Normative Values of the Nasal Obstruction Symptom Evaluation Scale

Background: The Nasal Obstruction Symptom Evaluation (NOSE) scale is widely used by clinicians in evaluation of nasal airway obstruction (NAO). Objective: To determine normative values for the NOSE scale among both symptomatic and asymptomatic members of the general U.S. population. Methods: A survey of NAO symptoms in adults of age 18 years and older was performed. The distribution of NOSE scores among the general population was estimated. Influence of features including age, gender, race, location, and symptomatology on NOSE scores was evaluated. Results: Surveys were completed by 2333 participants. Mean NOSE score was 11 (standard deviation [SD] 11) in the asymptomatic, and 28 (SD 22) in the symptomatic population (p < 0.0001). Increasing age was associated with an increase in scores until 45 years, after which it was associated with decreasing scores. No significant differences were found related to other investigated demographics. Conclusions: Normative ranges for the NOSE scale are established, and are largely consistent with values in the existing literature. NOSE scores do not appear to be influenced by gender, race, or geography, although age should be considered in their interpretation.

Models for estimating the biological age of five organs using clinical biomarkers that are commonly measured in clinical practice settings

OBJECTIVES

To date, no worldwide studies have been conducted to estimate the biological age of five organs using clinical biomarkers that are associated with the aging status. Therefore, we conducted this study to develop the models for estimating the biological age of five organs (heart, lung, liver, pancreas, and kidney) using clinical biomarkers which are commonly measured in clinical practice.

DESIGN

A cross sectional study.

METHODS

Subjects were recruited from the routine health check-up centers in Korea from 2004 through 2010. Data obtained from 121,189 subjects (66,168 men and 55,021 women) were used for clinical evaluation and statistical analysis. We examined the relations between clinical biomarkers associated with five organs and the chronological age and proposed a model for estimating the biological age of five organs.

RESULTS

In the models for predicting the biological ages of the heart, lung, liver, pancreas and kidney in men, 12, 2, 8, 3, and 5 parameters were respectively included (R(2)=0.652, 0.427, 0.107, 0.245, and 0.651). In contrast to men, 10, 2, 8, 3, and 5 parameters in women were respectively included (R(2)=0.780, 0.435, 0.140, 0.384, and 0.501).

CONCLUSION

We first proposed the models for predicting the biological age of five organs in the current study. We developed those using clinical parameters that can be easily obtained in clinical practice settings. Our biological age prediction models may be used as supplementary tools to assess the aging status of five organs in clinical practice settings.

Development of models for predicting biological age (BA) with physical, biochemical, and hormonal parameters

Individual differences are the hallmark of aging. Chronological age (CHA) is known that fails to provide an accurate indicator of the aging but biological age (BA) estimates the functional status of an individual in reference to his or her chronological peers on the basis of how well he or she functions in comparison with others of the same CHA. Therefore, we developed models for predicting BA that can be applicable in clinical practice settings. This was a community-based cross-sectional study. Subjects were recruited from the health promotion center in Korea from 2001 to 2005. Among these, data obtained from the 3575 participants (1302 men and 2273 women) was used for clinical evaluation and statistical analysis. For our test battery we selected 25 parameters among the routine tests. For males, the best models were developed using 15, 7, 5, and 4 of the 25 chosen parameters for total, physical, biochemical and hormonal characteristics, respectively (R(2)=0.62, 0.38, 0.33, and 0.36, respectively). Similar to males, for the females, 14, 6, 8, and 3 parameters were developed as the models (R(2)=0.66, 0.40, 0.42, and 0.37, respectively). Our BA prediction models may be used as supplementary tools adding knowledge in the evaluation of aging status.

A review of anthropological approaches to ageing

It is evident that the pattern of ageing among humans has a unique character. Therefore, when undertaking any research on human ageing one has to specify a proper methodology and methods which are available in the anthropological perspective. The paper is aimed at providing a review of anthropological approaches to the study of ageing. On the basis of the meaning and scope of the concept of ageing, its sources and causal factors are discussed. Further, functional, physiological and morphological indicators of ageing are briefly described. Much attention is focused on the concept of biological age which is the key notion for assessment of variation in the rates of human ageing.

