Favorable Lifestyle Research Articles

Plasma metabolites, systolic blood pressure, lifestyle and stroke risk: a UK Biobank based cohort study.

Background To estimate the associations of stroke risk with plasma metabolites, metabolic risk score (MRS), the combinations of MRS with hypertension or lifestyle, and lifestyle-related metabolic signature. To assess the improvement of the stroke risk prediction model through the incorporation of MRS. Methods A total of 77,315 participants from the UK Biobank were included in this study. Xgboost and LASSO-COX regression were used to select metabolites and construct MRS. Elastic net regression was utilized to construct the lifestyle-related metabolic signature. Multivariate Cox regression was used to estimate the associations between metabolites, MRS, the combinations of MRS with hypertension or lifestyle, lifestyle-related metabolic signature and stroke risk. Results We identified 48, 63, 39, and 4 metabolites associated with the risk of stroke, ischemic stroke (IS), subarachnoid hemorrhage (SAH), and intracerebral hemorrhage (ICH), respectively. High MRS significantly increased the risk of stroke (HR= 2.65 [95%CI 2.09-3.35]), IS (HR= 2.45 [95%CI 1.89-3.17]), ICH (HR= 2.74 [95%CI 1.55-4.85]), and SAH (HR= 4.64 [95%CI 2.25-9.56]). In the combination analyses, compared with normal SBP and low MRS, normal/high SBP and high MRS significantly increased stroke risk (HR= 5.80 [95% CI: 2.75-12.27]/6.37 [95% CI 3.22-12.62]). A favorable/unfavorable lifestyle and high MRS also significantly increased stroke risk (HR= 2.38 [95% CI: 1.73-3.28]/3.86 [95% CI 2.63-5.67]) compared with a favorable lifestyle and low MRS. Incorporating MRS into the 15-year stroke and IS risk prediction model increased the AUCs from 0.746 to 0.766 and from 0.771 to 0.811, respectively. The metabolic signature was correlated with adherence to a healthy lifestyle (r = 0.414; P = 2.22e-16) and inversely associated with stroke risk (HR= 0.80 [95% CI 0.73-0.86]). Conclusions Various metabolites and MRS were significantly associated with the risk of stroke, IS, ICH and SAH. Individuals with a high MRS may face an elevated stroke risk among populations with high SBP or unhealthy lifestyle, even those with normal SBP or healthy lifestyle. MRS provided modest improvement to the stroke risk prediction model. The lifestyle-related metabolic signature could reduce 20% stroke risk.

Cardiovascular risk according to genetic predisposition to gout, lifestyle and metabolic health across prospective European and Korean cohorts

ObjectiveRecent studies have reported that gout is associated with a risk of cardiovascular disease (CVD) later in life. However, the predictive value of genetic predisposition to gout combined with lifestyle...

Associations of socioeconomic status and healthy lifestyle with incident dementia and cognitive decline: two prospective cohort studies

Little is known about the complex associations of socioeconomic status (SES) and healthy lifestyle with cognitive dysfunction. Using data from the Health and Retirement Study (HRS) [2008-2020] and the English Longitudinal Study of Ageing (ELSA) [2004-2018], SES was constructed by latent class analysis using education level, total household income and wealth. Overall healthy lifestyle was derived using information on never smoking, low to moderate alcohol consumption (drinks/day: (0, 1] for women and (0, 2] for men), top tertile of physical activity, and active social contact. A total of 12,437 and 6565 participants from the HRS and ELSA were included (40.8% and 46.0% men and mean age 69.3 years and 65.1 years, respectively). Compared with participants of high SES, those of low SES had higher risk of incident dementia (hazard ratio 3.17, 95% confidence interval 2.72-3.69 in the HRS; 1.43, 1.09-1.86 in the ELSA), and the proportions mediated by overall lifestyle were 10.4% (7.3%-14.6%) and 2.7% (0.5%-14.0%), respectively. Compared with participants of high SES and favorable lifestyle, those with low SES and unfavorable lifestyle had a higher risk of incident dementia (4.27, 3.40-5.38 in the HRS; 2.02, 1.25-3.27 in the ELSA) and accelerated rate of global cognitive decline (β=-0.058 SD/year; 95% CI:-0.073,-0.043 in the HRS; β=-0.049 SD/year; 95% CI:-0.063,-0.035 in the ELSA). Unhealthy lifestyle only mediated a small proportion of the socioeconomic inequality in dementia risk in both US and UK older adults. This work was supported by grants from the National Natural Science Foundation of China (82088102 and 82370819), the National Key R&D Program of China (2023YFC2506700), the Shanghai Municipal Government (22Y31900300), the Shanghai Clinical Research Center for Metabolic Diseases (19MC1910100), the Innovative Research Team of High-Level Local Universities in Shanghai, the Special Project for Clinical Research in Health Industry of Shanghai Municipal Health Commission (202340084), and Ruijin Hospital Youth Incubation Project (KY20240805). Y.X. is supported by the National Top Young Talents program.

