Association of healthy lifestyle score with all-cause mortality and life expectancy: a city-wide prospective cohort study of cancer survivors

Antineoplastics for treating Alzheimer's disease and dementia: Evidence from preclinical and observational studies

As the world population ages, there will be an increasing need for effective therapies for aging-associated neurodegenerative disorders, which remain untreatable. Dementia due to Alzheimer's disease (AD) is one of the leading neurological diseases in the aging population. Current therapeutic approaches to treat this disorder are solely symptomatic, making the need for new molecular entities acting on the causes of the disease extremely urgent. One of the potential solutions is to use compounds that are already in the market. The structures have known pharmacokinetics, pharmacodynamics, toxicity profiles, and patient data available in several countries. Several drugs have been used successfully to treat diseases different from their original purposes, such as autoimmunity and peripheral inflammation. Herein, we divulge the repurposing of drugs in the area of neurodegenerative diseases, focusing on the therapeutic potential of antineoplastics to treat dementia due to AD and dementia. We briefly touch upon the shared pathological mechanism between AD and cancer and drug repurposing strategies, with a focus on artificial intelligence. Next, we bring out the current status of research on the development of drugs, provide supporting evidence from retrospective, clinical, and preclinical studies on antineoplastic use, and bring in new areas, such as repurposing drugs for the prion-like spreading of pathologies in treating AD.

Association of lifestyle with sleep health in general population in China: a cross-sectional study

The concept of a healthy lifestyle is receiving increasing attention. This study sought to identify an optimal healthy lifestyle profile associated with sleep health in general population of China. An online cross-sectional survey was conducted from June to July 2022. Six healthy lifestyle factors were assessed: healthy diet, regular physical exercise, never smoking, never drinking alcohol, low sedentary behavior, and normal weight. Participants were categorized into the healthy lifestyle (5-6 factors), average (3-4 factors), and unhealthy lifestyle groups (0-2 factors). The study's primary outcome was sleep health, which included sleep quality, duration, pattern, and the presence of any sleep disorder or disturbance, including insomnia, excessive daytime sleepiness, obstructive apnea syndrome, and narcolepsy. Multivariable logistic regression analysis was applied to explore lifestyles associated with the selected sleep health outcomes. 41,061 individuals were included, forming 18.8% healthy, 63.8% average, and 17.4% unhealthy lifestyle groups. After adjusting for covariates, participants with healthy lifestyle were associated with a higher likelihood of good sleep quality (OR = 1.56, 95% CI = 1.46-1.68), normal sleep duration (OR = 1.60, 95% CI = 1.49-1.72), healthy sleep pattern (OR = 2.15, 95% CI = 2.00-2.31), and lower risks of insomnia (OR = 0.66, 95% CI = 0.61-0.71), excessive daytime sleepiness (OR = 0.66, 95% CI = 0.60-0.73), and obstructive apnea syndrome (OR = 0.40, 95% CI = 0.37-0.43), but not narcolepsy (OR = 0.92, 95% CI = 0.83-1.03), compared to those with unhealthy lifestyle. This large cross-sectional study is the first to our knowledge to quantify the associations of a healthy lifestyle with specific aspects of sleep health. The findings offer support for efforts to improve sleep health by modulating lifestyle.

Post-diagnostic lifestyle and mortality of cancer survivors: Results from a prospective cohort study

OBJECTIVE

Lifestyle factors after cancer diagnosis could influence cancer survival. This study aimed to investigate the joint effects of smoking, physical activity, alcohol consumption, diet and sleep duration on all-cause, cancer and non-cancer mortality of cancer survivors in UK biobank.

METHODS

The follow-up period concluded in December 2021, with post-diagnostic lifestyle factors assessed at baseline. A lifestyle score ranging from 0 to 5 was assigned based on adherence to the selected lifestyle factors. The study employed Cox regression models for hazard ratios (HRs) and Kaplan-Meier for survival rates, with stratified and sensitivity analyses to assess the robustness of our findings under various assumptions.

