Mark E. McGovern

From Angela's Ashes to the Celtic Tiger: Early Life Conditions and Adult Health in Ireland

We use data from the Irish census and exploit regional and temporal variation in infant mortality rates over the 20th century to examine effects of early life conditions on later life health. The urban mortality penalty collapsed in Ireland in the years right after World War II. Our main identification is public health interventions centered on improved sanitation and food safety, which we believed played a leading role in eliminating the Irish urban infant mortality penalty. Our estimates suggest that a unit decrease in mortality rates at time of birth reduces the probability of being disabled as an adult by about 12-18%.

Physical stature decline and the health status of the elderly population in England

Few research papers in economics have examined the extent, causes or consequences of physical stature decline in aging populations. Using repeated observations on objectively measured data from the English Longitudinal Study of Aging (ELSA), we document that reduction in height is an important phenomenon among respondents aged 50 and over. On average, physical stature decline occurs at an annual rate of between 0.08% and 0.10% for males, and 0.12% and 0.14% for females-which approximately translates into a 2-4 cm reduction in height over the life course. Since height is commonly used as a measure of long-run health, our results demonstrate that failing to take age-related height loss into account substantially overstates the health advantage of older birth cohorts relative to their younger counterparts. We also show that there is an absence of consistent predictors of physical stature decline at the individual level. However, we demonstrate how deteriorating health and reductions in height occur simultaneously. We document that declines in muscle mass and bone density are likely to be the mechanism through which these effects are operating. If this physical stature decline is determined by deteriorating health in adulthood, the coefficient on measured height when used as an input in a typical empirical health production function will be affected by reverse causality. While our analysis details the inherent difficulties associated with measuring height in older populations, we do not find that significant bias arises in typical empirical health production functions from the use of height which has not been adjusted for physical stature decline. Therefore, our results validate the use of height among the population aged over 50.

Using interviewer random effects to remove selection bias from HIV prevalence estimates

BackgroundSelection bias in HIV prevalence estimates occurs if non-participation in testing is correlated with HIV status. Longitudinal data suggests that individuals who know or suspect they are HIV positive are less likely to participate in testing in HIV surveys, in which case methods to correct for missing data which are based on imputation and observed characteristics will produce biased results.MethodsThe identity of the HIV survey interviewer is typically associated with HIV testing participation, but is unlikely to be correlated with HIV status. Interviewer identity can thus be used as a selection variable allowing estimation of Heckman-type selection models. These models produce asymptotically unbiased HIV prevalence estimates, even when non-participation is correlated with unobserved characteristics, such as knowledge of HIV status. We introduce a new random effects method to these selection models which overcomes non-convergence caused by collinearity, small sample bias, and incorrect inference in existing approaches. Our method is easy to implement in standard statistical software, and allows the construction of bootstrapped standard errors which adjust for the fact that the relationship between testing and HIV status is uncertain and needs to be estimated.ResultsUsing nationally representative data from the Demographic and Health Surveys, we illustrate our approach with new point estimates and confidence intervals (CI) for HIV prevalence among men in Ghana (2003) and Zambia (2007). In Ghana, we find little evidence of selection bias as our selection model gives an HIV prevalence estimate of 1.4% (95% CI 1.2% – 1.6%), compared to 1.6% among those with a valid HIV test. In Zambia, our selection model gives an HIV prevalence estimate of 16.3% (95% CI 11.0% - 18.4%), compared to 12.1% among those with a valid HIV test. Therefore, those who decline to test in Zambia are found to be more likely to be HIV positive.ConclusionsOur approach corrects for selection bias in HIV prevalence estimates, is possible to implement even when HIV prevalence or non-participation is very high or very low, and provides a practical solution to account for both sampling and parameter uncertainty in the estimation of confidence intervals. The wide confidence intervals estimated in an example with high HIV prevalence indicate that it is difficult to correct statistically for the bias that may occur when a large proportion of people refuse to test.

