Using administrative data to evaluate national policy impacts on child and maternal health: a research framework from the Maternal and Child Health Network (MatCHNet)

Reducing health inequalities by addressing the social circumstances in which children are conceived and raised is a societal priority. Early interventions are key to improving outcomes in childhood and long-term into adulthood. Across the UK nations, there is strong political commitment to invest in the early years. National policy interventions aim to tackle health inequalities and deliver health equity for all children. Evidence to determine the effectiveness of socio-structural policies on child health outcomes is especially pressing given the current social and economic challenges facing policy-makers and families with children. As an alternative to clinical trials or evaluating local interventions, we propose a research framework that supports evaluating the impact of whole country policies on child health outcomes. Three key research challenges must be addressed to enable such evaluations and improve policy for child health: (1) policy prioritisation, (2) identification of comparable data and (3) application of robust methods.

To what extent does income explain the effect of unemployment on mental health? Mediation analysis in the UK Household Longitudinal Study

BACKGROUND

Employment and income are important determinants of mental health (MH), but the extent that unemployment effects are mediated by reduced income is unclear. We estimated the total effect (TE) of unemployment on MH and the controlled direct effect (CDE) not acting via income.

METHODS

We included adults 25-64 years from nine waves of the UK Household Longitudinal Study (n = 45 497/obs = 202 297). Unemployment was defined as not being in paid employment; common mental disorder (CMD) was defined as General Health Questionnaire-12 score ≥4. We conducted causal mediation analysis using double-robust marginal structural modelling, estimating odds ratios (OR) and absolute differences for effects of unemployment on CMD in the same year, before (TE) and after (CDE) blocking the income pathway. We calculated percentage mediation by income, with bootstrapped standard errors.

RESULTS

The TE of unemployment on CMD risk was OR 1.66 (95% CI 1.57-1.76), with 7.09% (6.21-7.97) absolute difference in prevalence; equivalent CDEs were OR 1.55 (1.46-1.66) and 6.08% (5.13-7.03). Income mediated 14.22% (8.04-20.40) of the TE. Percentage mediation was higher for job losses [15.10% (6.81-23.39)] than gains [8.77% (0.36-17.19)]; it was lowest for those 25-40 years [7.99% (-2.57 to 18.51)] and in poverty [2.63% (-2.22 to 7.49)].

CONCLUSIONS

A high proportion of the short-term effect of unemployment on MH is not explained by income, particularly for younger people and those in poverty. Population attributable fractions suggested 16.49% of CMD burden was due to unemployment, with 13.90% directly attributable to job loss rather than resultant income changes. Similar analytical approaches could explore how this differs across contexts, by other factors, and consider longer-term effects.

Medication-related problems in critical care survivors: a systematic review

OBJECTIVES

There are numerous, often single centre discussions of assorted medication-related problems after hospital discharge in patients who survive critical illness. However, there has been little synthesis of the incidence of medication-related problems, the classes of medications most often studied, the factors that are associated with greater patient risk of such problems or interventions that can prevent them.

METHODS

We undertook a systematic review to understand medication management and medication problems in critical care survivors in the hospital discharge period. We searched OVID Medline, Embase, PsychINFO, CINAHL and the Cochrane database (2001-2022). Two reviewers independently screened publications to identify studies that examined medication management at hospital discharge or thereafter in critical care survivors. We included randomised and non-randomised studies. We extracted data independently and in duplicate. Data extracted included medication type, medication-related problems and frequency of medication issues, alongside demographics such as study setting. Cohort study quality was assessed using the Newcastle Ottowa Score checklist. Data were analysed across medication categories.

RESULTS

The database search initially retrieved 1180 studies; following the removal of duplicates and studies which did not fit the inclusion criteria, 47 papers were included. The quality of studies included varied. The outcomes measured and the timepoints at which data were captured also varied, which impacted the quality of data synthesis. Across the studies included, we found that as many as 80% of critically ill patients experienced medication-related problems in the posthospital discharge period. These issues included inappropriate continuation of newly prescribed drugs such as antipsychotics, gastrointestinal prophylaxis and analgesic medications, as well as inappropriate discontinuation of chronic disease medications, such as secondary prevention cardiac drugs.

CONCLUSIONS

Following critical illness, a high proportion of patients experience problems with their medications. These changes were present across multiple health systems. Further research is required to understand optimal medicine management across the full recovery trajectory of critical illness.

PROSPERO REGISTRATION NUMBER

CRD42021255975.

Identifying opportunities for upstream evaluations relevant to child and maternal health: a UK policy-mapping review

OBJECTIVE

Interventions to tackle the social determinants of health can improve outcomes during pregnancy and early childhood, leading to better health across the life course. Variation in content, timing and implementation of policies across the 4 UK nations allows for evaluation. We conducted a policy-mapping review (1981-2021) to identify relevant UK early years policies across the social determinants of health framework, and determine suitable candidates for evaluation using administrative data.

METHODS

We used open keyword and category searches of UK and devolved Government websites, and hand searched policy reviews. Policies were rated and included using five criteria: (1) Potential for policy to affect maternal and child health outcomes; (2) Implementation variation across the UK; (3) Population reach and expected effect size; (4) Ability to identify exposed/eligible group in administrative data; (5) Potential to affect health inequalities. An expert consensus workshop determined a final shortlist.

RESULTS

336 policies and 306 strategy documents were identified. Policies were mainly excluded due to criteria 2-4, leaving 88. The consensus workshop identified three policy areas as suitable candidates for natural experiment evaluation using administrative data: pregnancy grants, early years education and childcare, and Universal Credit.

CONCLUSION

Our comprehensive policy review identifies valuable opportunities to evaluate sociostructural impacts on mother and child outcomes. However, many potentially impactful policies were excluded. This may lead to the inverse evidence law, where there is least evidence for policies believed to be most effective. This could be ameliorated by better access to administrative data, staged implementation of future policies or alternative evaluation methods.

Subsidised housing and diabetes mortality: a retrospective cohort study of 10 million low-income adults in Brazil

INTRODUCTION

Housing-related factors can be predictors of health, including of diabetes outcomes. We analysed the association between subsidised housing residency and diabetes mortality among a large cohort of low-income adults in Brazil.

RESEARCH DESIGN AND METHODS

A cohort of 9 961 271 low-income adults, observed from January 2010 to December 2015, was created from Brazilian administrative records of social programmes and death certificates. We analysed the association between subsidised housing residency and time to diabetes mortality using a Cox model with inverse probability of treatment weighting and regression adjustment. We assessed inequalities in this association by groups of municipality Human Development Index. Diabetes mortality included diabetes both as the underlying or a contributory cause of death.

RESULTS

At baseline, the mean age of the cohort was 40.3 years (SD 15.6 years), with a majority of women (58.4%). During 29 238 920 person-years of follow-up, there were 18 775 deaths with diabetes as the underlying or a contributory cause. 340 683 participants (3.4% of the cohort) received subsidised housing. Subsidised housing residents had a higher hazard of diabetes mortality compared with non-residents (HR 1.17; 95% CI 1.05 to 1.31). The magnitude of this association was more pronounced among participants living in municipalities with lower Human Development Index (HR 1.30; 95% CI 1.04 to 1.62).