Disturbed glucose homeostasis and its increased allostatic load in response to individual, joint and fluctuating air pollutants exposure: Evidence from a longitudinal study in prediabetes

We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3−, NH4+, OM, SO42−, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018–2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.

Association of healthy lifestyle factors and genetic liability with bipolar disorder: Findings from the UK Biobank

BackgroundThe interplay between genetic and lifestyle factors in the development of bipolar disorder (BD) remains unclear. MethodsA cohort study was carried out on 365,517 participants from the UK Biobank. Lifestyle scores, based on smoking, physical activity, diet, alcohol consumption, sedentary behavior, sleep duration, and social contact, were grouped as favorable (scores 6–7), intermediate (scores 4–5), or unfavorable (scores 0–3). The BD polygenic risk score (PRS) was also categorized into high, intermediate, and low-risk groups using PRS tertiles. Cox regression models determined hazard ratios (HRs) and 95 % confidence intervals (CIs) for BD. ResultsDuring the 12.9-year follow-up, 529 individuals developed BD. Comparing those with favorable lifestyles to those with unfavorable participants, the HR of developing BD was 3.28 (95 % CI, 2.76–3.89). Similarly, individuals with a high PRS had a risk of 3.20 (95 % CI, 2.83–3.63) compared to those with a low PRS. Notably, individuals with both a high PRS and an unfavorable lifestyle had a significantly higher risk of BD (HR = 6.31, 95 % CI, 4.14–9.63) compared to those with a low PRS and a favorable lifestyle. Additionally, the interaction between PRS and lifestyle contributed an additional risk, with a relative excess risk of 1.74 (95 % CI, 0.40–3.07) and an attributable proportion due to the interaction of 0.37 (95 % CI, 0.16–0.58). ConclusionsOur findings suggest that genetic liability for BD, measured as PRS, and lifestyle have an additive effect on the risk of developing BD. A favorable lifestyle was associated with a reduced risk of developing BD.

Modifiable lifestyle factors and the risk of post-COVID-19 multisystem sequelae, hospitalization, and death

Effective prevention strategies for post-COVID complications are crucial for patients, clinicians, and policy makers to mitigate their cumulative burden. This study evaluated the association of modifiable lifestyle factors (smoking, alcohol intake, BMI, physical activity, sedentary time, sleep duration, and dietary habits) with COVID-19 multisystem sequelae, death, and hospitalization in the UK Biobank cohort (n = 68,896). A favorable lifestyle (6-10 healthy factors; 46.4%) was associated with a 36% lower risk of multisystem sequelae (HR, 0.64; 95% CI, 0.58-0.69; ARR at 210 days, 7.08%; 95% CI, 5.98-8.09) compared to an unfavorable lifestyle (0-4 factors; 12.3%). Risk reductions spanned all 10 organ systems, including cardiovascular, coagulation, metabolic, gastrointestinal, kidney, mental health, musculoskeletal, respiratory disorders, and fatigue. This beneficial effect was largely attributable to direct lifestyle impacts independent of corresponding pre-infection comorbidities (71% for any sequelae). A favorable lifestyle was also related to the risk of post-COVID death (HR 0.59, 0.52-0.66) and hospitalization (HR 0.78, 0.73-0.84). These associations persisted across acute and post-acute infection phases, irrespective of hospitalization status, vaccination, or SARS-CoV-2 variant. These findings underscore the clinical and public health importance of adhering to a healthy lifestyle in mitigating long-term COVID-19 adverse impacts and enhancing future pandemic preparedness.

