Seroconversion and seroprevalence of TORCH infections in a pregnant women cohort study, Mombasa, Kenya, 2017-2019.

Women infected during pregnancy with TORCH (Toxoplasmosis, Other, Rubella, Cytomegalovirus, and Herpes simplex viruses) pathogens have a higher risk of adverse birth outcomes including stillbirth / miscarriage because of mother-to-child transmission. To investigate these risks in pregnant women in Kenya, we analyzed serum specimens from a pregnancy cohort study at three healthcare facilities. A sample of 481 participants was selected for TORCH pathogen antibody testing to determine seroprevalence. A random selection of 285 from the 481 participants was selected to measure seroconversion. These sera were tested using an IgG enzyme-linked immunosorbent assay against 10 TORCH pathogens. We found that the seroprevalence of all but three of the 10 TORCH pathogens at enrollment was >30%, except for Bordetella pertussis (3.8%), Treponema pallidum (11.4%), and varicella zoster virus (0.5%). Conversely, very few participants seroconverted during their pregnancy and were herpes simplex virus type 2 (n = 24, 11.2%), parvovirus B19 (n = 14, 6.2%), and rubella (n = 12, 5.1%). For birth outcomes, 88% of the participant had live births and 12% had stillbirths or miscarriage. Cytomegalovirus positivity at enrolment had a statistically significant positive association with a live birth outcome (p = 0.0394). Of the 10 TORCH pathogens tested, none had an association with adverse pregnancy outcome.

Association between low maternal serum aflatoxin B1 exposure and adverse pregnancy outcomes in Mombasa, Kenya, 2017-2019: A nested matched case-control study.

We examined the association between serum aflatoxin B1-lysine adduct (AFB1-lys) levels in pregnant women and adverse pregnancy outcomes (low birthweight, miscarriage and stillbirth) through a nested matched case-control study of pregnant women enroled at ≤28 weeks' gestation in Mombasa, Kenya, from 2017 to 2019. Cases comprised women with an adverse birth outcome, defined as either delivery of a singleton infant weighing <2500 g, or a miscarriage, or a stillbirth, while controls were women who delivered a singleton live infant with a birthweight of ≥2500 g. Cases were matched to controls at a ratio of 1:2 based on maternal age at enrolment, gestational age at enrolment and study site. The primary exposure was serum AFB1-lys. The study included 125 cases and 250 controls. The median gestation age when serum samples were collected was 23.0 weeks (interquartile range [IQR]: 18.1-26.0) and 23.5 (IQR: 18.1-26.5) among cases and controls, respectively. Of the 375 tested sera, 145 (38.7%) had detectable serum AFB1-lys: 36.0% in cases and 40.0% in controls. AFB1-lys adduct levels were not associated with adverse birth outcomes on multivariable analysis. Mid-upper arm circumference was associated with a 6% lower odds of adverse birth outcome for every unit increase (p = 0.023). Two-fifths of pregnant women had detectable levels of aflatoxin midway through pregnancy. However, we did not detect an association with adverse pregnancy outcomes, likely because of low serum AFB1-lys levels and low power, restricting meaningful comparison. More research is needed to understand the public health risk of aflatoxin in pregnant women to unborn children.

The impact of facility characteristics on Merkel cell carcinoma outcomes: A retrospective cohort study.

BACKGROUND: Previous work has suggested that facility-level characteristics, such as case volume and academic affiliation, are associated with patient survival for rare malignancies. Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with high mortality and rising incidence. The effect of facility characteristics on MCC outcomes is not yet established. OBJECTIVE: We aimed to investigate whether facility academic affiliation or case volume was associated with MCC patient survival. METHODS: We conducted a retrospective cohort analysis of US adult MCC cases diagnosed during 2004-2014 in the National Cancer Database. RESULTS: Both facility academic affiliation (P < .001) and case volume (P < .001) were significantly associated with patient survival. The 5-year survival of patients treated at academic facilities was 63.0% (standard error [SE] 1.7) and that of a propensity score- matched cohort of patients treated at nonacademic facilities was 53.4% (SE 1.9). The 5-year survival of patients treated at high-case volume facilities was 67.4% (SE 2.1) and that of a propensity score-matched cohort of patients treated at low- and intermediate-case volume facilities was 58.6% (SE 2.0). LIMITATIONS: Disease-specific survival and local recurrence data were not available. CONCLUSION: Treatment of MCC at academic and high-volume centers is associated with significantly improved patient survival. Further studies evaluating comorbidities and disease-specific survival are needed to establish whether experienced centers have improved outcomes in MCC treatment.

