Is a spot urine sample a good substitution to estimate 24-h urinary sodium excretion in a population ≥ 50 years old? A validation study.

PURPOSE: A variety of prediction equations have been able to estimate 24-h urinary sodium excretion from spot urine samples; however, Iranians over the age of 50 have not been compared and verified. Using spot urine samples as a substitute for 24-h urine samples to estimate 24-h urine sodium excretion among the population age 50 and older are the purpose of this study. METHODS: A 24-h urinary sodium excretion was studied by well-known Kawasaki, INTERSALT, Tanaka, and World Health Organization/Pan American Health Organization (WHO/PAHO) formulas. On 360 individuals, the mean bias, agreements between estimated and measured values, correlation, absolute and relative differences, and misclassification rates were evaluated for four equations. RESULTS: As a result, the mean urinary sodium excretion for a 24-h period was 136.3 ± 52.21 mmol/24-h, which corresponds to a calculated intake of 9.1 ± 3.8 g of salt per day. According to the WHO/PAHO formula, the mean bias between measured values and estimated 24-h urinary sodium excretion is - 21.6 mg/day (95% confidence interval (CI) - 144.8, 101.6 mg/day), which is the smallest difference compared with the other three formulas. The lowest rate of individual misclassification of salt intake was 40% for WHO/PAHO, especially for those who consumed less than 9 g/day, while Kawasaki had the lowest misclassification rate at higher levels of salt intake. CONCLUSION: As a result of our research, the WHO/PAHO equations accurately predict 24-h urinary sodium excretion among Iranians aged ≥ 50 more than other equations, both at the population level and at the individual level. However, further study is needed in regard to different ages in Iran.

Metabolic Syndrome and Body Composition Among People Aged 50 Years and Over: Results from The Neyshabur Longitudinal Study on Ageing (NeLSA).

There are few studies regarding body composition and metabolic syndrome (MetS) association in older adults. To evaluate the association between MetS and body composition indices in a large-scale population of subjects with an age of 50 and up. This study was based on the data from Neyshabur Longitudinal Study on Ageing (NeLSA) in a total of 7462 people of Neyshabur city in IRAN. The best cut-off scores and AUC value of body composition variables for having association with likelihood of MetS were determined by using a receiver operating curve analysis. Each unit increase in the Waist/Hip ratio, the odds of having MetS increase 3-6 times (OR: 4.937, 95%CI: 3.930, 6.203 in men; OR: 3.322, 95%CI: 2.259, 4.884 in women). In addition, in the case of BMI (OR: 1.256, 95% Cl: 1.226, 1.286 in men; OR: 1.104, 95% Cl: 1.086, 1.121 in women) and BFM (OR: 1.119, 95% Cl: 1.105, 1.133 in men; OR: 1.050, 95% Cl: 1.041, 1.060 in women), the chance of having MetS increases with increasing these variables. Totally, BMI and BFM showed the best AUC values. The optimal cut-off values for BMI in men was 26.45 and in women was 27.35 and for BFM in men was 23.35 and in women was 26.85. These results suggest that adiposity measures such as BMI and BFM are associated with likelihood of having MetS in subjects with an age of 50 and up, and that avoiding high adiposity is important to prevent MetS incidence.

Longitudinal assessment of the health-related quality of life among older people with diabetes: results of a nationwide study in New Zealand.

BACKGROUND: The current work examined experiences of Health-Related Quality of Life (HRQOL) among older adults with a diagnosis of Diabetes Mellitus (DM) over time compared to those without a diagnoses DM. METHODS: The sample was drawn from six biennial waves of the New Zealand Health, Work and Retirement survey, a prospective population-based cohort study of older adults 55-70 years at baseline. Data on sociodemographic factors, health behaviours, chronic disease diagnoses and physical and mental HRQOL (SF-12v2) were obtained using six biennial surveys administered 2006-2016. Generalised Estimating Equation models, adjusted for time-constant and -varying factors, were employed to compare HRQOL and its determinants over time for older adults with and without a diagnosis of DM. RESULTS: DM was negatively associated with physical HRQOL [ß (95% CI) - 7.43 (- 8.41, - 6.44)] with older adults affected by DM reporting scores 7.4 points lower than those without DM. Similarly, the mean Mental HRQOL score was lower among those affected by DM [ß = - 4.97 (- 5.93, - 4.01)] however, scores increased over time for both groups (p < 0.001). Greater age, more chronic conditions, sight and sleep problems, obesity, lower annual income, and fewer years of education were predictors of poorer HRQOL among older adults. CONCLUSIONS: Older adults affected by diabetes experienced poorer physical and mental HRQOL compared to those not affected when controlling for a range of sociodemographic and health related indices. A management aim must be to minimise the gap between two groups, particularly as people age.

