Attributable is Preventable: Corrected and revised estimates of population attributable fraction of TB related to undernutrition in 30 high TB burden countries

IntroductionThe Global TB Report 2020 estimated the population attributable fractions (PAF) for the major risk factors of TB. Undernourishment emerged as the leading risk factor accounting for 19% of the cases. The WHO however used the terms undernourishment and undernutrition interchangeably in its computation of PAF. Undernourishment is an indirect model derived estimate of decreased per capita energy availability, while undernutrition is defined by direct anthropometric measurements of nutritional status.MethodsWe re-estimated the PAF of undernutrition (instead of undernourishment) in 30 high TB burden countries, using the prevalence of undernutrition (age standardized estimate of BMI < 18.5 kg/m2 in adults for both sexes), and the relative risk (RR) of 3.2. Further, we revised PAF estimates of undernutrition with an RR of 4.49, in light of recent evidence.FindingsTwenty four percent of TB in high burden countries is attributable to undernutrition. The PAF of undernutrition was highest in Asian countries, unlike the PAF of undernourishment that was highest in Africa. The corrected estimate led up to 65% increase in number of cases attributable to undernutrition in Asian countries. More than one-third to nearly half of TB cases in India could be attributable to undernutrition.InterpretationEstimation of the PAF of TB related to undernutrition is methodologically valid and operationally relevant, rather than PAF related to undernourishment. Addressing undernutrition, the leading driver of TB in high TB burden countries (especially Asia) could enable achievement of END TB milestones of TB incidence for 2025.

Best Estimate Selection Bias in the Value of a Statistical Life

Selection of the best estimates of economic parameters frequently relies on the “best estimates” or a meta-analysis of the “best set” of parameter estimates from the literature. Using an all-set dataset consisting of all reported estimates of the value of a statistical life (VSL) as well as a best-set sample of the best estimates from these studies, this article estimates statistically significant publication selection biases in each case. Biases are much greater for the best-set sample, as one might expect, given the subjective nature of the best-set selection process. For the all-set sample, the mean bias-corrected estimate of the VSL for the preferred specification is $8.1 million for the whole sample and $11.4 million based on the CFOI data, while for the best-set results, the whole sample value is $3.5 million, and the CFOI data estimate is $4.4 million. Previous estimates of huge publication selection biases in the VSL estimates are attributable to these studies’ reliance on best-set samples.

Employment Outcomes of Work for the Dole: An Analysis of the DEWRSB Net Impact Report

Since the data necessary to make a formal quantitative analysis of Work for the Dole employment outcomes is not available to researchers who are independent of Commonwealth Government Departments, this article examines the (then) Department of Employment, Workplace Relations and Small Business (DEWRSB) net impact report, finding in it a number of weaknesses. The combined effect of these is to inflate the estimated value for net impact but a corrected estimate is still higher than many consider likely. Any figure for the net impact estimate of an Australian labour market program can only be a broad indicator. This article argues that in the case of Work for the Dole the net impact is definitely positive and by more than a trivial amount.