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1.  Trends and determinants of excess winter mortality in New Zealand: 1980 to 2000 
BMC Public Health  2007;7:263.
Background
Although many countries experience an increase in mortality during winter, the magnitude of this increase varies considerably, suggesting that some winter excess may be avoidable. Conflicting evidence has been presented on the role of gender, region and deprivation. Little has been published on the magnitude of excess winter mortality (EWM) in New Zealand (NZ) and other Southern Hemisphere countries.
Methods
Monthly mortality rates per 100,000 population were calculated from routinely collected national mortality data for 1980 to 2000. Generalised negative binomial regression models were used to compare mortality rates between winter (June–September) and the warmer months (October–May).
Results
From 1980–2000 around 1600 excess winter deaths occurred each year with winter mortality rates 18% higher than expected from non-winter rates. Patterns of EWM by age group showed the young and the elderly to be particularly vulnerable. After adjusting for all major covariates, the winter:non-winter mortality rate ratio from 1996–2000 in females was 9% higher than in males. Mortality caused by diseases of the circulatory system accounted for 47% of all excess winter deaths from 1996–2000 with mortality from diseases of the respiratory system accounting for 31%. There was no evidence to suggest that patterns of EWM differed by ethnicity, region or local-area based deprivation level. No decline in seasonal mortality was evident over the two decades.
Conclusion
EWM in NZ is substantial and at the upper end of the range observed internationally. Interventions to reduce EWM are important, but the surprising lack of variation in EWM by ethnicity, region and deprivation, provides little guidance for how such mortality can be reduced.
doi:10.1186/1471-2458-7-263
PMCID: PMC2174476  PMID: 17892590
2.  Socioeconomic Factors and All Cause and Cause-Specific Mortality among Older People in Latin America, India, and China: A Population-Based Cohort Study 
PLoS Medicine  2012;9(2):e1001179.
Cleusa Ferri and colleagues studied mortality rates in over 12,000 people aged 65 years and over in Latin America, India, and China and showed that chronic diseases are the main causes of death and that education has an important effect on mortality.
Background
Even in low and middle income countries most deaths occur in older adults. In Europe, the effects of better education and home ownership upon mortality seem to persist into old age, but these effects may not generalise to LMICs. Reliable data on causes and determinants of mortality are lacking.
Methods and Findings
The vital status of 12,373 people aged 65 y and over was determined 3–5 y after baseline survey in sites in Latin America, India, and China. We report crude and standardised mortality rates, standardized mortality ratios comparing mortality experience with that in the United States, and estimated associations with socioeconomic factors using Cox's proportional hazards regression. Cause-specific mortality fractions were estimated using the InterVA algorithm. Crude mortality rates varied from 27.3 to 70.0 per 1,000 person-years, a 3-fold variation persisting after standardisation for demographic and economic factors. Compared with the US, mortality was much higher in urban India and rural China, much lower in Peru, Venezuela, and urban Mexico, and similar in other sites. Mortality rates were higher among men, and increased with age. Adjusting for these effects, it was found that education, occupational attainment, assets, and pension receipt were all inversely associated with mortality, and food insecurity positively associated. Mutually adjusted, only education remained protective (pooled hazard ratio 0.93, 95% CI 0.89–0.98). Most deaths occurred at home, but, except in India, most individuals received medical attention during their final illness. Chronic diseases were the main causes of death, together with tuberculosis and liver disease, with stroke the leading cause in nearly all sites.
Conclusions
Education seems to have an important latent effect on mortality into late life. However, compositional differences in socioeconomic position do not explain differences in mortality between sites. Social protection for older people, and the effectiveness of health systems in preventing and treating chronic disease, may be as important as economic and human development.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Worldwide, half of all deaths occur in people aged 60 or older. Yet mortality among older people is a neglected topic in global health. In high income countries, where 84% of people do not die until they are aged 65 years or older, the causes of death among older people and the factors (determinants) that affect their risk of dying are well documented. In Europe, for example, the leading causes of death among older people are heart disease, stroke, and other chronic (long-term) diseases. Moreover, as in younger age groups, having a better education and owning a house reduces the risk of death among older people. By contrast, in low and middle income countries (LMICs), where three-quarters of deaths of older people occur, reliable data on the causes and determinants of death among older people are lacking, in part because many LMICs have inadequate vital registration systems—official records of all births and deaths.
Why Was This Study Done?
In many LMICs, chronic diseases are replacing communicable (infectious) diseases as the leading causes of death and disability—health experts call this the epidemiological transition (epidemiology is the study of the distribution and causes of disease in populations)—and the average age of the population is increasing (the demographic transition). Faced with these changes, which occur when countries move from a pre-industrial to an industrial economy, policy makers in LMICs need to introduce measures to improve health and reduce deaths among older people. However, to do this, they need reliable data on the causes and determinants of death in this section of the population. In this longitudinal population-based cohort study (a type of study that follows a group of people from a defined population over time), researchers from the 10/66 Dementia Research Group, which is carrying out population-based research on dementia, aging, and non-communicable diseases in LMICs, investigate the patterns of mortality among older people living in Latin America, India, and China.
What Did the Researchers Do and Find?
Between 2003 and 2005, the researchers completed a baseline survey of people aged 65 years or older living in six Latin American LMICs, China, and India. Three to five years later, they determined the vital status of 12,373 of the study participants (that is, they determined whether the individual was alive or dead) and interviewed a key informant (usually a relative) about each death using a standardized “verbal autopsy” questionnaire that includes questions about date and place of death, and about medical help-seeking and signs and symptoms noted during the final illness. Finally, they used a tool called the InterVA algorithm to calculate the most likely causes of death from the verbal autopsies. Crude mortality rates varied from 27.3 per 1,000 person-years in urban Peru to 70.0 per 1,000 person-years in urban India, a three-fold difference in mortality rates that persisted even after allowing for differences in age, sex, education, occupational attainment, and number of assets among the study sites. Compared to the US, mortality rates were much higher in urban India and rural China; much lower in urban and rural Peru, Venezuela, and urban Mexico; but similar elsewhere. Although several socioeconomic factors were associated with mortality, only a higher education status provided consistent independent protection against death in statistical analyses. Finally, chronic diseases were the main causes of death; stroke was the leading cause of death at all the sites except those in rural Peru and Mexico.
What Do These Findings Mean?
These findings identify the main causes of death among older adults in a range of LMICs and suggest that there is an association of education with mortality that extends into later life. However, these findings may not be generalizable to other LMICs or even to other sites in the LMICs studied, and because some of the information provided by key informants may have been affected by recall error, the accuracy of the findings may be limited. Nevertheless, these findings suggest how health and mortality might be improved in elderly people in LMICs. Specifically, they suggest that efforts to ensure universal access to education should confer substantial health benefits and that interventions that target social and economic vulnerability in later life and promote access to effectively organized health care (particularly for stroke) should be considered.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001179.
The World Health Organization provides information on mortality around the world and projections of global mortality up to 2030
The 10/66 Dementia Research Group is building an evidence base to inform the development and implementation of policies for improving the health and social welfare of older people in LMICs, particularly people with dementia; its website includes background information about demographic and epidemiological aging in LMICs
Wikipedia has a page on the demographic transition (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Information about the InterVA tool for interpreting verbal autopsy data is available
The US Centers for Disease Control and Prevention has information about healthy aging
doi:10.1371/journal.pmed.1001179
PMCID: PMC3289608  PMID: 22389633
3.  Excess Winter Mortality and Cold Temperatures in a Subtropical City, Guangzhou, China 
PLoS ONE  2013;8(10):e77150.
Background
A significant increase in mortality was observed during cold winters in many temperate regions. However, there is a lack of evidence from tropical and subtropical regions, and the influence of ambient temperatures on seasonal variation of mortality was not well documented.
Methods
This study included 213,737 registered deaths from January 2003 to December 2011 in Guangzhou, a subtropical city in Southern China. Excess winter mortality was calculated by the excess percentage of monthly mortality in winters over that of non-winter months. A generalized linear model with a quasi-Poisson distribution was applied to analyze the association between monthly mean temperature and mortality, after controlling for other meteorological measures and air pollution.
Results
The mortality rate in the winter was 26% higher than the average rate in other seasons. On average, there were 1,848 excess winter deaths annually, with around half (52%) from cardiovascular diseases and a quarter (24%) from respiratory diseases. Excess winter mortality was higher in the elderly, females and those with low education level than the young, males and those with high education level, respectively. A much larger winter increase was observed in out-of-hospital mortality compared to in-hospital mortality (45% vs. 17%). We found a significant negative correlation of annual excess winter mortality with average winter temperature (rs=-0.738, P=0.037), but not with air pollution levels. A 1 °C decrease in monthly mean temperature was associated with an increase of 1.38% (95%CI:0.34%-2.40%) and 0.88% (95%CI:0.11%-1.64%) in monthly mortality at lags of 0-1 month, respectively.
Conclusion
Similar to temperate regions, a subtropical city Guangzhou showed a clear seasonal pattern in mortality, with a sharper spike in winter. Our results highlight the role of cold temperature on the winter mortality even in warm climate. Precautionary measures should be strengthened to mitigate cold-related mortality for people living in warm climate.
doi:10.1371/journal.pone.0077150
PMCID: PMC3792910  PMID: 24116214
4.  The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis 
PLoS Medicine  2009;6(12):e1000207.
Marc Lipsitch and colleagues use complementary data from two US cities, Milwaukee and New York City, to assess the severity of pandemic (H1N1) 2009 influenza in the United States.
Background
Accurate measures of the severity of pandemic (H1N1) 2009 influenza (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources.
Methods and Findings
We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data—medically attended cases in Milwaukee or self-reported influenza-like illness (ILI) in New York—were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information, and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated an sCFR of 0.048% (95% credible interval [CI] 0.026%–0.096%), sCIR of 0.239% (0.134%–0.458%), and sCHR of 1.44% (0.83%–2.64%). Using self-reported ILI, we obtained estimates approximately 7–9× lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5–17 y. sCHR appears to be lowest in persons aged 5–17; our data were too sparse to allow us to determine the group in which it was the highest.
Conclusions
These estimates suggest that an autumn–winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with the greatest impact in children aged 0–4 and adults 18–64. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the total proportion of the population symptomatically infected were lower than assumed.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and about half a million people die as a result. In the US alone, an average of 36,000 people are thought to die from influenza-related causes every year. These seasonal epidemics occur because small but frequent changes in the virus mean that an immune response produced one year provides only partial protection against influenza the next year. Occasionally, influenza viruses emerge that are very different and to which human populations have virtually no immunity. These viruses can start global epidemics (pandemics) that kill millions of people. Experts have been warning for some time that an influenza pandemic is long overdue and in, March 2009, the first cases of influenza caused by a new virus called pandemic (H1N1) 2009 (pH1N1; swine flu) occurred in Mexico. The virus spread rapidly and on 11 June 2009, the World Health Organization declared that a global pandemic of pH1N1 influenza was underway. By the beginning of November 2009, more than 6,000 people had died from pH1N1 influenza.
Why Was This Study Done?