The outcome in patients with brain stroke: A deep learning neural network modeling.

BACKGROUND: The artificial intelligence field is obtaining ever-increasing interests for enhancing the accuracy of diagnosis and the quality of patient care. Deep learning neural network (DLNN) approach was considered in patients with brain stroke (BS) to predict and classify the outcome by the risk factors. MATERIALS AND METHODS: A total of 332 patients with BS (mean age: 77.4 [standard deviation: 10.4] years, 50.6% - male) from Imam Khomeini Hospital, Ardabil, Iran, during 2008-2018 participated in this prospective study. Data were gathered from the available documents of the BS registry. Furthermore, the diagnosis of BS was considered based on computerized tomography scans and magnetic resonance imaging. The DLNN strategy was applied to predict the effects of the main risk factors on mortality. The quality of the model was measured by diagnostic indices. RESULTS: The finding of this study for 81 selected models demonstrated that ranges of accuracy, sensitivity, and specificity are 90.5%-99.7%, 83.8%-100%, and 89.8%-99.5%, respectively. Based on the optimal model (tangent hyperbolic activation function with the minimum-maximum hidden units of 10-20, max epochs of 400, momentum of 0.5, and learning rate of 0.1), the most important predictors for BS mortality were time interval after 10 years (accuracy = 92.2%), age category (75.6%), the history of hyperlipoproteinemia (66.9%), and education level (66.9%). The other independent variables are at moderate importance (66.6%) which include sex, employment status, residential place, smoking habits, history of heart disease, cerebrovascular accident type, blood pressure, diabetes, oral contraceptive pill use, and physical activity. CONCLUSION: The best means for dropping the BS load is effective BS prevention. DLNN strategy showed a surprising presentation in the prediction of BS mortality based on the main risk factors with an excellent diagnostic accuracy. Moreover, the time interval after 10 years, age, the history of hyperlipoproteinemia, and education level are the most important predictors for BS.

Epidemiological characteristics and trends in the incidence of animal bites in Maku County, Islamic Republic of Iran, 2003-2012.

This study examined the epidemiological characteristics and incidence over time of animal bites in Maku County. Data were obtained from health centre records of animal bites from 2003 to 2012. Information on demographic characteristics and bite-related factors were recorded. A total of 2232 people were bitten; the frequency of bites was highest among males (75.4%), rural residents (72.3%) and those < 20 years (47.3%). Most bites were to the legs and feet (65%) and dogs were responsible for 92% of bites. Over 25% of those bitten delayed seeking care for more than a day, particularly rural residents. The mean incidence was 250 per 100 000 population and there was a statistically significant increasing linear trend over the 10-year period. There is a need to raise public awareness, especially among rural residents, of the importance of early treatment. Given the increasing trend in animal bites, a health policy to tackle this problem is needed.

Is poor sleep quality associated with lipid profile in elderly population? Finding from Iranian Longitudinal Study on Ageing.

BACKGROUND: Abnormal lipid profile as one of reversible cardiovascular disease risk factors might be affected by poor sleep quality. AIM: This study aimed to assess the association between poor sleep quality and serum concentration of lipid profile in Iranian elderly population. METHODS: The study was performed on a representative sample of 3452 Iranian older people (≥60 years) who contributed in the Iranian Longitudinal Study on Ageing (IRLSA). Sleep quality was measured through the validated Persian version of Pittsburgh Sleep Quality Index (PSQI). Fasting blood samples were collected from the participants to measure plasma levels lipid profile. We used multiple linear regression model to evaluate the independent association of poor sleep quality with lipid profile. RESULTS: The mean age of participants was 68.0±6.7 years and 52.5% of them were male. In total, 52.4% of study population reported poor sleep quality (PSQI>5). Mean serum concentration of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) was 143.2±74.2 mg/dl, 195.6±43.2 mg/dl, 112.9±31.0 mg/dl, and 57.3±12.4 mg/dl, respectively. Poor sleep quality was significantly associated with serum levels of TG (ß=17.85; P=0.006), LDL-C (ß=5.45; P=0.039) and HDL-C (ß=-2.13; P=0.039) after adjusting for studied covariates. CONCLUSION: Our study illustrates that poor sleep quality is a risk factor for poorer lipid profile. Therefore, early behavioral or pharmacological interventions that improve sleep quality are necessary to modify lipid profile in elderly population.

