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Jan P Vandenbroucke,1– 3 Henrik Toft Sørensen,1,4 David H Rehkopf,5 Jaimie L Gradus,6 Johan P Mackenbach,7 M Maria Glymour,8 Sandro Galea,9 Victor W Henderson1,10 1Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark; 2Leiden University, Leiden, Netherlands; 3London School of Hygiene & Tropical Medicine, London, UK; 4Aarhus University Hospital, Aarhus, Denmark; 5Stanford Center for Population Health Sciences, Stanford University, CA, USA; 6Department of Epidemiology, School of Public Health, Boston University, Boston, MA, USA; 7Department of Public Health, Erasmus University Rotterdam, Rotterdam, Holland; 8Department of Epidemiology, Boston University School of Public Health, Boston University, Boston, MA, USA; 9School of Public Health, Boston University, Boston, MA, USA; 10Departments of Epidemiology & Population Health and of Neurology & Neurological Sciences, Stanford University, Stanford, CA, USAAbstract: This paper is a summary of key presentations from a workshop in Iceland on May 3– 4, 2023 arranged by Aarhus University and with participation of the below-mentioned scientists.Below you will find the key messages from the presentations made by:Professor Jan Vandenbroucke, Department of Clinical Epidemiology, Aarhus University, Emeritus Professor, Leiden University; Honorary Professor, London School of Hygiene & Tropical Medicine, UKProfessor, Chair Henrik Toft Sørensen, Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, DenmarkProfessor David H. Rehkopf, Director, the Stanford Center for Population Health Sciences, Stanford University, CA., USProfessor Jaimie Gradus, Department of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts, USProfessor Johan Mackenbach, Emeritus Professor, Department of Public Health, Erasmus University Rotterdam, HollandProfessor, Chair M Maria Glymour, Department of Epidemiology, Boston University School of Public Health, Boston University, Boston, Massachusetts, USProfessor, Dean Sandro Galea, School of Public Health, Boston University, Boston, Massachusetts, USProfessor Victor W. Henderson, Departments of Epidemiology & Population Health and of Neurology & Neurological Sciences, Stanford University, Stanford, CA, US; Department of Clinical Epidemiology, Aarhus University, Aarhus, DKKeywords: Ageing, Multimorbidity, Social inequality

Background: Economic disadvantage is associated with depression and suicide. We sought to determine whether economic disadvantage reduces the effectiveness of depression treatments received in primary care.Methods: We conducted differential-effects analyses of the Prevention of Suicide in Primary Care Elderly: Collaborative Trial, a primary-care-based randomized, controlled trial for late-life depression and suicidal ideation conducted between 1999 and 2001, which included 514 patients with major depression or clinically significant minor depression.Results: The intervention effect, defined as change in depressive symptoms from baseline, was stronger among persons reporting financial strain at baseline (differential effect size = -4.5 Hamilton Depression Rating Scale points across the study period [95% confidence interval = -8.6 to -0.3]). We found similar evidence for effect modification by neighborhood poverty, although the intervention effect weakened after the initial 4 months of the trial for participants residing in poor neighborhoods. There was no evidence of substantial differences in the effectiveness of the intervention on suicidal ideation and depression remission by economic disadvantage.Conclusions: Economic conditions moderated the effectiveness of primary-care-based treatment for late-life depression. Financially strained individuals benefited more from the intervention; we speculate this was because of the enhanced treatment management protocol, which led to a greater improvement in the care received by these persons. People living in poor neighborhoods experienced only temporary benefit from the intervention. Thus, multiple aspects of economic disadvantage affect depression treatment outcomes; additional work is needed to understand the underlying mechanisms. [ABSTRACT FROM AUTHOR]