With the onset of autumn—drier weather and the return of children to school help the influenza virus to spread—pH1N1 cases, hospitalizations, and deaths in the Northern Hemisphere have greatly increased. Although public-health officials have been preparing for this resurgence of infection, they cannot be sure of its impact on human health without knowing more about the severity of pH1N1 infections. The severity of an infection can be expressed as a case-fatality ratio (CFR; the proportion of cases that result in death), as a case-hospitalization ratio (CHR; the proportion of cases that result in hospitalization), and as a case-intensive care ratio (CIR; the proportion of cases that require treatment in an intensive care unit). Because so many people have been infected with pH1N1 since it emerged, the numbers of cases and deaths caused by pH1N1 infection are not known accurately so these ratios cannot be easily calculated. In this study, the researchers estimate the severity of pH1N1 influenza in the US between April and July 2009 by combining data on pH1N1 infections from several sources using a statistical approach known as Bayesian evidence synthesis.
What Did the Researchers Do and Find?
By using data on medically attended and hospitalized cases of pH1N1 infection in Milwaukee and information from New York City on hospitalizations, intensive care use, and deaths, the researchers estimate that the proportion of US cases with symptoms that died (the sCFR) during summer 2009 was 0.048%. That is, about 1 in 2,000 people who had symptoms of pH1N1 infection died. The “credible interval” for this sCFR, the range of values between which the “true” sCFR is likely to lie, they report, is 0.026%–0.096% (between 1 in 4,000 and 1 in 1,000 deaths for every symptomatic case). About 1 in 400 symptomatic cases required treatment in intensive care, they estimate, and about 1 in 70 symptomatic cases required hospital admission. When the researchers used a different approach to estimate the total number of symptomatic cases—based on New Yorkers' self-reported incidence of influenza-like-illness from a telephone survey—their estimates of pH1N1 infection severity were 7- to 9-fold lower. Finally, they report that the sCFR and the sCIR were highest in people aged 18 or older and lowest in children aged 5–17 years.
What Do These Findings Mean?
Many uncertainties (for example, imperfect detection and reporting) can affect estimates of influenza severity. Even so, the findings of this study suggest that an autumn–winter pandemic wave of pH1N1 will have a death toll only slightly higher than or considerably lower than that caused by seasonal influenza in an average year, provided pH1N1 continues to behave as it did during the summer. Similarly, the estimated burden on hospitals and intensive care facilities ranges from somewhat higher than in a normal influenza season to considerably lower. The findings of this study also suggest that, unlike seasonal influenza, which kills mainly elderly adults, a high proportion of deaths from pH1N1infection will occur in nonelderly adults, a shift in age distribution that has been seen in previous pandemics. With these estimates in hand and with continued close monitoring of the pandemic, public-health officials should now be in a better position to plan effective strategies to deal with the pH1N1 pandemic.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000207.
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on pandemic H1N1 (2009) influenza
Flu.gov, a US government Web site, provides access to information on H1N1, avian and pandemic influenza
The World Health Organization provides information on seasonal influenza and has detailed information on pandemic H1N1 (2009) influenza (in several languages)
The UK Health Protection Agency provides information on pandemic influenza and on pandemic H1N1 (2009) influenza
More information for patients about H1N1 influenza is available through Choices, an information resource provided by the UK National Health Service
doi:10.1371/journal.pmed.1000207
PMCID: PMC2784967  PMID: 19997612
5.  Effect of Previous-Winter Mortality on the Association between Summer Temperature and Mortality in South Korea 
Environmental Health Perspectives  2011;119(4):542-546.
Background
It has recently been postulated that low mortality levels in the previous winter may increase the proportion of vulnerable individuals in the pool of people at risk of heat-related death during the summer months.
Objectives
We explored the sensitivity of heat-related mortality in summer (June–August) to mortality in the previous winter (December–February) in Seoul, Daegu, and Incheon in South Korea, from 1992 through 2007, excluding the summer of 1994.
Methods
Poisson regression models adapted for time-series data were used to estimate associations between a 1°C increase in average summer temperature (on the same day and the previous day) above thresholds specific for city, age, and cause of death, and daily mortality counts. Effects were estimated separately for summers preceded by winters with low and high mortality, with adjustment for secular trends.
Results
Temperatures above city-specific thresholds were associated with increased mortality in all three cities. Associations were stronger in summers preceded by winters with low versus high mortality levels for all nonaccidental deaths and, to a lesser extent, among persons ≥ 65 years of age. Effect modification by previous-winter mortality was not evident when we restricted deaths to cardiovascular disease outcomes in Seoul.
Conclusions
Our results suggest that low winter all-cause mortality leads to higher mortality during the next summer. Evidence of a relation between increased summer heat-related mortality and previous wintertime deaths has the potential to inform public health efforts to mitigate effects of hot weather.
doi:10.1289/ehp.1002080
PMCID: PMC3080938  PMID: 21233056
high temperature; mortality; preventive heath services; South Korea; weather
6.  Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study 
PLoS Medicine  2013;10(11):e1001558.
Lone Simonsen and colleagues use a two-stage statistical modeling approach to estimate the global mortality burden of the 2009 influenza pandemic from mortality data obtained from multiple countries.
Please see later in the article for the Editors' Summary
Background
Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries.
Methods and Findings
We obtained weekly virology and underlying cause-of-death mortality time series for 2005–2009 for 20 countries covering ∼35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%–85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in persons <65 y. Limitations include lack of representation of low-income countries among single-country estimates and an inability to study subsequent pandemic waves (2010–2012).
Conclusions
We estimate that 2009 global pandemic respiratory mortality was ∼10-fold higher than the World Health Organization's laboratory-confirmed mortality count. Although the pandemic mortality estimate was similar in magnitude to that of seasonal influenza, a marked shift toward mortality among persons <65 y of age occurred, so that many more life-years were lost. The burden varied greatly among countries, corroborating early reports of far greater pandemic severity in the Americas than in Australia, New Zealand, and Europe. A collaborative network to collect and analyze mortality and hospitalization surveillance data is needed to rapidly establish the severity of future pandemics.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and hundreds of thousands of people (mainly elderly individuals) die as a result. These seasonal epidemics occur because small but frequent changes in the influenza virus mean that the immune response produced by infection with one year's virus provides only partial protection against the next year's virus. Influenza viruses also occasionally emerge that are very different. Human populations have virtually no immunity to these new viruses, which can start global epidemics (pandemics) that kill millions of people. The most recent influenza pandemic, which was first recognized in Mexico in March 2009, was caused by the 2009 influenza A H1N1 pandemic (H1N1pdm09) virus. This virus spread rapidly, and on 11 June 2009, the World Health Organization (WHO) declared that an influenza pandemic was underway. H1N1pdm09 caused a mild disease in most people it infected, but by the time WHO announced that the pandemic was over (10 August 2010), there had been 18,632 laboratory-confirmed deaths from H1N1pdm09.
Why Was This Study Done?
The modest number of laboratory-confirmed H1N1pdm09 deaths has caused commentators to wonder whether the public health response to H1N1pdm09 was excessive. However, as is the case with all influenza epidemics, the true mortality (death) burden from H1N1pdm09 is substantially higher than these figures indicate because only a minority of influenza-related deaths are definitively diagnosed by being confirmed in laboratory. Many influenza-related deaths result from secondary bacterial infections or from exacerbation of preexisting chronic conditions, and are not recorded as related to influenza infection. A more complete assessment of the impact of H1N1pdm09 on mortality is essential for the optimization of public health responses to future pandemics. In this modeling study (the Global Pandemic Mortality [GLaMOR] project), researchers use a two-stage statistical modeling approach to estimate the global mortality burden of the 2009 influenza pandemic from mortality data obtained from multiple countries.
What Did the Researchers Do and Find?
The researchers obtained weekly virology data from the World Health Organization FluNet database and national influenza centers to identify influenza active periods, and obtained weekly national underlying cause-of-death time series for 2005–2009 from collaborators in more than 20 countries (35% of the world's population). They used a multivariate linear regression model to measure the numbers and rates of pandemic influenza respiratory deaths in each of these countries. Then, in the second stage of their analysis, they used a multiple imputation model that took into account country-specific geographical, economic, and health indicators to project the single-country estimates to all world countries. The researchers estimated that between 123,000 and 203,000 pandemic influenza respiratory deaths occurred globally from 1 April through 31 December 2009. Most of these deaths (62%–85%) occurred in people younger than 65 years old. There was a striking regional heterogeneity in deaths, with up to 20-fold higher mortality in Central and South American countries than in European countries. Finally, the model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season. Notably, only 19% of these deaths occurred in people younger than 65 years old.
What Do These Findings Mean?
These findings suggest that respiratory mortality from the 2009 influenza pandemic was about 10-fold higher than laboratory-confirmed mortality. The true total mortality burden is likely to be even higher because deaths that occurred late in the winter of 2009–2010 and in later pandemic waves were missed in this analysis, and only pandemic influenza deaths that were recorded as respiratory deaths were included. The lack of single-country estimates from low-income countries may also limit the accuracy of these findings. Importantly, although the researchers' estimates of mortality from H1N1pdm09 and from seasonal influenza were of similar magnitude, the shift towards mortality among younger people means that more life-years were lost during the 2009 influenza pandemic than during an average pre-pandemic influenza season. Although the methods developed by the GLaMOR project can be used to make robust and comparable mortality estimates in future influenza pandemics, the lack of timeliness of such estimates needs to be remedied. One potential remedy, suggest the researchers, would be to establish a collaborative network that analyzes timely hospitalization and/or mortality data provided by sentinel countries. Such a network should be able to provide the rapid and reliable data about the severity of pandemic threats that is needed to guide public health policy decisions.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001558.
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including archived information on H1N1pdm09
Flu.gov, a US government website, provides access to information on seasonal and pandemic influenza H1N1pdm09
The World Health Organization provides information on influenza and on the global response to H1N1pdm09, including a publication on the evolution of H1N1pdm09 (some information in several languages). Information on FluNet, a global tool for influenza surveillance, is also available
Public Health England provides information on pandemic influenza and archived information on H1N1pdm09
More information for patients about H1N1pdm09 is available through Choices, an information resource provided by the UK National Health Service
More information about the GLaMOR project is available
doi:10.1371/journal.pmed.1001558
PMCID: PMC3841239  PMID: 24302890
7.  Vaccinating to Protect a Vulnerable Subpopulation 
PLoS Medicine  2007;4(5):e174.
Background
Epidemic influenza causes serious mortality and morbidity in temperate countries each winter. Research suggests that schoolchildren are critical in the spread of influenza virus, while the elderly and the very young are most vulnerable to the disease. Under these conditions, it is unclear how best to focus prevention efforts in order to protect the population. Here we investigate the question of how to protect a population against a disease when one group is particularly effective at spreading disease and another group is more vulnerable to the effects of the disease.
Methods and Findings
We developed a simple mathematical model of an epidemic that includes assortative mixing between groups of hosts. We evaluate the impact of different vaccine allocation strategies across a wide range of parameter values. With this model we demonstrate that the optimal vaccination strategy is extremely sensitive to the assortativity of population mixing, as well as to the reproductive number of the disease in each group. Small differences in parameter values can change the best vaccination strategy from one focused on the most vulnerable individuals to one focused on the most transmissive individuals.
Conclusions
Given the limited amount of information about relevant parameters, we suggest that changes in vaccination strategy, while potentially promising, should be approached with caution. In particular, we find that, while switching vaccine to more active groups may protect vulnerable groups in many cases, switching too much vaccine, or switching vaccine under slightly different conditions, may lead to large increases in disease in the vulnerable group. This outcome is more likely when vaccine limitation is stringent, when mixing is highly structured, or when transmission levels are high.
