Abnormal lung function is commonly identified by comparing observed spirometric values to corresponding reference values. It is recommended that such reference values for spirometry are evaluated and updated frequently. The aim of this study was to estimate new reference values for Swedish adults by fitting a multivariable regression model to a healthy non-smoking general population sample from northern Sweden. Further aims were to evaluate the external validity of the obtained reference values on a contemporary sample from south-western Sweden, and to compare them to the Global Lung Function Initiative (GLI) reference values.n=501 healthy non-smoking adults aged 22–91 years, with age and height as predictors. The models were extended to allow the scatter around the outcome variable to depend on age, and age-dependent spline functions were incorporated into the models to provide a smooth fit over the entire age range. Mean values and lower limits of normal, defined as the lower 5th percentiles, were derived.Sex-specific multivariable linear regression models were fitted to the spirometric data of 1) and, in particular, forced expiratory vital capacity (FVC) were lower than both the observed values and the new reference values, but higher for the FEV1/FVC ratio.This modelling approach resulted in unbiased estimates of the spirometric outcomes, and the obtained estimates were appropriate not only for the northern Sweden sample but also for the south-western Sweden sample. On average, the GLI reference values for forced expiratory volume in one second (FEVThe evaluation based on the sample of healthy non-smokers from northern Sweden show that the Obstructive Lung Disease in Northern Sweden reference values are valid. Furthermore, the evaluation based on the south-western Sweden sample indicates a high external validity. The comparison with GLI brought further evidence to the consensus that, when available, appropriate local population-specific reference values may be preferred. Dynamic spirometry is an important tool for the assessment of lung function in daily clinical practice. Abnormal lung function is identified by comparing an observed value with a reference value. There are a large number of published reference values for spirometry available –14. The It is essential that the sample from which the reference values are derived is representative for the contemporary healthy non-smoking population. The age range and other anthropometric, ethnic, environmental, and socio-economic factors must be considered, since such factors can affect lung function . In addiLinear regression models have commonly been used to model lung function. In most models, the predictors are sex, age, and height, but sometimes also weight and ethnicity –6, 9–13.Recently, progress has been made in the area of modelling lung function and the Lambda-Mu-Sigma (LMS) method imbedded in the generalised additive models for location, scale and shape (GAMLSS) models , 29 is pThe aim of this study was to estimate new up-to-date reference values for spirometry for adults of European ancestry by fitting a multivariable regression model to data from Caucasian healthy non-smokers sampled from the general population of northern Sweden. Further aims were to evaluate the external validity of the new reference values on contemporary data of healthy non-smokers from south-western Sweden and to compare them with the GLI reference values.As a part of the Obstructive Lung Disease in Northern Sweden (OLIN) studies, 1,016 randomly selected respondents from a large postal questionnaire survey in 2006  were invHealthy non-smokers were defined as having none of the following criteria: usually wheeze when breathing; sputum production most days in periods of 3 months per year; ever have had asthma; been diagnosed as having asthma, chronic bronchitis, COPD or emphysema by a physician; ever use of asthma medication regularly or when needed; ever use of medication for chronic bronchitis, COPD, or emphysema; ever had ischemic heart disease; wheeze in past 12 months with concurrent breathlessness; wheeze in past 12 months without having a cold; wheeze in the past 12 months most days per week; any other disability that could affect the lung capacity; or mMRC dyspnoea scale≥2. A further exclusion criterion was a cumulative life-long smoking history of>1 pack year.1), forced expiratory vital capacity (FVC), and slow expiratory vital capacity (SVC). The procedure followed the ATS/ERS recommendations  absolute differences between the highest and the second highest values were: 38 ml (27 ml) for women and 59 ml (45 ml) for men in FEV1, and 53 ml (44 ml) for women and 69 ml (54 ml) for men in FVC. In total, 2.8% of the FEV1 measurements and 6.1% of the FVC measurements deviated>150 ml. Vital capacity (VC) was defined as the highest value of FVC and SVC. In total, 501 subjects, 49% women, were identified as healthy non-smoking subjects of European ancestry with adequate spirometry quality. Further details regarding the measurements of lung function can be found in the The age was calculated by one decimal point as the difference between date of birth and date of examination. Date of birth was collected from the Swedish national registry. Height was measured without shoes with an accurate stadiometer with 0.5 cm precision. Weight was measured with 0.5 kg precision with empty pockets without jacket and shoes. Caucasian ethnicity was defined as a subject of European ancestry. Two Jaeger Masterscope spirometers  were used to measure forced expiratory volume in one second . This assumption was extended to include the case when the SD is a linear function of one of the regression variables (an explanatory variable), in this case age. Further details of the statistical modelling are described in the Normal Q–Q plots were used to evaluate and confirm normal distribution of the spirometric indices FEVZ-scores  and percentiles were calculated for each subject. If the observed value has a perfect normal distribution with mean and SD equal to the mean and SD of the reference values, then mean and SD of the percentile point will be 0.50 and 0.2887, respectively. Equivalently, the mean and SD of the Z-score will be 0 and 1, respectively. These facts were used to statistically test the accuracy of the estimations. A p≥0.05 implies good model accuracy. In addition, possible relationships between Z-scores and age, height, weight, and sex were examined by ordinary linear regression models, with significant associations presented as Beta-coefficients. If the reference values are in perfect agreement with the observed values, no such relationship will exist.To evaluate the external validity of the OLIN reference values, they were also applied to spirometry data of a general population sample from another region in Sweden. In 2009–2012, clinical examinations were performed on a sample aged 17–78 years from the Swedish region of West Gothia . The exa1, FVC and FEV1/FVC ratio (meanOLIN and LLNOLIN) was compared to predictions by the GLI reference values (meanGLI and LLNGLI). The comparisons are displayed in graphs, for a male of 180 cm and a female of 165 cm, which are approximately the sex-specific average heights in Sweden.The predicted sex- and age-specific FEVAs a result of the modelling technique, the SD, reference value (mean), and lower limit of normal  for each of the spirometric indices are calculated by the following formulas:SD: A+B*ageMean: (B(J)*X(J))*SDLLN: Mean −1.645*SDwhere possible values for J ranges from 1–5, age is expressed in years, and the coefficients A, B, B1-5 and the variables X1-5 are found in The mean ages for the 244 women and 257 men in the reference sample from northern Sweden were 49.2 (range 22–91) and 46.6 (range 22–86) years, respectively. The mean height was 163.3 cm (range 139.0–181.0) for women and 178.9 cm (range 162.5–198.0) for men, and the mean weight was 68.2 kg (range 45.0–118.0) for women and 84.8 kg (range 56.0–148.0) for men. These are the ranges of age, height, and weight in which the equations for the OLIN reference values are valid.n=501) are shown in Mean observed and predicted values, observed values as percent of predicted values, Z-scores and percentiles for the reference sample (n=358). However, statistical testing revealed that the model fit was not perfect for some of the spirometric indices, especially among women . When also corrected for weight, the association between the Z-scores for FVC and FEV1/FVC reached statistical significance for female sex . No other statistically significant associations between the Z-scores and age, height, or weight were found when weight was included, except for the Z-score for FVC where height measured in cm yielded a B-coefficient of 0.018 with p-value 0.049.The OLIN reference values were applied to the south-western Sweden sample, and percent of predicted, Z-scores and percentiles were calculated for each subject. The mean percent of predicted was close to 100% and mean absolute values of the Z-scores are approximately≤0.4, corresponding to approximately≤3% of predicted, for all spirometric indices in both age groups and for both sexes in the south-western Sweden sample  than the predicted meanOLIN for women and 103 ml lower (p<0.001) than the predicted meanOLIN for men. For FVC, the predicted meanGLI was on average 203 ml lower for women (p<0.001) and 190 ml lower for men (p<0.001). The average predicted meanGLI for the FEV1/FVC ratio was 0.028 units higher (p<0.001) for women and 0.011 units higher for men (p<0.001).The predicted mean1, FVC and the FEV1/FVC ratio (mean and LLN) for a woman and man of average height are plotted by age in GLI for both FEV1 and, in particular, for FVC, were lower than meanOLIN across the ages 22–86 years. For a woman of average height, meanOLIN and meanGLI for FEV1 were similar, but meanGLI FVC is constantly lower than meanOLIN FVC. Consequently, the meanGLI FEV1/FVC ratio was also consistently lower than the meanOLIN for the woman. For a woman of average height, the LLNGLI and LLNOLIN for the FEV1/FVC ratio was well in concordance throughout the age span, but less so for FEV1 and FVC where LLNGLI was consistently lower than LLNOLIN. The pattern was somewhat different for the average height man, where the gap between LLNGLI and LLNOLIN increased with increasing age for all three spirometric indices. LLNGLI for the FEV1/FVC ratio reached below 0.7 at the age between 46 and 47 years for a woman of average height and at the age 39–40 years for a man of average height. The corresponding ages when LLNOLIN reached below 0.7 for the FEV1/FVC ratio are 43–44 years for the woman and 53–54 years for the man. Both the LLNGLI and LLNOLIN for FEV1/FVC reached below 0.7 in earlier stages in life for taller subjects compared to for shorter subjects of both sexes.To make further comparisons to the GLI reference values, the predicted reference values of FEV1 and FVC were lower than the corresponding values in our sample, but higher for the FEV1/FVC ratio. In addition, the SD for the GLI reference values was larger for all spirometric indices, which can impact the LLN. Furthermore, the results indicate a high external validity for Swedish conditions, when evaluated on the sample from south-western Sweden.The modelling approach in this study produced unbiased estimates of mean observed values in the reference sample from northern Sweden. The approach to model lung function by linear regression is a powerful technique, which we successfully extended to let the SD depend on age. In general, the GLI reference values for FEVHistorically, multivariable linear regression has commonly been used to model spirometric outcomes since it is robust and straight-forward. However, linear regression assumes that the outcome variable is normally distributed; an assumption not always true for all spirometric indices , 10. In 1, FVC and FEV1/FVC for a woman and man of average height differ across the entire life span with differences generally more pronounced in older ages. Despite recent debate of its appropriateness (1 and FVC expressed as percent of the predicted value (1/FVC ratio is used as a key element for the diagnosis of airway obstruction, the use of GLI may lead to invalid diagnosis of airway obstruction along with erroneous classification of airway and lung disease severity in the Swedish population (It is essential that reference values are evaluated and updated frequently in order to confirm that the classifications of normal and abnormal reflects the realities of the contemporary general population , 24, 25.iateness , classifed value . Also, spulation .A prominent advantage of the GLI reference values is that they cover an extensive age span and different ethnicities, and thus provide estimates without junction points. The GLI reference values for Caucasians are based on collated data from>57,000 subjects, and estimations based on such an extensive amount of data are likely to be valid. Undoubtedly, the GLI is an extremely valuable contribution to the field of lung function reference values, and provide the opportunity to compare a subject or a population to the world-wide average within each ethnicity which is of substantial value for, for example, international multi-centre studies. Quanjer et al.  has prev1 and FVC, reference values are provided also for SVC and for the highest value of the forced and slow VC, that is, the VC. Although the FVC is a recognised proxy for the VC, additional information of the lung function can be obtained by measuring the SVC, especially in subjects where FVC is reduced by air-trapping due to small-airways obstruction, for example, at early stages of COPD. For example, it is common practice that the FEV1/VC ratio is relied on when diagnosing obstruction and the GOLD criteria for the diagnosis of COPD recognise this alternative to the FEV1/FVC ratio (An advantage of our study is that, along with FEVVC ratio , but hitVC ratio , 26 and VC ratio , while sTwo spirometers, instead of only one, were used for the northern Sweden sample. However, they were of identical brand and model which limits the possible bias. The spirometers were calibrated on a daily basis, but the syringes were not sent for yearly calibration according to the ERS/ATS recommendations and there is a lack of calibration traceability. Further, future studies would most likely benefit from European Spirometry Driving Licenses for the staff and deep insight in previous study protocols such as the NHANES , 41. HowThe random sample size of 501 subjects is greater than the sample sizes in commonly used Swedish reference values , 5 and sTo summarise, the evaluation of the OLIN reference values based on the reference sample of healthy non-smokers from northern Sweden show that the models are valid. Further, the evaluation based on the healthy non-smokers from south-western Sweden indicates a high external validity of the model. The comparison with GLI brought further evidence to the consensus that, when available, appropriate local population-specific reference values may be preferred.


