addition, all the confounders were examined for whether they moderate the relationship between alcohol and the health-related outcomes through interaction analyses. Results We found that women who consumed ≥100 g/week had better SRH than those who consumed < 100 g/week; OR 1.85 (1.46–2.34). This pattern was not found in men OR 1.18 (0.99–1.42). We identified an equal mortality risk in both women and men who exceeded 100 g/week compared with those who consumed less than 100 g/week; HR 0.95 (0.73–1.22) and HR 0.89 (0.77–1.03), respectively. Conclusions There was no clear evidence of an independent negative effect on either self-rated health trajectories or all-cause mortality for exceeding an average of 100 g/week compared to lower drinking levels in this study with up to 25 years follow-up. However, some sex-specific risk factors in combination with the highest level of alcohol consumption led to adverse effects on self-rated health. In men it was the use of sleeping pills or tranquilisers and ≥ 20 years of smoking, in women it was physical illness and older age.

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Section: Discussionmentioning

confidence: 99%

The effects of exceeding low-risk drinking thresholds on self-rated health and all-cause mortality in older adults: the Tromsø study 1994–2020

et al. 2023

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“…We selected the established factors that have been clearly identified in previous research as control variables for healthy aging (Appendix 2 in the Supplement), including: physical condition (chronic diseases, teeth) [ 2 – 4 , 34 , 35 , 38 , 40 ], SES (education, ACE, household income) [ 3 , 4 , 6 , 8 , 9 , 34 , 35 , 40 – 44 ], lifestyle habits (smoke, drink) [ 3 , 6 , 7 , 34 , 35 , 41 , 43 , 45 ], and demographic factors (geographical distribution, urban–rural distribution, age, gender, and marital status) [ 3 , 4 , 6 , 9 , 34 , 35 , 40 , 42 ].…”

Section: Methodsmentioning

confidence: 99%

Examining dynamic developmental trends: the interrelationship between age-friendly environments and healthy aging in the Chinese population—evidence from China Health and Retirement Longitudinal Study, 2011–2018

Cheng,

Chen,

Wei

et al. 2024

BMC Geriatr

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Background The objective of this research is to investigate the dynamic developmental trends between Age-Friendly Environments (AFE) and healthy aging in the Chinese population. Methods This study focused on a sample of 11,770 participants from the CHARLS and utilized the ATHLOS Healthy Aging Index to assess the level of healthy aging among the Chinese population. Linear mixed model (LMM) was used to explore the relationship between AFE and healthy aging. Furthermore, a cross-lagged panel model (CLPM) and a random-intercept cross-lagged panel model (RI-CLPM) were used to examine the dynamic developmental trends of healthy aging, taking into account both Between-Person effects and Within-Person effects. Results The results from LMM showed a positive correlation between AFE and healthy aging (β = 0.087, p < 0.001). There was a positive interaction between the geographic distribution and AFE (central region * AFE: β = 0.031, p = 0.038; eastern region * AFE: β = 0.048, p = 0.003). In CLPM and RI-CLPM, the positive effect of healthy aging on AFE is a type of Between-Person effects (β ranges from 0.147 to 0.159, p < 0.001), while the positive effect of AFE on healthy aging is Within-Person effects (β ranges from 0.021 to 0.024, p = 0.004). Conclusion Firstly, individuals with high levels of healthy aging are more inclined to actively participate in the development of appropriate AFE compared to those with low levels of healthy aging. Furthermore, by encouraging and guiding individuals to engage in activities that contribute to building appropriate AFE, can elevate their AFE levels beyond the previous average level, thereby improving their future healthy aging levels. Lastly, addressing vulnerable groups by reducing disparities and meeting their health needs effectively is crucial for fostering healthy aging in these populations.

