The infant health effects of starting universal child benefits in pregnancy: Evidence from England and Wales

Child benefits are typically paid from birth. This paper asks whether starting universal child benefits in pregnancy leads to improvements in infant health. Leveraging administrative birth registry and hospital microdata from England and Wales, I study the effects of the Health in Pregnancy Grant, a universal conditional cash transfer equivalent to three months of child benefit (190 GBP) as a lump sum to pregnant mothers from 2009 to 2011. I exploit quasi-experimental variation in eligibility with a regression discontinuity design in the date of birth of the baby. I find that the policy increased birth weight by 8–12 grams on average, reduced low birth weight ($<$2500 g) by 3-6 percent and decreased prematurity by 9–11 percent. Younger mothers, particularly those living in deprived areas, benefit the most. I present evidence that the mechanisms are unlikely to be antenatal care, nutrition or smoking, with reductions in stress remaining a possible explanation.     

COVID-19 Gender Disparities and Mitigation Recommendations: A Narrative Review

The coronavirus disease 2019 (COVID-19) pandemic has rapidly created widespread impacts on global health and the economy. Data suggest that women are less susceptible to severe illness. However, sex-disaggregated data are incomplete, leaving room for misinterpretation, and focusing only on biologic sex underestimates the gendered impact of the pandemic on women. This narrative review summarizes what is known about gender disparities during the COVID-19 pandemic and the economic, domestic, and health burdens along with overlapping vulnerabilities related to the pandemic. In addition, this review outlines recommended strategies that advocacy groups, community leaders, and policymakers should implement to mitigate the widening gender disparities related to COVID-19.     

The impact of the housing status on clinical outcomes and health care utilization among individuals living with HIV

ABSTRACT

The lack of stable housing can impair access and continuity of care for patients living with human immunodeficiency virus (HIV). This study investigated the relationship between housing status assessed at multiple time points and several core HIV-related outcomes within the same group of HIV patients experiencing homelessness. Patients with consistently stable housing (CSH) during the year were compared to patients who lacked CSH (non-CSH group). The study outcomes included HIV viral load (VL), CD4 counts, and health care utilization. Multivariable and propensity weighted analyses were used to assess outcomes adjusting for potential group differences. Of 208 patients, 88 (42%) had CSH and 120 (58%) were non-CSH. Patients with CSH had significantly higher proportion of VL suppression and higher mean CD4 counts. The frequency of nurse visits in the CSH group was less than a half of that in the non-CSH group. Patients with CSH were less likely to be admitted to the medical respite facility, and if admitted, their length of stay was about a half of that for the non-CSH group. Our study findings show that patients with CSH had significantly better HIV virologic control and immune status as well as improved health care utilization.     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

The success of Australia’s ‘No Jab,No Pay’ policy at a local level; retrospective clinical audit of a single medical practice assessing incidence of catch-up vaccinations

Vaccination is a vital health care initiative to prevent individual and population infection. To increase vaccination rates the federal government implemented the ‘No Jab, No Pay’ policy, where eligibility for several government benefits required children to be fully vaccinated by removing ‘conscientious objections’ and expanding the age range of children whose families receive benefits. This study assesses the impact of this policy at a local area within a single medical practice community in NSW, Australia. A retrospective clinical audit was performed between 2012 and 2017 on a single general practice's vaccination records for children ≤19 years. Catch-up vaccinations were assessed based on age at vaccination. Incidence of catch-up vaccinations was assessed for each of four years before and two years after the implementation of the ‘No Jab, No Pay’ policy in January 2016, along with the age of children and vaccination(s) given. Catch-up vaccinations were assessed temporally either side of implementation of ‘No Jab, No Pay’. Comparing the average annual vaccination catch-up incidence rate of 6.2% pre-implementation (2012–2015), there was an increase to 9.2% in 2016 (p < .001) and 7.8% in 2017 (p = .027). Secondary outcome measurement of catch-up vaccination incidence rates before (2012–2015) and after (2016–2017) ‘No Jab, No Pay’ implementation showed statistically significant increases for children aged 8–11 years (3.2%–5.6%, p = .038), 12–15 years (7.5%–14.7%, p < .001) and 16–19 years (3.3%–10.2%, p < .001) along with a statistically significant reduction in children aged 1–3 years (11.4%–6.2%, p = .015). Also, catch-up rates for DTPa significantly increased after program implementation. This study demonstrates that the Australian federal government vaccination policy ‘No Jab, No Pay’ was coincident with an increase in catch-up vaccinations within a rural NSW community served by one medical practice, especially for older children.