Identifying correlates of sedentary behavior in older adults is of major importance to healthcare. To our knowledge, there are no population studies in Latin America examining which factors are associated to high sitting time in older adults. Thus, the purpose of this study is to identify socio-demographic, clinical, and health behavior correlates of sitting time in a representative sample of older adults living in Southeastern Brazil.A cross-sectional study was conducted in twenty-four municipalities of the Triangulo Mineiro region in the State of Minas Gerais, Southeastern Brazil. A structured questionnaire was applied to obtain information on socio-demographic, clinical, and health behavior factors. Overall sitting time was assessed using a self-report instrument. A Multiple Correspondence Analysis was used to verify the association of sitting time with socio-demographic, clinical, and health behavior factors.3,296 older adults (61.5% women and 38.5% men) were included in the analysis. The overall median was 240.0 minutes of sitting time/day. The Multiple Correspondence Analysis showed that the group with the highest sitting time presented the following characteristics: women, age greater than 70 years, unschooled status, arterial hypertension, diabetes mellitus, use of medication, poor self-rated health, dependence in basic activities of daily living, and absence of regular physical activity.This study reveals that socio-demographic, clinical, and health behavior factors are associated with high sitting time in older adults from Southeastern Brazil. The results may help to identify older adults that should be targeted in interventions aiming at reducing sitting time. Life expectancy has increased substantially in developed countries in the last fifty years. This same phenomenon is taking place in developing countries and the impact of this demographic transition is one of the major challenges in the field of Public Healthcare ,2.In addition to the demographic transition, technological advances have facilitated performance of everyday tasks but at the same time are leading to a less active lifestyle . This caStudies have shown that prolonged sedentary behavior, independent of physical activity level, is associated with various negative health conditions such as cardiovascular disease , obesitySelf-reported sitting time has been used in many studies as a specific indicator of sedentary behavior ,11. In oFrom this evidence, it is essential to identify correlates of sitting time in older adults so that future interventions can target those individuals at higher likelihood for engaging in sedentary behaviors . Althoug2 with an average human development index of 0.717 [This cross-sectional study is part of the research project entitled “Health profile of the elderly population of the municipalities of the Regional Healthcare Administration - Uberaba/Minas Gerais”. The project contemplated a population of 79,924 people aged 60+ years  living iof 0.717 .Calculation of the representative sample took as reference the population of older adults of each municipality  and the Inclusion criteria for this study were: age ≥ 60 years; agreement to participate in the study by signing an informed consent form; achievement of the minimum score on the Mini-Mental State Examination ,29 and aData were collected from May 2012 to April 2013. Participants answered a structured questionnaire applied by trained interviewers containing questions on socio-demographic information, clinical factors, health behaviors, and sitting time. Body mass (kilograms) and height (meters) were measured on the same day of the interview.The socio-demographic factors included age, sex , monthly household income , living arrangements , and schooling . Given the low-educational level of our sample, we decided to adopt a simple classification of the participants as unschooled if they have never been to school, and schooled if they ever attended school.Clinical factors included: presence of arterial hypertension and/or diabetes mellitus, use of medication , falls in the last year , self-rated health, ability to perform basic activities of daily living, and body mass index (BMI).2) [Self-rated health was assessed using a scale that is commonly employed in epidemiological studies assessing sedentary behavior in older adults ,16,25. S2) .1) Do you currently smoke?, 2) Do you currently consume alcoholic beverages/drinks?, and 3) Do you engage in physical activity regularly? Answers to these questions were either yes or no.Health behaviors were assessed with questions pertaining to smoking, alcohol consumption and regular physical activity. The questions were: Overall sitting time was evaluated using questions regarding time spent seated on a usual weekday and a usual weekend day according to the International Physical Activity Questionnaire  validateData were entered in duplicate on Excel software, version 2007, and the statistical analyses were performed using the STATISTICA software .Descriptive analysis was performed for all variables. The overall sitting time in minutes/day was determined from the weighted average of the time spent seated on a weekday and on a weekend day. Participants were divided into two groups: the first group (G1) corresponded to values under the 75th percentile and the second group (G2) corresponded to values of the 75th percentile or above. This approach was used because previous research suggests that individuals at the highest quartile of sitting time are those with the highest risks for adverse health outcomes ,17.2) of the angle between the variables and respective dimensions. The candidate variables in the factorial plan for the bivariate analysis of sitting time with socio-demographic, clinical and health behavior factors were determined by statistical significance (p < 0.05). The criterion adopted for variables to remain in the factorial plan was the selection of variables with greater discrimination in each dimension. The number of dimensions was chosen by analyzing the decline of eigenvalues [A Multiple Correspondence Analysis was used for examining the association of sitting time with socio-demographic, clinical, and health behavior factors. The Multiple Correspondence Analysis method projects data into space-dimensions and searches for patterns in the dataset, helping to identify the variables more closely associated with different groups. A matrix of eigenvalues was determined to identify a combination of variables that presented more stability in the factorial plan and explained the largest percentage of variability in the dataset. This was verified by the square of the cosine .The initial sample was comprised of 3,430 older adults aged 60+ years. A total of 134 were excluded from the study due to incomplete data, resulting in a final sample of 3,296 older adults with a mean age of 70 ± 7.29 years (age range: 60 to 96 years). The overall median for sitting time  was 240.00  minutes/day.According to Table In terms of clinical factors, 65.9% n = 2,171) suffered from arterial hypertension, 19.9% (n = 655) had diabetes mellitus, 87.3%  used medication, 52.1%  had poor self-rated health, 27.5% (n = 905) had a fall in the previous year, 14.6% (n = 481) were dependent in basic activities of daily living, and 25.0% (n = 826) were obese  were smokers, 15.8% (n = 522) reported consuming alcoholic beverages, and 43.1%  did not engage in regular physical activity (Table  were smop < 0.05) for associations with sitting time and were candidates for the Multiple Correspondence Analysis.According to Tables In the analysis of the factorial plan, BMI was not among the combination of variables that showed greater stability and explanatory power for the percentage of variability in sitting time. Therefore, BMI was disregarded from further analyses. Variables with greater discrimination in each dimension and which therefore remained in the factorial plan were: sex, age, schooling, arterial hypertension, diabetes mellitus, use of medication, self-rated health, basic activities of daily living, and regular physical activity.2) to dimensions 1 and 2. Dimension 1 consisted of clinical factors with the highest contribution to high sitting time (G2). These clinical factors were: arterial hypertension, diabetes mellitus, use of medication, self-rated health, and basic activities of daily living. Dimension 2 consisted of socio-demographic factors with the highest contribution to high sitting time (G2). These socio-demographic factors were: age and schooling.The analysis of the eigenvalues favored dimensions 1 and 2 with values of 0.445 and 0.379, respectively. Table The variables of dimensions 1 and 2 were found by using coordinates  in the factorial plan, and explained 17.90% and 12.93% of the variability of the data, respectively  group (G2) were in general: women over 70 years of age, unschooled, had arterial hypertension and/or diabetes, used medication, had poor self-rated health, were dependent in basic activities of daily living, and did not engage in regular physical activity.These results are in line with previous research showing that sedentary behavior is influenced by several factors, including personal, social and cultural factors . In BrazWatching television is considered a leisure activity and is frequently reported as the most common sedentary activity in this age group ,41. ProlA factor that may influence sedentary behavior is the built environment ,43. A stSedentary behavior may also be influenced by gender but there is no consensus within the research community -49. In tAmong the clinical factors associated with sitting time in the present study, it is possible to highlight some negative health outcomes, including arterial hypertension, diabetes mellitus, medication use, and poor self-rated health. The association of higher sitting time with arterial hypertension and diabetes mellitus corroborates the results of other cross-sectional studies that previously examined this subject ,47,48,53In view of this evidence, interventions aiming at reducing time spent in sedentary behavior may be effective for achieving and maintaining good health by improving self-rated health and reducing medication use, hypertension and diabetes.Sedentary behavior is also associated with reductions in components of physical fitness among the elderly population ,57. ThesFinally, physical activity level tends to be lower with increasing age . In thisIn summary, this study identified the socio-demographic, clinical, and health behavior correlates of sitting time in a representative sample of older adults from Southeastern Brazil. The observed results are indicative of the need for future investigations to further identify other determinants of sedentary behavior in older adults from developing countries. In this context, longitudinal investigations may be of major importance. Given that sedentary behavior is considered a risk factor for chronic diseases and mortality, there is a need to develop interventions aiming at reducing this behavior. However, before intervening, it is always important to identify the ‘at-risk’ groups. Therefore, the present study contributes to identifying those older adults that should be prioritized in interventions in Southeastern Brazil aiming at reducing sitting time in this age group.This study has strengths and limitations. The strengths of this study include the representative sample of older adults residents of twenty-four municipalities as well as the use of the Mini-Mental State Examination in order to ensure inclusion of only those older adults who could reliably answer the questions during the interview . AnotherHigh sitting time in this study was associated with specific socio-demographic, clinical, and health behavior factors. The present study improves the understanding of the correlates of sitting time in older adults from a developing country. The results may be important for identifying the ‘at-risk’ groups of older adults when designing interventions strategies to reduce sitting time in developing countries with similar characteristics of Brazil.


