The impact of place on multimorbidity: A systematic scoping review.

Multimorbidity, commonly defined as the co-existence of two or more long-term conditions, is a major global public health challenge with significant impacts for health and social care systems. There is a substantial body of work identifying different individual- and household-level determinants of multimorbidity, yet the role of place-based characteristics in affecting multimorbidity remains limited. This systematic scoping review identifies place-based risk factors for multimorbidity and further synthesises the potential pathways explaining these relationships using longitudinal evidence. By systematically searching seven major databases, such as Medline, Embase, and Web of Science, using relevant search terms (e.g., MeSH) relating to place-based risk factors and multimorbidity, 76 out of 7761 studies were included for evidence synthesis. We include studies exploring the relationship between place-based risk factors and multimorbidity among the general population older than 18 years old in the setting of community-dwelling, primary, and secondary care. We identified 12 types of place-based risk factors, with the impacts of area-level deprivation/SES, pollution, and urban/rurality on multimorbidity being most frequently considered and with the most consistent findings, with people living in more deprived/low SES, highly polluted, or more urbanised areas having increased risks of multimorbidity. Further, the impact of these place-based risk factors on multimorbidity varied according to the operationalisation of the multimorbidity measure. We also identified that the impacts of other types of place-based factors on multimorbidity remain underexplored, such as social cohesion and greenspace. Finally, using these longitudinal findings, we propose a conceptual framework linking place and multimorbidity. We suggest that future studies explore a wider range of place-level environmental exposures and use more precise measures, exploit electronic health records to implement more consistent and reproducible measurements of multimorbidity, moreover, make greater use of longitudinal study designs or analytical approaches better suited to identifying causal processes.

Higher ultraviolet light exposure is associated with lower mortality: An analysis of data from the UK biobank cohort study.

We aimed to examine associations between ultraviolet (UV) exposure and mortality among older adults in the United Kingdom (UK). We used data from UK Biobank participants with two UV exposures, validated with measured vitamin D levels: solarium use and annual average residential shortwave radiation. Associations between the UV exposures, all-cause and cause-specific mortality were examined as adjusted hazard ratios. The UV exposures were inversely associated with all-cause, cardiovascular disease (CVD) and cancer mortality. Solarium users were also at a lower risk of non-CVD/non-cancer mortality. The benefits of UV exposure may outweigh the risks in low-sunlight countries.

Higher air pollution exposure in early life is associated with worse health among older adults: A 72-year follow-up study from Scotland.

Air pollution increases the risk of mortality and morbidity. However, limited evidence exists on the very long-term associations between early life air pollution exposure and health, as well as on potential pathways. This study explored the relationship between fine particle (PM2.5) exposure at age 3 and limiting long-term illness (LLTI) at ages 55, 65 and 75 using data from the Scottish Longitudinal Study Birth Cohort 1936, a representative administrative cohort study. We found that early life PM2.5 exposure was associated with higher odds of LLTI in mid-to-late adulthood (OR = 1.10, 95% CI: 1.06, 1.14 per 10 µg m-3 increment) among the 2085 participants, with stronger associations among those growing up in disadvantaged families. Path analyses suggested that 15-21% of the association between early life PM2.5 concentrations and LLTI at age 65 (n = 1406) was mediated through childhood cognitive ability, educational qualifications, and adult social position. Future research should capitalise on linked administrative and health data, and explore causal mechanisms between environment and specific health conditions across the life course.

Does cycle commuting reduce the risk of mental ill-health? An instrumental variable analysis using distance to nearest cycle path.

BACKGROUND: Previous studies have linked cycling with improved mental wellbeing but these studies tend to use cross-sectional survey data that have small sample sizes and self-reported health measures, and are potentially susceptible to omitted-variable bias and reverse causation. We use an instrumental variable approach and an objective measure of mental ill-health taken from linked administrative data to ask: 'Does cycle commuting reduce the risk of mental ill-health?' METHODS: Our study links data on commuting in Edinburgh and Glasgow from the Scottish population census with mental health prescriptions from the National Health Service Prescribing Information System records. We use road distance from home to nearest cycle path as an instrumental variable for cycle commuting. RESULTS: In total, 378 253 people aged 16-74 years living and working in the City of Edinburgh and Glasgow City council areas at the 2011 census were included in our study; 1.85% of commuters in Glasgow and 4.8% of commuters in Edinburgh cycled to work. Amongst cyclists, 9% had a prescription for mental health compared with 14% amongst non-cyclists. Using a bivariate probit model, we estimate a mean average reduction in prescriptions for antidepressants and/or anxiolytics in the 5 years following the census of -15.1% (95% CI: -15.3% to -15.0%) amongst cycle commuters compared with those who use any other mode to commute. CONCLUSIONS: This work suggests that cycle commuting is causally related to reduced mental ill-health and provides further evidence in support of the promotion of active travel to encourage commuters travelling shorter distances to shift to cycle commutes.