Sleep duration and quality are associated with health-related quality of life in adults aged 60 years and older.

BACKGROUND: The current study aimed to determine the association between sleep duration and quality with health-related quality of life (HRQoL) among the Iranian older persons. METHODS: This study was conducted on a representative sample of 3452 Iranian older people (≥ 60 years) who participated in the Iranian Longitudinal Study on Ageing (IRLSA) launched in Neyshabur (Razavi Khorasan province, northeastern Iran). The Persian versions of 12-Item Short Form Survey (SF-12) and Pittsburgh Sleep Quality Index (PSQI) were utilized to measure the level of HRQoL and the level of sleep duration and quality, respectively. Multiple linear regression model was performed to analyze the data and clarify the independent association of sleep duration and quality with HRQoL. RESULTS: More than half of the study population (52.4%) suffered from poor sleep quality. 57.3% and 3.9% of individuals were short sleepers (< 7 h) and long sleepers (equal or more than 9 h), respectively. The total score of HRQoL was achieved 65.87 ± 20.55. After adjusting the covariates, the results indicated that short sleep duration was negatively associated with HRQoL (P < 0.05), whereas no significant associations were found between long sleep duration and HRQoL (P > 0.05). Interestingly, the results of multiple linear regression model revealed a significant negative association between poor sleep quality and HRQoL (P < 0.001). CONCLUSION: The current study confirmed that short sleep duration and poor sleep quality were independently associated with lower HRQoL in the older persons. Therefore, interventional courses should be planned to enrich sleep-related healthcare and general HRQoL in the older persons.

The epidemiology and treatment outcomes of COVID-19 patients admitted to an intensive care unit in an Iranian hospital in Neyshabur city.

Background and Aims: The COVID-19 pandemic and the infection of numerous individuals from diverse societies have emerged as major global challenges. Given the limited resources in intensive care units, effective bed management and resource allocation require a deep understanding of the disease. This study aimed to assess the epidemiology and treatment outcomes of COVID-19 patients admitted to an intensive care unit in an Iranian hospital in Neyshabur city. Methods: This cross-sectional study was conducted on COVID-19 patients hospitalized in intensive care units in Razavi Khorasan, Iran in 2021. Census sampling was used to include all intensive care units. Of the initial 480 cases, 54 cases were excluded based on the exclusion criteria, leaving 426 cases for the study. Data were collected with the help of a data collection form that was designed by the researcher and its content validity and reliability were measured with Cronbach's alpha coefficient (α = 89%.). Data were analyzed with SPSS version 20 software. Descriptive and inferential statistics were used to analyze the data. Mean, standard deviation, and interquartile range indicators were used for descriptive statistics, and absolute frequency and relative frequency (percentage) were used to show numbers and ratios. Results: The mean (SD) age of the patients was 66.33 (15.05) years, and 49.3% were female. The results showed that arterial blood oxygen saturation, respiratory rate, and Alzheimer's disease were significant variables for predicting mortality. Furthermore, arterial blood oxygen saturation, respiratory rate, and the need for transfusion of blood products were significant variables in predicting hospitalization and the risk of acute respiratory distress syndrome (ARDS). Conclusion: This study demonstrated that arterial blood oxygen saturation, respiratory rate, and Alzheimer's disease are crucial variables for predicting death. Furthermore, arterial blood oxygen saturation and respiratory rate are significant factors in predicting the risk of ARDS.

Association Between Metabolic Syndrome and Health-Related Quality of Life in Older Adults: Findings from the IRanian Longitudinal Study on Ageing.

