Obesity and metabolic syndrome (MetS) share common pathophysiological characteristics with aging. To better understand their interplay, we examined how body mass index (BMI) and MetS jointly associate with physiological age, and if the associations changed from midlife to late-life. We used longitudinal data from 1,825 Swedish twins. Physiological age was measured as frailty index (FI) and functional aging index (FAI) and modeled independently in linear mixed-effects models adjusted for chronological age, sex, education, and smoking. We assessed curvilinear associations of BMI and chronological age with physiological age, and interactions between BMI, MetS, and chronological age. We found a significant three-way interaction between BMI, MetS, and chronological age on FI (p-interaction = 0<middle dot>006), not FAI. Consequently, we stratified FI analyses by age: < 65, 65-85, and >= 85 years, and modeled FAI across ages. Except for FI at ages >= 85, BMI had U-shaped associations with FI and FAI, where BMI around 26-28 kg/m(2) was associated with the lowest physiological age. MetS was associated with higher FI and FAI, except for FI at ages < 65, and modified the BMI-FI association at ages 65-85 (p-interaction = 0<middle dot>02), whereby the association between higher BMI levels and FI was stronger in individuals with MetS. Age modified the MetS-FI association in ages >= 85, such that it was stronger at higher ages (p-interaction = 0<middle dot>01). Low BMI, high BMI, and metabolic syndrome were associated with higher physiological age, contributing to overall health status among older individuals and potentially accelerating aging.

BACKGROUND: In 2020 the Swedish Government started a gradual raising of the retirement age, but employers have been silent on the issue. Little is known about whether and how they reflect on what it will mean for their organization, or whether they already have, or are going to, make arrangements in order to facilitate and motivate older workers to stay longer.

OBJECTIVE: The aim of this study was to explore and describe managers' experiences of older workers and age management in connection with the increase of the retirement age in Sweden.

METHODS: Data was collected through semi-structured interviews with fourteen managers from a broad set of organizations in the public and private sectors, and from the Middle and East of Sweden. The transcribed material was analysed in line with qualitative content analysis.

RESULTS: The analysis ended up in seven main categories with associated sub-categories: Older Workers, Retirement Ages, Transition Initiatives, Competence Transfer, Competence Development, Increased Retirement Ages, Knowledge Gaps.

CONCLUSION: Our findings reveal that there is an ambivalence in addressing the issue of age among the interviewed managers, what we have interpreted and labelled as "silent age discrimination", and it was shown that they do not have elaborated strategies for age management.

An increasing number of older persons have complex health care needs. This, along with the organizational principle of remaining at home, emphasizes the need to develop collaborations among organizations caring for older persons. A health care model developed in Sweden, the Mobile Integrated Care Model aims to promote work in teams across organizations. The aim of the study was to describe nurses’ experiences in working and providing health care in the Mobile Integrated Care Model in the home with home health care physicians. Semi-structured interviews were conducted with 18 nurses and analyzed through qualitative content analysis. The method was compliant with the COREQ checklist. A mutually trusting collaboration with physicians, which formed person-centered care, created work satisfaction for the nurses. Working within the Mobile Integrated Care Model was negatively impacted by being employed by different organizations, lack of time to provide health care, and physicians’ person-centered work abilities.

Background: The organizational principle of remaining at home has offset care from the hospital to the home of the older person where care from formal and informal caregivers is needed. Globally, formal care is often organized to handle singular and sporadic health problems, leading to the need for several health care providers. The need for an integrated care model was therefore recognized by health care authorities in one county in Sweden, who created a cross-organisational integrated care model to meet these challenges. The Mobile integrated care model with a home health care physician (MICM) is a collaboration between regional and municipal health care. Descriptions of patients’ and next of kin’s experiences of integrated care is however lacking, motivating exploration.

Method: A qualitative thematic study. Data collection was done before the patients met the MICM physician, and again six months later.

Results: The participants expected a sense of relief when admitted to MICM, and hoped for shared responsibility, building a personal contact and continuity but experienced lack of information about what MICM was. At the follow-up interview, participants described having an easier daily life. The increased access to the health care personnel (HCP) allowed participants to let go of responsibility, and created a sense of safety through the personalised contact and continuity. However, some felt ignored and that the personnel teamed up against the patient. The MICM structure was experienced as hierarchical, which influenced the possibility to participate. However, the home visits opened up the possibility for shared decision making.

Conclusion: Participants had an expectation of receiving safe and coherent health care, to share responsibility, personal contact and continuity. After six months, the participants expressed that MICM had provided an easier daily life. The direct access to HCP reduced their responsibility and they had created a personalised contact with the HCP and that the individual HCP mattered to them, which could be perceived as in line with the goals in the shift to local health care. The MICM was experienced as a hierarchic structure with impact on participation, indicating that all dimensions of person-centred care were not fulfilled.

