Clustering of behavioural risk factors for health in UK adults in 2016: a cross-sectional survey

Co-occurrence of behavioural risk factors for non-communicable diseases among 40-year and above aged community members in three regions of Myanmar

Background

Risky behaviours such as smoking, alcohol consumption, physical inactivity and inadequate consumption of fruits and vegetables are known contributing factors for non-communicable diseases (NCDs) which account for 74% of global mortality. Such behavioural risk factors co-occur frequently resulting in synergistic action for developing NCD related morbidity and mortality. This study aims to assess the existence of multiple risk behaviours and determine the socio-economic and demographic factors associated with co-occurrence of behavioural risks among Myanmar adult population.

Method

Data were collected, in the context of the SUNI-SEA project (Scaling Up NCD interventions in Southeast Asia), from 660 community members aged 40 years and above of both sexes, residing in selected urban and rural areas from Ayeyawaddy, Yangon and Mandalay regions of Myanmar. The co-occurrence of behavioural risk factors was presented as percentage with 95% CI and its determinants were identified by multinomial logistic regression.

Results

The co-occurrence of two risk behaviours and three or four risk behaviours were found in 40% (95% CI: 36.2%, 43.9%) and 10.8% (95% CI: 8.5%, 13.4%) respectively. Urban residents, men, participants without formal schooling and unemployed persons were more likely to exhibit co-occurrence of two risk behaviors and three or four risk behaviours.

Conclusion

The current study shows high prevalence of co-occurrence of behavioural risk factors among Myanmar adults in the study area. NCD prevention and control programs emphasizing management of behavioural risks should be intensively promoted, particularly directed towards multiple behavioural risk factors, and not focused on individual factors only.

Clustering and trajectories of key noncommunicable disease risk factors in Norway: the NCDNOR project

Noncommunicable diseases (NCDs) are a leading cause of premature death globally and have common preventable risk factors. In Norway, the NCDNOR-project aims at establishing new knowledge in the prevention of NCDs by combining information from national registries with data from population-based health studies. In the present study, we aimed to harmonize data on key NCD risk factors from the health studies, describe clustering of risk factors using intersection diagrams and latent class analysis, and identify long-term risk factor trajectories using latent class mixed models. The harmonized study sample consisted of 808,732 individuals (1,197,158 participations). Two-thirds were exposed to ≥ 1 NCD risk factor (daily smoking, physical inactivity, obesity, hypertension, hypercholesterolaemia or hypertriglyceridaemia). In individuals exposed to ≥ 2 risk factors (24%), we identified five distinct clusters, all characterized by fewer years of education and lower income compared to individuals exposed to < 2 risk factors. We identified distinct long-term trajectories of smoking intensity, leisure-time physical activity, body mass index, blood pressure, and blood lipids. Individuals in the trajectories tended to differ across sex, education, and body mass index. This provides important insights into the mechanisms by which NCD risk factors can occur and may help the development of interventions aimed at preventing NCDs.

Clustering of the Adult Population According to Behavioural Health Risk Factors as the Focus of Community-Based Public Health Interventions in Poland

Effective lifestyle health promotion interventions require the identification of groups sharing similar behavioural risk factors (BRF) and socio-demographic characteristics. This study aimed to identify these subgroups in the Polish population and check whether local authorities' health programmes meet their needs. Population data came from a 2018 question survey on a random representative sample of 3000 inhabitants. Four groups were identified with the TwoStep cluster analysis method. One of them ("Multi-risk") differed from the others and the general population by a high prevalence of numerous BRF: 59% [95% confidence interval: 56-63%] of its members smoke, 35% [32-38%] have alcohol problems, 79% [76-82%] indulge in unhealthy food, 64% [60-67%] do not practice recreational physical activity, and 73% [70-76%] are overweight. This group, with an average age of 50, was characterised by an excess of males (81% [79-84%]) and people with basic vocational education (53% [50-57%]). In 2018, only 40 out of all 228 health programmes in Poland addressed BRF in adults; only 20 referred to more than one habit. Moreover, access to these programmes was limited by formal criteria. There were no programmes dedicated to the reduction of BRF exclusively. The local governments focused on improving access to health services rather than on a pro-health change in individual behaviours.