Adverse childhood experience, adopting a healthy lifestyle in adulthood, and risk of cardiovascular diseases

BackgroundBoth adverse childhood experiences (ACEs) and lifestyle factors have been associated with risk of cardiovascular diseases (CVDs) in later life, but whether and to what extent adherence to a healthy lifestyle in adulthood can offset the increased cardiovascular risk associated with ACEs is unclear. We aimed to determine whether and to what extent adopting to a healthy lifestyle in adulthood can offset the risk of CVDs in individuals according to their ACEs. MethodsA prospective cohort study included 143,869 participants aged 38–72 years, free of CVDs at baseline from the UK Biobank. The history of ACEs was assessed using the Childhood Trauma Screener. Participants were divided into three risk groups based on ACEs: low (no ACEs), intermediate (one or two ACEs), and high (three or more ACEs). A healthy lifestyle score in adulthood was constructed as the sum of four modifiable lifestyle factors (no smoking, adequate physical activity, healthy diet, no obesity), and participants were then categorized into three groups based on this score (unfavorable [0–1 point], intermediate [2–3 points], favorable [4 points]). Cox proportional hazard models were conducted to investigate the association between ACEs, healthy lifestyle, and incident CVDs. ResultsDuring a median follow-up of 12.49 years, 13,373 incident cases of overall CVDs were identified. This included 7521 cases of coronary heart disease (CHD), 6175 cases of atrial fibrillation (AF) and 1813 cases of stroke. Individuals with high ACEs had a greater risk of incident overall CVDs (hazard ratio [HR] = 1.39, [95%CI = 1.29 to 1.50]), CHD (1.50 [1.36 to 1.65]) and AF (1.18 [1.05 to 1.33]) compared to those with low ACEs. The risk of CVDs decreased moving from unfavorable to favorable lifestyle categories (P for trend<0.001), with the lowest risk observed among individuals with a favorable lifestyle (0.70 [0.66 to 0.74] for overall CVDs, 0.69 [0.64 to 0.75] for CHD, and 0.71 [0.65 to 0.78] for AF). Participants with high ACEs and a favorable lifestyle had a 39 %, 40 % and 47 % lower risk of developing overall CVDs (0.61 [0.48 to 0.76]), CHD (0.60 [0.44 to 0.81], and AF (0.53 [0.36 to 0.77]) than those with high ACEs and an unfavorable lifestyle. ConclusionsHaving a healthy lifestyle in adulthood could substantially attenuate the increased risk of overall CVDs, CHD, and AF conferred by ACEs.

Multimodal Machine Learning-Based Marker Enables Early Detection and Prognosis Prediction for Hyperuricemia.

Hyperuricemia (HUA) has emerged as the second most prevalent metabolic disorder characterized by prolonged and asymptomatic period, triggering gout and metabolism-related outcomes. Early detection and prognosis prediction for HUA and gout are crucial for pre-emptive interventions. Integrating genetic and clinical data from 421287 UK Biobank and 8900 Nanfang Hospital participants, a stacked multimodal machine learning model is developed and validated to synthesize its probabilities as an in-silico quantitative marker for hyperuricemia (ISHUA). The model demonstrates satisfactory performance in detecting HUA, exhibiting area under the curves (AUCs) of 0.859, 0.836, and 0.779 within the train, internal, and external test sets, respectively. ISHUA is significantly associated with gout and metabolism-related outcomes, effectively classifying individuals into low- and high-risk groups for gout in the train (AUC, 0.815) and internal test (AUC, 0.814) sets. The high-risk group shows increased susceptibility to metabolism-related outcomes, and participants with intermediate or favorable lifestyle profiles have hazard ratios of 0.75 and 0.53 for gout compared with those with unfavorable lifestyles. Similar trends are observed for other metabolism-related outcomes. The multimodal machine learning-based ISHUA marker enables personalized risk stratification for gout and metabolism-related outcomes, and it is unveiled that lifestyle changes can ameliorate these outcomes within high-risk group, providing guidance for preventive interventions.