Impact of individual, household, and area characteristics on health and social care outcomes for people with multimorbidity: Protocol for a multilevel analysis.

BACKGROUND: Multimorbidity is one of the greatest challenges facing health and social care systems globally. It is associated with high rates of health service use, adverse healthcare events, and premature death. Despite its importance, little is known about the effects of contextual determinants such as household and area characteristics on health and care outcomes for people with multimorbidity. This study protocol presents a plan for the examination of associations between individual, household, and area characteristics with important health and social care outcomes. METHODS: The study will use a cross-section of data from the SAIL Databank on 01 January 2019 and include all people alive and registered with a Welsh GP. The cohort will be stratified according to the presence or absence of multimorbidity, defined as two or more long-term conditions. Multilevel models will be used to examine covariates measured for individuals, households, and areas to account for social processes operating at different levels. The intra-class correlation coefficient will be calculated to determine the strength of association at each level of the hierarchy. Model outcomes will be any emergency department attendance, emergency hospital or care home admission, or mortality, within the study follow-up period. DISCUSSION: Household and area characteristics might act as protective or risk factors for health and care outcomes for people with multimorbidity, in which case results of the analyses can be used to guide clinical and policy responses for effective targeting of limited resources.

Early life PM2.5 exposure, childhood cognitive ability and mortality between age 11 and 86: A record-linkage life-course study from Scotland.

BACKGROUND: Living in areas with high air pollution concentrations is associated with all-cause and cause-specific mortality. Exposure in sensitive developmental periods might be long-lasting but studies with very long follow-up are rare, and mediating pathways between early life exposure and life-course mortality are not fully understood. METHODS: Data were drawn from the Scottish Longitudinal Study Birth Cohort of 1936, a representative record-linkage study comprising 5% of the Scottish population born in 1936. Participants had valid age 11 cognitive ability test scores along with linked mortality data until age 86. Fine particle (PM2.5) concentrations estimated with the EMEP4UK atmospheric chemistry transport model were linked to participants' residential address derived from the National Identity Register in 1939 (age 3). Confounder-adjusted Cox regression estimated associations between PM2.5 and mortality; regression-based causal mediation analysis explored mediation through childhood cognitive ability. RESULTS: The final sample consisted of 2734 individuals with 1608 deaths registered during the 1,833,517 person-months at risk follow-up time. Higher early life PM2.5 exposure increased the risk of all-cause mortality (HR = 1.03, 95% CI: 1.01-1.04 per 10 µg m-3 increment), associations were stronger for mortality between age 65 and 86. PM2.5 increased the risk of cancer-related mortality (HR = 1.05, 95% CI: 1.02-1.08), especially for lung cancer among females (HR = 1.11, 95% CI: 1.02-1.21), but not for cardiovascular and respiratory diseases. Higher PM2.5 in early life (≥50 µg m-3) was associated with lower childhood cognitive ability, which, in turn, increased the risk of all-cause mortality and mediated 25% of the total associations. CONCLUSIONS: In our life-course study with 75-year of continuous mortality records, we found that exposure to air pollution in early life was associated with higher mortality in late adulthood, and that childhood cognitive ability partly mediated this relationship. Findings suggest that past air pollution concentrations will likely impact health and longevity for decades to come.

Impact of data source choice on multimorbidity measurement: a comparison study of 2.3 million individuals in the Welsh National Health Service.

