Reducing the impact of the coronavirus on disadvantaged migrants and ethnic minorities.

Studies from several countries have shown that the COVID-19 pandemic has disproportionally affected migrants. Many have numerous risk factors making them vulnerable to infection and poor clinical outcome. Policies to mitigate this effect need to take into account public health principles of inclusion, universal health coverage and the right to health. In addition, the migrant health agenda has been compromised by the suspension of asylum processes and resettlement, border closures, increased deportations and lockdown of camps and excessively restrictive public health measures. International organizations including the World Health Organization and the World Bank have recommended measures to actively counter racism, xenophobia and discrimination by systemically including migrants in the COVID-19 pandemic response. Such recommendations include issuing additional support, targeted communication and reducing barriers to accessing health services and information. Some countries have had specific policies and outreach to migrant groups, including facilitating vaccination. Measures and policies targeting migrants should be evaluated, and good models disseminated widely.

Neonatal mortality rates, characteristics, and risk factors for neonatal deaths in Ghana: analyses of data from two health and demographic surveillance systems.

BACKGROUND: Reducing neonatal mortality rates (NMR) in developing countries is a key global health goal, but weak registration systems in the region stifle public health efforts. OBJECTIVE: To calculate NMRs, investigate modifiable risk factors, and explore neonatal deaths by place of birth and death, and cause of death in two administrative areas in Ghana. METHODS: Data on livebirths were extracted from the health and demographic surveillance systems in Navrongo (2004-2012) and Kintampo (2005-2010). Cause of death was determined from neonatal verbal autopsy forms. Univariable and multivariable logistic regression were used to analyse factors associated with neonatal death. Multiple imputations were used to address missing data. RESULTS: The overall NMR was 18.8 in Navrongo (17,016 live births, 320 deaths) and 12.5 in Kintampo (11,207 live births, 140 deaths). The annual NMR declined in both areas. 54.7% of the births occurred in health facilities. 70.9% of deaths occurred in the first week. The main causes of death were infection (NMR 4.3), asphyxia (NMR 3.7) and prematurity (NMR 2.2). The risk of death was higher among hospital births than home births: Navrongo (adjusted OR 1.14, 95% CI: 1.03-1.25, p = 0.01); Kintampo (adjusted OR 1.76, 95% CI: 1.55-2.00, p < 0.01). However, a majority of deaths occurred at home (Navrongo 61.3%; Kintampo 50.7%). Among hospital births dying in hospital, the leading cause of death was asphyxia; among hospital and home births dying at home, it was infection. CONCLUSION: The NMR in these two areas of Ghana reduced over time. Preventing deaths by asphyxia and infection should be prioritised, centred respectively on improving post-delivery care in health facilities and subsequent post-natal care at home.

Migration, ethnicity, racism and the COVID-19 pandemic: A conference marking the launch of a new Global Society.

The inaugural conference of the Global Society on Migration, Ethnicity, Race and Health COVID-19 examined the impact of the COVID-19 pandemic on migrants and ethnic minorities and the role of racism. Migrants everywhere have faced tightening immigration restrictions, more obstacles to healthcare, increased racism and worsening poverty. Higher COVID-19 mortality rates have been otbserved in ethnic/racial minorities in the United Kingdom and the United States. Structural racism has been implicated, operating, for example, through more crowded living conditions and higher-risk occupations. In Brazil, good data are lacking but a seroprevalence survey suggested higher rates of infection among ethnic minorities and slum dwellers. Considerable disruption of services for migrants at the border with Venezuela have occurred. National policy responses to protect vulnerable groups have been lacking. In Australia, with strict COVID-19 control metrtrun 0asures and inclusive policies, there have been few cases and deaths reported in Indigenous communities so far. In most countries, the lack of COVID-19 data by ethnic/racial group or migrant status should be addressed. Otherwise, racism and consequent inequalities will go undetected.

Assessment of health care, hospital admissions, and mortality by ethnicity: population-based cohort study of health-system performance in Scotland.