Workers in Primary Health Care are often exposed to stressful conditionsat work. This study investigated the association between adversepsychosocial work conditions and poor quality of life among PrimaryHealth Care workers.Effort-Reward Imbalance model. Associationswere verified using multiple logistic regression.This cross-sectional study included all 797 Primary Health Care workersof a medium-sized city, Brazil: doctors, nurses, nursing technicians andnursing assistants, dentists, oral health technicians, and auxiliaryoral hygienists, and community health workers. Data were collected byinterviews. Quality of life was assessed using the WHOQOL-BREF; generalquality of life, as well as the physical, psychological, social andenvironmental domains were considered, with scores from 0 to 100. Higherscores indicate a better quality of life. Poor quality of life wasdefined by the lowest quartiles of the WHOQOL score distributions foreach of the domains. Adverse psychosocial work conditions wereinvestigated by the Poor quality of life was observed in 117 (15.4%) workers. Workers withimbalanced effort-reward (high effort/low reward) had an increasedprobability of general poor quality of life , and in the physical , and environmental  domains; those with low effort/low reward demonstrateda greater probability of poor quality of life in the social domain. Workers with overcommitment atwork had an increased likelihood of poor quality of life in the physical and environmental domains. These associationswere independent of individual characteristics, job characteristics,lifestyle, perception of general health, or psychological and biologicalfunctions.There is an association between adverse psychosocial work conditions andpoor quality of life among Primary Health Care workers. Quality of life is a multidimensional construct, which can be influenced by aspectsof work and personal life, physical and psychological health, social relations, andthe environment where a person lives . The WorQuality of life has been recognized as a relevant measure in various healthypopulations, including workers . Work isJob stress has become a subject of interest due to its significant impact on health,and has been associated with various health disorders, such as psychologicaldifficulties, coronary heart disease, signs and symptoms of muscle and skeletalproblems, and weight loss or gain -8. A sysEffort-Reward Imbalance model was developed to analyse job stress. Itfocuses on reciprocity of exchange in occupational life, in which a perceivedimbalance between high effort spent at work and low reward may elicit sustainedstress reactions with emotional disorders and adverse consequences for health , length of time in theprofession, length of time working in the Primary Health Care, labour regime[contracted (worker has no job security) or effective (worker has job security)],having another job (yes or no), and job satisfaction. Job satisfaction was assessedby the question, ‘– Lifestyle: Level of physical activity, smoking habits, andalcohol consumption. Level of physical activity was measured by the InternationalPhysical Activity Questionnaire (IPAQ), tested and validated in Brazil , which w– As for smoking habits, for those who reported being smokersor former smokers, the cumulative lifetime use of cigarettes was calculated,considering the daily intensity and duration of smoking throughout theworker’s entire life . The num In the case of alcohol consumption, the consumption of beer, wine,and spirits each was considered, based on the answer to the question, ‘Whatalcoholic beverage do you drink the most?’ To estimate the intensity oflifetime alcohol consumption, a weighted score was calculated taking into accountthe measurement of the drink , the quantity of this measurement that was consumed , the frequency , and the number of years of alcohol consumption. To classify thesubjects’ alcohol consumption, three categories were considered: never drank;lesser or greater alcohol consumption throughout life (based on median of thescore). In the case of wine, consumption was at most 1.71 glasses per day. Due tothe low consumption, this variable was dichotomized between those who consume wineor not.Perception of general health:self-perceived health , dichotomized aspositive  or negative .– Health condition: Presence of common mental disorders, assessed by the General Health Questionnaire(QSG-12) , whose rPresence of systemic diseases diagnosed by a physician.Hosmer-Lemeshow test.The program SPSS® version 17.0 for Windows was used for data analysis.Descriptive statistics were performed to obtain absolute and relativefrequencies of the categorical and ordinal variables, and median, mean, andstandard deviation for the quantitative variables. The frequency ofworkers’ responses to each question from the WHOQOL-BREF was obtained forthe different levels of the variables effort-reward imbalance, andovercommitment at work. In the bivariate analysis, the association between theindependent variables and the general quality of life and each of its domainswas verified by simple logistic regression analysis, obtaining a crude oddsratio, its statistical significance, and 95% confidence interval. Variablesassociated with general quality of life or the domains of quality of life(p < 0.20) in the bivariate analysis, or theoretically importantvariables in determining this outcome were included in the multiple logisticregression model. The interaction between the categorical independent variableswas observed by combining two variables to create a third. Of the new variables,one remained statistically significant in its association with quality of lifeand its domains, the combination of self-perceived health and mental disorderswith four categories . This combined variable was used in all models, rather than theisolated use of the two variables that comprise it. Interaction terms betweenthe variables were created between the quantitative variables. The fit of themodel was checked using the This study was approved by the Research Ethics Committee of Funorte and allparticipants signed an informed consent form (CEP/SOEBRAS: 0208/08).A total of 762 workers participated in the interviews (95.6%); two were excludedbecause they did not respond to two or more items from the psychological domain ofquality of life. The mean age of workers was 31.87 years old(±8.18 years). They studied 13.29 years on average(±3.23 years), had mean monthly income of US$ 715.06 (±US$ 891.53).Most workers were female (79.9%), lived with a partner (51.1%), were contracted(56.2%), and had no other job (84.1%). The middle level contained the most workers(63.0%), followed by superior (21.3%), and technical (15.7%). Approximately halfwere moderately satisfied with their job (53.4%), 20.5% were dissatisfied, and 26.1%were satisfied. The distribution of workers regarding lifestyle variables were forphysical activity level: very active, 29.5%; active, 48.7%; and irregularly activeor inactive, 21.8%; smoking habits: non-smokers, 93.3%; light or moderate smokers,2.0%; heavy smokers, 4.7%; and beer consumption: none, 68.0%; low or moderateconsumption, 16.3%; high or very high, 15.7%. Most did not drink wine (92.4%) orspirits (97.4%); 91.6% of workers showed positive self-perceived health; 29.9% hadan illness diagnosed by a physician and 22.4% exhibited common mental disorders.Most workers reported having good quality of life (84.6%); 117 workers (15.4%)related poor quality of life. The prevalence of poor quality of life in the physicaldomain was 37.1%; 25.1% in the psychological domain; 21.9% in the social domain, and27.2% in the environment domain. The 25th percentiles scores for quality of lifedomains were the following: physical 25th percentile = 64; psychological25th percentile = 60; social 25th percentile = 67;environmental 25th percentile = 50.More than half of the workers did not report adverse psychosocial work conditions, asrepresented by low effort/high reward (49.2%); 13.9% demonstrated high effort/highreward; 12.2% low effort/low reward; 24.6% high effort/low reward, and 40.5%reported overcommitment at work. The frequency of poor quality of life for all itemsthat comprise the domains of quality of life according to the different levels ofthe effort-reward imbalance variable and overcommitment at work is presented inTable The chance of general poor quality of life was significantly higher among workerswith high effort/high reward and with high effort/low reward. It was also higheramong workers who reported lower levels of physical activity, those with a negativeself-perceived health and common mental disorders, and those who reported systemicdisease diagnosed by a physician Table .There was a greater likelihood of poor quality of life in the physical andenvironmental domains among workers who had high effort/low reward, and in thesocial domain among workers with low effort/low reward, compared to those with loweffort/high reward. Workers with high overcommitment had a higher likelihood of poorquality of life in the physical and environmental domains Tables  and 4.Also associated with an increased likelihood of poor quality of life in the physicaldomain were living without a partner, job dissatisfaction, the presence of commonmental disorders, negative self-perceived health, and presence of systemic diseasesdiagnosed by a physician. In the psychological domain, a greater likelihood of poorquality of life was also observed among female workers, the oldest workers, thosewith fewer years of study, those