Health Study Research Articles

Cataloging health state utility estimates for Duchenne muscular dystrophy and related conditions.

Duchenne muscular dystrophy (DMD) is a genetic disease resulting in progressive muscle weakness, loss of ambulation, and cardiorespiratory complications. Direct estimation of health-related quality of life for patients with DMD is challenging, highlighting the need for proxy measures. This study aims to catalog and compare existing published health state utility estimates for DMD and related conditions. Using two search strategies, relevant utilities were extracted from the Tufts Cost-Effectiveness Analysis Registry, including health states, utility estimates, and study and patient characteristics. Analysis One identified health states with comparable utility estimates to a set of published US patient population utility estimates for DMD. A minimal clinically important difference of ± 0.03 was applied to each DMD utility estimate to establish a range, and the registry was searched to identify other health states with associated utilities that fell within each range. Analysis Two used pre-defined search terms to identify health states clinically similar to DMD. Mapping was based on the degree of clinical similarity. Analysis One identified 4,308 unique utilities across 2,322 cost-effectiveness publications. The health states captured a wide range of acute and chronic conditions; 34% of utility records were extrapolated for US populations (n = 1,451); 1% were related to pediatric populations (n = 61). Analysis Two identified 153 utilities with health states clinically similar to DMD. The median utility estimates varied among identified health states. Health states similar to the early non-ambulatory DMD phase exhibited the greatest difference between the median estimate of the sample (0.39) and the existing estimate from published literature (0.21). When available estimates are limited, using novel search strategies to identify utilities of clinically similar conditions could be an approach for overcoming the information gap. However, it requires careful evaluation of the utility instruments, tariffs, and raters (proxy or self).

Cruciferous vegetables lower blood pressure in adults with mildly elevated blood pressure in a randomized, controlled, crossover trial: the VEgetableS for vaScular hEaLth (VESSEL) study.

Higher cruciferous vegetable intake is associated with lower cardiovascular disease risk in observational studies. The pathways involved remain uncertain. We aimed to determine whether cruciferous vegetable intake (active) lowers 24-h brachial systolic blood pressure (SBP; primary outcome) compared to root and squash vegetables (control) in Australian adults with mildly elevated BP (SBP 120-160mmHg inclusive). In this randomized, controlled, crossover trial, participants completed two 2-week dietary interventions separated by a 2-week washout. Cruciferous vegetables were compared to root and squash vegetables (~ 300g/day) consumed with lunch and dinner meals. Participants were blinded to which interventions were the active and control. Adherence was assessed using food diaries and biomarkers (S-methyl cysteine sulfoxide (SMCSO, active) and carotenoids (control)). Twenty-four-hour brachial ambulatory SBP and secondary outcomes were assessed pre- and post each intervention. Differences were tested using linear mixed effects regression. Eighteen participants were recruited (median (IQR) age: 68 (66-70); female: n = 16/18; mean ± SD clinic SBP: 135.9 ± 10.0mmHg). For both interventions, 72% participants had 100% adherence (IQR: 96.4-100%). SMCSO and carotenoids were significantly different between interventions (mean difference active vs. control SMCSO: 22.93mg/mL, 95%CI 15.62, 30.23, P < 0.0001; carotenoids: - 0.974mg/mL, 95%CI - 1.525, - 0.423, P = 0.001). Twenty-four-hour brachial SBP was significantly reduced following the active vs. control (mean difference - 2.5mmHg, 95%CI - 4.2, - 0.9, P = 0.002; active pre: 126.8 ± 12.6mmHg, post: 124.4 ± 11.8mmHg; control pre: 125.5 ± 12.1mmHg, post: 124.8 ± 13.1mmHg, n = 17), driven by daytime SBP (mean difference - 3.6mmHg, 95%CI - 5.4, - 1.7, P < 0.001). Serum triglycerides were significantly lower following the active vs. control (mean difference - 0.2mmol/L, 95%CI - 0.4, - 0.0, P = 0.047). Increased intake of cruciferous vegetables resulted in reduced SBP compared to root and squash vegetables. Future research is needed to determine whether targeted recommendations for increasing cruciferous vegetable intake benefits population health. Clinical trial registry ACTRN12619001294145. https://www.anzctr.org.au.