CONCLUSIONS

Subsidised housing residents had a greater risk of diabetes mortality, particularly those living in low socioeconomic status municipalities. This finding suggests the need to intensify diabetes prevention and control actions and prompt treatment of the diabetes complications among subsidised housing residents, particularly among those living in low socioeconomic status municipalities.

Effects of poverty on mental health in the UK working-age population: causal analyses of the UK Household Longitudinal Study

BACKGROUND

Addressing poverty through taxation or welfare policies is likely important for public mental health; however, few studies assess poverty's effects using causal epidemiology. We estimated the effect of poverty on mental health.

METHODS

We used data on working-age adults (25-64 years) from nine waves of the UK Household Longitudinal Survey (2009-19; n = 45 497/observations = 202 207 following multiple imputation). We defined poverty as a household equivalized income <60% median, and the outcome likely common mental disorder (CMD) as a General Health Questionnaire-12 score ≥4. We used double-robust marginal structural modelling with inverse probability of treatment weights to generate absolute and relative effects. Supplementary analyses separated transitions into/out of poverty, and stratified by gender, education, and age. We quantified potential impact through population attributable fractions (PAFs) with bootstrapped standard errors.

RESULTS

Good balance of confounders was achieved between exposure groups, with 45 830 observations (22.65%) reporting poverty. The absolute effect of poverty on CMD prevalence was 2.15% [%-point change; 95% confidence interval (CI) 1.45, 2.84]; prevalence in those unexposed was 20.59% (95% CI 20.29%, 20.88%), and the odds ratio was 1.17 (95% CI 1.12, 1.24). There was a larger absolute effect for transitions into poverty [2.46% (95% CI 1.56, 3.36)] than transitions out of poverty [-1.49% (95% CI -2.46, -0.53)]. Effects were also slightly larger in women than men [2.34% (95% CI 1.41, 3.26) versus 1.73% (95% CI 0.72, 2.74)]. The PAF for moving into poverty was 6.34% (95% CI 4.23, 8.45).

CONCLUSIONS

PAFs derived from our causal estimates suggest moves into poverty account for just over 6% of the burden of CMD in the UK working-age population, with larger effects in women.

How much of the unemployment effect on mental health is due to income? Mediation analysis in UK data

Background

Employment and income are important determinants of mental health (MH), but the extent to which unemployment effects are mediated by reduced income is unclear. We estimated the total effect (TE) of unemployment on MH and the controlled direct effect (CDE) not acting via income.

Methods

We studied adults 25-64y from nine waves of the representative UK Household Longitudinal Study (n = 45,497/obs=202,297). Unemployment was defined as not being in paid employment; common mental disorder (CMD) was defined as a General Health Questionnaire-12 score ≥4. We conducted causal mediation analysis using inverse probability of treatment weights to estimate odds ratios (OR) and absolute differences for the effects of unemployment on CMD as measured in the same sweep, before (TE) and after (CDE) blocking the income pathway. The percentage mediated by income was 100*(TE-CDE)/TE, with standard errors calculated via bootstrapping. Multiple imputation addressed missingness.

Results

The TE of unemployment on short-term CMD risk was OR: 1.66 (95% CI 1.57-1.76), with 7.09% (6.21-7.97) absolute difference in prevalence; equivalent CDEs were OR 1.55 (1.46-1.66) and 6.08% (5.13-7.03). Income mediated 14.22% (8.04-20.40) of the TE. Percentage mediation was higher for job losses (15.10% [6.81-23.39]) than job gains (8.77% [0.36-17.19]). Mediation by income was lowest for those aged 25-40y (7.99% [-2.57, 18.51]) and those in poverty (2.63% [-2.22, 7.49]).

Conclusions

In the UK, a high proportion of the short-term effect of unemployment on MH is not explained by income, particularly for those who are younger or already living in poverty. Population attributable fractions suggested 16.5% of CMD burden was due to unemployment, with 13.9% directly attributable to job loss rather than resultant income changes. Further research is needed across different European countries to determine how different welfare regimes might moderate these effects, and to investigate longer-term effects.

Key messages

• Unemployment has a clear detrimental effect on MH in the short-term.

• Only a small proportion of this effect appears to be mediated by income.

Differentials in death count records by databases in Brazil in 2010

OBJECTIVE

To compare the death counts from three sources of information on mortality available in Brazil in 2010, the Mortality Information System (SIM - Sistema de Informações sobre Mortalidade ), Civil Registration Statistic System (RC - Sistema de Estatísticas de Resgistro Civil ), and the 2010 Demographic Census at various geographical levels, and to confirm the association between municipal socioeconomic characteristics and the source which showed the highest death count.

METHODS

This is a descriptive and comparative study of raw data on deaths in the SIM, RC and 2010 Census databases, the latter held in Brazilian states and municipalities between August 2009 and July 2010. The percentage of municipalities was confirmed by the database showing the highest death count. The association between the source of the highest death count and socioeconomic indicators - the Índice de Privação Brasileiro (IBP - Brazilian Deprivation Index) and Índice de Desenvolvimento Humano Municipal (IHDM - Municipal Human Development Index) - was performed by bivariate choropleth and Moran Local Index of Spatial Association (LISA) cluster maps.

RESULTS

Confirmed that the SIM is the database with the highest number of deaths counted for all Brazilian macroregions, except the North, in which the highest coverage was from the 2010 Census. Based on the indicators proposed, in general, the Census showed a higher coverage of deaths than the SIM and the RC in the most deprived (highest IBP values) and less developed municipalities (lowest IDHM values) in the country.

CONCLUSION

The results highlight regional inequalities in how the databases chosen for this study cover death records, and the importance of maintaining the issue of mortality on the basic census questionnaire.

Mortality inequalities measured by socioeconomic indicators in Brazil: a scoping review

OBJECTIVE

Summarize the literature on the relationship between composite socioeconomic indicators and mortality in different geographical areas of Brazil.

METHODS

This scoping review included articles published between January 1, 2000, and August 31, 2020, retrieved by means of a bibliographic search carried out in the Medline, Scopus, Web of Science, and Lilacs databases. Studies reporting on the association between composite socioeconomic indicators and all-cause, or specific cause of death in any age group in different geographical areas were selected. The review summarized the measures constructed, their associations with the outcomes, and potential study limitations.

RESULTS

Of the 77 full texts that met the inclusion criteria, the study reviewed 24. The area level of composite socioeconomic indicators analyzed comprised municipalities (n = 6), districts (n = 5), census tracts (n = 4), state (n = 2), country (n = 2), and other areas (n = 5). Six studies used composite socioeconomic indicators such as the Human Development Index, Gross Domestic Product, and the Gini Index; the remaining 18 papers created their own socioeconomic measures based on sociodemographic and health indicators. Socioeconomic status was inversely associated with higher rates of all-cause mortality, external cause mortality, suicide, homicide, fetal and infant mortality, respiratory and circulatory diseases, stroke, infectious and parasitic diseases, malnutrition, gastroenteritis, and oropharyngeal cancer. Higher mortality rates due to colorectal cancer, leukemia, a general group of neoplasms, traffic accident, and suicide, in turn, were observed in less deprived areas and/or those with more significant socioeconomic development. Underreporting of death and differences in mortality coverage in Brazilian areas were cited as the main limitation.

