Is prenatal sex selection associated with lower female child mortality?

I examine whether prenatal sex selection has substituted postnatal excess female mortality by analysing the dynamics of child sex ratios between 1980 and 2015 using country-level life table data. I decompose changes in child sex ratios into a ‘fertility’ component attributable to prenatal sex selection and a ‘mortality’ component attributable to sex differentials in postnatal survival. Although reductions in numbers of excess female deaths have accompanied increases in missing female births in all countries experiencing the emergence of prenatal sex selection, relative excess female mortality has persisted in some countries but not others. In South Korea, Armenia, and Azerbaijan, mortality reductions favouring girls accompanied increases in prenatal sex selection. In India, excess female mortality was much higher and largely stable as prenatal sex selection emerged, but slight reductions were seen in the 2000s. In China, although absolute measures showed reductions, relative excess female mortality persisted as prenatal sex selection increased.     

Mortality and Attrition Processes in Longitudinal Studies in Africa: An Appraisal of the Iford Surveys

This paper considers the impact of sample-attrition through dropouts on mortality analyses, using the pioneering IFORD survey of Yaounde (Cameroon). The essential issue in the IFORD surveys is the possibility that mortality of members of the cohort may differentially select some children, with specific underlying characteristics. The paper implements a method to assess the following three distinct concerns that may arise in the analysis of the IFORD data: (a) the estimation of the relationship between the covariates and the rate of occurrence of mortality or attrition over time; (b) the study of the interrelation between processes under a specific set of conditions during intervals between rounds for those children still alive and in the survey at the beginning of each interval; and (c) the issue of whether mortality and mortality differentials are affected when attrition is ignored. This approach accounts for sample-selection bias that may have resulted in the attrition process. The analyses provide insights into the debate, which has been ongoing since the late 1970s among students of African demography, regarding the selection problem in the IFORD surveys. Based on a multinomial survival modelling and bivariate probit with sample-selection framework, the results substantiate the belief that average levels and differentials of mortality would not have been different for children who dropped out from the survey than for those who remained in the survey. This is evidence that mortality estimates are virtually unaffected if attrition is ignored.     

A Turning Point in Gender Bias in Mortality? An Update on the Number of Missing Women

Amartya Sen started a debate about gender bias in mortality by estimating the number of “missing women,” which refers to the number of females of any age who have presumably died as a result of discriminatory treatment. Depending on the assumptions made, the combined estimates for countries exhibiting the presence of such gender bias varied between 60 and 107 million. As new population data have become available for these countries, this article examines whether the number of “missing women” has changed in the past decade. The combined estimate of the number of missing women has risen in absolute terms but has fallen slightly in relation to overall population. Considerable improvement is evident in West Asia, North Africa, and parts of South Asia, while only small improvements have occurred in India and a deterioration took place in China. Analyses of the underlying causes of gender bias in mortality suggest that improvements are largely related to improved female education and employment opportunities and rising overall incomes, while deterioration is mostly attributable to the rising incidence of sex‐selective abortions.     

Microcredit and Domestic Violence in Bangladesh: An Exploration of Selection Bias Influences

This article explores the relationship between women’s participation in microcredit groups and domestic violence in Bangladesh. Several recent studies have raised concern about microcredit programs by reporting higher levels of violence among women who are members. These results, however, may be attributable to selection bias because members might differ from nonmembers in ways that make them more susceptible to violence to begin with. Using a sample of currently married women from the 2007 Bangladesh Demographic Health Survey (BDHS) (N = 4,195), we use propensity score matching (PSM) as a way of exploring selection bias in this relationship. Results suggest that the previously seen strong positive association between membership and violence does not hold when an appropriate comparison group, generated using PSM, is used in the analyses. Additional analyses also suggest that levels of violence do not differ significantly between members and nonmembers and instead could depend on context-specific factors related to poverty. Members for whom a match is not found report considerably higher levels of violence relative to nonmembers in the unmatched group. The background characteristics of members and nonmembers who do not match suggest that they are more likely to be younger and from relatively well-to-do households.     

Death by survey: Estimating adult mortality without selection bias from sibling survival data

The widely used methods for estimating adult mortality rates from sample survey responses about the survival of siblings, parents, spouses, and others depend crucially on an assumption that, as we demonstrate, does not hold in real data. We show that when this assumption is violated so that the mortality rate varies with sibship size, mortality estimates can be massively biased. By using insights from work on the statistical analysis of selection bias, survey weighting, and extrapolation problems, we propose a new and relatively simple method of recovering the mortality rate with both greatly reduced potential for bias and increased clarity about the source of necessary assumptions.     