Objectives: There are some studies without consensus on the association between metabolic syndrome (MetS) and health-related quality of life (HRQoL) and few studies among elderly participants; therefore, the aim of this study is evaluating the association between MetS and HRQoL between elderly participants after adjusting for possible confounding factors. Methods: A cross-sectional analysis was conducted with the data from baseline phase of the IRanian Longitudinal Study on Ageing. The MetS diagnosis was conducted based on the National Cholesterol Education Program Adult Treatment Panel III guidelines. The participants were 3452 subjects aged ≥60 years with and without MetS. The Prospective Epidemiological Research Studies in Iran version of the SF-12 questionnaire was used to examine subjects' perspectives on their well-being and general health level. The association between MetS and HRQoL was evaluated through multivariable linear regression model after adjusting for possible covariates. Results: MetS independently had an inverse association with subscales of HRQoL including physical functioning, physical problems, general health, social functioning, and emotional problems, even after fully adjusting for studied confounding factors. An inverse association was also observed between MetS and both mental component summary and physical component summary in the fully adjusted model. Conclusion: Older adults with MetS had a relatively worse physical and mental HRQoL in comparison with individuals without MetS. Independent of any underlying factors, the inverse association of MetS with HRQoL emphasizes the necessity of routine screening and treatment of MetS in older populations.

Independent roles of country of birth and socioeconomic status in the occurrence of type 2 diabetes.

BACKGROUND: There is strong evidence based on previous studies that ethnicity and socioeconomic status are important determinants of diversity in the occurrence of diabetes. However, the independent roles of socioeconomic status, country of birth and lifestyle factors in the occurrence of type 2 diabetes have not been clearly identified. This study investigated the relationships between socioeconomic status, country of birth and type 2 diabetes in a large diverse sample of residents of New South Wales, Australia, and aged 45 years and over. METHODS: The analysis used self-reported baseline questionnaire data from 266,848 participants in the 45 and Up Study. Educational attainment, work status and income were used as indicators of socioeconomic status. Logistic regression models were built to investigate associations between socioeconomic status, country of birth and type 2 diabetes. RESULTS: The adjusted odds of type 2 diabetes were significantly higher for people born in many overseas countries, compared to Australian-born participants. Compared with participants who had a university degree or higher qualification, the adjusted odds ratio (OR) for diabetes was higher in all other educational categories. Diabetes was more prevalent in people who were retired, unemployed or engaged in other types of work, compared with people who were in paid work. The prevalence of diabetes was higher in people with lower incomes. Compared with people who earned more than $50,000, the adjusted OR for diabetes was 2.05 (95% CI 1.95-2.14) for people who had an income less than $20,000 per annum. The relationships between socioeconomic factors and country of birth and diabetes were attenuated slightly when all were included in the model. Addition of smoking, obesity and physical activity to the model had marked impacts on adjusted ORs for some countries of birth, but relationships between diabetes and all measures of socioeconomic status and country of birth remained strong and significant. CONCLUSIONS: Country of birth and socioeconomic status are independent predictors of type 2 diabetes. However, in this population, country of birth had a stronger association with type 2 diabetes.

Predicting mortality in brain stroke patients using neural networks: outcomes analysis in a longitudinal study.

In this study, Neural Networks (NN) modelling has emerged as a promising tool for predicting outcomes in patients with Brain Stroke (BS) by identifying key risk factors. In this longitudinal study, we enrolled 332 patients form Imam hospital in Ardabil, Iran, with mean age: 77.4 (SD 10.4) years, and 50.6% were male. Diagnosis of BS was confirmed using both computerized tomography scan and magnetic resonance imaging, and risk factor and outcome data were collected from the hospital's BS registry, and by telephone follow-up over a period of 10 years, respectively. Using a multilayer perceptron NN approach, we analysed the impact of various risk factors on time to mortality and mortality from BS. A total of 100 NN classification algorithm were trained utilizing STATISTICA 13 software, and the optimal model was selected for further analysis based on their diagnostic performance. We also calculated Kaplan-Meier survival probabilities and conducted Log-rank tests. The five selected NN models exhibited impressive accuracy ranges of 81-85%. However, the optimal model stood out for its superior diagnostic indices. Mortality rate in the training and the validation data set was 7.9 (95% CI 5.7-11.0) per 1000 and 8.2 (7.1-9.6) per 1000, respectively (P = 0.925). The optimal model highlighted significant risk factors for BS mortality, including smoking, lower education, advanced age, lack of physical activity, a history of diabetes, all carrying substantial importance weights. Our study provides compelling evidence that the NN approach is highly effective in predicting mortality in patients with BS based on key risk factors, and has the potential to significantly enhance the accuracy of prediction. Moreover, our findings could inform more effective prevention strategies for BS, ultimately leading to better patient outcomes.