Dyadic Appraisals of Family Decisions and Health Tasks in Midlife-Older Couples.

Shared appraisals and collaboration within couples play important roles in optimizing health. Less is known about concordance regarding collaboration, factors associated with concordance, and implications for health. Data from 2,761 couples from the Health and Retirement Study (2014/2016 and 2016/2018 waves) were examined to determine within-couple concordance in completion of two tasks (family decisions and medical forms). The majority of couples were concordant regarding who makes family decisions (69.7%) and who completes medical forms (64.4%); 62% agreed they make family decisions collaboratively versus 25.5% completing medical forms collaboratively. Concordance was significantly associated with greater marital support and longer marital duration. Concordance was not significantly associated with depressive symptoms 2 years later, but the link between concordance in making major family decisions and self-rated health differed by age and gender. Future research at the intersection of concordance and collaboration may shed important light on how older couples navigate tasks and decisions.

Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis

Lung cancer risk prediction models might efficiently identify individuals who should be offered lung cancer screening. However, their performance has not been comprehensively evaluated in Europe. We aimed to externally validate and evaluate the performance of several risk prediction models that predict lung cancer incidence or mortality in prospective European cohorts. We analysed 240 137 participants aged 45-80 years with a current or former smoking history from nine European countries in four prospective cohorts from the pooled database of the Lung Cancer Cohort Consortium: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (Finland), the Nord-Trøndelag Health Study (Norway), CONSTANCES (France), and the European Prospective Investigation into Cancer and Nutrition (Denmark, Germany, Italy, Spain, Sweden, the Netherlands, and Norway). We evaluated ten lung cancer risk models, which comprised the Bach, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 model (PLCOm2012), the Lung Cancer Risk Assessment Tool (LCRAT), the Lung Cancer Death Risk Assessment Tool (LCDRAT), the Nord-Trøndelag Health Study (HUNT), the Optimized Early Warning Model for Lung Cancer Risk (OWL), the University College London-Death (UCLD), the University College London-Incidence (UCLI), the Liverpool Lung Project version 2 (LLP version 2), and the Liverpool Lung Project version 3 (LLP version 3) models. We quantified model calibration as the ratio of expected to observed cases or deaths and discrimination using the area under the receiver operating characteristic curve (AUC). For each model, we also identified risk thresholds that would screen the same number of individuals as each of the US Preventive Services Task Force 2021 (USPSTF-2021), the US Preventive Services Task Force 2013 (USPSTF-2013), and the Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) criteria. Among the participants, 1734 lung cancer cases and 1072 lung cancer deaths occurred within five years of enrolment. Most models had reasonable calibration in most countries, although the LLP version 2 overpredicted risk by more than 50% in eight countries (expected to observed ≥1·50). The PLCOm2012, LCDRAT, LCRAT, Bach, HUNT, OWL, UCLD, and UCLI models showed similar discrimination in most countries, with AUCs ranging from 0·68 (95% CI 0·59-0·77) to 0·83 (0·78-0·89), whereas the LLP version 2 and LLP version 3 showed lower discrimination, with AUCs ranging from 0·64 (95% CI 0·57-0·72) to 0·78 (0·74-0·83). When pooling data from all countries (but excluding the HUNT cohort), 33·9% (73 313 of 216 387) of individuals were eligible by USPSTF-2021 criteria, which included 74·8% (1185) of lung cancers and 76·3% (730) of lung cancer deaths occurring over 5 years. Fewer individuals were selected by USPSTF-2013 and NELSON criteria. After applying thresholds to select a population of equal size to USPSTF-2021, the PLCOm2012, LCDRAT, LCRAT, Bach, HUNT, OWL, UCLD, and UCLI, models identified 77·6%-79·1% of future cases, although they selected slightly older individuals compared with USPSTF-2021 criteria. Results were similar for USPSTF-2013 and NELSON. Several lung cancer risk prediction models showed good performance in European countries and might improve the efficiency of lung cancer screening if used in place of categorical eligibility criteria. US National Cancer Institute, l'Institut National du Cancer, Cancer Research UK.