Jonathan Dushoff and colleagues model the benefits of different vaccination strategies and suggest that small differences in how populations mix can change the best vaccination strategy from one focused on the most vulnerable individuals to one focused on the most transmissive individuals.
Editors' Summary
Background.
Every winter, millions of people take to their beds with influenza—a viral infection of the nose, throat, and airways that is transmitted in airborne droplets released by coughing and sneezing. Most people who catch flu recover within a few days, but some develop serious complications such as pneumonia, and in the US alone, about 36,000 people—mainly infants, elderly, and chronically ill individuals—die every year. To minimize the morbidity (illness) and mortality (death) associated with seasonal (epidemic) influenza, the World Health Organization recommends that these vulnerable people be vaccinated against influenza every autumn. Annual vaccination is necessary because flu viruses continually make small changes to the viral proteins that the immune system recognizes.
Why Was This Study Done?
Although infants and the elderly are particularly vulnerable to influenza, schoolchildren are more likely to spread the flu virus. Also, vaccination is more effective in schoolchildren than in elderly people. So could vaccination of schoolchildren be the best way to reduce influenza morbidity and mortality? Some Japanese and US data suggest that it might be, but policymakers need to know more about the likely effects of changing the current influenza vaccination strategy. They need to know in what circumstances the direct effects of vaccination (protection of vaccinated individuals from disease) outweigh its indirect effects (reduced infection in vulnerable individuals caused by the reduced spread of disease in the whole population) and when the opposite is true. In this study, the researchers have used mathematical modeling to investigate how vaccination affects the spread of diseases such as influenza for which a “core” group in the population spreads the disease and a distinct “vulnerable” group is sensitive to its effects.
What Did the Researchers Do and Find?
The researchers developed a mathematical model in which members of each group mixed mainly with their own group (assortative mixing) and used it to predict how changing the proportion of a limited amount of vaccine given to each group might affect disease spread under different conditions. For example, they report that in a population in which the two groups were very unlikely to mix and viral transmission was low, switching vaccine from the vulnerable group to the core group initially increased infections in the vulnerable group because fewer individuals were directly protected but, as more vaccine was allocated to the core group, fewer vulnerable people became infected because the size of the epidemic decreased. When viral transmission was high, vaccination of the vulnerable group was always best. However, when viral transmission was moderate, shifting vaccine from the vulnerable group first increased, then decreased infections in this group before increasing them again. This last change occurred when vaccination in the vulnerable group was so low that viral transmission was sufficient to maintain the epidemic within this group.
What Do These Findings Mean?
As with all mathematical modeling, the researchers' findings depend on the assumptions included in the model, many of which are based on limited information. The model also considers a population that contains only two groups, an unlikely situation in real life. Nevertheless, these findings indicate that in a population in which one group of people is mainly responsible for the spread of a disease and another is most vulnerable to its effects, the best vaccination strategy is very sensitive to how the groups mix and how well the disease spreads in each group. Small changes in these poorly understood parameters can change the optimal vaccination strategy from one that vaccinates vulnerable individuals to one that mainly vaccinates the people who spread the disease. Importantly, a beneficial change in strategy can become deleterious if taken too far, so policy makers need to approach potentially promising changes in vaccination policy cautiously. Finally, for influenza, the model supports the idea that using some vaccine stocks in schoolchildren might decrease morbidity and mortality among elderly people but suggests that—even if this turns out to be correct—if all the vaccine were given to schoolchildren, more old people might die. Thus, the most prudent policy would be to supplement rather than replace vaccination of the elderly with vaccination of children.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040174.
US Centers for Disease Control and Prevention provide information about influenza for patients and professionals, including key facts about the flu vaccine (in English and Spanish)
World Health Organization, fact sheet on influenza and information on vaccination (in English, Spanish, French, Arabic, Chinese and Russian)
UK Health Protection Agency, information on seasonal influenza
MedlinePlus encyclopedia entries on influenza and the influenza vaccine (in English and Spanish)
Public disease mortality and morbidity data at the International Infectious Disease Data Archive (IIDDA)
doi:10.1371/journal.pmed.0040174
PMCID: PMC1872043  PMID: 17518515
8.  The impact of targeting all elderly persons in England and Wales for yearly influenza vaccination: excess mortality due to pneumonia or influenza and time trend study 
BMJ Open  2013;3(8):e002743.
Objective
To investigate the impact on mortality due to pneumonia or influenza of the change from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales.
Design
Excess mortality estimated using time series of deaths registered to pneumonia or influenza, accounting for seasonality, trend and artefacts. Non-excess mortality plotted as proxy for long-term trend in mortality.
Setting
England and Wales.
Participants
Persons aged 65–74 and 75+ years whose deaths were registered to underlying pneumonia or influenza between 1975/1976 and 2004/2005.
Outcome measures
Multiplicative effect on average excess pneumonia and influenza deaths each winter in the 4–6 winters since age group-based targeting of vaccination was introduced (in persons aged 75+ years from 1998/1999; in persons aged 65+ years from 2000/2001), estimated using multivariable regression adjusted for temperature, antigenic drift and vaccine mismatch, and stratified by dominant circulating influenza subtype. Trend in baseline weekly pneumonia and influenza death rates.
Results
There is a suggestion of lower average excess mortality in the six winters after age group-based targeting began compared to before, but the CI for the 65–74 years age group includes no difference. Trend in baseline pneumonia and influenza mortality shows an apparent downward turning point around 2000 for the 65–74 years age group and from the mid-1990s in the 75+ years age group.
Conclusions
There is weakly supportive evidence that the marked increases in vaccine coverage accompanying the switch from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales were associated with lower levels of pneumonia and influenza mortality in older people in the first 6 years after age group-based targeting began. The possible impact of these policy changes is observed as weak evidence for lower average excess mortality as well as a turning point in baseline mortality coincident with the changes.
doi:10.1136/bmjopen-2013-002743
PMCID: PMC3733298  PMID: 23906952
Influenza; Mortality; Mass Vaccination; Aged; Trends
9.  Living Alone and Alcohol-Related Mortality: A Population-Based Cohort Study from Finland 
PLoS Medicine  2011;8(9):e1001094.
Kimmo Herttua and colleagues showed that living alone is associated with a substantially increased risk of alcohol-related mortality, irrespective of gender, socioeconomic status, or cause of death, and that this effect was exacerbated after a price reduction in alcohol in 2004.
Background
Social isolation and living alone are increasingly common in industrialised countries. However, few studies have investigated the potential public health implications of this trend. We estimated the relative risk of death from alcohol-related causes among individuals living alone and determined whether this risk changed after a large reduction in alcohol prices.
Methods and Findings
We conducted a population-based natural experimental study of a change in the price of alcohol that occurred because of new laws enacted in Finland in January and March of 2004, utilising national registers. The data are based on an 11% sample of the Finnish population aged 15–79 y supplemented with an oversample of deaths. The oversample covered 80% of all deaths during the periods January 1, 2000–December 31, 2003 (the four years immediately before the price reduction of alcohol), and January 1, 2004–December 31, 2007 (the four years immediately after the price reduction). Alcohol-related mortality was defined using both underlying and contributory causes of death. During the 8-y follow-up about 18,200 persons died due to alcohol-related causes. Among married or cohabiting people the increase in alcohol-related mortality was small or non-existing between the periods 2000–2003 and 2004–2007, whereas for those living alone, this increase was substantial, especially in men and women aged 50–69 y. For liver disease in men, the most common fatal alcohol-related disease, the age-adjusted risk ratio associated with living alone was 3.7 (95% confidence interval 3.3, 4.1) before and 4.9 (95% CI 4.4, 5.4) after the price reduction (p<0.001 for difference in risk ratios). In women, the corresponding risk ratios were 1.7 (95% CI 1.4, 2.1) and 2.4 (95% CI 2.0, 2.9), respectively (p ≤ 0.01). Living alone was also associated with other mortality from alcohol-related diseases (range of risk ratios 2.3 to 8.0) as well as deaths from accidents and violence with alcohol as a contributing cause (risk ratios between 2.1 and 4.7), both before and after the price reduction.
Conclusions
Living alone is associated with a substantially increased risk of alcohol-related mortality, irrespective of gender, socioeconomic status, or the specific cause of death. The greater availability of alcohol in Finland after legislation-instituted price reductions in the first three months of 2004 increased in particular the relative excess in fatal liver disease among individuals living alone.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Throughout most of human history, people have lived in tight-knit communities where there was likely to be someone to turn to for help, advice, or company. But the modern way of life in industrialized countries is greatly reducing the quantity and quality of social relationships. Instead of living in extended families, many people now live miles away from their relatives, often living and working alone. Others commute long distances to work, which leaves little time for socializing with friends or relatives. And many delay or forgo getting married and having children. Consequently, loneliness and social isolation are getting more common. In the UK, according to a recent survey by the Mental Health Foundation, 10% of people often feel lonely, a third have a close friend or relative who they think is very lonely, and half think people are getting lonelier in general. Similarly, over the past two decades, there has been a three-fold increase in the number of Americans who say they have no close confidants.
Why Was This Study Done?
Some experts think that loneliness is bad for human health. They point to studies that show that people with fewer social relationships die earlier on average than people with more social relationships. But does loneliness increase the risk of dying from specific causes? It is important to investigate the relationship between loneliness and cause-specific mortality (death) because, if for example, loneliness increases the risk of dying from alcohol-related causes (heavy drinking causes liver and heart damage, increases the risk of some cancers, contributes to depression, and increases the risk of death by violence or accident), doctors could advise their patients who live alone about safe drinking. But, although loneliness is recognized as both a contributor to and a consequence of alcohol abuse, there have been no large, population-based studies on the association between living alone and alcohol-related mortality. In this population-based study, the researchers estimate the association between living alone (an indicator of a lack of social relationships) and death from alcohol-related causes in Finland for four years before and four years after an alcohol price reduction in 2004 that increased alcohol consumption.
What Did the Researchers Do and Find?
The researchers obtained information on about 80% of all people who died in Finland between 2000 and 2007 from Statistics Finland, which collects official Finnish statistics. During this period, about 18,200 people (two-thirds of whom lived alone) died from underlying alcohol-related causes (for example, liver disease and alcoholic poisoning) or contributory alcohol-related causes (for example, accidents, violence, and cardiovascular disease, with alcohol as a contributing cause). Among married and cohabiting people, the rate of alcohol-related mortality was similar in 2000–2003 and 2004–2007 but for people living alone (particularly those aged 50–69 years) the 2004 alcohol price reduction substantially increased the alcohol-related mortality rate. For liver disease in men, the risk ratio associated with living alone was 3.7 before and 4.9 after the price reduction. That is, between 2000 and 2003, men living alone were 3.7 times more likely to die of liver disease than married or cohabiting men; between 2004 and 2007, they were 4.9 times more likely to die of liver disease. In women, the corresponding risk ratios for liver disease were 1.7 and 2.4, respectively. Living alone was also associated with an increased risk of dying from other alcohol-related diseases and accidents and violence both before and after the price reduction.
What Do These Findings Mean?