CONCLUSIONS

Studies analyzed mortality inequalities in different geographical areas by means of composite socioeconomic indicators, showing that the association directions vary according to the mortality outcome. But studies on all-cause mortality and at the census tract level remain scarce. The results may guide the development of new composite socioeconomic indicators for use in mortality inequality analysis.

Impact of Brazil's Bolsa Família Programme on cardiovascular and all-cause mortality: a natural experiment study using the 100 Million Brazilian Cohort

BACKGROUND

Cardiovascular disease (CVD) has a disproportionate effect on mortality among the poorest people. We assessed the impact on CVD and all-cause mortality of the world's largest conditional cash transfer, Brazil's Bolsa Família Programme (BFP).

METHODS

We linked administrative data from the 100 Million Brazilian Cohort with BFP receipt and national mortality data. We followed individuals who applied for BFP between 1 January 2011 and 31 December 2015, until 31 December 2015. We used marginal structural models to estimate the effect of BFP on all-age and premature (30-69 years) CVD and all-cause mortality. We conducted stratified analyses by levels of material deprivation and access to healthcare. We checked the robustness of our findings by restricting the analysis to municipalities with better mortality data and by using alternative statistical methods.

RESULTS

We studied 17 981 582 individuals, of whom 4 855 324 were aged 30-69 years. Three-quarters (76.2%) received BFP, with a mean follow-up post-award of 2.6 years. We detected 106 807 deaths by all causes, of which 60 893 were premature; and 23 389 CVD deaths, of which 15 292 were premature. BFP was associated with reductions in premature all-cause mortality [hazard ratio (HR) = 0.96, 95% CI = 0.94-0.98], premature CVD (HR = 0.96, 95% CI = 0.92-1.00) and all-age CVD (HR = 0.96, 95% CI = 0.93-1.00) but not all-age all-cause mortality (HR = 1.00, 95% CI = 0.98-1.02). In stratified and robustness analyses, BFP was consistently associated with mortality reductions for individuals living in the two most deprived quintiles.

CONCLUSIONS

BFP appears to have a small to null effect on premature CVD and all-cause mortality in the short term; the long-term impact remains unknown.

Does persistent precarious employment affect health outcomes among working age adults? A systematic review and meta-analysis

OBJECTIVE

To evaluate the impact of persistent precarious employment (lasting 12+ months) on the health of working age adults, compared with more stable employment. Persistent precarity reflects a shift towards less secure forms of employment and may be particularly important for health.

METHODS

Nine databases were systematically searched to identify quantitative studies that assessed the relationship between persistent precarious employment and health outcomes. Risk of bias (RoB) was assessed using an adaptation of the Effective Public Health Practice Project tool. Narrative synthesis and random effects meta-analysis were conducted. Certainty of evidence was assessed using the Grades of Recommendations, Assessment, Development and Evaluation (GRADE) approach.

RESULTS

Of 12 940 records screened, 50 studies met the inclusion criteria and 29 were included in meta-analyses. RoB was generally high (n=18). The most reported outcome domain was mental health; with evidence also reported relating to general health, physical health,and health behaviours. Of GRADE assessed outcomes, persistent precarious employment was associated with increased risk of poor self-rated health (OR 1.53, 95% CI 1.09 to 2.14, I2=80%) and mental health symptoms (OR 1.44, 95% CI 1.23 to 1.70, I2=65%). The association with all-cause mortality was imprecisely estimated (OR 1.10, 5% CI 0.91 to 1.33, I2=73%). There was very low GRADE certainty across all outcomes.

CONCLUSIONS

Persistent precarious employment is associated with poorer health, particularly for outcomes with short time lags, though associations are small and causality is highly uncertain. Further research using more robust methods is needed but given potential health harms of persistent precarious employment, exploration of precautionary labour regulations and employment policies is warranted.

Longitudinal study of diabetes prevalence and hospitalisations among care experienced and general population children in Scotland: evidence of an end of care “cliff edge”?

ObjectivesCare experienced people have poorer health in UK and internationally, but the direction of causation is debated. Using longitudinal cross-sectoral data linkage we explore if inequalities in diabetes prevalence and hospitalisation are present before entering care or develop during or after leaving care. ApproachHealth and social care data were linked for 13,830 care experienced children (CEC) and together with 649,771 general population children (GPC) their prescriptions and hospitalisations were followed from birth between 1990-2004 to study end in 2016. Diabetes prevalence was estimated as at least one prescription   or inpatient hospitalisation for diabetes. We compared hospitalisation percentages and rates in the two cohorts by age and gender. Results from multivariable models adjusted for socioeconomic status, age, gender, care type/length, local authority, and comorbidities will be presented at conference. ResultsDiabetes prevalence was similar in both cohorts and higher in females. However, CEC had twice as many hospitalisations as GPC. Mean hospitalisations were highest among care experienced males (6 compared to 3.6 in females and 2 in GPC). 24% of CEC were hospitalised 3-9 times and 13% 10+ times, for GPC these were 19% and 3% respectively. Hospitalisation rates increase with age in both cohorts, as do differences between cohorts. At ages 0-4 hospitalisation rates are similar, by ages 12-15 CEC have twice as high and at ages 18-27 4-times higher hospitalisation rates. Among CEC, across all ages hospitalisation rates are lower while the child is in care, with the lowest rates in foster care. Hospitalisation rates are highest before entering and after leaving care. ConclusionResults for diabetes hospitalisations suggest that being in care can be good for children’s health. However, a sudden withdrawal of support can create a “cliff edge” and health may deteriorate after leaving care. Data linkage has significant potential to inform policy and practice, including supporting CEC after leaving care.

How do income changes impact on mental health and wellbeing for working-age adults? A systematic review and meta-analysis

BACKGROUND

Lower incomes are associated with poorer mental health and wellbeing, but the extent to which income has a causal effect is debated. We aimed to synthesise evidence from studies measuring the impact of changes in individual and household income on mental health and wellbeing outcomes in working-age adults (aged 16-64 years).

METHODS

For this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Science, PsycINFO, ASSIA, EconLit, and RePEc on Feb 5, 2020, for randomised controlled trials (RCTs) and quantitative non-randomised studies. We had no date limits for our search. We included English-language studies measuring effects of individual or household income change on any mental health or wellbeing outcome. We used Cochrane risk of bias (RoB) tools. We conducted three-level random-effects meta-analyses, and explored heterogeneity using meta-regression and stratified analyses. Synthesis without meta-analysis was based on effect direction. Critical RoB studies were excluded from primary analyses. Certainty of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE). This study is registered with PROSPERO, CRD42020168379.

FINDINGS

Of 16 521 citations screened, 136 were narratively synthesised (12·5% RCTs) and 86 meta-analysed. RoB was high: 30·1% were rated critical and 47·1% serious or high. A binary income increase lifting individuals out of poverty was associated with 0·13 SD improvement in mental health measures (95% CI 0·07 to 0·20; n=42 128; 18 studies), considerably larger than other income increases (0·01 SD improvement, 0·002 to 0·019; n=216 509, 14 studies). For wellbeing, increases out of poverty were associated with 0·38 SD improvement (0·09 to 0·66; n=101 350, 8 studies) versus 0·16 for other income increases (0·07 to 0·25; n=62 619, 11 studies). Income decreases from any source were associated with 0·21 SD worsening of mental health measures (-0·30 to -0·13; n=227 804, 11 studies). Effect sizes were larger in low-income and middle-income settings and in higher RoB studies. Heterogeneity was high (I²=79-87%). GRADE certainty was low or very low.