Association between internet exclusion and depressive symptoms among older adults: panel data analysis of five longitudinal cohort studies

Internet exclusion and depressive symptoms are prevalent phenomena among older adults; however, the association between internet exclusion and depressive symptoms remains limited. This study aims to investigate the association between internet exclusion and depressive symptoms among older adults from high-income countries (HICs) and low- and middle-income countries (LMICs). We conducted a comprehensive longitudinal, cross-cultural analysis, and the participants were adults aged 60 years and older from 32 countries participating in five nationally representative longitudinal cohort studies: the Health and Retirement Study (HRS), the English Longitudinal Study of Ageing (ELSA), the Survey of Health, Ageing and Retirement in Europe (SHARE), the China Health and Retirement Longitudinal Study (CHARLS), and the Mexican Health and Ageing Study (MHAS). Internet exclusion was defined as the self-reported absence from internet use. Depressive symptoms were evaluated using the Centre for Epidemiologic Studies of Depression scale (CES-D) or the Euro-Depression scale (Euro-D). These five cohorts, being heterogeneous, were respectively conducted with panel data analysis. Logistic regression, implemented within the generalized estimating equations framework, was used to examine the association between internet exclusion and the likelihood of experiencing depressive symptoms, adjusting for the causal-directed-acyclic-graph (DAG) minimal sufficient adjustment set (MSAS), including gender, age, education, labour force status, household wealth level, marital status, co-residence with children, residence status, cognitive impairment, and functional ability. Our study included a total of 129,847 older adults during the period from 2010 to 2020, with a median follow-up of 5 (2, 7) years. The pooled proportion of internet exclusion was 46.0% in HRS, 32.6% in ELSA, 54.8% in SHARE, 92.3% in CHARLS, and 65.3% in MHAS. Internet exclusion was significantly associated with depressive symptoms across all cohort studies: HRS (OR=1.13, 95% CI 1.07-1.20), ELSA (OR=1.22, 95% CI 1.11-1.34), SHARE (OR=1.55, 95% CI 1.47-1.62), CHARLS (OR=1.49, 95% CI 1.26-1.77), and MHAS (OR=1.48, 95% CI 1.39-1.58). Moreover, internet exclusion was found to be associated with all dimensions of depression in the SHARE, MHAS, and ELSA cohorts (except for sleep and felt sad) cohorts. A considerable proportion of older adults experienced internet exclusion, particularly those in LMICs. Internet exclusion among older adults, irrespective of their geographic location in HICs or LMICs, was associated with a higher likelihood of experiencing depressive symptoms, which demonstrated the importance of addressing barriers to internet access and promoting active participation in the internet society among older adults. National Key R&D Program of China (grant number 2022ZD0160704), the Scientific Research and Innovation Team of The First Affiliated Hospital of Zhengzhou University (grant number ZYCXTD2023005), the Collaborative Innovation Major Project of Zhengzhou (grant number 20XTZX08017), the Joint Project of Medical Science and Technology of Henan Province (grant number LHGJ20220428), and National Natural Science Foundation of China (grant number 82373341).

Examining First- and Second-Level Digital Divide at the Intersection of Race/Ethnicity, Gender, and Socioeconomic Status: An Analysis of the National Health and Aging Trends Study.