BACKGROUND: Measurement of multimorbidity in research is variable, including the choice of the data source used to ascertain conditions. We compared the estimated prevalence of multimorbidity and associations with mortality using different data sources. METHODS: A cross-sectional study of SAIL Databank data including 2,340,027 individuals of all ages living in Wales on 01 January 2019. Comparison of prevalence of multimorbidity and constituent 47 conditions using data from primary care (PC), hospital inpatient (HI), and linked PC-HI data sources and examination of associations between condition count and 12-month mortality. RESULTS: Using linked PC-HI compared with only HI data, multimorbidity was more prevalent (32.2% versus 16.5%), and the population of people identified as having multimorbidity was younger (mean age 62.5 versus 66.8 years) and included more women (54.2% versus 52.6%). Individuals with multimorbidity in both PC and HI data had stronger associations with mortality than those with multimorbidity only in HI data (adjusted odds ratio 8.34 [95% CI 8.02-8.68] versus 6.95 (95%CI 6.79-7.12] in people with ≥ 4 conditions). The prevalence of conditions identified using only PC versus only HI data was significantly higher for 37/47 and significantly lower for 10/47: the highest PC/HI ratio was for depression (14.2 [95% CI 14.1-14.4]) and the lowest for aneurysm (0.51 [95% CI 0.5-0.5]). Agreement in ascertainment of conditions between the two data sources varied considerably, being slight for five (kappa < 0.20), fair for 12 (kappa 0.21-0.40), moderate for 16 (kappa 0.41-0.60), and substantial for 12 (kappa 0.61-0.80) conditions, and by body system was lowest for mental and behavioural disorders. The percentage agreement, individuals with a condition identified in both PC and HI data, was lowest in anxiety (4.6%) and highest in coronary artery disease (62.9%). CONCLUSIONS: The use of single data sources may underestimate prevalence when measuring multimorbidity and many important conditions (especially mental and behavioural disorders). Caution should be used when interpreting findings of research examining individual and multiple long-term conditions using single data sources. Where available, researchers using electronic health data should link primary care and hospital inpatient data to generate more robust evidence to support evidence-based healthcare planning decisions for people with multimorbidity.

Ethnic inequalities in positive SARS-CoV-2 tests, infection prognosis, COVID-19 hospitalisations and deaths: analysis of 2 years of a record linked national cohort study in Scotland.

BACKGROUND: This study aims to estimate ethnic inequalities in risk for positive SARS-CoV-2 tests, COVID-19 hospitalisations and deaths over time in Scotland. METHODS: We conducted a population-based cohort study where the 2011 Scottish Census was linked to health records. We included all individuals ≥ 16 years living in Scotland on 1 March 2020. The study period was from 1 March 2020 to 17 April 2022. Self-reported ethnic group was taken from the census and Cox proportional hazard models estimated HRs for positive SARS-CoV-2 tests, hospitalisations and deaths, adjusted for age, sex and health board. We also conducted separate analyses for each of the four waves of COVID-19 to assess changes in risk over time. FINDINGS: Of the 4 358 339 individuals analysed, 1 093 234 positive SARS-CoV-2 tests, 37 437 hospitalisations and 14 158 deaths occurred. The risk of COVID-19 hospitalisation or death among ethnic minority groups was often higher for White Gypsy/Traveller (HR 2.21, 95% CI (1.61 to 3.06)) and Pakistani 2.09 (1.90 to 2.29) groups compared with the white Scottish group. The risk of COVID-19 hospitalisation or death following confirmed positive SARS-CoV-2 test was particularly higher for White Gypsy/Traveller 2.55 (1.81-3.58), Pakistani 1.75 (1.59-1.73) and African 1.61 (1.28-2.03) individuals relative to white Scottish individuals. However, the risk of COVID-19-related death following hospitalisation did not differ. The risk of COVID-19 outcomes for ethnic minority groups was higher in the first three waves compared with the fourth wave. INTERPRETATION: Most ethnic minority groups were at increased risk of adverse COVID-19 outcomes in Scotland, especially White Gypsy/Traveller and Pakistani groups. Ethnic inequalities persisted following community infection but not following hospitalisation, suggesting differences in hospital treatment did not substantially contribute to ethnic inequalities.

The impact of varying the number and selection of conditions on estimated multimorbidity prevalence: A cross-sectional study using a large, primary care population dataset.

