Klemera-Doubal Method Research Articles

The Association Between Accelerated Biological Aging and Cardiovascular Outcomes in Older Adults with Hypertension.

Current hypertension treatments rely on chronological age, which may not reflect individual differences in aging and its impact on cardiovascular health. This study aimed to determine whether biological age can predict adverse outcomes in older adults with hypertension, independent of traditional risk factors including chronological age. An analysis of a prospective cohort was conducted using data from the Health and Retirement Study, a longitudinal survey of older adults in the United States. The Klemera-Doubal method was employed to calculate the biological age of the participants with hypertension at the time of enrollment in 2016. Discrete-time survival analysis was conducted to analyze the relationship between accelerated biological aging and the risk of mortality, heart disease, and stroke over four years of follow-up. A total of 4,442 individuals were analyzed. Of these, 2,438 showed decelerated aging, whereas 2,004 experienced accelerated aging (biological age > chronological age). The median age of the patients in both groups was around 70 years. Both groups had similar racial and ethnic distributions and predominantly consisted of non-Hispanic whites. The accelerated aging group had a higher prevalence of chronic diseases, lower education levels, and less wealth than the decelerated aging group. After adjustment for these differences, accelerated aging was associated with a higher risk of a composite outcome of death, heart disease, and stroke, with an adjusted hazard ratio (a-HR) of 1.62 (95% confidence interval: 1.27-2.06, p= 0.001). Accelerated biological age is a predictor of cardiovascular outcomes and death in patients with hypertension.

Clinical biomarker-based biological ageing and the risk of adverse outcomes in patients with chronic kidney disease.

Patients with chronic kidney disease (CKD) show features of premature ageing. We aimed to evaluate the association between biological ageing and adverse outcomes, including end-stage kidney disease (ESKD), cardiovascular diseases (CVD) and all-cause mortality, in patients with CKD. 23435 participants with CKD and free of related adverse outcomes at baseline from the UK Biobank were included. Leukocyte telomere length (LTL) was measured by quantitative polymerase chain reaction assay. Clinical biomarker-based biological ages were quantified using Klemera-Doubal method biological age (KDM-BA) and PhenoAge algorithms. During a median follow-up of 12years, 3417 incident CVD, 383 incident ESKD and 3195 all-cause mortality were recorded. Per SD increment of KDM-BA acceleration was associated with a 56% [95% confidence interval (CI): 41%-73%], 26% (95% CI: 21%-31%) and 39% (95% CI: 34%-44%) increase in the risk of incident ESKD, incident CVD and all-cause mortality, respectively. Similar results were found for PhenoAge acceleration. LTL (per SD increment) was inversely associated with the risk of incident CVD [hazard ratio (HR): 0.96, 95% CI: 0.92-0.99] and all-cause mortality (HR: 0.94, 95% CI: 0.91-0.98) and was not significantly associated with the risk of incident ESKD (HR: 0.96, 95% CI: 0.86-1.06). Adding KDM-BA acceleration or PhenoAge acceleration, but not LTL, to the traditional validated clinical prediction models significantly improved the predictive performance for incident ESKD, all-cause mortality and CVD. In patients with CKD, both KDM-BA acceleration and PhenoAge acceleration were associated with an increased risk of ESKD, CVD and all-cause mortality, and KDM-BA or PhenoAge may be a better predictor on adverse outcomes than LTL.

Association of biological aging with prostate cancer: insights from the National Health and Nutrition Examination Survey.

The link between biological aging and prostate cancer (PCa) risk, particularly as indicated by elevated prostate-specific antigen (PSA) levels, remains uncertain. This study utilized data from the National Health and Nutrition Examination Survey (2001-2010) to explore this association. Biological age was assessed using Klemera-Doubal method age (KDMAge) and phenotypic age (PhenoAge). PCa was identified through self-reported diagnoses, and highly probable PCa was determined by PSA levels. We analyzed the prevalence of PCa and PSA-defined highly probable PCa across quartiles of biological age measures using weighted chi-square and linear trend tests. Associations were evaluated using weighted multiple logistic regression models. Among 7,209 and 6,682 males analyzed, the overall weighted prevalence of PCa was 2.86%, increasing to 9.60% in those aged 65 and above. A significant rise in PCa prevalence was observed with higher quartiles of KDMAge or PhenoAge (P for trend < 0.001), particularly in those under 65. In this younger group, higher PhenoAge acceleration quartiles were linked to increased PCa prevalence and higher risk of PCa (OR = 1.50, P = 0.015) as well as highly probable PCa in those without a diagnosis (OR = 1.28, P = 0.031). These findings suggest that accelerated biological aging is associated with an increased risk of PCa and may indicate early risk as signaled by PSA levels, even in those without a PCa diagnosis.