INTERPRETATION

Income changes probably impact mental health, particularly where they move individuals out of poverty, although effect sizes are modest and certainty low. Effects are larger for wellbeing outcomes, and potentially for income losses. To best support population mental health, welfare policies need to reach the most socioeconomically disadvantaged.

FUNDING

Wellcome Trust, Medical Research Council, Chief Scientist Office, and European Research Council.

Comparison of mortality hazard ratios associated with health behaviours in Canada and the United States: a population-based linked health survey study

BACKGROUND

Modern health surveillance and planning requires an understanding of how preventable risk factors impact population health, and how these effects vary between populations. In this study, we compare how smoking, alcohol consumption, diet and physical activity are associated with all-cause mortality in Canada and the United States using comparable individual-level, linked population health survey data and identical model specifications.

METHODS

The Canadian Community Health Survey (CCHS) (2003-2007) and the United States National Health Interview Survey (NHIS) (2000, 2005) linked to individual-level mortality outcomes with follow up to December 31, 2011 were used. Consistent variable definitions were used to estimate country-specific mortality hazard ratios with sex-specific Cox proportional hazard models, including smoking, alcohol, diet and physical activity, sociodemographic indicators and proximal factors including disease history.

RESULTS

A total of 296,407 respondents and 1,813,884 million person-years of follow-up from the CCHS and 58,232 respondents and 497,909 person-years from the NHIS were included. Absolute mortality risk among those with a 'healthy profile' was higher in the United States compared to Canada, especially among women. Adjusted mortality hazard ratios associated with health behaviours were generally of similar magnitude and direction but often stronger in Canada.

CONCLUSION

Even when methodological and population differences are minimal, the association of health behaviours and mortality can vary across populations. It is therefore important to be cautious of between-study variation when aggregating relative effect estimates from differing populations, and when using external effect estimates for population health research and policy development.

Process and impact of implementing a smoke-free policy in prisons in Scotland: TIPs mixed-methods study

Background

Prisons had partial exemption from the UK’s 2006/7 smoking bans in enclosed public spaces. They became one of the few workplaces with continuing exposure to second-hand smoke, given the high levels of smoking among people in custody. Despite the introduction of smoke-free prisons elsewhere, evaluations of such ‘bans’ have been very limited to date.

Objective

The objective was to provide evidence on the process and impact of implementing a smoke-free policy across a national prison service.

Design

The Tobacco in Prisons study was a three-phase, multimethod study exploring the periods before policy formulation (phase 1: pre announcement), during preparation for implementation (phase 2: preparatory) and after implementation (phase 3: post implementation).

Setting

The study was set in Scotland’s prisons.

Participants

Participants were people in custody, prison staff and providers/users of prison smoking cessation services.

Intervention

Comprehensive smoke-free prison rules were implemented across all of Scotland’s prisons in November 2018.

Main outcome measures

The main outcome measures were second-hand smoke levels, health outcomes and perspectives/experiences, including facilitators of successful transitions to smoke-free prisons.

Data sources

The study utilised cross-sectional surveys of staff (total, n = 3522) and people in custody (total, n = 5956) in each phase; focus groups and/or one-to-one interviews with staff (n = 237 across 34 focus groups; n = 38 interviews), people in custody (n = 62 interviews), providers (n = 103 interviews) and users (n = 45 interviews) of prison smoking cessation services and stakeholders elsewhere (n = 19); measurements of second-hand smoke exposure (e.g. 369,208 minutes of static measures in residential areas at three time points); and routinely collected data (e.g. medications dispensed, inpatient/outpatient visits).

Results

Measures of second-hand smoke were substantially (≈ 90%) reduced post implementation, compared with baseline, largely confirming the views of staff and people in custody that illicit smoking is not a major issue post ban. Several factors that contributed to the successful implementation of the smoke-free policy, now accepted as the ‘new normal’, were identified. E-cigarette use has become common, was recognised (by both staff and people in custody) to have facilitated the transition and raises new issues in prisons. The health economic analysis (lifetime model) demonstrated that costs were lower and the number of quality-adjusted life-years was larger for people in custody and staff in the ‘with smoke-free’ policy period than in the ‘without’ policy period, confirming cost-effectiveness against a £20,000 willingness-to-pay threshold.

Limitations

The ability to triangulate between different data sources mitigated limitations with constituent data sets.

Conclusions

To our knowledge, this is the first study internationally to analyse the views of prison staff and people in custody; objective measurements of second-hand smoke exposure and routine health and other outcomes before, during and after the implementation of a smoke-free prison policy; and to assess cost-effectiveness. The results are relevant to jurisdictions considering similar legislation, whether or not e-cigarettes are permitted. The study provides a model for partnership working and, as a multidimensional study of a national prison system, adds to a previously sparse evidence base internationally.

Future work

Priorities are to understand how to support people in custody in remaining smoke free after release from prison, and whether or not interventions can extend benefits to their families; to evaluate new guidance supporting people wishing to reduce or quit vaping; and to understand how prison vaping practices/cultures may strengthen or weaken long-term reductions in smoking.

Study registration

This study is registered as Research Registry 4802.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 10, No. 1. See the NIHR Journals Library website for further project information.

Social inequalities and hospital admission for unintentional injury in young children in Scotland: A nationwide linked cohort study

Background

Unintentional injury is a leading cause of death/disability, with more disadvantaged children at greater risk. Understanding how inequalities vary by injury type, age, severity, and place of injury, can inform prevention.

Methods

For all Scotland-born children 2009-2013 (n=195,184), hospital admissions for unintentional injury (HAUI) were linked to socioeconomic circumstances (SECs) at birth: area deprivation via the Scottish Index of Multiple Deprivation (SIMD), mother's occupational social class, parents’ relationship status. HAUI was examined from birth-five, and during infancy. We examined HAUI frequency, severity, injury type, and injury location (home vs. elsewhere). We estimated relative inequalities using the relative indices of inequality (RII, 95% CIs), before and after adjusting for demographics and other non-mediating SECs.

Findings

More disadvantaged children were at greater risk of any HAUI from birth-five, RII: 1•59(1•49-1•70), 1•74(1•62-1•86), 1•97(1•84-2•12) for area deprivation, maternal occupational social class, and relationship status respectively. These attenuated after adjustment (1•15 [1•06-1•24], 1.22 [1•12-1•33], 1.32 [1•21-1•44]). Inequalities were greater for severe (vs. non-severe), multiple (vs. one-off) and home (vs. other location) injuries. Similar patterns were seen in infancy, excluding SIMD-inequalities in falls, where infants living in more disadvantaged neighbourhoods were at lower risk (0•79 [0•62-1•00]). After adjustment, reverse SIMD-gradients were also observed for all injuries and poisonings.

Interpretation

Children living in more disadvantaged households are more likely to be injured across multiple dimensions of HAUI in Scotland. Upstream interventions which tackle family-level disadvantage may be most effective at reducing childhood HAUI.

Funding

Wellcome Trust, Medical Research Council, Scottish Government Chief Scientist Office.