These findings indicate that, in Finland, living alone is associated with an increased risk of alcohol-related mortality. Because of the study design, it is impossible to say whether living alone is a cause or a consequence of alcohol abuse, but the greater increase in alcohol-related deaths (particularly fatal liver disease) among people living alone compared to married and cohabiting people after the alcohol price reduction suggests that people living alone are more vulnerable to the adverse effects of increased alcohol availability. Further research in other countries is now needed to identify whether living alone is a cause or effect of alcohol abuse and to extend these findings to cultures where the pattern of alcohol consumption is different. However, the findings of this natural experiment suggest that living alone should be regarded as a potential risk marker for death from alcohol-related causes.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001094.
The Mental Health America Live Your Life Well webpage includes information about how social relationships improve mental and physical health
The Mental Health Foundation (a UK charity) presents the report The Lonely Society?
The US National Institute on Alcohol Abuse and Alcoholism has information about alcohol and its effects on health
The US Centers for Disease Control and Prevention has a website on alcohol and public health that includes information on the health risks of excessive drinking
The UK National Health Service Choices website provides detailed information about drinking and alcohol, including information on the risks of drinking too much, and personal stories about alcohol problems, including stories from people living alone (My drinks diary shock and I used to drink all day)
MedlinePlus provides links to many other resources on alcohol
doi:10.1371/journal.pmed.1001094
PMCID: PMC3176753  PMID: 21949642
10.  Assessing Optimal Target Populations for Influenza Vaccination Programmes: An Evidence Synthesis and Modelling Study 
PLoS Medicine  2013;10(10):e1001527.
Marc Baguelin and colleagues use virological, clinical, epidemiological, and behavioral data to estimate how policies for influenza vaccination programs may be optimized in England and Wales.
Please see later in the article for the Editors' Summary
Background
Influenza vaccine policies that maximise health benefit through efficient use of limited resources are needed. Generally, influenza vaccination programmes have targeted individuals 65 y and over and those at risk, according to World Health Organization recommendations. We developed methods to synthesise the multiplicity of surveillance datasets in order to evaluate how changing target populations in the seasonal vaccination programme would affect infection rate and mortality.
Methods and Findings
Using a contemporary evidence-synthesis approach, we use virological, clinical, epidemiological, and behavioural data to develop an age- and risk-stratified transmission model that reproduces the strain-specific behaviour of influenza over 14 seasons in England and Wales, having accounted for the vaccination uptake over this period. We estimate the reduction in infections and deaths achieved by the historical programme compared with no vaccination, and the reduction had different policies been in place over the period. We find that the current programme has averted 0.39 (95% credible interval 0.34–0.45) infections per dose of vaccine and 1.74 (1.16–3.02) deaths per 1,000 doses. Targeting transmitters by extending the current programme to 5–16-y-old children would increase the efficiency of the total programme, resulting in an overall reduction of 0.70 (0.52–0.81) infections per dose and 1.95 (1.28–3.39) deaths per 1,000 doses. In comparison, choosing the next group most at risk (50–64-y-olds) would prevent only 0.43 (0.35–0.52) infections per dose and 1.77 (1.15–3.14) deaths per 1,000 doses.
Conclusions
This study proposes a framework to integrate influenza surveillance data into transmission models. Application to data from England and Wales confirms the role of children as key infection spreaders. The most efficient use of vaccine to reduce overall influenza morbidity and mortality is thus to target children in addition to older adults.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza, a viral infection of the airways. Most infected individuals recover quickly, but seasonal influenza outbreaks (epidemics) kill about half a million people annually. In countries with advanced health systems, these deaths occur mainly among elderly people and among individuals with long-term illnesses such as asthma and heart disease that increase the risk of complications occurring after influenza virus infection. Epidemics of influenza occur because small but frequent changes in the influenza virus mean that an immune response produced one year through infection provides only partial protection against influenza the following year. Annual immunization with a vaccine that contains killed influenza viruses of the major circulating strains can greatly reduce a person's risk of catching influenza by preparing the immune system to respond quickly when challenged by a live influenza virus. Consequently, many countries run seasonal influenza vaccination programs that, in line with World Health Organization recommendations, target individuals 65 years old and older and people in high-risk groups.
Why Was This Study Done?
Is this approach the best use of available resources? Might, for example, vaccination of children—the main transmitters of influenza—provide more benefit to the whole population than vaccination of elderly people? Vaccination of children would not directly prevent as many influenza-related deaths as vaccination of elderly people, but it might indirectly prevent deaths in elderly adults by inducing herd immunity—vaccination of a large part of a population can protect unvaccinated members of the population by reducing the chances of an infection spreading. Policy makers need to know whether a change to an influenza vaccination program is likely to provide additional population benefits before altering the program. In this evidence synthesis and modeling study, the researchers combine (synthesize) longitudinal influenza surveillance datasets (data collected over time) from England and Wales, develop a mathematical model for influenza transmission based on these data using a Bayesian statistical approach, and use the model to evaluate the impact on influenza infections and deaths of changes to the seasonal influenza vaccination program in England and Wales.
What Did the Researchers Do and Find?
The researchers developed an influenza transmission model using clinical data on influenza-like illness consultations collected in a primary care surveillance scheme for each week of 14 influenza seasons in England and Wales, virological information on respiratory viruses detected in a subset of patients presenting with clinically suspected influenza, and data on vaccination coverage in the whole population (epidemiological data). They also incorporated data on social contacts (behavioral data) and on immunity to influenza viruses in the population (seroepidemiological data) into their model. To estimate the impact of potential changes to the current vaccination strategy in England and Wales, the researchers used their model, which replicated the patterns of disease observed in the surveillance data, to run simulated epidemics for each influenza season and for three strains of influenza virus under various vaccination scenarios. Compared to no vaccination, the current program (vaccination of people 65 years old and older and people in high-risk groups) averted 0.39 infections per dose of vaccine and 1.74 deaths per 1,000 doses. Notably, the model predicted that extension of the program to target 5–16-year-old children would increase the efficiency of the program and would avert 0.70 infections per dose and 1.95 deaths per 1,000 doses.
What Do These Findings Mean?
The finding that the transmission model developed by the researchers closely fit the available surveillance data suggests that the model should be able to predict what would have happened in England and Wales over the study period if an alternative vaccination regimen had been in place. The accuracy of such predictions may be limited, however, because the vaccination model is based on a series of simplifying assumptions. Importantly, given that influenza vaccination for children is being rolled out in England and Wales from September 2013, the model confirms that children are key spreaders of influenza and suggests that a vaccination program targeting children will reduce influenza infections and potentially influenza deaths in the whole population. More generally, the findings of this study support wider adoption of national vaccination strategies designed to block influenza transmission and to target those individuals most at risk from the complications of influenza infection.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371.journal.pmed.1001527.
The UK National Health Service Choices website provides information for patients about seasonal influenza and about vaccination; Public Health England (formerly the Health Protection Agency) provides information on influenza surveillance in the UK, including information about the primary care surveillance database used in this study
The World Health Organization provides information on seasonal influenza (in several languages)
The European Influenzanet is a system to monitor the activity of influenza-like illness with the aid of volunteers via the Internet
The US Centers for Disease Control and Prevention also provides information for patients and health professionals on all aspects of seasonal influenza, including information about vaccination and about the US influenza surveillance system; its website contains a short video about personal experiences of influenza
Flu.gov, a US government website, provides access to information on seasonal influenza and vaccination
MedlinePlus has links to further information about influenza and about immunization (in English and Spanish)
doi:10.1371/journal.pmed.1001527
PMCID: PMC3793005  PMID: 24115913
11.  Indigenous Health and Socioeconomic Status in India 
PLoS Medicine  2006;3(10):e421.
Background
Systematic evidence on the patterns of health deprivation among indigenous peoples remains scant in developing countries. We investigate the inequalities in mortality and substance use between indigenous and non-indigenous, and within indigenous, groups in India, with an aim to establishing the relative contribution of socioeconomic status in generating health inequalities.
Methods and Findings
Cross-sectional population-based data were obtained from the 1998–1999 Indian National Family Health Survey. Mortality, smoking, chewing tobacco use, and alcohol use were four separate binary outcomes in our analysis. Indigenous status in the context of India was operationalized through the Indian government category of scheduled tribes, or Adivasis, which refers to people living in tribal communities characterized by distinctive social, cultural, historical, and geographical circumstances.
Indigenous groups experience excess mortality compared to non-indigenous groups, even after adjusting for economic standard of living (odds ratio 1.22; 95% confidence interval 1.13–1.30). They are also more likely to smoke and (especially) drink alcohol, but the prevalence of chewing tobacco is not substantially different between indigenous and non-indigenous groups. There are substantial health variations within indigenous groups, such that indigenous peoples in the bottom quintile of the indigenous-peoples-specific standard of living index have an odds ratio for mortality of 1.61 (95% confidence interval 1.33–1.95) compared to indigenous peoples in the top fifth of the wealth distribution. Smoking, drinking alcohol, and chewing tobacco also show graded associations with socioeconomic status within indigenous groups.
Conclusions
Socioeconomic status differentials substantially account for the health inequalities between indigenous and non-indigenous groups in India. However, a strong socioeconomic gradient in health is also evident within indigenous populations, reiterating the overall importance of socioeconomic status for reducing population-level health disparities, regardless of indigeneity.
Indigenous groups in India were found to have excess mortality rates compared with non-indigenous groups. A socioeconomic gradient within indigenous populations was also found.
Editors' Summary
Background.
In many parts of the world the majority of the population are the descendants of immigrants who arrived there within the last few hundred years. Living alongside of them, and in a minority, are the so-called indigenous (or aboriginal) people who are the descendants of people who lived there in more ancient times. It is estimated that there are 300 million indigenous people worldwide. They are frequently marginalized from the rest of the population, their human rights are often abused, and there are serious concerns about their health and welfare. The state of health of the indigenous people of developed countries such as the US and Australia has often been studied, and we have a fairly clear idea of the kinds of problems these people face. Most indigenous people, however, live in developing countries, and less is known about their health.
India is the second-most populous country in the world, with an estimated 1.1 billion inhabitants. An estimated 90 million indigenous people live in India, where they are often referred to as “scheduled tribes” or Adivasis. They live in many parts of the country but are much more numerous in some Indian states than in others.
Why Was This Study Done?
It has often been said that indigenous people in India have worse health than other Indians, though no figures have been compiled to confirm these claims. The researchers wanted to establish whether it is simply an issue of indigenous people being poorer than other Indians—poverty being well known as a cause of disease—or whether being indigenous is, in itself, a health risk. The researchers also wanted to establish whether there are health inequalities within indigenous groups, and if these differences also followed a socioeconomic patterning.
What Did the Researchers Do and Find?
They used figures collected in the 1998–1999 Indian National Family Health Survey. When this survey was conducted, it was noted whether people were considered to be members of scheduled tribes. The researchers also knew, from the survey, about the income of the families, their death rates, and whether they drank alcohol or smoked or chewed tobacco. They found that indigenous people had higher death rates than other Indians. They made statistical calculations to account for differences in standard of living, and this substantially reduced the difference in death rate among indigenous groups, but an indigenous person was still 1.2 times more likely to die than a non-indigenous person with the same standard of living. Indigenous people were also more likely to drink alcohol and smoke tobacco, and here again, differences in standard of living accounted for a substantial portion of the differences. Importantly, the researchers' analysis showed a strong socioeconomic patterning of health inequalities within the indigenous population groups: the health differences between the poorest and richest indigenous groups were similar in scale to the differences between the poorest and richest non-indigenous groups.
What Do These Findings Mean?
