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Two expert groups on global health from Norway and Denmark have recently made important strides in reenergizing the debate on the role of the Nordic countries in global health. Their tailored recommendations — emphasizing core values of human rights, equity, accountability, and local ownership alongside health security — have proven influential at a time when new forms of international collaboration in global health are urgently needed.
To investigate the association between food insecurity (FI) and diet quality in private sector service workers.
Design:
Data were collected via electronic questionnaires (2019) and the national register data (2018–2019). FI was measured using the Household Food Insecurity Access Scale (HFIAS) and diet quality using an FFQ and a modified Healthy Food Intake Index (mHFII). The associations between HFIAS and mHFII were studied using ANOVA and ordinal regression analysis.
Setting:
Cross-sectional survey and register data for all municipalities in Finland in 2018–2019.
Participants:
Individuals (n 6435) belonging to the Finnish Service Union United. The members are predominantly women and work mainly in retail trade, tourism, restaurant and leisure services, property maintenance and security services.
Results:
Overall diet quality, measured by mHFII, was significantly lower in those experiencing severe FI than in those who were food secure (8·0 v. 9·1). Additionally, those with severe FI were less likely to have higher (more optimal) scores in sugar-sweetened beverages (OR: 0·67), fibre-rich grains (OR: 0·79), vegetables (OR: 0·54), fruits and berries (OR: 0·61), vegetable oil (OR: 0·80), fish (OR: 0·65), milk (OR: 0·89) and nuts and seeds (OR: 0·66) than food-secure participants. Severe FI was associated with higher odds for less frequent consumption of red and processed meat (OR: 1·15, a higher score represents less frequent consumption).
Conclusions:
Severe FI was linked to both lower overall diet quality and suboptimal consumption of several food groups. Individuals experiencing severe FI may be predisposed to accumulating dietary risk factors for chronic diseases.
Historical research on urban epidemics has focused on the interaction of diseases with social and spatial gradients, such as class, ethnicity, or neighborhood. Even sophisticated historical studies usually lack data on health-related behavior or health-related perceptions, which modern analysts tend to emphasize. With detailed source material from the Finnish city of Tampere during a typhoid epidemic in 1916, we are able to combine both dimensions and look at how material and social constraints interacted with behavior and knowledge to produce unequal outcomes. We use data on socioeconomic status, location, and physical habitat as well as the self-reported behavior and expressed understandings of transmission mechanisms of the infected people to identify the determinants of some falling ill earlier or later than others. Applying survival analysis to approximately 2,500 cases, we show that disease avoidance behavior was deficient and constrained by physical habitat, regardless of considerable public health campaigning. Behavioral guidelines issued by authorities were sub-optimally communicated, unrealistic, and inadequately followed. Boiling water was hampered by shared kitchens, and access to laundry houses for additional hygiene was uneven. Centralized chemical water purification finally leveled the playing field by socializing the cost of prevention and eliminating key sources of unequal risk.
By 2050 the number of adults living with obesity in the UK will rise with approximately one in four in the adult population. This rising trend is not equitable, with higher prevalence in socially disadvantaged groups. There is an apparent paradox of not being able to provide food for the family to eat, a feature of food insecurity and living with obesity. With the current cost-of-living crisis, there is a challenge to afford both food and fuel bills. Environmentally sustainable and healthy diets are proposed to improve public health and reduce the impact of the food system on the environment, while also improving diet quality. However, healthier foods tend to be nearly three times more expensive than unhealthy foods, and this provides a challenge for citizens on low incomes. In this review, we explore some of the evidence for solutions in the retail food environment to support the UK food system to be safe, nutritious, environmentally friendly and fair for all. We highlight the value of co-production in research, to give value and power to the lived experience to address these inequalities. Our multidisciplinary research approach within the FIO Food research grant will generate new insights into modifiable and potentially impactful changes to the UK food system, specifically for the retail food sector. We believe that the co-creation, design and delivery of research with those living with obesity and food insecurity will help to transform the UK food system for health and the environment in this vulnerable group.