A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses

ABSTRACT Estimates of HIV prevalence are important for policy to establish the health status of a country’s population and to evaluate the effectiveness of population-based interventions and campaigns. However, participation rates in testing for surveillance conducted as part of household surveys, on which many of these estimates are based, can be low. HIV positive individuals may be less likely to participate because they fear disclosure, in which case estimates obtained using conventional approaches to deal with missing data, such as imputation-based methods, will be biased. We develop a Heckman-type simultaneous equation approach that accounts for nonignorable selection, but unlike previous implementations, allows for spatial dependence and does not impose a homogenous selection process on all respondents. In addition, our framework addresses the issue of separation, where for instance some factors are severely unbalanced and highly predictive of the response, which would ordinarily prevent model convergence. Estimation is carried out within a penalized likelihood framework where smoothing is achieved using a parameterization of the smoothing criterion, which makes estimation more stable and efficient. We provide the software for straightforward implementation of the proposed approach, and apply our methodology to estimating national and sub-national HIV prevalence in Swaziland, Zimbabwe, and Zambia. Supplementary materials for this article are available online.

On the assumption of bivariate normality in selection models: a Copula approach applied to estimating HIV prevalence.

Background: Heckman-type selection models have been used to control HIV prevalence estimates for selection bias when participation in HIV testing and HIV status are associated after controlling for observed variables. These models typically rely on the strong assumption that the error terms in the participation and the outcome equations that comprise the model are distributed as bivariate normal. Methods: We introduce a novel approach for relaxing the bivariate normality assumption in selection models using copula functions. We apply this method to estimating HIV prevalence and new confidence intervals (CI) in the 2007 Zambia Demographic and Health Survey (DHS) by using interviewer identity as the selection variable that predicts participation (consent to test) but not the outcome (HIV status). Results: We show in a simulation study that selection models can generate biased results when the bivariate normality assumption is violated. In the 2007 Zambia DHS, HIV prevalence estimates are similar irrespective of the structure of the association assumed between participation and outcome. For men, we estimate a population HIV prevalence of 21% (95% CI = 16%–25%) compared with 12% (11%–13%) among those who consented to be tested; for women, the corresponding figures are 19% (13%–24%) and 16% (15%–17%). Conclusions: Copula approaches to Heckman-type selection models are a useful addition to the methodological toolkit of HIV epidemiology and of epidemiology in general. We develop the use of this approach to systematically evaluate the robustness of HIV prevalence estimates based on selection models, both empirically and in a simulation study.

Vaccination and All-Cause Child Mortality From 1985 to 2011: Global Evidence From the Demographic and Health Surveys

Based on models with calibrated parameters for infection, case fatality rates, and vaccine efficacy, basic childhood vaccinations have been estimated to be highly cost effective. We estimated the association of vaccination with mortality directly from survey data. Using 149 cross-sectional Demographic and Health Surveys, we determined the relationship between vaccination coverage and the probability of dying between birth and 5 years of age at the survey cluster level. Our data included approximately 1 million children in 68,490 clusters from 62 countries. We considered the childhood measles, bacillus Calmette-Guérin, diphtheria-pertussis-tetanus, polio, and maternal tetanus vaccinations. Using modified Poisson regression to estimate the relative risk of child mortality in each cluster, we also adjusted for selection bias that resulted from the vaccination status of dead children not being reported. Childhood vaccination, and in particular measles and tetanus vaccination, is associated with substantial reductions in childhood mortality. We estimated that children in clusters with complete vaccination coverage have a relative risk of mortality that is 0.73 (95% confidence interval: 0.68, 0.77) times that of children in a cluster with no vaccinations. Although widely used, basic vaccines still have coverage rates well below 100% in many countries, and our results emphasize the effectiveness of increasing coverage rates in order to reduce child mortality.

