Seasonal variation in cardiovascular disease risk factors in a subarctic population : the Tromso Study 1979-2008

Background Seasonal changes in cardiovascular disease (CVD) risk factors may be due to exposure to seasonal environmental variables like temperature and acute infections or seasonal behavioural patterns in physical activity and diet. Investigating the seasonal pattern of risk factors should help determine the causes of the seasonal pattern in CVD. Few studies have investigated the seasonal variation in risk factors using repeated measurements from the same individual, which is important as individual and population seasonal patterns may differ. Methods The authors investigated the seasonal pattern in systolic and diastolic blood pressure, heart rate, body weight, total cholesterol, triglycerides, high-density lipoprotein cholesterol, C reactive protein and fibrinogen. Measurements came from 38 037 participants in the population-based cohort, the Tromsø Study, examined up to eight times from 1979 to 2008. Individual and population seasonal patterns were estimated using a cosinor in a mixed model. Results All risk factors had a highly statistically significant seasonal pattern with a peak time in winter, except for triglycerides (peak in autumn), C reactive protein and fibrinogen (peak in spring). The sizes of the seasonal variations were clinically modest. Conclusions Although the authors found highly statistically significant individual seasonal patterns for all risk factors, the sizes of the changes were modest, probably because this subarctic population is well adapted to a harsh climate. Better protection against seasonal risk factors like cold weather could help reduce the winter excess in CVD observed in milder climates.

Particulate air pollution and cardiorespiratory hospital admissions in a temperate Australian city: A case-crossover analysis

Although ambient air pollution exposure has been linked with poor health in many parts of the world, no previous study has investigated the effect on morbidity in the city of Adelaide, South Australia. To explore the association between particulate matter (PM) and hospitalisations, including respiratory and cardiovascular admissions in Adelaide, South Australia. Methods: For the study period September 2001 to October 2007, daily counts of all-cause, cardiovascular and respiratory hospital admissions were collected, as well as daily air quality data including concentrations of particulates, ozone and nitrogen dioxide. Visibility codes for presentweather conditions identified dayswhen airborne dust or smoke was observed. The associations between PM and hospitalisations were estimated using timestratified case-crossover analyses controlling for covariates including temperature, relative humidity, other pollutants, day of the week and public holidays. Mean PM10 concentrations were higher in the warm season, whereas PM2.5 concentrations were higher in the cool season. Hospital admissions were associated with PM10 in the cool season and with PM2.5 in both seasons. No significant effect of PM on all-age respiratory admissions was detected, however cardiovascular admissions were associated with both PM2.5 and PM10 in the cool season with the highest effects for PM2.5 (4.48%, 95% CI: 0.74%, 8.36% increase per 10 μg/m3 increase in PM2.5). These findings suggest that despite the city's relatively low levels of air pollution, PMconcentrations are associated with increases in morbidity in Adelaide. Further studies are needed to investigate the sources of PM which may be contributing to the higher cool season effects.

Cold and heat waves in the United States

Extreme cold and heat waves, characterised by a number of cold or hot days in succession, place a strain on people’s cardiovascular and respiratory systems. The increase in deaths due to these waves may be greater than that predicted by extreme temperatures alone. We examined cold and heat waves in 99 US cities for 14 years (1987–2000) and investigated how the risk of death depended on the temperature threshold used to define a wave, and a wave’s timing, duration and intensity. We defined cold and heat waves using temperatures above and below cold and heat thresholds for two or more days. We tried five cold thresholds using the first to fifth percentiles of temperature, and five heat thresholds using the ninety-fifth to ninety-ninth percentiles. The extra wave effects were estimated using a two-stage model to ensure that their effects were estimated after removing the general effects of temperature. The increases in deaths associated with cold waves were generally small and not statistically significant, and there was even evidence of a decreased risk during the coldest waves. Heat waves generally increased the risk of death, particularly for the hottest heat threshold. Cold waves of a colder intensity or longer duration were not more dangerous. Cold waves earlier in the cool season were more dangerous, as were heat waves earlier in the warm season. In general there was no increased risk of death during cold waves above the known increased risk associated with cold temperatures. Cold or heat waves earlier in the cool or warm season may be more dangerous because of a build up in the susceptible pool or a lack of preparedness for cold or hot temperatures.

Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.

Suicide rates in Shandong, China, 1991–2010 : rapid decrease in rural rates and steady increase in male–female ratio

Background China has one of the highest suicide rates in the world; however, the recent trends in suicide have not been adequately studied. This study aimed to examine the potential changes in the rates and characteristics in a Chinese population. Methods Data on suicide deaths in 1991–2010 were extracted from the Shandong Disease Surveillance Point (DSP) mortality dataset based on ICD-10 codes. The temporal trend in age-adjusted suicide rates for each subpopulation was tested using log-linear Poisson regression analysis. Results From 1991 to 2010, there was a marked decrease in the overall suicide rate in Shandong, with an average reduction of 8% per year. The decrease trend was stronger in rural than in urban areas and more evident in females than in males. Similar decreases were observed for all age groups. Pesticide ingestion and hanging remained the top two methods for suicide. Limitations There are likely quality concerns in the morality data, such as underreporting and misclassification, as well as low accuracy in determining the underlying causes of deaths. The representativeness of the DSP system may also be problematic due to the rapid changes in economy and demography. Conclusions Completed suicides in Shandong have sharply declined over the past 20 years. Higher rates in females versus males and in rural versus urban areas, which were previously considered to be distinguishing features of suicide in China, are becoming less pronounced.

Exercise for health : a randomized, controlled trial evaluating impact of a pragmatic, translational exercise intervention on quality of life, function and treatment-related side effects following breast cancer

Purpose Exercise for Health was a randomized, controlled trial designed to evaluate two modes of delivering (face-to-face [FtF] and over-the-telephone [Tel]) an 8-month translational exercise intervention, commencing 6-weeks post-breast cancer surgery (PS). Methods Outcomes included quality of life (QoL), function (fitness and upper-body) and treatment-related side effects (fatigue, lymphoedema, body mass index, menopausal symptoms, anxiety, depression and pain). Generalised estimating equation modelling determined time (baseline [5-weeks PS], mid-intervention [6-months PS], post-intervention [12-months PS]), group (FtF, Tel, Usual Care [UC]) and time-by-group effects. 194 women representative of the breast cancer population were randomised to the FtF (n=67), Tel (n=67) and UC (n=60) groups. Results: There were significant (p<0.05) interaction effects on QoL, fitness and fatigue, with differences being observed between the treatment groups and the UC group. Trends observed for the treatment groups were similar. The treatment groups reported improved QoL, fitness and fatigue over time and changes observed between baseline and post-intervention were clinically relevant. In contrast, the UC group experienced no change, or worsening QoL, fitness and fatigue, mid-intervention. Although improvements in the UC group occurred by 12-months post-surgery, the change did not meet the clinically relevant threshold. There were no differences in other treatment-related side-effects between groups. Conclusion This translational intervention trial, delivered either face-to-face or over-the-telephone, supports exercise as a form of adjuvant breast cancer therapy that can prevent declines in fitness and function during treatment and optimise recovery post-treatment.

Can slide positivity rates predict malaria transmission?

Background: Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China. Methods: Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. Results: The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (beta = 1.244, p = 0.000) alone and combination (SPR, beta = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates. Conclusion: SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

One-year delayed effect of fog on malaria transmission : a time-series analysis in the rain forest area of Mengla County, south-west China

Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

Spatial and temporal distribution of falciparum malaria in China

Background: Falciparum malaria is the most deadly among the four main types of human malaria. Although great success has been achieved since the launch of the National Malaria Control Programme in 1955, malaria remains a serious public health problem in China. This paper aimed to analyse the geographic distribution, demographic patterns and time trends of falciparum malaria in China. Methods: The annual numbers of falciparum malaria cases during 1992–2003 and the individual case reports of each clinical falciparum malaria during 2004–2005 were extracted from communicable disease information systems in China Center for Diseases Control and Prevention. The annual number of cases and the annual incidence were mapped by matching them to corresponding province- and county-level administrative units in a geographic information system. The distribution of falciparum malaria by age, gender and origin of infection was analysed. Time-series analysis was conducted to investigate the relationship between the falciparum malaria in the endemic provinces and the imported falciparum malaria in non-endemic provinces. Results: Falciparum malaria was endemic in two provinces of China during 2004–05. Imported malaria was reported in 26 non-endemic provinces. Annual incidence of falciparum malaria was mapped at county level in the two endemic provinces of China: Yunnan and Hainan. The sex ratio (male vs. female) for the number of cases in Yunnan was 1.6 in the children of 0–15 years and it reached 5.7 in the adults over 15 years of age. The number of malaria cases in Yunnan was positively correlated with the imported malaria of concurrent months in the non-endemic provinces. Conclusion: The endemic area of falciparum malaria in China has remained restricted to two provinces, Yunnan and Hainan. Stable transmission occurs in the bordering region of Yunnan and the hilly-forested south of Hainan. The age and gender distribution in the endemic area is characterized by the predominance of adult men cases. Imported falciparum malaria in the non-endemic area of China, affected mainly by the malaria transmission in Yunnan, has increased both spatially and temporally. Specific intervention measures targeted at the mobile population groups are warranted.

Food insecurity among adults residing in disadvantaged urban areas : potential health and dietary consequences

Objective: Food insecurity is the limited or uncertain availability or access to nutritionally-adequate, culturally-appropriate and safe foods. Food insecurity may result in inadequate dietary intakes, overweight or obesity and the development of chronic disease. Internationally, few studies have focused on the range of potential health outcomes related to food insecurity among adults residing in disadvantaged locations and no such Australian studies exist. The objective of this study was to investigate associations between food insecurity, socio-demographic and health factors and dietary intakes among adults residing in disadvantaged urban areas. Design: Data were collected by mail survey (n= 505, 53% response rate), which ascertained information about food security status, demographic characteristics (such as age, gender, household income, education) fruit and vegetable intakes, take-away and meat consumption, general health, depression and chronic disease. Setting: Disadvantaged suburbs of Brisbane city, Australia, 2009. Subjects: Individuals aged ≥ 20 years. Results: Approximately one-in-four households (25%) were food insecure. Food insecurity was associated with lower household income, poorer general health, increased healthcare utilisation and depression. These associations remained after adjustment for age, gender and household income. Conclusion: Food insecurity is prevalent in urbanised disadvantaged areas in developed countries such as Australia. Low-income households are at high risk of experiencing food insecurity. Food insecurity may result in significant health burdens among the population, and this may be concentrated in socioeconomically-disadvantaged suburbs.

When the right to be counted doesn’t count : the politics and challenges of researching the health of asylum seekers

A fundamental prerequisite of population health research is the ability to establish an accurate denominator. This in turn requires that every individual in the study population is counted. However, this seemingly simple principle has become a point of conflict between researchers whose aim is to produce evidence of disparities in population health outcomes and governments whose policies promote(intentionally or not) inequalities that are the underlying causes of health disparities. Research into the health of asylum seekers is a case in point. There is a growing body of evidence documenting the adverse affects of recent changes in asylum-seeking legislation, including mandatory detention. However, much of this evidence has been dismissed by some governments as being unsound, biased and unscientific because, it is argued, evidence is derived from small samples or from case studies. Yet, it is the policies of governments that are the key barrier to the conduct of rigorous population health research on asylum seekers. In this paper, the authors discuss the challenges of counting asylum seekers and the limitations of data reported in some industrialized countries. They argue that the lack of accurate statistical data on asylum seekers has been an effective neo-conservative strategy for erasing the health inequalities in this vulnerable population, indeed a strategy that renders invisible this population. They describe some alternative strategies that may be used by researchers to obtain denominator data on hard-to-reach populations such as asylum seekers.