Significant societal and technological changes in the 2010s called for an up-to-date understanding of the digital divide among older adults in the United States. This trend study aimed to examine the effects of race/ethnicity and the intersecting effects of race/ethnicity with other marginalized identities related to gender, income, education, and occupation on the first- and second-level digital divide. Utilizing a nationally representative sample of older community dwellers from the National Health and Aging Trends Study, we conducted weighted logistic regressions at 3 time points (2011/2013, 2015, and 2019). The first-level digital divide was measured by access to working phones or computers/laptops; the second-level divide was measured by 7 activities in personal task, social, and health-related Internet use. The first-level racial/ethnic digital divide became nonsignificant in 2019, whereas the disparities in all second-level measures persisted. The intersecting effects of race/ethnicity with low education and/or low income became nonsignificant in 2019 for personal-task use. However, the interactions with low education and/or low income became significant for social and health-related use in 2015 and/or 2019. This study highlights the persistence of the second-level racial/ethnic digital divide among older community dwellers in the United States, especially the exacerbated social and health-related digital divide for people of color with low socioeconomic status. By considering intersections of marginalized social identities, policymakers and stakeholders should develop targeted strategies to bridge the digital divide, promote health outcomes, and reduce health disparities.

Application of High-Dimensional Propensity Score Methods to the National Health and Aging Trends Study.

High-dimensional propensity scoring (HDPS) is a method for empirically identifying potential confounders within large healthcare databases such as administrative claims data. However, this method has not yet been applied to large national health surveys such as the National Health and Aging Trends Study (NHATS), an ongoing nationally representative survey of older adults in the United States and important resource in gerontology research. In this Research Practice article, we present an overview of HDPS and describe the specific data transformation steps and analytic considerations needed to apply it to national health surveys. We applied HDPS within NHATS to investigate the association between self-reported visual difficulty and incident dementia, comparing HDPS to conventional confounder selection methods. Among 7 207 dementia-free NHATS Wave 1 respondents, 528 (7.3%) had self-reported visual difficulty. In an unadjusted discrete time proportional hazards model accounting for the complex survey design of NHATS, self-reported visual difficulty was strongly associated with incident dementia (odds ratio [OR] 2.34, 95% confidence interval [CI]: 1.95-2.81). After adjustment for standard investigator-selected covariates via inverse probability weighting, the magnitude of this association decreased, but evidence of an association remained (OR 1.44, 95% CI: 1.11-1.85). Adding 75 HDPS-prioritized variables to the investigator-selected propensity score model resulted in further attenuation of the association between visual impairment and dementia (OR 0.94, 95% CI: 0.70-1.23). HDPS can be successfully applied to national health surveys such as NHATS and may improve confounder adjustment. We hope developing this framework will encourage future consideration of HDPS in this setting.

Phenotyping Lipid Profiles in Type 2 Diabetes: Risk Association and Outcomes from the Cardiovascular Health Study

AimsTo determine whether discrete lipid profiles (refer to as lipid phenotyping) can be used to stratify cardiovascular risk in individuals with type 2 diabetes. Methods and ResultsCardiovascular Health Study participants with diabetes and fasting lipid profiles at baseline (n = 866) were categorized separately by level of LDL cholesterol and HDL-C/Triglyceride (Tg) profiles (low Tg/high HDL-C; high Tg/low HDL-C; high Tg only or low HDL-C only). We performed Cox multivariate regression analysis to assess the risk of CVD mortality, incident myocardial infarction (MI), heart failure (HF), stroke, and composite MACE (MI, HF, stroke, and CVD mortality) associated with each lipid category. We also calculated risk estimates for MACE using lipid measures as continuous variables. In the fully adjusted model, the high triglyceride plus low HDL-C cholesterol phenotype demonstrated risk that was at least as high as the highest LDL-C sub-group phenotype for CVD mortality (Hazard ratio {HR} 1.58 vs 1.48), MI (HR 1.53 vs 1.58), HF (HR 1.47 vs 1.20), stroke (HR 2.02 vs 1.43), and MACE (HR 1.58 vs 1.38). When modeled continuously, the HR per SD for MACE was 1.12 (p=0.03) for LDL-C and 1.19-1.20 (p<0.001) for triglycerides or remnant cholesterol. ConclusionsParticipants with the high triglyceride/low HDL-C phenotype had equivalent or higher CVD risk than those with the high LDL-C phenotype. Further studies are necessary to determine whether lipid phenotyping accounts for the substantial CVD risk not explained by LDL cholesterol among individuals with type 2 diabetes.