Association of solid fuel use with cognitive function and the modifying role of lifestyle: A nationwide cohort study in China

BackgroundAs opposed to a healthy lifestyle, indoor air pollution from solid fuel use may be harmful for cognitive function. However, the extent to which lifestyle modifies the association between solid fuel use and cognitive function remains unknown. MethodsA total of 21,008 individuals aged 16 to 92 were enrolled in 2010 and followed up to 2014 in the China Family Panel Studies (CFPS). Cognitive function was assessed using standardized math and word tests in two waves. Solid fuel use at baseline was assessed by self-reporting of firewood, straw, or coal used for cooking. Lifestyle profile was classified into two groups (favorable vs. unfavorable) based on five modifiable lifestyle factors including alcohol drinking, smoking, body mass index, diet, and physical activity. Linear mixed-effects models were employed to assess the association of solid fuel use and lifestyle with cognitive function. The effect modification of lifestyle was analyzed. ResultsA total of 49.7% of the study population used solid fuels for cooking and 17.4% had a favorable lifestyle. Solid fuel use was associated with a significant decrease in cognitive function (β = −0.29, 95% CI: −0.39, −0.19 for math test; β = −0.62, 95% CI: −0.84, −0.41 for word test). Lifestyle significantly modified this association (p-interaction: 0.006 for math test; 0.016 for word test), with the corresponding association being less pronounced among participants adhering to a favorable lifestyle compared to those with an unfavorable lifestyle. ConclusionA favorable lifestyle may attenuate the adverse association between solid fuel use and cognitive function. Adopting a favorable lifestyle has the potential to mitigate the adverse neurological effects due to indoor air pollution.

Lifestyle modifies the associations of early-life smoking behaviors and genetic susceptibility with type 2 diabetes: A prospective cohort study involving 433,872 individuals from UK Biobank

BackgroundTo investigate whether and what lifestyle factors in later life modify the associations of early-life smoking behaviors and genetic susceptibility with type 2 diabetes (T2D). MethodsIn the UK Biobank, in utero tobacco exposure (n=354,493) and age of smoking initiation (n=353,557) were self-reported. A composite lifestyle score was calculated based on diet, physical activity, nicotine exposure, sleep duration, and BMI. Hazard ratio (HR) and absolute risk difference (ARD) were used to estimate the associations of early-life smoking behaviors and genetic risk with incident T2D, as well as the effect modification of the lifestyle score. ResultsDuring a median follow-up of 14.6 years, the HRs (95% CIs) of T2D for in utero tobacco exposure, and smoking initiation in adulthood, adolescence, and childhood, compared with no smoking behavior, were 1.19 (1.16-1.23), 1.34 (1.29-1.39), 1.58 (1.53-1.64), 2.22 (2.11-2.32), respectively (P for trend<0.001). Early-life smoking behaviors and high genetic risk (vs no smoking behavior and low genetic risk) were associated with a 302%-593% higher T2D risk (P for additive interaction<0.05). Compared to participants with early-life smoking behaviors, high genetic risk, and an unfavorable lifestyle, those who adhered to a favorable lifestyle had a lower T2D risk in all subgroups (HRs from 0.05 to 0.36 and ARD from -14.97% to -9.51%), with the highest ARD attributable to lifestyle in participants with early-life smoking behaviors and high genetic risk. ConclusionsThe T2D risk associated with early-life smoking behaviors and genetic risk was modified by a favorable lifestyle.

Association between Lifestyle Modification and All-Cause, Cardiovascular, and Premature Mortality in Individuals with Non-Alcoholic Fatty Liver Disease.

