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Abstract Background Prior studies on longevity often examine predictors in isolation and rely solely on baseline information, limiting our understanding of the most important predictors and their dynamic nature. In this study, we used an innovative regression tree model to explore the common characteristics of those who lived longer than their age and sex peers in 35-years follow-up. We identified different pathways leading to a long life, and examined to how changes in characteristics over 10 years (from 1979 to 1989) affect the findings on longevity predictors. Methods Data was obtained from the “Tampere Longitudinal Study on Ageing” (TamELSA) in Finland. Survey data was collected in 1979 from 1056 participants aged 60–89 years (49.8% men). In 1989, a second survey was conducted among 432 survivors from the 1979 cohort (40.2% men). Dates of death were provided by the Finnish Population Register until 2015. We employed an individual measure of longevity known as the realized probability of dying (RPD), which was calculated based on each participant’s age and sex, utilizing population life tables. RPD is based on a comparison of the survival time of each individual of a specific age and sex with the survival time of his/her peers in the total population. A regression tree analysis was used to examine individual-based longevity with RPD as an outcome. Results This relative measure of longevity (RPD) provided a complex regression tree where the most important characteristics were self-rated health, years of education, history of smoking, and functional ability. We identified several pathways leading to a long life such as individuals with (1) good self-rated health (SRH), short smoking history, and higher education, (2) good SRH, short smoking history, lower education, and excellent mobility, and (3) poor SRH but able to perform less demanding functions, aged 75 or older, willing to do things, and sleeping difficulties. Changes in the characteristics over time did not change the main results. Conclusion The simultaneous examination of a broad range of potential predictors revealed that longevity can be achieved under very different conditions and is achieved by heterogeneous groups of people.

Abstract Background In Europe, mortality rates from noncommunicable diseases (NCDs) among persons 30–69 years of age (“NCD premature mortality rates”) have declined significantly, except in twelve countries of Eastern Europe and Central Asia, namely Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine and Uzbekistan. Data on long-term trends in NCD mortality in these countries are limited. We analyzed NCD premature mortality rates, identified change points in NCD mortality trends and forecasted how likely countries are to achieve the global NCD targets, stratified by gender and NCD type. Methods We used the 1990–2019 Global Burden of Disease database to analyze NCD trends and identified country-specific change points by using piecewise linear regression. We assessed the likelihood of achieving the global targets for reducing NCD premature mortality rates among persons 30–69 years of age from four NCDs: cancers, diabetes, cardiovascular and chronic respiratory diseases. The global NCD targets are 25% reduction in mortality from 2010 to 2025 (WHO 25X25 target) and 33%—from 2015 to 2030 (SDG 3.4.1). We applied the analysis to both genders and four NCDs. Results Only Kazakhstan and Russia are likely to achieve the global NCD targets. For Kazakhstan, WHO 25X25 and SDG 3.4.1 global targets for mortality rates were 494.3 and 374.8 per 100,000 population respectively; the corresponding predicted values (PVs) were 360.6 [CI 260.1–461.1] and 245.1 [CI 113.4–376.8]. For Russia, WHO 25X25 and SDG 3.4.1 global targets were 560.5 and 442.8 per 100,000 population respectively; the corresponding PVs were 427.7 [CI 270.3–585.1] and 311.0 [CI 102.8–519.1]. Achieving NCD global targets is less likely for Kyrgyzstan, while it is unlikely for the rest of countries. Most countries had higher mortality rates and slower progress among men compared with women. The likelihood of achieving overall global NCD targets was mainly explained by reduction in cardiovascular mortality. Conclusions In most Eastern Europe and Central Asia countries, progress towards achieving NCD global targets is slow, or there’s a reverse trend. Further quantitative and qualitative research is needed to understand the underlying reasons. Separate indicators are needed to monitor trends for cancers, diabetes and chronic respiratory diseases.