dissatisfied with their work, and those who hadboth negative self-perceived health and the presence of common mental disordersTable .In the social domain, those more likely to exhibit poor quality of life were workerswho were living without a partner, workers in the middle levels, heavy smokers, andworkers with common mental disorders and systemic disease diagnosed by a physician.In the environmental domain, an increase in the years of study and income of workerswas associated with a decrease in the occurrence of poor quality of life.Individuals without a partner were less likely to have poor quality of life in thisdomain. There was a greater likelihood of poor quality of life among contractedworkers, those dissatisfied with their work, those who had common mental disorders,and those who had both common mental disorders and negative self-perceived healthTable .The effect of psychosocial work conditions on the quality of life of health workerswas assessed among workers of the Primary Health Care. After adjusting forindividual characteristics, job characteristics, and lifestyle and healthconditions, there remained a significant association between effort-reward imbalanceand poor quality of life, for general quality of life, as well as its physical,social, and environmental domains. Overcommitment was significantly associated withpoor quality of life in the physical and environmental domains. Overall, there was agreater prevalence of poor quality of life among workers with effort-rewardimbalance (high effort/low reward) and high overcommitment.This study revealed poor quality of life among 15.4% of workers, a lower percentagethan that recorded among dentists in the public service of Paraná, Brazil(26.2%) . HoweverWorkers with high effort/low reward and/or high overcommitment had a higherprevalence of general poor quality of life. Quality of life can be compromised byadverse psychosocial conditions at work, which has an impact on public andoccupational health . WorkplaAdditionally, the precariousness of health services within the scope of the BrazilianPrimary Health Care is a fact, represented by the accumulation of work, uncertainwork contracts, insecurity and/or job instability, lack of plans for positions andsalaries, and difficulty in exercising labor rights ,25,34. TEffort-Reward Imbalance model, workers with higheffort/low reward experience high physical and psychological demands at work withoutthe benefit of rewards in the form of financial gain , self-esteem(respect and support from colleagues and superiors), and/or safety and opportunities. Overcommitment is apersonal intrinsic component, resulting in a set of attitudes, behaviours, andemotions that reflect excessive stress in combination with a strong desire to beaccepted and appreciated. People with overcommitment tend to exaggerate theirefforts. There is evidence that excessive stress results in an underestimation ofthe challenge, which in turn can be triggered by an underlying motivation to try andexperience esteem and approval [Effort-RewardImbalance model were analysed separately to adhere to the predominantmanner used in the literature. Thus, it was possible to discuss the factors relatedto the individual worker separate from those related to the work environment.The prevalence of poor quality of life in the physical, and environmental domains wasgreater among workers with high effort/low reward and/or high overcommitment. Poorquality of life in in the physical domain was manifested by dissatisfaction withsleep, an inability to perform activities of daily life due to a lack of energy, theneed for medical treatment to carry out daily activities, and an incapacity forwork. According to the approval . Still, approval . A Braziapproval . In the Effort-RewardImbalance model) among Primary Health Care workers have not beenidentified. There is a consistency between the results of this study and thosestudies involving health workers [Sociomedical Panel of Employees).In this longitudinal study [Short-Form Health Survey (SF-36), includes items regardinglimitations in performing activities of daily life, similar to those comprising thephysical domain of the WHOQOL-BREF.Effort-reward imbalance and high overcommitment at work have been considered a riskfactor for health, such as cardiovascular disease, musculoskeletal pain, andpsychosomatic complaints -6, and i workers  or worke workers . The eff workers . In a lo workers , work abal study , the assEffort-Reward Imbalancemodel, was independently associated with poorer self-perceived health [There was no association between effort-reward imbalance and overcommitment withquality of life in the psychological domain. This result was surprising, since thepsychological consequences of stress at work are discussed in the literature ,7. In thd health . One hypEffort-Reward Imbalance model, reward includesrespect and support from work colleagues and superiors, the feeling of being treatedfairly and/or promotion prospects, job security, and social status. The resultssuggest that work relations interfere in the perception of an individual’spersonal relationships; or those who have problems in relationships in the workplacecan also more frequently exhibit problems in other areas of life. However,interpersonal relationships in the workplace have been identified as a challenge inthe Primary Health Care. Among the workers of the Primary Health Care in FederalDistrict, Brazil, the socio-professional relationships in teams presented the mostserious situation in the work process. The authors noted difficulties incommunication between management and subordinates, lack of integration in theworkplace, poor communication among staff, and lack of support from management forprofessional development [In the social domain, workers with low effort/low reward demonstrated a greaterprevalence of poor quality of life compared with those with low effort/high reward.In this domain, low reward was revealed as a determinant of poor quality of life,manifested in dissatisfaction with the support received from friends and personalrelationships. In the elopment . Such a elopment .Workers with high effort/low reward and high overcommitment had a higher prevalenceof poor quality of life in the environmental domain, revealed by feelings ofinsecurity on a daily basis, an unhealthy physical environment, a lack of access toinformation, less opportunity for leisure activities, dissatisfaction with wherethey live, and less access to health services. This result may reflect jobinsecurity, work overload, lack of professional development and inadequate workingconditions. Such conditions can affect people's perception of life and theenvironment where they live. Related to this finding was the observation made byPrimary Health Care workers of the Federal District, Brazil, that working conditionswere negatively affected by discomfort in the physical environment, the existence ofnoise in the workplace, the inadequacy of the workplace for the completion of tasks,and by people’s insecurity . Of the As previously noted in the literature, numerous variables were associated with anincreased prevalence of poor quality of life in general, and in the four domains,including individual characteristics and job characteristics, lifestyle and generalhealth variables: increased age , income One limitation of this study is that its data are based on subjective evaluations.Some authors suggest that using the same method to assess the independent anddependent variables leads to an inflated correlation. This situation can beexplained by negative affectivity, which is a personality trait that predisposesindividuals to experience negative emotions, leading to pessimism about the world.Thus, these people tend to consider their living conditions worse, their job morestressful, and their quality of life more affected than others without negativeaffectivity . In addiThis study indicates the need to investigate public policies promoting employeehealth, programs for managing stress in the workplace, and professional development.The quality of life of Primary Health Care workers may indicate the quality ofservices offered by health institutions, and for this reason, investing in thequality of life of those who care for other people in the Unified Health System canbring benefits to not only to workers, but also its users.Adverse psychosocial conditions at work, represented by effort-reward imbalance andhigh overcommitment, are associated with poorer quality of life among Primary HealthCare workers. Moreover, quality of life was determined by individualcharacteristics, job characteristics, lifestyle, and health conditions of theworkers. This result confirms the multifactorial construct of the quality of life.Actions aimed at improving the health and quality of life of workers must haveintersectoral nature taking into account the adverse psychosocial workingconditions.The authors have no financial or non-financial competing interests with any people ororganizations.MABT contributed to acquisition of data, and was the main writer of the paper. MRBparticipated in the literature review and drafting of the article. AMDV contributedto analysis and interpretation of data. VEG e EFF contributed to writing the articleand revised the final version. AMEBM contributed to conception and design, andinterpretation of data. RCF completed the statistical analysis, contributed to thedrafting of the article, and revised the final version. All authors read andapproved the final manuscript.