This study is designed to explore the correlation between multiple healthy lifestyles within the framework of "lifestyle medicine", and the mortality risk of nonalcoholic fatty liver disease (NAFLD). The National Health and Nutrition Examination Survey (NHANES) database was employed. The analysis consisted of 5542 participants with baseline NAFLD and 5542 matched non-NAFLD participants from the database. Lifestyle information, including five low risk factors advocated by lifestyle medicine (healthy diet, vigorous physical activity, healthy sleep duration, avoiding smoking, and maintaining a non-depressed psychological status), was collected through a baseline questionnaire. Cox proportional hazards regression models and Kaplan-Meier survival curve were used to evaluate risk of mortality. In addition, subgroups were analyzed according to gender, age, body mass index and waist circumference. In total, 502 deaths (n = 181 deaths from cardiovascular disease (CVD)) were recorded among NAFLD participants after the median follow up duration of 6.5 years. In the multivariate-adjusted model, compared to participants with an unfavorable lifestyle (scoring 0-1), NAFLD participants with a favorable lifestyle (scoring 4-5) experienced a 56% reduction in all-cause mortality and a 66% reduction in CVD mortality. Maintaining an undepressed psychological state and adhering to vigorous exercise significantly reduced CVD mortality risk in NAFLD participants (HR, 0.64 [95% CI, 0.43-0.95]; HR, 0.54 [95% CI, 0.33-0.88]) while maintaining healthy sleep reduced premature mortality due to CVD by 31%. Healthy lifestyle, characterized by maintaining an undepressed mental state and healthy sleep, significantly mitigates the risk of all-cause, CVD, and premature mortality risk among NAFLD patients, with a particularly pronounced effect observed in female and obese subpopulations.

The Impact of Lifestyle on Cardiovascular Risk in Patients with Gout: a Population-based Cohort Study.

Gout is associated with a significant burden of cardiovascular disease. The aim of this study was to evaluate the impact of a favorable lifestyle on incident cardiovascular events in patients with gout. We identified 9110 patients with gout from the UK Biobank cohort based on self-report and/or hospital diagnostic codes. Lifestyle behaviors, including smoking status, physical activity, obesity, and diet, were categorized into three patterns: favorable (3-4 healthy factors), intermediate (2 healthy factors), and unfavorable (0-1 healthy factor). The cardiovascular risk of participants with and without gout was estimated based on their serum uric acid levels and lifestyle patterns. Among 9110 patients with gout and 457596 participants without gout, the median follow-up duration was 8.9 years. The incidence rate of cardiovascular disease was significantly higher in the gout population than in the non-gout population (11.38vs 5.49 per 1000 person-years). The gout population consistently exhibited a high cardiovascular risk, irrespective of uric acid levels, whereas a positive correlation was observed between uric acid levels and cardiovascular risk in the non-gout population. Adopting a favorable lifestyle pattern was associated with a lower risk of cardiovascular disease in both gout and non-gout populations. Across all categories of uric acid, a favorable lifestyle was found to reduce cardiovascular risk in patients with gout. Patients with gout remain at high risk of developing cardiovascular disease despite having normal uric acid levels. Lifestyle modifications may represent an effective and cost-efficient therapeutic approach for preventing cardiovascular events in this population.

Mid-to-Late Life Healthy Lifestyle Modifies Genetic Risk for Longitudinal Cognitive Aging among Asymptomatic Individuals.

Genetic and lifestyle factors contribute to an individual's risk of developing Alzheimer's disease. However, it is unknown whether and how adherence to healthy lifestyles can mitigate the genetic risk of Alzheimer's. The aim of this study is to investigate whether adherence to healthy lifestyles can modify the impact of genetic predisposition to Alzheimer's disease on later-life cognitive decline. This prospective cohort study included 891 adults of European ancestry, aged 40 to 65, who were without dementia and had complete healthy-lifestyle and cognition data during the follow-up. Participants joined the Wisconsin Registry for Alzheimer's Prevention (WRAP) beginning in 2001. We conducted replication analyses using a subsample with similar baseline age range from the Health and Retirement Study (HRS). We assessed participants' exposures using a continuous non-APOE polygenic risk score for Alzheimer's, a binary indicator for APOE-ε4 carrier status, and a weighted healthy-lifestyle score, including factors such as no current smoking, regular physical activity, healthy diet, light to moderate alcohol consumption, and frequent cognitive activities. We z-standardized cognitive scores for global (Preclinical Alzheimer's Cognitive Composite score 3 - PACC3) and domain-specific assessments (delayed recall and immediate learning). We followed 891 individuals for up to 10 years (mean [SD] baseline age, 58 [6] years, 31% male, 38% APOE-ε4 carriers). After false discovery rate (FDR) correction, we found statistically significant PRS × lifestyle × age interactions on preclinical cognitive decline but the evidence is stronger among APOE-ε4 carriers. Among APOE-ε4 carriers, PRS-related differences in overall and memory-related domains between people scoring 0-1 and 4-5 regarding healthy lifestyles became evident around age 67 after FDR correction. These findings were robust across several sensitivity analyses and were replicated in the population-based HRS. A favorable lifestyle can mitigate the genetic risk associated with current known non-APOE genetic variants for longitudinal cognitive decline, and these protective effects are particularly pronounced among APOE-ε4 carriers.

