The accumulation of disparate diseases in complex multimorbidity makes prevention difficult if each disease is targeted separately. We aimed to examine obesity as a shared risk factor for common ...diseases, determine associations between obesity-related diseases, and examine the role of obesity in the development of complex multimorbidity (four or more comorbid diseases).
We did an observational study and used pooled prospective data from two Finnish cohort studies (the Health and Social Support Study and the Finnish Public Sector Study) comprising 114 657 adults aged 16–78 years at study entry (1998–2013). A cohort of 499 357 adults (aged 38–73 years at study entry; 2006–10) from the UK Biobank provided replication in an independent population. BMI and clinical characteristics were assessed at baseline. BMIs were categorised as obesity (≥30·0 kg/m2), overweight (25·0–29·9 kg/m2), healthy weight (18·5–24·9 kg/m2), and underweight (<18·5 kg/m2). Via linkage to national health records, participants were followed-up for death and diseases diagnosed according to the International Classification of Diseases 10th Revision (ICD-10). Hazard ratios (HRs) with 95% CIs and population attributable fractions (PAFs) for associations between BMI and multimorbidity were calculated.
Mean follow-up duration was 12·1 years (SD 3·8) in the Finnish cohorts and 11·8 years (1·7) in the UK Biobank cohort. Obesity was associated with 21 non-overlapping cardiometabolic, digestive, respiratory, neurological, musculoskeletal, and infectious diseases after Bonferroni multiple testing adjustment and ignoring HRs of less than 1·50. Compared with healthy weight, the confounder-adjusted HR for obesity was 2·83 (95% CI 2·74–2·93; PAF 19·9% 95% CI 19·3–20·5) for developing at least one obesity-related disease, 5·17 (4·84–5·53; 34·4% 33·2–35·5) for two diseases, and 12·39 (9·26–16·58; 55·2% 50·9–57·5) for complex multimorbidity. The proportion of participants of healthy weight with complex multimorbidity by age 75 years was observed by age 55 years in participants with obesity, and degree of obesity was associated with complex multimorbidity in a dose–response relationship. Compared with obesity, the association between overweight and complex multimorbidity was more modest (HR 2·67, 95% CI 1·94–3·68; PAF 13·3% 95% CI 9·6–16·3). The same pattern of results was observed in the UK Biobank cohort.
Obesity is associated with diverse, increasing disease burdens, and might represent an important target for multimorbidity prevention that avoids the complexities of multitarget preventive regimens.
Wellcome Trust, Medical Research Council, National Institute on Aging.
Socioeconomic disadvantage is a risk factor for many diseases. We characterised cascades of these conditions by using a data-driven approach to examine the association between socioeconomic status ...and temporal sequences in the development of 56 common diseases and health conditions.
In this multi-cohort study, we used data from two Finnish prospective cohort studies: the Health and Social Support study and the Finnish Public Sector study. Our pooled prospective primary analysis data comprised 109 246 Finnish adults aged 17–77 years at study entry. We captured socioeconomic status using area deprivation and education at baseline (1998–2013). Participants were followed up for health conditions diagnosed according to the WHO International Classification of Diseases until 2016 using linkage to national health records. We tested the generalisability of our findings with an independent UK cohort study—the Whitehall II study (9838 people, baseline in 1997, follow-up to 2017)—using a further socioeconomic status indicator, occupational position.
During 1 110 831 person-years at risk, we recorded 245 573 hospitalisations in the Finnish cohorts; the corresponding numbers in the UK study were 60 946 hospitalisations in 186 572 person-years. Across the three socioeconomic position indicators and after adjustment for lifestyle factors, compared with more advantaged groups, low socioeconomic status was associated with increased risk for 18 (32·1%) of the 56 conditions. 16 diseases formed a cascade of inter-related health conditions with a hazard ratio greater than 5. This sequence began with psychiatric disorders, substance abuse, and self-harm, which were associated with later liver and renal diseases, ischaemic heart disease, cerebral infarction, chronic obstructive bronchitis, lung cancer, and dementia.