Decompression of Period Old-Age Mortality: When Adjusted for Bias,the Variance in the Ages at Death Shows Compression

Formal derivations and empirical evidence, in the framework of Fries-Kannisto's hypothesis, show that the indicators of mortality compression based on age-at-death distribution, left-censored at a fixed old age, may be subject to a bias toward showing mortality decompression in the case of a mortality decline. The previously reported increasing variance in ages at death above fixed old ages in developed countries was mainly the effect of a mortality shift, not decompression. When adjusted for this bias, the indicators of variance in ages at death show a compression of period mortality.     

Unequal transitions: Selection bias and the compensatory effect of social background in educational careers

Previous studies have shown that social background inequality differs among educational transitions and it is stronger for those transitions that involve a higher risk of social demotion. This paper focuses on two processes that may account for part of the observed differences in social background inequality across educational transitions. First, it studies how the family of origin might compensate for a ‘false step’ in the early stage of young people's educational careers. This compensatory effect of social background can be described as the likelihood of having ‘a second chance’ for unsuccessful educational transitions. Second, it focuses on two unobserved factors that might potentially bias the effect of social background across educational transitions. These are the students’ unobserved cognitive and non-cognitive skills and their unobserved anticipated choices of dropping out of the education system. Two issues – the compensatory effect of social background and selection bias in educational transitions – are addressed by estimating a probit model with sample selection for the transition to post-compulsory education in Spain.     

老龄健康的经济学研究现状、问题与对策

通过文献回顾发现,目前老龄健康研究最大的问题是研究结论的不一致,甚至相互矛盾,其根本原因在于未能正确处理内生性、生态学谬误等问题。建议通过工具变量法解决联立性偏误、随机分配法解决自选择偏误、Heckman二阶段法解决样本选择偏误、面板数据解决变量遗漏、利用滞后期数据解决反向因果关系问题,利用HLM模型解决生态学谬误。     

The Contribution of Smoking to Black-White Differences in U.S. Mortality

Smoking has significantly impacted American mortality and remains a major cause of morbidity and mortality. No previous study has systematically examined the contribution of smoking-attributable deaths to mortality trends among blacks or to black-white mortality differences at older ages over time in the United States. In this article, we employ multiple methods and data sources to provide a comprehensive assessment of this contribution. We find that smoking has contributed to the black-white gap in life expectancy at age 50 for males, accounting for 20 % to 48 % of the gap between 1980 and 2005, but not for females. The fraction of deaths attributable to smoking at ages above 50 is greater for black males than for white males; and among men, current smoking status explains about 20 % of the black excess relative risk in all-cause mortality at ages above 50 without adjustment for socioeconomic characteristics. These findings advance our understanding of the contribution of smoking to contemporary mortality trends and differences and reinforce the need for interventions that better address the needs of all groups.     

Age distribution, sex ratio and mortality of the red foxVulpes vulpes in Tochigi, central Japan: an estimation using a museum collection

One hundred and thirty carcasses of the red fox were collected in Tochigi Prefecture, by the Tochigi Prefectural Museum, from 1981 to 1991. The young/adult ratio of the sample was 1.60, which suggests that the hunting pressure has been relatively low in this area. Six percent of the animals were 5 years or older which compares to those taken in Hokkaido, but is higher than those in Europe and North America. The sex ratio for all specimens had a tendency towards male bias (0.587), but this bias was higher for the adult (0.605) than for the young (0.576). Among young (0 year-old) foxes, more individuals were killed on roads than by trapping or shooting (P<0.02, chisquare test). This mortality pattern was caused by high mortality of young males (P<0.02). The proportions of adults killed by the three mortality factors were similar, though only one of the 14 foxes older than 4 years old was shot, probably due to age-linked activity patterns. Most road-kills of young foxes occurred in May when juveniles began exploiting and in November when sub-adults began dispersal. The ratios of road-kills for the whole sample and for adults alone were 42% and 34%, respectively. These high rates of road-kills suggest that the mortality pattern in Tochigi has been affected by factors characteristic of urban environments.     

Migration bias in indirect estimates of regional childhood mortality levels

Demographers often use Brass‐style indirect methods to obtain childhood mortality estimates for regions within developing countries. Regional populations are not closed to migration, however, and mortality reports of women resident in a certain region on the survey date may contain information on events and exposure that occurred elsewhere as the mother migrated. Including this “imported”; mortality information may cause significant bias in regional estimates. In this paper the authors: (1) investigate the possible magnitude of migration bias using a multiregional simulation model, (2) propose a modification to standard methods which should reduce bias in many circumstances, and (3) apply the modified technique to data from Brazil's 1980 Census. We find that migration bias can indeed be significant, and that in the specific case of São Paulo state, imported mortality information may result in overestimates of local mortality levels of 10–15% when using Brass‐style methods.     