Optimal lifestyle patterns for delaying ageing and reducing all-cause mortality: insights from the UK Biobank

BackgroundWith the rapid aging of the global population, identifying lifestyle patterns that effectively delay aging and reduce mortality risk is of paramount importance. This study utilizes the UK Biobank to analyze the associations of the Dietary Inflammatory Index, physical activity, and sleep on biological aging and all-cause mortality.MethodsA prospective cohort study was conducted using data from over half a million UK Biobank participants. Two datasets were created by subjective and objective measurements of physical activity: the Subjective Physical Activity (SPA) and Objective Physical Activity (OPA) datasets. Lifestyle patterns, including diet habits, exercise levels, and sleep quality, were assessed within these datasets. Biological aging was quantified using validated methods, including Homeostatic Dysregulation, Klemera-Doubal Method Biological Age, Phenotypic Age, and Telomere Length. All-cause mortality data were obtained from the National Health Service. Statistical analyses included weighted linear regression and Cox proportional hazard models, adjusted for a range of covariates.ResultsThe findings indicate that, in most cases, maintaining an anti-inflammatory diet, engaging in at least moderate physical activity, and ensuring healthy sleep conditions are associated with delayed physiological aging (Cohen’s d ranging from 0.274 to 0.633) and significantly reduced risk of all-cause mortality (HR-SPA: 0.690, 95% CI: 0.538, 0.884; HR-OPA: 0.493, 95% CI: 0.293, 0.828). These effects are particularly pronounced in individuals under 60 years of age and in women. However, it was observed that the level of physical activity recommended by the World Health Organization (600 MET-minutes/week) does not achieve the optimal effect in delaying biological aging. The best effect in decelerating biological aging was seen in the high-level physical activity group (≥ 3000 MET-minutes/week). The study also highlights the potential of biological age acceleration and telomere length as biomarkers for predicting the risk of mortality.ConclusionsChoosing healthy lifestyle patterns, especially an anti-inflammatory diet, at least moderate physical activity, and healthy sleep patterns, is crucial for delaying aging and reducing mortality risk. These findings support the development of targeted interventions to improve public health outcomes. Future research should focus on objective assessments of lifestyle to further validate these associations.

Association between indoor PM2.5 components and accelerated biological aging in schizophrenia patients: Evidence from multi-omics mechanisms

Indoor fine particulate matter (PM2.5) poses a considerable hazard to the aging process, particularly in vulnerable populations such as schizophrenia patients who frequently spend extended periods in indoor environments. Currently, the evidence on which PM2.5 components contribute to accelerated aging remains unclear. To address these issues, we conducted a prospective, repeated-measurement study on 104 schizophrenia patients. Our findings indicated that exposure to PM2.5 components was significantly associated with accelerated biological aging in schizophrenia patients. Notably, the most prominent effects were observed for thallium (1.303, 95% CI: 0.481-2.125), chromium (1.029, 95% CI: 0.303-1.756), lead (1.021, 95% CI: 0.296-1.746), antimony (0.915, 95% CI: 0.233-1.597), selenium (0.854, 95% CI: 0.209-1.499), and manganese (0.833, 95% CI: 0.186-1.480). Multivariate analysis revealed that PM2.5 components predominantly induced alterations in serum glycerophospholipid metabolites, accelerating the aging process. This intricate connection was closely linked to the gut microbiota, particularly to species such as Dorea and Blautia. Mediation analysis showed that the Blautia-PC (16:0/0:0) pathway mediated the largest proportion (30.69%) of the effect of manganese exposure on accelerating immune biological aging in schizophrenia patients, as measured using the Klemera-Doubal method. These results underscore the need to address pollution sources that harm health, and provide new evidence for improving regional air quality.