Modeling of correlated cognitive function and functional disability outcomes with bounded and missing data in a longitudinal aging study.

Longitudinal studies of correlated cognitive and disability outcomes among older adults are characterized by missing data due to death or loss to follow-up from deteriorating health conditions. The Mini-Mental State Examination (MMSE) score for assessing cognitive function ranges from a minimum of 0 (floor) to a maximum of 30 (ceiling). To study the risk factors of cognitive function and functional disability, we propose a shared parameter model to handle missingness, correlation between outcomes, and the floor and ceiling effects of the MMSE measurements. The shared random effects in the proposed model handle missingness (either missing at random or missing not at random) and correlation between these outcomes, while the Tobit distribution handles the floor and ceiling effects of the MMSE measurements. We used data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and a simulation study. By ignoring the MMSE floor and ceiling effects in the analyses of the CLHLS, the association of systolic blood pressure with cognitive function was not significant and the association of age with cognitive function was lower by 16.6% (from -6.237 to -5.201). By ignoring the MMSE floor and ceiling effects in the simulation study, the relative bias in the estimated association of female gender with cognitive function was 43 times higher (from -0.01 to -0.44). The estimated associations obtained with data missing at random were smaller than those with data missing not at random, demonstrating how the missing data mechanism affects the analytic results. Our work underscores the importance of proper model specification in longitudinal analysis of correlated outcomes subject to missingness and bounded values.

A machine-learning modified CART algorithm informs Merkel cell carcinoma prognosis.

BACKGROUND: Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with a high mortality rate. MCC staging is currently based on tumour primary size, clinical detectability of lymph node metastases, performance of a lymph node biopsy, and presence of distant metastases. OBJECTIVE: We aimed to use a modified classification and regression tree (CART) algorithm using available data points in the National Cancer Database (NCDB) to elucidate novel prognostic factors for MCC. METHODS: Retrospective cohort study of the NCDB and Surveillance, Epidemiology, and End Results (SEER) registries. Cases from the NCDB were randomly assigned to either the training or validation cohorts. A modified CART algorithm was created with data from the training cohort and used to identify prognostic groups that were validated in the NCDB validation and SEER cohorts. RESULTS: A modified CART algorithm using tumour variables available in the NCDB identified prognostic strata as follows: I: local disease, II: ≤3 positive nodes, III: ≥4 positive nodes, and IV: presence of distant metastases. Three-year survival for these groups in the NCDB validation cohort were 81.2% (SE: 1.7), 59.6% (SE: 3.0), 38.0% (SE: 6.0), and 20.2% (SE: 7.0), respectively. These strata were exhibited greater within-group homogeneity than AJCC groups and were more predictive of survival. CONCLUSIONS: Risk-stratified grouping of MCC patients incorporating positive lymph node count were strongly predictive of survival and demonstrated a high degree of within-group homogeneity and survival prediction. Incorporation of positive lymph node count within overall staging or sub-staging may help to improve future MCC staging criteria.

Associations of food groups and cardiometabolic and inflammatory biomarkers: does the meal matter?