The concurrent accuracy of the modified telephone interview for cognitive status and mini-mental state examination tools in detection of cognitive impairment among older adults.

Due to the need for face-to-face administration of many cognitive screening tests, it is not always feasible to screen large-scale samples. Objective: This study aimed to assess the discriminant validity of the Persian version of Telephone Interview for Cognitive Status (P-TICS-m) and Mini-Mental State Examination in the middle-aged Iranian population. Methods: The P-TICS-m and MMSE were administered to 210 randomly selected middle-aged community-dwelling adults who had been registered in the Neyshabur Longitudinal Study on Ageing. Participants also underwent psychological examination by two neurologists to assess cognitive impairment based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria. To evaluate the discriminant validity of P-TICS-m and MMSE with DSM-V criteria, the sensitivity, specificity, positive and negative predictive values (PPV and NPV), and positive and negative likelihood ratios (LR+ and LR-) were calculated. Results: The mean age of the participants was 59.6±6.8 years. The TICS and MMSE were highly correlated (r=0.635, p<0.001). The sensitivity, specificity, PPV, NPV, LR+, and LR- to discriminate cognitive impairment were, respectively, 83%, 92%, 68%, 96%, 10, and 0.182 for MMSE and 100%, 13%, 19%, 100%, 1.16, and 0 for TICS-m. The receiver operating characteristic curve analysis results showed no statistically significant differences between P-TICS-m and MMSE. Conclusions: Our findings indicate that the TICS-m test can be used as a screening tool instead of the MMSE. Due to the low specificity and low PPV of the TICS-m compared to MMSE, the diagnosis should be confirmed using definitive diagnostic tests when a subject is classified as having cognitive impairment.

Diante da necessidade de administração face a face de muitos testes de triagem cognitiva, nem sempre é viável rastrear amostras em grande escala. Objetivo: O objetivo deste estudo foi avaliar a validade discriminante da versão persa do Telephone Interview for Cognitive Status (TICS-m) e do Miniexame do Estado Mental (MMSE) na população iraniana de meia-idade. Métodos: A versão persa do TICS-m (P-TICS-m) e do MMSE foi administrada a 210 adultos de meia-idade residentes na comunidade e selecionados aleatoriamente, que haviam sido registrados no Neyshabur Longitudinal Study on Ageing. Os participantes também foram submetidos a exame psicológico por dois neurologistas para serem avaliados quanto ao comprometimento cognitivo com base nos critérios do Manual de Diagnóstico e Estatística de Transtornos Mentais (DSM-V). Para avaliar a validade discriminante do P-TICS-m e do MMSE com os critérios do DSM-V, foram calculados a sensibilidade, a especificidade, os valores preditivos positivo e negativo (PPV e NPV) e a razão de verossimilhança positiva e negativa (LR+ e LR-). Resultados: A média de idade dos participantes foi de 59,6±6,8 anos. O TICS e o MMSE foram altamente correlacionados (r = 0,635, p <0,001). A sensibilidade, a especificidade, o PPV, o NPV, a LR+ e a LR- do MMSE para discriminar comprometimento cognitivo foram 83, 92, 68, 96%, 10, 0,182; e, para TICS-m, foram 100, 13, 19, 100%, 1,16 e zero, respectivamente. Os resultados da análise da curva característica de operação do receptor (ROC) não mostraram diferenças estatisticamente significativas entre P-TICS-m e MMSE. Conclusões: Nossos achados mostram que o teste TICS-m pode ser utilizado como ferramenta de triagem em vez do MEEM. Por causa da baixa especificidade e do baixo PPV do TICS-m em relação ao MMSE, o diagnóstico deve ser confirmado por meio de testes diagnósticos definitivos quando um indivíduo é classificado como portador de comprometimento cognitivo.