RESULTS

During a median follow-up of 12.7 years, 5652 deaths were documented from 34,184 cancer survivors. Compared to scoring 0-1, the HRs (95% CIs) for all-cause mortality with lifestyle scores of 2, 3, 4, and 5 were 0.70 (95% CI: 0.64, 0.76), 0.57 (0.52, 0.62), 0.50 (0.45, 0.54) and 0.43 (0.38, 0.48), respectively. Specific cancer types, particularly digestive, breast, female reproductive, non-solid, and skin cancers, showed notable benefits from adherence to healthy lifestyle, with the HRs of 0.55 (0.39, 0.79), 0.54 (0.42, 0.70), 0.32 (0.19, 0.53), 0.58 (0.39, 0.86), and 0.36 (0.28, 0.46) for lifestyle score of 5, respectively. Stratified analyses indicated the association was particularly significant among those with normal/lower BMI and higher Townsend Deprivation Index (Pinteraction = 0.001 and < 0.001, respectively).

CONCLUSIONS

Healthier lifestyles were significantly linked with reduced mortality among cancer survivors. These findings highlight the need for adherence to healthy lifestyle habits to improve survival.

Healthy lifestyle is associated with reduced cardiovascular disease, depression and mortality in people at elevated risk of sleep apnea

We assessed: (1) the independent and joint association of obstructive sleep apnea risk and healthy lifestyle with common consequences (excessive daytime sleepiness, depression, cardiovascular disease and stroke) of obstructive sleep apnea; and (2) the effect of healthy lifestyle on survival in people with increased obstructive sleep apnea risk. Data from 13,694 adults (median age 46 years; 50% men) were used for cross-sectional and survival analyses (mortality over 15 years). A healthy lifestyle score with values from 0 (most unhealthy) to 5 (most healthy) was determined based on diet, alcohol intake, physical activity, smoking and body mass index. In the cross-sectional analysis, obstructive sleep apnea risk was positively associated with all chronic conditions and excessive daytime sleepiness in a dose-response manner (p for trend < 0.001). The healthy lifestyle was inversely associated with all chronic conditions (p for trend < 0.001) but not with excessive daytime sleepiness (p for trend = 0.379). Higher healthy lifestyle score was also associated with reduced odds of depression and cardiovascular disease. We found an inverse relationship between healthy lifestyle score with depression (p for trend < 0.001), cardiovascular disease (p for trend = 0.003) and stroke (p for trend = 0.025) among those who had high obstructive sleep apnea risk. In the survival analysis, we found an inverse association between healthy lifestyle and all-cause mortality for all categories of obstructive sleep apnea risk (moderate/high- and high-risk groups [p for trend < 0.001]). This study emphasises the crucial role of a healthy lifestyle in mitigating the effects of obstructive sleep apnea risk in individuals with an elevated obstructive sleep apnea risk.

Association of depressive symptoms and sleep disturbances with survival among US adult cancer survivors

BACKGROUND

Depression and sleep disturbances are associated with increased risks of various diseases and mortality, but their impacts on mortality in cancer survivors remain unclear. The objective of this study was to characterize the independent and joint associations of depressive symptoms and sleep disturbances with mortality outcomes in cancer survivors.

METHODS

This population-based prospective cohort study included cancer survivors aged ≥ 20 years (n = 2947; weighted population, 21,003,811) from the National Health and Nutrition Examination Survey (NHANES) 2007-2018 cycles. Depressive symptoms and sleep disturbances were self-reported. Depressive symptoms were assessed using the Patient Health Questionnaire 9 (PHQ-9). Death outcomes were determined by correlation with National Death Index records through December 31, 2019. Primary outcomes included all-cause, cancer-specific, and noncancer mortality.

RESULTS

During the median follow-up of 69 months (interquartile range, 37-109 months), 686 deaths occurred: 240 participants died from cancer, 146 from heart disease, and 300 from other causes. Separate analyses revealed that compared with a PHQ-9 score (0-4), a PHQ-9 score (5-9) was associated with a greater risk of all-cause mortality (hazard ratio [HR], 1.28; 95% CI, 1.03-1.59), and a PHQ-9 score (≥ 10) was associated with greater risk of all-cause mortality (HR, 1.37; 95% CI, 1.04-1.80) and noncancer mortality (HR, 1.45; 95% CI, 1.01-2.10). Single sleep disturbances were not associated with mortality risk. In joint analyses, the combination of a PHQ-9 score ≥ 5 and no sleep disturbances, but not sleep disturbances, was associated with increased risks of all-cause mortality, cancer-specific mortality, and noncancer mortality. Specifically, compared with individuals with a PHQ-9 score of 0-4 and no sleep disturbances, HRs for all-cause mortality and noncancer mortality in individuals with a PHQ-9 score of 5-9 and no sleep disturbances were 1.72 (1.21-2.44) and 1.69 (1.10-2.61), respectively, and 2.61 (1.43-4.78) and 2.77 (1.27-6.07), respectively, in individuals with a PHQ-9 score ≥ 10 and no sleep disturbances; HRs for cancer-specific mortality in individuals with a PHQ-9 score ≥ 5 and no sleep disturbances were 1.95 (1.16-3.27).