Increased attention has been paid to circadian patterns and how predisposition to metabolic disorders can be affected by meal timing. Currently, it is not clear which role can be attributed to the foods selected at meals. On a cross-sectional sub-cohort study (815 adults) within the European Prospective Investigation into Cancer and Nutrition-Potsdam study, we investigated whether the same foods (vegetables, fruits, refined grains, whole grains, red and processed meats) eaten at different meals (breakfast, lunch or dinner) show different associations with biomarkers of cardiometabolic risk. Meal-specific usual intakes were calculated from multiple 24-h dietary recalls. Multivariable-adjusted linear regression models showed that intake of vegetables at breakfast was associated with lower LDL-cholesterol (-0·37 mmol/l per 50 g; 95 % CI -0·61, -0·12) and vegetables at dinner was associated with higher HDL-cholesterol (0·05 mmol/l per 50 g; 95 % CI 0, 0·10). Fruit intake at breakfast was associated with lower glycated Hb (HbA1c) (-0·06 % per 50 g; 95 % CI -0·10, -0·01) and fruits at dinner with lower C-reactive protein (CRP) (-0·21 mg/l per 50 g; 95 % CI -0·42, -0·01). Red and processed meat intake at breakfast was associated with higher HbA1c (0·25 % per 50 g; 95 % CI 0·05, 0·46) and CRP (0·76 mg/l per 50 g; 95 % CI 0·15, 1·36). Our results suggest that by preferring fruits and vegetables and avoiding red and processed meats at specific meals (i.e. breakfast and dinner), cardiometabolic profiles and ultimately chronic disease risk could be improved. Lunch seemed to be a less important meal in terms of food-biomarker associations.

Treatment of primary nonmetastatic melanoma at high-volume academic facilities is associated with improved long-term patient survival.

BACKGROUND: Previous studies of cancer care have demonstrated improved long-term patient outcomes for those treated at high-volume centers. The influence of treatment center characteristics on outcomes for primary nonmetastatic melanoma is not currently established. OBJECTIVE: We aimed to investigate the association of cancer treatment center case volume and academic affiliation with long-term patient survival for cases of primary nonmetastatic melanoma. METHODS: Cases of melanoma diagnosed in US adults from 2004 to 2014 and included in the National Cancer Database were identified. Hospitals were grouped by yearly case-volume quartile: bottom quartile, 2 middle quartiles, and top quartile. RESULTS: Facility case volume was significantly associated with long-term patient survival (P < .0001). The 5-year survival rates were 76.8%, 81.9%, and 86.4% for patients treated at institutions in the bottom, middle, and top quartiles of case volume, respectively. On multivariate analysis, treatment at centers in both middle quartiles (hazard ratio, 0.834; 95% confidence interval, 0.778-0.895) and in the top quartile (hazard ratio, 0.691; 95% confidence interval, 0.644-0.741) of case volume was associated with improved survival relative to that of patients treated at hospitals in the bottom quartile of case volume. Academic affiliation was associated with improved outcomes for top-quartile- but not middle-quartile-volume facilities. LIMITATIONS: Disease-specific survival was not available. CONCLUSIONS: Treatment at a high-volume facility is associated with improved long-term patient survival for melanoma. High-volume academic centers have improved patient outcomes compared with other high-volume centers.

Meal analysis for understanding eating behavior: meal- and participant-specific predictors for the variance in energy and macronutrient intake.

BACKGROUND: Meals differ in their nutritional content. This variation has not been fully addressed despite its potential contribution in understanding eating behavior. The aim of this study was to investigate the between-meal and between-individual variance in energy and macronutrient intake as a measure of variation in intake and the meal type-specific relative importance of predictors of these intake variations. METHODS: Energy and macronutrient intake were derived from three 24 h dietary recalls in an EPIC-Potsdam sub-cohort of 814 German adults. Intra-class correlation was calculated for participants and meal type. Predictors of intake were assessed using meal type-specific multilevel regression models in a structural equation modeling framework at intake and participant levels using the Pratt Index. The importance of the predictor energy misreporting was assessed in sensitivity analyses on 682 participants. 95% confidence intervals were calculated based on 1000 bootstrap samples. RESULTS: Differences between meal types explain a large proportion of the variation in intake (intra-class correlation: 39% for energy, 25% for carbohydrates, 47% for protein, and 33% for fat). Between-participant variation in intake was much lower, with a maximum of 3% for carbohydrate and fat. Place of meal was the most important intake-level predictor of energy and macronutrient intake (Pratt Index of up to 65%). Week/weekend day was important in the breakfast meal, and prior interval (hours passed since last meal) was important for the afternoon snack and dinner. On the participant level, sex was the most important predictor, with Pratt Index of up to 95 and 59% in the main and in the sensitivity analysis, respectively. Energy misreporting was especially important at the afternoon snack, accounting for up to 69% of the explained variance. CONCLUSIONS: The meal type explains the highest variation in energy and macronutrient intakes. We identified key predictors of variation in the intake and in the participant levels. These findings suggest that successful dietary modification efforts should focus on improving specific meals.