BACKGROUND: Multimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include. METHODS AND FINDINGS: We conducted a cross-sectional study using English primary care data for 1,168,260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity (defined as ≥2 conditions) when varying the number and selection of conditions considered for 80 conditions. Included conditions featured in ≥1 of the 9 published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK (HDR-UK) Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common 2 conditions, 3 conditions, etc., up to 80 conditions. Second, prevalence was calculated using 9 condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the 2 commonest conditions were considered was 4.6% (95% CI [4.6, 4.6] p < 0.001), rising to 29.5% (95% CI [29.5, 29.6] p < 0.001) considering the 10 commonest, 35.2% (95% CI [35.1, 35.3] p < 0.001) considering the 20 commonest, and 40.5% (95% CI [40.4, 40.6] p < 0.001) when considering all 80 conditions. The threshold number of conditions at which multimorbidity prevalence was >99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0- to 9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of "comorbidity." Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition-lists, but this highlights further variability in prevalence estimates across studies. CONCLUSIONS: In this study, we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence.

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis.

BACKGROUND: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised. AIM: To examine variation in prevalence using different definitions of multimorbidity. DESIGN AND SETTING: Cross-sectional study of 1 168 620 people in England. METHOD: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental-physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions. RESULTS: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental-physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental-physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental-physical MM at 40-45 years younger, followed by MM2+ at 15-20 years younger, and MM3+ and MM3+ from 3+ at 10-15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental-physical MM. CONCLUSION: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.

Household and area determinants of emergency department attendance and hospitalisation in people with multimorbidity: a systematic review.

OBJECTIVES: Multimorbidity is one of the greatest challenges facing healthcare internationally. Emergency department (ED) attendance and hospitalisation rates are higher in people with multimorbidity, but most research focuses on associations with individual characteristics, ignoring household or area mediators of service use. DESIGN: Systematic review reported using the synthesis without meta-analysis framework. DATA SOURCES: Twelve electronic databases (1 January 2000-21 September 2021): MEDLINE/OVID, Embase, Global Health, PsycINFO, ASSIA, CAB Abstracts, Science Citation Index Expanded/ISI Web of Science, Scopus, Cumulative Index to Nursing and Allied Health Literature, Sociological Abstracts, the Cochrane Library, and OpenGrey. ELIGIBILITY CRITERIA: Adults aged ≥16 years, with multimorbidity. Exposure(s) were household and/or area determinants of health. Outcomes were ED attendance and/or hospitalisation. The literature search was limited to publications in English. DATA EXTRACTION AND SYNTHESIS: Independent double screening of titles and abstracts to select relevant full-text studies. Methodological quality was assessed using an adaptation of the Newcastle-Ottawa Quality Assessment Scale tool. Given high study heterogeneity, narrative synthesis was performed. RESULTS: After deduplication, 10 721 titles and abstracts were screened, and 142 full-text articles were reviewed, of which 10 were eligible for inclusion. In people with multimorbidity, household food insecurity was associated with hospitalisation (OR 1.58 (95% CI 1.06 to 2.36) in concordant multimorbidity). People with multimorbidity living in the most versus least deprived areas attended ED more frequently (8.9% (95% CI 8.6 to 9.1) in most versus 6.3% (95% CI 6.1 to 6.6) in least), had higher rates of hospitalisation (26% in most versus 22% in least), and higher probability of hospitalisation (6.4% (95% CI 5.8 to 7.2) in most versus 4.2% (95% CI 3.8 to 4.7) in least). There was non-conclusive evidence that household income is associated with ED attendance and hospitalisation. No statistically significant relationships were found between marital status, living with others with multimorbidity, or rurality with ED attendance or hospitalisation. CONCLUSIONS: There is some evidence that household and area contexts mediate associations of multimorbidity with ED attendance and hospitalisation, but firm conclusions are constrained by the small number of studies published and study design heterogeneity. Further research is required on large population samples using robust analytical methods. PROSPERO REGISTRATION NUMBER: CRD42021283515.

SARS-CoV-2 tests, confirmed infections and COVID-19-related hospital admissions in children and young people: birth cohort study.

