Biological age can be assessed by means of clinical parameters. Some parameters are more suitable than others; criteria for a rational selection of such parameters are discussed in detail. The main tool used in this essay is multiple linear regression. The data reveal a characteristic sex difference in human and, presumably, mammalian aging.
To the Editor: Epidemiological studies have repeatedly shown a link between poor fetal growth and increased risk of developing type 2 diabetes [1]. Month of birth is a good instrument for the assessment of effects of early growth on adult health independent of life-course factors. This is true because in decades past there were important seasonal differences in nutrition, especially in developing countries such as Ukraine. These differences in access to high-quality food supply can potentially influence intrauterine growth, depending on the month of gestation [2]. Other possible triggering factors for developing type 2 diabetes, such as production of vitamin D [3] and outdoor temperature [4], also tend to change seasonally.Seasonal pattern of birth in type 1 diabetic children and adolescents was repeatedly described around the world, including our recent study in Ukraine [5]. In contrast, the seasonality of birth in type 2 diabetic patients was previously reported only in a few small-sample studies, e.g. in 155 African-American type 2 diabetic adolescent [6] and 282 adult patients in the Netherlands [7]. To study whether abnormal seasonality of birth exists in middle-to old-aged type 2 diabetic patients in Ukraine, we compared the month-of-birth patterns in type 2 diabetic patients in three large Ukrainian regions with those in general populations.Information on date of birth, sex and year of diagnosis was extracted from the nationwide primary-care-based Ukrainian diabetes mellitus register created in 2000 in the Institute of Endocrinology, Kiev, Ukraine. The definition of type 2 diabetes was based on onset after 39 years of age, irrespective of the type of treatment.Cases were identified from the three regional diabetes registers with high completeness of ascertainment: Chernigiv (100%), Kherson (99.7%) and Rivne (86.2%). These registers cover 7.4% of the total Ukraine population. A female excess was evident in all three registers. Cases were all people alive with diagnosis of type 2 diabetes as of 1 January 2008, and who were diagnosed at age 40 or later. Only people born before 1 January 1960 were included; thus all cases included were at least 48. In total, 17,510 male and 34,704 female type 2 diabetic patients were finally included in the study. Reference populations were based on the Ukraine census 2001 depersonalised data. These populations included people who had been born during the same period and were residents of the same regions: Chernigiv, 247,253 men and 369,357 women; Kherson, 208,944
Aims/hypothesis Numerous epidemiological studies have shown differences in seasonality of birth patterns between the general population and the group who develop type 1 diabetes mellitus. This finding indicates that environmental factors operating during pre-and/or postnatal development could be aetiologically important. We examined whether the pattern of month of birth for type 1 diabetes patients in Ukraine differs from that for total live births. Methods Data consist of prevalent cases of type 1 diabetes in Ukraine by the end of 2003. Cases are restricted to persons born after 1 January 1960, diagnosed with type 1 diabetes before the age of 30 years (n=20,117). People born during the same time in the general population (n=29,105,560) were the reference standard. Seasonal patterns were estimated using logistic regression with harmonic terms. Results We found a strongly significant seasonal pattern of type 1 diabetes incidence rates (p<0.001), with the lowest rates in December and the highest in April. The rate ratio between the extremes was 1.32 (95% CI 1.27-1.39). Tests for seasonal patterns in subgroups defined by sex and age or by sex and date of birth were all significant with p values less than 0.02. We found no interactions with sex (p=0.142) or age at diagnosis (p=0.207), but found a strong interaction with period of birth (p<0.0001). Conclusions/interpretationThe results obtained indicate that early-life factors linked to seasons may influence type 1 diabetes risk later in life.
The long-term effects of X-irradiation with 0.25, 0.5, 0.75 and 1 Gy of 1 h eggs on the fitness-related life history traits in adult Drosophila melanogaster fruit flies and their offspring were investigated. Following irradiation with 0.25, 0.5 and 0.75 Gy, both F0 and F1 flies have decreased adult body weight and increased locomotor (photo- and geotactic) activity, whereas metabolic rate measured as the rate of CO2 production was unchanged or even increased, and female fecundity was slightly reduced compared to appropriate controls. In some cases, irradiation resulted in hormetic effects increased resistance to both starvation and heat shock stresses as well as life extension. An explanation of the beneficial long lasting effects induced by early irradiation is offered, which suggests that these effects are due to cross-life stage and cross-generational adaptive phenotypic plasticity.
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