51638 A Population Based Study of Mental Health and Socioeconomic Status in Psoriasis Patients with Skin of Color

51638 A Population Based Study of Mental Health and Socioeconomic Status in Psoriasis Patients with Skin of Color

The mediational role of hearing acuity in the association between personality and memory: Evidence from the health and retirement study and the English Longitudinal Study of Aging

The mediational role of hearing acuity in the association between personality and memory: Evidence from the health and retirement study and the English Longitudinal Study of Aging

Serial gait speed measurements over time and dynamic survival prediction in older adults

BackgroundA one-time gait speed measurement predicts mortality risk. A framework for updating a clinician’s mortality risk perception with new information from each clinic visit is needed. We used joint modeling of longitudinal and survival data for dynamic prediction of mortality risk. MethodsWe fit sex-stratified joint models to 20-meter (bi)annual longitudinal gait speed measured every 6 months and 14-year survival data from the Health, Aging and Body Composition Study allowing for non-linear fluctuations of gait speed and controlling for important covariates such as age, recent hospitalization, blood pressure, obesity, and comorbidities. ResultsParticipants (N = 3048) were 74 years old with gait speed 1.18 m/s. They were 42% Black, and 52% died over 14 years. Higher gait speed of 0.1 m/s was associated with 23% (95% confidence interval or CI = 20–25%) and 25% (CI = 21–28%) reductions in mortality risk in men and women; and a 0.05 m/s annualized slowing (slope) with 31% (CI = 13–51%) increase in men (all p < 0.05), with findings persisting after covariate adjustment. Distant gait speed history over a year prior contributed little for mortality risk prediction with mean change of only 1–2% in 5-year risk. ConclusionThe two most recent gait speeds appear sufficient to consider for mortality risk in the present initial analysis. More frequent gait speeds need to be considered in mortality risk prediction before definitive conclusions supporting real-world application.

Joint trajectories of pain, depression and frailty and associations with adverse outcomes among community-dwelling older adults: A longitudinal study

This study aimed to examine joint trajectories of pain, depression and frailty and their associations with adverse outcomes. Four waves of national data from the China Health and Retirement Longitudinal Study (CHARLS 2011–2018) were used, involving 4217 participants aged ≥60 years. Joint trajectories were fit using parallel-process latent class growth analysis, and their associations with adverse outcomes were evaluated using modified Poisson regression. Four joint trajectories were identified. Compared with most favorable group, other three joint trajectory groups had higher risk of functional disability and hospitalization. Slowly progressive pain, depression and frailty and persistent combination of pain, depression and frailty were also associated with cognitive decline, while slowly reduced pain and depression but persistent frailty was associated with all-cause mortality. The findings highlight unique characteristics and health impacts of concurrent changes in pain, depression and frailty over time, implicating the integrated physical and psychological care for older adults.

Latent profile analysis of depression and its influencing factors in older adults raising grandchildren in China

ObjectiveTo explore the latent profile of depression in older adults raising grandchildren in China, and to analyze the differences in the characteristics of the different profiles of the population and the factors influencing them. MethodsThis study utilized the 2018 China Health and Retirement Longitudinal Study (CHARLS). Through a cross-sectional study, the latent profile analysis was used to analyze the potential classification of depression among older adults raising grandchildren, and using ordered multi-categorical logistic regression analyses to assess the effects of each factor on their different classifications. ResultsThe 1271 older adults raising grandchildren with depression symptoms were divided into three categories: low-level depression (55.4%), moderate-level depression (31.2%), and high-level depression (13.4%). Ordered multi-categorical Logistic results showed: Gender, marital status, pension insurance, physical health status, life satisfaction, and IADL were predictors of latent profile classification of depression symptoms in older adults raising grandchildren (P < 0.05). ConclusionsIn the future of primary care, it will be more meaningful to provide targeted interventions for different subgroups of depression in older adults raising grandchildren.