The authors consider their finding that there is a socioeconomic gradient in mortality and health behaviors among indigenous people to be an important result from the study. The socioeconomic marginalization of indigenous people from the rest of Indian society does seem to increase their health risks, and so does their use of alcohol and tobacco. However, if their standard of living can be improved there would be major benefits for their health and welfare.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0030421.
A useful discussion of the term “indigenous people” (with links to documents about international agreements intended to improve their human rights) may be found on Wikipedia. (Wikipedia is an internet encyclopedia that anyone can edit.)
Survival International is a human rights organization that campaigns for the rights of indigenous peoples, helping them preserve their land and culture.
The charity Health Unlimited also works with indigenous people and its Web site includes links to recent studies and conferences.
A news item from the BBC describes a recent investigation into the health of indigenous people worldwide.
The World Health Organization has produced a number of reports on the health of indigenous people
doi:10.1371/journal.pmed.0030421
PMCID: PMC1621109  PMID: 17076556
12.  The severity of pandemic H1N1 influenza in the United States, April – July 2009 
PLoS Currents  2009;1:RRN1042.
Background
Accurate measures of the severity of pandemic influenza A/H1N1 (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely.
Methods and Findings
We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data: medically attended cases in Milwaukee or self-reported influenza-like illness in New York, were used to estimate ratios of symptomatic cases:hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic cases that died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated sCFR of 0.048% (95% credible interval, CI 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately7-9x lower. sCFR and sCIR appear to be highest in persons 18 and older, and lowest in children 5-17. sCHR appears to be lowest in persons 5-17; our data were too sparse to allow us to determine the group in which it was highest.
Conclusions
These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with greatest impact in young children and non-elderly adults. These estimates of impact depend on assumptions about total incidence of infection in the autumn-winter. Impacts would larger if autumn-winter incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the proportion infected or symptomatic were lower.
doi:10.1371/currents.RRN1042
PMCID: PMC2762775  PMID: 20029614
13.  The severity of pandemic H1N1 influenza in the United States, April – July 2009 
PLoS Currents  2009;1:RRN1042.
Background
Accurate measures of the severity of pandemic influenza A/H1N1 (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely.
Methods and Findings
We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data: medically attended cases in Milwaukee or self-reported influenza-like illness in New York, were used to estimate ratios of symptomatic cases:hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic cases that died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated sCFR of 0.048% (95% credible interval, CI 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately7-9x lower. sCFR and sCIR appear to be highest in persons 18 and older, and lowest in children 5-17. sCHR appears to be lowest in persons 5-17; our data were too sparse to allow us to determine the group in which it was highest.
Conclusions
These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with greatest impact in young children and non-elderly adults. These estimates of impact depend on assumptions about total incidence of infection in the autumn-winter. Impacts would larger if autumn-winter incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the proportion infected or symptomatic were lower.
doi:10.1371/currents.RRN1042
PMCID: PMC2762775  PMID: 20029614
14.  The severity of pandemic H1N1 influenza in the United States, April – July 2009 
PLoS Currents  2009;1:RRN1042.
This knol is in the midst of revision. Please do not read until this notice has been removed
Background
Accurate measures of the severity of pandemic influenza A/H1N1 (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely.
Methods and Findings
We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data: medically attended cases in Milwaukee or self-reported influenza-like illness in New York, were used to estimate ratios of symptomatic cases:hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic cases that died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated sCFR of 0.048% (95% credible interval, CI 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately7-9x lower. sCFR and sCIR appear to be highest in persons 18 and older, and lowest in children 5-17. sCHR appears to be lowest in persons 5-17; our data were too sparse to allow us to determine the group in which it was highest.
Conclusions
These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with greatest impact in young children and non-elderly adults. These estimates of impact depend on assumptions about total incidence of infection in the autumn-winter. Impacts would larger if autumn-winter incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the proportion infected or symptomatic were lower.
doi:10.1371/currents.RRN1042
PMCID: PMC2762775  PMID: 20029614
15.  The severity of pandemic H1N1 influenza in the United States, April – July 2009 
PLoS Currents  2009;1:RRN1042.
This knol is in the midst of revision. Please do not read until this notice has been removed
Background
Accurate measures of the severity of pandemic influenza A/H1N1 (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely.
Methods and Findings
We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data: medically attended cases in Milwaukee or self-reported influenza-like illness in New York, were used to estimate ratios of symptomatic cases:hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic cases that died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated sCFR of 0.048% (95% credible interval, CI 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately7-9x lower. sCFR and sCIR appear to be highest in persons 18 and older, and lowest in children 5-17. sCHR appears to be lowest in persons 5-17; our data were too sparse to allow us to determine the group in which it was highest.
Conclusions
These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with greatest impact in young children and non-elderly adults. These estimates of impact depend on assumptions about total incidence of infection in the autumn-winter. Impacts would larger if autumn-winter incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the proportion infected or symptomatic were lower.
doi:10.1371/currents.RRN1042
PMCID: PMC2762775  PMID: 20029614
16.  The severity of pandemic H1N1 influenza in the United States, April – July 2009 
PLoS Currents  2009;1:RRN1042.
Background
Accurate measures of the severity of pandemic influenza A/H1N1 (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely.
Methods and Findings
We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data: medically attended cases in Milwaukee or self-reported influenza-like illness in New York, were used to estimate ratios of symptomatic cases:hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic cases that died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated sCFR of 0.048% (95% credible interval, CI 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately7-9x lower. sCFR and sCIR appear to be highest in persons 18 and older, and lowest in children 5-17. sCHR appears to be lowest in persons 5-17; our data were too sparse to allow us to determine the group in which it was highest.
Conclusions
These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with greatest impact in young children and non-elderly adults. These estimates of impact depend on assumptions about total incidence of infection in the autumn-winter. Impacts would larger if autumn-winter incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the proportion infected or symptomatic were lower.
doi:10.1371/currents.RRN1042
PMCID: PMC2762775  PMID: 20029614
17.  The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States. 
Environmental Health Perspectives  2001;109(Suppl 2):185-189.
Heat and heat waves are projected to increase in severity and frequency with increasing global mean temperatures. Studies in urban areas show an association between increases in mortality and increases in heat, measured by maximum or minimum temperature, heat index, and sometimes, other weather conditions. Health effects associated with exposure to extreme and prolonged heat appear to be related to environmental temperatures above those to which the population is accustomed. Models of weather-mortality relationships indicate that populations in northeastern and midwestern U.S. cities are likely to experience the greatest number of illnesses and deaths in response to changes in summer temperature. Physiologic and behavioral adaptations may reduce morbidity and mortality. Within heat-sensitive regions, urban populations are the most vulnerable to adverse heat-related health outcomes. The elderly, young children, the poor, and people who are bedridden or are on certain medications are at particular risk. Heat-related illnesses and deaths are largely preventable through behavioral adaptations, including the use of air conditioning and increased fluid intake. Overall death rates are higher in winter than in summer, and it is possible that milder winters could reduce deaths in winter months. However, the relationship between winter weather and mortality is difficult to interpret. Other adaptation measures include heat emergency plans, warning systems, and illness management plans. Research is needed to identify critical weather parameters, the associations between heat and nonfatal illnesses, the evaluation of implemented heat response plans, and the effectiveness of urban design in reducing heat retention.
PMCID: PMC1240665  PMID: 11359685
18.  Reduced Glomerular Filtration Rate and Its Association with Clinical Outcome in Older Patients at Risk of Vascular Events: Secondary Analysis 
PLoS Medicine  2009;6(1):e1000016.
Background
Reduced glomerular filtration rate (GFR) is associated with increased cardiovascular risk in young and middle aged individuals. Associations with cardiovascular disease and mortality in older people are less clearly established. We aimed to determine the predictive value of the GFR for mortality and morbidity using data from the 5,804 participants randomized in the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER).
Methods and Findings
Glomerular filtration rate was estimated (eGFR) using the Modification of Diet in Renal Disease equation and was categorized in the ranges ([20–40], [40–50], [50–60]) ≥ 60 ml/min/1.73 m2. Baseline risk factors were analysed by category of eGFR, with and without adjustment for other risk factors. The associations between baseline eGFR and morbidity and mortality outcomes, accrued after an average of 3.2 y, were investigated using Cox proportional hazard models adjusting for traditional risk factors. We tested for evidence of an interaction between the benefit of statin treatment and baseline eGFR status. Age, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol, C-reactive protein (CRP), body mass index, fasting glucose, female sex, histories of hypertension and vascular disease were associated with eGFR (p = 0.001 or less) after adjustment for other risk factors. Low eGFR was independently associated with risk of all cause mortality, vascular mortality, and other noncancer mortality and with fatal and nonfatal coronary and heart failure events (hazard ratios adjusted for CRP and other risk factors (95% confidence intervals [CIs]) for eGFR < 40 ml/min/1.73m2 relative to eGFR ≥ 60 ml/min/1.73m2 respectively 2.04 (1.48–2.80), 2.37 (1.53–3.67), 3.52 (1.78–6.96), 1.64 (1.18–2.27), 3.31 (2.03–5.41). There were no nominally statistically significant interactions (p < 0.05) between randomized treatment allocation and eGFR for clinical outcomes, with the exception of the outcome of coronary heart disease death or nonfatal myocardial infarction (p = 0.021), with the interaction suggesting increased benefit of statin treatment in subjects with impaired GFRs.
Conclusions
We have established that, in an elderly population over the age of 70 y, impaired GFR is associated with female sex, with presence of vascular disease, and with levels of other risk factors that would be associated with increased risk of vascular disease. Further, impaired GFR is independently associated with significant levels of increased risk of all cause mortality and fatal vascular events and with composite fatal and nonfatal coronary and heart failure outcomes. Our analyses of the benefits of statin treatment in relation to baseline GFR suggest that there is no reason to exclude elderly patients with impaired renal function from treatment with a statin.
Using data from the PROSPER trial, Ian Ford and colleagues investigate whether reduced glomerular filtration rate is associated with cardiovascular and mortality risk among elderly people.
Editors' Summary
Background.
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a common cause of death in developed countries. In the USA, for example, the single leading cause of death is coronary heart disease, a CVD in which narrowing of the heart's blood vessels slows or stops the blood supply to the heart and eventually causes a heart attack. Other types of CVD include stroke (in which narrowing of the blood vessels interrupts the brain's blood supply) and heart failure (a condition in which the heart can no longer pump enough blood to the rest of the body). Many factors increase the risk of developing CVD, including high blood pressure (hypertension), high blood cholesterol, having diabetes, smoking, and being overweight. Tools such as the “Framingham risk calculator” assess an individual's overall CVD risk by taking these and other risk factors into account. CVD risk can be minimized by taking drugs to reduce blood pressure or cholesterol levels (for example, pravastatin) and by making lifestyle changes.
Why Was This Study Done?
Another potential risk factor for CVD is impaired kidney (renal) function. In healthy people, the kidneys filter waste products and excess fluid out of the blood. A reduced “estimated glomerular filtration rate” (eGFR), which indicates impaired renal function, is associated with increased CVD in young and middle-aged people and increased all-cause and cardiovascular death in people who have vascular disease. But is reduced eGFR also associated with CVD and death in older people? If it is, it would be worth encouraging elderly people with reduced eGFR to avoid other CVD risk factors. In this study, the researchers determine the predictive value of eGFR for all-cause and vascular mortality (deaths caused by CVD) and for incident vascular events (a first heart attack, stroke, or heart failure) using data from the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER). This clinical trial examined pravastatin's effects on CVD development among 70–82 year olds with pre-existing vascular disease or an increased risk of CVD because of smoking, hypertension, or diabetes.
