The politics of temporary work deregulation in Europe: solving the French puzzle

Temporary work has expanded in the last three decades with adverse implications for inequalities. Because temporary workers are a constituency that is unlikely to impose political costs, governments often choose to reduce temporary work regulations. While most European countries have indeed implemented such reforms, France went in the opposite direction, despite having both rigid labour markets and high unemployment. My argument to solve this puzzle is that where replaceability is high, workers in permanent and temporary contracts have overlapping interests, and governments choose to regulate temporary work to protect permanent workers. In turn, replaceability is higher where permanent workers’ skills are general and wage coordination is low. Logistic regression analysis of the determinants of replaceability — and how this affects governments’ reforms of temporary work regulations — supports my argument. Process tracing of French reforms also confirm that the left has tightened temporary work regulations to compensate for the high replaceability.

Association of the PPARGC1A gene polymorphism with diabetic nephropathy in an Asian Indian population (CURES-41)

BACKGROUND: The aim of this study was to evaluate the association of polymorphisms of the peroxisome proliferator-activated receptor gamma (PPARG) gene and peroxisome proliferators-activated receptor gamma co-activator 1 alpha (PPARGC1A) gene with diabetic nephropathy (DN) in Asian Indians. METHODS: Six common polymorphisms, 3 of the PPARG gene [-1279G/A, Pro12Ala, and His478His (C/T)] and 3 of the PPARGC1A gene (Thr394Thr, Gly482Ser, and +A2962G) were studied in 571 normal glucose-tolerant (NGT) subjects, 255 type 2 diabetic (T2D) subjects without nephropathy, and 141 DN subjects. Genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and direct sequencing. Logistic regression analysis was performed to assess the covariables associated with DN. RESULTS: Among the 6 polymorphisms examined, only the Gly482Ser of the PPARGC1A gene was significantly associated with DN. The genotype frequency of Ser/Ser genotype of the PPARGC1A gene was 8.8% (50/571) in NGT subjects, 7.8% (20/255) in T2D subjects, and 29.8% (42/141) in DN subjects. The odds ratios (ORs) for DN for the susceptible Gly/Ser and Ser/Ser genotype after adjusting for age, sex, body mass index, and duration of diabetes were 2.14 [95% confidence interval (CI), 1.23-3.72; P = 0.007] and 8.01 (95% CI, 3.89-16.47; P < 0.001), respectively. The unadjusted OR for DN for the XA genotype of the Thr394Thr polymorphism was 1.87 (95% CI, 1.20-2.92; P = 0.006) compared to T2D subjects. However, the significance was lost (P = 0.061) when adjusted for age, sex, BMI, and duration of diabetes. The +A2962G of PPARGC1A and the 3 polymorphisms of PPARG were not associated with DN. CONCLUSION: The Gly482Ser polymorphism of the PPARGC1A gene is associated with DN in Asian Indians.

A novel association of a polymorphism in the first intron of adiponectin gene with type 2 diabetes, obesity and hypoadiponectinemia in Asian Indians

Adiponectin is an adipose tissue specific protein that is decreased in subjects with obesity and type 2 diabetes. The objective of the present study was to examine whether variants in the regulatory regions of the adiponectin gene contribute to type 2 diabetes in Asian Indians. The study comprised of 2,000 normal glucose tolerant (NGT) and 2,000 type 2 diabetic, unrelated subjects randomly selected from the Chennai Urban Rural Epidemiology Study (CURES), in southern India. Fasting serum adiponectin levels were measured by radioimmunoassay. We identified two proximal promoter SNPs (-11377C-->G and -11282T-->C), one intronic SNP (+10211T-->G) and one exonic SNP (+45T-->G) by SSCP and direct sequencing in a pilot study (n = 500). The +10211T-->G SNP alone was genotyped using PCR-RFLP in 4,000 study subjects. Logistic regression analysis revealed that subjects with TG genotype of +10211T-->G had significantly higher risk for diabetes compared to TT genotype [Odds ratio 1.28; 95% Confidence Interval (CI) 1.07-1.54; P = 0.008]. However, no association with diabetes was observed with GG genotype (P = 0.22). Stratification of the study subjects based on BMI showed that the odds ratio for obesity for the TG genotype was 1.53 (95%CI 1.3-1.8; P < 10(-7)) and that for GG genotype, 2.10 (95% CI 1.3-3.3; P = 0.002). Among NGT subjects, the mean serum adiponectin levels were significantly lower among the GG (P = 0.007) and TG (P = 0.001) genotypes compared to TT genotype. Among Asian Indians there is an association of +10211T-->G polymorphism in the first intron of the adiponectin gene with type 2 diabetes, obesity and hypoadiponectinemia.

