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Results for “Demographic modelling”

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PubMed1999

Modeling the effects of nutritional and socioeconomic factors on the growth and morbidity of Kenyan school children.

This paper estimates dynamic models for the height, head circumference, weight, and morbidity of approximately 110 Kenyan school children (6-9 years) in a multivariate longitudinal data framework. Dynamic models allow anthropometric dimensions to depend on the respective measurements in the previous period. The system of 4 equations specified for height, head circumference, weight, and morbidity incorporates the inter-relationships among these variables; explanatory variables in the model consist of nutritional, socioeconomic, demographic, and environmental factors. The model parameters are estimated using the principle of maximum-likelihood, while controlling for the unobserved between-children differences. The main findings are, first, that calcium intakes are positively associated with height while protein and energy intakes are associated with weight. Vitamin A intakes are negatively associated with morbidity. Second, socioeconomic status plus the cash income of the household is a significant predictor of height, head circumference, and morbidity. Third, maternal height is positively associated with children's height and maternal body mass index (BMI) is positively associated with children's weight. Fourth, parents' scores on psychological tests, mother's age, and children's hemoglobin concentration are negatively associated with morbidity while mothers' morbidity is positively associated with children's morbidity. Implications of the modeling results are discussed. Am. J. Hum. Biol. 11:317-326, 1999. Copyright 1999 Wiley-Liss, Inc.

Journal Article↗

PubMed1983

[The dynamics of multi-regional demographic systems--the case of a nonlinear migration model].

"To provide new insight into the evolution of multiregional population systems, this article presents a dynamic study of a nonlinear variant of the components-of-change model. In this variant, migrants out of a region do not distribute themselves among destination regions in constant proportions (as in the classical linear variant). Rather their allocation is proportional to that of population (weighted so as to account for the difficulty to move between regions). The analysis focuses on the existence, characteristics, and determination of equilibrium states. It is illustrated with an application to the population of Canada and its five large regions." (summary in ENG)

Americas↗

PubMed1999

Association of dialyzer reuse with hospitalization and survival rates among U.S. hemodialysis patients: do comorbidities matter?

The objective of this study was to determine whether the associations between reuse of hemodialyzers and higher rates of death and hospitalization persist after adjustment for comorbidity. This was a nonconcurrent cohort study of survival and hospitalization rates among 1491 U.S. chronic hemodialysis patients beginning treatment in 1986 and 1987. The impact of dialyzer reuse was compared across three survival models: an unadjusted model, a "base" model adjusted only for demographics and renal diagnosis, and an "augmented" model additionally adjusted for comorbidities. We found that reuse of dialyzers was associated with a similarly higher rate of death in analyses unadjusted for confounders (relative risk [RR] 1.25, 95% confidence interval [CI] 0.97-1.61), adjusted for demographics and renal diagnosis (RR 1.16, 95% CI 0.96-1.41), and analyses additionally adjusted for comorbidities (RR = 1.25, CI, 1.03, 1.52). Reusing dialyzers was also associated with a greater rate of hospitalization that was stable regardless of adjustment procedures. We conclude that higher rates of death and hospitalization associated with dialyzer reuse persist regardless of adjustment for demographic characteristics or baseline comorbidities. These findings amplify concerns that there exists elevated morbidity among hemodialysis patients treated in facilities that reuse hemodialyzers. Although the association we observed was not confounded by comorbidity, a cause-and-effect relationship between dialyzer reuse and morbidity could not be proved because of the inability to control for aspects of care other than dialyzer reuse.

Adult↗

PubMed1992

Epidemic and demographic interaction in the spread of potentially fatal diseases in growing populations.

The spread of a potentially fatal infectious disease is considered in a host population that would increase exponentially in the absence of the disease. Taking into account how the effective contact rate C(N) depends on the population size N, the model demonstrates that demographic and epidemiological conclusions depend crucially on the properties of the contact function C. Conditions are given for the following scenarios to occur: (i) the disease spreads at a lower rate than the populations grows and does not modify the population growth rate: (ii) the disease initially spreads at a faster rate than the population grows and lowers the population growth rate in the long run and the following three subscenarios are possible: (iia) the population still grows exponentially, but at a slower rate; (iib) population growth is limited, but the population size does not decay; (iic) population increase is converted into population decrease.

