Solja T Nyberg’s research while affiliated with University of Helsinki and other places

Social disadvantage, like advanced age, is a risk factor for a broad range of health conditions; however, whether it influences the aging process remains unclear. Here, using a multicohort approach, we investigated the associations of social disadvantage with age-related plasma proteins and age-related diseases. We found proteomic signatures of accelerated immune aging and 14 specific age-related proteins linked to social disadvantage during both early and later life. Individuals experiencing social disadvantage had an increased risk of 66 age-related diseases, with up to 39% of these associations mediated by the 14 age-related proteins (for example, DNAJB9, F2, HSPA1A, BGN). The main enriched pathway involved the upregulation of the pro-inflammatory regulator NF-κB24 and its downstream factor interleukin-8. Our findings support the hypothesis that social disadvantage throughout the life course may accelerate aging, a biological mechanism that could explain why social stratification plays such a fundamental role in determining human health.

Background Regular physical activity is recommended for all aged 5 years and older, but the health benefits gained might differ across population subgroups. The aim of this study was to examine these benefits in terms of years lived free from major non-communicable diseases in subgroups with varying levels of risk factors. Methods Our analysis was based on a multicohort study of initially healthy European adults from the IPD-Work Consortium and initially healthy participants from the UK Biobank study. Self-reported leisure-time physical activity levels at baseline (1986–2010) were categorised as low (no or very little), intermediate (between low and recommended levels), and WHO-recommended (≥2·5 h of moderate or ≥1·25 h of vigorous physical activity per week). We divided the study population into 36 overlapping subgroups based on socioeconomic factors, lifestyle, and mental health at baseline, and assessed disease-free years between ages 40 years and 75 years for both the overall population and subgroups, accounting for coronary heart disease, stroke, type 2 diabetes, cancer, asthma, and chronic obstructive pulmonary disease. Findings 14 IPD-Work studies were assessed and six studies were excluded due to missing outcome data and unavailable data for pooling, resulting in the inclusion of eight studies with 124 909 participants. After the exclusion of 7685 participants due to prevalent diseases and 9265 due to missing data, the sample consisted of 107 959 initially healthy European adults (63 567 [58·9%] females and 44 392 [41·1%] males) from the IPD-Work consortium. For the UK Biobank sample, 9 238 453 million individuals were invited, 8 736 094 (94·6%) were non-respondents, and 502 359 participated in the baseline examination. After the exclusion of 73 460 participants, 428 899 participants had data on at least one measure of physical activity. 236 258 (55·1%) were female and 192 641 (44·9%) were male. During 1·6 million person-years at risk, 21 231 IPD-Work participants developed a non-communicable disease, while 101 319 UK Biobank participants developed a non-communicable disease over 4·8 million person-years at risk. Compared with individuals with low physical activity, those meeting the recommended physical activity levels during leisure-time gained an additional 1·1 (95% CI 1·0–1·2) to 2·0 (1·7–2·3) disease-free years, depending on sex and study. In males from the IPD-Work and UK Biobank cohorts, greater gains in disease-free years were observed in current smokers (2·4 [95% CI 2·1–2·8]) versus never smokers (0·7 [0·5–0·9]); those with low education (1·4 [1·1–1·7]) versus high education (0·8 [0·7–1·0]); low socioeconomic status (1·7 [1·5–2·0]) versus high socioeconomic status (0·9 [0·7–1·1]); and those with (1·6 [1·3–1·9]) versus without depressive symptoms (1·0 [0·9–1·1]; p value range <0·0001–0·0008). Similar differences were seen in women for smoking (2·3 [95% CI 1·9–2·7] vs 0·9 [0·7–1·1]), socioeconomic status (1·7 [1·4–2·0] vs 0·8 [0·5–1·0]), depressive symptoms (1·4 [1·1–1·7] vs 1·0 [0·9–1·1]), and for heavy drinkers compared with moderate drinkers (1·4 [1·1–1·6] vs 0·9 [0·7–1·1]; p value range <0·0001–0·010). No differences in physical activity-related health gains were observed between risk groups and non-risk groups by BMI, history of depression, and, in men, alcohol use (p value range 0·11–0·86). Interpretation In addition to confirming the association between leisure-time physical activity and increased disease-free years across population subgroups, our findings show that these health benefits are often more pronounced among individuals with pre-existing health risks or disadvantaged backgrounds than in those with more favourable risk factor profiles. This suggests that enhancing population-wide physical activity initiatives could help reduce health disparities, while incorporating physical activity into targeted strategies addressing social disadvantage, unhealthy lifestyles, and depression might enhance their effectiveness. Funding Wellcome Trust, UK Medical Research Council, US National Institute on Aging, and Research Council of Finland.

