Biodemography

test 8 NOV

Although there has been increasing effort aimed at using biological, genetic and cognitive evidence to better assess patterns and levels of aging and longevity, it is still very troublesome to actually use that evidence in order to draw conclusions, in a demographic manner, about the phenomenon of mortality and longevity. Since there are various factors involved in determining mortality, many of which are seen from an environmental, behavioral and socioeconomic perspective, it is difficult to decompose those factors and try to understand which one has its prevalence in which context. That is a typical epistemological and methodological problem that social scientists face when trying to measure reality. Our argument is that with the advances of the natural sciences, for instance the field of neuroscience (which aggregates in its multidiscplinary perspective evidences from genetics, biology, cognitive science and social sciences), the path of linking individual-micro level to the macro-social level has become clearer to take. Our paper intents to discuss how demography could gain from using that amount of biological/neuroscientific evidence shrewdly, within its already developed frameworks and models.

One of the most important questions in research on the biodemography of human aging involves the extent to which early life conditions affect frailty and mortality at advanced ages. We addressed this question experimentally by manipulating dietary conditions of Mexican fruit fly cohorts at younger and older ages. The study yielded five main results: (1) frailty at transfer age (55 days) was far greater in flies maintained on lower quality diet (sugar) at early ages than those maintained on full diets for both sexes; (2) using mortality as a proxy, within-treatment frailty was far greater in males than in females at all advanced ages; (3) remaining life expectancy at advanced ages depended on both past and current dietary conditions for both sexes. Thus the mortality was not memoryless as has been reported in several other studies;. (4) after the initial 1- to 3-day mortality spike due to transfer stress, age-specific mortality for many treatments differed in scale but not in pattern—several were largely age-independent; (5) egg production in older females was drastically affected by past and current conditions. Implications for understanding the effects of early life experience on old age frailty and mortality in human populations will be discussed.

Evidences from across several countries hints towards a secular decline in the age at onset of menarche over past two centuries with considerable spatial variations. However, data substantiating any secular trend in the age at menarche among Indian population has been hitherto fragmented and inadequately verified.
Using nationally representative data on 91394 women aged 15-49 years from the Indian Human Development Survey (2005), this research evaluated the cohort specific trends in the age at onset of menarche among Indian women born between 1955-1989. Besides, salient demographic, socioeconomic, and contextual factors determining the age at onset of menarche were also investigated.
The adjusted predicted mean age at onset of menarche among Indian women was 13.76 years (95 % CI: 13.75, 13.77) in 2005. It declined by 3.0 months from 13.83 years (95% CI: 13.81, 13.85) among women born prior to 1955-1964, to nearly 13.62 years (95% CI: 13.58, 13.67) among women born during late 1985-1989. However, there was extensive spatial heterogeneity as adjusted predicted menarcheal age varied from 15.0 years among women from Himachal Pradesh born during 1955-1964 (95% CI: 14.89-15.11) to about 12.1 years among women from Assam (95% CI: 11.63-12.56) born between 1985-1989.

Low levels of fertility in Western countries are often attributed to men and women pursuing careers first and babies later. Research has shown considerable similarity between parents-children and siblings in completed fertility and education. This raises the possibility that the effect of education on fertility is not causal, but has a genetic basis and/or arises due to non-genetic factors of the family of origin. Relatively little research investigates the (common) genetic origin of these outcomes. Most of the existing bio-demographic research on fertility uses the Danish Twin Study (cf. Kohler and Rodgers). It is crucial to extend this line of research to other contexts to generalize findings and gain insight into possible environmental variability. Unfortunately, twin data are not readily available for most contexts, but genetic origins can also be investigated using information from multi-generation surveys using the so-called ‘animal model’. This is a mixed model that takes advantage of information on the relatedness of all individuals in a pedigree to estimate the genetic merit of an individual. We apply this model to the Netherlands Kinship Panel Study (8,200 families and 56,000 individuals) to investigate the role of additive genetic effects, maternal and paternal effects on (the co-variation of) fertility and education.

