Age moderation of genetic and environmental contributions to Digits Forward, Digits Backward, Block Design, Symbol Digit, Vocabulary, and Synonyms was investigated in a sample of 14,534 twins aged 26 to 98 years. The Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium contributed the sample, which represents nine studies from three countries (USA, Denmark, and Sweden). Average test performance was lower in successively older age groups for all tests. Significant age moderation of additive genetic, shared environmental, and non-shared environmental variance components was observed, but the pattern varied by test. The genetic contribution to phenotypic variance across age was smaller for both Digit Span tests, greater for Synonyms, and stable for Block Design and Symbol Digit. The non-shared environmental contribution was greater with age for the Digit Span tests and Block Design, while the shared environmental component was small for all tests, often more so with age. Vocabulary showed similar age-moderation patterns as Synonyms, but these effects were nonsignificant. Findings are discussed in the context of theories of cognitive aging. 

Background Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background.

Methods and findings

The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18–69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m2 lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m2 lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m2 higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/ m2 higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m2, 95% CI 0.04, 0.23 among men; -0.04 kg/m2, 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade.

Conclusions

Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m2 

INTRODUCTION:

Research indicate that cognitive impairment might be related to hospitalization, but little is known about these effects over time.

OBJECTIVE:

To assess cognitive change before and after hospitalization among older adults in a population-based longitudinal study with up to 25 years of follow-up.

METHOD:

A longitudinal study on 828 community living men and women aged 50-86 from the Swedish Adoption/Twin Study of Ageing (SATSA) were linked to The Swedish National Inpatient Register. Up to 8 assessments of cognitive performance (general cognitive ability, verbal, spatial/fluid, memory, and processing speed) from 1986 to 2010 were available. Latent growth curve modelling was used to assess the association between cognitive performance and hospitalization including spline models to analyse cognitive trajectories pre- and post-hospitalization.

RESULTS:

A total of 735 persons (89%) had at least one hospital admission during the follow-up. Mean age at first hospitalization was 70.2 (±9.3)years. Persons who were hospitalized exhibited a lower mean level of cognitive performance in general ability, processing speed and spatial/fluid ability compared with those who were not hospitalized. The two-slope models revealed steeper cognitive decline before hospitalization than after among those with at least one hospitalization event, as compared to non-hospitalized persons who showed steeper cognitive decline after the centering age of 70 years.

CONCLUSIONS:

Persons being hospitalized in late life have lower cognitive performance across all assessed domains. The results indicate that the main decline occurs before the hospitalization, and not after. This might indicate that when you get treatment you also benefit cognitively.

Background: Diabetes has been linked to dementia risk; however, the cognitive trajectories in older adults with diabetes remain unclear. We aimed to investigate the effect of prediabetes and diabetes on cognitive trajectories among cognitively intact older adults in a long-term follow-up study.

Methods: Within the Swedish Adoption/Twin Study of Aging, 793 cognitively intact older adults aged ≥50 were identified at baseline and followed for up to 23 years. Based on standardized scores from 11 cognitive tests, administered at baseline and up to seven follow-ups, four cognitive domains (verbal abilities, spatial/fluid, memory, perceptual speed) were identified by principal-component analysis. Prediabetes was defined according to blood glucose levels in diabetes-free participants. Diabetes was ascertained based on self-report, hypoglycemic medication use and blood glucose levels. Data were analyzed with linear mixed-effect models adjusting for potential confounders.

Results: At baseline, 68 participants (8.6%) had prediabetes and 45 (5.7%) had diabetes. Compared to diabetes-free individuals, people with diabetes had a steeper decline over time in perceptual speed and verbal abilities. The annual declines in these domains were greater than the annual decline in memory. Prediabetes was associated with lower performance in memory in middle-age, but also associated with a less steep memory decline over the follow-up.

Conclusions: Diabetes is associated with a faster decline in perceptual speed and verbal abilities, while prediabetes is associated with lower memory performance in middle-age. However, the detrimental effects of hyperglycemia seem to not affect memory over time.

BACKGROUND: Population-based health registers are potential assets in epidemiological research; however, the quality of case ascertainment is crucial.

OBJECTIVE: To compare the case ascertainment of dementia, from the National Patient Register (NPR) and the Cause of Death Register (CDR) with dementia diagnoses from six Swedish population based studies.

METHODS: Sensitivity, specificity, and positive predictive value (PPV) of dementia identification in NPR and CDR were estimated by individual record linkage with six Swedish population based studies (n = 19,035). Time to detection in NPR was estimated using data on dementia incidence from longitudinal studies with more than two decades of follow-up.

RESULTS: Barely half of the dementia cases were ever detected by NPR or CDR. Using data from longitudinal studies we estimated that a record with a dementia diagnosis appears in the NPR on average 5.5 years after first diagnosis. Although the ability of the registers to detect dementia cases was moderate, the ability to detect non-dementia cases was almost perfect (99%). When registers indicate that there is a dementia diagnosis, there are very few instances in which the clinicians determined the person was not demented. Indeed, PPVs were close to 90%. However, misclassification between dementia subtype diagnoses is quite common, especially in NPR.