Significance of health fitness appraisal in an aging society

There is no doubt that the older population in Japan is rapidly increasing. The over-65 age group is the fastest growing age group in Japanese society. The quality of life for this rapidly growing segment of the population can no longer be ignored without disastrous consequences. The advent of an increased life expectancy has focused attention on the issue of functionality versus disability. We are all faced with the inevitable consequences of aging, yet each of us has the capacity to modify the aging process physiologically through appropriate physical activity and other preventive health measures. Therefore, with the aid of a physically healthy lifestyle, an exercise participant can be physically capable, energetic, and live actively beyond the ages of 50, 60, or even 70 years. Consequently, a key issue for successful or healthy aging would appear to be the improvement in perception of physical ability through education, as well as improvement in health-related physical fitness through a change in lifestyle involving regular exercise. In addition, it is a major responsibility of the physical education profession and related health fields to clarify and publicize the benefits, risks, and specific parameters of physical activity, and to develop an effective prescription for physical activity in programs that are age adjusted. This review discusses from this perspective the significance of health fitness appraisal in the aged society. Much more research is needed to clarify these issues in Japanese society.

Aging of the normal nose in adults

Like other organs, the nose changes as the body ages. A review of the literature reveals a basic understanding of the aging process in the nose but a paucity of documentation and few organized studies. This study was designed to identify systematically the agerelated changes in the normal, nondiseased adult nose. A nasal-sinus laboratory was created, and a computerized patient database was developed. Four separate investigations were conducted. First, 111 subjects ranging in age from 21 to 94 years of age were studied prospectively using 135 variables. The following data were collected: history, symptoms, physical examination, rhinomanometry, ciliary beat frequency, smell testing, and incentive spirometry. Second, photographs of a separate group of 105 subjects 20 to 86 years of age were studied to ascertain the facial cephalometric changes that occur with aging. Third, a histopathologic examination of the nasal septum was performed in 20 additional subjects to evaluate the cellular changes that accompany aging. Finally, an epidemiologic study analyzing the prevalence of various nasal complaints by age was conducted, based on a review of more than 11,000 patient charts from surgeries and office visits. A number of specific age-related changes in the nose were identified, including an increased likelihood of certain nasal complaints, a pattern of increasing airflow resistance, and a decrease in physical abnormalities in the nasopharynx. The appearance of the nose, as measured by the nasolabial angle and the height/length ratio, was also found to change with age.

Measuring human functional age: a review of empirical findings

A review of empirical functional age studies published in English was conducted. Types of biomarkers used in functional age studies included sensorimotor, cognitive, psychosocial, behavioral, anthropometric, biomedical, physiological, and dental variables. Previous criticisms of the validity and utility of functional age research were evaluated with reference to empirical studies. While some of these criticisms remain valid, areas of research currently using established biomarkers to predict functional outcomes were identified, including driving, falls, and cognitive functioning. It was concluded that the success of functional age research is dependent on the relevance of biomarkers to specific functional outcomes.

The relative utility of health-related fitness tests and skilled motor performance tests as measures of biological age in Japanese men

In the present paper we report the results of a study in which we compared 2 different approaches to the computation of biological age (BA) in a sample of 322 Japanese men (age range 20 to 79 years). In the first approach, 4 commonly used measures of health-related fitness (VO2peak, trunk flexion from a standing position, body fat, and grip strength) were reduced to a single BA score (HRF Age) using principal component analysis. In contrast, in the second approach, 3 commonly used measures of skilled motor performance and agility (vertical jump, stepping side-to-side, and balancing on one leg with eyes closed) were reduced to a single BA score (SMP Age) using similar multivariate procedures. The criterion-related validity of both of the BA measures was examined by assessing each measure's ability to discriminate between healthy and active groups of subjects. This was achieved by classifying the original subject pool into regularly active (ACT; n = 108) and healthy (HLTH; n = 169) subgroups on the basis of self-reported activity levels. Analyses revealed that HRF Age was a more powerful discriminator between the two activity groups than SMP Age. While HRF Age of HLTH subjects was very close to their chronological age (CA), in the ACT group, HRF Age was on average 15 years less than their CA (P < 0.05). In a separate analysis, we assessed the HRF Age of patients with ischemic heart disease, hypertension, obesity, or diabetes (PAT; n = 45). The HRF Age of these subjects averaged 10 years above their CA. Our data suggest that commonly used measures of health-related fitness can be usefully employed as indices of BA which differentiate between individuals of similar ages but differing health and physical activity status. In contrast, measures of skilled motor performance were found to be less valuable measures of BA. The implication of our findings for future experimental design in exercise and aging research is discussed.