The number of diseases and physical functioning difficulties tend to increase with age. The aim of this study was to examine the trajectories of physical functioning across age groups and whether the trajectories differ according to disease status in different population subgroups.Repeat data from a nationally representative population sample, the Health and Retirement Study, was used. Participants were 10,709 men and 13,477 women aged 60–107 years at baseline with biennial surveys from 1992 to 2010. Average length of follow-up was 10.3 years ranging from 0 to 18 years. Disease status and physical functioning was asked about at all study phases and 10 items were summed to obtain a physical functioning score (0–10).Age modified the relationship between number of chronic diseases and physical functioning with older participants having more physical functioning difficulties with increasing number of diseases. An average 70-year-old participant with no diseases had 0.89 (95% CI: 0.85–0.93) physical functioning difficulties, with one disease 1.72 (95% CI: 1.69–1.76) difficulties, with two diseases 2.57 (95% CI: 2.52–2.62) difficulties, and with three or more diseases 3.82 (95% CI: 3.76–3.88) difficulties. Of the individual diseases memory-related diseases, stroke, pulmonary diseases, and arthritis were associated with significantly higher physical functioning difficulties compared with other diseases.Comorbidity is associated with greater burden of physical functioning difficulties. Of the studied diseases, memory-related diseases, stroke, pulmonary diseases, and arthritis alone or in combination limit most physical functioning. Loss of physical functioning seriously threatens the independence and quality of life of older people  is a longitudinal cohort study of retirement and health among a representative sample of older people in the United States. The extraordinarily rich and complex data with repeated measurements of exposure and outcome variables provides an opportunity to examine the trajectories of physical functioning across age groups and whether the trajectories differ according to disease status. We also examined the role of sociodemographic characteristics in the association between morbidity and physical functioning.The HRS is an ongoing cohort study of Americans, with interview data collected biennially on demographics, health behavior, health status, employment, income and wealth, and insurance status. The first cohort was interviewed in 1992 and every 2 years subsequently, with five additional cohorts added in the phases in between 1994 and 2010. The full details of the study are described elsewhere . Ethicaln = 24,186  and a total of 127,061 person-years of observation. The average length of follow-up was 10.2 years, ranging from 0 to 18 years.In this study, we used data from 1992 to 2010 including participants aged 60–107 years, Eight time-varying chronic diseases, previously found to be associated with physical functioning ,8,9, werIn addition, depressive symptoms were measured with the eight-item Center for Epidemiological Studies Depression scale (CES-D) . The CESBased on a priori decision, the number of chronic conditions at each study wave was summed and categorized as 0, 1, 2, and 3 or more, which was also supported by the variable distribution. The analyses were conducted by number of diseases and by individual diseases. The disease variables were treated as time-varying variables and their value was taken from the same time point as physical functioning.Physical functioning relevant for daily activities was asked about in each wave using standardized instruments ,21. DiffThree time-invariant variables were included in our regression models: gender, race, and education. Race was categorized into three groups . Education was categorized in three levels . Nonhousing financial wealth was used as time-variant and was divided into tertiles .Study population characteristics are reported across study waves by age as proportions for categorical variables. Age-related physical functioning trajectories were assessed using linear regression analyses with generalized estimation equations (GEE) using an exchangeable correlation structure to control for the intraindividual correlation between repeated measurements ,28. In tTo examine whether the age-related trajectories were dependent on disease status, we tested disease status × age interaction terms. Age, divided into 10-year categories, represents the time variable in the model and was determined by the respondent’s age at each interview phase. In the analyses, we examined the differences in number of physical functioning difficulties and their trajectories at different ages. The analyses were conducted by number of diseases and by individual diseases. We also examined these differences in different disease combinations and according to sociodemographic characteristics. Adjusted mean estimates were calculated to represent the average level of physical functioning at different age groups and sociodemographic factors. All models were adjusted for sociodemographic factors .Our sensitivity analysis addressed the possibility that including those who dropped out from the study or died during the follow-up may have confounded the results because of the selection due to poor health. We repeated the main analysis by taking into account only those who remained in the study over at least six visits. The SAS 9.3 Statistical Package was used for all analyses .p < .0001). For example, on average 70- to 79-year-old participants with no diseases had 0.89 (95% CI: 0.85–0.93) physical functioning difficulties, with one disease it rose to 1.72 (95% CI: 1.68–1.76) difficulties, with two diseases 2.57 (95% CI: 2.52–2.62) difficulties and with three or more diseases 3.82 (95% CI: 3.76–3.88) difficulties.The average age of the participants entering to the study was 73.0 (SD 8.1) years and they were followed biennially on average 10.2 years (median: 10 years). Of the individual diseases memory-related disease was associated with highest number of physical functioning difficulties across age groups. Among the participants aged 60–69 years stroke was also related to higher number of physical functioning difficulties. Among the participants aged 70 years and older arthritis and pulmonary disease were associated with significantly higher physical functioning difficulties compared with other diseases . Table 2Supplementary Table 1. Women with any disease showed much higher levels of physical functioning difficulties than men across age groups. In addition, those with low levels of education and nonhousing financial wealth and any disease had more physical functioning difficulties compared with highest level of education and wealth, respectively. Participants with other ethnic background had lower levels of physical functioning difficulties compared with white and black participants.Stratified analysis by sex, race, education, and nonhousing financial wealth are shown in n = 83,787 person observations) replicating the main findings (Supplementary Table 2). Finally, because the 10-item physical functioning outcome includes different aspects of physical functioning, we wanted to examine whether the results would be different with less heterogeneous outcome and the analysis were repeated focusing only to the mobility items. The results were very similar for the number of diseases and the individual diseases were almost in the same order as in the 10-item physical functioning outcome. The role of memory-related diseases was highlighted in both outcomes, but arthritis and pulmonary diseases did not stand out as much with mobility outcome and with overall 10-item physical functioning outcome.A sensitivity analysis was conducted by including only those who remained in the study at least six visits and with no missing data on diseases  or cognitive decline are independently associated with functional loss ,38. ThesThe main strengths of the study include the prospective longitudinal design with biennially updated information on physical functioning averaging 10 years, and in some cases even 18 years, of follow-up. The results can be generalized to the U.S. adult population due to the nationally representative sample.The limitations of the study also need to be acknowledged. First, chronic diseases were assessed by self-report and information on disease severity was not available. It is possible that self-reports may lead to under-reporting of diseases—persons who are infrequent users of health care and/or who display mild symptoms are least likely to report a doctor’s diagnosis. However, the reliability of self-reported heart disease in the HRS is shown to be highly consistent with self-reports of heart disease based on the National Health Interview Survey . Second, memory-related diseases and depressive symptoms were not measured in each study wave, thus likely underestimating the role of these diseases. Third, the effect of prevalent and incident diseases on physical functioning was not differentiated in the analyses, which has potential to bias the results for diseases occurring unexpectedly and having catastrophic and rapid effects on physical functioning, such as stroke and myocardial infarction. However, based on the additional analysis, we observed that in the HRS data the number of physical functioning difficulties were almost equally associated with both prevalent and incident diseases across the age groups, and thus the bias is in unlikely state. In addition, in our analyses chronic diseases are treated as time varying variables so that newly occurring diseases were also included in the analysis. Fourth, limited list of diseases was assessed in the HRS, and we lacked information on fractures, osteoporosis, peripheral arterial disease, and Parkinson’s diseases, all of which have been shown to be important predictors of physical disability ,9,40.Finally, difficulties in physical functioning were also based on self-reported information. Replication using objective physical performance measures would alleviate concerns regarding potential self-reported bias. On the other hand, self-reports provide valuable information about the person’s own perception of his/her functioning in the living environment . The outTo conclude, data from a population-based sample of US adults indicate that comorbidity is associated with the number of physical functioning difficulties and age modified this relationship. Early prevention of chronic diseases and proper treatment of existing diseases are important in order to help older people to maintain good physical functioning into old age.http://biomedgerontology.oxfordjournals.org/Supplementary material can be found at: EU’s Era-Age 2 program . S.S. is also supported by the Academy of Finland (273850). M.K. is also supported by the UK Medical Research Council (K013351), the National Heart, Lung and Blood Institute (HL36310), the National Institute of Aging (AG034454), and a professorial fellowship from the Economic and Social Research Council. J.H. is supported by the Economic and Social Research Council (ES/K01336X/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This work was supported by the The authors declare no conflict of interest.


