The relative effects of non-pharmaceutical interventions on wave one Covid-19 mortality: natural experiment in 130 countries.

BACKGROUND: Non-pharmaceutical interventions have been implemented around the world to control Covid-19 transmission. Their general effect on reducing virus transmission is proven, but they can also be negative to mental health and economies, and transmission behaviours can also change voluntarily, without mandated interventions. Their relative impact on Covid-19 attributed mortality, enabling policy selection for maximal benefit with minimal disruption, is not well established due to a lack of definitive methods. METHODS: We examined variations in timing and strictness of nine non-pharmaceutical interventions implemented in 130 countries and recorded by the Oxford COVID-19 Government Response Tracker (OxCGRT): 1) School closing; 2) Workplace closing; 3) Cancelled public events; 4) Restrictions on gatherings; 5) Closing public transport; 6) Stay at home requirements ('Lockdown'); 7) Restrictions on internal movement; 8) International travel controls; 9) Public information campaigns. We used two time periods in the first wave of Covid-19, chosen to limit reverse causality, and fixed country policies to those implemented: i) prior to first Covid-19 death (when policymakers could not possibly be reacting to deaths in their own country); and, ii) 14-days-post first Covid-19 death (when deaths were still low, so reactive policymaking still likely to be minimal). We then examined associations with daily deaths per million in each subsequent 24-day period, which could only be affected by the intervention period, using linear and non-linear multivariable regression models. This method, therefore, exploited the known biological lag between virus transmission (which is what the policies can affect) and mortality for statistical inference. RESULTS: After adjusting, earlier and stricter school (- 1.23 daily deaths per million, 95% CI - 2.20 to - 0.27) and workplace closures (- 0.26, 95% CI - 0.46 to - 0.05) were associated with lower Covid-19 mortality rates. Other interventions were not significantly associated with differences in mortality rates across countries. Findings were robust across multiple statistical approaches. CONCLUSIONS: Focusing on 'compulsory', particularly school closing, not 'voluntary' reduction of social interactions with mandated interventions appears to have been the most effective strategy to mitigate early, wave one, Covid-19 mortality. Within 'compulsory' settings, such as schools and workplaces, less damaging interventions than closing might also be considered in future waves/epidemics.

Ethnic inequalities in health-related quality of life among older adults in England: secondary analysis of a national cross-sectional survey.

BACKGROUND: The population of older adults (ie, those aged ≥55 years) in England is becoming increasingly ethnically diverse. Previous reports indicate that ethnic inequalities in health exist among older adults, but information is limited by the paucity of data from small minority ethnic groups. This study aimed to analyse inequalities in health-related quality of life (HRQoL) and five determinants of health in older adults across all ethnic groups in England. METHODS: In this cross-sectional study, we analysed data from five waves (July 1, 2014, to April 7, 2017) of the nationally representative English General Practice Patient Survey (GPPS). Study participants were adults aged 55 years or older who were registered with general practices in England. We used regression models (age-adjusted and stratified by gender) to estimate the association between ethnicity and HRQoL, measured by use of the EQ-5D-5L index and its domains (mobility, self-care, usual activities, pain or discomfort, and anxiety or depression). We also estimated associations between ethnicity and five determinants of health (presence of long-term conditions or multimorbidity, experience of primary care, degree of support from local services, patient self-confidence in managing own health, and degree of area-level social deprivation). We examined robustness to differential handling of missing data, alternative EQ-5D-5L value sets, and differences in area-level social deprivation. FINDINGS: There were 1 416 793 GPPS respondents aged 55 years and older. 1 394 361 (98·4%) respondents had complete data on ethnicity and gender and were included in our analysis. Of these, 152 710 (11·0%) self-identified as belonging to minority ethnic groups. HRQoL was worse for men or women, or both, in 15 (88·2%) of 17 minority ethnic groups than the White British ethnic group. In both men and women, inequalities were widest for Gypsy or Irish Traveller (linear regression coefficient -0·192 [95% CI -0·318 to -0·066] in men; -0·264 [-0·354 to -0·173] in women), Bangladeshi (-0·111 [-0·136 to -0·087] in men; -0·209 [-0·235 to -0·184] in women), Pakistani (-0·084 [-0·096 to -0·073] in men; -0·206 [-0·219 to -0·193] in women), and Arab (-0·061 [-0·086 to -0·035] in men; -0·145 [-0·180 to -0·110] in women) ethnic groups, with magnitudes generally greater for women than men. Differentials tended to be widest for the self-care EQ-5D-5L domain. Ethnic inequalities in HRQoL were accompanied by increased prevalence of long-term conditions or multimorbidity, poor experiences of primary care, insufficient support from local services, low patient self-confidence in managing their own health, and high area-level social deprivation, compared with the White British group. INTERPRETATION: We found evidence of wide ethnic inequalities in HRQoL and five determinants of health for older adults in England. Outcomes varied between minority ethnic groups, highlighting heterogeneity in the direction and magnitude of associations. We recommend further research to understand the drivers of inequalities, together with policy changes to improve equity of socioeconomic opportunity and access to services for older adults from minority ethnic groups. FUNDING: University of Manchester and National Institute for Health Research.