Correction to: Meal analysis for understanding eating behavior: meal- and participant-specific predictors for the variance in energy and macronutrient intake.

Following publication of the original article [1], the authors reported an error in Table 3. The correct Table 3 is provided below.

Longitudinal associations between different dementia diagnoses and medication use jointly accounting for dropout.

ABSTRACTBackground:Longitudinal studies of older adults are characterized by high dropout rates, multimorbid conditions, and multiple medication use, especially proximal to death. We studied the association between multiple medication use and incident dementia diagnoses including Alzheimer's disease (AD), vascular dementia (VD), and Lewy-body dementia (LBD), simultaneously accounting for dropout. METHODS: Using the National Alzheimer's Coordinating Center data with three years of follow-up, a set of covariate-adjusted models that ignore dropout was fit to complete-case data, and to the whole-cohort data. Additionally, covariate-adjusted joint models with shared random effects accounting for dropout were fit to the whole-cohort data. Multiple medication use was defined as polypharmacy (⩾ five medications), hyperpolypharmacy (⩾ ten medications), and total number of medications. RESULTS: Incident diagnoses were 2,032 for AD, 135 for VD, and 139 for LBD. Percentages of dropout at the end of follow-up were as follows: 71.8% for AD, 81.5% for VD, and 77.7% for LBD. The odds ratio (OR) estimate for hyperpolypharmacy among those with LBD versus AD was 2.19 (0.78, 6.15) when estimated using complete-case data and 3.00 (1.66, 5.40) using whole-cohort data. The OR reduced to 1.41 (0.76, 2.64) when estimated from the joint model accounting for dropout. The OR for polypharmacy using complete-case data differed from the estimates using whole-cohort data. The OR for dementia diagnoses on total number of medications was similar, but non-significant when estimated using complete-case data. CONCLUSION: Reasons for dropout should be investigated and appropriate statistical methods should be applied to reduce bias in longitudinal studies among high-risk dementia cohorts.

A zero-augmented generalized gamma regression calibration to adjust for covariate measurement error: A case of an episodically consumed dietary intake.

Measurement error in exposure variables is a serious impediment in epidemiological studies that relate exposures to health outcomes. In nutritional studies, interest could be in the association between long-term dietary intake and disease occurrence. Long-term intake is usually assessed with food frequency questionnaire (FFQ), which is prone to recall bias. Measurement error in FFQ-reported intakes leads to bias in parameter estimate that quantifies the association. To adjust for bias in the association, a calibration study is required to obtain unbiased intake measurements using a short-term instrument such as 24-hour recall (24HR). The 24HR intakes are used as response in regression calibration to adjust for bias in the association. For foods not consumed daily, 24HR-reported intakes are usually characterized by excess zeroes, right skewness, and heteroscedasticity posing serious challenge in regression calibration modeling. We proposed a zero-augmented calibration model to adjust for measurement error in reported intake, while handling excess zeroes, skewness, and heteroscedasticity simultaneously without transforming 24HR intake values. We compared the proposed calibration method with the standard method and with methods that ignore measurement error by estimating long-term intake with 24HR and FFQ-reported intakes. The comparison was done in real and simulated datasets. With the 24HR, the mean increase in mercury level per ounce fish intake was about 0.4; with the FFQ intake, the increase was about 1.2. With both calibration methods, the mean increase was about 2.0. Similar trend was observed in the simulation study. In conclusion, the proposed calibration method performs at least as good as the standard method.