Absence of Association of Metabolic Syndrome with PPARGC1A, PPARG and UCP1 Gene Polymorphisms in Asian Indians

The objective of this study was to evaluate the association of PPARG coactivator1 alpha (PPARGC1A), peroxisome proliferator activated receptor gamma (PPARG), and uncoupling protein1 (UCP1) gene polymorphisms with the metabolic syndrome (MS) in an Asian Indian population. Nine common polymorphisms were genotyped via polymerase chain reaction restriction fragment length polymorphism and direct sequencing in 950 normal glucose-tolerant subjects and 550 type 2 diabetic subjects, chosen randomly from the Chennai Urban Rural Epidemiological Study, an ongoing population based study in Southern India. Among the 9 polymorphisms examined, only the Thr394Thr variant of the PPARGC1A gene was significantly associated with diabetes and obesity. The genotype frequency of GA of Thr394Thr variant was 16% (138/887) in the nonMS group and 22% (136/613) in the MS group, and this genotype frequency was significantly higher with MS both in males (p = 0.01) and females (p = 0.05), compared to the without-MS group. Logistic regression analysis revealed that the odds ratio for MS for the susceptible genotype GA of Thr394Thr was 1.411 [95% CI: 1.03-1.84, p = 0.012]. In the multiple logistic regression analysis, however, there was no association of this polymorphism as an independent factor with MS. Hence, the study shows that the polymorphisms in the PPARGC1A, PPARG and UCP1 genes are not associated with MS in Asian Indians.

Association of low adiponectin levels with the metabolic syndrome--the Chennai Urban Rural Epidemiology Study (CURES-4)

The aim of the study was to assess the relation of adiponectin levels with the metabolic syndrome in Asian Indians, a high-risk group for diabetes and premature coronary artery disease. The study was conducted on 100 (50 men and 50 women) type 2 diabetic subjects and 100 age and sex matched subjects with normal glucose tolerance selected from the Chennai Urban Rural Epidemiology Study, an ongoing population study in Chennai in southern India. Metabolic syndrome was defined using modified Adult Treatment Panel III (ATPIII) guidelines. Adiponectin values were significantly lower in diabetic subjects (men: 5.2 vs 8.3 microg/mL, P=.00l; women: 7.6 vs 11.1 microg/mL, P<.00l) and those with the metabolic syndrome (men: 5.0 vs 6.8 microg/mL, P=.01; women: 6.5 vs 9.9 microg/mL, P=.001) compared with those without. Linear regression analysis revealed adiponectin to be associated with body mass index (P<.05), waist circumference (P<.01), fasting plasma glucose (P=.001), glycated hemoglobin (P<.001), triglycerides (P<.00l), high-density lipoprotein (HDL) cholesterol (P<.001), cholesterol/HDL ratio (P<.00l), and insulin resistance measured by homeostasis assessment model (P<.00l). Factor analysis identified 2 factors: factor 1, negatively loaded with adiponectin and HDL cholesterol and positively loaded with triglycerides, waist circumference, and insulin resistance measured by homeostasis assessment model; and factor 2, with a positive loading of waist circumference and systolic and diastolic blood pressure. Logistic regression analysis revealed adiponectin to be negatively associated with metabolic syndrome (odds ratio [OR], 0.365; P<.001) even after adjusting for age (OR, 0.344; P<.00l), sex (OR, 0.293; P<.001), and body mass index (OR, 0.292; P<.00l). Lower adiponectin levels are associated with the metabolic syndrome per se and several of its components, particularly, diabetes, insulin resistance, and dyslipidemia in this urban south Indian population.

Visceral and central abdominal fat and anthropometry in relation to diabetes in Asian Indians

OBJECTIVE: The objective of the study was to examine body fat distribution using computed tomography (CT), dual-energy X-ray absorptiometry (DEXA), and anthropometry in relation to type 2 diabetes in urban Asian Indians. RESEARCH DESIGN AND METHODS: This is a case-control study of 82 type 2 diabetic and 82 age- and sex-matched nondiabetic subjects from the Chennai Urban Rural Epidemiology Study, an ongoing epidemiological study in southern India. Visceral, subcutaneous, and total abdominal fat were measured using CT, while DEXA was used to measure central abdominal and total body fat. Anthropometric measures included BMI, waist circumference, sagittal abdominal diameter (SAD), and waist-to-hip ratio. RESULTS: Visceral and central abdominal fat showed a strong correlation with each other (P <0.0001), and kappa analysis revealed a fairly good agreement between tertiles of visceral and central abdominal fat (kappa=0.44, P <0.0001). Diabetic subjects had significantly higher visceral (P=0.005) and central abdominal (P=0.011) fat compared with nondiabetic subjects. Waist circumference and SAD showed a strong correlation with visceral (P <0.01) and central abdominal (P <0.0001) fat in both diabetic and nondiabetic subjects. Logistic regression analysis revealed visceral (odds ratio [OR] 1.011, P=0.004) and central abdominal (OR 1.001, P=0.013) fat to be associated with diabetes, even after adjusting for age and sex. CONCLUSIONS: Visceral and central abdominal fat showed a strong association with type 2 diabetes. Both measures correlated well with each other and with waist circumference and SAD in diabetic and nondiabetic urban Asian Indians.

Self-congruence, functional congruence, and destination choice

This study's purpose is to investigate the effects of self-congruence and functional congruence on tourists' destination choice. The present research contributes to the gap in the consumer behavior literature by examining the relationships among self-congruence, functional congruence, and destination choice. Based on a sample of 367 British residents, the three research hypotheses are tested using multinomial logistic regression analysis. The study results suggest that a tourist's destination choice is influenced strongly by functional congruence, but not by self-congruence. The article closes with theoretical and managerial implications as well as future research directions.