Animals↗

PubMed1996

Cohort-specific rural-urban migration in Africa.

"Rural-urban migration has been modeled by both demographers and economists since the 1960s. Little regard has been given by either discipline for the other's models.... The purpose of this paper is to address this void in the African context. We examine three hypotheses: (1) that variables explaining the net urban in-migration rates vary with the age of the migrants; (2) that changes in the availability of services in urban areas [are] a factor in migration; and (3) that cohort structures (age pyramids) are also part of the explanation."

Africa↗

PubMed1983

Demographic factors and cancer mortality. A mathematical model for cancer mortality in Denmark 1943-78.

Deaths from cancer in Denmark from 1943-1978 were extracted from the Danish National Death Register at the Danish Institute for Clinical Epidemiology. This paper illustrates the relationship between demographic factors and mortality from a large group of cancers, which increases progressively from young adult life into old age. One-year age-specific mortality rates between 30 and 79 years of age were computed for 14 different cancer sites among both males and females, in five ten-year birth cohorts and for the capital and provinces. The number of deaths at a particular age were found to follow a Poisson distribution and the mortality rate could be expressed by the function lx = bxk, where lx is the mortality rate at age x, and b and k are parameters to be estimated. With this model a straight line is obtained, when mortality and age are plotted on a double logarithmic scale. The maximum likelihood estimates of b and k were found iteratively for each of the 280 combinations of sex--cancer site--residence--cohort. For fixed sex and cancer site the relationship between age, residence and cohort was examined. It appeared that k was independent of residence. For 10 of the male cancers and 12 of the female cancers, k was found to be independent of cohort and in the last 6 cases k was found to be a linear function of cohort. For 12 out of 14 cancer sites among males the ratio of mortality in the capital to mortality in the provinces was significantly greater than one.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed2003

Initial burden of disease estimates for South Africa, 2000.

BACKGROUND: This paper describes the first national burden of disease study for South Africa. The main focus is the burden due to premature mortality, i.e. years of life lost (YLLs). In addition, estimates of the burden contributed by morbidity, i.e. the years lived with disability (YLDs), are obtained to calculate disability-adjusted life years (DALYs); and the impact of AIDS on premature mortality in the year 2010 is assessed. METHOD: Owing to the rapid mortality transition and the lack of timely data, a modelling approach has been adopted. The total mortality for the year 2000 is estimated using a demographic and AIDS model. The non-AIDS cause-of-death profile is estimated using three sources of data: Statistics South Africa, the National Department of Home Affairs, and the National Injury Mortality Surveillance System. A ratio method is used to estimate the YLDs from the YLL estimates. RESULTS: The top single cause of mortality burden was HIV/AIDS followed by homicide, tuberculosis, road traffic accidents and diarrhoea. HIV/AIDS accounted for 38% of total YLLs, which is proportionately higher for females (47%) than for males (33%). Pre-transitional diseases, usually associated with poverty and underdevelopment, accounted for 25%, non-communicable diseases 21% and injuries 16% of YLLs. The DALY estimates highlight the fact that mortality alone underestimates the burden of disease, especially with regard to unintentional injuries, respiratory disease, and nervous system, mental and sense organ disorders. The impact of HIV/AIDS is expected to more than double the burden of premature mortality by the year 2010. CONCLUSION: This study has drawn together data from a range of sources to develop coherent estimates of premature mortality by cause. South Africa is experiencing a quadruple burden of disease comprising the pre-transitional diseases, the emerging chronic diseases, injuries, and HIV/AIDS. Unless interventions that reduce morbidity and delay morbidity become widely available, the burden due to HIV/AIDS can be expected to grow very rapidly in the next few years. An improved base of information is needed to assess the morbidity impact more accurately.