Association between essential metals, adherence to healthy lifestyle behavior, and ankle-brachial index

BackgroundAnkle-brachial index (ABI) is a noninvasive diagnostic method for peripheral arterial disease (PAD) and a predictor of cardiovascular events. ObjectiveThe present study aimed to evaluate the association between individual or combined essential metals and ABI, as well as assess the collective impact of essential metals when coupled with healthy lifestyle on ABI. MethodsA total of 2865 participants were recruited in Wuhan Tongji Hospital between August 2018 and March 2019. Concentrations of essential metals in urine were measured by inductively coupled plasma mass spectrometer. ResultsThe results of general linear regression models demonstrated that after adjusting for confounding factors, there was a positive association between ABI increase and per unit increase of log 10-transformed, creatinine-corrected urinary Cr (β (95 % CI): 0.010 (0.004, 0.016), PFDR = 0.007), Fe (β (95 % CI): 0.010 (0.003, 0.017), PFDR = 0.018), and Co (β (95 % CI): 0.013 (0.005, 0.021), PFDR = 0.007). The WQS regression revealed a positive relationship between the mixture of essential metals and ABI (β (95 % CI): 0.006 (0.003, 0.010), P < 0.001), with Cr and Co contributing most to the relationship (weighted 45.48 % and 40.14 %, respectively). Compared to individuals with unfavorable lifestyle and the lowest quartile of Cr, Fe and Co, those with favorable lifestyle and the highest quartile of Cr, Fe and Co exhibited the most increase in ABI (β (95 % CI): 0.030 (0.017, 0.044) for Cr, β (95 % CI): 0.027 (0.013, 0.040) for Fe, and β (95 % CI): 0.030 (0.016, 0.044) for Co). ConclusionIn summary, our study indicates that adequate essential metal intake together with healthy lifestyle behaviors perform crucial roles in PAD protection.

Favorable Lifestyle Behaviors as Reverse Risk Factors and Treatment for Postpartum Depression

Background. Lifestyle behaviors such as sleep, sedentary behavior, physical activity (PA) or exercise, and diet may influence risk for postpartum depression (PPD) or serve as treatment options for those diagnosed with PPD. The purpose of this review was to summarize existing research about four key lifestyle behaviors (sleep, sedentary behavior, PA and exercise, and diet) and their potential influence on PPD. Methods. Studies that were published in English after 2000 were drawn from the PubMed database. Observational studies, systematic reviews, meta-analyses, and randomized, controlled trials that enrolled &gt;50 participants were considered for inclusion. Results. Quality sleep and PA or exercise during pregnancy and the postpartum period may reduce PPD risk or help improve PPD symptoms. Data regarding the utility of intervening on diet patterns or specific nutrients for lessening PPD risk or serving as PPD treatment are inconsistent. Evidence for vitamin D supplementation is extensive, while evidence supporting other vitamins, nutrients, and minerals remains inconclusive. Research linking sedentary behavior and PPD is extremely limited. Conclusion. Sleep quality and PA or exercise may reduce the risk of PPD or mitigate its symptoms. Further high- quality research studies examining the relationship between sedentary behavior and PPD risk are necessary. Healthy lifestyle behaviors, alone or in conjunction with other evidence-based strategies recommended by healthcare providers, may serve as effective preventive measures and treatments for PPD in the pregnancy and postpartum periods.