International population-based health surveys linked to outcome data: A new resource for public health and epidemiology

BACKGROUND

National health surveys linked to vital statistics and health care information provide a growing source of individual-level population health data. Pooling linked surveys across jurisdictions would create comprehensive datasets that are larger than most existing cohort studies, and that have a unique international and population perspective. This paper's objectives are to examine the feasibility of pooling linked population health surveys from three countries, facilitate the examination of health behaviours, and present useful information to assist in the planning of international population health surveillance and research studies.

DATA AND METHODS

The design, methodologies and content of the Canadian Community Health Survey (2003 to 2008), the United States National Health Interview Survey (2000, 2005) and the Scottish Health Survey (SHeS) (2003, 2008 to 2010) were examined for comparability and consistency. The feasibility of creating common variables for measuring smoking, alcohol consumption, physical activity and diet was assessed. Sample size and estimated mortality events were collected.

RESULTS

The surveys have comparable purposes, designs, sampling and administration methodologies, target populations, exclusions, and content. Similar health behaviour questions allow for comparable variables to be created across the surveys. However, the SHeS uses a more detailed risk factor evaluation for alcohol consumption and diet data. Therefore, comparisons of alcohol consumption and diet data between the SHeS and the other two surveys should be performed with caution. Pooling these linked surveys would create a dataset with over 350,000 participants, 28,424 deaths and over 2.4 million person-years of follow-up.

DISCUSSION

Pooling linked national population health surveys could improve population health research and surveillance. Innovative methodologies must be used to account for survey dissimilarities, and further discussion is needed on how to best access and analyze data across jurisdictions.

Mental health and health behaviours before and during the initial phase of the COVID-19 lockdown: longitudinal analyses of the UK Household Longitudinal Study

BACKGROUND

There are concerns that COVID-19 mitigation measures, including the 'lockdown', may have unintended health consequences. We examined trends in mental health and health behaviours in the UK before and during the initial phase of the COVID-19 lockdown and differences across population subgroups.

METHODS

Repeated cross-sectional and longitudinal analysis of the UK Household Longitudinal Study, including representative samples of over 27,000 adults (aged 18+) interviewed in four survey waves between 2015 and 2020. A total of 9748 adults had complete data for longitudinal analyses. Outcomes included psychological distress (General Health Questionnaire-12), loneliness, current cigarette smoking, use of e-cigarettes and alcohol consumption. Cross-sectional prevalence estimates were calculated and multilevel Poisson regression assessed associations between time period and the outcomes of interest, as well as differential associations by age, gender, education level and ethnicity.

RESULTS

Psychological distress increased 1 month into lockdown with the prevalence rising from 19.4% (95% CI 18.7% to 20.1%) in 2017-2019 to 30.6% (95% CI 29.1% to 32.3%) in April 2020 (RR=1.3, 95% CI 1.2 to 1.4). Groups most adversely affected included women, young adults, people from an Asian background and those who were degree educated. Loneliness remained stable overall (RR=0.9, 95% CI 0.6 to 1.5). Smoking declined (RR=0.9, 95% CI=0.8,1.0) and the proportion of people drinking four or more times per week increased (RR=1.4, 95% CI 1.3 to 1.5), as did binge drinking (RR=1.5, 95% CI 1.3 to 1.7).

CONCLUSIONS

Psychological distress increased 1 month into lockdown, particularly among women and young adults. Smoking declined, but adverse alcohol use generally increased. Effective measures are required to mitigate negative impacts on health.

Mental health and health behaviours before and during the initial phase of the COVID-19 lockdown: longitudinal analyses of the UK Household Longitudinal Study

BACKGROUND

There are concerns that COVID-19 mitigation measures, including the 'lockdown', may have unintended health consequences. We examined trends in mental health and health behaviours in the UK before and during the initial phase of the COVID-19 lockdown and differences across population subgroups.

METHODS

Repeated cross-sectional and longitudinal analysis of the UK Household Longitudinal Study, including representative samples of over 27,000 adults (aged 18+) interviewed in four survey waves between 2015 and 2020. A total of 9748 adults had complete data for longitudinal analyses. Outcomes included psychological distress (General Health Questionnaire-12), loneliness, current cigarette smoking, use of e-cigarettes and alcohol consumption. Cross-sectional prevalence estimates were calculated and multilevel Poisson regression assessed associations between time period and the outcomes of interest, as well as differential associations by age, gender, education level and ethnicity.

RESULTS

Psychological distress increased 1 month into lockdown with the prevalence rising from 19.4% (95% CI 18.7% to 20.1%) in 2017-2019 to 30.6% (95% CI 29.1% to 32.3%) in April 2020 (RR=1.3, 95% CI 1.2 to 1.4). Groups most adversely affected included women, young adults, people from an Asian background and those who were degree educated. Loneliness remained stable overall (RR=0.9, 95% CI 0.6 to 1.5). Smoking declined (RR=0.9, 95% CI=0.8,1.0) and the proportion of people drinking four or more times per week increased (RR=1.4, 95% CI 1.3 to 1.5), as did binge drinking (RR=1.5, 95% CI 1.3 to 1.7).

CONCLUSIONS

Psychological distress increased 1 month into lockdown, particularly among women and young adults. Smoking declined, but adverse alcohol use generally increased. Effective measures are required to mitigate negative impacts on health.

Scaling COVID-19 against inequalities: should the policy response consistently match the mortality challenge?

BACKGROUND

The mortality impact of COVID-19 has thus far been described in terms of crude death counts. We aimed to calibrate the scale of the modelled mortality impact of COVID-19 using age-standardised mortality rates and life expectancy contribution against other, socially determined, causes of death in order to inform governments and the public.

METHODS

We compared mortality attributable to suicide, drug poisoning and socioeconomic inequality with estimates of mortality from an infectious disease model of COVID-19. We calculated age-standardised mortality rates and life expectancy contributions for the UK and its constituent nations.

RESULTS

Mortality from a fully unmitigated COVID-19 pandemic is estimated to be responsible for a negative life expectancy contribution of -5.96 years for the UK. This is reduced to -0.33 years in the fully mitigated scenario. The equivalent annual life expectancy contributions of suicide, drug poisoning and socioeconomic inequality-related deaths are -0.25, -0.20 and -3.51 years, respectively. The negative impact of fully unmitigated COVID-19 on life expectancy is therefore equivalent to 24 years of suicide deaths, 30 years of drug poisoning deaths and 1.7 years of inequality-related deaths for the UK.

CONCLUSION

Fully mitigating COVID-19 is estimated to prevent a loss of 5.63 years of life expectancy for the UK. Over 10 years, there is a greater negative life expectancy contribution from inequality than around six unmitigated COVID-19 pandemics. To achieve long-term population health improvements it is therefore important to take this opportunity to introduce post-pandemic economic policies to 'build back better'.

Scaling COVID-19 against inequalities: should the policy response consistently match the mortality challenge?

BACKGROUND

The mortality impact of COVID-19 has thus far been described in terms of crude death counts. We aimed to calibrate the scale of the modelled mortality impact of COVID-19 using age-standardised mortality rates and life expectancy contribution against other, socially determined, causes of death in order to inform governments and the public.

METHODS

We compared mortality attributable to suicide, drug poisoning and socioeconomic inequality with estimates of mortality from an infectious disease model of COVID-19. We calculated age-standardised mortality rates and life expectancy contributions for the UK and its constituent nations.

