Explaining Family Change and Variation: Challenges for Family Demographers

Twenty years ago, the National Institute of Child Health and Human Development (NICHD) issued a request for proposals that resulted in the National Survey of Families and Households (NSFH), a unique survey valuable to a wide range of family scholars. This paper describes the efforts of an interdisciplinary group of family demographers to build on the progress enabled by the NSFH and many other theoretical and methodological innovations. Our work, also supported by NICHD, will develop plans for research and data collection to address the central question of what causes family change and variation. We outline the group's initial assessments of orienting frameworks, key aspects of family life to study, and theoretical and methodological challenges for research on family change. Finally, we invite family scholars to follow our progress and to help develop this shared public good.     

Simulating Behavioral Influences on Community Flood Risk under Future Climate Scenarios

Flood risk is a function of both climate and human behavior, including individual and societal actions. For this reason, there is a need to incorporate both human and climatic components in models of flood risk. This study simulates behavioral influences on the evolution of community flood risk under different future climate scenarios using an agent-based model (ABM). The objective is to understand better the ways, sometimes unexpected, that human behavior, stochastic floods, and community interventions interact to influence the evolution of flood risk. One historic climate scenario and three future climate scenarios are simulated using a case study location in Fargo, North Dakota. Individual agents can mitigate flood risk via household mitigation or by moving, based on decision rules that consider risk perception and coping perception. The community can mitigate or disseminate information to reduce flood risk. Results show that agent behavior and community action have a significant impact on the evolution of flood risk under different climate scenarios. In all scenarios, individual and community action generally result in a decline in damages over time. In a lower flood risk scenario, the decline is primarily due to agent mitigation, while in a high flood risk scenario, community mitigation and agent relocation are primary drivers of the decline. Adaptive behaviors offset some of the increase in flood risk associated with climate change, and under an extreme climate scenario, our model indicates that many agents relocate.     

Modeling Logistic Performance in Quantitative Microbial Risk Assessment

In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times—mutually dependent in successive steps in the chain—cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for  Listeria monocytogenes  in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.     

Minimum phi-divergence estimators for loglinear models with linear constraints and multinomial sampling

In this paper the family ofφ-divergence estimators for loglinear models with linear constraints and multinomial sampling is studied. This family is an extension of the maximum likelihood estimator studied by Haber and Brown (1986). A simulation study is presented and some alternative estimators to the maximum likelihood are obtained. This work was parcially supported by Grant DGES PB2003-892     

Human Immunodeficiency Virus (HIV) Seropositive Homeless Men: Behavioral and Social Characteristics

Homeless persons living in US. innercities are at risk for human immunodeficiency virus (HW) infection, but few studies have examined the continued risk behaviors of HIV infected homeless men. We investigated the sexual behavior of 32 homeless men who had tested HIV seropositive. Twenty-five percent of HW positive men reported a history of injection drug use, 34% had sex with men, over 40% had participated in commercial sex, and 59% had been treated for a non-HIV sexually transmitted disease. HIV seropositive men also reported recent sexual behavior, with 62% having sex in the previous month and 50% currently sexually active. Condom use was inconsistent among seropositive men; 44% of vaginal and 50% of anal intercourse occasions in the preceding three months did not involve condoms, and 28% of HW seropositive men did not use a condom during their most recent sexual encounter. Substance use was frequently associated with unprotected sexual behavior among HW seropositive men. Finally, measures of life satisfaction showed that HIV seropositive men were most satisfied with their relationships, mental health, and spiritual well being. These data suggest a need for intensive behavioral.interventions tailored for homeless HW infected men and we recommend that existing substance use treatment and holistic care be incorporated into behavioral interventions for HW infected men.     

A program of research with Hispanic and African American families: three decades of intervention development and testing influenced by the changing cultural context of Miami

In this article we summarize work with poor, inner-city Hispanic and African American families conducted at the University of Miami Center for Family Studies. We elucidate ways in which this research program has paralleled the treatment development paradigm and has been responsive to changes in local demographics. Specific cultural issues pertaining to Hispanics and African Americans are discussed in light of treatment development and implementation. Future directions and challenges for working with poor, inner-city minority families are addressed.     

Trauma symptoms, sexual behaviors, and substance abuse: correlates of childhood sexual abuse and HIV risks among men who have sex with men

Childhood sexual abuse is associated with high-risk sexual behavior in men who have sex with men. This study examined psychological and behavioral correlates of HIV risk behavior associated with childhood sexual abuse in a sample of men who have sex with men. Men attending a large gay pride event (N = 647) completed anonymous surveys that assessed demographic characteristics, childhood sexual abuse history, symptoms of dissociation and trauma-related anxiety, borderline personality characteristics, substance use, and sexual risk behavior. Results indicated that men who have a history of childhood sexual abuse were more likely to: engage in high-risk sexual behavior (i.e., unprotected receptive anal intercourse), trade sex for money or drugs, report being HIV positive, and experience non-sexual relationship violence. Results of this study extend previous research to show that men who have sex with men and who have a history of child sexual abuse are more likely to be at high risk for HIV infection.     

Combining forward and backward mortality estimation

Demographers often form estimates by combining information from two data sources—a challenging problem when one or both data sources are incomplete. A classic example entails the construction of death probabilities, which requires death counts for the subpopulations under study and corresponding base population estimates. Approaches typically entail ‘back projection', as in Wrigley and Schofield's seminal analysis of historical English data, or ‘inverse’ or ‘forward projection’ as used by Lee in his important reanalysis of that work, both published in the 1980s. Our paper shows how forward and backward approaches can be optimally combined, using a generalized method of moments (GMM) framework. We apply the method to the estimation of death probabilities for relatively small subpopulations within the United States (men born 1930–39 by state of birth by birth cohort by race), combining data from vital statistics records and census samples.