CONCLUSIONS: Although the overall sensitivity is low, the specificity and the positive predictive value are very high. This suggests that hospital and death registers can be used to identify dementia cases in the community, but at the cost of missing a large proportion of the cases.

Although genetic factors significantly contribute to variation in body-mass index (BMI), the effects appear to differ with age. To investigate this, we applied polygenic methods to longitudinal data from the Swedish Twin Registry where BMI was available for age categories ranging from 20–35 to above 80. Using GCTA, a polygenic method to estimate heritability, we showed that heritability explains around 20% of the variability in BMI across age categories. However, a polygenic risk score based on the largest GWAS of BMI (PRSBMI) explained 4–6% of the variation in BMI before 65, but less than 0.5% after age 65. This indicates that while there is substantial heritability of BMI across adulthood and late-life, the genetic variants identified in GWAS mainly predict BMI before age 65. Hence, more work is warranted studying the genetics of BMI in late-life, to better understand its biology and what distinguishes it from BMI earlier in adulthood.

Introduction 

Hospital readmissions of older persons are common and often associated with complex health problems. The objectives were to analyze risk factors for readmission within 30 days from hospital discharge.

Methods

A prospective study with a multifactorial approach based on the population-based longitudinal Swedish Adoption/ Twin Study of Aging (SATSA) was conducted. During 9 years of follow-up, information on hospitalizations, readmissions and associated diagnoses were obtained from national registers. Logistic regression models controlling for age and sex were conducted to analyze risk factors for readmissions.

Results

Of the 772 participants, [mean age 69.7 (±11.1), 84 (63%)] were hospitalized and among these 208 (43%) had one or several readmissions within 30 days during the follow-up period. Most of the readmissions (57%) occurred within the frst week; mean days from hospital discharge to readmission was 7.9 (±6.2). The most common causes of admission and readmission were cardiovascular diseases and tumors. Only 8% of the readmissions were regarded as avoidable admissions. In a multivariate logistic regression, falling within the last 12 months (OR 0.57, p=0.039) and being a male (OR 1.84, p=0.006) increased the risk of readmission.

Conclusions

Most older persons that are readmitted return to hospital within the frst week after discharge. Experiencing a fall was a particular risk factor of readmission. Preventive actions should preferably take place already at the hospital to reduce the numbers of readmission. Still, it should be remembered that most readmissions were considered to be necessary.

This study aimed to investigate the association between shift work and incident dementia in two population-based cohorts from the Swedish Twin Registry (STR). The STR-1973 sample included 13,283 participants born 1926–1943 who received a mailed questionnaire in 1973 that asked about status (ever/never) and duration (years) of shift work employment. The Screening Across the Lifespan Twin (SALT) sample included 41,199 participants born 1900–1958 who participated in a telephone interview in 1998–2002 that asked about night work status and duration. Dementia diagnoses came from Swedish patient registers. Cox proportional-hazards regression was used to estimate hazard ratios (HR) with 95% confidence intervals (CI). Potential confounders such as age, sex, education, diabetes, cardiovascular disease and stroke were included in adjusted models. In genotyped subsamples (n = 2977 in STR-1973; n = 10,366 in SALT), APOE ε4 status was considered in models. A total of 983 (7.4%) and 1979 (4.8%) dementia cases were identified after a median of 41.2 and 14.1 years follow-up in the STR-1973 and SALT sample, respectively. Ever shift work (HR 1.36, 95% CI 1.15–1.60) and night work (HR 1.12, 95% CI 1.01–1.23) were associated with higher dementia incidence. Modest dose-response associations were observed, where longer duration shift work and night work predicted increased dementia risk. Among APOE ε4 carriers, individuals exposed to ≥ 20 years of shift work and night work had increased dementia risk compared to day workers. Findings indicate that shift work, including night shift work, compared to non-shift jobs is associated with increased dementia incidence. Confirmation of findings is needed. 

Background: While research has shown that sleep disorders are prevalent among people with dementia, the temporal relationship is unclear. We investigated whether atypical sleep characteristics were associated with incident dementia while accounting for baseline cognitive functioning.

Methods: Screening Across the Lifespan Twin Study (SALT) participants were 11,247 individuals from the Swedish Twin Registry who were at least 65 years at baseline (1998-2002). Sleep and baseline cognitive functioning were assessed via the SALT telephone screening interview. Data on dementia diagnoses came from national health registers. Cox regression was performed to estimate hazard ratios (HR) for dementia.

Results: After 17 years of follow-up, 1,850 dementia cases were identified. Short (≤ 6 hours) and extended (> 9 hours) time-in-bed (TIB) compared to the middle reference group (HR=1.40, 95% CI=1.06-1.85, HR=1.11, 95% CI=1.00-1.24, respectively) and rising at 8:00AM or later compared to earlier rising (HR=1.12, 95% CI=1.01-1.24) were associated with higher dementia incidence. Bedtime, sleep quality, restorative sleep, and heavy snoring were not significant predictors. Findings stratified by baseline cognitive status indicated that the association between short TIB and dementia remained in those cognitively intact at the start.

Conclusions: Short and extended TIB as well as delayed rising among older adults predicted increased dementia incidence in the following 17 years. The pattern of findings suggests that extended TIB and late rising represent prodromal features whereas short TIB appeared to be a risk factor for dementia.