RESULTS

Mortality from a fully unmitigated COVID-19 pandemic is estimated to be responsible for a negative life expectancy contribution of -5.96 years for the UK. This is reduced to -0.33 years in the fully mitigated scenario. The equivalent annual life expectancy contributions of suicide, drug poisoning and socioeconomic inequality-related deaths are -0.25, -0.20 and -3.51 years, respectively. The negative impact of fully unmitigated COVID-19 on life expectancy is therefore equivalent to 24 years of suicide deaths, 30 years of drug poisoning deaths and 1.7 years of inequality-related deaths for the UK.

CONCLUSION

Fully mitigating COVID-19 is estimated to prevent a loss of 5.63 years of life expectancy for the UK. Over 10 years, there is a greater negative life expectancy contribution from inequality than around six unmitigated COVID-19 pandemics. To achieve long-term population health improvements it is therefore important to take this opportunity to introduce post-pandemic economic policies to 'build back better'.

Economic impacts of implementing a national smoke-free prison policy

Background

Worldwide, over 600,000 non-smokers are killed annually due to exposure to secondhand smoke (SHS); the UK societal cost of SHS is estimated at £700million per annum. Prior to recent smoke free policy in Scottish prisons smoking rates were very high (70-75%), well above population rates, subjecting people in custody (PiC) and prison staff to high levels of SHS. Eradicating SHS exposure in prisons could lead to improved health in previous smokers and non-smokers alike, and decrease demand on the National Health Service. However, to date, there is little evidence relating to the economic impact of smoking bans in prisons.

Methods

An economic evaluation estimating the short-term and lifetime impacts of smokefree prison policy in Scotland policy used data from the TIPs study (Jun 2016-Nov 2019) for prison staff and PiC. The analyses adopted a public health and personal perspective and key resources included: implementation costs, cessation support services, health service use and personal costs. For the short-term analyses data were sourced from TIPs staff and PiC surveys, and routine data from the Scottish Prison Service and NHS National Services Scotland. Outcomes included SHS exposure, staff sickness absence, violent incidents and quality adjusted life years (QALYs). The life-time analysis used a Markov model to estimate cost per QALY for both staff and PiC.

Results

SHS exposure measures show a median reduction of 91%. Costs and economic outcome results (mean cost pre- and post-ban, cost-consequences balance sheet and incremental cost per QALYs) are confidential until May 2020 due to their sensitivity and will be available to present at EUPHA 2020.

Conclusions

Previous economic evaluations have focussed on smoking bans in public places and raising the smoking age. This is the first economic analysis of a national prison smoking ban and analysis will be of interest to prison services in other jurisdictions which have yet to implement smokefree policy.

Smokefree policy and medication dispensing for people in prison: interrupted time series analysis

Background

Previous evaluations of smokefree prison policies have suggested improvements in self-rated health and some smoking-related symptoms. No studies to date have investigated impacts on medication use as proxy measures of objective ill-health or as indicators of potential negative unintended consequences. These is limited evidence to date on these important outcomes.

Methods

We obtained from NHS National Services Scotland aggregate data on medication items dispensed in prisons, based on individual named patient medication records, and from the Scottish Prison Service data on the prison population, for the period Jan 2013-Nov 2019. Items of interest comprised those for smoking cessation (varenicline and buproprion); nicotine replacement; specific smoking-related health conditions (glyceryl trinitrate; inhaled bronchodilators and steroids; antibiotics; chloramphenicol eye drops; and proton pump inhibitors and H2 receptor antagonists), and potential unintended mental health consequences (anti-depressants). We also included a set of negative controls for which dispensing was not expected to be affected by the new smokefree policy (anticonvulsants, excluding pregabalin and gabapentin). Analyses were undertaken using AutoRegressive Integrated Moving Average (ARIMA) time series methods, with the dates of the policy's announcement and of implementation included as pre-specified breakpoints.

Results

The results of ARIMA modelling of medication dispensing are confidential until May 2020 due to their sensitivity and will be available to present at WCPH 2020.

Conclusions

The use of routinely available dispensing data as an indicator of objective health impacts and potential negative unintended consequences provides novel insights into the effectiveness of smokefree prison policies. Results will be of interest to international jurisdictions considering such policies and to those seeking to harness the potential of administrative data for natural experiments.

The causal effects of transition into poverty on mental health in the UK working-age population

Background

Addressing the impact of poverty through income and welfare policies is likely important for public mental health; however, few studies assess potential effect size using causally-informed methodologies. To provide meaningful information for policymakers, we aimed to estimate the average treatment effect of transitioning into poverty on mental health.

Methods

We used data for working-age adults (aged 25-64) from nine waves of the nationally representative UK Household Longitudinal Survey (2009-2019, n = 39,553 obs=155,963). Exposure was transition into poverty (household equiv. income &lt;60% median). Outcome was score ≥4 on General Health Questionnaire-12, indicating likely common mental disorder (CMD). To minimise the influence of reverse causation and time-varying confounders we used a marginal structural modelling (MSM) approach to create inverse probability of treatment weights. We performed secondary analysis stratifying by sex, and calculated population attributable fractions for each model.

Results

Good balance of confounders was achieved between exposure groups. Experiencing new poverty was associated with increased odds of CMD (adjusted OR 1.33, 95% CI 1.24-1.42, p &lt; 0.001) with a 4.8% (3.6-6.0) absolute difference in prevalence: 24.0% vs 19.2%. There was a difference in relative effect by sex, with OR 1.40 (1.25-1.56, p &lt; 0.001) for men vs OR 1.28 (1.18-1.38, p &lt; 0.001) for women. However, there was no marked difference in absolute effect by sex: 4.9% (3.1-6.8) for men vs 4.5% (3.0-6.1) for women. For all analyses traditional logistic regression using the same confounders underestimated the effect in comparison with MSM.

Conclusions

Moving below the poverty line increased odds of CMD by 32.7% after accounting for confounding and reverse causality, with a greater relative impact on men. Our causal estimates suggest transition into poverty currently accounts for 10.7% of the burden of CMD in the UK working-age population - 8.9% for women and 13.1% for men.

Key messages

Reductions in household income worsen mental health, and traditional analytical approaches may be underestimating this causal relationship. Applying causal methodologies to observational data can provide exposure-outcome estimates less susceptible to common biases, which may be of more use to policymakers.

Using cross-sectoral data linkage to understand the health of people experiencing multiple exclusion

Background

People affected by the intersection of homelessness, drug use, and/or serious mental illness have high rates of mortality and morbidity. However, they are often missed from routine information sources on population health, such as surveys and censuses. In many countries, administrative data are available which could help address this knowledge gap. We created a novel virtual cohort using cross-sectoral data linkage in order to inform policy and practice responses to these co-occurring issues.

Methods

Individual-level data from local authority homelessness services (HL), opioid substitution therapy dispensing (OST), and a psychosis case register (PSY) in Glasgow, Scotland between 2011-15 were confidentially linked to National Health Service records, using a mix of probabilistic and deterministic linkage. A de-identified dataset was made available to researchers through a secure analysis platform. Demographic characteristics associated with different exposure combinations were analysed using descriptive statistics.