BACKGROUND: Ethnic minorities often experience barriers to health care. We studied six established quality indicators of health-system performance across ethnic groups in Scotland. METHODS: In this population-based cohort study, we linked ethnicity from Scotland's Census 2001 (April 29, 2001) to hospital admissions and mortality records, with follow-up until April 30, 2013. Indicators of health-system performance included amenable deaths (ie, deaths avertable by effective treatment), preventable deaths (ie, deaths avertable by public health policy), avoidable deaths (combined amenable and preventable deaths), avoidable hospital admissions, unplanned readmissions, and length of stay. We calculated rate ratios and odds ratios (with 95% CIs) using Poisson and logistic regression, which we multiplied by 100, adjusting first for age-related covariates and then for socioeconomic-related and birthplace-related covariates. The white Scottish population was the reference (rate ratio [RR] 100). FINDINGS: The results are based on 4·61 million people. During the 50·5 million person-years of study, 1·17 million avoidable hospital admissions, 587 740 unplanned readmissions, and 166 245 avoidable deaths occurred. South Asian groups had higher avoidable hospital admissions than the white Scottish group, with the highest reported RRs in Pakistani groups (RR 140·6 [95% CI 131·9-150·0] in men; RR 141·0 [129·0-154·1] in women). There was little variation between ethnic groups in length of stay or unplanned readmission. Preventable and amenable mortality were higher in the white Scottish group than several ethnic minorities including other white British, other white, Indian, and Chinese groups. Such differences were partly diminished by adjustment for socioeconomic status, whereas adjustment for country of birth had little additional effect. INTERPRETATION: These data suggest concerns about the access to and quality of primary care to prevent avoidable hospital admissions, especially for south Asians. Relatively high preventable and amenable deaths in white Scottish people, compared with several ethnic minority populations, were unexpected. Future studies should both corroborate and examine explanations for these patterns. Studies using several indicators simultaneously are also required internationally. FUNDING: Chief Scientist's Office, Medical Research Council, NHS Research Scotland, Farr Institute.

Mortality, ethnicity, and country of birth on a national scale, 2001-2013: A retrospective cohort (Scottish Health and Ethnicity Linkage Study).

BACKGROUND: Migrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth. METHODS AND FINDINGS: We linked the Scottish 2001 Census to mortality data (2001-2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI. CONCLUSIONS: There was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities.

Is the linkage of census and health data justified? Views from a public panel of the Scottish Health and Ethnicity Linkage study.

Background: Using routine health data for research aimed at improving health requires the public's awareness and trust. The Scottish Health and Ethnicity Linkage study explores variations in health between ethnic groups. We aimed to establish a public panel to obtain their views on its methods, findings and dissemination, including use of routine health data without individual opt-in consent. Methods: Adult applicants were sought via a range of sources, aiming for a balance of age, gender and ethnicity. Three half-day meetings were held in 2015-16. Discussion covered the study's aims and governance; record linkage methods; data security; main findings, dissemination and publication processes. Results: Of 29 applicants, 19 joined the panel. Panellists were from 10 ethnic groups, 11 were females, ages 29-69 years. With some reservations, they enjoyed the meetings. After methods and security were explained, they unanimously accepted the study's use of linked data without individual opt-in consent. They thought explaining such complex methods to the general public was difficult. They recommended more should be done to communicate study findings to the public, practitioners and policy makers. Conclusions: The panellists' support for the study methods was reassuring. Their recommendations have led to the implementation of a wider dissemination plan.

Life expectancy of different ethnic groups using death records linked to population census data for 4.62 million people in Scotland.

BACKGROUND: Few countries record the data needed to estimate life expectancy by ethnic group. Such information is helpful in assessing the extent of health inequality. METHOD: Life tables were created using 3 years of deaths (May 2001-April 2004) linked to Scottish 2001 Census data for 4.62 million individuals with self-reported ethnicity. We created 8 ethnic groups based on the census definitions, each with at least 5000 individuals and 40 deaths. Life expectancy at birth was calculated using the revised Chiang method. RESULTS: The life expectancy of White Scottish males at birth was 74.7 years (95% CI 74.6 to 74.8), similar to Mixed Background (73.0; 70.2 to 75.8) and White Irish (75.0; 74.0 to 75.9), but shorter than Indian (80.9; 78.4 to 83.4), Pakistani (79.3; 76.9 to 81.6), Chinese (79.0; 76.5 to 81.5), Other White British (78.9; 78.6 to 79.2) and Other White (77.2; 76.4 to 78.1). The life expectancy of White Scottish females was 79.4 years (79.3 to 79.5), similar to mixed background (79.3; 76.6 to 82.0), but shorter than Pakistani (84.6; 82.0 to 87.3), Chinese (83.4; 81.1 to 85.7), Indian (83.3; 80.7 to 85.9), Other White British (82.6; 82.3 to 82.9), other White (82.0; 81.3 to 82.8) and White Irish (81; 80.2 to 81.8). CONCLUSIONS: Males and females in most of the larger ethnic minority groups in Scotland have longer life expectancies than the majority White Scottish population.

