Blood Cell In Vitro Cytokine Production in Response to Lipopolysaccharide Stimulation in a Healthy Population: Effects of Age, Sex, and Smoking

Immune system functionality has been commonly assessed by a whole-blood or isolated-cell stimulation assay. The aim of this study was to determine whether cytokine production in whole-blood-stimulated samples is influenced by age, sex, and smoking. A descriptive cross-sectional study in 253 healthy participants aged 18–55 years was conducted. Whole blood samples were stimulated for 24 h with LPS and concentrations of IL-6, IL-10, and TNF-α were determined in the culture media. Among parameters considered, statistical regression analysis indicated that smoking (change in R2 = 0.064, p < 0.001) and sex (change in R2 = 0.070, p < 0.001) were the main predictors for IL-10 production, with higher values for women and non-smokers. Age was also found to be a significant predictor (change in R2 = 0.021, p < 0.001), with higher values for younger ages. Age (change in R2 = 0.089, p = 0.013) and smoking (change in R2 = 0.037, p = 0.002) were found to be negative predictors for IL-6 production. Regarding TNF-α-stimulated production, age (change in R2 = 0.029, p = 0.009) and smoking (change in R2 = 0.022, p = 0.022) were found to be negative predictors. Furthermore, sex (change in R2 = 0.016, p = 0.045) was found to be a significant predictor, with lower values for women. In conclusion, sex, age, and smoking were found to be independent determinants of stimulated cytokine production. While female sex is associated with higher IL-10 and lower TNF-α production, aging and smoking are associated with lower IL-6, IL-10, and TNF-α production.

AGE CHANGE OF FACTORS IN THE HEALTH TRAJECTORY BY SELF-ASSESSMENT OF FEMALE CHILDREN AND ADOLESCENTS

The study was conducted by questioning the dynamics of changes in the assessment of health and influencing environmental factors in 4 age groups of women from 8 to 18 years. As we get older, we observe a decrease in the ability to fully recover during sleep, a good mood, an increase in the frequency of headaches, the need for sweets. Seventy-five percent of participants in the 12-14 age group considered themselves healthy, 56% in the 16-18 age group and 12% considered themselves unhealthy.

AGE CHANGE IN PRODUCTIVITY OF COWS OF DIFFERENT LINES

The age dynamics of milk productivity of cows has been studied. It has an unequal character depending on the lineage and individual characteristics of the breeding bulls. This must be taken into account when predicting the effect of selection for these traits.

Age change in healthcare settings: a reply to Lippert-Rasmussen and Petersen

Lippert-Rasmussen and Petersen discuss my ‘Moral case for legal age change’ in their article ‘Age change, official age and fairness in health’. They argue that in important healthcare settings (such as distributing vital organs for dying patients), the state should treat people on the basis of their chronological age because chronological age is a better proxy for what matters from the point of view of justice than adjusted official age. While adjusted legal age should not be used in deciding who gets scarce vital organs, I remind the readers that using chronological age as a proxy is problematic as well. Using age as a proxy could give wrong results and it is better, if possible, for states to use the vital information directly than use age as a proxy.

Age change, official age and fairness in health

In a recent JME article, Joona Räsänen makes the case for allowing legal age change. We identify three problems with his argument and, on that basis, propose an improved version thereof. Unfortunately, even the improved argument is vulnerable to the objection that chronological age is a better proxy for justice in health than both legal and what we shall call official age.

On legal age change

Joona Räsänen argues some people have a right to change their legal age to prevent age discrimination. He proposes two prerequisites—the person feels his age differs from his legal age, and that person’s biological age differs from his chronological age. I argue we can achieve the same protections from ageism through restricting access to one’s birth date. I review several moral reasons in favour of changing one’s legal age, concluding the enterprise is folly.

Further defence of legal age change: a reply to the critics

In ‘Moral case for legal age change’, I argue that sometimes people should be allowed to change their age. I refute six immediate objections against the view that age change is permissible. I argue that the objections cannot show that legal age change should always be prohibited. In this paper, I consider some further objections against legal age change raised by Iain Brassington, Toni Saad and William Simkulet. I argue that the objections fail to show that age change should never be allowed.

What a drag it is getting old: a response to Räsänen

In this brief response to Joona Räsänen’s argument for the coherence and desirability of being able legally to change one’s age, I outline a couple of reasons for thinking that the case he makes is deeply flawed. As such, I contend that we have no reason to think that age should be the kind of thing that one should be able to change legally. Moreover, we have at least one good reason for thinking that legal age change would be positively undesirable.

Parent BMI Increase 2 to 5 Years Post-study Related to Change in Age but Independent of Other Sociodemographics, Health Behavior, and Study Engagement (P16-001-19)

Objectives Characterize parent (P) weight change 2–5 y post participation in Fuel for Fun (FFF) a controlled trial of a school and family intervention focused on culinary and physical activity experiences for 4th grade youth. Methods P who had participated with their 4th grader in FFF were recruited via email to enroll in a follow-up (FFF-FU) assessment. FFF-FU survey set included measures from the original study and new items pertinent to P of adolescents. Physical activity was measured with the IPAQ; low income was denoted as using an income-based program or worry about money for food. Height, weight, age in FFF and FFF-FU were self-reported. Perimenopausal age included 47 y within BL and FFF-FU. Youth in FFF cohorts 1 and 4 were controls and cohorts 2 and 3 included the multi-component intervention. P were enrolled in 1 of 4 treatments varying in type and intensity. FFF and FFF-FU data were collected online using the Qualtrics platform. FFF P completed surveys at baseline (BL), post-intervention, and 4 months post-study. FFF-FU data were collected spring 2018, about 2 to 5 years years post-BL. Data were analyzed with repeated measures controlling for BL or FFF-FU sociodemographics, engagement, health behaviors. Results Of the 418 FFF P, 127 completed FFF-FU surveys (mean age 42.5 6.0 y) with 115 providing weight and height. FFF-FU sample was female (88%), white (84%), active (44% high activity), educated (69% college degree or higher), but had lower BMI and fewer with low income than FFF P. Of FFF-FU providing heights/weights at the 4 assessments, mean (SE) BMIs were 24.2 (0.5), 24.4 (0.5), 24.6 (0.6) and 25.7 (0.6) respectively. Change in BMI was significant after controlling for age, stress, ethnicity, sex, physical activity level, P treatment and engagement, but not when BL to FFU-FU change in age or perimenopausal age were controlled. The significantly greater increase in BMI for P of intervention youth than controls persisted when controlling for sociodemographic and health behavior findings, but not when BL to FFF-FU age change, perimenopausal age or activity level were controlled. Conclusions Significant weight gain by P of youth in a nutrition intervention 2 to 5 years post-study was unrelated to stress, ethnicity, activity level, income, but was related to the FFF-FU age change from BL and perimenopausal age. Funding Sources NIFA.