Background Ageing hallmarks, characterising features of cellular ageing, have a role in the pathophysiology of many age-related diseases. We examined whether obesity is associated with an increased risk of developing such hallmark-related diseases. Methods In this multicohort study, we included people aged 38–72 years with data on weight, height, and waist circumference measured during a clinical examination at baseline between March 13, 2006, and Oct 1, 2010, from the UK Biobank with follow-up until Nov 12, 2021. To test reproducibility of the findings (replication analysis), we used data from people aged 40 years or older included in the Finnish Public Sector study and the Finnish Health and Social Support study who responded to the study surveys, had data on BMI, and were successfully linked to electronic health records from national registers up to Dec 31, 2016. Obesity and clinical characteristics were assessed at baseline. Via linkage to national health records, participants were followed up for 83 diseases related to nine ageing hallmarks (genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication). Outcomes were the first instance of hallmark-related disease, in addition to co-occurrence of three or more hallmark-related diseases and mortality. Findings 496 530 adults (mean age 57·0 years [SD 8·1]) from the UK Biobank were included in the primary analysis, and 83 249 (mean age 48·2 years [6·4]) adults from the Finnish cohorts were included in the replication analysis. Median follow-up was 12·7 years (IQR 12·0–13·4) in the UK Biobank and 14·0 years (8·0–15·0) in the Finnish cohorts. After adjusting for demographic characteristics, lifestyle factors, and depression, UK Biobank participants with obesity (BMI ≥30·0 kg/m2) had a 1·40 (95% CI 1·38–1·41) times higher hazard ratio for the first hallmark-related disease than those with a healthy weight (BMI 18·5–24·9 kg/m2). The corresponding hazard ratios for three co-occurring diseases were 2·92 (95% CI 2·64–3·22) for deregulated nutrient sensing, 2·73 (2·46–3·02) for telomere attrition, 2·33 (2·10–2·60) for epigenetic alterations, 2·30 (2·14–2·48) for mitochondrial dysfunction, 2·23 (2·04–2·45) for stem cell exhaustion, 2·02 (1·89–2·16) for altered intercellular communication, 2·01 (1·89–2·15) for cellular senescence, 1·83 (1·67–2·00) for loss of proteostasis, and 1·39 (1·27–1·52) for genomic instability. These findings were replicated in the Finnish cohorts. In both studies, the associations between other risk factors (low education, unhealthy dietary factors [available only in the UK Biobank], smoking, high alcohol consumption, physical inactivity, and depression) and hallmark-related diseases were weaker than those with obesity. 45–60% of the excess mortality in people with obesity was attributable to hallmark-related diseases. Interpretation Obesity might have an important role in the development of diseases associated with cellular ageing. Tackling ageing mechanisms could potentially help to reduce the disease and mortality burden resulting from the obesity epidemic. Funding Wellcome Trust, UK Medical Research Council, US National Institute on Aging, Academy of Finland, and Finnish Foundation for Cardiovascular Research. Translations For the German and Finnish translations of the abstract see Supplementary Materials section.

Background: Climate change scenarios illustrate various pathways in terms of global warming ranging from "sustainable development" (Shared Socioeconomic Pathway SSP1-1.9), the best-case scenario, to 'fossil-fueled development' (SSP5-8.5), the worst-case scenario. Objectives: We examined the extent to which increase in daily average urban summer temperature is associated with future cause-specific mortality and projected heat-related mortality burden for the current warming trend and these two scenarios. Methods: We did an observational cohort study of 363,754 participants living in six cities in Finland. Using residential addresses, participants were linked to daily temperature records and electronic death records from national registries during summers (1 May to 30 September) 2000 to 2018. For each day of observation, heat index (average daily air temperature weighted by humidity) for the preceding 7 d was calculated for participants' residential area using a geographic grid at a spatial resolution of 1km×1km. We examined associations of the summer heat index with risk of death by cause for all participants adjusting for a wide range of individual-level covariates and in subsidiary analyses using case-crossover design, computed the related period population attributable fraction (PAF), and projected change in PAF from summers 2000-2018 compared with those in 2030-2050. Results: During a cohort total exposure period of 582,111,979 summer days (3,880,746 person-summers), we recorded 4,094 deaths, including 949 from cardiovascular disease. The multivariable-adjusted rate ratio (RR) for high (≥21°C) vs. reference (14-15°C) heat index was 1.70 (95% CI: 1.28, 2.27) for cardiovascular mortality, but it did not reach statistical significance for noncardiovascular deaths, RR=1.14 (95% CI: 0.96, 1.36), a finding replicated in case-crossover analysis. According to projections for 2030-2050, PAF of summertime cardiovascular mortality attributable to high heat will be 4.4% (1.8%-7.3%) under the sustainable development scenario, but 7.6% (3.2%-12.3%) under the fossil-fueled development scenario. In the six cities, the estimated annual number of summertime heat-related cardiovascular deaths under the two scenarios will be 174 and 298 for a total population of 1,759,468 people. Discussion: The increase in average urban summer temperature will raise heat-related cardiovascular mortality burden. The estimated magnitude of this burden is >1.5 times greater if future climate change is driven by fossil fuels rather than sustainable development. https://doi.org/10.1289/EHP12080.

OBJECTIVE: This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers. METHODS: This prospective cohort study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting ≥90 days during a 4-year follow-up. RESULTS: The C-index of 0.73 [95% confidence interval (CI) 0.70–0.77] for a questionnaire-only based prediction model, 0.71 (95% CI 0.67–0.75) for an administrative records-only model, and 0.79 (95% CI 0.76–0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome. CONCLUSIONS: The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings.