Younger Older Americans and Sarcopenic Obesity: The Moderating Role of Living Alone.

Previous studies have indicated that compared to older adults, younger older adults (e.g., baby boomers) are more susceptible to obesity, but their risk decreases as they age. However, there is a lack of research on how individuals experience sarcopenic obesity, which increases in later life and is a mortality risk factor. This study examined how younger cohorts of older Americans and their demographic traits are related to sarcopenic obesity. Generalized estimating equations were used to analyze participants aged 65 years and older, stratified by sex using data from the 2006-2016 Health and Retirement Study, with survey weights (n = 2,896 men and n = 4,268 women). The findings indicate that the youngest cohort (born between 1948 and 1953) had greater odds of sarcopenic obesity than older cohorts (born before 1931). However, the youngest cohort did not have significantly different risks from those born between 1931 and 1947. Unexpectedly, the youngest cohort of older women living alone tended not to have sarcopenic obesity compared to the older cohorts living alone. These results remained significant even after adjusting for various covariates, including marital status, race, education level, wealth, and other factors. This paper contributes to the existing literature on population health and demographic change in 2 ways. First, the risk of sarcopenic obesity is higher among younger cohorts of older Americans relative to older cohorts (born before 1931). Second, living alone may not necessarily be considered a worse health condition, particularly for younger female cohorts.

Is subjective life expectancy stronger in older adults with more physical activity? Evidence from China

To explore the relationship between physical activity and subjective life expectancy in an older population. Repeated-measures ANOVA, as well as construction of a cross-lagged model, was conducted with a sample of 4969 older adults from the China Health and Retirement Longitudinal Study data in 2018 and 2020. It was found that T1 subjective life expectancy significantly predicted T2 physical activity (β=0.03, P < 0.01) and T1 physical activity significantly predicted T2 subjective life expectancy (β=0.05, P < 0.05). There was a significant bidirectional predictive relationship between physical activity and subjective life expectancy in older adults, and physical activity is a causal variable for subjective life expectancy.

Reference site selection based on state-and-transition models for soil health gap evaluation within cropland reference ecological units

Comparative soil health studies are critical in soil conservation and gauging the success of different management practices in soil health improvement. A primary challenge in these studies is the selection of a consistent natural reference site. Current choices vary widely, from minimally disturbed areas to pristine prairies. This methodological paper underscores the need for deliberate and thoughtful reference site selection for benchmark soil properties. Utilizing the State &Transition models, the study introduces a framework for this selection, drawing upon the ecological site (ES) and reference plant communities detailed in an ecological site description (ESD) within a respective Major Land Resource Area (MLRA). This study advocates for a localized classification within the framework of the Cropland Reference Ecological Unit (CREU), emphasizing the significance of local precipitation and soil data to ensure unbiased comparisons. Soil samples from eastern (MLRA 106) and western (MLRA 67A) Nebraska were collected, representing distinct pedogenetic and climatic differences. Analysis of soil organic matter between MLRAs displayed substantial variations, suggesting potential biases and complexities in soil health gap calculations when using reference sites and croplands not in the same MLRA, soil types (texture class), or precipitation zones. However, refining the comparisons by delineating the MLRA, soil, and precipitation zones within the framework of CREU yielded more consistent and realistic comparative data. Integrating the MLRA and ES, complemented by granular soil and precipitation data, provides a robust method for establishing soil health benchmark data.

Inflammation, Cholesterol, Lipoprotein(a), and 30-Year Cardiovascular Outcomes in Women.

