ObjectiveTo study the characteristics of large-scale loyalty card data obtained in Finland, and to evaluate their potential and challenges in health research.MethodsWe contacted the holders of a certain loyalty card living in a specific region in Finland via email, and requested their electronic informed consent to obtain their basic background characteristics and grocery expenditure data from 2016 for health research purposes. Non-participation and the characteristics and expenditure of the participants were mainly analysed using summary statistics and figures.ResultsThe data on expenditure came from 14,595 (5.6% of those contacted) consenting loyalty card holders. A total of 68.5% of the participants were women, with an average age of 46 years. Women and residents of Helsinki were more likely to participate. Both young and old participants were underrepresented in the sample. We observed that annual expenditure represented roughly two-thirds of the nationally estimated annual averages. Customers and personnel differed in their characteristics and expenditure, but not so much in their most frequently bought items.ConclusionsLoyalty card data from a major retailer enabled us to reach a large, heterogeneous sample with fewer resources than conventional surveys of the same magnitude. The potential of the data was great because of their size, coverage, objectivity, and long periods of dynamic data collection, which enables timely investigations. The challenges included bias due to non-participation, purchases in other stores, the level of detail in product grouping, and the knowledge gaps in what is being consumed and by whom. Loyalty card data are an underutilised resource in research, and could be used not only in retailers’ activities, but also for societal benefit.

Background To date, the evaluation of diet has mostly been based on questionnaires and diaries that have their limitations in terms of being time and resource intensive, and a tendency toward social desirability. Loyalty card data obtained in retailing provides timely and objective information on diet-related behaviors. In Finland, the market is highly concentrated, which provides a unique opportunity to investigate diet through grocery purchases. Objective The aims of this study were as follows: (1) to investigate and quantify the selection bias in large-scale (n=47,066) loyalty card (LoCard) data and correct the bias by developing weighting schemes and (2) to investigate how the degree of loyalty relates to food purchases. Methods Members of a loyalty card program from a large retailer in Finland were contacted via email and invited to take part in the study, which involved consenting to the release of their grocery purchase data for research purposes. Participants’ sociodemographic background was obtained through a web-based questionnaire and was compared to that of the general Finnish adult population obtained via Statistics Finland. To match the distributions of sociodemographic variables, poststratification weights were constructed by using the raking method. The degree of loyalty was self-estimated on a 5-point rating scale. Results On comparing our study sample with the general Finnish adult population, in our sample, there were more women (65.25%, 30,696/47,045 vs 51.12%, 2,273,139/4,446,869), individuals with higher education (56.91%, 20,684/36,348 vs 32.21%, 1,432,276/4,446,869), and employed individuals (60.53%, 22,086/36,487 vs 52.35%, 2,327,730/4,446,869). Additionally, in our sample, there was underrepresentation of individuals aged under 30 years (14.44%, 6,791/47,045 vs 18.04%, 802,295/4,446,869) and over 70 years (7.94%, 3,735/47,045 vs 18.20%, 809,317/4,446,869), as well as retired individuals (23.51%, 8,578/36,487 vs 31.82%, 1,414,785/4,446,869). Food purchases differed by the degree of loyalty, with higher shares of vegetable, red meat & processed meat, and fat spread purchases in the higher loyalty groups. Conclusions Individuals who consented to the use of their loyalty card data for research purposes tended to diverge from the general Finnish adult population. However, the high volume of data enabled the inclusion of sociodemographically diverse subgroups and successful correction of the differences found in the distributions of sociodemographic variables. In addition, it seems that food purchases differ according to the degree of loyalty, which should be taken into account when researching loyalty card data. Despite the limitations, loyalty card data provide a cost-effective approach to reach large groups of people, including hard-to-reach population subgroups.

There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.

In neonates and infants with critical aortic coarctation, balloon angioplasty is considered for rescue therapy of heart failure. The use of conventional stents is limited because of further vessel growth, the need of redilation, and later surgical removal. However, a novel bioabsorbable magnesium stent (AMS) might overcome such restrictions of vessel stenting in newborns. Presented is the first use of an AMS for acute treatment of a newborn with severely impaired heart function due to a long segment recoarctation after a complex surgical repair. We hypothesize that bioabsorbable stents will dramatically change the treatment of coarctation and recoarctation in newborns. © 2006 Wiley‐Liss, Inc.

Objectives Despite the stable incidence of mental disorders in Finland and Europe, mental health-related occupational disability has been increasing. We unveiled the paths to permanent psychiatric disability, recovery, or death, by analysing sequences of labour market participation. Methods The RETIRE register database includes information regarding all persons (n = 42,170) awarded an ICD-10 psychiatric disability pension between 2010 and 2015 in Finland. We identified clusters of typical paths of pre-retirement labour market history. Controlling for major mental disorders, age, and sex, we evaluated factors associated with returning to work (RTW), or death, over a 5-year follow-up period. Results Only 10.5% of the disabled subjects returned to work within the follow-up. Half of them ended up with a permanent disability pension. Seven distinguishable paths to disability were identified. Subjects in the cluster characterized by steady employment were relatively often females, lost their work ability due to affective disorders, and had the highest rate of returning to work (16.3%). Mortality was highest (9%) among the cluster characterized by long-term unemployment. Distributions of major diagnostic groups, as well as age and sex, differed between clusters. After their adjustment in the analysis of RTW or death, the identified labour market history paths prior to losing work ability remained as important independent prognostic factors for both outcomes. Conclusions The complex retirement process involves identifiable clinical and contextual associating factors. Labour market history patterns associate with varying prognoses after psychiatric retirement. Prolonged unemployment appears as a predictor of relatively poor prognoses, whereas employment indicates the opposite.