Ultra-processed food (UPF) intake is associated with increased non-communicable disease risks. However, systematic reports on sociodemographic predictors of UPF intake are lacking. This review aimed to understand UPF consumption based on sociodemographic factors, using nationally representative cohorts. The systematic review was pre-registered (PROSPERO:CRD42022360199), following PRISMA guidelines. PubMed/MEDLINE searches (‘ultra-processed/ultraprocessed’ and ‘ultra-processing/ultraprocessing’) until 7 September 2022 retrieved 1131 results. Inclusion criteria included: observational, nationally representative adult samples, in English, in peer-reviewed journals, assessing the association between sociodemographics and individual-level UPF intake defined by the NOVA classification. Exclusion criteria included: not nationally representative, no assessment of sociodemographics and individual-level UPF intake defined by NOVA. Risk of bias was assessed using the Newcastle–Ottawa Scale (NOS). Fifty-five papers were included, spanning thirty-two countries. All thirteen sociodemographic variables identified were significantly associated with UPF intake in one or more studies. Significant differences in UPF intake were seen across age, race/ethnicity, rural/urbanisation, food insecurity, income and region, with up to 10–20% differences in UPF intake (% total energy). Higher UPF intakes were associated with younger age, urbanisation and being unmarried, single, separated or divorced. Education, income and socioeconomic status showed varying associations, depending on country. Multivariate analyses indicated that associations were independent of other sociodemographics. Household status and gender were generally not associated with UPF intake. NOS averaged 5·7/10. Several characteristics are independently associated with high UPF intake, indicating large sociodemographic variation in non-communicable disease risk. These findings highlight significant public health inequalities associated with UPF intake, and the urgent need for policy action to minimise social injustice-related health inequalities.
Exposure to (a liberal) democracy can have an impact on both the political attention and visibility of the needs of marginalized populations, as well as the design of health policies that can influence the distribution of population health. This paper investigates the effect of exposure to democracy, that is, the number of years spent in a democracy as measured by democracy indexes, on various measures of inequality in self-reported health across European countries. We use an instrumental variable strategy to leverage the potential endogeneity of a country’s exposure to democracy, drawing on both bivariate (socioeconomic) and univariate health inequality measures. Our estimates provide evidence that an additional year in a democracy reduces both bivariate (income-related) health inequality and overall (univariate) health inequality. Our preferred specification suggests a two-point rank reduction in inequality with an additional year under a democracy. The effect is mainly driven by a reduction of “health poverty” alongside other effects.
The purpose of this study is to determine if healthier neighbourhood food environments are associated with healthier diet quality.
Design:
This was a cross-sectional study using linear regression models to analyse data from the Maastricht Study. Diet quality was assessed using data collected with a FFQ to calculate the Dutch Healthy Diet (DHD). A buffer zone encompassing a 1000 m radius was created around each participant home address. The Food Environment Healthiness Index (FEHI) was calculated using a Kernel density analysis within the buffers of available food outlets. The association between the FEHI and the DHD score was analysed and adjusted for socio-economic variables.
Setting:
The region of Maastricht including the surrounding food retailers in the Netherlands.
Participants:
7367 subjects aged 40–75 years in the south of the Netherlands.
Results:
No relationship was identified between either the FEHI (B = 0·62; 95 % CI = –2·54, 3·78) or individual food outlets, such as fast food (B = –0·07; 95 % CI = –0·20, 0·07) and diet quality. Similar null findings using the FEHI were identified at the 500 m (B = 0·95; 95 % CI = –0·85, 2·75) and 1500 m (B = 1·57; 95 % CI = –3·30, 6·44) buffer. There was also no association between the food environment and individual items of the DHD including fruits, vegetables and sugar-sweetened beverages.
Conclusion:
The food environment in the Maastricht area appeared marginally unhealthy, but the differences in the food environment were not related to the quality of food that participants reported as intake.
The process of decision making is not linear and is affected by multiple factors, other than availability of evidence, such as political context, personal over public interests, decision makers’ accountability, relationships with stakeholders, and familiar experiences in the past. Evidence-informed decisions positively influence access, quality, efficiency, equity, and sustainability of health services, and improve transparency and accountability thereby reducing wastage, abuse, and corruption in the health system. This chapter presents six decision making tools that help policy makers and managers take evidence-informed decisions: burden of disease analysis; health technology assessment; cost-effectiveness analysis; health equity analysis; national health accounts analysis; and stakeholder analysis. The list of tools is not exhaustive, and additional tools can be explored to respond to the context and nature of the public health concern. Policymakers are not expected to know all their methodological aspects, rather they should know what tools are available, their purpose and application, strengths and limitations, and how to interpret the results in the local context.
Rural-urban migrants, though facing unique social and institutional constraints, remain a largely overlooked population in research on health inequality in China. This study applies the inequality of opportunity (IOp) framework to investigate health inequality among children in China. Instead of comparing only urban and rural children, we include rural-urban migrants. Drawing upon three waves of a nation-wide survey, we find that migrant children in China remain disadvantaged in terms of health when compared to urban and rural children. The decomposition of the determinants indicates that while the direct influence of hukou, China’s household registration system, on IOp in health is low and has decreased, particularly between 2007 and 2013, one’s province of residence still matters. Parental health contributes substantially to IOp in health, which likely is an indirect effect of hukou that creates barriers for migrant parents in regard to accessing healthcare. The policy implication of these findings is that although the direct influence of hukou has decreased, when coupled with the continued lack of local government support for the welfare of migrant workers, it perpetuates health inequalities.