Associations of daily eating frequency and nighttime fasting duration with biological aging in National Health and Nutrition Examination Survey (NHANES) 2003–2010 and 2015–2018

BackgroundInformation on the influences of daily eating frequency (DEF) and nighttime fasting duration (NFD) on biological aging is minimal. Our study investigated the potential associations of DEF and NFD with accelerated aging.MethodsOut of 24212 participants in NHANES 2003–2010 and 2015–2018, 4 predicted age metrics [homeostatic dysregulation (HD), Klemera–Doubal method (KDM), phenoAge (PA), and allostatic load (AL)] were computed based on 12 blood chemistry parameters. Utilizing 24-h dietary recall, DEF was measured by the frequency of eating occurrences, while NFD was determined by assessing the timing of the initial and final meals throughout the day. Weighted multivariate linear regression models and restricted cubic spline (RCS) were utilized to examine the associations.ResultsCompared to DEF of ≤ 3.0 times, subjects with DEF ≥ 4.6 times demonstrated lower KDM residual [β: -0.57, 95% confidence-interval (CI): (-0.97, -0.17)] and PA residual [β: -0.47, 95% CI: (-0.69, -0.25)]. In comparison to NFD between 10.1 and 12.0 h, individuals with NFD ≤ 10.0 h were at higher HD [β: 0.03, 95% CI: (0.01, 0.04)], KDM residual [β: 0.34, 95% CI: (0.05, 0.63)], and PA residual [β: 0.38, 95% CI: (0.18, 0.57)]. Likewise, those with NFD ≥ 14.1 h also had higher HD [β: 0.02, 95% CI: (0.01, 0.04)] and KDM residual [β: 0.33, 95% CI: (0.03, 0.62)]. The results were confirmed by the dose–response relationships of DEF and NFD with predicted age metrics. Lactate dehydrogenase (LDH) and globulin (Glo) were acknowledged as implicated in and mediating the relationships.ConclusionsDEF below 3.0 times and NFD less than 10.0 or more than 14.1 h were independently associated with higher predicted age metrics.

Association between plant and animal protein and biological aging: findings from the UK Biobank

PurposeThis study aimed to evaluate the relationship between plant protein, animal protein and biological aging through different dimensions of biological aging indices. Then explore the effects of substitution of plant protein, animal protein, and their food sources on biological aging.MethodsThe data came from 79,294 participants in the UK Biobank who completed at least two 24-h dietary assessments. Higher Klemera-Doubal Method Biological Age (HKDM-BA), higher PhenoAge (HPA), higher allostatic load (HAL), and longer telomere length (LTL) were estimated to assess biological aging. Logistic regression was used to estimate protein-biological aging associations. Substitution model was performed to assess the effect of dietary protein substitutions.ResultsPlant protein intake was inversely associated with HKDM-BA, HPA, HAL, and positively associated with LTL (odds ratios after fully adjusting and comparing the highest to the lowest quartile: 0.83 (0.79–0.88) for HKDM-BA, 0.86 (0.72–0.94) for HPA, 0.90 (0.85–0.95) for HAL, 1.06 (1.01–1.12) for LTL), while animal protein was not correlated with the four indices. Substituting 5% of energy intake from animal protein with plant protein, replacing red meat or poultry with whole grains, and replacing red or processed meat with nuts, were negatively associated with HKDM-BA, HPA, HAL and positively associated with LTL. However, an inverse association was found when legumes were substituted for yogurt. Gamma glutamyltransferase, alanine aminotransferase, and aspartate aminotransferase mediated the relationship between plant protein and HKDM-BA, HPA, HAL, and LTL (mediation proportion 11.5–24.5%; 1.9–6.7%; 2.8–4.5%, respectively).ConclusionHigher plant protein intake is inversely associated with biological aging. Although there is no association with animal protein, food with animal proteins displayed a varied correlation.