CONCLUSIONS

Depressive symptoms were linked to a high risk of mortality in cancer survivors. The combination of a PHQ-9 score (≥ 5) and an absence of self-perceived sleep disturbances was associated with greater all-cause mortality, cancer-specific mortality, and noncancer mortality risks, particularly in individuals with a PHQ-9 score (≥ 10).

Association of lifestyles and multimorbidity with mortality among individuals aged 60 years or older: Two prospective cohort studies

Lifestyles are associated with all-cause mortality, yet limited research has explored the association in the elderly population with multimorbidity. We aim to investigate the impact of adopting a healthy lifestyle on reducing the risk of all-cause mortality in older individuals with or without multimorbidity in both China and UK. This prospective study included 29,451 and 173,503 older adults aged 60 and over from Chinese Longitudinal Healthy Longevity Survey (CLHLS) and UK Biobank. Lifestyles and multimorbidity were categorized into three groups, respectively. Cox proportional hazards regression was used to estimate the Hazard Ratios (HRs), 95% confidence intervals (95% CIs), and dose-response for all-cause mortality in relation to lifestyles and multimorbidity, as well as the combination of both factors. During a mean follow-up period of 4.7 years in CLHLS and 12.14 years in UK Biobank, we observed 21,540 and 20,720 deaths, respectively. For participants with two or more conditions, compared to those with an unhealthy lifestyle, adopting a healthy lifestyle was associated with a 27%-41% and 22%-42% reduction in mortality risk in the CLHLS and UK Biobank, respectively; Similarly, for individuals without multimorbidity, this reduction ranged from 18% to 41%. Among participants with multimorbidity, individuals with an unhealthy lifestyle had a higher mortality risk compared to those maintaining a healthy lifestyle, with HRs of 1.15 (95% CI: 1.00, 1.32) and 1.27 (95% CI: 1.16, 1.39) for two conditions, and 1.24 (95% CI: 1.06, 1.45) and 1.73 (95% CI: 1.56, 1.91) for three or more conditions in CLHLS and UK Biobank, respectively. Adherence to a healthy lifestyle can yield comparable mortality benefits for older individuals, regardless of their multimorbidity status. Furthermore, maintaining a healthy lifestyle can alleviate the mortality risks linked to a higher number of diseases.

Healthy lifestyle and cancer survival: A multinational cohort study

Lifestyle factors after a cancer diagnosis could influence the survival of cancer 60 survivors. To examine the independent and joint associations of healthy lifestyle factors with mortality outcomes among cancer survivors, four prospective cohorts (National Health and Nutrition Examination Survey [NHANES], National Health Interview Survey [NHIS], UK Biobank [UKB] and Kailuan study) across three countries. A healthy lifestyle score (HLS) was defined based on five common lifestyle factors (smoking, alcohol drinking, diet, physical activity and body mass index) that related to cancer survival. We used Cox proportional hazards regression to estimate the hazard ratios (HRs) for the associations of individual lifestyle factors and HLS with all-cause and cancer mortality among cancer survivors. During the follow-up period of 37,095 cancer survivors, 8927 all-cause mortality events were accrued in four cohorts and 4449 cancer death events were documented in the UK and US cohorts. Never smoking (adjusted HR = 0.77, 95% CI: 0.69-0.86), light alcohol consumption (adjusted HR = 0.86, 95% CI: 0.82-0.90), adequate physical activity (adjusted HR = 0.90, 95% CI: 0.85-0.94), a healthy diet (adjusted HR = 0.69, 95% CI: 0.61-0.78) and optimal BMI (adjusted HR = 0.89, 95% CI: 0.85-0.93) were significantly associated with a lower risk of all-cause mortality. In the joint analyses of HLS, the HR of all-cause and cancer mortality for cancer survivors with a favorable HLS (4 and 5 healthy lifestyle factors) were 0.55 (95% CI 0.42-0.64) and 0.57 (95% CI 0.44-0.72), respectively. This multicohort study of cancer survivors from the United States, the United Kingdom and China found that greater adherence to a healthy lifestyle might be beneficial in improving cancer prognosis.

