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.

Analysing seasonal data

Many common diseases, such as the flu and cardiovascular disease, increase markedly in winter and dip in summer. These seasonal patterns have been part of life for millennia and were first noted in ancient Greece by both Hippocrates and Herodotus. Recent interest has focused on climate change, and the concern that seasons will become more extreme with harsher winter and summer weather. We describe a set of R functions designed to model seasonal patterns in disease. We illustrate some simple descriptive and graphical methods, a more complex method that is able to model non-stationary patterns, and the case–crossover for controlling for seasonal confounding.

Institutional and individual labor market discrimination based on hukou status : an artefactual field experiment

We study discrimination based on the hukou system that segregates citizens in groups of migrants and locals in urban China. We use an artefactual field experiment with a labor market framing. We recruit workers on their real labor market as experimental participants and investigate if official discrimination motivates individual discrimination based on hukou status. In our experimental results we observe discrimination based on the hukou characteristic: however, statistical discrimination does not seem to be the source of this, as status is exogeneous for our participants and migrants and locals behave similarly. Furthermore, discrimination increases between two experimental frameworks when motives for statistical discrimination are removed.

The use of hypnosis in labor and delivery : a preliminary study

Self-hypnosis was taught to 87 obstetric patients (HYP) and was not taught to 56 other patients (CNTRL), all delivered by the same family physician, in order to determine whether the use of self-hypnosis by low-risk obstetric patients leads to fewer technologic interventions during their deliveries or greater satisfaction of parturients with their delivery experience or both. The outcomes of the deliveries of these two groups were compared, and the HYP group was compared to 352 low-risk patients delivered by other family physicians at the same hospital (WCH). Questionnaires were mailed postpartum to 156 patients, all delivered by the same family physician, to determine satisfaction with delivery using the Labor and Delivery Satisfaction Index (LADSI). The hypnosis group showed a significant reduction in the number of epidurals (11.4% less than CNTRL and 17.9% less than WCH, p < 0.05) and the use of intravenous lines (18.5% less for both, p < 0.05). The number of episiotomies was significantly less in the HYP group compared to WCH (15.9%, p < 0.05) and 11.5% less when compared to CNTRL. The tear rate was not statistically different. Combined use of the intervention triad (epidural–forceps–episiotomy) was less for HYP than for CNTRL (15.8% less) and WCH (10.2% less, p < 0.05). More deliveries were done in the labor room with HYP than CNTRL (21%, p < 0.05). The second stage was shortened by 10 min (HYP vs CNTRL). Overall satisfaction of HYP and CNTRL patients was similar and generally favorable.

Labor market reform and the changing structure of wage determination in China's state sector during the 1980s

China's market-oriented labor market reform has been in place for about one and a half decades. This study uses individual data for 1981 and 1987 to examine the success of the first half of the reform program. Success is evaluated by examining changes in the wage setting structure in the state-owned sector over the reform period. Have the market reforms stimulated worker incentives by increasing the returns to human capital acquisition? Has the wage structure altered to more closely mimic that of a market economy? In 1987, there is evidence of a structural change in the system of wage determination, with slightly increased rates of return to human capital. However, changes in industrial wage differentials appear to play the dominant role. It is argued that this may be due to labor market reforms, in particular the introduction of the profit related bonus scheme.J. Comp. Econom.,December 1997,25(3), pp. 403–421. Australian National University, Canberra, ACT0200, Australia and University of Tasmania, Hobart, Tasmania, Australia, and University of Aberdeen, Old Aberdeen, Scotland AB24 3QY.

Role of land use and seasonal factors in water quality degradation

Surface water and groundwater are the most important water sources in the natural environment. Land use and seasonal factors play an important role in influencing the quality of these water sources. An in-depth understanding of the role of these two influential factors can help to implement an effective catchment management strategy for the protection of these water sources. This paper discusses the outcomes of an extensive research study which investigated the role of land use and seasonal factors on surface water and groundwater pollution in a mixed land use coastal catchment. The study confirmed that the influence exerted on the water environment by seasonal factors is secondary to that of land use. Furthermore, the influence of land use and seasonal factors on surface water and groundwater quality varies with the pollutant species. This highlights the need to specifically take into consideration the targeted pollutants and the key influential factors for the effective protection of vulnerable receiving water environments.

No more Labor heartland?

Growing up, my family worshipped at the altar of unionism. My parents embraced ‘working class’ as an active social position not as a step on the aspirational treadmill. In those days and in the areas where I lived, it was nothing special. It was a given that everyone was in a union and voted Labor, manning factories and building sites and marching or striking when the need arose...

Semiparametric estimates of the supply and demand effects of disability on labor force participation

This paper modifies and uses the semiparametric methods of Ichimura and Lee (1991) on standard cross-section data to decompose the effect of disability on labor force participation into a demand and a supply effect. It shows that straightforward use of Ichimura and Lee leads to meaningless results while imposing monotonicity on the unknown function leads to substantial results. The paper finds that supply effects dominate the demand effects of disability.

Seasonal amplitude of hemorrhagic fever with renal syndrome in China : a call for attention to neglected regions

Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne viral disease characterized by fever, hemorrhagic, kidney damage and hypotension, is caused by different species of hantaviruses [1]. Every year, HFRS affects thousands of people in Asia, and more than 90% of these cases are reported in China [2, 3]. Due to its high fatality, HFRS has attracted considerable research attention, and prior studies have predominantly focused on quantifying HFRS morbidity [4], identifying high risk areas [5] and populations [6], or exploring peak time of HFRS occurrence [3]. To date, no study has assessed the seasonal amplitude of HFRS in China, even though it reveals the seasonal fluctuation and thus may provide pivotal information on the possibility of HFRS outbreaks.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

Seasonal factors influencing the failure of buried water reticulation pipes

While the use of environmental factors in the analysis and prediction of failures of buried reticulation pipes in cold environments has been the focus of extensive work, the same cannot be said for failures occurring on pipes in other (non-freezing) environments. A novel analysis of pipe failures in such an environment is the subject of this paper. An exploratory statistical analysis was undertaken, identifying a peak in failure rates during mid to late summer. This peak was found to correspond to a peak in the rate of circumferential failures, whilst the rate of longitudinal failures remained constant. Investigation into the effect of climate on failure rates revealed that the peak in failure rates occurs due to differential soil movement as the result of shrinkage in expansive soils.

Impact of child labor on academic performance : evidence from the program "Edúcame Primero Colombia"

In this study, the effects of different variables of child labor on academic performance are investigated. To this end, 3302 children participating in the child labor eradication program “Edúcame Primero Colombia” were interviewed. The interview format used for the children's enrollment into the program was a template from which socioeconomic conditions, academic performance, and child labor variables were evaluated. The academic performance factor was determined using the Analytic Hierarchy Process (AHP). The data were analyzed through a logistic regression model that took into account children who engaged in a type of labor (n = 921). The results showed that labor conditions, the number of weekly hours dedicated to work, and the presence of work scheduled in the morning negatively affected the academic performance of child laborers. These results show that the relationship between child labor and academic performance is based on the conflict between these two activities. These results do not indicate a linear and simple relationship associated with the recognition of the presence or absence of child labor. This study has implications for the formulation of policies, programs, and interventions for preventing, eradicating, and attenuating the negative effects of child labor on the social and educational development of children.