Our findings highlight the importance of mental health and behavioural problems in setting in motion the development of a range of socioeconomically patterned physical illnesses. Policy and health-care practice addressing psychological health issues in social context and early in the life course could be effective strategies for reducing health inequalities.
UK Medical Research Council, US National Institute on Aging, NordForsk, British Heart Foundation, Academy of Finland, and Helsinki Institute of Life Science.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed ...to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight.
We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m2), overweight (25·0–29·9 kg/m2), class I (mild) obesity (30·0–34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (<20 kg/m2) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis.
Participants were 120 813 adults (mean age 51·4 years, range 35–103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973–2012). During a mean follow-up of 10·7 years (1995–2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio OR 2·0, 95% CI 1·7–2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5–5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1–21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9–2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1–17·9) for vascular disease followed by diabetes, 18·6 (16·6–20·9) for diabetes only, and 29·8 (21·7–40·8) for diabetes followed by vascular disease.
The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes.
NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
AbstractObjectiveTo examine whether physical inactivity is a risk factor for dementia, with attention to the role of cardiometabolic disease in this association and reverse causation bias that arises ...from changes in physical activity in the preclinical (prodromal) phase of dementia.DesignMeta-analysis of 19 prospective observational cohort studies.Data sourcesThe Individual-Participant-Data Meta-analysis in Working Populations Consortium, the Inter-University Consortium for Political and Social Research, and the UK Data Service, including a total of 19 of a potential 9741 studies.Review methodThe search strategy was designed to retrieve individual-participant data from prospective cohort studies. Exposure was physical inactivity; primary outcomes were incident all-cause dementia and Alzheimer’s disease; and the secondary outcome was incident cardiometabolic disease (that is, diabetes, coronary heart disease, and stroke). Summary estimates were obtained using random effects meta-analysis.ResultsStudy population included 404 840 people (mean age 45.5 years, 57.7% women) who were initially free of dementia, had a measurement of physical inactivity at study entry, and were linked to electronic health records. In 6.0 million person-years at risk, we recorded 2044 incident cases of all-cause dementia. In studies with data on dementia subtype, the number of incident cases of Alzheimer’s disease was 1602 in 5.2 million person-years. When measured <10 years before dementia diagnosis (that is, the preclinical stage of dementia), physical inactivity was associated with increased incidence of all-cause dementia (hazard ratio 1.40, 95% confidence interval 1.23 to 1.71) and Alzheimer’s disease (1.36, 1.12 to 1.65). When reverse causation was minimised by assessing physical activity ≥10 years before dementia onset, no difference in dementia risk between physically active and inactive participants was observed (hazard ratios 1.01 (0.89 to 1.14) and 0.96 (0.85 to 1.08) for the two outcomes). Physical inactivity was consistently associated with increased risk of incident diabetes (hazard ratio 1.42, 1.25 to 1.61), coronary heart disease (1.24, 1.13 to 1.36), and stroke (1.16, 1.05 to 1.27). Among people in whom cardiometabolic disease preceded dementia, physical inactivity was non-significantly associated with dementia (hazard ratio for physical activity assessed >10 before dementia onset 1.30, 0.79 to 2.14).ConclusionsIn analyses that addressed bias due to reverse causation, physical inactivity was not associated with all-cause dementia or Alzheimer’s disease, although an indication of excess dementia risk was observed in a subgroup of physically inactive individuals who developed cardiometabolic disease.