Effects of Lifestyle Interventions on Health and Life Quality of Colorectal Cancer Survivors: A Systematic Review and Meta-analysis

BACKGROUND

The results of previous studies on the effects of lifestyle interventions on the quality of life (QoL) in colorectal cancer (CRC) survivors remain controversial, and there have been several new publications in this area in recent years.

OBJECTIVES

To assess whether lifestyle interventions can lead to favorable health outcomes and improved QoL in CRC survivors, we performed a meta-analysis.

METHODS

PubMed, EMBASE, Web of Science, and Cochrane Library were systematically searched to obtain relevant literature published from January 1, 1990, to November 1, 2021. The required data were extracted and summarized to compare the physical activity levels, QoL, mental health assessment, and anthropometric data between lifestyle interventions and routine nursing.

RESULTS

Twelve studies were included. Compared with the control group, lifestyle interventions could significantly increase the physical activity time (weighted mean difference [WMD], 9.84; 95% confidence interval [CI], 1.20-18.48; P = .026), metabolic equivalent task levels (WMD, 10.40; 95% CI, 5.30-15.49; P < .001), and Functional Assessment of Cancer Therapy Scale-Colorectal scores (WMD, 3.12; 95% CI, 0.24-5.99; P = .034). However, lifestyle interventions were not noticeably able to improve the fatigue, depression levels, anxiety levels, waist circumference, or body mass index in CRC survivors.

CONCLUSION

Lifestyle interventions could generate an increase in physical activity time, metabolic equivalent task levels, and QoL in CRC survivors.

IMPLICATIONS FOR PRACTICE

Lifestyle interventions in the future that include physical activity, diet, or comprehensive programs are needed to increase physical activity levels and improve QoL in CRC survivors.

Association Between Fear of Cancer Recurrence, Fatigue, and Healthy Lifestyle Behaviors Among Breast Cancer Survivors in South Korea

BACKGROUND

Improving healthy lifestyle behaviors in breast cancer survivors can promote their physical and mental health, thereby reducing the risk of cancer recurrence. Therefore, it is crucial to identify and control the factors affecting healthy lifestyle behaviors among breast cancer survivors.

OBJECTIVE

This study aimed to examine the effects of physiological, psychological, and situational factors and symptoms on healthy lifestyle behaviors in breast cancer survivors.

METHODS

Data were collected from August to September 2021, and a questionnaire was administered through an online breast cancer patient community's bulletin board. Finally, 162 questionnaires were included in the analysis.

RESULTS

The model was statistically significant, explaining 33.2% of the variance. A decrease in healthy lifestyle behaviors in breast cancer survivors was influenced by an age of 40 years or younger, 5 years or more since a breast cancer diagnosis, low income, fear of cancer recurrence, and fatigue.

CONCLUSIONS

Intervention strategies, such as easily accessible online content that accounts for age and survival period after cancer diagnosis, should be used to promote healthy lifestyle behaviors among breast cancer survivors. Healthcare providers should be given appropriate guidelines on managing patients' fear of cancer recurrence and reducing fatigue to ensure timely access to clinical interventions. Adequate financial support from local communities and governments is needed to promote healthy lifestyle behaviors.

IMPLICATIONS FOR PRACTICE

To improve breast cancer survivors' healthy lifestyle behaviors, an understanding of the influencing factors and a multidimensional approach are required. Nurses play a role in developing and implementing interventions to improve healthy lifestyle behaviors.

Association of depression with incident sarcopenia and modified effect from healthy lifestyle: The first longitudinal evidence from the CHARLS

BACKGROUND

The prospective association of depression with incident sarcopenia remains unknown, as does whether such an association is modified by a healthy lifestyle. Thus, the goal of this study was to determine whether depression is independently related to the risk of developing sarcopenia and to detect the effect of a healthy lifestyle on its modification.

METHODS

The prospective study included 9486 participants from the China Health and Retirement Longitudinal Study who were followed from 2011 to 2015. We calculated a lifestyle score based on body mass index, drinking, smoking, social activities, and sleeping time. Cox proportional hazards regression models with hazard ratios (HRs) and 95 % confidence intervals were used to estimate the effect of depression on the risk of sarcopenia and the modification effect of lifestyle (CIs).