We provide food for thought on some pressing questions about health inequalities – why some of us maintain good health into old age, and the inequity of infectious and Non-Communicable Diseases, both very relevant now to COVID-19. We use historical perspectives and modern examples to discuss the population explosion, social determinants of health and how development over the first 1,000 days influences later health. Some ideas are likely to be quite novel to the reader, such as the risk of disease being increased by ‘mismatch’ between our developmental environment and where and how we live later. This takes the story across the globe, from high- to low-income countries, where early development is often less healthy but economic progress is changing environments fast. Can young people in such settings escape, or has the anvil on which their bodies were forged in early life left them with unalterable inequalities? We ask who needs to ‘own’ these problems and why solutions to them have been slow to emerge. The wider, global perspective, sets the scene for the final chapter which focuses on what we can all do as individuals now that we know some of the secrets of our first 1,000 days.
The health of the public is determined by a spectrum of complex individual, social, cultural, economic and environmental factors. This has been attributed to determinants of health.Based on the concept of a new public health, it is argued that public health practice is situated within the context of broader social issues concerning the underlying social, economic, cultural, environmental and political determinants of health and disease. Thus, this book has its emphasis on the sociocultural environment rather than on the biological and genetic factors associated with health. This chapter introduces public health and the salient issues relevant to it from local and global perspectives. The definition of public health, its values and major public health organisations are included. The chapter also discusses major public health challenges in Australia and from a global context. The social model of health, health inequalities and social justice are also discussed.
Already home to 23% of the global elderly population, China will experience further demographic change in the coming decades. To address the consequences of population ageing, the Chinese government is implementing major social insurance reforms and promotes the development of private insurance markets. We aim to inform these initiatives by developing a new method to project healthy life expectancy (HLE) in different regions. HLE is an important population health measure which is increasingly used in the actuarial literature. Our new approach relies on publicly available data from the Global Burden of Disease Study for life expectancy and HLE for 139 countries. We use the model to estimate HLE at birth in 2015 for 31 province-level regions in China for both males and females. We discuss the implications of our results for planned increases in the retirement age in China and for long-term care insurance pricing.
To obtain projections of the prevalence of childhood malnutrition indicators up to 2030 and to analyse the changes of wealth-based inequality in malnutrition indicators and the degree of contribution of socio-economic determinants to the inequities in malnutrition indicators in Bangladesh. Additionally, to identify the risk factors of childhood malnutrition.
Design:
Cross-sectional study. A Bayesian linear regression model was used to estimate trends and projections of malnutrition. For equity analysis, slope index, relative index and decomposition in concentration index were used. Multilevel logistic models were used to identify risk factors of malnutrition.
Setting:
Household surveys in Bangladesh from 1996 to 2014.
Participants:
Children under the age of 5 years.
Results:
A decreasing trend was observed for all malnutrition indices. In 1990, predicted prevalence of stunting, wasting and underweight was 55·0, 15·9 and 61·8 %, respectively. By 2030, prevalence is projected to reduce to 28·8 % for stunting, 12·3 % for wasting and 17·4 % for underweight. Prevalence of stunting, wasting and underweight were 34·3, 6·9 and 32·8 percentage points lower in the richest households than the poorest households. Contribution of the wealth index to child malnutrition increased over time and the largest contribution of pro-poor inequity was explained by wealth index. Being an underweight mother, parents with a lower level of education and poorer households were the key risk factors for stunting and underweight.
Conclusions:
Our findings show an evidence-based need for targeted interventions to improve education and household income-generating activities among poor households to reduce inequalities and reduce the burden of child malnutrition in Bangladesh.
This paper develops a theory of human capital to investigate the role of early childhood health in explaining the large and persistent schooling gaps observed within and across countries. Quantitative analysis using the theory and data from 98 countries shows that early health inequalities within developingcountries strongly amplify later schooling gaps— counterfactually eliminating inequalities reduces schooling Ginis by an average of 18% in developing economies but has only mild effects in richer countries. Moreover, early health inequalities are found to be an important source of schooling variation across countries— universally equating early health to the average US level reduces the cross-country standard deviation of average schooling attainment by over 40%. Additional policy experiments reveal that the gains from early health interventions tend to be amplified by later educational investments in developing economies, while those targeting school-aged children may be limited if early health conditions are ignored.
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