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What governs labour force participation in later life and why is it so different across countries? Health and labour force participation in older ages are not strongly linked, but we observe a large variation across countries in old-age labour force participation. This points to the important role of country-specific regulations governing pension receipt and old-age labour force participation. In addition to the statutory eligibility age for a pension, such country-specific regulations include: earnings tests that limit the amount of earnings when pension benefits are received; the amount of benefit deductions for early retirement; the availability of part-time pensions before normal retirement; special regulations that permit early retirement for certain population groups; and either subsidies or extra costs for employers if they keep older employees in their labour force. This paper asks two questions: Can we link a relatively low labour force participation at ages 60–64 to country-specific regulations that make early retirement attractive? and Can we link a relatively high labour force participation at ages 65–74 to country-specific regulations that make late retirement attractive? To answer these questions, we compared the experiences in a set of developed countries around the world in order to understand better the impact of country-specific rules and laws on work and retirement behaviour at older ages and, by consequence, on the financial sustainability of pension systems.
The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural–geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
To characterise the dissemination patterns of uropathogenic Escherichia coli (UPEC) in a community, we conducted a study utilising molecular and fundamental descriptive epidemiology. The subjects, consisted of women having community-acquired acute urinary tract infection (UTI), were enrolled in the study from 2011 to 2012. UPEC isolates were subjected to antibacterial-susceptibility testing, O serogrouping, phylotyping, multilocus-sequence typing with phylogenetic-tree analysis and pulsed-field-gel electrophoresis (PFGE). From the 209 unique positive urinary samples 166 UPEC were isolated, of which 129 were fully susceptible to the tested antibiotics. Of the 53 sequence types (STs), the four most prevalent STs (ST95, ST131, ST73 and ST357) accounted for 60% of all UPEC strains. Antimicrobial resistance was less frequently observed for ST95 and ST73 than for the others. A majority of rare STs and a few common STs constituted the diversity pattern within the population structure, which was composed of the two phylogenetically distinct clades. Eleven genetically closely related groups were determined by PFGE, which accounted for 42 of the 166 UPEC isolates, without overt geo-temporal clustering. Our results indicate that a few major lineages of UPEC, selected by unidentified factors, are disseminated in this community and contribute to a large fraction of acute UTIs.
Diet, obesity and adipokines play important roles in diabetes and CVD; yet, limited studies have assessed the relationship between diet and multiple adipokines. This cross-sectional study assessed associations between diet, adiposity and adipokines in Mexican Americans. The cohort included 1128 participants (age 34·7±8·2 years, BMI 29·5±5·9 kg/m2, 73·2 % female). Dietary intake was assessed by 12-month food frequency questionnaire. Adiposity was measured by BMI, total percentage body fat and percentage trunk fat using dual-energy X-ray absorptiometry. Adiponectin, apelin, C-reactive protein (CRP), dipeptidyl peptidase-4 (DPP-IV), IL-1β, IL-1ra, IL-6, IL-18, leptin, lipocalin, monocyte chemo-attractant protein-1 (MCP-1), resistin, secreted frizzled protein 4 (SFRP-4), SFRP-5, TNF-α and visfatin were assayed with multiplex kits or ELISA. Joint multivariate associations between diet, adiposity and adipokines were analysed using canonical correlations adjusted for age, sex, energy intake and kinship. The median (interquartile range) energy intake was 9514 (7314, 11912) kJ/d. Overall, 55 % of total intake was accounted for by carbohydrates (24 % from sugar). A total of 66 % of the shared variation between diet and adiposity, and 34 % of diet and adipokines were explained by the top canonical correlation. The diet component was most represented by sugar-sweetened beverages (SSB), fruit and vegetables. Participants consuming a diet high in SSB and low in fruits and vegetables had higher adiposity, CRP, leptin, and MCP-1, but lower SFRP-5 than participants with high fruit and vegetable and low SSB intake. In Mexican Americans, diets high in SSB but low in fruits and vegetables contribute to adiposity and a pro-inflammatory adipokine profile.