RESULTS

During a mean of 3.53 years of follow-up, 1373 individuals developed sarcopenia. After adjusting for confounding factors, depression was significantly associated with a higher risk of incident sarcopenia (HR = 1.34; 95 % CI: 1.19, 1.50). In addition, we observed that individuals adhering to a healthy lifestyle had an 18 % lower risk of sarcopenia onset, compared with individuals with an unhealthy lifestyle.

LIMITATIONS

We couldn't completely rule out potential residual bias due to its observational design. Second, ascertainment of the history of diseases in CHARLS was based on self-reported information, which may introduce recall bias or misclassification.

CONCLUSIONS

Depression was associated with a higher risk of sarcopenia in Chinese adults, and such a risk may be alleviated by adhering to a healthy lifestyle.

Adherence to a healthy lifestyle and its association with cognitive impairment in community-dwelling older adults in Shanghai

Introduction

There is a growing body of recent literature linking the association of specific or multiple lifestyles with cognitive impairment, but most of these studies have been conducted in Western populations, and it is necessary to study multiple lifestyles and cognitive abilities in different populations, with the primary population of this study being a select group of community-dwelling older adults in Shanghai, China.

Methods

The sample included 2,390 community-dwelling Chinese participants. Their cognitive function was assessed using the Mini-Mental State Examination (MMSE). We defined a healthy lifestyle score on the basis of being non-smoking, performing ≥210 min/wk moderate/vigorous-intensity physical activity, having light to moderate alcohol consumption, eating vegetables and fruits daily, having a body mass index (BMI) of 18.5-23.9 kg/m2, and having a waist-to-hip ratio (WHR) <0.90 for men and <0.85 for women, for an overall score ranging from 0 to 6.

Results

Compared with participants with ≤2 healthy lifestyle factors, the adjusted odds ratio (OR) and 95% confidence interval (CI) for participants with 4, 5, and 6 healthy lifestyle factors were 0.53 (95% CI, 0.29-0.98), 0.40 (95% CI, 0.21-0.75), and 0.36 (95% CI, 0.16-0.79), respectively. Only WHR (OR = 0.54, 95% CI = 0.37-0.78) and physical activity (OR = 0.69, 95% CI = 0.51-0.92) were associated with cognitive impairment. A healthy lifestyle correlated with overall cognition (β = 0.066, orientation (β = 0.049), language ability (β = 0.060), delayed recall (β = 0.045) and executive function (β = 0.044) (P all < 0.05).

Conclusion

The study provides evidence on an inverse association between healthy lifestyles and cognitive impairment. We investigated whether healthy lifestyle was related to specific cognitive functions to provide a theoretical basis for accurate clinical prescription.

The association between maternal healthy lifestyle factors during pregnancy and the neonatal anthropometric indicators based on a prospective cohort study

BACKGROUND AND OBJECTIVES

We aimed to evaluate the associations between a combined healthy lifestyle during the second and third trimesters and offspring anthropometric outcomes in China.

METHODS AND STUDY DESIGN

We examined these associations among 548 participants from nine community health centers and three hospitals in the North China cohort. A pregnant women's healthy lifestyle score (HLS) was constructed based on six lifestyle factors: smoking, alcohol consumption, physical activity, sedentary behavior, diet, and gestational weight gain. Anthropometric indicators at birth like birth weight (BW), head circumference (HC), and birth length (BL) were collected, and weight to head circumference ratio (WHC, kg/m), body mass index (BMI, kg/m2) and Ponderal Index (PI, kg/m3) were calculated. Multivariate linear and logistic regression models were used to examine the effects of HLS during the second and third trimesters on anthropometric outcomes at birth, respectively.

RESULTS

In fully adjusted models, we found a negative association between second and third-trimester HLS and offspring HC and a positive relationship between second-trimester HLS and BL (p<0.05). Neonates with mothers in the highest HLS tertile had a 5.6% relatively lower HC and 2.3% relatively longer body length than women in the lowest tertile. Each additional unit in third-trimester HLS had an associated decrease in HC by 0.96 cm. None of the associations between HLS and BW, WHC, BMI, and PI of offspring were observed.

CONCLUSIONS

A healthy lifestyle score may significantly impact offspring head circumference and body length, supporting the important role of healthy lifestyles in improving the health of offspring.

Lifestyle, clinical and histological indices-based prediction models for survival in cancer patients: a city-wide prospective cohort study in China

PURPOSE

We developed a nomogram to predict 3-year, 5-year and 7-year cancer survival rates of cancer patients.