Lifestyle and genetic predisposition are associated with incident irritable bowel syndrome: A population-based prospective cohort study

Few prospective studies have investigated the joint effect of lifestyle factors and genetic susceptibility on the risk of irritable bowel syndrome (IBS). This study aims to evaluate the associations of lifestyle and genetic factors with incident IBS in the UK Biobank. We analyzed data from 481,057 participants (54% female) without prevalent IBS at enrollment in the UK Biobank. An overall healthy lifestyle was defined using six modifiable lifestyle factors, including smoking, body mass index (BMI), sleep duration, diet, physical activity, and alcohol consumption, and hence categorized into ‘favorable’, ‘intermediate’, and ‘unfavorable’ lifestyles. A Cox proportional hazard model was used to investigate the association between a healthy lifestyle and incident IBS. Furthermore, we constructed a polygenic risk score (PRS) for IBS and assessed whether lifestyle modified the effect of genetics on the development of IBS. During a median follow-up of 12.1 years, 8,645 incident IBS were ascertained. Specifically, among the six modifiable lifestyle factors, adequate sleep demonstrates the greatest protective effect (hazard ratio [HR]: 0.72, 95% CI: 0.69,0.75) against IBS.Compared with a favorable lifestyle, an unfavorable lifestyle was associated with a 56% (95% CI: 46%-67%) increased risk of IBS (P = 8.99×10-40). The risk of incident IBS was 12% (95% CI: 4%-21%) higher among those at high genetic risk compared with those at low genetic risk (P = 0.005). When considering the joint effect of lifestyle and genetic susceptibility, the HR nearly doubled among individuals with high genetic risk and unfavorable lifestyle (HR: 1.80; 95% CI:1.51-2.15; P = 3.50×10-11) compared to those with low genetic risk and favorable lifestyle. No multiplicative or addictive interaction was observed between lifestyle and genetics. The findings from this study indicated that lifestyle and genetic factors were independently associated with the risk of incident IBS. All these results implicated a possible clinical strategy of lowering the incidence of IBS by advocating a healthy lifestyle.

Abstract 3035: Associations Of Genetic And Lifestyle Risk Factors With Incident Peripheral Artery Disease: A Prospective Cohort Study

Background: The joint associations between genetic and lifestyle factors, and peripheral artery disease (PAD) remain unclear, yet understanding the connections is crucial for precise PAD prevention. Methods: Genetic susceptibility to PAD was estimated by a polygenic risk score of 50 genetic variants selected by P &lt; 5х10 -8 and r 2 &lt;0.01 from a GWAS including 31,307 cases. Tertiles categorized genetic risk into low, intermediate, and high. A healthy lifestyle score was constructed based on 4 lifestyle factors (never smoking, non-excessive alcohol consumption, high cardiometabolic healthy diet adherence, and regular physical activity) and categorized into favorable (3-4 healthy factors), intermediate (2 healthy factors), and unfavorable (0-1 healthy factors) groups. Cox regression estimated hazard ratios (HR) and 95% confidence interval (CI) with adjustment for age (time scale), sex, BMI, education, baseline cardiovascular risk factors, 20 principal components. Results: Over 11.9 years, 4299 incident PAD cases were diagnosed in 379,228 UK Biobank participants free of baseline PAD. Genetic risk and unhealthy lifestyle categories were monotonically associated with PAD. Compared with low genetic risk, the HR was 1.69 (95% CI 1.56-1.89) for high genetic risk. Compared with favorable lifestyle, the HR for unfavorable lifestyle was 2.70 (95% CI 2.50-2.94). There was no multiplicative interaction between genetic and lifestyle factors ( P = 0.461). The association between unfavorable lifestyle and higher PAD risk was consistent in genetic risk groups. Joint categorization analysis detected an HR for high genetic risk and favorable lifestyle was (1.85, 95% CI 1.54-2.22) reducing by &gt; 50%, compared with high genetic risk and unfavorable lifestyle (HR 4.76, 95% CI 4.00-5.56). Conclusions: Genetic and lifestyle factors independently associated with incident PAD. Adhering to a favorable lifestyle substantially reduced PAD risk, even in individuals at high genetic risk.

Optimizing type 2 diabetes management: AI-enhanced time series analysis of continuous glucose monitoring data for personalized dietary intervention.