Acquired Immunodeficiency Syndrome↗

PubMed1998

Androgen metabolism and prostate cancer: establishing a model of genetic susceptibility.

The prostate is an androgen-regulated organ, which has led to long-standing interest in the role of androgens in prostate carcinogenesis. Although evidence of a hormonal etiology for prostate cancer is strong, it is almost entirely circumstantial. Much of the problem in proving a causal relationship relates to the continued difficulties in reliably measuring human tissue-specific exposure to endogenous steroid hormones. The international and racial-ethnic variations in prostate cancer incidence, combined with the effects of migration on risk patterns, have suggested that whereas environmental factors are likely to be important, genetic factors might also play a central role in determining prostate cancer risk. We are developing a polygenic model of prostate carcinogenesis focused around a series of genes involved in androgen biosynthesis and androgen activation, transport, and metabolism in the prostate. In this developing model, we have initially targeted four genes based on three main criteria: (a) all encode products that play important roles in inducing androgen stimulation in the prostate; (b) all are polymorphic; and (c) all show substantial allelic variation in the polymorphic marker among the racial-ethnic groups of greatest interest in terms of prostate cancer risk. In addition to studying how the polymorphic markers of interest are related to prostate cancer development within and between racial-ethnic groups, we are concurrently evaluating whether genotypic variations correlate in the anticipated direction with biochemical parameters in vitro and in vivo. We summarize the development of this model and the state of knowledge related to each of the genes comprising the current model. We discuss the extent to which the current model can explain demographic variation in prostate cancer risk as well as the potential for future expansion of the model to incorporate environmental risk factors as well as additional genes. The model, when fully developed, can potentially provide a basis for targeting populations for screening interventions and/or preventive strategies aimed at the multigene products or at the genes themselves.

3-Hydroxysteroid Dehydrogenases↗

PubMed1975

The size and demographic composition of social groups of wild orang-utans.

Mackinnon (1974) observed social sub-groups of wild orang-utans. The groups' distribution of size and age-sex composition can test mathematical models of group formation. As predicted by models published previously, a truncated Poisson distribution describes the group sizes well. The inferred parameters governing group formation conform to a pattern in other primate species. A simple model for the demographic composition of a sub-group assumes that an individual joins a sub-group with a probability independent of his age-sex class and of other members of the sub-group. This model's predictions, which agree poorly with observation, offer a quantitative baseline against which one can infer when a demographic combination occurs with a non-random frequency.

Age Factors↗

PubMed2006

Relationships among mental health status, social context, and demographic characteristics in Taiwanese aboriginal adolescents: a structural equation model.

The purposes of this study were to examine the relationships among mental health status, demographic characteristics, and social contexts, including family conflict and support, connectedness to school, and affiliation with peers who exhibit delinquent behavior and who use substances, among Taiwanese aboriginal adolescents. A total of 251 aboriginal junior high school students in an isolated mountainous area of southern Taiwan were recruited, and the relationships among mental health status, demographic characteristics, and social contexts among them were examined using a structural equation model (SEM). The SEM revealed that family conflict and support had direct influences on mental health status and connectedness to school. Family conflict had a direct relationship with affiliation with peers who use substances, and family conflict and support were both indirectly linked with affiliation with peers who exhibit delinquent behavior and who used substances; these were mediated by a poor mental health status. Female and older age were directly linked with a poor mental health status and were indirectly linked with a greater number of peers who exhibit delinquent behavior and who use substances via the poor mental health status. Disruptive parenting was directly linked with affiliation with peers who use substances. The authors suggest that those who devise strategies to improve aboriginal adolescents' mental health and discourage substance use should take these relationships among mental health, demographic characteristics, and social contexts into account.

Adolescent↗

PubMed2004

Coexistence of multiple pathogen strains in stochastic epidemic models with density-dependent mortality.