Previous studies have shown that the renin–angiotensin system (RAS) is affected by adverse maternal nutrition during pregnancy. The aim of this study was to investigate the effects of a maternal low-protein diet on proinflammatory cytokines, reactive oxygen species and RAS components in kidney samples isolated from adult male offspring. We hypothesized that post-weaning losartan treatment would have beneficial effects on RAS activity and inflammatory and oxidative stress markers in these animals. Pregnant Sprague–Dawley rats were fed with a control (20% casein) or low-protein diet (LP) (6% casein) throughout gestation. After weaning, the LP pups were randomly assigned to LP and LP-losartan groups (AT1 receptor blockade: 10 mg/kg/day until 20 weeks of age). At 20 weeks of age, blood pressure levels were higher and renal RAS was activated in the LP group. We also observed several adverse effects in the kidneys of the LP group, including a higher number of CD3, CD68 and proliferating cell nuclear antigen-positive cells and higher levels of collagen and reactive oxygen species in the kidney. Further, our results revealed that post-weaning losartan treatment completely abolished immune cell infiltration and intrarenal RAS activation in the kidneys of LP rats. The prevention of augmentation of angiotensin (Ang II) concentration abolished inflammatory and fibrotic events, indicating that Ang II via the AT1 receptor is essential for pathological initiation. Our results suggest that the prenatal programming of hypertension is dependent on the up-regulation of local RAS and presence of immune cells in the kidney.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
Glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) are the incretin hormones secreted from the intestine in response to enteral feeding to stimulate insulin secretion. We investigated the relationship serum GIP and GLP-1 levels with gestational age, and insulin secretion in preterm infants. Serum GIP and GLP-1 levels were measured at birth and at 1, 2 and 4 weeks after birth in 30 infants, including 12 born before 30th week of gestation (early group) and 18 born after 30th week of gestation (late group). Blood glucose and serum insulin levels were measured, and the quantitative insulin sensitivity check index (QUICKI) was also calculated. The levels of GLP-1 at 2 and 4 weeks were significantly higher in the early group than those in the late group. The levels of GIP were not significantly different between two groups. At 4 weeks, serum insulin level was significantly higher and QUICKI was significantly lower in the early group. Furthermore, GLP-1 levels were significantly correlated with QUICKI and the serum insulin levels in all infants at 4 weeks. In preterm infants, enteral feeding to premature intestine may be associated with GLP-1 secretion. GLP-1 is also related to stimulated insulin secretion in early postnatal period.
We report on a study, employing direct numerical simulations, of the turbulent/non-turbulent interface of a wake in a stably stratified fluid. It is found that thresholds for both enstrophy and potential enstrophy are needed to identify the interface. Using conditional averaging relative to the location of the interface, various quantities of interest are examined. The thickness of the interface is found to scale with the Kolmogorov scale. From an examination of the Ozmidov and Kolmogorov length scales as well as the buoyancy Reynolds number, it is found that the buoyancy Reynolds number decreases and becomes of order 1 near the interface, indicating the suppression of the turbulence there by the stable stratification. Finally the overall rate of loss of energy due to internal wave radiation is found to be comparable to the overall rate of loss due to turbulent kinetic energy dissipation.
Recent studies have shown that it is important to understand the brain mechanism specifically by focusing on the common and unique functional connectivity in each disorder including depression.
To specify the biomarker of major depressive disorder (MDD), we applied the sparse machine learning algorithm to classify several types of affective disorders using the resting state fMRI data collected in multiple sites, and this study shows the results of depression as a part of those results.
The aim of this study is to understand some specific pattern of functional connectivity in MDD, which would support diagnosis of depression and development of focused and personalized treatments in the future.
The neuroimaging data from patients with major depressive disorder (MDD, n = 100) and healthy control adults (HC: n = 100) from multiple sites were used for the training dataset. A completely separate dataset (n = 16) was kept aside for testing. After all preprocessing of fMRI data, based on one hundred and forty anatomical region of interests (ROIs), 9730 functional connectivities during resting states were prepared as the input of the sparse machine-learning algorithm.
As results, 20 functional connectivities were selected with the classification performance of Accuracy: 83.0% (Sensitivity: 81.0%, Specificity: 85.0%). The test data, which was completely separate from the training data, showed the performance accuracy of 83.3%.
The selected functional connectivities based on the sparse machine learning algorithm included the brain regions which have been associated with depression.
Disclosure of interest
The authors have not supplied their declaration of competing interest.