Sex-specific prevalence of metabolic syndrome in older adults: results from the Neyshabur longitudinal study on aging, Iran.

Purpose: The prevalence of metabolic syndrome (MetS) and associated diseases grows as the population ages. This study aimed to investigate sex differences in the prevalence of MetS and its components among people aged 50 years and older in Iran. Methods: Data were drawn from the Neyshabur Longitudinal Study on Ageing (NeLSA), which is an ageing component of the Prospective Epidemiological Research Studies in IraAn (PERSIAN). The NCEP ATP III and IDF criteria were used to identify the prevalence of MetS among 3383 men and 3873 women aged 50 years and older. Sociodemographic information, lifestyle and clinical factors were collected via an interview-based questionnaire. Weight and height, waist circumferences and blood pressure were measured. Laboratory measures such as fasting blood sugar, triglycerides and high-density cholesterol were also assessed. Results: The overall prevalence of the MetS according to the NCEP ATP III and IDF definitions were 45% and 47%, respectively. The prevalence of the MetS in men and women was 37% and 63% according to the NCEP ATP III definition, 33% and 67% by the IDF definition, respectively. The prevalence of MetS components was significantly higher in women than in men. Conclusion: In the current study, the prevalence of MetS and its components was significantly higher among women than men. We also observed good concordance between IDF and NCEP ATP III criteria.

Modeling Survival in Patients With Brain Stroke in the Presence of Competing Risks.

OBJECTIVES: After heart disease, brain stroke (BS) is the second most common cause of death worldwide, underscoring the importance of understanding preventable and treatable risk factors for the outcomes of BS. This study aimed to model the survival of patients with BS in the presence of competing risks. METHODS: This longitudinal study was conducted on 332 patients with a definitive diagnosis of BS. Demographic characteristics and risk factors were collected by a validated checklist. Patients' mortality status was investigated by telephone follow-up to identify deaths that may be have been caused by stroke or other factors (heart disease, diabetes, high cholesterol, etc.). Data were analyzed by the Lunn-McNeil approach at alpha=0.1. RESULTS: Older age at diagnosis (59-68 years: adjusted hazard ratio [aHR], 2.19; 90% confidence interval [CI], 1.38 to 3.48; 69-75 years: aHR, 5.04; 90% CI, 3.25 to 7.80; ≥76 years: aHR, 5.30; 90% CI, 3.40 to 8.44), having heart disease (aHR, 1.65; 90% CI, 1.23 to 2.23), oral contraceptive pill use (women only) (aHR, 0.44; 90% CI, 0.24 to 0.78) and ischemic stroke (aHR, 0.52; 90% CI, 0.36 to 0.74) were directly related to death from BS. Older age at diagnosis (59-68 years: aHR, 21.42; 90% CI, 3.52 to 130.39; 75-69 years: aHR, 16.48; 90% CI, 2.75 to 98.69; ≥76 years: aHR, 26.03; 90% CI, 4.06 to 166.93) and rural residence (aHR, 2.30; 90% CI, 1.15 to 4.60) were directly related to death from other causes. Significant risk factors were found for both causes of death. CONCLUSIONS: BS-specific and non-BS-specific mortality had different risk factors. These findings could be utilized to prescribe optimal and specific treatment.

The moderating role of underlying predictors of survival in patients with brain stroke: a statistical modeling.

Determining subclinical Brain stroke (BS) risk factors may allow for early and more operative BS prevention measures to find the main risk factors and moderating effects of survival in patients with BS. In this prospective study, a total of 332 patients were recruited from 2004 up to 2018. Cox's proportional hazard regressions were used to analyze the predictors of survival and the moderating effect by introducing the interaction effects. The survival probability 1-, 5- and 10-year death rates were 0.254, 0.053, and 0. 023, respectively. The most important risk factors for predicting BS were age category, sex, history of blood pressure, history of diabetes, history of hyperlipoproteinemia, oral contraceptive pill, hemorrhagic cerebrovascular accident. Interestingly, the age category and education level, smoking and using oral contraceptive pill moderates the relationship between the history of cerebrovascular accident, history of heart disease, and history of blood pressure with the hazard of BS, respectively. Instead of considerable advances in the treatment of the patient with BS, effective BS prevention remains the best means for dropping the BS load regarding the related factors found in this study.