BACKGROUND: There have been no population-based studies of SARS-CoV-2 testing, PCR-confirmed infections and COVID-19-related hospital admissions across the full paediatric age range. We examine the epidemiology of SARS-CoV-2 in children and young people (CYP) aged <23 years. METHODS: We used a birth cohort of all children born in Scotland since 1997, constructed via linkage between vital statistics, hospital records and SARS-CoV-2 surveillance data. We calculated risks of tests and PCR-confirmed infections per 1000 CYP-years between August and December 2020, and COVID-19-related hospital admissions per 100 000 CYP-years between February and December 2020. We used Poisson and Cox proportional hazards regression models to determine risk factors. RESULTS: Among the 1 226 855 CYP in the cohort, there were 378 402 tests (a rate of 770.8/1000 CYP-years (95% CI 768.4 to 773.3)), 19 005 PCR-confirmed infections (179.4/1000 CYP-years (176.9 to 182.0)) and 346 admissions (29.4/100 000 CYP-years (26.3 to 32.8)). Infants had the highest COVID-19-related admission rates. The presence of chronic conditions, particularly multiple types of conditions, was strongly associated with COVID-19-related admissions across all ages. Overall, 49% of admitted CYP had at least one chronic condition recorded. CONCLUSIONS: Infants and CYP with chronic conditions are at highest risk of admission with COVID-19. Half of admitted CYP had chronic conditions. Studies examining COVID-19 vaccine effectiveness among children with chronic conditions and whether maternal vaccine during pregnancy prevents COVID-19 admissions in infants are urgently needed.

The Impacts of Benefit Sanctions: A Scoping Review of the Quantitative Research Evidence.

In recent decades, the use of conditionality backed by benefit sanctions for those claiming unemployment and related benefits has become widespread in the social security systems of high-income countries. Critics argue that sanctions may be ineffective in bringing people back to employment or indeed harmful in a range of ways. Existing reviews largely assess the labour market impacts of sanctions but our understanding of the wider impacts is more limited. We report results from a scoping review of the international quantitative research evidence on both labour market and wider impacts of benefit sanctions. Following systematic search and screening, we extract data for 94 studies reporting on 253 outcome measures. We provide a narrative summary, paying attention to the ability of the studies to support causal inference. Despite variation in the evidence base and study designs, we found that labour market studies, covering two thirds of our sample, consistently reported positive impacts for employment but negative impacts for job quality and stability in the longer term, along with increased transitions to non-employment or economic inactivity. Although largely relying on non-experimental designs, wider-outcome studies reported significant associations with increased material hardship and health problems. There was also some evidence that sanctions were associated with increased child maltreatment and poorer child well-being. Lastly, the review highlights the generally poor quality of the evidence base in this area, with few studies employing research methods designed to identify the causal impact of sanctions, especially in relation to wider impacts.

Lower social participation partly explains the association between perceived neighbourhood crime and depressive symptoms in European adults aged 50 years or older: A longitudinal mediation analysis.

Neighbourhood crime likely increases the risk of developing depression among older adults. However, little is known about the underlying behavioural and social pathways. We examined the association between perceived neighbourhood crime and depressive symptoms and whether this relationship was mediated by health behaviours (physical activity, smoking, and alcohol consumption) and social participation. Furthermore, we explored differential vulnerability across age, gender, education and household wealth. Data were drawn from six waves of longitudinal data (from 2004/2005 to 2017) of approximately 15,000 adults aged 50 years and older, derived from the multi-national Survey of Health, Ageing and Retirement in Europe. Perceived neighbourhood crime and covariates were measured at baseline, time-variant mediators and depressive symptoms across all waves. Confounder-adjusted mediator and outcome models were fitted with mixed-effects models. Total association was decomposed into direct and indirect pathways applying causal mediation analyses with Monte-Carlo simulations. Perceived crime was associated with higher risk of depressive symptoms; 4.6% of the effect was mediated via lower engagement in social activities (b = 0.005; 95% CI: 0.001-0.009). No mediation was detected through physical activity, smoking or alcohol consumption. Exploratory analyses revealed that the mediating role of social participation was more pronounced among participants with low household wealth (b = 0.012; 95% CI: 0.004-0.023; 7.3% mediated). Lower engagement in social activities partly explained the association between perceived neighbourhood crime and depressive symptoms in adults aged 50 years or older. Policies targeting disadvantaged communities to prevent crime and support social participation might be beneficial for population mental health, especially among financially vulnerable older residents.

The impact of neighbourhood crime on mental health: A systematic review and meta-analysis.