Exploring Child Mortality Risks Associated with Diverse Patterns of Maternal Migration in Haiti

Internal migration is a salient dimension of adulthood in Haiti, particularly among women. Despite the high prevalence of migration in Haiti, it remains unknown whether Haitian women’s diverse patterns of migration influence their children’s health and survival. In this paper, we introduce the concept of lateral (i.e., rural-to-rural, urban-to-urban) versus nonlateral (i.e., rural-to-urban, urban-to-rural) migration to describe how some patterns of mothers’ internal migration may be associated with particularly high mortality among children. We use the 2006 Haitian Demographic and Health Survey to estimate a series of discrete-time hazard models among 7,409 rural children and 3,864 urban children. We find that compared with their peers with nonmigrant mothers, children born to lateral migrants generally experience lower mortality, whereas those born to nonlateral migrants generally experience higher mortality. Although there are important distinctions across Haiti’s rural and urban contexts, these associations remain net of socioeconomic factors, suggesting they are not entirely attributable to migrant selection. Considering the timing of maternal migration uncovers even more variation in the child health implications of maternal migration; however, the results counter the standard disruption and adaptation perspective. Although future work is needed to identify the processes underlying the differential risk of child mortality across lateral versus nonlateral migrants, the study demonstrates that looking beyond rural-to-urban migration and considering the timing of maternal migration can provide a fuller, more complex understanding of migration’s association with child health.     

Mortality attributable to obesity among middle-aged adults in the united states

Obesity is considered a major cause of premature mortality and a potential threat to the longstanding secular decline in mortality in the United States. We measure relative and attributable risks associated with obesity among middle-aged adults using data from the Health and Retirement Study (1992–2004). Although class II/III obesity (BMI _ 35.0 kg/m2) increases mortality by 40% in females and 62% in males compared with normal BMI (BMI = 18.5-24.9), class I obesity (BMI = 30.0-34.9) and being overweight (BMI = 25.0-29.9) are not associated with excess mortality. With respect to attributable mortality, class II/III obesity (BMI _ 35.0) is responsible for approximately 4% of deaths among females and 3% of deaths among males. Obesity is often compared with cigarette smoking as a major source of avoidable mortality. Smoking-attributable mortality is much larger in this cohort: about 36% in females and 50% in males. Results are robust to confounding by preexisting diseases, multiple dimensions of socioeconomic status (SES), smoking, and other correlates. These findings challenge the viewpoint that obesity will stem the long-term secular decline in U.S. mortality.     

Wives and ex-wives: A new test for homogamy bias in the widowhood effect

Increased mortality following the death of a spouse (the “widowhood effect”) may be due to (1) causation, (2) bias from spousal similarity (homogamy), or (3) bias from shared environmental exposures. This article proposes new tests for bias in the widowhood effect by examining husbands, wives, and ex-wives in a longitudinal sample of over 1 million elderly Americans. If the death of an ex-wife has no causal effect on the mortality of her husband, then an observed association between the mortality of an ex-wife and her husband may indicate bias, while the absence of an effect of an ex-wife’s death on her husband’s mortality would discount the possibility of homogamy bias (and also of one type of shared-exposure bias). Results from three empirical tests provide strong evidence for an effect of a current wife’s death on her husband’s mortality yet no statistically signifi cant evidence for an effect of an ex-wife’s death on her husband’s mortality. These results strengthen the causal interpretation of the widowhood effect by suggesting that the widowhood effect is not due to homogamy bias to any substantial degree.     

Estimating the Effect of Smoking on Slowdowns in Mortality Declines in Developed Countries

Declines in mortality rates for females at older ages in some developed countries, including the United States, have slowed in recent decades even as decreases have steadily continued in some other countries. This study presents a modified version of the indirect Peto-Lopez method, which uses lung cancer mortality rates as a proxy for smoking exposure, to analyze this trend. The modified method estimates smoking-attributable mortality for more-specific age groups than does the Peto-Lopez method. An adjustment factor is also introduced to account for low mortality in the indirect method’s study population. These modifications are shown to be useful specifically in the estimation of deaths attributable to smoking for females at older ages, and in the estimation of smoking-attributable mortality more generally. In a comparison made between the United States and France with the modified method, smoking is found to be responsible for approximately one-half the difference in life expectancy for females at age 65.     