Socio-demographic and lifestyle factors associated with multimorbidity in New Zealand.

OBJECTIVES: The incidence of multimorbidity (MM) and its correlates among older adults remain poorly understood. This study aimed to examine the socio-demographic and lifestyle factors associated with MM in New Zealand. METHODS: People aged 55-70 years were invited to participate in a population-based cohort study, the Health Work and Retirement Study, in 2006. Those who accepted the invitation and completed the baseline questionnaire were followed up on a biennial basis. Data on socio-demographic factors, health and lifestyle behaviours, and diagnoses of chronic diseases were obtained from baseline and 6 waves of follow-up. Generalised estimating equations (GEE) adjusted for both time-constant and time-varying factors were used to model factors associated with the onset of MM. RESULTS: A total of 1,673 participants (with 0 or 1 chronic condition) contributed to an overall 8,616 person-years of observation. There were 590 new cases of MM over 10 years of follow-up, corresponding to an overall incidence of 68.5 per 1,000 person-years. The results of the age- and sex-adjusted GEE analysis showed that age, ethnicity, living alone, obesity, hypertension, and having 1 chronic condition at baseline were significant predictors of MM onset. Higher education, income, physical activity, and regular alcohol consumption were protective factors. In a fully adjusted model, marital status (odds ratio [OR], 1.18; 95% confidence interval [CI], 1.01 to 1.37; p=0.039), hypertension (OR, 1.23; 95% CI, 1.02 to 1.48; p=0.032) and having 1 chronic condition at baseline (OR, 2.92; 95% CI, 2.33 to 3.67; p<0.001) remained significant. CONCLUSIONS: The higher incidence of MM among Maori people, socioeconomically disadvantaged groups, those with low physical activity, and obese individuals highlights the importance of targeted prevention strategies.

Predictors of long-term mortality after first-ever stroke.

BACKGROUND AND OBJECTIVE: Data on the factors affecting long-term mortality following a stroke in Iran are scarce. The current research aimed at investigating the extent of 2-year mortality following a stroke and the factors affecting it in the northwest of Iran. MATERIALS AND METHODS: This prospective cohort study was conducted in Tabriz, Northwest of Iran. Patients with computed tomography/magnetic resonance imaging confirmed the first-ever stroke were included in this study and followed up to 2 years. Clinical examinations, including the severity of the stroke using the modified National Institutes of Health Stroke Scale (mNIHSS), were conducted by a neurologist. The general characteristics, lifestyle factors, and laboratory tests were also completed. To estimate the survival, Kaplan-Meier analysis was used; and for group comparison, the log-rank method was applied. To identify the factors predicting 2-year mortality, semiparametric Cox regression analysis was used. RESULTS: A total of 1036 first-ever stroke patients were included in the present study. The mortality rates of stroke in 6-month, 1-year, and 2-years follow-up periods were 31.6%, 34.5%, and 38%, respectively. The two-year mortality rate was 33.6% in ischemic and 58.7% in hemorrhagic stroke (P < 0.001). In the multivariate Cox model, variables age, type of stroke, diabetes, and severity of the stroke, according to the mNIHSS index, were identified as factors predicting 2-year mortality following the stroke. CONCLUSION: The 2-year mortality following acute stroke was relatively high compared to that of in developed countries. Implementation of secondary prevention is recommended to better management of modifiable predictors of mortality.

Effect of Whey Protein Supplementation on Inflammatory and Antioxidant Markers, and Clinical Prognosis in Acute Ischemic Stroke (TNS Trial): A Randomized, Double Blind, Controlled, Clinical Trial.