BACKGROUND: Growing evidence indicates that the residential neighbourhood contributes to the complex aetiology of mental disorders. Although local crime and violence, key neighbourhood stressors, may be linked to mental health through direct and indirect pathways, studies are inconclusive. This systematic review and meta-analysis aimed to synthetize the evidence on the association between neighbourhood crime and individual-level mental health problems. METHOD: We searched 11 electronic databases, grey literature and reference lists to identify relevant studies published before September 14, 2020. Studies were included if they reported confounder-adjusted associations between objective or perceived area-level crime and anxiety, depression, psychosis or psychological distress/internalising symptoms in non-clinical samples. Effect measures were first converted into Fisher's z-s, pooled with three-level random-effects meta-analyses, and then transformed into Pearson's correlation coefficients. Univariate and multivariate mixed-effects models were used to explore between-study heterogeneity. RESULTS: We identified 63 studies reporting associations between neighbourhood crime and residents' mental health. Pooled associations were significant for depression (r = 0.04, 95% CI 0.03-0.06), psychological distress (r = 0.04, 95% CI 0.02-0.06), anxiety (r = 0.05, 95% CI 0.01-0.10), and psychosis (r = 0.04, 95% CI 0.01-0.07). Moderator analysis for depression and psychological distress identified stronger associations with perceived crime measurement and weaker in studies adjusted for area-level deprivation. Importantly, even after accounting for study characteristics, neighbourhood crime remained significantly linked to depression and psychological distress. Findings on anxiety and psychosis were limited due to low number of included studies. CONCLUSIONS: Neighbourhood crime is an important contextual predictor of mental health with implications for prevention and policy. Area-based crime interventions targeting the determinants of crime, prevention and service allocation to high crime neighbourhoods may have public mental health benefits. Future research should investigate the causal pathways between crime exposure and mental health, identify vulnerably groups and explore policy opportunities for buffering against the detrimental effect of neighbourhood stressors.

Antenatal Exposure to UV-B Radiation and Preeclampsia: A Retrospective Cohort Study.

Background Risk of preeclampsia varies by month of delivery. We tested whether this seasonal patterning may be mediated through maternal vitamin D concentration using antenatal exposure to UV-B radiation as an instrumental variable. Methods and Results Scottish maternity records were linked to antenatal UV-B exposure derived from satellites between 2000 and 2010. Logistic regression analyses were used to explore the association between UV-B and preeclampsia, adjusting for the potential confounding effects of month of conception, child's sex, gestation, parity, and mean monthly temperature. Of the 522 896 eligible singleton deliveries, 8689 (1.66%) mothers developed preeclampsia. Total antenatal UV-B exposure ranged from 43.18 to 101.11 kJ/m2 and was associated with reduced risk of preeclampsia with evidence of a dose-response relationship (highest quintile of exposure: adjusted odds ratio, 0.57; 95% CI, 0.44-0.72; P<0.001). Associations were demonstrated for UV-B exposure in all 3 trimesters. Conclusions The seasonal patterning of preeclampsia may be mediated through low maternal vitamin D concentration in winter resulting from low UV-B radiation. Interventional studies are required to determine whether vitamin D supplements or UV-B-emitting light boxes can reduce the seasonal patterning of preeclampsia.

Air Pollution, housing and respirfatory tract Infections in Children: NatIonal birth Cohort study (PICNIC): study protocol.

INTRODUCTION: Respiratory tract infections (RTIs) are the most common reason for hospital admission among children <5 years in the UK. The relative contribution of ambient air pollution exposure and adverse housing conditions to RTI admissions in young children is unclear and has not been assessed in a UK context. METHODS AND ANALYSIS: The aim of the PICNIC study (Air Pollution, housing and respiratory tract Infections in Children: NatIonal birth Cohort Study) is to quantify the extent to which in-utero, infant and childhood exposures to ambient air pollution and adverse housing conditions are associated with risk of RTI admissions in children <5 years old. We will use national administrative data birth cohorts, including data from all children born in England in 2005-2014 and in Scotland in 1997-2020, created via linkage between civil registration, maternity and hospital admission data sets. We will further enhance these cohorts via linkage to census data on housing conditions and socioeconomic position and small area-level data on ambient air pollution and building characteristics. We will use time-to-event analyses to examine the association between air pollution, housing characteristics and the risk of RTI admissions in children, calculate population attributable fractions for ambient air pollution and housing characteristics, and use causal mediation analyses to explore the mechanisms through which housing and air pollution influence the risk of infant RTI admission. ETHICS, EXPECTED IMPACT AND DISSEMINATION: To date, we have obtained approval from six ethics and information governance committees in England and two in Scotland. Our results will inform parents, national and local governments, the National Health Service and voluntary sector organisations of the relative contribution of adverse housing conditions and air pollution to RTI admissions in young children. We will publish our results in open-access journals and present our results to the public via parent groups and social media and on the PICNIC website. Code and metadata will be published on GitHub.