A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data.

BACKGROUND: Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. METHODS: We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. RESULTS: Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. CONCLUSIONS: The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.

An Epidemiologic Study on Ageing and Dysphagia in the Acute Care Geriatric-Hospitalized Population: A Replication and Continuation Study.

United States census data project dramatic increases in the geriatric population ageing demographics by 2060 with concomitant health-care consequences. The purpose of this replication and continuation study was to collect new 2014 demographic data relative to ageing, swallow evaluation referral rates, and oral feeding status in geriatric-hospitalized patients for comparison with published data from 2000 to 2007. This was a planned data acquisition study of consecutive hospitalized patients referred for swallow assessments. Swallow evaluation referral rates for 2014 were described according to inpatient discharges, age range 60-105 years grouped by decade, gender, admitting diagnostic category, results of swallow evaluations, and oral feeding status. Determination of aspiration risk status was made with the Yale Swallow Protocol and diagnosis of dysphagia made with fiberoptic endoscopic evaluation of swallowing (FEES). There were 1348 referrals and 961 patients ≥60 years of age participated. Overall swallow evaluation referral rates increased an average of 63 % between the comparison years 2007 and 2014 with consistent increases corresponding to the decades, i.e., 60-69 (46 %), 70-79 (68 %), 80-89 (53 %), and 90+ (222 %). A total of 75 % of participants resumed oral alimentation and oral medications. Swallow evaluation referral rates increased by 63 % for 60-90+ year-old acute care geriatric-hospitalized participants despite only a 23 % increase in inpatient discharges for the years 2007 versus 2014. This corroborated previously reported increases for individual years from 2000 to 2007. For timely, safe, and successful initiation of oral alimentation, it is important to perform a reliable swallow screen for aspiration risk assessment with the Yale Swallow Protocol and, if failed, instrumental testing with FEES. More dysphagia specialists are needed through 2060 and beyond due to projections of continued population ageing resulting in ever increasing referral rates for swallow assessments.

Evaluation of a two-part regression calibration to adjust for dietary exposure measurement error in the Cox proportional hazards model: A simulation study.

Dietary questionnaires are prone to measurement error, which bias the perceived association between dietary intake and risk of disease. Short-term measurements are required to adjust for the bias in the association. For foods that are not consumed daily, the short-term measurements are often characterized by excess zeroes. Via a simulation study, the performance of a two-part calibration model that was developed for a single-replicate study design was assessed by mimicking leafy vegetable intake reports from the multicenter European Prospective Investigation into Cancer and Nutrition (EPIC) study. In part I of the fitted two-part calibration model, a logistic distribution was assumed; in part II, a gamma distribution was assumed. The model was assessed with respect to the magnitude of the correlation between the consumption probability and the consumed amount (hereafter, cross-part correlation), the number and form of covariates in the calibration model, the percentage of zero response values, and the magnitude of the measurement error in the dietary intake. From the simulation study results, transforming the dietary variable in the regression calibration to an appropriate scale was found to be the most important factor for the model performance. Reducing the number of covariates in the model could be beneficial, but was not critical in large-sample studies. The performance was remarkably robust when fitting a one-part rather than a two-part model. The model performance was minimally affected by the cross-part correlation.

The effect of COVID-19 pandemic on healthcare seeking in an urban informal settlement in Nairobi and a rural setting in western Kenya.