Despite advanced health facilities in many developed countries, diabetic patients face multifold health challenges. Type 2 diabetes mellitus (T2DM) go along with conspicuous symptoms due to frequent peaks, hypoglycemia <=70 mg/dL (while fasting), or hyperglycemia >=180 mg/dL two hours postprandial, according to the American Diabetes Association (ADA)). The worse effects of Type 2 diabetes mellitus are precisely associated with the poor lifestyle adopted by patients. In particular, a healthy diet and nutritious food are the key to success for such patients. This study was done to help T2DM patients improve their health by developing a favorable lifestyle under an AI-assisted Continuous glucose monitoring (CGM) digital system. This study aims to reduce the blood glucose level fluctuations of such patients by rectifying their daily diet and maintaining their exertion vs. food consumption records. In this study, a well-precise prediction is obtained by training the ML model on a dataset recorded from CGM sensor devices attached to T2DM patients under observation. As the data obtained from the CGM sensor is time series, to predict blood glucose levels, the time series analysis and forecasting are done with XGBoost, SARIMA, and Prophet. The results of different Models are then compared based on performance metrics. This helped in monitoring various trends, specifically irregular patterns of the patient's glucose data, collected by the CGM sensor. Later, keeping track of these trends and seasonality, the diet is adjusted accordingly by adding or removing particular food and keeping track of its nutrients with the intervention of a commercially available all-in-one AI solution for food recognition. This created an interactive assistive system, where the predicted results are compared to food contents to bring the blood glucose levels within the normal range for maintaining a healthy lifestyle and to alert about blood glucose fluctuations before the time that are going to occur sooner. This study will help T2DM patients get in managing diabetes and ultimately bring HbA1c within the normal range (<= 5.7%) for diabetic and pre-diabetic patients, three months after the intervention.

Genetic predisposition, modifiable lifestyles, and their joint effects on human lifespan: evidence from multiple cohort studies

ObjectiveTo investigate the associations across genetic and lifestyle factors with lifespan.DesignA longitudinal cohort study.SettingUK Biobank.Participants353 742 adults of European ancestry, who were recruited from 2006 to 2010 and were followed...

Clustering of lifestyle risk factors in relation to suicidal thoughts and behaviors in young adolescents: a cross-national study of 45 low- and middle-income countries

BackgroundPrior research has reaffirmed lifestyle risk behaviors to cluster among adolescents. However, the lifestyle cluster effect on suicidal thoughts and behaviors (STBs) was unclear among adolescents in low- and middle-income countries (LMICs). No comparison of such associations was conducted across nations.MethodsData from 45 LMICs were obtained from the Global School-based Student Health Survey (GSHS) between 2009 and 2019. Lifestyle behavior factors were collected through a structured questionnaire. Suicidal ideation, plan, and attempt were ascertained by three single-item questions. Lifestyle risk scores were calculated via a sufficient dimension reduction technique, and lifestyle risk clusters were constructed using a latent class analysis. Generalized linear mixed models with odds ratio (OR) and 95% confidence interval (CI) were used to estimate the lifestyle-STB associations.ResultsA total of 229,041 adolescents were included in the final analysis. The weighted prevalence of suicidal ideation, plan, and attempt was 7.37%, 5.81%, and 4.59%, respectively. Compared with the favorable lifestyle group, the unfavorable group had 1.48-, 1.53-, and 3.11-fold greater odds of suicidal ideation (OR = 1.48, 95%CI: 1.30–1.69), plan (OR = 1.53, 95%CI 1.34–1.75), and attempt (OR = 3.11, 95%CI 2.64–3.65). Four clusters of lifestyle risk behaviors were identified, namely healthy lifestyles (H–L), insufficient intake of vegetables and fruit (V-F), frequent consumption of soft drinks and fast food (D-F), and tobacco smoking and alcohol drinking (S-A) clusters. Compared with H–L cluster, V-F cluster was associated with 43% and 42% higher odds of suicidal ideation and plan, followed by S-A cluster (26% for ideation and 20% for plan), but not significant in D-F cluster (P > 0.05). D-F cluster was associated with 2.85-fold increased odds of suicidal attempt, followed by V-F cluster (2.43-fold) and S-A cluster (1.18-fold).ConclusionsClustering of lifestyle risk behaviors is informative for risk stratification of STBs in resource-poor settings. Lifestyle-oriented suicide prevention efforts should be initiated among school-attending adolescents in LMICs.