Is place or person more important in determining higher rural cancer mortality? A data-linkage study to compare individual versus area-based measures of deprivation.

Data from Northeast Scotland for 11,803 cancer patients (diagnosed 2007-13) were linked to UK Censuses to explore relationships between hospital travel-time, timely-treatment and one-year-mortality, adjusting for both area and individual-level socioeconomic status (SES). Adjusting for area-based SES, those living >60 minutes from hospital received timely-treatment more often than those living <15 minutes. Substituting individual-level SES changed little. Adjusting for area-based SES those living >60 minutes from hospital died within one year more often than those living <15 minutes. Again, substituting individual-level SES changed little. In Northeast Scotland distance to services, rather than individual SES, likely explains poorer rural cancer survival. BACKGROUND AND OBJECTIVE: The Northeast and Aberdeen Scottish Cancer and Residence (NASCAR) study found rural-dwellers are treated quicker but more likely to die within a year of a cancer diagnosis. A potential confounder of the relationship between geography and cancer mortality is socioeconomic status (SES). We linked the original NASCAR cohort to the UK Censuses of 2001 and 2011, at an individual level, to explore the relationship between travel time to key healthcare facilities, timely cancer treatment and one-year mortality adjusting for both area and individual-level markers of socioeconomic status. METHODS: A data linkage study of 11803 patients examined the association between travel times, timely treatment and one-year mortality with adjustment for area, and for individual-level, markers of socioeconomic status. RESULTS: Following adjustment for area-based SES measures those living more than 60 minutes from the cancer treatment centre were significantly more likely to be treated within 62 days of GP referral than those living within 15 minutes (Odds Ratio [OR]) 1.41; 95% (Confidence Interval [CI]) 1.23, 1.60]. Replacing area-based with individual-level SES measures from UK Censuses made little impact on the results [OR 1.39; 95% CI 1.22, 1.57].Following adjustment for area-based SES measures of socioeconomic status those living more than 60 minutes from the cancer treatment centre were significantly more likely to die within one year than those living closer by [OR 1.22; 95% CI 1.08, 1.38]. Again, replacing area-based with individual-level SES measures from UK Censuses made little impact on the result [OR 1.20; CI 1.06, 1.35]. CONCLUSIONS: Distribution of individual measures of socioeconomic status did not differ significantly between rural and urban cancer patients. The relationship between distance to service, timely treatment and one-year survival were the same adjusting for both area-based and individual SES. Overall, it seems that distance to services, rather than personal characteristics, influences poorer rural cancer survival.

A data linkage study of the effects of the Great Recession and austerity on antidepressant prescription usage.

BACKGROUND: International literature shows unemployment and income loss during the Great Recession worsened population mental health. This individual-level longitudinal study examines how regional economic trends and austerity related to depression using administrative prescription data for a large and representative population sample. METHODS: Records from a sample of the Scottish Longitudinal Study (N=86 500) were linked to monthly primary care antidepressant prescriptions (2009-15). Regional economic trends were characterized by annual full-time employment data (2004-14). Economic impact of austerity was measured via annual income lost per working age adult due to welfare reforms (2010-15). Sequence analysis identified new cases of antidepressant use, and group-based trajectory modelling classified regions into similar economic trajectories. Multi-level logistic regression examined relationships between regional economic trends and new antidepressant prescriptions. Structural equation mediation analysis assessed the contributory role of welfare reforms. RESULTS: Employed individuals living in regions not recovering post-recession had the highest risk of beginning a new course of antidepressants (AOR 1.23; 95% CI 1.08-1.38). Individuals living in areas with better recovery trajectories had the lowest risk. Mediation analyses showed that 50% (95% CI 7-61%) of this association was explained by the impact of welfare benefit reforms on average incomes. CONCLUSIONS: Following the Great Recession, local labour market decline and austerity measures were associated with growing antidepressant usage, increasing regional inequalities in mental health. The study evidences the impact of austerity on health inequalities and suggests that economic conditions and welfare policies impact on population health. Reducing the burden of mental ill-health primarily requires action on the social determinants.