Introduction & Background Food retailers’ transaction data are increasingly used for research. Unlike many other digital footprints, the representativeness of automatically accumulating food purchase data as such is less biased as food is consumed by all individuals. However, the process of obtaining individual/household level data requires consents from the consumers and, thus, may create selection bias. Objectives & Approach The aim of this work is to describe the recruitment process and participant characteristics in the Finnish LoCard study to evaluate the selection mechanism. The Finnish LoCard study comprises two cohorts collected in 2018 and 2023 with 47,066 and 42,340 participants, respectively, who have consented to release their food purchase data for research. The study collaborates with S group, the leading retailer in Finland with 47% market share. Members from their loyalty card program were invited to consent to their purchase data being used for research and voluntarily respond to a background questionnaire. Relevance to Digital Footprints Our analyses may provide further insights into the selectivity of consumers who are willing to share their purchase data for research purposes. Results For both LoCard cohorts, all loyalty card holders (n~2.3M) were considered. In LoCard I, the invitations were sent to 1.1M primary card holders with confirmed email addresses, of whom 47,066 (3.9%) participated and consented to their purchase data being used for research. In this cohort, women, middle-aged individuals, individuals with higher education, and employed individuals were overrepresented whereas the retired individuals, those with lower education and individuals with children were underrepresented. In the LoCard II, loyalty card holders (n ~2.24M) with an email address were invited. Of these, 852,009 (37.7%) opened the invitation link, and a further 42,340 provided the consent, resulting in response rate of 1.9% from the original population and 4.9% from those reacting to the email invitation. Data on the characteristics of LoCard II participants are not available yet but will be presented in the conference presentation. Conclusions & Implications This work investigates selection mechanisms in the Finnish LoCard study and evaluates the feasibility of reaching underrepresented groups in health studies, such as socioeconomically disadvantaged groups or young men, through a combination of loyalty card program and email invitations.

Introduction Evidence on the effectiveness of prostate cancer screening based on prostate-specific antigen is inconclusive and suggests a questionable balance between benefits and harms due to overdiagnosis, and complications from biopsies and overtreatment. However, diagnostic accuracy studies have shown that detection of clinically insignificant prostate cancer can be reduced by MRI combined with targeted biopsies.The aim of the paper is to describe the analysis of the ProScreen randomised trial to assess the performance of the novel screening algorithm in terms of the primary outcome, prostate cancer mortality and secondary outcomes as intermediate indicators of screening benefits and harms of screening.Methods The trial aims to recruit at least 111 000 men to achieve sufficient statistical power for the primary outcome. Men will be allocated in a 1:3 ratio to the screening and control arms. Interim analysis is planned at 10 years of follow-up, and the final analysis at 15 years. Difference between the trial arms in prostate cancer mortality will be assessed by Gray’s test using intention-to-screen analysis of randomised men. Secondary outcomes will be the incidence of prostate cancer by disease aggressiveness, progression to advanced prostate cancer, death due to any cause and cost-effectiveness of screening.Ethics and dissemination The trial protocol was reviewed by the ethical committee of the Helsinki University Hospital (2910/2017). Results will be disseminated through publications in international peer-reviewed journals and at scientific meetings.Trial registration number NCT03423303