Evaluating the role of biological age in osteoporosis risk among middle-aged and older adults: A nationwide perspective

ObjectivesThis study aimed to investigate the association between biological age acceleration and osteoporosis (OP) risk in middle-aged and older adults using data from the National Health and Nutrition Examination Survey (NHANES). The research focused on analyzing the relationship between two biological aging metrics, Klemera-Doubal Method Age (KDMAge) and Phenotypic Age (PhenoAge), and OP risk. MethodsThe study analyzed data from NHANES, which included 6550 participants aged 50 and above from survey cycles 2005–2010 and 2017–2018. Linear and logistic regression were used to investigate the relationship between biological age acceleration (KDMAgeAccel and PhenoAgeAccel) and OP. Subgroup analysis was performed by age, gender and other factors. Multivariable Cox regression analysis yielded Hazard Ratios (HRs) relating biological age acceleration to mortality were evaluated. The study also considered the mediating roles of body mass index (BMI). ResultsKDMAgeAccel (odds ratio [OR] = 2.34, 95 % CI, 1.72–3.18) and PhenoAgeAccel (OR = 2.03, 95 % CI, 1.48–2.78) were significantly associated with increased OP risk and reduced bone mineral density (BMD). Specifically, higher KDMAgeAccel and PhenoAgeAccel were linked to higher OP prevalence and lower BMD at multiple sites. Subgroup analyses indicated that the association between accelerated biological age acceleration and OP risk was consistent across different demographics. Mediation analysis revealed that BMI partially mediated the relationship between accelerated biological age and OP, although other mechanisms are likely involved. Statistical analysis indicated that individuals with higher biological age metrics had increased mortality risk related to OP. ConclusionThe findings suggest that accelerated biological age is a robust predictor of OP risk and related mortality. KDMAgeAccel and PhenoAgeAccel could serve as valuable biomarkers for identifying individuals at high risk for OP, guiding preventive strategies.

The Long-Term Associations of Perinatal Obesogenic Environment with Offspring Biological Aging.

Biological age (BA), reflecting aging-related health decline beyond chronological age, varies among individuals. While previous research explored associations of maternal pregnancy-related body size with offspring health outcomes, its implications for BA in young adults remain unclear. Utilizing longitudinal data of 1,148 mother-offspring pairs from the Jerusalem Perinatal Study, we analyzed associations of maternal pre-pregnancy BMI and gestational weight gain (GWG) with offspring Klemera-Doubal method (KDM)-based BA at age 32, and potential familial life-course underlying mechanisms. Maternal pregnancy-related body size, adjusted for sociodemographic/lifestyle factors was associated with offspring BA (βmaternal pre-pregnancy BMI=0.183,95%CI:0.098,0.267;βGWG=0.093,95%CI:0.021,0.165). Association of GWG with BA was largely direct (90%,95%CI,44%,100%), while association with maternal pre-pregnancy BMI was partially mediated through adolescent BMI (36%,95%CI=18%,75%), with both associations eliminated after adjustment for offspring adult BMI. Associations persisted after adjusting for offspring polygenic risk score for BMI (βmaternal pre-pregnancy BMI=0.128;95%CI=0.023,0.234; βGWG=0.102;95%CI=0.006,0.198), and somewhat altered after adjustment for maternal cardiometabolic conditions (βmaternal pre-pregnancy BMI=0.144,95%CI=0.059, 0.230). Impact on GWG associations was negligible. Thus, perinatal obesogenic environment contributes to offspring BA beyond sociodemographic factors and maternal cardiometabolic history, yet intergenerational transmission of obesity seems to underlie these associations. Nonetheless, the period between adolescence and young adulthood could be targeted for weight-reducing interventions, ultimately promoting healthy aging.

Biological aging mediates the association between periodontitis and cardiovascular disease: results from a national population study and Mendelian randomization analysis

