Assessing logistic regression applied to respondent-driven sampling studies : a simulation study with an application to empirical data

The aim of this study is to investigate the impact of different logistic regression estimators applied to RDS studies via simulation and the analysis of empirical data. Four simulated populations were created with different connectivity characteristics. Each simulated individual received two attributes, one of them associated to the infection process. RDS samples with different sizes were obtained. The observed coverage of three logistic regression estimators were applied to assess the association between the attributes and the infection status. In simulated datasets, unweighted logistic regression estimators emerged as the best option, although all estimators showed a fairly good performance. In the empirical dataset, the performance of weighted estimators presented an unexpected behavior, making them a risky option. The unweighted logistic regression estimator is a reliable option to be applied to RDS samples, with a performance roughly similar to random samples and, therefore, should be the preferred option

Effect of the carbohydrate counting method on glycemic control in patients with type 1 diabetes

<p>Abstract</p> <p>Background</p> <p>The importance of achieving and maintaining an appropriate metabolic control in patients with type 1 diabetes mellitus (DM1) has been established in many studies aiming to prevent the development of chronic complications. The carbohydrate counting method can be recommended as an additional tool in the nutritional treatment of diabetes, allowing patients with DM1 to have more flexible food choices. This study aimed to evaluate the influence of nutrition intervention and the use of multiple short-acting insulin according to the carbohydrate counting method on clinical and metabolic control in patients with DM1.</p> <p>Methods</p> <p>Our sample consisted of 51 patients with DM1, 32 females, aged 25.3 ± 1.55 years. A protocol of nutritional status evaluation was applied and laboratory analysis was performed at baseline and after a three-month intervention. After the analysis of the food records, a balanced diet was prescribed using the carbohydrate counting method, and short-acting insulin was prescribed based on the total amount of carbohydrate per meal (1 unit per 15 g of carbohydrate).</p> <p>Results</p> <p>A significant decrease in A1c levels was observed from baseline to the three-month evaluation after the intervention (10.40 ± 0.33% and 9.52 ± 0.32%, respectively, p = 0.000). It was observed an increase in daily insulin dose after the intervention (0.99 ± 0.65 IU/Kg and 1.05 ± 0.05 IU/Kg, respectively, p = 0.003). No significant differences were found regarding anthropometric evaluation (BMI, waist, hip or abdominal circumferences and waist to hip ratio) after the intervention period.</p> <p>Conclusions</p> <p>The use of short-acting insulin based on the carbohydrate counting method after a short period of time resulted in a significant improvement of the glycemic control in patients with DM1 with no changes in body weight despite increases in the total daily insulin doses.</p

The impact of transitions from employment to retirement on suicidal behaviour among older aged Australians

PURPOSE: Transition from employment to retirement may be detrimental to mental health, and associated with suicidal behaviour. This study investigated the association between employment and retirement status and suicidal behaviour among older aged Australians. METHODS: This study was based on the '45 and Up Study', a large prospective cohort study of participants from New South Wales (Australia) aged 45 years and older (N = 267,153), followed up over the period 2006-2018. The risk of attempted suicide and suicide was compared between categories of employment and retirement status in a series of recurrent event survival analysis models adjusting for identified time variant and invariant confounders. RESULTS: Compared to those who were employed, the risk of attempted suicide was higher among those who were not in the labour force and not retired (predominantly those who were sick or disabled, or carers) (HR = 1.97-95% CI 1.49-2.62), those who retired involuntarily (HR = 1.35-95% CI 1.03-1.77), and to a lesser extent those unemployed (HR = 1.31-95% CI 0.89-1.92). Risk of attempted suicide among those who retired voluntarily was similar to those who remained employed (HR = 1.09-95% CI 0.82-1.45). A similar pattern was evident for suicide, with a higher risk of suicide among those who were not in the labour force or retired, and those who retired involuntarily, compared to those who remained employed; however, these differences were not statistically significant. CONCLUSION: Transition from employment to retirement may be an important precipitating factor for suicidal behaviour, affected by current and previous mental health status. Services and programs facilitating continued or re-employment in older age, and adjustment to the transition from employment to retirement may prevent suicidal behaviour

Assessing respondent-driven sampling : a simulation study across different networks

The purpose was to assess RDS estimators in populations simulated with diverse connectivity characteristics, incorporating the putative influence of misreported degrees and transmission processes. Four populations were simulated using different random graph models. Each population was “infected” using four different transmission processes. From each combination of population x transmission, one thousand samples were obtained using a RDS-like sampling strategy. Three estimators were used to predict the population-level prevalence of the “infection”. Several types of misreported degrees were simulated. Also, samples were generated using the standard random sampling method and the respective prevalence estimates, using the classical frequentist estimator. Estimation biases in relation to population parameters were assessed, as well as the variance. Variability was associated with the connectivity characteristics of each simulated population. Clustered populations yield greater variability and no RDS-based strategy could address the estimation biases. Misreporting degrees had modest effects, especially when RDS estimators were used. The best results for RDS-based samples were observed when the “infection” was randomly attributed, without any relation with the underlying network structure