A review of the evidence linking child stunting to economic outcomes

Abstract Background To understand the full impact of stunting in childhood it is important to consider the long-run effects of undernutrition on the outcomes of adults who were affected in early life. Focusing on the costs of stunting provides a means of evaluating the economic case for investing in childhood nutrition. Methods We review the literature on the association between stunting and undernutrition in childhood and economic outcomes in adulthood. At the national level, we also evaluate the evidence linking stunting to economic growth. Throughout, we consider randomized controlled trials (RCTs), quasi-experimental approaches and observational studies. Results Long-run evaluations of two randomized nutrition interventions indicate substantial returns to the programmes (a 25% and 46% increase in wages for those affected as children, respectively). Cost-benefit analyses of nutrition interventions using calibrated return estimates report a median return of 17.9:1 per child. Assessing the wage premium associated with adult height, we find that a 1-cm increase in stature is associated with a 4% increase in wages for men and a 6% increase in wages for women in our preferred set of studies which attempt to address unobserved confounding and measurement error. In contrast, the evidence on the association between economic growth and stunting is mixed. Conclusions Countries with high rates of stunting, such as those in South Asia and sub-Saharan Africa, should scale up policies and programmes aiming to reduce child undernutrition as cost-beneficial investments that expand the economic opportunities of their children, better allowing them and their countries to reach their full potential. However, economic growth as a policy will only be effective at reducing the prevalence of stunting when increases in national income are directed at improving the diets of children, addressing gender inequalities and strengthening the status of women, improving sanitation and reducing poverty and inequities.

Culture Positivity of CVCs Used for TPN: Investigation of an Association with Catheter-Related Infection and Comparison of Causative Organisms between ICU and Non-ICU CVCs

A relationship between central venous catheter (CVC) tip colonisation and catheter-related blood-stream infection (CRBSI) has been suggested. We examined culture positivity of CVC tips (colonised and infected CVCs) in a total parenteral nutrition (TPN) population. Our aims were to define the relationship between culture positivity and CRBSI, and to compare causative organisms between culture positive and CRBSI CVCS, and between ward and ICU CVCs. All patients receiving TPN via non-tunnelled CVCs during the study (1997–2009) were included. All CVC tips were analysed. Data were collated contemporaneously. A TPN audit committee determined whether CVC tip culture positivity reflected colonisation/CRBSI using CDC criteria. 1,392 patients received TPN via 2,565 CVCs over 15,397 CVC days. 25.4% of CVCs tips were culture positive, of these 32% developed CRBSI. There was a nonsignificant trend of higher Gram negative Bacilli isolation in ICU CVCs (P = 0.1), ward CVCs were associated with higher rates of staphylococcal isolation (P = 0.01). A similar pattern of organisms were cultured from CRBSI and culture positive CVCs. The consistent relationship between CRBSI and culture positive CVCs, and similar pattern of causative organisms further supports an aetiological relationship between culture positive CVC tips and CRBSI, supporting the contention that CVC culture-positivity may be a useful surrogate marker for CRBSI rates.

Do Gifts Increase Consent to Home-based HIV Testing? A Difference-in-Differences Study in Rural KwaZulu-Natal, South Africa

Abstract Background: Despite the importance of HIV testing for controlling the HIV epidemic, testing rates remain low. Efforts to scale up testing coverage and frequency in hard-to-reach and at-risk populations commonly focus on home-based HIV testing. This study evaluates the effect of a gift (a US

Education, gender, and state-level disparities in the health of older Indians: Evidence from biomarker data

5 food voucher for families) on consent rates for home-based HIV testing. Methods: We use data on 18u2009478 individuals (6u2009418 men and 12u2009060 women) who were successfully contacted to participate in the 2009 and 2010 population-based HIV surveillance carried out by the Wellcome Trusts Africa Health Research Institute in rural KwaZulu-Natal, South Africa. Of 18u2009478 potential participants contacted in both years, 35% (6u2009518) consented to test in 2009, and 41% (7u2009533) consented to test in 2010. Our quasi-experimental difference-in-differences approach controls for unobserved confounding in estimating the causal effect of the intervention on HIV-testing consent rates. Results: Allocation of the gift to a family in 2010 increased the probability of family members consenting to test in the same year by 25 percentage points [95% confidence interval (CI) 21–30 percentage points; Pu2009<u20090.001]. The intervention effect persisted, slightly attenuated, in the year following the intervention (2011). Conclusions: In HIV hyperendemic settings, a gift can be highly effective at increasing consent rates for home-based HIV testing. Given the importance of HIV testing for treatment uptake and individual health, as well as for HIV treatment-as-prevention strategies and for monitoring the population impact of the HIV response, gifts should be considered as a supportive intervention for HIV-testing initiatives where consent rates have been low.