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  • 1. Agogo, George O.
    et al.
    van der Voet, Hilko
    van 't Veer, Pieter
    Ferrari, Pietro
    Muller, David C.
    Sanchez-Cantalejo, Emilio
    Bamia, Christina
    Braaten, Tonje
    Knuppel, Sven
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    van Eeuwijk, Fred A.
    Boshuizen, Hendriek C.
    A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data2016In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 16, article id 139Article in journal (Refereed)
    Abstract [en]

    Background: Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. Methods: We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Results: Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. Conclusions: The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.

  • 2.
    Fottrell, Edward
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Byass, Peter
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Berhane, Yemane
    Addis Continental Inst Publ Hlth, Addis Ababa, Ethiopia.
    Demonstrating the robustness of population surveillance data: implications of error rates on demographic and mortality estimates2008In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 8, p. Article nr 13-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity.

    METHODS: This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data.

    RESULTS: The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data.

    CONCLUSION: The low sensitivity of parameter estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.

  • 3.
    Hammarström, Anne
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Socialmedicin.
    Westerlund, Hugo
    Kirves, Kaisa
    Nygren, Karina
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Socialmedicin.
    Virtanen, Pekka
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Socialmedicin. School of Health Sciences, University of Tampere, Tampere, Finland.
    Hägglöf, Bruno
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Child and Adolescent Psychiatry.
    Addressing challenges of validity and internal consistency of mental health measures in a 27- year longitudinal cohort study–the Northern Swedish Cohort study2016In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 16, article id 4Article in journal (Refereed)
    Abstract [en]

    Background:There are inherent methodological challenges in the measurement of mental health problems in longitudinal research. There is constant development in definitions, taxonomies and demands concerning the properties of mental health measurements. The aim of this paper was to construct composite measures of mental health problems (according to today’s standard) from single questionnaire items devised in the early 1980s, and to evaluate their internal consistency and factorial invariance across the life course using the Northern Swedish Cohort.Methods:All pupils in the last year of compulsory school in Luleå in 1981 (n= 1083) form a prospective cohort study where the participants have been followed with questionnaires from the age of 16 (in 1981) until the age of43 (in 2008). We created and tested the following composite measures from self-reports at each follow-up:depressive symptoms, anxiety symptoms, functional somatic symptoms, modified GHQ and positive health. Validity and internal consistency were tested by confirmatory factor analysis, including tests of factorial invariance over time.Results:As an overall assessment, the results showed that the composite measures (based on more than 30-year-old single item questions) are likely to have acceptable factorial invariance as well as internal consistency over time.Conclusions:Testing the properties of the mental health measures used in older studies according to the standards of today is of great importance in longitudinal research. Our study demonstrates that composite measures of mental health problems can be constructed from single items which are more than 30 years old and that these measures seem to have the same factorial structure and internal consistency across a significant part of the life course. Thus, it can be possible to overcome some specific inherent methodological challenges in using historical data in longitudinal research.

  • 4. Kabudula, Chodziwadziwa W.
    et al.
    Clark, Benjamin D.
    Gomez-Olive, Francesc Xavier
    Tollman, Stephen
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health. MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; INDEPTH Network, Accra, Ghana .
    Menken, Jane
    Reniers, Georges
    The promise of record linkage for assessing the uptake of health services in resource constrained settings: a pilot study from South Africa2014In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 14, article id 71Article in journal (Refereed)
    Abstract [en]

    Background: Health and Demographic Surveillance Systems (HDSS) have been instrumental in advancing population and health research in low-and middle-income countries where vital registration systems are often weak. However, the utility of HDSS would be enhanced if their databases could be linked with those of local health facilities. We assess the feasibility of record linkage in rural South Africa using data from the Agincourt HDSS and a local health facility. Methods: Using a gold standard dataset of 623 record pairs matched by means of fingerprints, we evaluate twenty record linkage scenarios (involving different identifiers, string comparison techniques and with and without clerical review) based on the Fellegi-Sunter probabilistic record linkage model. Matching rates and quality are measured by their sensitivity and positive predictive value (PPV). Background characteristics of matched and unmatched cases are compared to assess systematic bias in the resulting record-linked dataset. Results: A hybrid approach of deterministic followed by probabilistic record linkage, and scenarios that use an extended set of identifiers including another household member's first name yield the best results. The best fully automated record linkage scenario has a sensitivity of 83.6% and PPV of 95.1%. The sensitivity and PPV increase to 84.3% and 96.9%, respectively, when clerical review is undertaken on 10% of the record pairs. The likelihood of being linked is significantly lower for females, non-South Africans and the elderly. Conclusion: Using records matched by means of fingerprints as the gold standard, we have demonstrated the feasibility of fully automated probabilistic record linkage using identifiers that are routinely collected in health facilities in South Africa. Our study also shows that matching statistics can be improved if other identifiers (e.g., another household member's first name) are added to the set of matching variables, and, to a lesser extent, with clerical review. Matching success is, however, correlated with background characteristics that are indicative of the instability of personal attributes over time (e.g., surname in the case of women) or with misreporting (e.g., age).