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BFBNIB, CMK, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Personality may influence the risk of death, but the evidence remains inconsistent. We examined associations between personality traits of the five-factor model (extraversion, neuroticism, ...agreeableness, conscientiousness, and openness to experience) and the risk of death from all causes through individual-participant meta-analysis of 76,150 participants from 7 cohorts (the British Household Panel Survey, 2006-2009; the German Socio-Economic Panel Study, 2005-2010; the Household, Income and Labour Dynamics in Australia Survey, 2006-2010; the US Health and Retirement Study, 2006-2010; the Midlife in the United States Study, 1995-2004; and the Wisconsin Longitudinal Study's graduate and sibling samples, 1993-2009). During 444,770 person-years at risk, 3,947 participants (54.4% women) died (mean age at baseline = 50.9 years; mean follow-up = 5.9 years). Only low conscientiousness-reflecting low persistence, poor self-control, and lack of long-term planning-was associated with elevated mortality risk when taking into account age, sex, ethnicity/nationality, and all 5 personality traits. Individuals in the lowest tertile of conscientiousness had a 1.4 times higher risk of death (hazard ratio = 1.37, 95% confidence interval: 1.18, 1.58) compared with individuals in the top 2 tertiles. This association remained after further adjustment for health behaviors, marital status, and education. In conclusion, of the higher-order personality traits measured by the five-factor model, only conscientiousness appears to be related to mortality risk across populations.
Infections have been hypothesised to increase the risk of dementia. Existing studies have included a narrow range of infectious diseases, relied on short follow-up periods, and provided little ...evidence for whether the increased risk is limited to specific dementia subtypes or attributable to specific microbes rather than infection burden. We aimed to compare the risk of Alzheimer's disease and other dementias across a wide range of hospital-treated bacterial and viral infections in two large cohorts with long follow-up periods.
In this large, multicohort, observational study, the analysis was based on a primary cohort consisting of pooled individual-level data from three prospective cohort studies in Finland (the Finnish Public Sector study, the Health and Social Support study, and the Still Working study) and an independent replication cohort from the UK Biobank. Community-dwelling adults (≥18 years) with no dementia at study entry were included. Follow-up was until Dec 31, 2012, in the Health and Social Support study, Dec 31, 2016, in the public sector study and the Still Working study, and Feb 7, 2018, in the replication cohort. Through record linkage to national hospital inpatient registers, we ascertained exposure to 925 infectious diseases (using the International Classification of Diseases 10th Revision codes) before dementia onset, and identified incident dementia from hospital records, medication reimbursement entitlements, and death certificates. Hazard ratios (HRs) for the associations of each infectious disease or disease group (index infection) with incident dementia were assessed by use of Cox proportional hazards models. We then repeated the analysis after excluding incident dementia cases that occurred during the first 10 years after initial hospitalisation due to the index infection.
From March 1, 1986, to Jan 1, 2005, 260 490 people were included in the primary cohort, and from Dec 19, 2006, to Oct 1, 2010, 485 708 people were included in the replication cohort. In the primary cohort analysis based on 3 947 046 person-years at risk (median follow-up 15·4 years IQR 9·8–21·0), 77 108 participants had at least one hospital-treated infection before dementia onset and 2768 developed dementia. Hospitalisation for any infectious disease was associated with increased dementia risk in the primary cohort (adjusted HR aHR 1·48 95% CI 1·37–1·60) and replication cohort (2·60 2·38-2·83). The association remained when analyses were restricted to new dementia cases that occurred more than 10 years after infection (aHR 1·22 95% CI 1·09–1·36 in the primary cohort, the replication cohort had insufficient follow-up data for this analysis), and when comorbidities and other dementia risk factors were considered. There was evidence of a dose-response association between the number of episodes of hospital-treated infections and dementia risk in both cohorts (ptrend=0·0007). Although the greatest dementia risk was seen for central nervous system (CNS) infections versus no infection (aHR 3·01 95% CI 2·07–4·37), excess risk was also evident for extra-CNS infections (1·47 1·36–1·59). Although we found little difference in the infection-dementia association by type of infection, associations were stronger for vascular dementia than for Alzheimer's disease (aHR 2·09 95% CI 1·59–2·75 versus aHR 1·20 1·08–1·33 in the primary cohort and aHR 3·28 2·65–4·04 versus aHR 1·80 1·53–2·13 in the replication cohort).