Clustering of Health and Oral Health-Compromising Behaviours in Army Personnel in Central Peninsular Malaysia

Health- and oral health-compromising behaviours (HOHCBs) impact the health readiness of military personnel, resulting in decreased fitness performance, thus affecting combat readiness. This study aimed to identify the clustering patterns and number of HOHCBs in army personnel in Central Peninsular Malaysia. Thus, a cross-sectional study using a multistage sampling technique and a validated 42-item online questionnaire was conducted to assess ten health (medical screening, physical activity, sedentary lifestyle, smoking status, alcohol consumption, substance abuse, aggressive behaviours, sleep, and road safety habits) and five oral health behaviour domains (tooth brushing, fluoridated toothpaste use, flossing, dental visits, and bruxism). Each HOHCB was dichotomised into healthy and health-compromising behaviour and analysed using hierarchical agglomerative cluster analysis (HACA). With the majority being males (92.5%), of other ranks (96.8%), and healthy (83.9%), 2435 army members of a mean age of 30.3 years (SD = 5.9) participated, with a response rate of 100%. HACA identified two clustering patterns: (i) 'high-risk behaviours' (30 HOHCBs) and (ii) 'most common risk behaviours' (12 HOHCBs) with a mean clustering number of 14.1 (SD = 4.1). In conclusion, army personnel in Central Peninsular Malaysia displayed 2 broad HOHCB clustering patterns, 'high-risk' and 'most common risk', with an average of 14 HOHCB clusters per person.

Effects of lifestyle risk behaviour clustering on cardiovascular disease among UK adults: latent class analysis with distal outcomes

Lifestyle risk behaviours such as smoking, physical inactivity, and unhealthy diet account for a considerable disease burden globally. These risk behaviours tend to cluster within an individual, which could have detrimental health effects. In this study, we aimed to examine the clustering effect of lifestyle risk behaviours on cardiovascular disease (CVD) and CVD risk among adults in the United Kingdom (UK). We performed a latent class (LC) analysis with distal outcomes using the UK Biobank baseline (2006-2010) data. First, we estimated LC measurement models, followed by an auxiliary model conditional on LC variables. We reported continuous (mean difference-MD) and binary (odds ratio-OR) outcomes with 95% confidence intervals. We included 283,172 and 174,030 UK adults who had data on CVD and CVD risk, respectively. Multiple lifestyle risk behaviour clustering (physically inactive, poor fruit & vegetable intake, high alcohol intake, and prolonged sitting) had a 3.29 mean increase in CVD risk compared to high alcohol intake. In addition, adults with three risk behaviours (physically inactive, poor fruit & vegetable intake, and high alcohol intake) had 25.18 higher odds of having CVD than those with two risk behaviours (physically inactive, and poor fruit and vegetable intake). Social deprivation, gender and age were also associated with CVD. Individuals' LC membership with two or more lifestyle risk behaviours negatively affects CVD. Interventions targeting multiple lifestyle behaviours and social circumstances should be prioritized to reduce the CVD burden.

First Report on the Co-Occurrence and Clustering Profiles of Cardiovascular Lifestyle Risk Factors among Adults in Burkina Faso