Stochastic differential equations that model an SIS epidemic with multiple pathogen strains are derived from a system of ordinary differential equations. The stochastic model assumes there is demographic variability. The dynamics of the deterministic model are summarized. Then the dynamics of the stochastic model are compared to the deterministic model. In the deterministic model, there can be either disease extinction, competitive exclusion, where only one strain persists, or coexistence, where more than one strain persists. In the stochastic model, all strains are eventually eliminated because the disease-free state is an absorbing state. However, if the population size and the initial number of infected individuals are sufficiently large, it may take a long time until all strains are eliminated. Numerical simulations of the stochastic model show that coexistence cases predicted by the deterministic model are an unlikely occurrence in the stochastic model even for short time periods. In the stochastic model, either disease extinction or competitive exclusion occur. The initial number of infected individuals, the basic reproduction numbers, and other epidemiological parameters are important determinants of the dominant strain in the stochastic epidemic model.

Communicable Diseases↗

PubMed2003

HIV-related mental health care: factors influencing dropout among low-income, HIV-positive individuals.

A prospective design was used to collect data from 132 HIV-positive individuals presenting for mental health care at an inner-city HIV-related mental health clinic located in a large metropolitan area of the Southeastern USA. Data were analyzed to assess associations between study variables and whether participants returned for care following an initial mental health assessment. Hierarchical logistic regression analyses were conducted to determine the extent to which the addition of measures of health beliefs and HIV-related stigma would enhance the predictive capacity of a dropout model that included demographics and health status measures. As health beliefs and HIV-related stigma were added to the model, the predictive capacity increased significantly (R(2)=0.29 to R(2)=0.63, p<0.05). Those who did not return for care had higher levels of perceived barriers to mental health care, higher levels of HIV-related stigma, were more likely to be of non-white ethnicity and had lower T-cell counts. These findings indicate that mental health providers may need to ensure care systems are responsive to the social and cultural characteristics of clients, and the HIV epidemic itself, in order to effectively engage clients into care.

Adult↗

PubMed2006

Determinants of early outcome in spontaneous lobar cerebral hemorrhage.

OBJECTIVE: To identify determinants of early outcome in spontaneous lobar hemorrhage. MATERIALS AND METHODS: From 2500 acute stroke patients included in a prospective hospital-based stroke registry over a 12-year period, 97 cases of lobar hematoma were selected. Determinants of in-hospital mortality were studied in multiple regression models. RESULTS: Lobar hematomas accounted for 3.9% of all acute stroke patients and 35.9% of intracerebral hemorrhages. The presence of chronic obstructive pulmonary disease (COPD) was a significant predictive variable in the model based on demographic variables and vascular risk factors [odds ratio (OR): 17.18; 95% CI: 1.77-166.22] and in the model based on these variables plus clinical data (OR: 15.12; 95% CI: 1.27-179.59). Other predictive variables included altered consciousness, previous cerebral infarct and chronic liver disease. CONCLUSIONS: COPD appeared as the most important predictor of death during hospitalization after lobar cerebral hemorrhage, a finding not generally acknowledged earlier.

Aged↗

PubMed1996

The simultaneous analysis of patient, physician and group practice influences on annual mammography performance.

The current study examined the relationship of several variables at the patient (n = 2780), physician (n = 166), and group practice (n = 45) levels for predicting receipt of annual mammography screening. Patient-level variables included constructs from the Triandis Model of Choice; physician-level variables included measures of barriers and receptivity to prevention, as well as demographic information. Hierarchical modeling demonstrated that variables at the patient and physician level reliably predict annual mammography screening, while frequency of screening did not vary across group practices after accounting for patient and physician variables. Patient-level predictors included social norms, perceived consequences and perceived barriers. The only physician-level predictor identified was annual mammography recommendation. These findings add to data which emphasize the importance of public education and social support in health maintenance activities.

Aged↗

PubMed2005

Recombination hotspots as a point process.