Predicting Age in the Adult Years from Psychological Assessments of Abilities and Personality

Predictions of chronological age at the time of examination were made from scores on the 12 subtests of the General Aptitude Test Battery and the Cattell Sixteen Personality Factor Questionnaire for 970 men ranging in age from 28 to 83 years. Performance on the three ability tests, Disassemble, Tool Matching, and Turn accounted for about 25 percent of the variability in chronological age. Three scales from the Cattell Questionnaire, Factor F (surgency-desurgency), Factor Q3 (high vs. low self-sentiment), and Factor I (sensitive-insensitive) accounted for 8 percent of the variance in age. The combined contribution of both sets of measures to the prediction of age was about 30 percent; the amount of common variance was about 5 percent when these measures were used together to predict age. Scores on the ability tests and the measure of surgency decline with age, while scores on the measures of self-sentiment and sensitivity increased with age.

“The Ages of Me”: Toward Personal and Interpersonal Definitions of Functional Aging

Personal age (how old a person seems to himself) is proposed (a) as a potential component of total functional age and (b) as a basis of classification in attempts to create and modify “old behavior.” Companion constructs are those of interpersonal age (how old a person seems to others) and consensual age (degree of agreement between personal and interpersonal ages). Illustrative data are reported from a sample of 75 adults (38 women, 37 men) who range in age from 20 to 69; 43 are enrolled in advanced gerontology training programs. The results suggest that personal age is comprised of at least two fairly distinct components: how old S looks and how old he feels. There is a strong bias toward reporting personal age as more youthful than chronological age—a bias that becomes more pronounced with advancing chronological age level. All of the age constructs are related to chronological age, although not always in a linear or simple manner. At this point in the research program, gerontology specialists do not appear conspicuously different from nongerontologists in their response to personal age and other related questions.

Age differences in biochemical and hematological measures during middle age

Biochemical and hematological measures possibly associated with ageing were measured on a single occasion in 3402 male and 2152 female London Civil Servants aged from 35 to 59 years of age. These included erythrocyte sedimentation rate (ESR), blood hemoglobin and serum albumin, calcium, bilirubin, creatinine, urea, urate, high density lipoprotein (HDL), and total cholesterol. Independently and positively related to age were ESR with an estimated 47% 'increase' in men over the 15 years between ages 40 to 55 and a 40% increase in women; serum urea had a 6%/15-year increase in men and 20% in women; total cholesterol had a 6%/15-year increase in men and 18% in women; serum creatinine 'increased' by 2%/15-years in men and 5% in women. In women, urate, HDL cholesterol and hemoglobin increased with age group. Negatively related to age was serum bilirubin in both sexes (8% and 6% 'fall'/15-years in men and women respectively). Serum albumin and calcium fell with age group in men. The sexes differed in their relationship to aging for total cholesterol and HDL cholesterol (greater increase in women), serum calcium (small decrease in men and small increase in women), urate and hemoglobin (increases in women but not men). Urea increased more in women than men, and albumin decreased more in men than women (p < 0.001 for all comparisons with the exception of HDL cholesterol, p < 0.01). Changes during the menopause were thought to explain some of these findings.

The assessment of biological age: a report from the Department of Environment Study

Indicators of ageing were measured in 397 male and 130 female London Civil Servants aged from 37 to 58 years of age. Grey hair, skin inelasticity, and arcus senilis were strongly and independently related to chronological age. Also independently related were serum albumin (negatively related in both sexes), baldness, serum creatinine, systolic blood pressure, serum calcium (negatively) and ESR in men, and serum cholesterol in women. Chronological age was regressed on the above variables for men and women separately to provide regression equations. Biological age for an individual was calculated by entering his or her results and calculating the residuals. Biological age in those who stopped smoking tended to be younger than chronological age by an average of 12-13 months in men and 1-4 months in women. Men and women who had never smoked had higher biological than actual ages but not after adjusting for regression dilution bias. Men who currently smoked had higher biological ages of 2-3 months but not women smokers (4-6 months lower). Similarly, men of lower employment grades had an average biological age 13 months older and women 8 months, compared with higher employment grades. These differences between employment grade appeared to be due to ESR, arcus senilis, systolic blood pressure and serum cholesterol. These four measurements may be markers of biological rather than chronological age, and the value of attempting to measure biological age is discussed.