The COVID-19 pandemic caused widespread changes and disruptions to healthcare seeking behavior. There are limited studies on the effect of the COVID-19 pandemic on healthcare seeking patterns in low-and middle-income countries (LMICs), especially in settings with inequitable access to healthcare in rural and urban informal settlements. We investigated the effect of the COVID-19 pandemic on reported healthcare seeking at health facilities and chemists using morbidity data from participants in an ongoing population-based infectious disease surveillance platform in Asembo in Siaya County, a rural setting in western Kenya and Kibera, an urban informal settlement in Nairobi County. We described healthcare seeking patterns before (from 1st January 2016 to 12th March 2020) and during the pandemic (from 13th March 2020 to 31st August 2022) by gender and age for any reported illness and select clinical syndromes using frequencies and percentages. We used a generalized estimating equation with an exchangeable correlation structure to assess the effect of the pandemic on healthcare seeking adjusting for gender and age. Overall, there was a 19% (adjusted odds ratio, aOR: 0.81; 95% Confidence Interval, CI: 0.79-0.83) decline in odds of seeking healthcare at health facilities for any illness in Asembo during the pandemic, and a 30% (aOR: 0.70; 95% CI: 0.67-0.73) decline in Kibera. Similarly, there was a decline in seeking healthcare by clinical syndromes, e.g., for ARI, aOR: 0.76; 95% CI:0.73-0.79 in Asembo, and aOR: 0.68; 95% CI:0.64-0.72 in Kibera. The pandemic resulted in increased healthcare seeking at chemists (aOR: 1.23; 95% CI: 1.20-1.27 in Asembo, and aOR: 1.40; 95% CI: 1.35-1.46 in Kibera). This study highlights interruptions to healthcare seeking in resource-limited settings due to the COVID-19 pandemic. The pandemic resulted in a substantial decline in seeking care at health facilities, and an increase of the same at chemists.

A multivariate joint model to adjust for random measurement error while handling skewness and correlation in dietary data in an epidemiologic study of mortality.

PURPOSE: A substantial proportion of global deaths is attributed to unhealthy diets, which can be assessed at baseline or longitudinally. We demonstrated how to simultaneously correct for random measurement error, correlations, and skewness in the estimation of associations between dietary intake and all-cause mortality. METHODS: We applied a multivariate joint model (MJM) that simultaneously corrected for random measurement error, skewness, and correlation among longitudinally measured intake levels of cholesterol, total fat, dietary fiber, and energy with all-cause mortality using US National Health and Nutrition Examination Survey linked to the National Death Index mortality data. We compared MJM with the mean method that assessed intake levels as the mean of a person's intake. RESULTS: The estimates from MJM were larger than those from the mean method. For instance, the logarithm of hazard ratio for dietary fiber intake increased by 14 times (from -0.04 to -0.60) with the MJM method. This translated into a relative hazard of death of 0.55 (95% credible interval: 0.45, 0.65) with the MJM and 0.96 (95% credible interval: 0.95, 0.97) with the mean method. CONCLUSIONS: MJM adjusts for random measurement error and flexibly addresses correlations and skewness among longitudinal measures of dietary intake when estimating their associations with death.

Correcting for measurement error in assessing gestational age in a low-resource setting: a regression calibration approach.

Introduction: Measurement error in gestational age (GA) may bias the association of GA with a health outcome. Ultrasound-based GA is considered the gold standard and is not readily available in low-resource settings. We corrected for measurement error in GA based on fundal height (FH) and date of last menstrual period (LMP) using ultrasound from the sub-cohort and adjusted for the bias in associating GA with neonatal mortality and low birth weight (< 2,500 grams, LBW). Methods: We used data collected from 01/2015 to 09/2019 from pregnant women enrolled at two public hospitals in Siaya county, Kenya (N = 2,750). We used regression calibration to correct for measurement error in FH- and LMP-based GA accounting for maternal and child characteristics. We applied logistic regression to associate GA with neonatal mortality and low birth weight, with and without calibrating FH- and LMP-based GA. Results: Calibration improved the precision of LMP (correlation coefficient, ρ from 0.48 to 0.57) and FH-based GA (ρ from 0.82 to 0.83). Calibrating FH/LMP-based GA eliminated the bias in the mean GA estimates. The log odds ratio that quantifies the association of GA with neonatal mortality increased by 29% (from -0.159 to -0.205) by calibrating FH-based GA and by more than twofold (from -0.158 to -0.471) by calibrating LMP-based GA. Conclusion: Calibrating FH/LMP-based GA improved the accuracy and precision of GA estimates and strengthened the association of GA with neonatal mortality/LBW. When assessing GA, neonatal public health and clinical interventions may benefit from calibration modeling in settings where ultrasound may not be fully available.