BackgroundLoyalty card data automatically collected by retailers provide an excellent source for evaluating health-related purchase behavior of customers. The data comprise information on every grocery purchase, including expenditures on product groups and the time of purchase for each customer. Such data where customers have an expenditure value for every product group for each time can be formulated as 3D tensorial data. ObjectiveThis study aimed to use the modern tensorial principal component analysis (PCA) method to uncover the characteristics of health-related purchase patterns from loyalty card data. Another aim was to identify card holders with distinct purchase patterns. We also considered the interpretation, advantages, and challenges of tensorial PCA compared with standard PCA. MethodsLoyalty card program members from the largest retailer in Finland were invited to participate in this study. Our LoCard data consist of the purchases of 7251 card holders who consented to the use of their data from the year 2016. The purchases were reclassified into 55 product groups and aggregated across 52 weeks. The data were then analyzed using tensorial PCA, allowing us to effectively reduce the time and product group-wise dimensions simultaneously. The augmentation method was used for selecting the suitable number of principal components for the analysis. ResultsUsing tensorial PCA, we were able to systematically search for typical food purchasing patterns across time and product groups as well as detect different purchasing behaviors across groups of card holders. For example, we identified customers who purchased large amounts of meat products and separated them further into groups based on time profiles, that is, customers whose purchases of meat remained stable, increased, or decreased throughout the year or varied between seasons of the year. ConclusionsUsing tensorial PCA, we can effectively examine customers’ purchasing behavior in more detail than with traditional methods because it can handle time and product group dimensions simultaneously. When interpreting the results, both time and product dimensions must be considered. In further analyses, these time and product groups can be directly associated with additional consumer characteristics such as socioeconomic and demographic predictors of dietary patterns. In addition, they can be linked to external factors that impact grocery purchases such as inflation and unexpected pandemics. This enables us to identify what types of people have specific purchasing patterns, which can help in the development of ways in which consumers can be steered toward making healthier food choices.

Background Childhood exposure to dyslipidemia is associated with adult atherosclerosis, but it is unclear whether the long‐term risk associated with dyslipidemia is attenuated on its resolution by adulthood. We aimed to address this question by examining the links between childhood and adult dyslipidemia on carotid atherosclerotic plaques in adulthood. Methods and Results The Cardiovascular Risk in Young Finns Study is a prospective follow‐up of children that began in 1980. Since then, follow‐up studies have been conducted regularly. In 2001 and 2007, carotid ultrasounds were performed on 2643 participants at the mean age of 36 years to identify carotid plaques and plaque areas. For childhood lipids, we exploited several risk factor measurements to determine the individual cumulative burden for each lipid during childhood. Participants were categorized into the following 4 groups based on their childhood and adult dyslipidemia status: no dyslipidemia (reference), incident, resolved, and persistent. Among individuals with carotid plaque, linear regression models were used to study the association of serum lipids with plaque area. The prevalence of plaque was 3.3% (N=88). In models adjusted for age, sex, and nonlipid cardiovascular risk factors, the relative risk for carotid plaque was 2.34 (95% CI, 0.91–6.00) for incident adult dyslipidemia, 3.00 (95% CI, 1.42–6.34) for dyslipidemia resolved by adulthood, and 5.23 (95% CI, 2.57–10.66) for persistent dyslipidemia. Carotid plaque area correlated with childhood total, low‐density lipoprotein, and non–high‐density lipoprotein cholesterol levels. Conclusions Childhood dyslipidemia, even if resolved by adulthood, is a risk factor for adult carotid plaque. Furthermore, among individuals with carotid plaque, childhood lipids associate with plaque size. These findings highlight the importance of primordial prevention of dyslipidemia in childhood to reduce atherosclerosis development.

Abstract Background Foot-related diabetes complications reduce individual well-being, increase mortality and results in increased healthcare costs. Despite their notable stress on health services, studies examining the foot complication care pathways, especially from the viewpoint of health services, are limited. We aimed to identify the most typical care pathways following an initial foot-related diabetes complication, to characterize the patients on each pathway and calculate the related healthcare costs. Methods The identification of pathways was based on population-wide register-based data including all persons diagnosed with diabetes in Finland from 1964 to 2017. For each patient, initial foot-related complication from 2011–2016 was identified using the ICD-10 codes and related healthcare episodes were followed for two years until the end of 2017 or death. A sequence analysis was conducted on care episodes resulting in groups of typical care pathways, as well as their patient profiles. The costs of pathways resulting from the care episodes were calculated based on the data and the reported national unit costs and analyzed using linear models. Results We identified six groups of typical pathways each comprising mainly single type of care episodes. Three of the groups comprised over 10 000 patients while the remaining groups ranged from a few hundred to a few thousand. Majority of pathways consisted only single care episode. However, among the rest of the care pathways variability in length of care pathways was observed between and within group of pathways. On average, the patients were over 65 years of age and were diagnosed with diabetes for over a decade. The pathways resulted in an annual cost of EUR 13 million. The mean costs were nearly 20-fold higher in the group with the highest costs (EUR 11 917) compared to the group with the lowest costs (EUR 609). Conclusions We identified groups of typical care pathways for diabetic foot and discovered notable heterogeneity in the resource use within the groups. This information is valuable in guiding the development of diabetes care to meet the growing need. Nevertheless, reasons underlying the observed heterogeneity requires further examination. Since foot complications are largely preventable, substantial savings could be achieved using cost-effective technologies and more efficient organization of care.