High-sensitivity C-reactive protein (CRP), low-density lipoprotein (LDL) cholesterol, and lipoprotein(a) levels contribute to 5-year and 10-year predictions of cardiovascular risk and represent distinct pathways for pharmacologic intervention. More information about the usefulness of these biomarkers for predicting cardiovascular risk over longer periods of time in women is needed because early-life intervention represents an important risk-reduction method. We measured high-sensitivity CRP, LDL cholesterol, and lipoprotein(a) levels at baseline in 27,939 initially healthy U.S. women who were subsequently followed for 30 years. The primary end point was a first major adverse cardiovascular event, which was a composite of myocardial infarction, coronary revascularization, stroke, or death from cardiovascular causes. We calculated the adjusted hazard ratios and 95% confidence intervals across quintiles of each biomarker, along with 30-year cumulative incidence curves adjusted for age and competing risks. The mean age of the participants at baseline was 54.7 years. During the 30-year follow-up, 3662 first major cardiovascular events occurred. Quintiles of increasing baseline levels of high-sensitivity CRP, LDL cholesterol, and lipoprotein(a) all predicted 30-year risks. Covariable-adjusted hazard ratios for the primary end point in a comparison of the top with the bottom quintile were 1.70 (95% confidence interval [CI], 1.52 to 1.90) for high-sensitivity CRP, 1.36 (95% CI, 1.23 to 1.52) for LDL cholesterol, and 1.33 (95% CI, 1.21 to 1.47) for lipoprotein(a). Findings for coronary heart disease and stroke appeared to be consistent with those for the primary end point. Each biomarker showed independent contributions to overall risk. The greatest spread for risk was obtained in models that incorporated all three biomarkers. A single combined measure of high-sensitivity CRP, LDL cholesterol, and lipoprotein(a) levels among initially healthy U.S. women was predictive of incident cardiovascular events during a 30-year period. These data support efforts to extend strategies for the primary prevention of atherosclerotic events beyond traditional 10-year estimates of risk. (Funded by the National Institutes of Health; Women's Health Study ClinicalTrials.gov number, NCT00000479.).

Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants.

Continuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis. This cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree. Mean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor. Higher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

Comparing mapped park and greenspace boundaries in Philadelphia: implications for exposure assessment in health studies.

An important consideration in studies of the relationship between greenspace exposure and health is the use of mapped data to assign geographic exposures to participants. Previous studies have used validated data from municipal park departments to describe the boundaries of public greenspaces. However, this approach assumes that these data accurately describe park boundaries, that formal parks fully capture the park and greenspace exposure of residents, and (for studies that use personal GPS traces to assign participant exposures) that time spent within these boundaries represents time spent in greenspace. These assumptions are tested using a comparison and ground-truthing of four sources of mapped park and greenspace data in Philadelphia, Pennsylvania: PAD-US-AR, Philadelphia Parks and Recreation, the Delaware Valley Regional Planning Commission, and Open Street Maps. We find several important differences and tradeoffs in these data: the incorporation of highways and building lots within park boundaries, the inclusion or exclusion of formal park spaces (federal, state, and nonprofit), the exclusion of informal parks and greenspaces, and inconsistent boundaries for a linear park. Health researchers may wish to consider these issues when conducting studies using boundary data to assign park exposure.

‘Our biology is listening’: biomarkers as molecular vestiges of early life and the production of positive childhood experiences in behavioral epigenetics

AbstractThe sciences of environmental epigenetics and the Developmental Origins of Health and Disease have become central in efforts to understand how early life experiences impact health across the life course. This paper draws on interviews with epigenetic scientists and laboratory observations in the United States and Canada to show how scientists conceptualize epigenetic biomarkers as molecular vestiges of early life and the consequences this has for postgenomic approaches to health, risk, and intervention. We argue that this process demarcates early life as the optimal time to study and intervene in health and positions biomarkers as conceptual and methodological tools that scientists mobilize to reimagine early life environments. These environments include Positive Childhood Experiences (PCEs), which reflect an emergent and increasingly prominent epistemic object in behavioral epigenetics. Though distinct from widespread research on Early Life Adversity, we show how PCEs continue to essentialize experience in gendered and individualized ways. Further, this paper suggests that focusing on biomarkers as molecular vestiges of early life allows scientists to create stability despite ongoing epistemological and biological unknowns in epigenetics and DOHaD. Our findings contribute new perspectives to social studies of epigenetics, biomarkers, and the production of novel epistemic objects in postgenomic knowledge practices.