  • 5.
    Liv, Per
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
    Mathiassen, Svend Erik
    Svendsen, Susanne Wulff
    Accuracy and precision of variance components in occupational posture recordings: a simulation study of different data collection strategies2012In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 12, p. 58-Article in journal (Refereed)
    Abstract [en]

    Background: Information on exposure variability, expressed as exposure variance components, is of vital use in occupational epidemiology, including informed risk control and efficient study design. While accurate and precise estimates of the variance components are desirable in such cases, very little research has been devoted to understanding the performance of data sampling strategies designed specifically to determine the size and structure of exposure variability. The aim of this study was to investigate the accuracy and precision of estimators of between-subjects, between-days and within-day variance components obtained by sampling strategies differing with respect to number of subjects, total sampling time per subject, number of days per subject and the size of individual sampling periods.

    Methods: Minute-by-minute values of average elevation, percentage time above 90 degrees and percentage time below 15 degrees were calculated in a data set consisting of measurements of right upper arm elevation during four full shifts from each of 23 car mechanics. Based on this parent data, bootstrapping was used to simulate sampling with 80 different combinations of the number of subjects (10, 20), total sampling time per subject (60, 120, 240, 480 minutes), number of days per subject (2, 4), and size of sampling periods (blocks) within days (1, 15, 60, 240 minutes). Accuracy (absence of bias) and precision (prediction intervals) of the variance component estimators were assessed for each simulated sampling strategy.

    Results: Sampling in small blocks within days resulted in essentially unbiased variance components. For a specific total sampling time per subject, and in particular if this time was small, increasing the block size resulted in an increasing bias, primarily of the between-days and the within-days variance components. Prediction intervals were in general wide, and even more so at larger block sizes. Distributing sampling time across more days gave in general more precise variance component estimates, but also reduced accuracy in some cases.

    Conclusions: Variance components estimated from small samples of exposure data within working days may be both inaccurate and imprecise, in particular if sampling is laid out in large consecutive time blocks. In order to estimate variance components with a satisfying accuracy and precision, for instance for arriving at trustworthy power calculations in a planned intervention study, larger samples of data will be required than for estimating an exposure mean value with a corresponding certainty.

  • 6. Mathiassen, Svend Erik
    et al.
    Wahlström, Jens
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
    Forsman, Mikael
    Bias and imprecision in posture percentile variables estimated from short exposure samples2012In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 12, p. 36-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Upper arm postures are believed to be an important risk determinant for musculoskeletal disorder development in the neck and shoulders. The 10th and 90th percentiles of the angular elevation distribution have been reported in many studies as measures of neutral and extreme postural exposures, and variation has been quantified by the 10th-90th percentile range. Further, the 50th percentile is commonly reported as a measure of "average" exposure. These four variables have been estimated using samples of observed or directly measured postures, typically using sampling durations between 5 and 120 min.

    METHODS: The present study examined the statistical properties of estimated full-shift values of the 10th, 50th and 90th percentile and the 10th-90th percentile range of right upper arm elevation obtained from samples of seven different durations, ranging from 5 to 240 min. The sampling strategies were realized by simulation, using a parent data set of 73 full-shift, continuous inclinometer recordings among hairdressers. For each shift, sampling duration and exposure variable, the mean, standard deviation and sample dispersion limits (2.5% and 97.5%) of all possible sample estimates obtained at one minute intervals were calculated and compared to the true full-shift exposure value.

    RESULTS: Estimates of the 10th percentile proved to be upward biased with limited sampling, and those of the 90th percentile and the percentile range, downward biased. The 50th percentile was also slightly upwards biased. For all variables, bias was more severe with shorter sampling durations, and it correlated significantly with the true full-shift value for the 10th and 90th percentiles and the percentile range. As expected, shorter samples led to decreased precision of the estimate; sample standard deviations correlated strongly with true full-shift exposure values.