Going beyond the mean in examining relationships of adolescent non-cognitive skills with health-related quality of life and biomarkers in later-life.

Several studies have established associations between early-life non-cognitive skills and later-life health and health behaviours. However, no study addresses the more important policy concern about how this relationship varies along the health distribution. We use unconditional quantile regression to analyse the effects of adolescent non-cognitive skills across the distributions of the health-related quality of life at age 50 and biomarkers at age 45 years. We examine the effects of measures of conscientiousness, agreeableness and neuroticism recorded at age 16 for 3585 individuals from the National Child Development Study. Adolescent conscientiousness is positively associated with ability to cope with stress and negatively associated with risk of cardiovascular disease in middle-age. Adolescent agreeableness is associated with higher health-related quality of life and lower physiological 'wear and tear', but negatively associated with ability to cope with stress in middle-age. Adolescent neuroticism is associated with lower health-related quality of life, higher physiological 'wear and tear', and a higher risk of cardiovascular disease in middle-age. All of these associations are stronger at the lower end of the health distribution except for the cardiovascular risk biomarkers. These associations are robust to correcting for attrition using inverse probability weighting and consistent with causal bounds assuming proportional selection on observables and unobservables. They suggest policies that improve non-cognitive skills in adolescence could offer most long-term health benefit to those with the poorest health.

A Comparison of the EQ-5D-3L and EQ-5D-5L.

INTRODUCTION: The EQ-5D-3L (3L) and EQ-5D-5L (5L) are both frequently used measures of health status. Previous studies have found the EQ-5D-5L to have superior measurement properties but no study has compared the two measures in a large general population survey using matched respondents. METHODS: Using data from the GP Patient Survey, coarsened exact matching was used to match individuals completing the 3L in 2011 with those completing the 5L in 2012. Measurement properties were assessed for a general population and multimorbid population (chronic conditions ≥ 2), with ceiling effects, informativity and distribution of response compared. Changes in the direction of response, as well as the impact on utility distributions, were quantified. RESULTS: Matching resulted in a cohort of 1,023,218 respondents (2011: 511,609; 2012: 511,609) for analysis. Ceiling effects for the 5L were lower than the 3L (43.8% vs. 54.4%). The 5L had improved informativity and broader spread of responses than the 3L (5L top 50 profiles: 77.4% vs. 3L: 98.8%). Overall, there was an upwards shift in utility values for the 5L versus the 3L as respondents using the 5L reported ill health more frequently but with less severity. Measurement improvements and effects on utility values were more pronounced for the multimorbid population. CONCLUSION: The 5L had superior measurement properties than the 3L and should be preferred in general population surveys and for use in individuals with multimorbidity. At increasing levels of morbidity, the 5L is currently associated with higher utility values than the 3L.

Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units.

This paper examines the synthetic control method in contrast to commonly used difference-in-differences (DiD) estimation, in the context of a re-evaluation of a pay-for-performance (P4P) initiative, the Advancing Quality scheme. The synthetic control method aims to estimate treatment effects by constructing a weighted combination of control units, which represents what the treated group would have experienced in the absence of receiving the treatment. While DiD estimation assumes that the effects of unobserved confounders are constant over time, the synthetic control method allows for these effects to change over time, by re-weighting the control group so that it has similar pre-intervention characteristics to the treated group. We extend the synthetic control approach to a setting of evaluation of a health policy where there are multiple treated units. We re-analyse a recent study evaluating the effects of a hospital P4P scheme on risk-adjusted hospital mortality. In contrast to the original DiD analysis, the synthetic control method reports that, for the incentivised conditions, the P4P scheme did not significantly reduce mortality and that there is a statistically significant increase in mortality for non-incentivised conditions. This result was robust to alternative specifications of the synthetic control method. © 2015 The Authors. Health Economics published by John Wiley & Sons Ltd.