BackgroundThe relationship between periodontitis and cardiovascular disease (CVD) has been extensively studied, but the role of biological aging in this relationship remains poorly understood. This study is dedicated to investigating the effect of periodontitis on the incidence of CVD and to elucidating the potential mediating role of biological aging. Furthermore, this study will seek to elucidate the causal association between periodontitis, CVD, and biological aging.MethodsWe included 3269 participants from the National Health and Nutrition Examination Survey (2009–2014) with diagnostic information on periodontitis and composite CVD events. Biological aging was evaluated by utilizing both the Klemera–Doubal method’s calculated biological age (KDMAge) and phenotypic age (PhenoAge). Logistic regression, restricted cubic spline (RCS) analysis, and subgroup analysis were used for data analysis. Mediation analysis was employed to explore the mediating role of biological aging. Subsequently, Mendelian randomization (MR) analyses were performed using genome-wide association study databases to explore potential causal relationships between periodontitis, CVD, and biological aging.ResultsPeriodontitis was associated with a higher risk of CVD. Participants with periodontitis were found to have increased levels of biological aging, and elevated levels of biological aging were associated with increased CVD risk. Mediation analyses showed a partial mediating effect of biological aging (PhenoAge: 44.6%; KDMAge: 22.9%) between periodontitis and CVD risk. MR analysis showed that periodontitis played a causal role in increasing the risk of small vessel stroke, while myocardial infarction was found to increase the risk of periodontitis. In addition, reverse MR analysis showed that phenotypic aging can increase the risk of periodontitis, and there is a two-way causal relationship between CVD and biological aging.ConclusionsPeriodontitis is associated with an increased CVD risk, partially mediated by biological aging, with a complex causal interrelationship. Targeted interventions for periodontal health may slow the biological aging processes and reduce CVD risk.

Dietary Live Microbes Intake Associated With Biological Aging and Mortality.

This observational study aimed to investigate associations between dietary live microbe intake and mortality, as well as biological aging. Adults from the 1999-2018 National Health and Nutrition Examination Survey were categorized into low, medium, and high dietary live microbe groups. Foods with medium and high live microbe content were aggregated into a medium-high consumption category. The outcomes included all-cause, cardiovascular, and cancer mortality, along with biological age (BA) acceleration assessed by the Klemera-Doubal method (KDM) and PhenoAge. Multiple regression analyses and mediation analyses were conducted to assess associations, adjusting for potential confounders. A total of 34 133 adults were included in our analyses. Over an average follow-up period of 9.92 years, 5462 deaths occurred. In multivariate adjusted models, every 100g of medium-high group foods consumed was associated with reduced all-cause mortality (hazard ratio [HR] 0.94, 95% confidence interval [CI] 0.91 to 0.97, p < .001) and cardiovascular mortality (HR 0.91, 95% CI 0.86 to 0.96, p < .001), but not with cancer mortality (HR 1.01, 95% CI 0.95 to 1.07, p = .768). Every 100g medium-high group foods consumption was associated with decreased KDM-BA acceleration (fully adjusted regression coefficient -0.09, 95% CI -0.15 to -0.04, p = .001) and PhenoAge acceleration (fully adjusted regression coefficient -0.07, 95% CI -0.11 to -0.03, p < .001). Mediation analysis showed that BA acceleration partially mediated live microbes-mortality associations. Our results suggest that higher dietary live microbe intake is associated with lower mortality risk and slower biological aging. However, further research is needed to verify these findings.

Association of accelerated biological aging with brain volumes: A cross-sectional study

BackgroundMultiple epidemiological studies have observed the connection between aging and brain volumes. The concept of accelerated biological aging (BA) is more powerful for observing the degree of aging of an individual than chronologic age (CA). The objective of this study is to explore the relationship between BA and brain volumes. MethodsBA was measured from clinical traits using two blood-chemistry algorithms, the Klemera-Doubal method (KDM) and the PhenoAge. The two age acceleration biomarkers were calculated by the residuals from regressing CA, termed “KDM-acceleration” and “PhenoAge-acceleration”. Brain volumes were from brain magnetic resonance imaging (MRI) data. After adjustment for confounding factors, general linear regression models were used to examine associations between KDM-acceleration and PhenoAge-acceleration and brain volumes, respectively. Additionally, we stratified participants by sex, age, and the four quartiles of the Townsend Deprivation Index (TDI) for extra subgroup analysis. Results14,725 participants with available information were enrolled. After full adjustment, we observed negative associations between KDM-acceleration and brain volumes, such as gray matter (β = −0.029), white matter (β = −0.021), gray and white matter (β = −0.026), and hippocampus (β = −0.011 for left and β = −0.014 for right). There were also negative associations between PhenoAge-acceleration and brain volumes, such as white matter (β = −0.008), gray and white matter (β = −0.010), thalamus (β = −0.012 for left and β = −0.012 for right). In the subgroup analysis stratified by sex, age, and the four quartiles of TDI, the association between KDM-acceleration and PhenoAge-acceleration and brain volumes still existed. In subgroup analyses, the variation in associations suggests that socioeconomic and biological factors may differentially influence brain aging. ConclusionsOur research indicated that more advanced BA was associated with less brain tissue.