Optimizing the Lee-Carter Approach in the Presence of Structural Changes in Time and Age Patterns of Mortality Improvements

Researchers using the Lee-Carter approach have often assumed that the time-varying index evolves linearly and that the parameters describing the age pattern of mortality decline are time-invariant. However, as several empirical studies suggest, the two assumptions do not seem to hold when the calibration window begins too early. This problem gives rise to the question of identifying the longest calibration window for which the two assumptions hold true. To address this question, we contribute a likelihood ratio–based sequential test to jointly test whether the two assumptions are satisfied. Consistent with the mortality structural changes observed in previous studies, our testing procedure indicates that the starting points of the optimal calibration windows for most populations fall between 1960 and 1990. Using an out-of-sample analysis, we demonstrate that in most cases, models that are estimated to the optimized calibration windows result in more accurate forecasts than models that are fitted to all available data or data beyond 1950. We further apply the proposed testing procedure to data over different age ranges. We find that the optimal calibration windows for age group 0–49 are generally shorter than those for age group 50–89, indicating that mortality at younger ages might have undergone (another) structural change in recent years.     

Nonresponse in repeat population-based voluntary counseling and testing for HIV in rural Malawi

Despite the increasing number of population-based surveys in sub-Saharan Africa that provide testing and counseling for HIV over the past decade, understanding the nature of nonresponse in these surveys, especially panel HIV surveys, is still limited. This article uses longitudinal HIV data collected from rural Malawi in 2004 and 2006 to examine nonresponse in repeat population-based testing. It shows that nonresponse in repeat testing led to significant bias in the estimates of HIV prevalence and to inconsistent conclusions about the predictors of HIV status. In contrast, previous cross-sectional analyses found that nonresponse does not significantly bias the estimates of HIV prevalence. The difference in conclusions from cross-sectional and longitudinal analyses of nonresponse can be attributed to two factors: the different definitions of what constitutes nonresponse in both contexts, and the risk profiles of the missed populations. In particular, although refusal and temporary absence are the major sources ofnonresponse in the cross-sectional contexts, attrition attributable to mortality and out-migration are additional sources of nonresponse in repeat testing. Evidence shows that out-migrants have higher HIV prevalence than nonmigrants, which could account for significant bias in the estimates of prevalence among participants in both tests observed in this study.     

The Impact of Salmon Bias on the Hispanic Mortality Advantage: New Evidence from Social Security Data

A great deal of research has focused on factors that may contribute to the Hispanic mortality paradox in the United States. In this paper, we examine the role of the salmon bias hypothesis—the selective return of less-healthy Hispanics to their country of birth—on mortality at ages 65 and above. These analyses are based on data drawn from the Master Beneficiary Record and NUMIDENT data files of the Social Security Administration. These data provide the first direct evidence regarding the effect of salmon bias on the Hispanic mortality advantage. Although we confirm the existence of salmon bias, it is of too small a magnitude to be a primary explanation for the lower mortality of Hispanic than non-hispanic (NH)-White primary social security beneficiaries. Longitudinal surveys that follow individuals in and out of the United States are needed to further explore the role of migration in the health and mortality of foreign-born US residents and factors that contribute to the Hispanic mortality paradox.     

Grouped zero-inflated count data models of coital frequency

Various count data models are applied to data collected from a sample of Norfolk young persons, who were asked how many times they had had sexual intercourse during the previous two-week period. The models take account of the fact that the data are “grouped”, meaning that for some observations, the count is not known exactly but is known to fall in a particular range. Using a formal testing procedure, we find overwhelming evidence of the presence of excess zeros, and this we attribute to the fact that, at any time, a certain proportion of the population are sexually inactive. Our final model contains two equations, the first being the participation equation which determines whether an individual is sexually active, and the second being the frequency equation which determines the count, conditional on being active. Age, gender, salary, occupational status, marital status and type of living environment all have interesting effects on either participation or frequency. Since a significant proportion of the original sample declined to reveal coital frequency, we address the potential problem of selection bias by including a Heckman-type correction term during the model selection process. Received: 27 November 1998/Accepted: 19 May 1999     

Estimating Smoking-Attributable Mortality in the United States

Tobacco use is the largest single cause of premature death in the developed world. Two methods of estimating the number of deaths attributable to smoking use mortality from lung cancer as an indicator of the damage from smoking. We re-estimate the coefficients of one of these, the Preston/Glei/Wilmoth model, using recent data from U.S. states. We calculate smoking-attributable fractions for the 50 states and the United States as a whole in 2004, and estimate the contribution of smoking to the high adult mortality of the southern states. We estimate that 21% of deaths among men and 17% among women were attributable to smoking in 2004. Across states, attributable fractions range from 11% to 30% among men and from 7% to 23% among women. Smoking-related mortality also explains as much as 60% of the mortality disadvantage of southern states compared with other regions. At the national level, our estimates are in close agreement with those of the Centers for Disease Control and Prevention and Preston/Glei/Wilmoth, particularly for men, although we find greater variability by state than does CDC. We suggest that our coefficients are suitable for calculating smoking-attributable mortality in contexts with relatively mature epidemics of cigarette smoking.