The co-occurrence of cardiovascular risk factors is usually associated with a higher risk of cardiovascular disease (CVD) or cancer. This study aimed to determine the prevalence of the co-occurrence and its determinants and to identify the clustering profiles of lifestyle risk factors among the adult population in Burkina Faso. Among 4692 participants, 4377 adults from the first STEPS survey conducted in Burkina Faso were considered in this analysis. Four lifestyle risk factors (smoking, alcohol consumption, inadequate fruit and vegetable intake and low physical activity) were analysed. The clustering was evaluated using the observed/expected (O/E) ratio approach. To identify the determinants of co-occurrence, we performed a modified Poisson regression. The prevalence of the co-occurrence of two or more cardiovascular lifestyle risk factors was 46.4% (95% CI: 43.1–49.7). The main determinants of the co-occurrence were being male (adjusted prevalence ratio (aPR): 1.27 (95% CI: 1.16–1.38)), advanced age (55–64 years old: aPR: 1.45 (95% CI: 1.31–1.60)) and a high level of education (aPR: 1.29 (95% CI: 1.09–1.52)). The clustering profile for lifestyle risk factors was tobacco consumption combined with alcohol consumption (O/E: 2.77 (95% CI: 2.12–3.56)), and concurrent involvement in all four lifestyle risk factors (O/E = 1.51 (95% CI: 1.19–1.89)). This first population-based report on the co-occurrence of lifestyle risk factors calls for action to tailor health-promoting interventions to increase healthy lifestyle behaviors. The identified CVD-risk clustering should be considered as an important step in this strategy development in Burkina Faso.

A latent class analysis of health risk behaviours in the UK Police Service and their associations with mental health and job strain

BACKGROUND

Health risk behaviours (e.g., harmful drinking and smoking) often cluster together and can be associated with poor mental health and stress. This study examined how health risk behaviours cluster together in individuals in a high stress occupation (UK Police Service), and the associations with mental health and job strain.

METHODS

Data was obtained from the Airwave Health Monitoring Study (25,234 male and 14,989 female police employees), which included measures of health risk behaviours (alcohol use, diet, smoking status, physical activity), poor mental health (depression, anxiety, post-traumatic stress disorder [PTSD]), and job strain (low, high, active, passive). Classes of health risk behaviours were identified using Latent Class Analysis (LCA) and the associations with mental health and job strain were analysed through multinomial logistic regressions.

RESULTS

For men and women, a 5-class solution was the best fit. Men and women with depression, anxiety, and/or PTSD (analysed as separate variables) had at least double the odds of being assigned to the "high health risk behaviours" class, compared to those with no mental health problem. Compared to those reporting low strain, men and women reporting high strain had increased odds of being assigned to the "low risk drinkers with other health risk behaviours" classes.

CONCLUSIONS

These finding highlight the importance of holistic interventions which target co-occurring health risk behaviours, to prevent more adverse physical health consequences. Police employees with poor mental health are more likely to engage in multiple health risk behaviours, which suggests they may need additional support. However, as the data was cross-sectional, the temporal associations between the classes and mental health or job strain could not be determined.

Physical and social environmental factors related to co-occurrence of unhealthy lifestyle behaviors

Previous work identifying determinants of co-occurrence of behavioral risk factors have focused on their association with individuals' characteristics with scant attention paid to their relationship to contextual factors. Data came from 21,007 individuals ≥15 years of age who participated in the cross-sectional 2011-2012 Spanish National Health Survey. Two indicators were defined by tobacco consumption, alcohol intake, diet, physical activity, and body mass index. The first indicator, based on dichotomized measures, ranges from 0 to 5. The second one (unhealthy lifestyle index), ranges from 0 to 15, with 0 denoting the healthiest score. Among the determinants, we examined social support, five perceived characteristics of the neighborhood, and the socioeconomic deprivation index of the census tract of residence. Data were analyzed using multilevel linear and logistic regression models adjusted for the main sociodemographic characteristics. Using the dichotomized indicator, the probability of having 3-5 risk factors versus <3 factors was associated with low social support (Odds Ratio [OR] 1.50; 95% Confidence Interval [CI]: 1.25-1.80). Issues surrounding neighborhood cleanliness (OR = 1.18; 95%CI: 1.04-1.33), air pollution (OR = 1.38; 95%CI: 1.16-1.64), and street crime (OR = 1.21; 95%CI: 1.03-1.42) were associated with determinants of co-occurrence. Risk factors co-occurrence increased as deprivation level increased: the OR for the highest deprivation quintile versus the lowest was 1.30 (95%CI: 1.14-1.48). Similar results were observed when using the unhealthy lifestyle index. Poorer physical and social environments are related to greater co-occurrence of risk factors for chronic diseases. Health promotion interventions targeting the prevention of risk factors should consider the contextual characteristics of the neighborhood environment.