    CONCLUSIONS: The documented risk of pronounced bias and low precision of percentile estimates obtained from short posture samples presents a concern in ergonomics research and practice, and suggests that alternative, unbiased exposure variables should be considered if data collection resources are restricted.

  • 7. May, Anne M.
    et al.
    Adema, Lotte E.
    Romaguera, Dora
    Vergnaud, Anne-Claire
    Agudo, Antonio
    Ekelund, Ulf
    Steffen, Annika
    Orfanos, Philippos
    Slimani, Nadia
    Rinaldi, Sabina
    Mouw, Traci
    Rohrmann, Sabine
    Hermann, Silke
    Boeing, Heiner
    Bergmann, Manuela M.
    Jakobsen, Marianne Uhre
    Overvad, Kim
    Wareham, Nicholas J.
    Gonzalez, Carlos
    Tjonneland, Anne
    Halkjaer, Jytte
    Key, Timothy J.
    Spencer, Elizabeth A.
    Hellström, Veronica
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Manjer, Jonas
    Hedblad, Bo
    Lund, Eiliv
    Braaten, Tonje
    Clavel-Chapelon, Françoise
    Boutron-Ruault, Marie-Christine
    Rodriguez, Laudina
    Sánchez, Maria J.
    Dorronsoro, Miren
    Barricarte, Aurelio
    Maria Huerta, Jose
    Naska, Androniki
    Trichopoulou, Antonia
    Palli, Domenico
    Pala, Valeria
    Norat, Teresa
    Mattiello, Amalia
    Tumino, Rosario
    van der Daphne, A.
    Bueno-de-Mesquita, H. Bas
    Riboli, Elio
    Peeters, Petra H. M.
    Determinants of non- response to a second assessment of lifestyle factors and body weight in the EPIC-PANACEA study2012In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 12, article id 148Article in journal (Refereed)
    Abstract [en]

    Background: This paper discusses whether baseline demographic, socio-economic, health variables, length of follow-up and method of contacting the participants predict non-response to the invitation for a second assessment of lifestyle factors and body weight in the European multi-center EPIC-PANACEA study. Methods: Over 500.000 participants from several centers in ten European countries recruited between 1992 and 2000 were contacted 2-11 years later to update data on lifestyle and body weight. Length of follow-up as well as the method of approaching differed between the collaborating study centers. Non-responders were compared with responders using multivariate logistic regression analyses. Results: Overall response for the second assessment was high (81.6%). Compared to postal surveys, centers where the participants completed the questionnaire by phone attained a higher response. Response was also high in centers with a short follow-up period. Non-response was higher in participants who were male (odds ratio 1.09 (confidence interval 1.07; 1.11), aged under 40 years (1.96 (1.90; 2.02), living alone (1.40 (1.37; 1.43), less educated (1.35 (1.12; 1.19), of poorer health (1.33 (1.27; 1.39), reporting an unhealthy lifestyle and who had either a low (<18.5 kg/m2, 1.16 (1.09; 1.23)) or a high BMI (>25, 1.08 (1.06; 1.10); especially >= 30 kg/m2, 1.26 (1.23; 1.29)). Conclusions: Cohort studies may enhance cohort maintenance by paying particular attention to the subgroups that are most unlikely to respond and by an active recruitment strategy using telephone interviews.

  • 8. Trask, Catherine
    et al.
    Mathiassen, Svend Erik
    Jackson, Jennie
    Wahlström, Jens
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
    Data processing costs for three posture assessment methods2013In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 13, article id 124Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Data processing contributes a non-trivial proportion to total research costs, but documentation of these costs is rare. This paper employed a priori cost tracking for three posture assessment methods (self-report, observation of video, and inclinometry), developed a model describing the fixed and variable cost components, and simulated additional study scenarios to demonstrate the utility of the model.

    METHODS: Trunk and shoulder postures of aircraft baggage handlers were assessed for 80 working days using all three methods. A model was developed to estimate data processing phase costs, including fixed and variable components related to study planning and administration, custom software development, training of analysts, and processing time.