What Did the Researchers Do and Find?
The trial participants were divided into four groups based on their eGFR at the start of the study. The researchers then investigated the association between baseline CVD risk factors and baseline eGFR and between baseline eGFR and vascular events and deaths that occurred during the 3-year study. Several established CVD risk factors were associated with a reduced eGFR after allowing for other risk factors. In addition, people with a low eGFR (between 20 and 40 units) were twice as likely to die from any cause as people with an eGFR above 60 units (the normal eGFR for a young person is 100 units; eGFR decreases with age) and more than three times as likely to have nonfatal coronary heart disease or heart failure. A low eGFR also increased the risk of vascular mortality, other noncancer deaths, and fatal coronary heart disease and heart failure. Finally, pravastatin treatment reduced coronary heart disease deaths and nonfatal heart attacks most effectively among participants with the greatest degree of eGFR impairment.
What Do These Findings Mean?
These findings suggest that, in elderly people, impaired renal function is associated with levels of established CVD risk factors that increase the risk of vascular disease. They also suggest that impaired kidney function increases the risk of all-cause mortality, fatal vascular events, and fatal and nonfatal coronary heat disease and heart failure. Because the study participants were carefully chosen for inclusion in PROSPER, these findings may not be generalizable to all elderly people with vascular disease or vascular disease risk factors. Nevertheless, increased efforts should probably be made to encourage elderly people with reduced eGFR and other vascular risk factors to make lifestyle changes to reduce their overall CVD risk. Finally, although the effect of statins in elderly patients with renal dysfunction needs to be examined further, these findings suggest that this group of patients should benefit at least as much from statins as elderly patients with healthy kidneys.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000016.
The MedlinePlus Encyclopedia has pages on coronary heart disease, stroke, and heart failure (in English and Spanish)
MedlinePlus provides links to many other sources of information on heart disease, vascular disease, and stroke (in English and Spanish)
The US National Institute of Diabetes and Digestive and Kidney Diseases provides information on how the kidneys work and what can go wrong with them, including a list of links to further information about kidney disease
The American Heart Association provides information on all aspects of cardiovascular disease for patients, caregivers, and professionals (in several languages)
More information about PROSPER is available on the Web site of the Vascular Biochemistry Department of the University of Glasgow
doi:10.1371/journal.pmed.1000016
PMCID: PMC2628400  PMID: 19166266
19.  Excess winter mortality in Europe: a cross country analysis identifying key risk factors 
Objective: Much debate remains regarding why certain countries experience dramatically higher winter mortality. Potential causative factors other than cold exposure have rarely been analysed. Comparatively less research exists on excess winter deaths in southern Europe. Multiple time series data on a variety of risk factors are analysed against seasonal-mortality patterns in 14 European countries to identify key relations
Subjects and setting: Excess winter deaths (all causes), 1988–97, EU-14.
Design: Coefficients of seasonal variation in mortality are calculated for EU-14 using monthly mortality data. Comparable, longitudinal datasets on risk factors pertaining to climate, macroeconomy, health care, lifestyle, socioeconomics, and housing were also obtained. Poisson regression identifies seasonality relations over time.
Results: Portugal suffers from the highest rates of excess winter mortality (28%, CI=25% to 31%) followed jointly by Spain (21%, CI=19% to 23%), and Ireland (21%, CI=18% to 24%). Cross country variations in mean winter environmental temperature (regression coefficient (ß)=0.27), mean winter relative humidity (ß=0.54), parity adjusted per capita national income (ß=1.08), per capita health expenditure (ß=-1.19), rates of income poverty (ß=-0.47), inequality (ß=0.97), deprivation (ß=0.11), and fuel poverty (ß=0.44), and several indicators of residential thermal standards are found to be significantly related to variations in relative excess winter mortality at the 5% level. The strong, positive relation with environmental temperature and strong negative relation with thermal efficiency indicate that housing standards in southern and western Europe play strong parts in such seasonality.
Conclusions: High seasonal mortality in southern and western Europe could be reduced through improved protection from the cold indoors, increased public spending on health care, and improved socioeconomic circumstances resulting in more equitable income distribution.
doi:10.1136/jech.57.10.784
PMCID: PMC1732295  PMID: 14573581
20.  Respiratory symptoms in older people and their association with mortality 
Thorax  2005;60(4):331-334.
Methods: A total of 14 458 people aged 75 years and over participating in a trial of health screening of older people in general practice answered questions on three respiratory symptoms: cough, sputum production, and wheeze. The association of symptoms with mortality was examined for all cause and respiratory causes of death taking account of potential confounders.
Results: Coughing up phlegm in winter mornings had a prevalence of 27.0% (95% confidence interval (CI) 26.8 to 27.2). Those with this symptom had an adjusted hazard ratio for all cause mortality of 1.35 (95% CI 1.21 to 1.50), p<0.001 and for respiratory specific mortality of 2.01 (95% CI 1.66 to 2.41), p<0.001. Phlegm at any time of the day in winter had a prevalence of 16.5% (95% CI 16.3 to 16.7) with hazard ratios for all cause and respiratory specific mortality of 1.28 (95% CI 1.15 to 1.42) and 2.28 (95% CI 1.92 to 2.70), p<0.001. Wheeze or whistling from the chest had a prevalence of 14.3% (95% CI 14.1 to 14.5) with hazard ratios of 1.45 (95% CI 1.31 to 1.61) and 2.86 (95% CI 2.45 to 3.35), p<0.001.
Conclusions: The prevalence of respiratory symptoms is widespread among elderly people and their presence is a strong predictor of mortality.
doi:10.1136/thx.2004.029579
PMCID: PMC1747384  PMID: 15790990
21.  Hand Sanitiser Provision for Reducing Illness Absences in Primary School Children: A Cluster Randomised Trial 
PLoS Medicine  2014;11(8):e1001700.
In a cluster randomized trial, Patricia Priest and colleagues find that providing hand sanitizer along with hand hygiene education in primary school classrooms, compared with hand hygiene alone, does not reduce school absences.
Please see later in the article for the Editors' Summary
Background
The potential for transmission of infectious diseases offered by the school environment are likely to be an important contributor to the rates of infectious disease experienced by children. This study aimed to test whether the addition of hand sanitiser in primary school classrooms compared with usual hand hygiene would reduce illness absences in primary school children in New Zealand.
Methods and Findings
This parallel-group cluster randomised trial took place in 68 primary schools, where schools were allocated using restricted randomisation (1∶1 ratio) to the intervention or control group. All children (aged 5 to 11 y) in attendance at participating schools received an in-class hand hygiene education session. Schools in the intervention group were provided with alcohol-based hand sanitiser dispensers in classrooms for the winter school terms (27 April to 25 September 2009). Control schools received only the hand hygiene education session. The primary outcome was the number of absence episodes due to any illness among 2,443 follow-up children whose caregivers were telephoned after each absence from school. Secondary outcomes measured among follow-up children were the number of absence episodes due to specific illness (respiratory or gastrointestinal), length of illness and illness absence episodes, and number of episodes where at least one other member of the household became ill subsequently (child or adult). We also examined whether provision of sanitiser was associated with experience of a skin reaction. The number of absences for any reason and the length of the absence episode were measured in all primary school children enrolled at the schools. Children, school administrative staff, and the school liaison research assistants were not blind to group allocation. Outcome assessors of follow-up children were blind to group allocation. Of the 1,301 and 1,142 follow-up children in the hand sanitiser and control groups, respectively, the rate of absence episodes due to illness per 100 child-days was similar (1.21 and 1.16, respectively, incidence rate ratio 1.06, 95% CI 0.94 to 1.18). The provision of an alcohol-based hand sanitiser dispenser in classrooms was not effective in reducing rates of absence episodes due to respiratory or gastrointestinal illness, the length of illness or illness absence episodes, or the rate of subsequent infection for other members of the household in these children. The percentage of children experiencing a skin reaction was similar (10.4% hand sanitiser versus 10.3% control, risk ratio 1.01, 95% CI 0.78 to 1.30). The rate or length of absence episodes for any reason measured for all children also did not differ between groups. Limitations of the study include that the study was conducted during an influenza pandemic, with associated public health messaging about hand hygiene, which may have increased hand hygiene among all children and thereby reduced any additional effectiveness of sanitiser provision. We did not quite achieve the planned sample size of 1,350 follow-up children per group, although we still obtained precise estimates of the intervention effects. Also, it is possible that follow-up children were healthier than non-participating eligible children, with therefore less to gain from improved hand hygiene. However, lack of effectiveness of hand sanitiser provision on the rate of absences among all children suggests that this may not be the explanation.
Conclusions
The provision of hand sanitiser in addition to usual hand hygiene in primary schools in New Zealand did not prevent disease of severity sufficient to cause school absence.
Trial registration
Australian New Zealand Clinical Trials Registry ACTRN12609000478213
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Throughout human history, infectious diseases have been major killers. In the 1300 s, for example, the black death killed a third of the European population. Other diseases such as smallpox and cholera have also devastated human populations. Now, though, a better understanding of the bacteria, viruses, and other microbes that cause infectious diseases and the availability of effective vaccines and antibiotics mean that, for the first time in human history, non-communicable (chronic) diseases such as heart attacks and strokes are killing and disabling more people around the world than infectious diseases. But this does not mean that we can be complacent about infectious diseases. The control of infectious diseases remains important, even in high-income countries, because of the contribution of infectious diseases to ill-health and because we need to manage the risk of epidemics and pandemics (disease outbreaks that affect a large proportion of the population of a country or the world, respectively) of influenza and other diseases.
Why Was This Study Done?
The control of infectious disease transmission in children is a particularly important component of disease control because children tend to have high rates of infectious disease and to have more physical contact with peers and with adults than other age groups, particularly in the school environment. It might be possible, therefore, to reduce the occurrence of many infectious respiratory and gastrointestinal diseases in communities by interrupting the transmission of infectious diseases between children at school, but how can this be achieved? In health care settings, good hand hygiene is a key component of infectious disease control, so, here, the researchers undertake a cluster randomized trial among primary school children in New Zealand to investigate whether the promotion of extra hand cleaning through the provision of alcohol-based hand sanitizer in classrooms can reduce illness absences among school children compared with normal hand hygiene (washing with soap and water, mainly in school bathrooms). A cluster randomized trial compares the outcomes of groups of participants (in this case, schools) chosen randomly to receive different interventions.
What Did the Researchers Do and Find?
The researchers randomly assigned 68 city primary schools to the intervention or control group. All the children (aged 5–11 years) attending the participating schools received a thirty-minute in-class hand hygiene education session. Alcohol-based hand sanitizer dispensers were installed in the classrooms of the intervention schools during the winter term, and the children were asked to use the dispensers after coughing or sneezing and on the way out of the classroom for morning break and lunch. The researchers report that the trial's primary outcome—the rate of absence episodes per 100 child-days due to any illness among “follow-up” children, individuals whose caregivers agreed to be asked about the reason for any absence—was similar in the intervention and control groups. Moreover, among the follow-up children, the provision of hand sanitizer did not reduce the number of absences due to a specific illness (respiratory or gastrointestinal), the length of illness and length of absence from school, or the number of episodes in which at least one other family member became ill. Finally, the number of absences for any reason, and length of absence episodes, in all the children enrolled at the participating schools did not differ between the intervention and control groups.