METHODS

This prospective cohort study included 20,491 surviving patients first diagnosed with cancer in Guangzhou from 2010 to 2019. They were divided into a training and a validation group. Lifestyle, clinical and histological parameters (LCH) were included in multivariable Cox regression. Akaike information criterion was used to select prediction factors for the nomogram. The discrimination and calibration of models were assessed by concordance index (C-index), area under time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration plots. We used net reclassification index (NRI) and integrated discrimination improvement (IDI) to compare the clinical utility of LCH prediction model with the prediction model based on lifestyle factors (LF).

RESULTS

13 prediction factors including age, sex, BMI, smoking status, physical activity, sleep duration, regular diet, tumor grading, TNM stage, multiple primary cancer and anatomical site were included in the LCH model. The LCH model showed satisfactory discrimination and calibration (C-index = 0.81 (95% CI 0.80-0.82) for training group and 0.80 (0.79-0.81) for validation group, both time-dependent AUC > 0.70). The LF model including smoking status, physical activity, sleep duration, regular diet, and BMI showed less satisfactory discrimination (C-index = 0.60 (95% CI 0.59-0.61) for training and 0.60 (0.58-0.62) for validation group). The LCH model had better accuracy and discriminative ability than the LF model, as indicated by positive NRI and IDI values.

CONCLUSIONS

The LCH model shows good accuracy, clinical utility and precise prognosis prediction, and may serve as a tool to predict cancer survival of cancer patients.

Association of Unhealthy Lifestyle and Genetic Risk Factors With Mild Cognitive Impairment in Chinese Older Adults

Importance

Apolipoprotein E polymorphism ε4 (APOE ε4) and methylenetetrahydrofolate reductase (MTHFR) TT genotype are genetic risk factors of mild cognitive impairment (MCI), but whether this risk can be changed by modifiable lifestyle factors is unknown.

Objective

To explore whether unhealthy lifestyle (unhealthy dietary intake, current smoking, nonlimited alcohol consumption, and irregular physical activities) is associated with a higher risk of age-related MCI considering genetic risk.

Design, Setting, and Participants

This population-based cohort study used data from Tianjin Elderly Nutrition and Cognition (TENC) study participants, recruited from March 1, 2018, through June 30, 2021, and followed up until November 30, 2022. Participants were Chinese adults aged 60 years or older who completed the neuropsychological assessments, general physical examinations, and a personal interview.

Exposures

Healthy lifestyle was defined according to the Chinese Dietary Guidelines 2022, including healthy diet, regular physical activity, limited alcohol consumption, and no current smoking, categorized into healthy and unhealthy lifestyles according to weighted standardized lifestyle score. Genetic risk was defined by MTHFR TT genotype and APOE ε4, categorized into low and high genetic risk according to weighted standardized genetic risk score.

Main Outcomes and Measures

The main outcome was newly diagnosed MCI as identified using a modified version of Petersen criteria. Hazard ratios (HRs) and 95% CIs were estimated using Cox proportional hazard regression models.

Results

A total of 4665 participants were included (mean [SD] age, 67.9 [4.9] years; 2546 female [54.6%] and 2119 male [45.4%]); 653 participants with new-onset MCI (mean [SD] age, 68.4 [5.4] years; 267 female [40.9%] and 386 male [59.1%]) were identified after a median follow-up of 3.11 years (range, 0.82-4.61 years). Individuals with a low genetic risk and an unhealthy lifestyle (HR, 3.01; 95% CI, 2.38-3.79), a high genetic risk and a healthy lifestyle (HR, 2.65; 95% CI, 2.03-3.44), and a high genetic risk and an unhealthy lifestyle (HR, 3.58; 95% CI, 2.73-4.69) had a higher risk of MCI compared with participants with a low genetic risk and a healthy lifestyle. There was a synergistic interaction between lifestyle categories and genetic risk (β = 3.58; 95% CI, 2.73-4.69).

Conclusions and Relevance

In this cohort study of TENC participants, the findings show that unhealthy lifestyle and high genetic risk were significantly associated with a higher risk of MCI among Chinese older adults. Unhealthy lifestyle factors were associated with a higher risk of MCI regardless of genetic risk, and lifestyle and genetic risk had synergistic interactions. These findings could contribute to the development of dietary guidelines and the prevention of early-stage dementia.