Weight change across adulthood and accelerated biological aging in middle-aged and older adults.

BACKGROUND: Little is known regarding the association between weight change and accelerated aging. OBJECTIVES: This study aimed to estimate the influence of weight change across adulthood on biological aging acceleration in middle-aged and older adults in the United States. METHODS: We used data of 5553 adults (40-84 y) from the National Health and Nutrition Examination Survey 1999-2010. Weight change patterns (i.e., stable normal, maximal overweight, obese to nonobese, nonobese to obese, and stable obese) and absolute weight change groups across adulthood (i.e., from young to middle adulthood, young to late adulthood, and middle to late adulthood) were defined. A biological aging measure (i.e., phenotypic age acceleration [PhenoAgeAccel]) at late adulthood was calculated. Survey analysis procedures with the survey weights were performed. RESULTS: Across adulthood, maximal overweight, nonobese to obese, and stable obesity were consistently associated with higher PhenoAgeAccel. For instance, from young to middle adulthood, compared with participants who had stable normal weight, participants experiencing maximal overweight, moving from the nonobese to obese, and maintaining obesity had 1.71 (standard error [SE], 0.21; P < 0.001), 3.62 (SE, 0.28; P < 0.001), and 6.61 (SE, 0.58; P < 0.001) higher PhenoAgeAccel values, respectively. From young to middle adulthood, relative to absolute weight loss or gain of <2.5 kg, weight loss of ≥2.5 kg was marginally associated with lower PhenoAgeAccel (P = 0.054), whereas an obese to nonobese pattern from middle to late adulthood was associated with higher PhenoAgeAccel (P < 0.001). CONCLUSIONS: Maximal overweight, nonobese to obese, and stable obesity across adulthood, as well as an obese to nonobese pattern from middle to late adulthood, were associated with accelerated biological aging. In contrast, weight loss from young to middle adulthood was associated with decelerated biological aging. The findings highlight the potential role of weight management across adulthood for aging. Monitoring weight fluctuation may help identify the population at high risk of accelerated aging.

Associations of Midlife Dietary Patterns with Incident Dementia and Brain Structure: Findings from the UK Biobank Study.

BACKGROUND: At present, the results on the associations between dietary patterns and risk of dementia are inconsistent, and studies on the associations between dietary patterns and brain structures are limited. OBJECTIVES: We aimed to investigate the associations of midlife dietary patterns with incident dementia and brain structures. METHODS: On the basis of the UK Biobank Study, we investigated the 1) prospective associations of 4 healthy dietary pattern indices [healthy plant-based diet index (hPDI), Mediterranean diet score (MDS), recommended food score (RFS), and Mediterranean-DASH Intervention for Neurodegenerative Delay Diet (MIND)] with incident dementia (identified using linked hospital data; N = 114,684; mean age, 56.8 y; 55.5% females) using Cox proportional-hazards regressions and the 2) cross-sectional associations of these dietary pattern indices with brain structures (estimated using magnetic resonance imaging; N = 18,214; mean age, 55.9 y; 53.1% females) using linear regressions. A series of covariates were adjusted, and several sensitivity analyses were conducted. RESULTS: A total of 481 (0.42%) participants developed dementia during the average 9.4-y follow-up. Although the associations were not statistically significant, all dietary patterns exerted protective effects against incident dementia (all HRs < 1). Furthermore, higher dietary pattern indices were significantly associated with larger regional brain volumes, including volumes of gray matter in the parietal and temporal cortices and volumes of the hippocampus and thalamus. The main results were confirmed via sensitivity analyses. CONCLUSIONS: Greater adherence to hPDI, MDS, RFS, and MIND was individually associated with larger brain volumes in specific regions. This study shows a comprehensive picture of the consistent associations of midlife dietary patterns with risk of dementia and brain health, underscoring the potential benefits of a healthy diet in the prevention of dementia.