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“…Alcohol drinking status: Those who drink alcohol in the past 12 months from the time of data collection (Tyrovolas et al, 2020)…”

Section: Methodsmentioning

confidence: 99%

“…Length of hospital stay: Is the duration of a single episode of hospitalization which is calculated by subtracting the day of admission from the day of discharge (Tefera et al, 2020) Normal length of hospital stay: Hospital stays less than the 75 th percentile length of stay was used (Tefera et al, 2020) Prolonged length of hospital stay: Hospital stays greater than the 75 th percentile was used (Tefera et al, 2020) Smoking status: Who smoke in the past 3 months from the time of data collection (Jamal et al, 2018) Alcohol drinking status: Those who drink alcohol in the past 12 months from the time of data collection (Tyrovolas et al, 2020) Number of medication: Total number of medication taken by patients during hospital stay and classified as ≤2 and >2.…”

Section: Operational Definitionmentioning

confidence: 99%

Prolonged Length of Hospital Stay and Associated Factors Among Patients Admitted at a Surgical Ward in Selected Public Hospitals Arsi Zone, Oromia, Ethiopia, 2022

Fetene

Tekalegn

Abdela³

et al. 2022

Preprint

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BackgroundProlonged length of hospital stay is the most common indicator of poor quality of health care and inefficient utilization of hospital resources. Prolonged hospital stay associated with increased mortality, hospital-acquired infection, and unnecessary utilization of hospital bed and other resources. Predicting length of hospital stay facilitates resource designing and initiates quality improvement activities. However, data regarding the prolonged length of hospital stays, and associated factors were a scarce in Ethiopia.MethodsA hospital-based cross-sectional study was conducted on a sample of 316 adult patients from December 1 to January 10, 2022. A consecutive sampling technique was used during sampling procedure. A structured questionnaire was used to collect data regarding sociodemographic factors, clinical factors, medication factors, and behavioral factors through interview, medical record review and by using check list. The data was entered into the epidata4.6 version and exported to SPSS Version25 for binary logistic regression analysis. To identify factors associated with outcome variable, candidate variables (p<0.25) were fitted to multivariable analysis, and those with P-values<0.05 were considered as factors associated with prolonged length of hospital stay. Odds ratio with corresponding 95% CI was used to indicate the strength of association of variables with prolonged length of hospital stay.ResultOne fourth (24.7%) of the study participants experienced a prolonged length of stay at surgical ward. The odd of a prolonged length of hospital stay was high among patients who had comorbid condition [AOR=4.59, at 95% CI= (2.46-8.56)], who developed surgical site infection [AOR=5.02 at 95% CI= 1.97-12.80)], and who developed hospital acquired pneumonia during hospital stay [AOR= 3.43 at 95% CI= (1.36-8.64)].Conclusion and recommendationNear to quarter of the study participants’ experienced prolonged length of hospital stays. Comorbid condition, surgical site infection, and hospital acquired pneumonia were factors associated with prolonged length of hospital stay at surgical ward. Quality of care could be improved by adjusting surgical ward environment to prevent hospital acquired infection and focus on managing complication after surgery. Health care provider should be educating surgical patient about the risk of comorbidity on wound healing and early diagnosis and prevention of comorbid condition.

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Alcohol Drinking and Health in Ageing: A Global Scale Analysis of Older Individual Data through the Harmonised Dataset of ATHLOS

Cited by 10 publications

References 28 publications

The effects of exceeding low-risk drinking thresholds on self-rated health and all-cause mortality in older adults: the Tromsø study 1994–2020

The effects of exceeding low-risk drinking thresholds on self-rated health and all-cause mortality in older adults: the Tromsø study 1994–2020

Examining dynamic developmental trends: the interrelationship between age-friendly environments and healthy aging in the Chinese population—evidence from China Health and Retirement Longitudinal Study, 2011–2018

Prolonged Length of Hospital Stay and Associated Factors Among Patients Admitted at a Surgical Ward in Selected Public Hospitals Arsi Zone, Oromia, Ethiopia, 2022

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