Health behaviors and subsequent mental health problems during the COVID-19 pandemic: A longitudinal analysis of adults in the UK

Introduction

Public health mitigation policies aimed at slowing the spread of COVID-19 led to an increase in mental health problems (MHPs). This study examines the association between multiple pre-pandemic health behaviors and MHPs prior to, and during, the COVID-19 pandemic.

Methods

We analyzed a representative population sample of 11,256 adults (aged 20-65 years) from Understanding Society-The UK Household Longitudinal Study. Baseline data from participants interviewed in 2017/2019 (wave 9) were linked to web surveys conducted during the COVID-19 pandemic. We used latent class analysis (LCA) to identify mutually exclusive health behavior (physical activity, alcohol consumption, eating habits and smoking tobacco) clusters by gender, and examined the sociodemographic correlates of each cluster. We assessed how pre-pandemic latent classes of health behaviors were associated with changes in MHPs during the pandemic using fixed effects regression models.

Results

Three health behavior clusters were identified: positive (33%), moderate (24%), and high risk (43%), where similar behaviors clustered within individuals and sociodemographic circumstances. In particular, gender, age, migrant status and ethnicity were found to have strong associations with each cluster. Our results also demonstrated a clear association in MHPs with health behaviors both prior to, and during the pandemic. There were significant increases in MHPs between 2017/2019 and January 2021, with fluctuations coinciding with changes in public health mitigation policies. Assessments across the three clusters showed about 25.2%, 16.9%, and 0.7% increases in MHPs in the positive, moderate and high risk health behavior clusters, respectively.

Discussion

This study shows that pre-pandemic health behaviors were significantly associated with mental health before and during the pandemic. Holistic policy interventions and promotions targeting multiple health behaviors may be an effective strategy to improve mental health in the pandemic recovery period.

The Clustering of Health-Related Behaviors in the Adult Japanese Population

BACKGROUND

Research findings indicate that four health-related behaviors (HRBs), smoking, alcohol, diet, and physical activity, do not co-occur within individuals by chance and therefore cluster. To date, there is a lack of research investigating the clustering of these HRBs in the Japanese population.

METHODS

The Japanese National Health and Nutrition Survey 2010 was used, containing information on 8,015 community-dwelling adults. Latent profile analysis identified distinct cluster patterns of four HRBs: smoking status, alcohol consumption, calorie intake, and the number of steps per day.

RESULTS

For men, four distinct HRB clusters were identified. The largest cluster (54%) was characterized by drinking more than Japan's recommended alcohol guidelines and walking an inadequate number of steps per day. A small cluster (4%) also emerged, characterized by smoking, high calorie intake, and exceeding alcohol guidelines. Members of these clusters had higher systolic blood pressure than those in the remaining clusters. For women, five distinct HRB clusters were identified. The largest cluster (57%) was characterized by not smoking or drinking and walking an inadequate number of steps per day. For both genders, there was a relationship between cluster membership and age. Cluster membership was associated with income and health status among men but not women.

CONCLUSION

Detecting distinct clusters of HRBs in a Japanese population-based survey provides a person-centered understanding of Japanese lifestyles. This approach can assist policy makers in Japan and overseas to identify new strategies for targeting behavioral risk factors and make health promotion policies more effective in their respective countries.