Using GWAS data and about 1,000 married couples from the Framingham Heart study, this analysis investigates genomic assortative mating in human marriages. The study calculates (1) a SNP-specific correlation for each of the 320,195 SNPs, averaging 1,023 married couples and (2) a married couple-specific correlation for each couple, averaging 287,295 SNPs. Of the 320,195 SNP correlations, eight have a p-value 5x10-8 or smaller. These SNPs are all positively correlated for married couples, with a range of 0.16-0.27. The SNPs implicated in genes associated with BMI, height, risk behavior, or the human leukocyte antigen system are further examined. For the half of all SNPs having a more positive assortment, married couples average a statistically significant correlation that is 0.001 higher than randomly paired individuals. Our simulation shows that this difference in correlation can be explained by married couples assorting on about 200 SNPs.

Health and disease are critical concepts in bioethics with far-reaching social and political implications. In view of the aforesaid background it is proposed to study the differentials in Basal Metabolic Rate (BMR), Body Mass Index (BMI) and Diabetes and to study the effect of socio-economic and demographic indicators on BMR, BMI and Diabetes in selected states of India. The present study relies on National Family Health Survey-III conducted in 2005-06 for understanding the gender differentials in BMR, BMI and Diabetes (main dependent variables). The Independent variables will be various socio-demographic indicators like age, sex, highest educational level, place of residence, religion, caste/tribe, wealth index, occupation, alcohol and tobacco use. BMR, BMI and Diabetes are correlated with each other and differ by gender with different socio-economic and demographic characteristics. The means BMR is higher in males besides higher prevalence of diabetes than females. Females have highest percentage of overweight and underweight. Logistic regression result showed high correlation between those indicators with diabetes.

Overweight and obesity are major contributors of insulin resistance and their prevalence and determinants are known to vary in different populations.The objective of the study was to assess the proportion and determinants of overweight and obesity among diabetic women of reproductive age attending a tertiary hospital in Bangladesh.This cross-sectional analytic study was conducted among 888 diabetic women of reproductive age using a semi-structured questionnaire and purposive sampling technique.The overall prevalence of overweight was47%(95%CI48-45) and that of obesity was23%(95%CI21-24).On Pearson’s correlation analysis, BMI(r=0.135,p=0.001) and WC(r=0.162,p=0.001) were significantly associated with age and similarly BMI(r=0.151,p=0.001),WC(r=0.087,p=0.009)and WHR(r=0.094, p=0.005) were correlated with income.On binary logistic regression, BMI was significantly associated with age(p<0.05),income(p<0.05) and management of diabetes by OHA(p<0.05). On the other hand, WC was significantly associated with age(p<0.001),income(p<0.05) and management of diabetes by OHA(p<0.05).WHR was significantly associated with duration of diabetes(p<0.05).A high prevalence of both overweight and obesity exists in diabetic women of reproductive age and associated with increasing age, income, duration of diabetes, and use of oral hypoglycemic agents.

Investigating the effect of mortality shocks on humans is difficult in the absence of the possibility to set up laboratory experiments. However, some events in the human history serve as natural experiments.
This paper aims to analyze whether sudden changes in external conditions affect the slope of the mortality curve or shift the curve upwards proportionally at all ages.
Two cases of natural mortality experiments are presented and used for the analysis: Australian civilian prisoners during WWII in a Japanese camp and the Ukrainian Famine in 1933.
The death rates of the POWs were higher during the imprisonment but the slope of the curve appeared not to have changed compared to the normal mortality regime. During the Ukrainian Famine, instead, the curves for different years of famine converged at old ages. The results found evidence that selection could be the cause of the convergence.

The Gompertz distribution is often fitted to lifespan data, however testing whether the fit satisfies theoretical criteria was neglected. Here five goodness-of-fit measures, the Anderson-Darling statistic, the Kullback-Leibler discrimination information, the correlation coefficient test, testing for the mean of the sample hazard and a nested test against the generalized extreme value distributions are discussed. Along with an application to laboratory rat data, critical values calculated by the empirical distribution
of the test statistics are also presented.