What Do These Findings Mean?
These findings suggest that the provision of hand sanitizer in addition to usual hand hygiene in primary schools in New Zealand did not prevent any infectious diseases severe enough to warrant school absence. Because the trial was undertaken during an influenza epidemic, influenza-related public health messages about good hand hygiene may have increased hand hygiene among all the children in the study and lessened the intervention's effectiveness. Other study limitations—including that only a third of caregivers agreed to be contacted about their child's absences, and these may have been caregivers who had already taught their children good hand hygiene—may also affect the accuracy of these findings and their generalizability to other high-income countries. However, these findings suggest that, in high-income countries where clean water for hand washing is readily available, putting resources into extra hand hygiene by providing hand sanitizer in classrooms may not be an effective way to break the child-to-child transmission of infectious diseases.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001700.
The US Centers for Disease Control and Prevention has information about hand-washing, when and how to wash your hands and use sanitizer, and hand-washing as a family activity; it also provides information about the importance of hand hygiene in health care settings
Public Health England provides information about hand-washing; its webpage about hand-washing in primary schools contains links to lesson plans about hand-washing for children aged 5–7 years and to e-Bug, a web-based student resource about infectious diseases and their prevention for children aged 7–14 years
Kidshealth, a US-based not-for-profit organization, also provides information about the importance of hand-washing for parents, kids, and teens (in English and Spanish)
doi:10.1371/journal.pmed.1001700
PMCID: PMC4130492  PMID: 25117155
22.  Significant Reduction of Antibiotic Use in the Community after a Nationwide Campaign in France, 2002–2007 
PLoS Medicine  2009;6(6):e1000084.
Didier Guillemot and colleagues describe the evaluation of a nationwide programme in France aimed at decreasing unnecessary outpatient prescriptions for antibiotics. The campaign was successful, particularly in reducing prescriptions for children.
Background
Overuse of antibiotics is the main force driving the emergence and dissemination of bacterial resistance in the community. France consumes more antibiotics and has the highest rate of beta-lactam resistance in Streptococcus pneumoniae than any other European country. In 2001, the government initiated “Keep Antibiotics Working”; the program's main component was a campaign entitled “Les antibiotiques c'est pas automatique” (“Antibiotics are not automatic”) launched in 2002. We report the evaluation of this campaign by analyzing the evolution of outpatient antibiotic use in France 2000–2007, according to therapeutic class and geographic and age-group patterns.
Methods and Findings
This evaluation is based on 2000–2007 data, including 453,407,458 individual reimbursement data records and incidence of flu-like syndromes (FLSs). Data were obtained from the computerized French National Health Insurance database and provided by the French Sentinel Network. As compared to the preintervention period (2000–2002), the total number of antibiotic prescriptions per 100 inhabitants, adjusted for FLS frequency during the winter season, changed by −26.5% (95% confidence interval [CI] −33.5% to −19.6%) over 5 years. The decline occurred in all 22 regions of France and affected all antibiotic therapeutic classes except quinolones. The greatest decrease, −35.8% (95% CI −48.3% to −23.2%), was observed among young children aged 6–15 years. A significant change of −45% in the relationship between the incidence of flu-like syndromes and antibiotic prescriptions was observed.
Conclusions
The French national campaign was associated with a marked reduction of unnecessary antibiotic prescriptions, particularly in children. This study provides a useful method for assessing public-health strategies designed to reduce antibiotic use.
Editors' Summary
Background
In 1928, Alexander Fleming discovered penicillin, the first antibiotic (a drug that kills bacteria). By the early 1940s, large amounts of penicillin could be made and, in the following decades, several other classes of powerful antibiotics were discovered. For a time, it looked like bacteria and the diseases that they cause had been defeated. But bacteria rapidly became resistant to these wonder drugs and nowadays, antibiotic resistance is a pressing public-health concern. Almost every type of disease-causing bacteria has developed resistance to one or more antibiotic in clinical use, and multidrug-resistant bacteria are causing outbreaks of potentially fatal diseases in hospitals and in the community. For example, multidrug-resistant Streptococcus pneumoniae (multidrug-resistant pneumococci or MRP) is now very common. S. pneumoniae colonize the nose and throat (the upper respiratory tract) and can cause diseases that range from mild ear infections to life-threatening pneumonia, particularly in young children and elderly people.
Why Was This Study Done?
For years, doctors have been prescribing (and patients have been demanding) antibiotics for viral respiratory infections (VRIs) such as colds and flu even though antibiotics do not cure viral infections. This overuse of antibiotics has been the main driving force in the spread of MRP. Thus, the highest rate of S. pneumoniae antibiotic resistance in Europe occurs in France, which has one of the highest rates of antibiotic consumption in the world. In 2001 France initiated “le plan national pour préserver l'efficacité des antibiotiques” to reduce the inappropriate use of antibiotics, particularly for the treatment of VRIs among children. The main component of the program was the “Antibiotiques c'est pas automatique” (“Antibiotics are not automatic”) campaign, which ran from 2002 to 2007 during the winter months when VRIs mainly occur. The campaign included an educational campaign for health care workers, the promotion of rapid tests for diagnosis of streptococcal infections, and a public information campaign about VRIs and about antibiotic resistance. In this study, the researchers evaluate the campaign by analyzing outpatient antibiotic use throughout France from 2000 to 2007.
What Did the Researchers Do and Find?
The researchers obtained information about antibiotic prescriptions and about the occurrence of flu-like illnesses during the study period from the French National Health Insurance database and national disease surveillance system, respectively. After adjusting for variations in the frequency of flu-like illnesses, compared to the preintervention period (2000–2002), the number of antibiotic prescriptions per 100 inhabitants decreased by a quarter over the five winters of the “Antibiotics are not automatic” campaign. The use of all major antibiotic classes except quinolones decreased in all 22 regions of France. Thus, whereas in 2000, more than 70 prescriptions per 100 inhabitants were issued during the winter in 15 regions, by 2006/7, no regions exceeded this prescription rate. The greatest decrease in prescription rate (a decrease of more than a third by 2006/7) was among children aged 6–15 years. Finally, although the rates of antibiotic prescriptions reflected the rates of flu-like illness throughout the campaign, by 2006/7 this relationship was much weaker, which suggests that fewer antibiotics were being prescribed for VRIs.
What Do These Findings Mean?
These findings indicate that the “Antibiotics are not automatic” campaign was associated with a reduction in antibiotic prescriptions, particularly in children. Because the whole French population was exposed to the campaign, these findings do not prove that the campaign actually caused the reduction in antibiotic prescriptions. The observed decrease might have been caused by other initiatives in France or elsewhere or by the introduction of a S. pneumoniae vaccine during the study period, for example. However, an independent survey indicated that fewer members of the public expected an antibiotic prescription for a VRI at the end of the campaign than at the start, that more people knew that antibiotics only kill bacteria, and that doctors were more confident about not prescribing antibiotics for VRIs. Thus, campaigns like “Antibiotics are not automatic” may be a promising way to reduce the overuse of antibiotics and to slow the spread of antibiotic resistance until new classes of effective antibiotics are developed.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000084.
This study is further discussed in a PLoS Medicine Perspective by Stephen Harbarth and Benedikt Huttner
The Bugs and Drugs Web site from the UK National electronic Library of Infection provides information about antibiotic resistance and links to other resources
The US National Institute of Allergy and Infectious Diseases provides information on antimicrobial drug resistance and on pneumococcal pneumonia
The US Centers for Disease Control and Prevention also have information on antibiotic resistance (in English and Spanish)
The European Surveillance of Antimicrobial Consumption Web site provides information on antibiotic consumption in European countries
Les antibiotiques c'est pas automatique provides information about the “Antibiotics are not automatic” campaign (in French)
Information on the Plan National pour Pérserver l'efficacité des antibiotiques is also available (in French)
doi:10.1371/journal.pmed.1000084
PMCID: PMC2683932  PMID: 19492093
23.  The Fall and Rise of US Inequities in Premature Mortality: 1960–2002 
PLoS Medicine  2008;5(2):e46.
Background
Debates exist as to whether, as overall population health improves, the absolute and relative magnitude of income- and race/ethnicity-related health disparities necessarily increase—or derease. We accordingly decided to test the hypothesis that health inequities widen—or shrink—in a context of declining mortality rates, by examining annual US mortality data over a 42 year period.
Methods and Findings
Using US county mortality data from 1960–2002 and county median family income data from the 1960–2000 decennial censuses, we analyzed the rates of premature mortality (deaths among persons under age 65) and infant death (deaths among persons under age 1) by quintiles of county median family income weighted by county population size. Between 1960 and 2002, as US premature mortality and infant death rates declined in all county income quintiles, socioeconomic and racial/ethnic inequities in premature mortality and infant death (both relative and absolute) shrank between 1966 and 1980, especially for US populations of color; thereafter, the relative health inequities widened and the absolute differences barely changed in magnitude. Had all persons experienced the same yearly age-specific premature mortality rates as the white population living in the highest income quintile, between 1960 and 2002, 14% of the white premature deaths and 30% of the premature deaths among populations of color would not have occurred.
Conclusions
The observed trends refute arguments that health inequities inevitably widen—or shrink—as population health improves. Instead, the magnitude of health inequalities can fall or rise; it is our job to understand why.
Nancy Krieger and colleagues found evidence of decreasing, and then increasing or stagnating, socioeconomic and racial inequities in US premature mortality and infant death from 1960 to 2002.
Editors' Summary
Background
One of the biggest aims of public health advocates and governments is to improve the health of the population. Improving health increases people's quality of life and helps the population be more economically productive. But within populations are often persistent differences (usually called “disparities” or “inequities”) in the health of different subgroups—between women and men, different income groups, and people of different races/ethnicities, for example. Researchers study these differences so that policy makers and the broader public can be informed about what to do to intervene. For example, if we know that the health of certain subgroups of the population—such as the poor—is staying the same or even worsening as the overall health of the population is improving, policy makers could design programs and devote resources to specifically target the poor.
To study health disparities, researchers use both relative and absolute measures. Relative inequities refer to ratios, while absolute inequities refer to differences. For example, if one group's average income level increases from $1,000 to $10,000 and another group's from $2,000 to $20,000, the relative inequality between the groups stays the same (i.e., the ratio of incomes between the two groups is still 2) but the absolute difference between the two groups has increased from $1,000 to $10,000.
Examining the US population, Nancy Krieger and colleagues looked at trends over time in both relative and absolute differences in mortality between people in different income groups and between whites and people of color.
Why Was This Study Done?
There has been a lot of debate about whether disparities have been widening or narrowing as overall population health improves. Some research has found that both total health and health disparities are getting better with time. Other research has shown that overall health gains mask worsening disparities—such that the rich get healthier while the poor get sicker.
Having access to more data over a longer time frame meant that Krieger and colleagues could provide a more complete picture of this sometimes contradictory story. It also meant they could test their hypothesis about whether, as population health improves, health inequities necessarily widen or shrink within the time period between the 1960s through the 1990s during which certain events and policies likely would have had an impact on the mortality trends in that country.
What Did the Researchers Do and Find?
In order to investigate health inequities, the authors chose to look at two common measures of population health: rates of premature mortality (dying before the age of 65 years) and rates of infant mortality (death before the age of 1).