The variation of the recombination rate along chromosomal DNA is one of the important determinants of the patterns of linkage disequilibrium. A number of inferential methods have been developed which estimate the recombination rate and its variation from population genetic data. The majority of these methods are based on modelling the genealogical process underlying a sample of DNA sequences and thus explicitly include a model of the demographic process. Here we propose a different inferential procedure based on a previously introduced framework where recombination is modelled as a point process along a DNA sequence. The approach infers regions containing putative hotspots based on the inferred minimum number of recombination events; it thus depends only indirectly on the underlying population demography. A Poisson point process model with local rates is then used to infer patterns of recombination rate estimation in a fully Bayesian framework. We illustrate this new approach by applying it to several population genetic datasets, including a region with an experimentally confirmed recombination hotspot.

Bayes Theorem↗

PubMed2005

A multilocus sequence survey in Arabidopsis thaliana reveals a genome-wide departure from a neutral model of DNA sequence polymorphism.

The simultaneous analysis of multiple genomic loci is a powerful approach to studying the effects of population history and natural selection on patterns of genetic variation of a species. By surveying nucleotide sequence polymorphism at 334 randomly distributed genomic regions in 12 accessions of Arabidopsis thaliana, we examined whether a standard neutral model of nucleotide sequence polymorphism is consistent with observed data. The average nucleotide diversity was 0.0071 for total sites and 0.0083 for silent sites. Although levels of diversity are variable among loci, no correlation with local recombination rate was observed, but polymorphism levels were correlated for physically linked loci (<250 kb). We found that observed distributions of Tajima's D- and D/D(min)- and of Fu and Li's D-, D*- and F-, F*-statistics differed significantly from the expected distributions under a standard neutral model due to an excess of rare polymorphisms and high variances. Observed and expected distributions of Fay and Wu's H were not different, suggesting that demographic processes and not selection at multiple loci are responsible for the deviation from a neutral model. Maximum-likelihood comparisons of alternative demographic models like logistic population growth, glacial refugia, or past bottlenecks did not produce parameter estimates that were more consistent with observed patterns. However, exclusion of highly polymorphic "outlier loci" resulted in a fit to the logistic growth model. Various tests of neutrality revealed a set of candidate loci that may evolve under selection.

Arabidopsis↗

PubMed2004

Estimating HIV incidence and detection rates from surveillance data.

BACKGROUND: Markov models that incorporate HIV test information can increase precision in estimates of new infections and permit the estimation of detection rates. The purpose of this study was to assess the functioning of a Markov model for estimating new HIV infections and HIV detection rates in Louisiana using surveillance data. METHODS: We expanded a discrete-time Markov model by accounting for the change in AIDS case definition made by the Centers for Disease Control and Prevention in 1993. The model was applied to quarterly HIV/AIDS surveillance data reported in Louisiana from 1981 to 1996 for various exposure and demographic subgroups. When modeling subgroups defined by exposure categories, we adjusted for the high proportion of missing exposure information among recent cases. We ascertained sensitivity to changes in various model assumptions. RESULTS: The model was able to produce results consistent with other sources of information in the state. Estimates of new infections indicated a transition of the HIV epidemic in Louisiana from (1) predominantly white men and men who have sex with men to (2) women, blacks, and high-risk heterosexuals. The model estimated that 61% of all HIV/AIDS cases were detected and reported by 1996, yet half of all HIV/non-AIDS cases were yet to be detected. Sensitivity analyses demonstrated that the model was robust to several uncertainties. CONCLUSIONS: In general, the methodology provided a useful and flexible alternative for estimating infection and detection trends using data from a U.S. surveillance program. Its use for estimating current infection will need further exploration to address assumptions related to newer treatments.

Female↗

PubMed1990

Interregional migration in an extended input-output model.

"This article develops a two-region version of an extended input-output model that disaggregates consumption among employed, unemployed, and inmigrant households, and which explicitly models the influx into a region of migrants to take up a proportion of any jobs created in the regional economy. The model is empirically tested using real data for the Scotland (UK) regions of Strathclyde and Rest-of-Scotland. Sets of interregional economic, demographic, demo-economic, and econo-demographic multipliers are developed and discussed, and the effects of a range of economic and demographic impacts are modeled. The circumstances under which Hawkins-Simon conditions for non-negativity are breached are identified, and the limits of the model discussed."

Demography↗