Severe infections requiring hospital treatment are associated with long-term increased risk of dementia, including vascular dementia and Alzheimer's disease. This association is not limited to CNS infections, suggesting that systemic effects are sufficient to affect the brain. The absence of infection specificity combined with evidence of dose-response relationships between infectious disease burden and dementia risk support the hypothesis that increased dementia risk is driven by general inflammation rather than specific microbes.
UK Medical Research Council, US National Institute on Aging, Wellcome Trust, NordForsk, Academy of Finland, and Helsinki Institute of Life Science.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Working hours is a ubiquitous exposure given that most adults are employed, and one that is modifiable via legislative change if not always through individual-level choice. According to a recent ...report from the World Health Organization (WHO) and International Labour Organization (ILO), there is currently sufficient evidence to conclude that long working hours (i.e., ≥55 h per week) elevate the risk of fatal and non-fatal ischaemic heart disease to a clinically meaningful extent. After assessing the data used by the ILO/WHO, we feel that the expert group has not correctly applied their own framework for assessing the strength of the evidence. In the meta-analysis of observational studies in the report, the association between long working hours and incident heart disease appeared stronger in lower quality cohort studies with a high risk of bias (minimally-adjusted hazard ratio 1.20, 95% CI 1.01–1.41, compared to standard 35–40 weekly hours) than in the superior-quality studies with a lower risk of bias for which the estimate was not significantly different from the null (1.08, 95% CI 0.93–1.25). There was also marked effect modification, such that there was no increase in ischaemic heart disease for those working long hours in high socioeconomic status occupations, a finding also reported in analyses of a recent census-based cohort study which was not included in the report. Our meta-analysis of all these studies confirm that the findings are not consistent but differ between subgroups and that the summary age- and sex-adjusted hazard ratio for long working hours in high socioeconomic status occupations does not support excess risk: 0.85, 95% CI 0.63–1.13 (Pinteraction = 0.005, total N = 451,982). For these and other reasons detailed in this commentary, we advance a more cautious interpretation of the existing evidence. The conclusions should be restricted to low socioeconomic status occupations only and more research is still needed to confirm or refute harmfulness and determine clinical relevance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
IMPORTANCE: It is well established that selected lifestyle factors are individually associated with lower risk of chronic diseases, but how combinations of these factors are associated with ...disease-free life-years is unknown. OBJECTIVE: To estimate the association between healthy lifestyle and the number of disease-free life-years. DESIGN, SETTING, AND PARTICIPANTS: A prospective multicohort study, including 12 European studies as part of the Individual-Participant-Data Meta-analysis in Working Populations Consortium, was performed. Participants included 116 043 people free of major noncommunicable disease at baseline from August 7, 1991, to May 31, 2006. Data analysis was conducted from May 22, 2018, to January 21, 2020. EXPOSURES: Four baseline lifestyle factors (smoking, body mass index, physical activity, and alcohol consumption) were each allocated a score based on risk status: optimal (2 points), intermediate (1 point), or poor (0 points) resulting in an aggregated lifestyle score ranging from 0 (worst) to 8 (best). Sixteen lifestyle profiles were constructed from combinations of these risk factors. MAIN OUTCOMES AND MEASURES: The number of years between ages 40 and 75 years without chronic disease, including type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease. RESULTS: Of the 116 043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70 911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17 383 participants developed at least 1 chronic disease. There was a linear association between overall healthy lifestyle score and the number of disease-free years, such that a 1-point improvement in the score was associated with an increase of 0.96 (95% CI, 0.83-1.08) disease-free years in men and 0.89 (95% CI, 0.75-1.02) years in women. Comparing the best lifestyle score with the worst lifestyle score was associated with 9.9 (95% CI 6.7-13.1) additional years without chronic diseases in men and 9.4 (95% CI 5.4-13.3) additional years in women (P < .001 for dose-response). All of the 4 lifestyle profiles that were associated with the highest number of disease-free years included a body-mass index less than 25 (calculated as weight in kilograms divided by height in meters squared) and at least 2 of the following factors: never smoking, physical activity, and moderate alcohol consumption. Participants with 1 of these lifestyle profiles reached age 70.3 (95% CI, 69.9-70.8) to 71.4 (95% CI, 70.9-72.0) years disease free depending on the profile and sex. CONCLUSIONS AND RELEVANCE: In this multicohort analysis, various healthy lifestyle profiles appeared to be associated with gains in life-years without major chronic diseases.