Do personality traits predict ‘complaining’ consumers?

Although the effects of personality traits on complaining behaviour emerged in the early 1980s, there is limited research in the service industry. The purpose of this study is to examine whether consumer personality traits influence intentions to complain and whether product price and product types moderate the relationship between personality traits and intentions to complain in the retail industry. The research model is tested by logistic regression analysis on two groups of consumers who report passive and active complaining intentions. The study reveals that conscientious consumers who are open to new experiences tend to have higher intentions to complain. Being extroverted does not have any influence on complaining behaviour. Whilst price levels (low/high) and product types (grocery, clothing and electronics) improve the predictive ability of the complaining behaviour, the interaction effects relating to the three personality traits are statistically insignificant. Theoretical and managerial implications of the study findings are discussed.

Does stakeholder pressure influence corporate GHG emissions reporting? Empirical evidence from Europe

Purpose – The purpose of this paper is to seek to shed light on the practice of incomplete corporate disclosure of quantitative Greenhouse gas (GHG) emissions and investigates whether external stakeholder pressure influences the existence, and separately, the completeness of voluntary GHG emissions disclosures by 431 European companies. Design/methodology/approach – A classification of reporting completeness is developed with respect to the scope, type and reporting boundary of GHG emissions based on the guidelines of the GHG Protocol, Global Reporting Initiative and the Carbon Disclosure Project. Logistic regression analysis is applied to examine whether proxies for exposure to climate change concerns from different stakeholder groups influence the existence and/or completeness of quantitative GHG emissions disclosure. Findings – From 2005 to 2009, on average only 15 percent of companies that disclose GHG emissions report them in a manner that the authors consider complete. Results of regression analyses suggest that external stakeholder pressure is a determinant of the existence but not the completeness of emissions disclosure. Findings are consistent with stakeholder theory arguments that companies respond to external stakeholder pressure to report GHG emissions, but also with legitimacy theory claims that firms can use carbon disclosure, in this case the incomplete reporting of emissions, as a symbolic act to address legitimacy exposures. Practical implications – Bringing corporate GHG emissions disclosure in line with recommended guidelines will require either more direct stakeholder pressure or, perhaps, a mandated disclosure regime. In the meantime, users of the data will need to carefully consider the relevance of the reported data and develop the necessary competencies to detect and control for its incompleteness. A more troubling concern is that stakeholders may instead grow to accept less than complete disclosure. Originality/value – The paper represents the first large-scale empirical study into the completeness of companies’ disclosure of quantitative GHG emissions and is the first to analyze these disclosures in the context of stakeholder pressure and its relation to legitimation.

The impact of the elderly on inflation rates in developed countries

What explains the cross-national variation in inflation rates in developed countries? Previous literature has emphasised the role of ideas and institutions, and to a lesser extent interest groups, while leaving the role of electoral politics comparatively unexplored. This paper seeks to redress this neglect by focusing on one case where electoral politics matters for inflation: the share of the population above 65 years old in a country. I argue that countries with a larger share of elderly have lower inflation because older people are both more inflation averse and politically powerful, forcing governments to pursue lower inflation. I test my argument in three steps. First, logistic regression analysis of survey data confirms older people are more inflation averse. Second, panel data regression analysis of party manifesto data reveals that European countries with more old people have more economically orthodox political parties. Third, time series cross-section regression analyses demonstrate that the share of the elderly is negatively correlated with inflation in both a sample of 21 advanced OECD economies and a larger sample of 175 countries. Ageing may therefore push governments to adopt a low inflation regime.

A practical approach to a multi-level analysis with a sparse binary outcome within a large surgical trial

Objectives: To assess the potential source of variation that surgeon may add to patient outcome in a clinical trial of surgical procedures. Methods: Two large (n = 1380) parallel multicentre randomized surgical trials were undertaken to compare laparoscopically assisted hysterectomy with conventional methods of abdominal and vaginal hysterectomy; involving 43 surgeons. The primary end point of the trial was the occurrence of at least one major complication. Patients were nested within surgeons giving the data set a hierarchical structure. A total of 10% of patients had at least one major complication, that is, a sparse binary outcome variable. A linear mixed logistic regression model (with logit link function) was used to model the probability of a major complication, with surgeon fitted as a random effect. Models were fitted using the method of maximum likelihood in SAS((R)). Results: There were many convergence problems. These were resolved using a variety of approaches including; treating all effects as fixed for the initial model building; modelling the variance of a parameter on a logarithmic scale and centring of continuous covariates. The initial model building process indicated no significant 'type of operation' across surgeon interaction effect in either trial, the 'type of operation' term was highly significant in the abdominal trial, and the 'surgeon' term was not significant in either trial. Conclusions: The analysis did not find a surgeon effect but it is difficult to conclude that there was not a difference between surgeons. The statistical test may have lacked sufficient power, the variance estimates were small with large standard errors, indicating that the precision of the variance estimates may be questionable.