Background: Early-life socioeconomic status (SES) is associated with adult chronic disease, but it is unclear whether this effect is mediated entirely via adult SES or whether there is a direct effect of adverse early-life SES on adult disease. Major challenges in evaluating these alternatives include imprecise measurement of early-life SES and bias in conventional regression methods to assess mediation. In particular, conventional regression approaches to direct effect estimation are biased when there is time-varying confounding of the association between adult SES and chronic disease by chronic disease risk factors.Methods: First-reported heart disease, diabetes, and stroke diagnoses were assessed in a national sample of 9760 Health and Retirement Study participants followed biennially from 1992 through 2006. Early-life and adult SES measures were derived using exploratory and confirmatory factor analysis. Early-life SES was measured by parental education, father's occupation, region of birth, and childhood rural residence. Adult SES was measured by respondent's education, occupation, labor force status, household income, and household wealth. Using marginal structural models, we estimated the direct effect of early-life SES on chronic disease onset that was not mediated by adult SES. Marginal structural models were estimated with stabilized inverse probability-weighted log-linear models to adjust for risk factors that may have confounded associations between adult SES and chronic disease.Results: During follow-up, 24%, 18%, and 9% of participants experienced first onset of heart disease, diabetes, and stroke, respectively. Comparing those in the most disadvantaged with the least disadvantaged quartile, early-life SES was associated with coronary heart disease (risk ratio = 1.30 [95% confidence interval = 1.12-1.51]) and diabetes (1.23 [1.02-1.48]) and marginally associated with stroke via pathways not mediated by adult SES.Conclusions: Our results suggest that early-life socioeconomic experiences directly influence adult chronic disease outcomes. [ABSTRACT FROM AUTHOR]

Background: Selective attrition may introduce bias into analyses of the determinants of cognitive decline. This is a concern especially for risk factors, such as smoking, that strongly influence mortality and dropout. Using inverse-probability-of-attrition weights, we examined the influence of selective attrition on the estimated association of current smoking (vs. never smoking) with cognitive decline.Methods: Chicago Health and Aging Project participants (n = 3713), aged 65-109 years, who were current smokers or never- smokers, underwent cognitive assessments up to 5 times at 3-year interval. We used pooled logistic regression to fit predictive models of attrition due to death or study dropout across the follow-up waves. With these models, we computed inverse-probability-of-attrition weights for each observation. We fit unweighted and weighted, multivariable-adjusted generalized-estimating-equation models, contrasting rates of change in cognitive scores in current versus never-smokers. Estimates are expressed as rates of change in z score per decade.Results: During the 12 years of follow-up, smokers had higher mortality than never-smokers (hazard ratio = 1.93 [95% confidence interval = 1.67 to 2.23]). Higher previous cognitive score was associated with increased likelihood of survival and continued participation. In unweighted analyses, current smokers' cognitive scores declined 0.11 standard units per decade more rapidly than never-smokers' (95% CI = -0.20 to -0.02). Weighting to account for attrition yielded estimates that were 56% to 86% larger, with smokers' estimated 10-year rate of decline up to 0.20 units faster than never-smokers' (95% CI = -0.36 to -0.04).Conclusions: Estimates of smoking's effects on cognitive decline may be underestimated due to differential attrition. Analyses that weight for the inverse probability of attrition help compensate for this attrition. [ABSTRACT FROM AUTHOR]

We hypothesized that patterns of elevated stroke mortality among those born in the United States Stroke Belt (SB) states also prevailed for mortality related to all-cause dementia or Alzheimer Disease. Cause-specific mortality (contributing cause of death, including underlying cause cases) rates in 2000 for United States-born African Americans and whites aged 65 to 89 years were calculated by linking national mortality records with population data based on race, sex, age, and birth state or state of residence in 2000. Birth in a SB state (NC, SC, GA, TN, AR, MS, or AL) was cross-classified against SB residence at the 2000 Census. Compared with those who were not born in the SB, odds of all-cause dementia mortality were significantly elevated by 29% for African Americans and 19% for whites born in the SB. These patterns prevailed among individuals who no longer lived in the SB at death. Patterns were similar for Alzheimer Disease-related mortality. Some non-SB states were also associated with significant elevations in dementia-related mortality. Dementia mortality rates follow geographic patterns similar to stroke mortality, with elevated rates among those born in the SB. This suggests important roles for geographically patterned childhood exposures in establishing cognitive reserve. [ABSTRACT FROM AUTHOR]