Unraveling the influence of childhood emotional support on adult aging: Insights from the UK Biobank

BackgroundExploring the association between Childhood Emotional Support (CES) and the mechanisms of aging is pivotal for understanding its potential to lessen the incidence of age-related pathologies and promote a milieu for healthy aging. MethodsUtilizing data from the UK Biobank comprising nearly 160,000 individuals, comprehensive analyses were conducted to explore associations between CES levels and age-related diseases, biological age and aging hallmarks. Cox proportional hazards regression models were used to investigate the relationship between CES and the risk of hospitalization for age-related diseases. Linear regression models were employed to explore the associations between CES and the frailty index (FI), Klemera-Doubal method (KDM) biological age acceleration, homeostatic dysregulation (HD), C-reactive protein (CRP), white blood cell (WBC) count, and telomere length. ResultsThe analyses revealed a significant association between higher CES levels and a decreased risk of hospitalization for age-related diseases in later life. After adjustments for covariates, the hazard ratio for age-related diseases was 0.87 (95 % confidence interval, 0.83–0.91, p < 0.001) in those with the highest CES level compared to those with the lowest CES level. Participants with the highest CES level exhibited lower FI scores (coefficient = -0.033, p < 0.001), reduced CRP level (coefficient = -0.097, p < 0.05) and lower WBC counts (coefficient = -0.034, p < 0.05). Stratified analyses based on genetic susceptibility further elucidated the protective role of CES against age-related diseases. ConclusionThese findings underscore the potential of early interventions targeting CES to promote healthy aging and alleviating the burden of age-related diseases.

The Relationship Between Central Obesity and Osteoarthritis in US Adults: The Mediating Role of Biological Aging Acceleration

Objective This study aims to investigate the association between central obesity and the risk of osteoarthritis, and the mediating role of biological age and biological aging advance in this relationship. Methods The study is based on data from the National Health and Nutrition Examination Survey (NHANES) for the years 2005–2018. Thirteen commonly used clinical traits were used to calculate the Klemera-Doubal method age (KDM-Age) and phenotypic age (Pheno-Age) as two measures of biological aging. Additionally, KDM-Age advance and Pheno-Age advance were calculated as two measures of biological aging advance. Weighted multivariable logistic regression was used to analyze the association between central obesity and the risk of osteoarthritis (OA). Mediation analysis was then applied to elucidate the role of biological aging and biological aging advance in this relationship. Results A total of 31,162 subjects aged ≥20 years were included in this study, of which 3,964 subjects reported having OA (14%). Compared to the Non-OA group, the OA group showed significantly higher proportions of central obesity, KDM-Age, KDM-Age advance, PhenoAge, and PhenoAge advance. Compared to the Non-central obesity group, the central obesity group had higher KDM-Age, KDM-Age advance, PhenoAge, PhenoAge advance, and a higher risk of OA (p < 0.05). Additionally, higher KDM-Age, KDM-Age advance, PhenoAge, and PhenoAge advance were positively correlated with the risk of OA (p < 0.05). Mediation analysis revealed that part of the association between central obesity and the risk of OA was mediated by KDM-Age, KDM-Age advance, PhenoAge, and PhenoAge advance (p < 0.05). Conclusion Central obesity increases the risk of OA, with part of this association being mediated by biological aging and biological aging advance.

"Urological age" as a proxy of healthy longevity: analysis of prospective population-based cohorts in U.S. and China.