While midlife adiposity is a risk factor for dementia, adiposity in late-life appears to be associated with lower risk. What drives the associations is poorly understood, especially the inverse association in late-life. Using results from genome-wide association studies, we identified inflammation and lipid metabolism as biological pathways involved in both adiposity and dementia. To test if these factors mediate the effect of midlife and/or late-life adiposity on dementia, we then used cohort data from the Swedish Twin Registry, with measures of adiposity and potential mediators taken in midlife (age 40-64, n = 5999) or late-life (age 65-90, n = 7257). Associations between body-mass index (BMI), waist-hip ratio (WHR), C-reactive protein (CRP), lipid levels, and dementia were tested in survival and mediation analyses. Age was used as the underlying time scale, and sex and education included as covariates in all models. Fasting status was included as a covariate in models of lipids. One standard deviation (SD) higher WHR in midlife was associated with 25% (95% CI 2-52%) higher dementia risk, with slight attenuation when adjusting for BMI. No evidence of mediation through CRP or lipid levels was present. After age 65, one SD higher BMI, but not WHR, was associated with 8% (95% CI 1-14%) lower dementia risk. The association was partly mediated by higher CRP, and suppressed when high-density lipoprotein levels were low. In conclusion, the negative effects of midlife adiposity on dementia risk were driven directly by factors associated with body fat distribution, with no evidence of mediation through inflammation or lipid levels. There was an inverse association between late-life adiposity and dementia risk, especially where the body's inflammatory response and lipid homeostasis is intact.

Data from the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium were used to examine predictions of different models of gene-by-environment interaction to understand how genetic variance in self-rated health (SRH) varies at different levels of financial strain. A total of 11,359 individuals from 10 twin studies in Australia, Sweden, and the United States contributed relevant data, including 2,074 monozygotic and 2,623 dizygotic twin pairs. Age ranged from 22 to 98 years, with a mean age of 61.05 (SD = 13.24). A factor model was used to create a harmonized measure of financial strain across studies and items. Twin analyses of genetic and environmental variance for SRH incorporating age, age(2), sex, and financial strain moderators indicated significant financial strain moderation of genetic influences on self-rated health. Moderation results did not differ across sex or country. Genetic variance for SRH increased as financial strain increased, matching the predictions of the diathesis-stress and social comparison models for components of variance. Under these models, environmental improvements would be expected to reduce genetically based health disparities.

BACKGROUND: There is robust evidence that in midlife, higher body mass index (BMI) and metabolic syndrome (MetS), which often co-exist, are associated with increased mortality risk. However, late-life findings are inconclusive, and few studies have examined how metabolic health status (MHS) affects the BMI-mortality association in different age categories. We, therefore, aimed to investigate how mid- and late-life BMI and MHS interact to affect the risk of mortality. METHODS: This cohort study included 12,467 participants from the Swedish Twin Registry, with height, weight, and MHS measures from 1958-2008 and mortality data linked through 2020. We applied Cox proportional hazard regression with age as a timescale to examine how BMI categories (normal weight, overweight, obesity) and MHS (identification of MetS determined by presence/absence of hypertension, hyperglycemia, low HDL, hypertriglyceridemia), independently and in interaction, are associated with the risk of all-cause mortality. Models were adjusted for sex, education, smoking, and cardiovascular disease. RESULTS: The midlife group included 6,252 participants with a mean age of 59.6 years (range = 44.9-65.0) and 44.1% women. The late-life group included 6,215 participants with mean age 73.1 years (65.1-95.3) and 46.6% women. In independent effect models, metabolically unhealthy status in midlife increased mortality risks by 31% [hazard ratio 1.31; 95% confidence interval 1.12-1.53] and in late-life, by 18% (1.18;1.10-1.26) relative to metabolically healthy individuals. Midlife obesity increased the mortality risks by 30% (1.30;1.06-1.60) and late-life obesity by 15% (1.15; 1.04-1.27) relative to normal weight. In joint models, the BMI estimates were attenuated while those of MHS were less affected. Models including BMI-MHS categories revealed that, compared to metabolically healthy normal weight, the metabolically unhealthy obesity group had increased mortality risks by 53% (1.53;1.19-1.96) in midlife, and across all BMI categories in late-life (normal weight 1.12; 1.01-1.25, overweight 1.10;1.01-1.21, obesity 1.31;1.15-1.49). Mortality risk was decreased by 9% (0.91; 0.83-0.99) among those with metabolically healthy overweight in late-life. CONCLUSIONS: MHS strongly influenced the BMI-mortality association, such that individuals who were metabolically healthy with overweight or obesity in mid- or late-life did not carry excess risks of mortality. Being metabolically unhealthy had a higher risk of mortality independent of their BMI. 