Growth of Ready Meals in Australian Supermarkets: Nutrient Composition, Price and Serving Size

Pre-prepared, or ready meals (frozen, chilled and shelf-stable) are increasingly available in supermarkets in developed countries. This study aimed to investigate how the range of ready meals in Australian supermarkets has changed from 2014 to 2020, and how products vary by price, serving size, nutrient composition and Health Star Rating. Product information was obtained from the FoodTrack™ packaged food database for the years 2014 to 2019 and from an instore audit of products available in Adelaide, Australia for 2020. There was a 13% annual average increase in the number of ready meals available in supermarkets. Serving size did not change (median 350 g, p-trend = 0.100) and price increased modestly from 2014 to 2020 (median $1.67 to $1.79/100 g, p-trend < 0.001), with chilled ready meals being the most expensive. A modest decrease in sodium density from 2014 to 2020 (median 275 to 240 mg/100 g, p-trend < 0.001) was seen. However, the category has a wide range in Health Star Ratings and nutrient composition, highlighting the importance of appropriate consumer choice to optimise health benefits. With the increasing availability of ready meals, global improvements within this category should be encouraged and consumers guided to choose healthier products.

Modelling the size, cost and health impacts of universal basic income: What can be done in advance of a trial?

Opposition to Universal Basic Income (UBI) is encapsulated by Martinelli’s claim that ‘an affordable basic income would be inadequate, and an adequate basic income would be unaffordable’. In this article, we present a model of health impact that transforms that assumption. We argue that UBI can affect higher level social determinants of health down to individual determinants of health and on to improvements in public health that lead to a number of economic returns on investment. Given that no trial has been designed and deployed with that impact in mind, we present a methodological framework for assessing prospective costs and returns on investment through modelling to make the case for that trial. We begin by outlining the pathways to health in our model of change in order to present criteria for establishing the size of transfer capable of promoting health. We then consider approaches to calculating cost in a UK context to estimate budgetary burdens that need to be met by the state. Next, we suggest means of modelling the prospective impact of UBI on health before asserting means of costing that impact, using a microsimulation approach. We then outline a set of fiscal options for funding any shortfall in returns. Finally, we suggest that fiscal strategy can be designed specifically with health impact in mind by modelling the impact of reform on health and feeding that data cyclically back into tax transfer module of the microsimulation.

Effect of High Fat and Fructo-Oligosaccharide Consumption on Immunoglobulin A in Saliva and Salivary Glands in Rats

Consumption of indigestible dietary fiber increases immunoglobulin A (IgA) levels in saliva. The purpose of this study is to clarify the synergistic effect of the intake of a high amount of fats and indigestible dietary fiber on IgA levels in saliva and submandibular glands (SMG). Seven-week-old Wistar rats were fed a low-fat (60 g/kg) fiberless diet, low-fat fructo-oligosaccharide (FOS, 30 g/kg) diet, high-fat (220 g/kg) fiberless diet, or high-fat FOS diet for 70 days. The IgA flow rate of saliva (IgA FR-saliva) was higher in the low-fat FOS group than in the other groups (p < 0.05). Furthermore, the concentration of tyrosine hydroxylase (a marker of sympathetic nerve activation) in the SMG was higher in the low-fat FOS group (p < 0.05) and positively correlated with the IgA FR-saliva (rs = 0.68. p < 0.0001. n = 32) in comparison to that in the other groups. These findings suggest that during low-fat FOS intake, salivary IgA levels may increase through sympathetic nerve activation.

High educational attainment redresses the effect of occupational social class on health-related lifestyle: findings from four Spanish national health surveys

PURPOSE

Social determinants as occupational social class or educational attainment might influence health outcomes. This phenomenon is known as the social gradient of health and is related to a skewed distribution of health behaviours that might explain differences in morbidity and mortality between social groups. But social class and educational attainment differ in their nature and might have distinct effects on health. Here we study the combined effect of educational attainment and occupational social class on health-related lifestyle.

METHODS

We retrieved data from four large-scale, national representative Spanish surveys (n = 67,171). A latent class regression analysis was run to identify clusters of health-related lifestyle behaviours. Clusters were made according to sociodemographic factors, including a combined analysis of education and occupational social class.

RESULTS

Higher educational attainment and occupational social class were associated with a healthier lifestyle for both sexes. The combined analysis of education and social class indicated that women with secondary education showed a high risk combination of unhealthy behaviours, as men with middle, primary or no education.