Assessing urinary symptoms poses a complex challenge for primary care practitioners. In evaluating urological function, our approach involves constructing an urological age through the analysis of laboratory parameters and indicators of the urinary system. Based on the National Health and Nutrition Examination Survey (NHANES), urological laboratory tests and age-related symptoms were included in the development of urological age (UA) and urological age acceleration (UAA) through the Klemera Doubal method. In relation to mortality associated with UAA, the metric was categorized into grades (0, 1, 2) as a discrete variable. We investigated the correlation between UAA and its grades with mortality, conducted survival analysis based on UAA grades, and explored the correlation between multisystem ageing-related disorders and UAA grades based on the NHANES and the West China Natural Population Cohort Study. UA was related to age with the r to 0.85 in men and 0.84 in women. Each year the increase in UAA was related to higher 1% and 4% mortality for men and women. Those with UAA grades 1 and 2 were associated with more risk of mortality than individuals with UAA grade 0 (men 8% and 40%, women 24% and 157%). The advanced UAA grades kept pace with multisystem ageing. Healthy diets and lifestyle habits are associated with lower UAA. Urological age is related to multisystem ageing and increases mortality risk, and urological age can be used to screen high-risk individuals and inform precision clinical development for ageing intervention.

Flooding exposure accelerated biological aging: a population-based study in the UK

Floods have been the most common type of disaster and are expected to increase in frequency and intensity due to climate change. Although there is growing evidence on the impacts of floods on human health, none has so far investigated the association between flooding exposure and biological aging acceleration. We collected data from 364 841 participants from the UK Biobank project. Flooding data before baseline were retrieved from the Dartmouth Flood Observatory and linked to each participant. Cumulative flooding exposure within six years before the baseline was calculated. We calculated the two biological aging measures at baseline: PhenoAge and Klemera-Doubal method biological age (KDM-BA) and assessed their associations with flooding exposure using mixed-effects linear regression models. We observed that participants exposed to higher levels of floods were more likely to have accelerated biological aging. The risks associated with flooding exposure could last for several years, with the highest cumulative effect observed over 0–4 years. In the fully adjusted model, per interquartile increase in cumulative flood exposure was associated with an increase of 0.24 years (95% CI: 0.14, 0.34) in PhenoAge acceleration and 0.14 years (95% CI: 0.07, 0.21) in KDM-BA acceleration over lag 0–4 years. The associations were consistent regardless of lifestyles, demographics, and socio-economic status. Our findings suggest that exposure to floods may lead to accelerated biological aging. Our work provides the basis for further understanding of the flood-related health impacts and suggests that public health policies and adaptation measures should be initiated in the short-, medium- and even long-term after flooding.

Social Determinants of Health and Biological Age among Diverse U.S. Adults, NHANES 2011-2018.

We examined the sex-specific association between education and income with biological age (BA) and by race/ethnicity. The Klemera-Doubal method was used to calculate BA among 6,213 females and 5,938 males aged 30-75 years who were Hispanic, non-Hispanic (NH) White, NH Black (NHB), or NH Asian (NHA). Compared with a college education, less than a high school education was associated with greater BA by 3.06 years (95% CI: 1.58, 4.54) among females only; associations were strongest among NHB, Hispanic, and NHA females. Compared with an annual income of ≥$75,000, an income <$25,000 was associated with greater BA by 4.95 years (95% CI: 3.42, 6.48) among males and 2.76 years among females (95% CI: 1.51, 4.01); associations were strongest among NHW and NHA adults, and Hispanic males. Targeting upstream sources of structural disadvantage among racial/ethnic minority groups, in conjunction with improvements in income and education, may promote healthy aging in these populations.

The Association Between Grandchild Care and Biological Aging Among Middle-Aged and Older Adults in China.

Substantial evidence documents grandchild care is associated with self-reported health, life satisfaction, and depressive symptoms among middle-aged and older adults. However, little is known about the relationship between grandchild care and biological aging, especially in China, which emphasizes the unique cultural value of family. The current study sheds light on the biological consequence of grandchild care by examining the link between grandchild care and biological aging among middle-aged and older adults in China, and how gender and spousal involvement in caregiving affect this link. In a representative sample of Chinese adults aged 45-80 from the third wave of China Health and Retirement Longitudinal Study in 2015 (n = 3,384), we calculate biological age using Klemera-Doubal Method, and Ordinary Least Square models are used to examine the correlation between grandchild care and biological aging. High intensity of involvement in grandchild care is related to biological aging, and caring for grandchildren alone predicts greater biological aging. Compared with grandfathers, grandmothers lose more from grandchild care regardless of whether their husbands are involved in the care. Providing grandchild care should be a way to cope with age-related role discontinuity or loss, rather result in extra stress or burden for grandparents. Reducing the intensity of caregiving or increasing family support may attenuate the extent of biological aging.