Abstract
Aims
We examined the extent to which associations between education and cardiovascular disease (CVD) morbidity and mortality are attributable to income and work stress.
Methods and results
...We included all employed Danish residents aged 30–59 years in 2000. Cardiovascular disease morbidity analyses included 1 638 270 individuals, free of cardiometabolic disease (CVD or diabetes). Mortality analyses included 41 944 individuals with cardiometabolic disease. We assessed education and income annually from population registers and work stress, defined as job strain, with a job-exposure matrix. Outcomes were ascertained until 2014 from health registers and risk was estimated using Cox regression. During 10 957 399 (men) and 10 776 516 person-years (women), we identified 51 585 and 24 075 incident CVD cases, respectively. For men with low education, risk of CVD was 1.62 95% confidence interval (CI) 1.58–1.66 before and 1.46 (95% CI 1.42–1.50) after adjustment for income and job strain (25% reduction). In women, estimates were 1.66 (95% CI 1.61–1.72) and 1.53 (95% CI 1.47–1.58) (21% reduction). Of individuals with cardiometabolic disease, 1736 men (362 234 person-years) and 341 women (179 402 person-years) died from CVD. Education predicted CVD mortality in both sexes. Estimates were reduced with 54% (men) and 33% (women) after adjustment for income and job strain.
Conclusion
Low education predicted incident CVD in initially healthy individuals and CVD mortality in individuals with prevalent cardiometabolic disease. In men with cardiometabolic disease, income and job strain explained half of the higher CVD mortality in the low education group. In healthy men and in women regardless of cardiometabolic disease, these factors explained 21–33% of the higher CVD morbidity and mortality.
Objective: Diabetes is an increasingly important public health concern, but little is known about the contribution of psychological factors on diabetes risk. We examined whether personality is ...associated with risk of incident diabetes and diabetes-related mortality. Method: An individual-participant meta-analysis of 34,913 adults free of diabetes at baseline (average age 53.7 years, 57% women) from 5 prospective cohort studies from the United States and United Kingdom. Personality dimensions included extraversion, neuroticism, agreeableness, conscientiousness, and openness to experience based on the Five Factor Model. Results: During an average follow-up of 5.7 years, 1845 participants became diabetic. Of the 5 personality dimensions, only low conscientiousness was associated with an elevated diabetes risk (OR = 0.87, 95% CI = 0.82-0.91 per 1 standard deviation increment in conscientiousness). This association attenuated by 60% after adjustment for obesity and by 25% after adjustment for physical inactivity. Low conscientiousness was also associated with elevated risk of diabetes mortality (HR = 0.72, CI = 0.53-0.98 per 1 standard deviation increment in conscientiousness). Other personality traits were not consistently associated with diabetes incidence or mortality. Conclusions: Low conscientiousness-a cognitive-behavioral disposition reflecting careless behavior and a lack of self-control and planning-is associated with elevated risk of diabetes and diabetes-related mortality. The underlying mechanisms are likely to involve health behaviors, such as poor weight management, physical inactivity, and adherence to medical management recommendations.
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CEKLJ, FFLJ, NUK, ODKLJ, PEFLJ, UPUK
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