Importance: The clinical value of current multifactorial algorithms for individualized assessment of dementia risk remains unclear. Objective: To evaluate the clinical value associated with 4 widely used dementia risk scores in estimating 10-year dementia risk. Design, setting, and participants: This prospective population-based UK Biobank cohort study assessed 4 dementia risk scores at baseline (2006-2010) and ascertained incident dementia during the following 10 years. Replication with a 20-year follow-up was based on the British Whitehall II study. For both analyses, participants who had no dementia at baseline, had complete data on at least 1 dementia risk score, and were linked to electronic health records from hospitalizations or mortality were included. Data analysis was conducted from July 5, 2022, to April 20, 2023. Exposures: Four existing dementia risk scores: the Cardiovascular Risk Factors, Aging and Dementia (CAIDE)-Clinical score, the CAIDE-APOE-supplemented score, the Brief Dementia Screening Indicator (BDSI), and the Australian National University Alzheimer Disease Risk Index (ANU-ADRI). Main outcomes and measures: Dementia was ascertained from linked electronic health records. To evaluate how well each score predicted the 10-year risk of dementia, concordance (C) statistics, detection rate, false-positive rate, and the ratio of true to false positives were calculated for each risk score and for a model including age alone. Results: Of 465 929 UK Biobank participants without dementia at baseline (mean [SD] age, 56.5 [8.1] years; range, 38-73 years; 252 778 [54.3%] female participants), 3421 were diagnosed with dementia at follow-up (7.5 per 10 000 person-years). If the threshold for a positive test result was calibrated to achieve a 5% false-positive rate, all 4 risk scores detected 9% to 16% of incident dementia and therefore missed 84% to 91% (failure rate). The corresponding failure rate was 84% for a model that included age only. For a positive test result calibrated to detect at least half of future incident dementia, the ratio of true to false positives ranged between 1 to 66 (for CAIDE-APOE-supplemented) and 1 to 116 (for ANU-ADRI). For age alone, the ratio was 1 to 43. The C statistic was 0.66 (95% CI, 0.65-0.67) for the CAIDE clinical version, 0.73 (95% CI, 0.72-0.73) for the CAIDE-APOE-supplemented, 0.68 (95% CI, 0.67-0.69) for BDSI, 0.59 (95% CI, 0.58-0.60) for ANU-ADRI, and 0.79 (95% CI, 0.79-0.80) for age alone. Similar C statistics were seen for 20-year dementia risk in the Whitehall II study cohort, which included 4865 participants (mean [SD] age, 54.9 [5.9] years; 1342 [27.6%] female participants). In a subgroup analysis of same-aged participants aged 65 (±1) years, discriminatory capacity of risk scores was low (C statistics between 0.52 and 0.60). Conclusions and relevance: In these cohort studies, individualized assessments of dementia risk using existing risk prediction scores had high error rates. These findings suggest that the scores were of limited value in targeting people for dementia prevention. Further research is needed to develop more accurate algorithms for estimation of dementia risk.

Background: The excess risk of cardiovascular disease associated with a wide array of infectious diseases is unknown. We quantified the short- and long-term risk of major cardiovascular events in people with severe infection and estimated the population-attributable fraction. Methods: We analyzed data from 331 683 UK Biobank participants without cardiovascular disease at baseline (2006-2010) and replicated our main findings in an independent population from 3 prospective cohort studies comprising 271 533 community-dwelling participants from Finland (baseline 1986-2005). Cardiovascular risk factors were measured at baseline. We diagnosed infectious diseases (the exposure) and incident major cardiovascular events after infections, defined as myocardial infarction, cardiac death, or fatal or nonfatal stroke (the outcome) from linkage of participants to hospital and mortality registers. We computed adjusted hazard ratios (HRs) and 95% CIs for infectious diseases as short- and long-term risk factors for incident major cardiovascular events. We also calculated population-attributable fractions for long-term risk. Results: In the UK Biobank (mean follow-up, 11.6 years), 54 434 participants were hospitalized for an infection, and 11 649 had an incident major cardiovascular event at follow-up. Relative to participants with no record of infectious disease, those who were hospitalized experienced increased risk of major cardiovascular events, largely irrespective of the subtype of infection. This association was strongest during the first month after infection (HR, 7.87 [95% CI, 6.36-9.73]), but remained elevated during the entire follow-up (HR, 1.47 [95% CI, 1.40-1.54]). The findings were similar in the replication cohort (HR, 7.64 [95% CI, 5.82-10.03] during the first month; HR, 1.41 [95% CI, 1.34-1.48] during mean follow-up of 19.2 years). After controlling for traditional cardiovascular risk factors, the population-attributable fraction for severe infections and major cardiovascular events was 4.4% in the UK Biobank and 6.1% in the replication cohort. Conclusions: Infections severe enough to require hospital treatment were associated with increased risks for major cardiovascular disease events immediately after hospitalization. A small excess risk was also observed in the long-term, but residual confounding cannot be excluded.