CONCLUSIONS

Regardless of social class, a higher educational attainment redresses the effect of occupational social class on health-related behaviours. Our results suggest that education likely plays a crucial role in population health outcomes through its effects on lifestyle.

Clustering of lifestyle risk factors among adult population in India: A cross-sectional analysis from 2005 to 2016

Introduction

Individual’s early life style and health behaviors are directly linked to chronic non-communicable diseases. Considering the increased burden of NCDs during the last two decades, the aim of this study is to assess co-occurrence/clustering of lifestyle risk factors and its association with different socio-demographic and economic characteristics among adult men and women in India from 2005–2016.

Methods

This study utilized the data from the National Family Health Survey 2005–06 and 2015–16 survey rounds. Multinomial logistic regression is employed to evaluate co-occurrence of multiple risk factors among adult men and women of different socio-economic and demographic characteristics to identify the subgroups with elevated risk of clustering of multiple unhealthy lifestyle risk factors.

Results

More adult men in India tend to exhibit clustering of multiple non-communicable disease risk factors than females. Individuals between 30–49 years of age, residing in urban areas, the population with no education, separated couples and those from poor economic strata are the specific population subgroups show higher prevalence of co-occurrence of multiple risk factors. The regional pattern of clustering of risk factors shows that the prevalence of co-occurrence of multiple risk factors is higher among men and women from the North-Eastern part of India compared to the other regions of the country.

Conclusion

The prevalence of clustering of multiple risk factors associated with chronic NCDs is substantially high and has increased between 2005–06 to 2015–16. India may therefore experience a significant increase in the burden of chronic non-communicable diseases in the coming years. We therefore conclude that appropriate strategies should be implemented by policy makers and the government to reduce the overall health burden of NCDs due to lifestyle habits.

Health behaviors in major chronic diseases patients: trends and regional variations analysis, 2008-2017, Korea

Background

Improving the health behaviors of those with chronic diseases such as hypertension and diabetes is important for disease management. Few in-depth studies have been conducted in Korea on the health behaviors of chronic disease patients. This study examined the health behaviors of chronic disease patients over time and compared them with those of the general population.

Methods

Cross-sectional time-series data obtained from the Korea Community Health Survey from 2008 to 2017 were analyzed. Thirteen diseases were included in this analysis, namely, hypertension, diabetes, dyslipidemia, stroke, myocardial infarction, angina, osteoarthritis, osteoporosis, asthma, allergic rhinitis, atopic dermatitis, cataract, and depression. The current smoking rate, drinking rate, and the walking rate, which are leading health behaviors necessary for preventing chronic diseases, were analyzed by disease type. We compared patients’ health behaviors with those of the general population and identified regional variations.

Results

Although the current overall smoking rate was seemingly declining, the overall monthly drinking and high-risk drinking rates were increasing. In 2017, patients experiencing depression symptoms had a higher smoking rate than did the general population; hypertension and diabetes patients had a higher risk-drinking rate than did the latter. The general population’s walking rate was highest. There were considerable variations by region among chronic disease patients.

Conclusions

Chronic disease patients displayed worse health behaviors than those of the general population, in some instances. Rather than focusing only on chronic disease patients’ medication adherence, strategies must be devised to increase their smoking cessation rate, decrease their drinking rate, and increase their walking rate.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-09940-7.

Age-Dependent Disparities in the Prevalence of Single and Clustering Cardiovascular Risk Factors: A Cross-Sectional Cohort Study in Middle-Aged and Older Adults

Background

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide; with age acknowledged as an independent cardiovascular risk factor (CRF) in adults. Appreciating the association between age and classic CRFs is believed to boost all potential benefits of prevention.

Purpose

Assessment of the prevalence of single and clustered CRFs and their association with age.

Patients and Methods

The survey involved 4735 people (33.6% men) who were PONS project attendees aged 45-64. The study protocol comprised the Health Status Questionnaire, general medical examination, anthropometric measurements, and blood and urine sampling. The prevalence of single and clustered CRFs (hypertension, dyslipidemia, diabetes mellitus, and obesity) in the incrementally split age groups was calculated. The incidence rate of CRFs, against their absence, was determined by Poisson regression models with robust standard errors.