Ideal cardiovascular health metrics and life expectancy free of cardiovascular diseases: a prospective cohort study

Objectives

Whether cardiovascular health (CVH) metrics impact longevity with and without cardiovascular diseases (CVDs) has not been well established. This study aimed to investigate the association between CVH metrics and life expectancy in participants free of CVD events. We hypothesized that ideal CVH status was associated with increased life expectancy and assessed the effect of CVH status as a prevention target of longevity in the framework of predictive, preventive, and personalized medicine (PPPM/3PM).

Methods

A total of 92,795 participants in the Kailuan study were examined and thereafter followed up until 2020. We considered three transitions (from non-CVD events to incident CVD events, from non-CVD events to mortality, and from CVD events to mortality). The multistate lifetable method was applied to estimate the life expectancy.

Results

During a median follow-up of 13 years, 12,541 (13.51%) deaths occurred. Compared with poor CVH, ideal CVH attenuated the risk of incident CVD events and mortality without CVD events by approximately 58% and 27%, respectively. Women with ideal CVH at age 35 had a 5.00 (3.23-6.77) year longer life expectancy free of CVD events than did women with poor CVH metrics. Among men, ideal CVH was associated with a 6.74 (5.55-7.93) year longer life expectancy free of CVD events.

Conclusion

An ideal CVH status is associated with a lower risk of premature mortality and a longer life expectancy, either in the general population or in CVD patients, which are cost-effective ways for personalized medicine of potential CVD patients. Our findings suggest that the promotion of a higher CVH score or ideal CVH status would result in reduced burdens of CVD events and extended disease-free life expectancy, which offered an accurate prediction for primary care following the concept of PPPM/3PM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00322-8.

Lifestyle trajectories and ischemic heart diseases: a prospective cohort study in UK Biobank

AIMS

To evaluate the associations of baseline and long-term trajectories of lifestyle with incident ischemic heart diseases (IHD).

METHODS

29,164 participants in the UK Biobank who had at least one follow-up assessment and were free of IHD at the last follow-up assessment were included. We constructed a weighted unhealthy lifestyle score though summing five lifestyle factors (smoking, physical activity, diet, BMI, and sleep duration). Lifestyle assessed at baseline (2006-2009), the first follow-up assessment (2012-2013) and the second follow-up assessment (since 2014) were used to derive the trajectories of each individual. The joint categories were created through cross-classifying three baseline lifestyle categories (ideal, intermediate and poor) by three lifestyle trajectory categories (improve, maintain and decline).

RESULTS

During a median follow-up period of 4.2 years, 868 IHD events were recorded. The hazard ratio (HR) of incident IHD associated with per unit increase in unhealthy lifestyle trajectory was 1.08 (95% confidence interval (CI): 0.99-1.17). Subgroup analyses indicated such association was stronger among individuals with hypertension (HR: 1.13, 95%CI: 1.03-1.24), diabetes (HR: 1.23, 95%CI: 0.96-1.58) or hyperlipidemia (HR: 1.09, 95%CI: 0.97-1.22). Compared with participants consistently adhering to an ideal lifestyle (ideal-maintain), the HRs of incident IHD were: 1.30 (1.07-1.58) for intermediate-maintain, 1.52 (1.23-1.88) for poor-maintain, 1.25 (0.93-1.68) for intermedia-improve, 1.48 (1.17-1.88) for poor-improve, 1.46 (1.08-1.99) for intermedia-decline and 1.77 (1.21-2.59) for poor-decline.

CONCLUSIONS

A declined lifestyle trajectory increased the risk of incident IHD, irrespective of baseline lifestyle levels. Individuals with hypertension, diabetes or hyperlipidemia were more predisposed to the influence of lifestyle change.

Preference for Stronger Taste Associated with a Higher Risk of Hypertension: Evidence from a Cross-Sectional Study in Northwest China