Comparing the impact of personal and parental risk factors, and parental lifespan on all-cause mortality and cardiovascular disease: findings from the Midspan Family cohort study.

BACKGROUND: We aimed to identify which personal and parental factors best explained all-cause mortality and cardiovascular disease (CVD). METHODS: In 1996, data were collected on 2338 adult offspring of the participants in the 1972-1976 Renfrew and Paisley prospective cohort study. Recorded risk factors were assigned to 5 groups: mid-life biological and behavioural (BB), mid-life socioeconomic, parental BB, early-life socioeconomic and parental lifespan. Participants were followed up for mortality and hospital admissions to the end of 2011. Cox proportional hazards models were used to analyse how well each group explained all-cause mortality or CVD. Akaike's Information Criterion (AIC), a measure of goodness-of-fit, identified the most important groups. RESULTS: For all-cause mortality (1997 participants with complete data, 111 deaths), decreases in AIC from the null model (adjusting for age and sex) to models including mid-life BB, mid-life socioeconomic, parental BB, early-life socioeconomic and parental lifespan were 55.8, 21.6, 10.3, 7.3 and 5.9, respectively. For the CVD models (1736 participants, 276 with CVD), decreases were 37.8, 3.7, 6.7, 17.3 and 0.4. Mid-life BB factors were the most important for both all-cause mortality and CVD; mid-life socioeconomic factors were important for all-cause mortality, and early-life socioeconomic factors were important for CVD. Parental lifespan was the weakest factor. CONCLUSIONS: As mid-life BB risk factors best explained all-cause mortality and CVD, continued action to reduce these is warranted. Targeting adverse socioeconomic factors in mid-life and early life may contribute to reducing all-cause mortality and CVD risk, respectively.

Does smoking reduction in midlife reduce mortality risk? Results of 2 long-term prospective cohort studies of men and women in Scotland.

A long-term cohort study of working men in Israel found that smokers who reduced their cigarette consumption had lower subsequent mortality rates than those who did not. We conducted comparable analyses in 2 populations of smokers in Scotland. The Collaborative Study included 1,524 men and women aged 40-65 years in a working population who were screened twice, in 1970-1973 and 1977. The Renfrew/Paisley Study included 3,730 men and women aged 45-64 years in a general population who were screened twice, in 1972-1976 and 1977-1979. Both groups were followed up through 2010. Subjects were categorized by smoking intensity at each screening as smoking 0, 1-10, 11-20, or ≥21 cigarettes per day. At the second screening, subjects were categorized as having increased, maintained, or reduced their smoking intensity or as having quit smoking between the first and second screenings. There was no evidence of lower mortality in all reducers compared with maintainers. Multivariate adjusted hazard ratios of mortality were 0.91 (95% confidence interval (CI): 0.75, 1.10) in the Collaborative Study and 1.08 (95% CI: 0.97, 1.20) in the Renfrew/Paisley Study. There was clear evidence of lower mortality among quitters in both the Collaborative Study (hazard ratio = 0.66, 95% CI: 0.56, 0.78) and the Renfrew/Paisley Study (hazard ratio = 0.75, 95% CI: 0.67, 0.84). In the Collaborative Study only, we observed lower mortality similar to that of quitters among heavy smokers (≥21 cigarettes/day) who reduced their smoking intensity. These inconclusive results support the view that reducing cigarette consumption should not be promoted as a means of reducing mortality, although it may have a valuable role as a step toward smoking cessation.

Set points, settling points and some alternative models: theoretical options to understand how genes and environments combine to regulate body adiposity.