Association between single and mixed exposure to polycyclic aromatic hydrocarbons and biological aging.

Aging is one of the most important public health issues. Previous studies on the factors affecting aging focused on genetics and lifestyle, but the association between polycyclic aromatic hydrocarbons (PAHs) and aging is still unclear. This study utilized data from the National Health and Nutrition Examination Survey (NHANES) 2003-2010. A total of 8,100 participants was used to construct the biological age predictors by using recent advanced algorithms Klemera-Doubal method (KDM) and Mahalanobis distance. Two biological aging indexes, recorded as KDM-BA acceleration and PhenoAge acceleration, were used to investigate the relationship between single PAHs and biological age using a multiple linear regression analysis, and a weighted quantile sum (WQS) model was constructed to explore the mixed effects of PAHs on biological age. Finally, we constructed the restricted cubic spline (RCS) model to assess the non-linear relationship between PAHs and biological age. Exposure to PAHs was associated with PhenoAge acceleration. Each unit increase in the log10-transformed level of 1-naphthol, 2-naphthol, and 2-fluorene was associated with a 0.173 (95% CI: 0.085, 0.261), 0.310 (95% CI: 0.182, 0.438), and 0.454 (95% CI: 0.309, 0.598) -year increase in PhenoAge acceleration, respectively (all corrected P < 0.05). The urinary PAH mixture was relevant to KDM-BA acceleration (β = 0.13, 95% CI: 0, 0.26, P = 0.048) and PhenoAge acceleration (β = 0.59, 95% CI: 0.47, 0.70, P < 0.001), and 2-naphthol had the highest weight in the weighted quantile sum (WQS) regression. The RCS analyses showed a non-linear association between 2-naphthol and 2-fluorene with KDM-BA acceleration (all P < 0.05) in addition to a non-linear association between 1-naphthol, 2-naphthol, 3-fluorene, 2-fluorene, and 1-pyrene with PhenoAge acceleration (all P < 0.05). Exposure to mixed PAHs is associated with increased aging, with 2-naphthol being a key component of PAHs associated with aging. This study has identified risk factors in terms of PAH components for aging.

Childhood Maltreatment and Biological Aging in Middle Adulthood: The Role of Psychiatric Symptoms

BackgroundChildhood maltreatment and psychiatric morbidity have each been associated with accelerated biological aging primarily through cross-sectional studies. Using data from a prospective longitudinal study of individuals with histories of childhood maltreatment and control participants followed into midlife, we tested 2 hypotheses examining whether 1) psychiatric symptoms mediate the relationship between childhood maltreatment and biological aging and 2) psychiatric symptoms of anxiety, depression, or posttraumatic stress disorder (PTSD) act in conjunction with childhood maltreatment to exacerbate the association of child maltreatment to aging. MethodsChildren (ages 0–11 years) with documented histories of maltreatment and demographically matched control children were followed into adulthood (N = 607) and interviewed over several waves of the study. Depression, anxiety, and PTSD symptoms were assessed at mean ages of 29 (interview 1) and 40 (interview 2) years. Biological age was measured from blood chemistries collected later (mean age = 41 years) using the Klemera-Doubal method. Hypotheses were tested using linear regressions and path analyses. ResultsAdults with documented histories of childhood maltreatment showed more symptoms of depression, PTSD, and anxiety at both interviews and more advanced biological aging, compared with control participants. PTSD symptoms at both interviews and depression and anxiety symptoms only at interview 2 predicted accelerated biological aging. There was no evidence of mediation; however, anxiety and depression moderated the relationship between childhood maltreatment and biological aging. ConclusionsThese new findings reveal the shorter- and longer-term longitudinal impact of PTSD on biological aging and the amplifying effect of anxiety and depression on the relationship between child maltreatment and biological aging.