Purpose: Malnutrition is extensively prevalent amongst critically ill patients afflicted by ischemic stroke (IS). This study purpose was to evaluate the protein whey effect on inflammatory and antioxidant markers and functional prognosis in acute IS patients. Methods: out of 42 patients with acute IS who were referred to Imam Reza Educational Hospital, Tabriz, Iran, 40 patients participated in the study. Twenty-one patients as control group received the hospital routine formula, and 19 patients as intervention group received 20 g/daily of whey protein through oral gavage. Inflammation and oxidative stress indicators (e.g., albumin, malondialdehyde (MDA), total antioxidant capacity (TAC), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and high sensitivity C reactive protein (hs-CRP)and clinical variables included in were evaluated using National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) during admission and also 3 weeks after intervention. Results: Whey protein supplementation significantly decreased the NIHSS and mRS scores, TNF-α, IL-6, and hs-CRP by passing 3 weeks from intervention (P<0.05). However, whey formula had no significant effect on other markers including albumin, and MDA. The hs-CRP (P = 0.02) reduction was significantly higher in whey protein group in comparison with control group. Conclusion: Whey protein supplementation reduced inflammation markers in those patients with IS. However, these changes should be studied in larger-scale trials.

Health related outcomes among people with type 2 diabetes by country of birth: Result from the 45 and Up Study.

BACKGROUND: Ethnic variation in the occurrence of type 2 diabetes, complications, mortality, and health behaviours has been reported. The current research examined patterns of health-related outcomes by country of birth in people with diabetes aged 45years and over in New South Wales, Australia. METHODS: This study was based on the baseline data of 266,848 participants aged 45years and over from "The Sax Institute's 45 and Up Study" (2006-2009), NSW; Australia's most populous state. Health-related factors including self-rated overall health, Quality of Life (QoL), eyesight, subjective memory complaint, hearing loss, psychological distress and functional limitation were examined according to country of birth among 23,112 people with type 2 diabetes. Logistic regression modelling was used to compare the odds of poor outcomes between Australian-born and overseas-born participants, adjusting for potential confounding and mediating variables. Both age-sex and fully adjusted odds ratios (aORs) are reported. RESULTS: Nearly half of the people with diabetes in the sample reported hearing loss and high levels of functional limitations, a third reported poor overall health. Compared to people with diabetes born in Australia, people born in South East Europe, North Africa, the Middle East had significantly greater odds of poor outcomes across the majority of examined health-related factors, with the largest odds observed in the elevated level of psychological distress outcome (aOR=3.4 in North African and the Middle East group). Higher aORs of poor overall health, QoL, memory problems and poor eyesight, and lower aORs for hearing loss, were also found among those born in the Asian countries. CONCLUSIONS: The results demonstrated significant ethnic disparity in the prevalence of health-related outcomes. These findings provide important context for the formulation of culturally sensitive secondary prevention strategies.

Identifying Factors Associated with Functional Limitation Among Diabetic Patients in Northwest of Iran: Application of the Generalized Additive Model.

BACKGROUND: Functional limitation is one of the most important health - related concerns of diabetic patients. This study aimed to identify the factors associated with functional limitation among diabetic patients using generalized additive model (GAM) as a flexible technique to reveal the non - linear and non - monotonic association between the response and a set of independent variables. METHODS: The source data belonged to two cross - sectional studies conducted in 2014. A total of 694 people with type 2 diabetes in the age range of 31 - 70 years were selected via convenience sampling from diabetes clinics in Ardabil and Tabriz. The data were collected by interviewers using structured questionnaires and checklists. The functional capacity was measured using the physical functioning subscale of the Medical Outcomes Study Short Form 36 - Item Health Survey (SF36). Participants with a total functional capacity of less than 90 were considered to have "moderate or high level of functional limitation." To identify the factors associated with functional limitation and reveal the shape of associations, the GAM procedure with "logit" link function was applied to the dataset of 378 diabetic patients without any missing data by smoothening of the effect of underlying factors. The Akaike information criterion (AIC) as the relative quality of the model's criterion was computed for GAM and compared with AIC of the simple logistic regression. RESULTS: Sex (P = 0.029), age (P < 0.001), BMI (P = 0.029), and SBP (P = 0.04) were significant in the GAM. Moreover, age with a linear function (df = 0.98), BMI with quadratic function (df = 1.75), and SBP with the degree 1.33 were significantly related to functional capacity. AIC of the GAM was lower than that of the logistic model. CONCLUSIONS: In our sample, GAM could identify some linear and nonlinear associations between underlying factors and functional limitation in diabetic patients. These complex associations could relatively increase the fit quality of the GAM when compared to logistic regression.