To determine mortality rates, the authors used death statistics data from different counties, which are routinely collected by state and national governments. To be able to rank mortality rates for different income groups, they used data on the median family incomes of people living within those counties (meaning half the families had income above, and half had incomes below, the median value). They calculated mortality rates for the total population and for whites versus people of color. They used data from 1960 through 2002. They compared rates for 1966–1980 with two other time periods: 1960–1965 and 1981–2002. They also examined trends in the annual mortality rates and in the annual relative and absolute disparites in these rates by county income level.
Over the whole period 1960–2002, the authors found that premature mortality (death before the age of 65) and infant mortality (death before the age of 1) decreased for all income groups. But they also found that disparities between income groups and between whites and people of color were not the same over this time period. In fact, the economic disparities narrowed then widened. First, they shrank between 1966 and 1980, especially for Americans of color. After 1980, however, the relative health inequities widened and the absolute differences did not change. The authors conclude that if all people in the US population experienced the same health gains as the most advantaged did during these 42 years (i.e., as the whites in the highest income groups), 14% of the premature deaths among whites and 30% of the premature deaths among people of color would have been prevented.
What Do These Findings Mean?
The findings provide an overview of the trends in inequities in premature and infant mortality over a long period of time. Different explanations for these trends can now be tested. The authors discuss several potential reasons for these trends, including generally rising incomes across America and changes related to specific diseases, such as the advent of HIV/AIDS, changes in smoking habits, and better management of cancer and cardiovascular disease. But they find that these do not explain the fall then rise of inequities. Instead, the authors suggest that explanations lie in the social programs of the 1960s and the subsequent roll-back of some of these programmes in the 1980s. The US “War on Poverty,” civil rights legislation, and the establishment of Medicare occurred in the mid 1960s, which were intended to reduce socioeconomic and racial/ethnic inequalities and improve access to health care. In the 1980s there was a general cutting back of welfare state provisions in America, which included cuts to public health and antipoverty programs, tax relief for the wealthy, and worsening inequity in the access to and quality of health care. Together, these wider events could explain the fall then rise trends in mortality disparities.
The authors say their findings are important to inform and help monitor the progress of various policies and programmes, including those such as the Healthy People 2010 initiative in America, which aims to increase the quality and years of healthy life and decrease health disparities by the end of this decade.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed. 0050046.
Healthy People 2010 was created by the US Department of Health and Human Services along with scientists inside and outside of government and includes a comprehensive set of disease prevention and health promotion objectives for the US to achieve by 2010, with two overarching goals: to increase quality and years of healthy life and to eliminate health disparities
Johan Mackenbach and colleagues provide an overview of mortality inequalities in six Western European countries—Finland, Sweden, Norway, Denmark, England/Wales, and Italy—and conclude that eliminating mortality inequalities requires that more cardiovascular deaths among lower socioeconomic groups be prevented, as well as more attention be paid to rising death rates of lung cancer, breast cancer, respiratory disease, gastrointestinal disease, and injuries among women and men in the lower income groups.
The WHO Health for All program promotes health equity
A primer on absolute versus relative differences is provided by the American College of Physicians
doi:10.1371/journal.pmed.0050046
PMCID: PMC2253609  PMID: 18303941
24.  Mortality among residents near cokeworks in Great Britain 
OBJECTIVES: To investigate whether residents near cokeworks have a higher standardised mortality than those further away, particularly from cardiovascular and respiratory causes, which may be associated with pollution from cokeworks. METHOD: Cross sectional small area study with routinely collected postcoded mortality data and small area census statistics. Populations within 7.5 km of 22 cokeworks in Great Britain, 1981-92. Expected numbers of deaths within 2 and 7.5 km of cokeworks, and in eight distance bands up to 7.5 km of cokeworks, were calculated by indirect standardisation from national rates stratified for age and sex and a small area deprivation index, and adjusted for region. Age groups examined were all ages, 1-14, 15-64, 65-74, > or = 75. Only the 1-14 and 15-44 age groups were examined for asthma mortality. RESULTS: There was a 3% (95% confidence interval (95% CI) 1% to 4%) excess of all deaths within 2 km of cokeworks, and a significant decline in mortality with distance from cokeworks. The excess of deaths within 2 km was slightly higher for females and elderly people, but excesses within 2 km and declines in risk with distance were significant for all adult age groups and both sexes. The size of the excess within 2 km was 5% (95% CI 3% to 7%) for cardiovascular causes, 6% (95% CI 3% to 9%) for ischaemic heart disease, and 2% (95% CI -2% to 6%) for respiratory deaths, with significant declines in risk with distance for all these causes. There was a non-significant 15% (95% CI -1% to 101%) excess in asthma mortality in the 15-44 age group. There were no significant excesses in mortality among children but 95% CIs were wide. Within 2 km of cokeworks, the estimated additional excess all cause mortality for all ages combined related to region and mainly to the greater deprivation of the population over national levels was 12%. CONCLUSIONS: A small excess mortality near cokeworks as found in this study is plausible in the light of current evidence about the health impact of air pollution. However, in this study the effects of pollution from cokeworks, if any, are outweighed by the effects of deprivation on weighed by the effects of deprivation on mortality near cokeworks. It is not possible to confidently exclude socioeconomic confounding or biases resulting from inexact population estimation as explanations for the excess found.
 
PMCID: PMC1757656  PMID: 10341744
25.  Association between Class III Obesity (BMI of 40–59 kg/m2) and Mortality: A Pooled Analysis of 20 Prospective Studies 
PLoS Medicine  2014;11(7):e1001673.
In a pooled analysis of 20 prospective studies, Cari Kitahara and colleagues find that class III obesity (BMI of 40–59) is associated with excess rates of total mortality, particularly due to heart disease, cancer, and diabetes.
Please see later in the article for the Editors' Summary
Background
The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity.
Methods and Findings
In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per 100,000 persons per year) and multivariable-adjusted hazard ratios for adults, aged 19–83 y at baseline, classified as obese class III (BMI 40.0–59.9 kg/m2) compared with those classified as normal weight (BMI 18.5–24.9 kg/m2). Participants reporting ever smoking cigarettes or a history of chronic disease (heart disease, cancer, stroke, or emphysema) on baseline questionnaires were excluded. Among 9,564 class III obesity participants, mortality rates were 856.0 in men and 663.0 in women during the study period (1976–2009). Among 304,011 normal-weight participants, rates were 346.7 and 280.5 in men and women, respectively. Deaths from heart disease contributed largely to the excess rates in the class III obesity group (rate differences = 238.9 and 132.8 in men and women, respectively), followed by deaths from cancer (rate differences = 36.7 and 62.3 in men and women, respectively) and diabetes (rate differences = 51.2 and 29.2 in men and women, respectively). Within the class III obesity range, multivariable-adjusted hazard ratios for total deaths and deaths due to heart disease, cancer, diabetes, nephritis/nephrotic syndrome/nephrosis, chronic lower respiratory disease, and influenza/pneumonia increased with increasing BMI. Compared with normal-weight BMI, a BMI of 40–44.9, 45–49.9, 50–54.9, and 55–59.9 kg/m2 was associated with an estimated 6.5 (95% CI: 5.7–7.3), 8.9 (95% CI: 7.4–10.4), 9.8 (95% CI: 7.4–12.2), and 13.7 (95% CI: 10.5–16.9) y of life lost. A limitation was that BMI was mainly ascertained by self-report.
Conclusions
Class III obesity is associated with substantially elevated rates of total mortality, with most of the excess deaths due to heart disease, cancer, and diabetes, and major reductions in life expectancy compared with normal weight.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The number of obese people (individuals with an excessive amount of body fat) is increasing rapidly in many countries. Worldwide, according to the Global Burden of Disease Study 2013, more than a third of all adults are now overweight or obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30 kg/m2 (a 183-cm [6-ft] tall man who weighs more than 100 kg [221 lbs] is obese). Compared to people with a healthy weight (a BMI between 18.5 and 24.9 kg/m2), overweight and obese individuals (who have a BMI between 25.0 and 29.9 kg/m2 and a BMI of 30 kg/m2 or more, respectively) have an increased risk of developing diabetes, heart disease, stroke, and some cancers, and tend to die younger. Because people become unhealthily fat by consuming food and drink that contains more energy (kilocalories) than they need for their daily activities, obesity can be prevented or treated by eating less food and by increasing physical activity.
Why Was This Study Done?
Class III obesity (extreme, or morbid, obesity), which is defined as a BMI of more than 40 kg/m2, is emerging as a major public health problem in several high-income countries. In the US, for example, 6% of adults are now morbidly obese. Because extreme obesity used to be relatively uncommon, little is known about the burden of disease, including total and cause-specific mortality (death) rates, among individuals with class III obesity. Before we can prevent and treat class III obesity effectively, we need a better understanding of the health risks associated with this condition. In this pooled analysis of prospective cohort studies, the researchers evaluate the risk of total and cause-specific death and the years of life lost associated with class III obesity. A pooled analysis analyzes the data from several studies as if the data came from one large study; prospective cohort studies record the characteristics of a group of participants at baseline and follow them to see which individuals develop a specific condition.
What Did the Researchers Do and Find?
The researchers included 20 prospective (mainly US) cohort studies from the National Cancer Institute Cohort Consortium (a partnership that studies cancer by undertaking large-scale collaborations) in their pooled analysis. After excluding individuals who had ever smoked and people with a history of chronic disease, the analysis included 9,564 adults who were classified as class III obese based on self-reported height and weight at baseline and 304,011 normal-weight adults. Among the participants with class III obesity, mortality rates (deaths per 100,000 persons per year) during the 30-year study period were 856.0 and 663.0 in men and women, respectively, whereas the mortality rates among normal-weight men and women were 346.7 and 280.5, respectively. Heart disease was the major contributor to the excess death rate among individuals with class III obesity, followed by cancer and diabetes. Statistical analyses of the pooled data indicate that the risk of all-cause death and death due to heart disease, cancer, diabetes, and several other diseases increased with increasing BMI. Finally, compared with having a normal weight, having a BMI between 40 and 59 kg/m2 resulted in an estimated loss of 6.5 to 13.7 years of life.
What Do These Findings Mean?
These findings indicate that class III obesity is associated with a substantially increased rate of death. Notably, this death rate increase is similar to the increase associated with smoking among normal-weight people. The findings also suggest that heart disease, cancer, and diabetes are responsible for most of the excess deaths among people with class III obesity and that having class III obesity results in major reductions in life expectancy. Importantly, the number of years of life lost continues to increase for BMI values above 50 kg/m2, and beyond this point, the loss of life expectancy exceeds that associated with smoking among normal-weight people. The accuracy of these findings is limited by the use of self-reported height and weight measurements to calculate BMI and by the use of BMI as the sole measure of obesity. Moreover, these findings may not be generalizable to all populations. Nevertheless, these findings highlight the need to develop more effective interventions to combat the growing public health problem of class III obesity.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001673.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish)
The World Health Organization provides information on obesity (in several languages); Malri's story describes the health risks faced by an obese child
The UK National Health Service Choices website provides information about obesity, including a personal story about losing weight
The Global Burden of Disease Study website provides the latest details about global obesity trends
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-Control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
MedlinePlus provides links to other sources of information on obesity (in English and Spanish)
doi:10.1371/journal.pmed.1001673
PMCID: PMC4087039  PMID: 25003901

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