Results

The prevalence of CRFs was established in 90% of the respondents. Except dyslipidemia and ≥1 CRFs, prevalence of risk factors increased with age, although this trend was the weakest in men. In the total group, and in women, prevalence of dyslipidemia and ≥1 CRFs was unrelated to age, whereas in men, it was on the rise in the younger age groups. The incidence rate of CRFs was strongly related to age, and, with the exception of dyslipidemia, was higher in the older age groups.

Conclusion

Cardiovascular risk factors are common in the adult population, while their prevalence and clustering are more prevalent in seniors. Apart from dyslipidemia, the risk of CRFs is appreciably age-related, and higher in seniors.

Interpretation of Population Health Metrics: Environmental Lead Exposure as Exemplary Case

Our objective was to gain insight in the calculation and interpretation of population health metrics that inform disease prevention. Using as model environmental exposure to lead (ELE), a global pollutant, we assessed population health metrics derived from the Third National Health and Nutrition Examination Survey (1988 to 1994), the GBD (Global Burden of Disease Study 2010), and the Organization for Economic Co-operation and Development. In the National Health and Nutrition Examination Survey, the hazard ratio relating mortality over 19.3 years of follow-up to a blood lead increase at baseline from 1.0 to 6.7 µg/dL (10th–90th percentile interval) was 1.37 (95% CI, 1.17–1.60). The population-attributable fraction of blood lead was 18.0% (10.9%–26.1%). The number of preventable ELE-related deaths in the United States would be 412 000 per year (250 000–598 000). In GBD 2010, deaths and disability-adjusted life-years globally lost due to ELE were 0.67 million (0.58–0.78 million) and 0.56% (0.47%–0.66%), respectively. According to the 2017 Organization for Economic Co-operation and Development statistics, ELE-related welfare costs were $1 676 224 million worldwide. Extrapolations from the foregoing metrics assumed causality and reversibility of the association between mortality and blood lead, which at present-day ELE levels in developed nations is not established. Other issues limiting the interpretation of ELE-related population health metrics are the inflation of relative risk based on outdated blood lead levels, not differentiating relative from absolute risk, clustering of risk factors and exposures within individuals, residual confounding, and disregarding noncardiovascular disease and immigration in national ELE-associated welfare estimates. In conclusion, this review highlights the importance of critical thinking in translating population health metrics into cost-effective preventive strategies.

Interventions to Increase the Rate of Influenza and Pneumococcal Vaccination in Patients with Chronic Obstructive Pulmonary Disease: A Scoping Review

Background and Objective: Current evidence suggests that patients with chronic obstructive pulmonary disease (COPD) should receive influenza and pneumococcal vaccinations. Despite international guidelines recommending vaccination in patients with COPD, many patients remain unvaccinated. Reasons for vaccine non-acceptance are multifaceted and are likely to be influenced by multiple psychosocial factors and pre-existing health beliefs. The aim of this review was to identify interventions which have been shown to effectively increase vaccination rates in patients with COPD. Materials and Methods: A structured search of PubMed returned 491 titles. Following title and abstract screening, seven full-text articles reporting on 6 unique interventional studies were extracted for narrative synthesis. A variety of interventions were investigated which, for the purposes of this review, were grouped into patient-focussed, clinician-focussed and mixed interventions. Results: Three papers reported findings from clinical trials (2 unique studies) and 4 papers reported findings from before-after studies. Two studies were conducted in the primary care setting, the remaining studies were conducted in secondary and tertiary care. Most studies reported both influenza and pneumococcal vaccination rates. These studies suggest that multimodal interventions, which target multiple aspects of evidence-based care and use both patient-focussed and clinician-focussed techniques, may have the greatest impact on vaccination rates in patients with COPD. Conclusions: Further, adequately powered, high quality studies are needed. It is crucial for individual institutions to monitor their own vaccination rates to determine if there is scope for performance improvement.