Results

Linkage created a cohort of 24,767 unique individuals with any one of the experiences of interest between 2011-15. Preliminary results suggest that 89.2% of the cohort had one experience; 10.6% two; and 0.2% all three. The most common combination was HL & OST (n = 2,150; 8.7%), with other combinations much less frequent (HL & PSY, n = 279, 1.1%; OST & PSY, n = 188, 0.8%; HL & OST & PSY, n = 51, 0.2%). The odds of male gender increased with number of exposures (2 exposures, OR 2.1, 95% CI 1.9-2.2; 3 exposures, OR 4.1, 95% CI 2.3-7.2), but there was little difference in age. Work is ongoing to incorporate into the cohort additional datasets on criminal justice involvement.

Lessons

Administrative data linkage is a feasible approach to understanding the health of people affected by multiple exclusionary processes, but requires robust and timely governance. Our initiative can support service planning and evaluation of future policy or service changes.

Key messages

We describe the creation and characteristics of a novel virtual cohort of people affected by multiple exclusionary processes, using record linkage of administrative datasets. Cross-sectoral linkage has international potential for enhancing public health intelligence, especially for population groups who may be missed from surveys and censuses.

The Brazilian conditional cash transfer program and cardiovascular mortality: a data linkage study

Background

Conditional cash transfer programmes (CCTs) make monetary transfers to poor families conditional on health check-ups and/or education attendance. CCTs have been key in reducing poverty and improving child and maternal health in low- and middle-income countries (LMICs) but their impact on cardiovascular mortality have not been studied. We aimed to evaluate the effect of the CCT Bolsa Familia Program (BFP) on premature all-cause and cardiovascular mortality in Brazil.

Methods

The 100 Million Brazilian Cohort combined information about individuals applying for social programmes, the BFP and mortality data. We analysed ∼8 million individuals aged 30-69 who applied from 2011 to 2015. We calculated inverse probability weights (IPW) for the probability to receive BFP based on baseline observed characteristics (age, education, race, geographical location, household characteristics and year of application). Individuals were followed until they reached 70 years of age, died by any cause, or until 31st Dec 2015. We used Poisson regression (with person-years as the offset) and IPWs to compare BFP recipients to a comparable control population. Females and males were analysed separately.

Results

By following individuals for up to 4 years, 43,562 deaths by all-causes occurred among 4,197,658 females and 69,209 deaths among 3,672,393 males. Female BFP beneficiaries had approximately 60% lower all-cause mortality (IRR=0.40;95%CI=0.37-0.42) and CVD mortality (IRR=0.42;95%CI=0.37-0.47) than non-beneficiaries. Males who are BFP beneficiaries had ∼50% lower all-cause (IRR=0.53;95%CI=0.52-0.55) and 60% lower cardiovascular mortality (IRR=0.40;95%CI=0.38-0.42) than non-beneficiaries.

Conclusions

BFP, the world's largest CCT, may substantially decrease premature mortality. CCTs might have important implications for the growing burden of non-communicable diseases, with impacts potentially due to improved nutrition, socioeconomic conditions and improved primary care access.

Key messages

The Brazilian CCT, a widely recognized programme for poverty alleviation, have showed to be associated with lower overall and cardiovascular premature mortality in both women and men. Other countries, particularly LMICs, may learn from the health benefits of CCTs and should consider its potential large effect on mortality when planning austerity policies.

Women and evaluation of inequalities in the distribution of risk factors for Chronic non-communicable diseases (NCD), Vigitel 2016-2017

OBJECTIVE

To compare the distribution of chronic non-communicable diseases (CNCD) indicators among adult female beneficiaries and non-beneficiaries of the Bolsa Família Program (BFP) in Brazilian capitals.

METHODS

Analysis of Vigitel telephone survey data in 2016 and 2017. Gross and adjusted prevalence ratios (PR) and their respective confidence intervals were estimated using Poisson Regression model.

RESULTS

Women with BF have lower schooling, are young people, live more frequently in the Northeast and North of the country. Higher prevalence of risk factors were found in woman receiving BF. The adjusted PR of the BF women were: smokers (PR = 1.98), overweight (PR = 1.21), obesity (PR = 1.63), fruits and vegetables (PR = 0.63), consumption of soft drinks (PR = 1.68), bean consumption (PR = 1.25), physical activity at leisure (PR = 0.65), physical activity at home (PR = 1.35), time watching TV (PR = 1.37), self-assessment of poor health status (PR =2.04), mammography (PR = 0.86), Pap smears (PR = 0.91), hypertension (PR = 1.46) and diabetes (PR = 1,66). When women were compared among strata of the same schooling, these differences were reduced.

CONCLUSION

Worst indicators among women receiving BF reflect social inequalities inherent in this most vulnerable group. The study also shows that BF is being targeted at the most vulnerable women.

Individual and area-level factors associated with ambulatory care sensitive conditions in Finland

Background

Geographic variation is common in ambulatory care sensitive conditions (ACSCs) - used as a proxy indicator for primary care quality. Its use is debated as it is more strongly associated with individual socioeconomic position (SEP) and health status than factors related to primary care. While most earlier studies have been cross-sectional, this study aims to observe if these associations change over time. Finland offers a good possibility for this due to its extensive registers and unexplained over time convergence of geographic variation in ACSC.

Methods

This observational study obtained ACSCs in 2011-2017 from the Finnish Hospital Discharge Register and divided them into subgroups of acute, chronic and vaccine-preventable causes. In these subgroups we analysed geographic variations with a three-level multilevel logistic regression model - individuals, health centre areas (HC) and hospital districts (HD) - and estimated the proportion of the variance at each level explained by individual SEP and comorbidities, as well as both primary care and hospital supply and spatial access at three time points.

Results

In the preliminary results of the baseline geographic variation in total ACSCs in 2011-2013 - the model with age and sex - the variance between HDs was nearly twice that between HCs. Individual SEP and comorbidities explained 46% of the variance between HDs and 29% between HCs; and area-level proportion of ACSC periods in primary care inpatient wards a further 12% and 5%. This evened out the unexplained variance between HDs and HCs.

Conclusions

Geographic variation in ACSCs was more pronounced in hospital districts than in the smaller health centre areas. The excess variance between HDs was explained by individual SEP and health status as well as by use of primary care inpatient wards. Our findings suggest that not only hospital bed supply, but also the national structure of hospital services affects ACSCs. This challenges international ACSC comparisons.

Key messages

Geographic variation in ACSCs concentrated in larger areas with differing population characteristics. The national structure of hospital services, such as use of primary care inpatient wards, affects ACSCs.

Socio-economic inequalities in timing of childhood immunizations in Scotland

In Scotland, like many other European countries, childhood immunization coverage is generally high, often exceeding levels typically required to achieve herd immunity (95%): uptake of the primary vaccines (excluding rotavirus) is ∼96% (at 12month(m)), with the 1st dose of measles, mumps and rubella (MMR) at 97% (by 5 years). However, the recommended age to receive these vaccines is 2-4m and 12-13m respectively. Delays beyond these ages may indicate vaccine hesitancy or barriers to access and can increase the likelihood of disease outbreaks, especially if clustered among certain geographical or social groups. We used quantile regression to examine the age by which 95% coverage was met in different groups.