    RESULTS: Observation of video was the most costly data processing method with total cost of € 30,630, and was 1.2-fold more costly than inclinometry (€ 26,255), and 2.5-fold more costly than self-reported data (€ 12,491). Simulated scenarios showed altering design strategy could substantially impact processing costs. This was shown for both fixed parameters, such as software development and training costs, and variable parameters, such as the number of work-shift files processed, as well as the sampling frequency for video observation. When data collection and data processing costs were combined, the cost difference between video and inclinometer methods was reduced to 7%; simulated data showed this difference could be diminished and, even, reversed at larger study sample sizes. Self-report remained substantially less costly under all design strategies, but produced alternate exposure metrics.

    CONCLUSIONS: These findings build on the previously published data collection phase cost model by reporting costs for post-collection data processing of the same data set. Together, these models permit empirically based study planning and identification of cost-efficient study designs.

  • 9.
    Trask, Catherine
    et al.
    Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden.
    Mathiassen, Svend Erik
    Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden.
    Wahlström, Jens
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
    Heiden, Marina
    Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden.
    Rezagholi, Mahmoud
    Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden.
    Data collection costs in industrial environments for three occupational posture exposure assessment methods2012In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 12, no 1, p. 89-Article in journal (Refereed)
    Abstract [en]

    Background: Documentation of posture measurement costs is rare and cost models that do exist are generally nave. This paper provides a comprehensive cost model for biomechanical exposure assessment in occupational studies, documents the monetary costs of three exposure assessment methods for different stakeholders in data collection, and uses simulations to evaluate the relative importance of cost components. Methods: Trunk and shoulder posture variables were assessed for 27 aircraft baggage handlers for 3 full shifts each using three methods typical to ergonomic studies: self-report via questionnaire, observation via video film, and full-shift inclinometer registration. The cost model accounted for expenses related to meetings to plan the study, administration, recruitment, equipment, training of data collectors, travel, and onsite data collection. Sensitivity analyses were conducted using simulated study parameters and cost components to investigate the impact on total study cost. Results: Inclinometry was the most expensive method (with a total study cost of (sic) 66,657), followed by observation ((sic) 55,369) and then self report ((sic) 36,865). The majority of costs (90%) were borne by researchers. Study design parameters such as sample size, measurement scheduling and spacing, concurrent measurements, location and travel, and equipment acquisition were shown to have wide-ranging impacts on costs. Conclusions: This study provided a general cost modeling approach that can facilitate decision making and planning of data collection in future studies, as well as investigation into cost efficiency and cost efficient study design. Empirical cost data from a large field study demonstrated the usefulness of the proposed models.

  • 10.
    Waller, Göran
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Thalén, Peder
    Department for Cultural Studies, Religious Studies and Educational Sciences, University of Gävle, Gävle, Sweden.
    Janlert, Urban
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Hamberg, Katarina
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Forssén, Annika
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    A cross-sectional and semantic investigation of self-rated health in the northern Sweden MONICA-study2012In: BMC Medical Research Methodology, ISSN 1471-2288, E-ISSN 1471-2288, Vol. 12, article id 154Article in journal (Refereed)
    Abstract [en]

    Background: Self-Rated Health (SRH) correlates with risk of illness and death. But how are different questions of SRH to be interpreted? Does it matter whether one asks: “How would you assess your general state of health?”(General SRH) or “How would you assess your general state of health compared to persons of your own age?”(Comparative SRH)? Does the context in a questionnaire affect the answers? The aim of this paper is to examine the meaning of two questions on self-rated health, the statistical distribution of the answers, and whether the context of the question in a questionnaire affects the answers.

    Methods: Statistical and semantic methodologies were used to analyse the answers of two different SRH questions in a cross-sectional survey, the MONICA-project of northern Sweden.

    Results: The answers from 3504 persons were analysed. The statistical distributions of answers differed. The most common answer to the General SRH was “good”, while the most common answer to the Comparative SRH was “similar”. The semantic analysis showed that what is assessed in SRH is not health in a medical and lexical sense but fields of association connected to health, for example health behaviour, functional ability, youth, looks, way of life. The meaning and function of the two questions differ – mainly due to the comparing reference in Comparative SRH. The context in the questionnaire may have affected the statistics.

    Conclusions: Health is primarily assessed in terms of its sense-relations (associations) and Comparative SRH and General SRH contain different information on SRH. Comparative SRH is semantically more distinct. The context of the questions in a questionnaire may affect the way self-rated health questions are answered. Comparative SRH should not be eliminated from use in questionnaires. Its usefulness in clinical encounters should be investigated.

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