Background. Dietary modulation is a primary lifestyle approach for reducing the risk of hypertension. However, evidence of the potential role that a dietary taste preference plays in the risk of hypertension remains limited. Methods. A cross-sectional analysis was conducted based on the Shaanxi baseline survey of the Regional Ethnic Cohort Study. We used self-reported salt consumption and intensity preferences for sourness and spiciness to calculate the taste preference score, which was categorized into bland, moderate, and strong. A generalized linear mixed model and quantile regression were performed to estimate associations between taste preferences and hypertension/blood pressure. Results. Among 27,233 adults, 72.2% preferred a moderate taste and 21.4% preferred a strong taste. Compared with a bland taste, a stronger taste preference might be associated with a higher risk of hypertension (adjusted OR for a moderate taste = 1.25, 95% CI: 1.06, 1.49; adjusted OR for a strong taste = 1.41, 95% CI: 1.15, 1.71; Ptrend = 0.002), especially in females (adjusted OR for a moderate taste = 1.43, 95% CI: 1.24, 1.66; adjusted OR for a strong taste = 1.55, 95% CI: 1.32, 1.83; $P_{\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{n}\mathrm{d}}<0.001$ ). Quantile regression showed that the taste preference was positively associated with diastolic blood pressure (DBP) (P5-P80) in females, with an average increase of 3.31 mmHg for a strong taste (β = 3.31, $P<0.001$ ) and 1.77 mmHg for a moderate taste (β = 1.77, P = 0.008). Conclusions. A preference for stronger multitastes of salty, sour, and spicy might be associated with a higher risk of hypertension, especially in females. This relationship possibly occurs through increasing DBP. Dietary modulation with the promotion of a bland taste is encouraged.

Higher Adherence to Healthy Lifestyle Score Is Associated with Lower Odds of Non-Alcoholic Fatty Liver Disease

Growing evidence supports that individual lifestyle factors contribute to the development of non-alcoholic fatty liver disease (NAFLD) without considering the coexistence and synergistic effect of lifestyle factors. Our aim is to derive a healthy lifestyle score (HLS) and estimate its association with NAFLD. In this nationwide cross-sectional study, we derived a five-item HLS including dietary pattern, body mass index, physical activity, cigarette smoking, and sleep duration. NAFLD and clinically significant fibrosis (CSF) were assessed based on vibration-controlled transient elastography (VCTE). Liver function parameters were also tested. Multivariable logistic and linear regressions were applied to investigate the association between HLS and liver diseases. Of the 3893 participants with VCTE examination, approximately 14.1% of participants possessed zero or one healthy lifestyle, 62.5% possessed two or three healthy lifestyles, and 23.4% possessed four or five healthy lifestyles. Compared with participants with a low HLS (0−1 score), the adjusted odds ratios and 95% confidence intervals for those with a high HLS (4−5 score) were 0.25 (0.19~0.33, Ptrend < 0.001) for NAFLD and 0.30 (0.18~0.50, Ptrend < 0.001) for CSF. HLS was positively associated with albumin, total protein, and total bilirubin (all Ptrend ≤ 0.001), and was inversely associated with globulin, alanine aminotransferase, and gamma-glutamyl transaminase (all Ptrend ≤ 0.003). Higher adherence to HLS is associated with lower odds of NAFLD and CSF and may improve liver function. Strategies for the promotion of a healthy lifestyle should be considered as part of NAFLD prevention.

Socio-demographic factors and healthy lifestyle behaviours among Malaysian adults: National Health and Morbidity Survey 2019

This study aimed to investigate the association between socio-demographic factors and designated healthy lifestyle behaviours in a nationally-representative sample of Malaysian adults aged 18 years and above. Secondary data involving 7388 participants aged 18-96 years from the National Health and Morbidity Survey 2019, a national cross-sectional survey, was used in this study. A healthy lifestyle score (0-5 points) was calculated based on five modifiable lifestyle factors: non-smoker, body mass index < 25 kg/m², physically active, moderate (or less) alcohol intake, and daily consumption of ≥ 5 servings of fruits and vegetables. Associations between socio-demographic factors and healthy lifestyle behaviours were examined using multinomial logistic regression adjusted for sampling design. About 30.6% of the participants met at least four out of the five healthy lifestyle factors. In multinomial model, subjects who were female (aOR = 3.26, 95%CI = 2.58, 4.12), of Chinese (aOR = 2.31, 95%CI = 1.62, 3.30 or other ethnicity (aOR = 1.44, 95%CI = 1.05, 1.98), and aged 18-30 years (aOR = 1.74, 95% CI = 1.12, 2.71) showed significant association with achieving healthy lifestyle compared to male, Malay and ≥ 61 years old as reference categories. Our results indicated that gender, age and ethnicity associated with healthy lifestyle behaviours. Information on the influence of socio-demographic factors on the prevalence of healthy lifestyles will facilitate the development of effective intervention strategies to improve the adaptation of healthy lifestyle practices.