We analyzed data from the Scottish Immunisation and Recall System, for all children born in Scotland 2010-12 (n∼200,000), estimating proportions immunized ‘on time’ with the primary (by age 5m) and MMR (by 14m) vaccines. Next we used quantile regression (with 95% cut-points) to calculate the age by which 95% coverage was reached among this cohort of children, overall and according to neighbourhood deprivation (Scottish Index of Multiple Deprivation[SIMD] deciles).

As in national reports, uptake of the primaries (at 12m) and MMR (at 5y) was &gt;95%, with 91% and 89% immunized ‘on time’ (as defined above). Nationally, primary vaccines uptake reached 95% by age 7m. This varied by SIMD, from 6m in the least disadvantaged decile, to 9m in the most disadvantaged decile (difference 3m, CI: 2.7-3.3). Uptake of MMR reached 95% a year later than recommended (26m), with no discernible pattern by SIMD.

In Scotland, the age by which immunization levels meet those typically required to achieve herd immunity may be suboptimal, particularly for MMR and (for primary vaccines) disadvantaged neighborhoods. This same approach might be used in other nations with high coverage to identify population groups that may be experiencing barriers to access and inform local intervention content

Indicators of chronic noncommunicable diseases in women of reproductive age that are beneficiaries and non-beneficiaries of Bolsa Família

OBJECTIVE

To evaluate the prevalence of noncommunicable disease (NCD) indicators, including laboratory tests, in the population of Brazilian women of reproductive age, according to whether or not they receive the Bolsa Família (BF) benefit.

METHODS

A total of 3,131 women aged 18 to 49 years old who participated in the National Health Survey (Pesquisa Nacional de Saúde ) laboratory examination sub-sample were considered. We compared indicators among women of reproductive age (18 to 49 years old) who reported receiving BF or not, and calculated prevalence and confidence intervals, using Pearson's χ2.

RESULTS

Women of reproductive age who were beneficiaries of BF had worse health outcomes, such as a greater occurrence of being overweight (33.5%) and obese (26.9%) (p < 0.001), having hypertension (13.4% versus 4.4%, p < 0.001), used more tobacco (11.2% versus 8.2%, p = 0.029), and perceived their health as worse (6.2% versus 2.4%, p < 0.001).

CONCLUSION

Several NCD indicators were worse among women of childbearing age who were beneficiaries of BF. It should be emphasized that this is not a causal relationship, with BF being a marker of inequalities among women. The benefit has been directed to the population with greater health needs, and seeks to reduce inequities.

The potential impact of austerity on attainment of the Sustainable Development Goals in Brazil

In the recent decades, Brazil has outperformed comparable countries in its progress toward meeting the Millennium Development Goals. Many of these improvements have been driven by investments in health and social policies. In this article, we aim to identify potential impacts of austerity policies in Brazil on the chances of achieving the sustainable development goals (SDGs) and its consequences for population health. Austerity's anticipated impacts are assessed by analysing the change in federal spending on different budget programmes from 2014 to 2017. We collected budget data made publicly available by the Senate. Among the selected 19 programmes, only 4 had their committed budgets increased, in real terms, between 2014 and 2017. The total amount of extra money committed to these four programmes in 2017, above that committed in 2014, was small (BR$9.7 billion). Of the 15 programmes that had budget cuts in the period from 2014 to 2017, the total decrease amounted to BR$60.2 billion (US$15.3 billion). In addition to the overall large budget reduction, it is noteworthy that the largest proportional reductions were in programmes targeted at more vulnerable populations. In conclusion, it seems clear that the current austerity policies in Brazil will probably damage the population's health and increase inequities, and that the possibility of meeting SDG targets is lower in 2018 than it was in 2015.

Indicators of chronic noncommunicable diseases in women of reproductive age that are beneficiaries and non-beneficiaries of Bolsa Família

OBJECTIVE

To evaluate the prevalence of noncommunicable disease (NCD) indicators, including laboratory tests, in the population of Brazilian women of reproductive age, according to whether or not they receive the Bolsa Família (BF) benefit.

METHODS

A total of 3,131 women aged 18 to 49 years old who participated in the National Health Survey (Pesquisa Nacional de Saúde ) laboratory examination sub-sample were considered. We compared indicators among women of reproductive age (18 to 49 years old) who reported receiving BF or not, and calculated prevalence and confidence intervals, using Pearson's χ2.

RESULTS

Women of reproductive age who were beneficiaries of BF had worse health outcomes, such as a greater occurrence of being overweight (33.5%) and obese (26.9%) (p < 0.001), having hypertension (13.4% versus 4.4%, p < 0.001), used more tobacco (11.2% versus 8.2%, p = 0.029), and perceived their health as worse (6.2% versus 2.4%, p < 0.001).

CONCLUSION

Several NCD indicators were worse among women of childbearing age who were beneficiaries of BF. It should be emphasized that this is not a causal relationship, with BF being a marker of inequalities among women. The benefit has been directed to the population with greater health needs, and seeks to reduce inequities.

Initial protocol for a national evaluation of an area-based intervention programme (A Better Start) on early-life outcomes: a longitudinal cohort study with comparison (control) cohort samples

INTRODUCTION

Pregnancy and the first few years of a child's life are important windows of opportunity in which to equalise life chances. A Better Start (ABS) is an area-based intervention being delivered in five areas of socioeconomic disadvantage across England. This protocol describes an evaluation of the impact and cost-effectiveness of ABS.

METHODS AND ANALYSIS

The evaluation of ABS comprises a mixed-methods design including impact, cost-effectiveness and process components. It involves a cohort study in the 5 ABS areas and 15 matched comparison sites (n=2885), beginning in pregnancy in 2017 and ending in 2024 when the child is age 7, with a separate cross-sectional baseline survey in 2016/2017. Process data will include a profiling of the structure and services being provided in the five ABS sites at baseline and yearly thereafter, and data regarding the participating families and the services that they receive. Eligible participants will include pregnant women living within the designated sites, with recruitment beginning at 16 weeks of pregnancy. Data collection will involve interviewer-administered and self-completion surveys at eight time points. Primary outcomes include nutrition, socioemotional development, speech, language and learning. Data analysis will include the use of propensity score techniques to construct matched programme and comparison groups, and a range of statistical techniques to calculate the difference in differences between the intervention and comparison groups. The economic evaluation will involve a within-cohort study economic evaluation to compare individual-level costs and outcomes, and a decision analytic cost-effectiveness model to estimate the expected incremental cost per unit change in primary outcomes for ABS in comparison to usual care.

ETHICS AND DISSEMINATION

Ethical approval to conduct the study has been obtained. The learning and dissemination workstream involves working within and across the sites to generate learning via communities of practice and a range of learning and dissemination events.

Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research

Population health interventions are essential to reduce health inequalities and tackle other public health priorities, but they are not always amenable to experimental manipulation. Natural experiment (NE) approaches are attracting growing interest as a way of providing evidence in such circumstances. One key challenge in evaluating NEs is selective exposure to the intervention. Studies should be based on a clear theoretical understanding of the processes that determine exposure. Even if the observed effects are large and rapidly follow implementation, confidence in attributing these effects to the intervention can be improved by carefully considering alternative explanations. Causal inference can be strengthened by including additional design features alongside the principal method of effect estimation. NE studies often rely on existing (including routinely collected) data. Investment in such data sources and the infrastructure for linking exposure and outcome data is essential if the potential for such studies to inform decision making is to be realized.