Pasteurella multocida to adhere to and affect the rabbit respiratory epithelium. Nasal septa from rabbit fetuses were cultured with various lectins before the addition of P. multocida. The percentage of bacteria adhering to the epithelium was evaluated semiquantitatively by indirect immunoperoxidase (IIP) staining. The goblet cells (GCs) were counted in semithin sections stained with toluidine blue and served as the main morphological criterion to evaluate the inhibitory effect of the lectins. The lectins PNA, WGA, RCA120, and DBA significantly inhibited the adhesion of P. multocida to the ciliated epithelium (P < 0.05) and prevented the pathogen-induced increase in the number of GCs (P < 0.05) compared with those of positive control tissues. In addition, VVA, SJA, UEA I, DSL, SBA, and ECL significantly inhibited the increase in GCs compared with that of the control tissues. The results suggest that less aggressive therapeutic strategies, such as treatment with lectins, may represent alternative approaches to control bacterial respiratory infections.This study aimed to evaluate the ability of a panel of lectins to inhibit the ability of  Adhesion of pathogenic microorganisms to epithelial surfaces is an important step in the infection and colonization of a susceptible host –4. Infec E. coli K99 in swine and calves; adhesion and infection of this bacterium can be prevented using carbohydrates (CHOs) [ Helicobacter pylori to human gastric mucus and erythrocytes was inhibited by high molecular mass constituents derived from cranberries [Bacterial resistance to antibiotics is an ever-increasing concern. An alternative disease intervention strategy is to target important steps in disease pathogenesis rather than targeting the pathogen directly; in this case, we would seek to mitigate disease by limiting pathogen attachment to host cells and thereby reduce colonization using substances that, in contrast to antibacterial agents, do not destroy the pathogens but rather interfere with their first pathogenic step, namely, their attachment to host cells. Accordingly, antiadhesion therapies have been documented for the enteropathogens (CHOs) –13. In tnberries .Pasteurella multocida, which is considered a normal component of the upper respiratory tract flora in a variety of animal species, is a well-known pathogen responsible for a range of diseases and economic losses in bovines, swine, canines, laboratory animals, rabbits, and birds [ P. multocida can transition from being a normal inhabitant of the host to a pathogen capable of causing disease and death. Strategies to control P. multocida disease include vaccines and antibiotics, which can have limited efficacy [nd birds –19. Thisnd birds . Althougefficacy , 22. P. multocida serogroup A strains is hyaluronic acid [ P. multocida A serovar 3 strain Pm70 possesses CHO sequences similar to those found on several host epithelial surfaces [A major capsular component of allnic acid , 24, thenic acid , 26; addsurfaces , 28. The P. multocida infections with fewer side effects, this ex vivo study explored the possibility of inhibiting P. multocida adhesion to the respiratory epithelium  of fetal rabbits using lectins. The results showed that lectin pretreatment reduced the number of bacteria adhering to the apical surface of the epithelium and blocked the pathogen-induced increase in the number of GCs in respiratory tissues, thus raising the possibility of an alternative control strategy for bacterial infection.In a search for alternative strategies to controlP. multocida isolates from Pm147/08 to Pm160/08 were obtained from the turbinates, trachea, or lungs of diseased rabbits with rhinitis and bronchopneumonia [ P. multocida type A.neumonia . Routineneumonia , 31, conP. multocida isolates were passed through mice by intraperitoneal inoculation. Mice were euthanized after the first signs of disease, and the bacterium was recovered from the heart, liver, lung, and trachea and cultured on BHI agar at 37°C for 24 h before use. The bacterial mass was collected and diluted in glucose-enriched essential medium (MEM), achieving a final concentration of 107 CFU/mL via counting and plating.120, SBA, SJA, STL, UEA I, VVA, and WGA. They were selected based on a range of specificities for multiple sugars [A total of 18 distinct lectins from three commercial kits (Vector Laboratories) were used . These le sugars –37.This study was conducted with the approval of the Bioethics Committee of the Faculty of Veterinary Medicine of the National University of Colombia.−1) and ketamine (35 mg kg−1). The fetuses were delivered by caesarean and immediately euthanized by medullar sectioning; the females were also euthanized with an overdose of anesthetics immediately after the surgery. The skin, mandible, muscle, and palate of the fetuses were removed, and the nasal cavity was cross-sectioned with a sterile blade to obtain three slices, each 0.3 cm thick, from each animal. Sections were washed three times in MEM before tissue culture.Eight pregnant female rabbits at their 26th gestational day were anesthetized with xylazine ; six additional sections cultured without P. multocida or lectin and three sections incubated with each lectin alone were used as negative controls; six additional explants were incubated only with the bacterium and were used as positive controls. Tissue sections were immersed in 10 mL MEM supplemented with lectin in a 5 cm diameter Petri dish and incubated in a humid chamber with 5% CO2 and 95% O2 for 1 h. The samples were then washed three times with MEM to eliminate the nonadherent lectin. Next, 107 CFU of P. multocida was added to the samples, and they were incubated for 2 h. Three explants of each lectin treatment were fixed with 3.7% buffered formalin and three with Trump fixative  for 24 h. Control tissues were fixed in a similar manner [To evaluate the potential inhibitory effects of lectins onr manner , 38, 39.μg/mL of P. multocida was injected with complete Freund adjuvant (CFA); 7 days later, a booster dose with incomplete Freund adjuvant was applied. Finally, two doses of the antigen without adjuvant were inoculated one week apart. Animals were bled at 35 days p.i.; serum collected before inoculation served as a negative control. To eliminate cross-reactions, the serum was immunoadsorbed with normal nasal tissues of other fetuses. The serum was diluted 1 : 25 in sterile Tris-buffered saline (pH 7.6); 5 mL of the antiserum was then diluted in 1 mL of macerated sterile tissues previously washed with physiological salt solution. The mixture was centrifuged at 1000 rpm for 1 h at room temperature, and the supernatant was collected and frozen at −20°C until use. The working dilution of the primary antiserum was determined by indirect immunodot; a similar procedure was followed for the second antibody.A polyclonal antiserum raised in an adult female sheep was used. Briefly, as a first dose, 250 μm thick sections. The polyclonal antiserum raised in sheep was used as the specific primary antibody, and a commercial antiserum against ovine IgG produced in donkey was used as a secondary antibody  [The number of bacteria adhered to the ciliated border of the respiratory epithelial cells was assessed by an indirect immunoperoxidase (IIP) technique , 41. TheAldrich) . Nasal s P. multocida adherence to the epithelium was assessed by a semiquantitative procedure as follows: both epithelial surfaces of the nasal septa were considered the full area (100%) to which the bacteria could adhere, and a mean adherence level was determined; no bacteria adhering to the surface were scored as 0%; bacteria attached to >0–30% of the epithelial surface were considered to be of focal adhesion; bacteria adhered to >30–60% of the surface were considered to be multifocal; and bacteria adhered to >60% of the surface were interpreted to be of diffuse adherence.The level ofμm thick) were cut with a microtome (Microm) and stained with toluidine blue for approximately 30 s.Tissue sections fixed for 24 h in Trump solution were decalcified in 10% EDTA for seven days, washed with 0.1 mmol phosphate-buffered saline (pH 7.3), postfixed in 1% osmium tetroxide, dehydrated in an ascending alcohol gradient, and finally embedded in Epon 812 (Polysciences). Sections  in eight continuous fields of respiratory epithelium was analyzed in each of 3 replicates. The protective role of lectins was determined by calculating the percentage of GCs relative to those of other respiratory epithelial cells , 43. In  P. multocida were compared among the various lectin treatments and positive control tissues by ANOVA in a completely random model. To determine differences between treatments, a Dunnett test was performed, with P < 0.05 accepted as significant. To analyze the GC activity when the hypothesis was significant (P < 0.05), a Dunnett test was performed to compare each lectin treatment with the positive control [The mean proportions of ciliated respiratory epithelium covered by adhered and nonadhered control . P. multocida on the apical surface of the respiratory epithelium in lectin-treated tissues ranged from localized (>0–30%) (Immunostaining of(>0–30%)  to multi(>0–30%) ; by cont(>0–30%) .Lens culinaris), PNA (Arachis hypogaea), WGA (Triticum vulgaris), RCA120 (Ricinus communis), and DBA (Dolichos biflorus) significantly (P < 0.05) inhibited P. multocida adherence to the ciliated border of respiratory epithelial cells compared with that of the positive control tissues , DBA (Dolichos biflorus), RCA120 (Ricinus communis), SJA (Sophora japonica), UEA I (Ulex europaeus I), WGA (Triticum vulgaris), DSL (Datura stramonium), SBA (Glycine max), ECL , and PNA (Arachis hypogaea) also showed significant inhibitions (P < 0.05) of the GC number and activity , WGA (GlcNAc/Neu5Ac), RCA120 , DBA /GalNAc), and LCA (Man/Glc) significantly inhibited P. multocida adhesion to rabbit nasal respiratory epithelia and, in the cases of PNA, WGA, RCA120, and DBA also prevented an increase in the number and activity of GCs. These results suggest three possible explanations for the inhibitory activity of these lectins: (1) LCA, PNA, WGA, RCA120, and DBA bind to their specific CHO moieties present on the apical surface of the respiratory epithelium, thereby masking putative CHO receptors for corresponding lectins on the bacterial surface similar to those targeted in this work; (2) these lectins, on their side, recognize CHOs on the bacterial capsule and/or its LPS that serve as ligands for the corresponding lectin receptors on the apical membrane of the respiratory epithelium; and (3) both events occur simultaneously. Mason et al. [120, and WGA lectins recognize CHOs on the upper respiratory epithelium of laboratory rodents, partially confirming our results. In addition, Perfumo et al. [120) bind to receptors on the respiratory epithelial cells of the nasal cavity of healthy swine, as well as those suffering from atrophic rhinitis caused by P. multocida and B. bronchiseptica. Taken together, these findings indicate that CHOs and lectins with corresponding specificities are present on the apical surfaces of the respiratory epithelia of various animal species and most likely also on the surfaces of P. multocida and B. bronchiseptica, serving as receptors and ligands, respectively.In this study, treatment with the lectins PNA  and D-glucuronic acid residues, which are constituents of hyaluronan, a major nonsulfated glycosaminoglycan ubiquitous in all connective tissues; hyaluronan has also been described on both the apical and basal surfaces of the airway epithelium [ P. multocida serogroup A strains [ P. multocida serogroup A has been shown to adhere strongly to HeLa cells, turkey air sac macrophages, and alveolar macrophages; bacterial adhesion was reduced by treatment of the bacteria with hyaluronidase (to reduce the amount of capsule) or the addition of hyaluronic acid [ P. multocida serogroup A did not adhere to turkey air sac macrophages [ P. multocida isolated from rabbits to monolayers of HeLa cell cultures and to parakeratotic pharyngeal cells. Their most significant finding was that GlcNAc treatment inhibited bacterial adhesion to both cell lines. These results suggest that lectin-like molecules that serve as receptors for the microorganism are present on both epithelial surfaces. The main adherent role was attributed to P. multocida fimbriae [ P. multocida A3 fimbriae isolated from rabbits recognize GlcNAc on the cilia of the respiratory epithelium; they were also able to competitively block this binding using the same CHO. Conversely, Jacques et al. [ P. multocida possesses various structures able to contribute to its binding of the respiratory epithelial cells of swine and rabbits in vitro, the LPS and type IV fimbria are likely the main mediators of the adhesion, acting as the CHO and lectin ligands, respectively. It is conceivable that, in our studies, WGA simultaneously bound hyaluronan residues on the apical surface of the respiratory epithelium and on the capsule of P. multocida, thereby exerting a double inhibitory effect.WGA recognizes GlcNAc , indicating that soluble hyaluronan can prevent the adherence of LPS to membrane-bound hyaluronan [However, the protective effect of WGA in this research could also be