BACKGROUND: An increasing older population, along with the organizational principle of remaining at home, has moved health care from institutions into the older person's home, where several health care providers facilitate care. The Mobile Integrated Care Model strives to provide cost-efficient, coherent, person-centered health care in the home. In the integrated care team, where the home health care physician is the medical authority, several health care professions work across organizational borders. Therefore, the aim of this study was to describe Home Health Care Physicians perceptions of working and providing health care in the Mobile Integrated Care Model, as well as perceptions of participating in and forming health care.

METHODS: A phenomenographic qualitative study design, with semi-structured interviews using an interview guide.

RESULTS: Working within Mobile Integrated Care Model was a different way of working as a physician. The physicians' role was to support the patient by making safe medical decisions. Physicians described themselves as a piece in the team puzzle, where the professional knowledge of others was crucial to give quality health care. Being in the patients' homes was expressed as adding a unique dimension in the provision of health care, and the physicians learned more about the patients by meeting them in their homes than at an institution. This aided the physicians in respecting patient autonomy in medical decision making, even though the physicians sometimes disregarded patient autonomy in favor of their own medical experience. There was a divided view on next of kin participation among the home health care physicians, ranging from always including to total absence of involving next of kin in decision making.

CONCLUSIONS: The home health care physicians described the Mobile Integrated Care Model as the best way to work, but there was still a need for additional resources and structure when working in different organizations. The need for full-time employment, additional time or hours, more equipment, access to each other's medical records, and additional collaboration with other health care providers were expressed, which could contribute to increased work satisfaction and facilitate further development of person-centered care in the Mobile Integrated Care Model.

Aims: There are few cohorts of type 1 diabetes that follow individuals over more than half a century in terms of health outcomes. The aim of this study was to examine associations between type 1 diabetes, diagnosed before age 18, and long-term morbidity and mortality, and to investigate whether cognitive ability plays a role in long-term morbidity and mortality risk.

Methods: In a Swedish cohort, 120 men with type 1 diabetes and 469 without type 1 diabetes were followed between 18 and 77 years of age as regards morbidity and mortality outcomes, and impact of cognitive ability at military conscription for the outcomes. In Cox regression analyses and Kaplan-Meier analyses with log-rank tests, associations between diabetes and cognitive ability respectively, and outcomes (mortality, cardiovascular morbidity and diabetes complications) were investigated.

Results: Men with type 1 diabetes suffered from dramatically higher mortality (HR 4.62, 95% CI: 3.56–5.60), cardiovascular mortality (HR 5.60, 95% CI: 3.27–9.57), and cardiovascular events (HR 3.97, 95% CI: 2.79–5.64) compared to men without diabetes. Higher cognitive ability at military conscription was associated with lower mortality in men without diabetes, but was not associated with any outcome in men with diabetes.

Conclusions: In this historical cohort study with 60 years of follow-up time and a less effective treatment of diabetes than today, mortality rates and cardiovascular outcomes were high for men with type 1 diabetes. Morbidity or mortality did not differ between those that had low to normal or high cognitive ability among men with type 1 diabetes.

What’s new 

• There is little data from Scandinavia on the long-term prognosis of type 1 diabetes before 1970, and no studies that investigate cognitive ability early in life as a predictor of long-term morbidity and mortality in type 1 diabetes.
• Men with type 1 diabetes followed for 60 years had a 4.6 times higher risk of all-cause mortality than men without diabetes. Cognitive ability at 18 years significantly predicted mortality in men without, but not with, type 1 diabetes.
• The results add to the literature describing the prognosis of type 1 diabetes in Scandinavia during the time period from 1934 until today.

Introduction To study if declining cognition drives weight loss in preclinical dementia, we examined the longitudinal association between body mass index (BMI) and cognitive abilities in individuals who did or did not later develop dementia. Methods Using data from individuals spanning age 50 to 89, we applied dual change score models separately in individuals who remained cognitively intact (n = 1498) and those who were diagnosed with dementia within 5 years of last assessment (n = 459). Results Among the cognitively intact, there was a bidirectional association: Stable BMI predicted stable cognition and vice versa. Among individuals who were subsequently diagnosed with dementia, the association was unidirectional: Higher BMI predicted declining cognition but cognition did not predict change in BMI. Discussion Although BMI and cognition stabilized each other when cognitive functioning was intact, this buffering effect was missing in the preclinical dementia phase. This finding indicates that weight loss in preclinical dementia is not driven by declining cognition.