The close correspondence between energy intake and expenditure over prolonged time periods, coupled with an apparent protection of the level of body adiposity in the face of perturbations of energy balance, has led to the idea that body fatness is regulated via mechanisms that control intake and energy expenditure. Two models have dominated the discussion of how this regulation might take place. The set point model is rooted in physiology, genetics and molecular biology, and suggests that there is an active feedback mechanism linking adipose tissue (stored energy) to intake and expenditure via a set point, presumably encoded in the brain. This model is consistent with many of the biological aspects of energy balance, but struggles to explain the many significant environmental and social influences on obesity, food intake and physical activity. More importantly, the set point model does not effectively explain the 'obesity epidemic'--the large increase in body weight and adiposity of a large proportion of individuals in many countries since the 1980s. An alternative model, called the settling point model, is based on the idea that there is passive feedback between the size of the body stores and aspects of expenditure. This model accommodates many of the social and environmental characteristics of energy balance, but struggles to explain some of the biological and genetic aspects. The shortcomings of these two models reflect their failure to address the gene-by-environment interactions that dominate the regulation of body weight. We discuss two additional models--the general intake model and the dual intervention point model--that address this issue and might offer better ways to understand how body fatness is controlled.

Cause specific mortality, social position, and obesity among women who had never smoked: 28 year cohort study.

OBJECTIVE: To investigate the relations between causes of death, social position, and obesity in women who had never smoked. DESIGN: Prospective cohort study. SETTING: Renfrew and Paisley, Scotland. PARTICIPANTS: 8353 women and 7049 men aged 45-64 were recruited to the Renfrew and Paisley Study in 1972-6. Of these, 3613 women had never smoked and were the focus of this study. They were categorised by occupational class (I and II, III non-manual, III manual, and IV and V) and body mass index groups (normal weight, overweight, moderately obese, and severely obese). MAIN OUTCOME MEASURES: All cause and cause specific mortality during 28 years of follow-up by occupational class and body mass index, using Cox proportional hazards models adjusted for age and other confounders. RESULTS: The women in lower occupational classes who had never smoked were on average shorter and had poorer lung function and higher systolic blood pressure than women in the higher occupational classes. Overall, 43% (n = 1555) were overweight, 14% (n = 515) moderately obese, and 5% (n = 194) severely obese. Obesity rates were higher in lower occupational classes and much higher in all occupational classes than in current smokers in the full cohort. Half the women died, 51% (n = 916) from cardiovascular disease and 27% (n = 487) from cancer. Relative to occupational class I and II, all cause mortality rates were more than a third higher in occupational classes III manual (relative rate 1.35, 95% confidence interval 1.16 to 1.57) and IV and V (1.34, 1.17 to 1.55) and largely explained by differences in obesity, systolic blood pressure, and lung function. Similar upward gradients were seen for cardiovascular disease and respiratory disease but not for cancer. Mortality rates were highest in severely obese women in the lowest occupational classes. CONCLUSIONS: Women who had never smoked and were not obese had the lowest mortality rates, regardless of their social position. Where obesity is socially patterned as in this cohort, it may contribute to health inequalities and increase pressure on health and social services serving more disadvantaged populations.

The combined effect of smoking tobacco and drinking alcohol on cause-specific mortality: a 30 year cohort study.

BACKGROUND: Smoking and consuming alcohol are both related to increased mortality risk. Their combined effects on cause-specific mortality were investigated in a prospective cohort study. METHODS: Participants were 5771 men aged 35-64, recruited during 1970-73 from various workplaces in Scotland. Data were obtained from a questionnaire and a screening examination. Causes of death were all cause, coronary heart disease (CHD), stroke, alcohol-related, respiratory and smoking-related cancer. Participants were divided into nine groups according to their smoking status (never, ex or current) and reported weekly drinking (none, 1-14 units and 15 or more). Cox proportional hazards models were used to obtain relative rates of mortality, adjusted for age and other risk factors. RESULTS: In 30 years of follow-up, 3083 men (53.4%) died. Compared with never smokers who did not drink, men who both smoked and drank 15+ units/week had the highest all-cause mortality (relative rate = 2.71 (95% confidence interval 2.31-3.19)). Relative rates for CHD mortality were high for current smokers, with a possible protective effect of some alcohol consumption in never smokers. Stroke mortality increased with both smoking and alcohol consumption. Smoking affected respiratory mortality with little effect of alcohol. Adjusting for a wide range of confounders attenuated the relative rates but the effects of alcohol and smoking still remained. Premature mortality was particularly high in smokers who drank 15 or more units, with a quarter of the men not surviving to age 65. 30% of men with manual occupations both smoked and drank 15+ units/week compared with only 13% with non-manual ones. CONCLUSIONS: Smoking and drinking 15+ units/week was the riskiest behaviour for all causes of death.