A study on the basic nature of human biological aging processes based upon a hierarchical factor solution of the age-related physiological variables

The purpose of this study is to determine the laws governing the aging processes based on a hierarchical factor solution of the age-related physiological variables. Healthy individuals (462) who had taken a 2-day health examination were studied. Twenty-seven physiological variables were submitted to hierarchical factor solution. The analysis revealed that there was a fixed pattern in the variations of these 27 physiological variables. In this hierarchical factor solution, three group factors as functioning at different levels of complexity composed of the 16 common factors were extracted. Of these group factors, the first and third group factors can be referred to the aging process. The first group factor, the so-called factor 1 loaded with most of physiological variables, was interpreted as a primary aging factor which presented the primary process of human aging. The third group factor, the so-called factor 6 to 16 loaded only with a few variables related to a single physiological system or organ, were interpreted as system-specific secondary aging factor. These results obtained by the hierarchical factor solution thus seem to support the notion that biological age changes can be viewed as time dependent complex integration of the primary and secondary aging processes.

Assessment of biological age by principal component analysis

A method of assessing biological age by the application of principal component analysis is reported. Healthy individuals (462) randomly selected from about 6000 men who had taken a 2-day health examination were studied. Out of the 30 physiological variables examined in routine check-ups, 11 variables were selected as suitable for the assessment of biological age based on the results of factor analysis and the physiological meaning of each test. This variable set was then submitted to principal component analysis, and the 1st principal component obtained from this analysis was used as an equation for assessing one's biological age. However, the biological age calculated from this equation is expressed as a score, so the estimated score was transformed to years (biological age) using the T-score idea. The biological age estimated by this method is practically useful and theoretically valid in contrast with the multiple regression model, because this approach eliminates and overcomes the following 2 big problems of the multiple regression model: (1) the distortion of the individual biological age at the regression edges; and (2) a theoretical contradiction in that a perfect model will merely be predicting the subject's chronological age, not his biological age.

In defense of the concept of biological aging measurement--current status

Biological age is the objective assessment of a person's health status. Theoretically, a 'normal' person's biological age--in terms of appearance, performance, and functional capacity--should be the same as his chronological age. Many scientists have attempted to develop systems to accurately determine individuals' biological age. Typically, the approach is to select a battery of test parameters comprised of tests which correlate closely with chronological age. This approach assumes that those traits which vary most closely with age are the best indicators of the aging process. The goal has been to compare an individual to his chronological age peers to determine his relative aging status. Two papers (Costa and McCrae, 1980 and 1985) that criticize this concept and approach have heretofore gone unanswered. Lack of published dissent has caused many gerontologists to assume that Costa and McCrae are correct in their assertions that biological age cannot be measured and is not a valid concept. Consequently, some scientists have been reluctant to pursue research in this area. The purposes of this paper are: to critically evaluate the questions raised by Costa and McCrae; to reaffirm the validity of the concept of biological age; and to urge continued research in this most important subject.

Toward the behavioral assessment of biological aging in the laboratory mouse: concepts, terminology, and objectives

The thesis is presented that much of the controversy and confusion concerning the measurement of biological aging stems from the lack of agreement on clearly defined objectives, constructs, and methods to validate measures. To alleviate some of the confusion, basic terminology borrowed from psychometrics is offered to provide a conceptual framework within which such issues can be discussed. This psychometric nomenclature is subsequently applied to the development and evaluation of a test battery designed to assess biological aging in laboratory mice at a behavioral level of analysis. Reference is made to the assessment of reliability, content validity, construct validity, and predictive validity of tests of biological aging.

Physiological and behavioral correlates of lifespan in aged C57BL/6J mice

Physiological and behavioral measurements were made in a cohort of 29-month-old male C57BL/6J mice to determine whether any correlated significantly with lifespan. Significant linear relationships with lifespan were found among the physiological measures, including hematocrit and hemoglobin levels and collagen denaturation rate; however, body weight failed to be a significant predictor of survival. Among the behavioral variables studied, significant quadratic relationships with lifespan were found for exploratory activity and passive avoidance learning, while performance on a rotorod and a tightwire showed no significant relationships with lifespan. Through the use of multiple regression techniques, about one-third of the variance in lifespan could be explained by a combination of physiological variables, and about two-fifths could be explained by a combination of behavioral variables.