OBJECTIVES: We compared the health of older US, English, and other European adults, stratified by wealth. METHODS: Representative samples of adults aged 50 to 74 years were interviewed in 2004 in 10 European countries (n = 17,481), England (n = 6527), and the United States (n = 9940). We calculated prevalence rates of 6 chronic diseases and functional limitations. RESULTS: American adults reported worse health than did English or European adults. Eighteen percent of Americans reported heart disease, compared with 12% of English and 11% of Europeans. At all wealth levels, Americans were less healthy than were Europeans, but differences were more marked among the poor. Health disparities by wealth were significantly smaller in Europe than in the United States and England. Odds ratios of heart disease in a comparison of the top and bottom wealth tertiles were 1.94 (95% confidence interval [CI] = 1.69, 2.24) in the United States, 2.13 (95% CI = 1.73, 2.62) in England, and 1.38 (95% CI = 1.23, 1.56) in Europe. Smoking, obesity, physical activity levels, and alcohol consumption explained a fraction of health variations. CONCLUSIONS: American adults are less healthy than Europeans at all wealth levels. The poorest Americans experience the greatest disadvantage relative to Europeans. [ABSTRACT FROM AUTHOR]

OBJECTIVE: We examined the relationships between the National Institute of Health Stroke Scale (NIHSS) and physical, cognitive, and social participation outcomes across subpopulations of stroke survivors on the basis of cortical involvement and lesion lateralization. DESIGN: Families in Recovery from Stroke Trial participants were classified with respect to lesion lateralization (n = 274) and cortical involvement (n = 158). NIHSS scores (average 13 days after stroke) were used to predict Physical Performance Test times (PPT), limitations in activities of daily living (Augmented Barthel Index (ABI)), Instrumental Activities of Daily Living (IADL), cognitive function, depressive symptoms (Center for Epidemiologic Studies Depression scale [CES-D]), and productive, recreational, self-care, and social role activities 3 and 6 mos later. We compared the relationship between NIHSS and each outcome in stroke subgroups classified by lesion lateralization and cortical involvement. RESULTS: NIHSS predicted physical performance, activities of daily living, and IADL independence. The association between NIHSS and both PPT and IADLs was less steep for patients with cortical lesions than for patients with exclusively subcortical lesions. NIHSS predicted physical performance, activities of daily living, or IADLs similarly for right- and left-hemisphere strokes, but hemisphere modified the association between NIHSS and CES-D and cognitive measures. CONCLUSIONS: The NIHSS may predict outcomes in subpopulations of stroke survivors with subcortical lesions better than in patients with cortical involvement. NIHSS predicted CES-D in patients with right-sided lesions but not in those with left-sided lesions. In contrast, NIHSS had little association with cognitive outcomes among patients without left-side involvement. [ABSTRACT FROM AUTHOR]

Scientific interest frequently focuses on how factors that influence disease onset subsequently affect disease progression. In this commentary, the author discusses four sources of bias that arise in such work. The focus is on Tyas et al.'s analyses (Am J Epidemiol 2007;165:1231-1238) of how the apolipoprotein E *E4 allele, a well-documented risk factor for Alzheimer's disease, influences progression of cognitive impairments from mild or global cognitive impairment to dementia or death. The author addresses four phenomena that can lead to spurious (noncausal) associations between apolipoprotein E *E4 status and rate of progression of cognitive impairments: beginning observations in the middle of a developing pathologic process, survivor bias, uncertainty in the timing of disease diagnosis, and nonlinear disease progression trajectories. Because these sources of bias are potentially relevant in any study of how risk factors for disease onset influence disease progression, the author advocates assessing their likely magnitude in specific contexts when interpreting results. [ABSTRACT FROM AUTHOR]