Effect of tobacco smoking on survival of men and women by social position: a 28 year cohort study.

OBJECTIVE: To assess the impact of tobacco smoking on the survival of men and women in different social positions. DESIGN: A cohort observational study. SETTING: Renfrew and Paisley, two towns in west central Scotland. PARTICIPANTS: 8353 women and 7049 men aged 45-64 years recruited in 1972-6 (almost 80% of the population in this age group). The cohort was divided into 24 groups by sex (male, female), smoking status (current, former, or never smokers), and social class (classes I + II, III non-manual, III manual, and IV + V) or deprivation category of place of residence. MAIN OUTCOME MEASURE: Relative mortality (adjusted for age and other risk factors) in the different groups; Kaplan-Meier survival curves and survival rates at 28 years. RESULTS: Of those with complete data, 4387/7988 women and 4891/6967 men died over the 28 years. Compared with women in social classes I + II who had never smoked (the group with lowest mortality), the adjusted relative mortality of smoking groups ranged from 1.7 (95% confidence interval 1.3 to 2.3) to 4.2 (3.3 to 5.5). Former smokers' mortalities were closer to those of never smokers than those of smokers. By social class (highest first), age adjusted survival rates after 28 years were 65%, 57%, 53%, and 56% for female never smokers; 41%, 42%, 33%, and 35% for female current smokers; 53%, 47%, 38%, and 36% for male never smokers; and 24%, 24%, 19%, and 18% for male current smokers. Analysis by deprivation category gave similar results. CONCLUSIONS: Among both women and men, never smokers had much better survival rates than smokers in all social positions. Smoking itself was a greater source of health inequality than social position and nullified women's survival advantage over men. This suggests the scope for reducing health inequalities related to social position in this and similar populations is limited unless many smokers in lower social positions stop smoking.

Changes in exposure of adult non-smokers to secondhand smoke after implementation of smoke-free legislation in Scotland: national cross sectional survey.

OBJECTIVE: To measure change in adult non-smokers' exposure to secondhand smoke in public and private places after smoke-free legislation was implemented in Scotland. DESIGN: Repeat cross sectional survey. SETTING: Scotland. PARTICIPANTS: Scottish adults, aged 18 to 74 years, recruited and interviewed in their homes. INTERVENTION: Comprehensive smoke-free legislation that prohibits smoking in virtually all enclosed public places and workplaces, including bars, restaurants, and cafes. OUTCOME MEASURES: Salivary cotinine, self reported exposure to smoke in public and private places, and self reported smoking restriction in homes and in cars. RESULTS: Overall, geometric mean cotinine concentrations in adult non-smokers fell by 39% (95% confidence interval 29% to 47%), from 0.43 ng/ml at baseline to 0.26 ng/ml after legislation (P<0.001). In non-smokers from non-smoking households, geometric mean cotinine concentrations fell by 49% (40% to 56%), from 0.35 ng/ml to 0.18 ng/ml (P<0.001). The 16% fall in cotinine concentrations in non-smokers from smoking households was not statistically significant. Reduction in exposure to secondhand smoke was associated with a reduction after legislation in reported exposure to secondhand smoke in public places (pubs, other workplaces, and public transport) but not in homes and cars. We found no evidence of displacement of smoking from public places into the home. CONCLUSIONS: Implementation of Scotland's smoke-free legislation has been accompanied within one year by a large reduction in exposure to secondhand smoke, which has been greatest in non-smokers living in non-smoking households. Non-smokers living in smoking households continue to have high levels of exposure to secondhand smoke.