attributed to the inhibition of adherence ofaluronan , 62. P. multocida, mainly its LPS. Using the same ex vivo model as in this study, a previous study from our group exposed nasal cultures to P. multocida or its LPS separately; in both cases, the main response of the respiratory epithelium was a statistically significant increase in the number and activity of GCs compared with those of controls [ in vivo and in vitro work on the LPS of Pseudomonas aeruginosa reinforced these observations, as the expression of the mucin MUC5AC in mucin-producing cells of the airways was stimulated by treatment with this molecule [ P. multocida, showed that the LPS was spontaneously released by the bacterium on the apical surface of the epithelial cells, where it entered the ciliated cells. This event was accompanied by increases in the number and activity of GCs, without any evidence of inflammatory cells [ P. multocida was one of the main targets of the inhibitory effect of the lectin WGA observed in this work.The increase in the number and activity of GCs observed in this study could be due to the stimulation of the bacterium itself but is more likely related to the presence of substances liberated bycontrols . Previoucontrols –65. Intrcontrols . Severalcontrols , 67. Recmolecule . Additiory cells . These r P. multocida adherence to the epithelium  also inhibited the increase in the number of GCs. It is not clear why LCA did not also have an inhibitory effect on these cells.Except for LCA, all lectins that prevented P. multocida adherence to the respiratory epithelium. Although we do not have a convincing explanation for the lack of inhibitory effect on P. multocida adhesion, part of the inhibitory effect of VVA, SJA, SBA, and ECL on GC number could be attributable to their specificity for CHOs residues containing Gal/GalNAc (and of DSL for GlcNAc), as these are important constituents of the LPS of P. multocida serovar 3, Pm70 [A different effect was found for VVA, SJA, UEA, DSL, SBA, and ECL, which significantly prevented the elevation in the number of GCs but did not significantly inhibit 3, Pm70 . P. multocida 3 Pm70 genome sequence identified two predicted filamentous hemagglutinin genes (fhaB1 and fhaB2) that might have similar adherent activities as that of the filamentous hemagglutinin protein of Bordetella pertussis, FhaB-FhaB1 FhaB2, for the adhesion to host cells [ P. multocida could have similar ligand affinity for CHO receptors on the airway epithelia of rabbits.Analysis of thest cells , 70, 71.st cells –74, an ist cells , 76, andst cells –80. The  P. multocida type A binds to the apical surface of rabbit nasal respiratory epithelia through several CHO-containing receptors, likely via bacterial surface structures, such as the capsule, LPS, type IV fimbriae, or lectin-like structures that may specifically bind to those glycosidic receptors, all of which would be potential targets for the inhibitory effect of the lectins observed in this work. We propose that, in addition to the potential use of lectins to inhibit the deleterious effects of P. multocida adhesion and colonization, it could also be more effective to employ the corresponding sugars, that is, D-Man, D-Glc, and GlcNAc, the effects of which have recently been demonstrated [The results of this study indicate thatnstrated . This apnstrated , 13, 82.nstrated , 9. P. multocida to the respiratory epithelia of fetal rabbit nasal septa ex vivo. The inhibition of P. multocida adhesion protected the respiratory cells from the lesions caused by the pathogen, and it is therefore highly probable that the undamaged mucosa would be able to clear the pathogen by innate protective mechanisms, such as mucociliary clearance. Preventing P. multocida colonization and cell damage in the upper respiratory tract may impede the bacteria from reaching deeper regions of the lungs. Our results support future investigations into whether the CHOs identified herein can also inhibit P. multocida adhesion in rabbits in vivo.A number of lectins were found to impede the attachment of


Legionella spp. Approximately 90% of all cases of legionellosis are caused by Legionella pneumophila, but other species can also be responsible for this infection. These bacteria are transmitted by inhalation of aerosols or aspiration of contaminated water. In Spain, environmental studies have demonstrated the presence of Legionella non-pneumophila species in drinking water treatment plants and water distribution networks. Aware that this evidence indicates a risk factor and the lack of routine assays designed to detect simultaneously diverse Legionella species, we analyzed 210 urine samples from patients presenting clinical manifestations of pneumonia using a semi-nested PCR for partial amplification of the 16S rDNA gene of Legionella and a diagnostic method used in hospitals for Legionella antigen detection. In this study, we detected a total of 15 cases of legionellosis (7.1%) and the first case of Legionnaires’ disease caused by L. anisa in Spain. While the conventional method used in hospitals could only detect four cases (1.9%) produced by L. pneumophila serogroup 1, using PCR, the following species were identified: Legionella spp. (10/15), L. pneumophila (4/15) and L. anisa (1/15). These results suggest the need to change hospital diagnostic strategies regarding the identification of Legionella species associated with this disease. Therefore, the detection of Legionella DNA by PCR in urine samples seems to be a suitable alternative method for a sensitive, accurate and rapid diagnosis of Legionella pneumonia, caused by L. pneumophila and also for L. non-pneumophila species.Legionnaires’ disease is a severe form of pneumonia, with worldwide relevance, caused by  Legionella spp. are environmental gram-negative bacteria that have been described as causative agents of Legionnaires’ disease. The infection is transmitted by inhalation of aerosols generated from man-made water systems or aspiration of water containing Legionella . To. To5′-GAmellitus and exposure to possible source of Legionella), signs and symptoms, clinical suspicions of atypical pneumonia, diagnosis of other pathogens and treatments.For positive cases, the patients’ clinical history was revised thoroughtly for informational purpose to set up a suitable correlation with our results. Laboratory analysis and image studies were checked as well as the presence of risk factors . The results obtained by immunochromatography and PCR were analyzed using McNemar test. p < 0.05 was considered to indicate statistical significance.All statistical analyses were performed using the IBMLegionella antigen and DNA, respectively  were positive for legionellosis with the following distribution: 4 cases were due to L. pneumophila (the same cases identified by immunochromatography), 1 case attributed to L. anisa and in the rest of positive samples (10 cases) the species of Legionella was not possible to identify (p < 0.05) between PCR and immunochromatography for the identification of Legionella in urine samples.A total of 210 urine samples from patients with a suspicion of pneumonia were analyzed using an immunochromatographic assay and molecular techniques to detect ectively . The firidentify . These rLegionella though water , similar to the values notified by the ECDC . The rep Network . The etiL. anisa was detected in our study. The patient was a 36 year-old female, immunocompetent, who attended the emergency room of a hospital in Madrid (Spain) presenting a 2-day fever (38.5–39°C), dyspnea, headache and cough. On physical examination, pulmonary auscultation revealed overall decreased breath sounds with discrete expiratory wheezing and bibasilar crackles. Chest X-ray showed an infiltrate to right lung base, which is characteristic for cases of atypical pneumonia (A case of legionellosis caused by neumonia .2 57 mmHg). Based on these results, this patient was admitted with a diagnosis of bilateral pneumonia. Samples were collected for microbiological analysis and treatment was started with bronchodilators and levofloxacin (500 mg/day). The following day, ceftriaxone was added to the intravenous antimicrobial regimen (2 g/day).Laboratory analysis revealed a white blood cell count of 14650/μL with 77% of neutrophil granulocytes, an elevated C-reactive protein level of 47.53 mg/L , a high LDH level of 660 U/L  and a condition of hypoxemia  during 10 days. After 15 days, examination showed resolution of the infection, with no infiltrates on a chest X-ray.In Europe, Spain is one of the countries that annually report an elevated number of legionellosis cases, ranking it in third position with 811 cases in 2013. Also, six of the largest European outbreaks of Legionnaires’ disease during the period 2008–2013, took place in Spain. These were associated with various sources including cooling towers, decorative fountains, water systems and pools .L. pneumophila  were identified by both methods, while in the remaining eleven diagnosed cases, Legionella spp.  and L. anisa , the detection was only possible through PCR. This difference could be due to the higher sensitivity and specificity of PCR methodology, as well as the existence of cases of L. non-pneumophila infections not identified by routine assays used in hospitals.In this study, we have detected 7.1% of positive cases of legionellosis (15 out of 210 samples) in patients with pneumonia who attended hospitals in Madrid, Spain. The diagnosis was carried out through routine and molecular techniques in urine samples. Cases of infection by L. pneumophila serogroup 1. In 2013, 92% of cases of legionellosis in Spain were diagnosed using this method, while 6% were by isolation in culture and the rest detected through a fourfold titre rise of Legionella antibody levels in serum [Legionella antigen in urine is the most common method used to confirm cases of Legionnaires' disease, because it is a rapid, easy, sensitive and specific technique [L. pneumophila serogroups or other Legionella species related to Legionnaire's disease [Legionella species in hospitals [Nowadays, diagnosis of legionellosis is mainly performed by antigen detection tests in urine specifically designed for in serum . The detechnique , 34. How disease , 35. Thiospitals .L. anisa in Spain, which was not detected by the hospital’s conventional method; on the contrary, it was identified through PCR and confirmed by DNA sequencing in urine and sputum samples. This result shows the important role that molecular techniques can have in the diagnosis of legionellosis, which have proved to be more sensitive and specific for the identification of different Legionella species such as L. anisa [For instance, we have reported the first case of Legionnaires’ disease caused by L. anisa , 36, 37.L. anisa is the most frequent L. non-pneumophila species in the environment, commonly being isolated in cooling towers, drinking water, wastewater treatment plants and in hospital water distribution systems [L. anisa in Midwest and Northeast Spain; it could therefore be associated with the appearance of cases of legionellosis by this species of Legionella in Spain [ systems , 38–41. in Spain .L. anisa as a causative agent of Legionnaire's disease and outbreaks of Pontiac fever have been previously demonstrated in Australia, France, the United Kingdom, the United States and Japan  [The role of nd Japan  [12, 18, (n = 2) .L. anisa in our patient with a diagnosis of pneumonia supported by clinical features and imaging study, allowed us to conclude that it could be a case of Legionnaire's disease attributed to L. anisa [According to the criteria established by the European Legionnaires’ Disease Surveillance Network and the evidences of the association of this microorganism with human disease, the identification of only L. anisa .Legionella spp. in man-made water systems may be important in preventing cases of Legionnaires’ disease.Legionnaires’ disease is not clinically distinguishable from other types of pneumonia, thus the development of powerful tools for the identification of legionellosis and a rational approach to diagnosis are required. Additionally, regular checks for Legionella in patients with clinical manifestations of respiratory disease was 7.1% in Madrid, in the period from September 2013 to December 2014, with one case a fatal outcome. In this study, we have described the first case of Legionnaire's disease caused by L. anisa in Spain, which was only detected through PCR and confirmed by DNA sequencing. These molecular methods demonstrated to be more suitable for the detection of cases of legionellosis than the diagnostic test used in hospitals. For this reason, semi-nested PCR for amplification of the 16S rDNA gene of Legionella could be a promising method for detection of cases of legionellosis by L. pneumophila as well as by L. non-pneumophila. The development of new easy-to-use performance diagnostic tools for simultaneous identification of different Legionella species remains an important goal in order to improve the management of patients with Legionella infection, allowing an earlier diagnosis so as to select a specific antimicrobial therapy.The prevalence of pneumonia caused by S1 Fig(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.


Individuals with no morbidities had lower mean WHtR values compared with individuals with at least one morbidity (p = 0.0075). In the multiple linear regression model, it was identified that when individuals had one or more of the most prevalent comorbidities, the mean WHtR increased by 0.0415 (p = 0.0065). A correlation between WHtR and CRP (p = 0.0379) was also verified. Based on the relationships observed between WHtR  and CRP among the elderly, WHtR may represent a screening tool because it is a simple and effective anthropometric index.The aim of this study was to analyze the association between waist-to-height ratio (WHtR) and C-reactive protein (CRP) in the elderly , to investigate the relationship between this anthropometric index and the presence of the most prevalent morbidities (isolated or combined), and to identify which morbidities  would have greater associations with WHtR. This cross-sectional population-based epidemiological study of a stratified sampling comprised 170 elderly individuals between 60 and 90 years of age (both genders). Home visits were used to administer questionnaires and to perform anthropometric measurements and blood collection. The mean patient age was younger than 70 years, with women comprising the majority (69.41%) and with 90% of the patients presenting with inadequate WHtR. Hypertension was the most prevalent morbidity in this cohort (58.52%), and when analyzed in combination, hypertension plus obesity were the most frequently diagnosed morbidities (17.65%). Obesity, which was among the most prevalent comorbidities, was the only comorbidity combined with WHtR ( As the population ages, increased longevity results in greater numbers of elderly individuals with higher survival rates ,2,3. TheAs an independent risk factor, abdominal obesity is directly associated with several morbidities , as wellLike anthropometric parameters, other variables are able to detect probable health risks, such as the plasma levels of inflammatory markers, particularly C-reactive protein (CRP), which predicts the development of cardiometabolic diseases . The CRPConsidering that non-communicable chronic diseases induce elevation in CRP values, and that the prevalence of these diseases is higher in the elderly, as is the elevation of CRP values ,20,21, iThis epidemiological study, was developed through Household Population Research, which is linked to the “First Diagnosis and Intervention of Food and Nutritional Status and Most Prevalent Non-communicable Diseases in the Population of João Pessoa, Brazil” (I DISANDNT/JP) project, conducted from July 2008 to January 2010. All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the protocol was approved by the Ethics Committee of Center for Health Sciences (CCS), Federal University of Paraíba (protocol number 0493).A representative sample of the city population was stratified using R software  and info2 [After training the team and after the pilot study, activities related to the study objectives were performed. The anthropometric evaluations included weight, height and waist circumference measurements. Each measurement procedure was performed in triplicate and the mean values were used. These measures were taken in the households of individuals participating. Excessive weight was assessed by BMI using the parameters proposed by the WHO, which considers general obesity as a BMI level ≥30 kg/m2 . Abdomin2 .After the patients fasted, qualified and trained nursing professionals collected blood samples in the patients’ homes for hs-CRP analysis. The samples were analyzed at the Clinical Laboratory of the “Lauro Wanderley” University Hospital where quantitative analysis was conducted by the agglutination of latex particles using an hs-CRP kit . The hs-CRP cut-off points for individuals between 60 and 64 years of age were <8.5 mg/dL for females and <7.9 mg/dL for males; for individuals 65 to 90 years of age, the cut-off values were <6.6 mg/dL for females and <6.8 mg/dL for males .i.e., an isolated morbidity), and the number of individuals with one or more morbidities .The presence of various diseases is common in the elderly . Morbidiet al. [Notably, demographic and socioeconomic descriptions of the elderly study population, as well as individual lifestyles, including smoking, alcohol consumption, the use of medications and physical activity, were also part of this study. Alcohol consumption was verified using the Quantitative Food Frequency Questionnaire (QFFQ) as reported by Luna et al. . The actet al. , which cThe number of subjects (n = 260) accounted for 12.81% of the entire population found in selected households (n = 2030). The elderly population originally selected (n = 212) comprised 18% of all subjects (n = 1175) and after drop-outs (n = 46), the study group comprised 170 seniors representing 14% of the selected population (n = 1175), higher than the percentage of the elderly in the municipality, which is 9.12% according to the Institute of Municipal Development and State of Paraiba [i.e., median, mean, standard deviation and range). Due to the non-normality of some variables, non-parametric tests were used. Spearman’s correlation test between the WHtR and CRP values was applied to analyze the dependence between these variables. To relate the WHtR and CRP variables with the discrete variables, the Wilcoxon test for the comparison of the means was used. Moreover, to determine whether there was an association between the WHtR and morbidities when analyzed in isolation, Fisher’s exact test was used. Finally, to adjust the WHtR and CRP research variables, the following multiple regression models were used:Descriptive statistics were initially applied, represented by simple frequency using central tendency and dispersion measures  . Regardii.e., the number of elderly patients with a single morbidity), hypertension was observed to be the most prevalent (32.35%), followed by obesity (8.23%) and diabetes (3.53%) (data not shown). However, when individuals with a single morbidity were analyzed in combination with individuals with combined comorbidities, the percentage of these pathologies  increased to 58.23%, 30% and 12.35%, respectively. However, when only the combined morbidities were analyzed , it was observed that the highest prevalence occurred for “hypertension + obesity” (17.65%), followed by “hypertension + diabetes” and “diabetes + obesity”.Regarding the prevalence of morbidities when analyzed in isolation , and it could be inferred that as WHtR increases, CRP also increases . By linking WHtR and CRP with discrete variables (Wilcoxon test), individuals without comorbidities had lower mean WHtR values compared to individuals with one or more comorbidities (p = 0.0075). Moreover, males have had lower WHtR values than females (p = 0.0490)  were combined with WHtR, the only association was with obesity, with a  0.0490) .p = 0.0065). However, in the second model proposed, no variable was significantly combined with CRP  was obtained, suggesting that in individuals with one or more of the most prevalent comorbidities found in this study, the average WHtR increased by 0.0415 units  and combined  in the elderly population of João Pessoa was analyzed based on a multiple regression model, along with the association between CRP values and WHtR.In the present study, we observed associations between WHtR, isolated and combined morbidity and CRP among the elderly. The association between the WHtR values and the occurrence of morbidities analyzed in isolation  [The association between high WHtR levels and the occurrence of one or more morbidities (combined) of high prevalence, such as hypertension, obesity and diabetes, is an unpublished result. The average WHtR value of individuals without any morbidity was lower than in individuals with at least one morbidity. A literature search revealed that the associations between anthropometric indicators and morbidities were analyzed only in isolation (yndrome) ,30,31. The high frequency of individuals with high WHtR levels (90%) in this study reinforces the results obtained from a cohort study in Taiwan involving subjects with an average age of 62.1 (±10.9) years, in which the prevalence of high WHtR (>0.50) was 83.9% . Becauseet al. [With respect to the influence of gender, it has been found that males have lower average WHtR values than females. These data are consistent with the findings of Jayawardana et al.  who obseet al.  who founet al. . Regardiet al. [p-value.Regarding the association between WHtR and CRP values in this study, Palacios et al.  investiget al. [The anthropometric parameter WHtR appears to be related to the onset of new cases of cardiovascular diseases in elderly individuals living in the rural area of Taiwan with wherein high WHtR levels (>0.50) were reported . Similaret al.  reportedThe relationships found demonstrated in this study reinforce the importance of using this anthropometric indicator as a screening tool because it is related to the most prevalent and most common morbidities analyzed in combination in individuals and not just merely to a certain morbidity in a population, as reported in other studies ,31. We concluded that, further studies should be performed with other populations and in different age groups, and cohort studies should be developed to verify whether the improvement of isolated and combined morbidities accompanied by a reduction in the values that are associated with of this relationship, which would better support the recommendation of using WHtR to screen for the combined morbidities that are most prevalent in a given population. It was considered the limitations of study cross-sectional design and self - reported morbidities.