Background: Workers attending to the essential functions of society have been most affected by COVID-19, but the well-being of workers outside the health care sector has scarcely been documented. We describe well-being profiles of Finnish blue-collar workers in private sector services and changes in their well-being during the COVID-19 pandemic. Methods: Altogether 6345 members of the Service Union United provided cross-sectional pre-COVID data in April-June 2019, and 2702 provided follow-up data on health-related indicators in November 2020. Job industry-specific profiles (retail, hospitality, and property maintenance) and change patterns were analysed. Regression models appropriate for different response types with a random intercept and time component were used. Results: Before COVID-19, the well-being profile − food security, body mass index, alcohol use, smoking, and self-perceived health, and adequacy of income − was worse among service workers than the population average and it varied by industry sector. During the first year of COVID-19 self-perceived health deteriorated (adjusted OR 0.78, 95% confidence interval 0.70-0.87). The proportion of severely food insecure fell from a third to a quarter (OR for improvement 2.66, 95% CI 2.37-2.99). Slight improvements were observed in heavy episodic drinking, smoking, and self-perceived adequacy of income. Employees in property maintenance were the most vulnerable regarding well-being profile and COVID-19-related changes. Conclusions: COVID-19 caused divergent changes, including improved food security and deteriorated self-perceived health. Workers with the lowest socioeconomic position and those facing job uncertainty were the most vulnerable to adverse outcomes. Provision of support to these groups is essential in welfare policy considerations.

Abstract Background Nowadays, various simulation approaches for evaluation and decision making in cancer screening can be found in the literature. This paper presents an overview of approaches used to assess screening programs for breast, lung, colorectal, prostate, and cervical cancers. Our main objectives are to describe methodological approaches and trends for different cancer sites and study populations, and to evaluate quality of cancer screening simulation studies. Methods A systematic literature search was performed in Medline, Web of Science, and Scopus databases. The search time frame was limited to 1999–2018 and 7101 studies were found. Of them, 621 studies met inclusion criteria, and 587 full-texts were retrieved, with 300 of the studies chosen for analysis. Finally, 263 full texts were used in the analysis (37 were excluded during the analysis). A descriptive and trend analysis of models was performed using a checklist created for the study. Results Currently, the most common methodological approaches in modeling cancer screening were individual-level Markov models (34% of the publications) and cohort-level Markov models (41%). The most commonly evaluated cancer types were breast (25%) and colorectal (24%) cancer. Studies on cervical cancer evaluated screening and vaccination (18%) or screening only (13%). Most studies have been conducted for North American (42%) and European (39%) populations. The number of studies with high quality scores increased over time. Conclusions Our findings suggest that future directions for cancer screening modelling include individual-level Markov models complemented by screening trial data, and further effort in model validation and data openness.

Abstract Background Although sociodemographic differences in dietary intake have been widely studied, the up-to-date evidence on the corresponding variations in motives for food selection is limited. We investigated how sociodemographic characteristics and special diets in households are associated with the relative importance of various food motives. Methods Participants were members of the S Group loyalty card program across Finland who consented to release their grocery purchase data to be used for research purposes and responded to a web-based questionnaire in 2018 (LoCard study). Self-reported information on sociodemographic factors (age, gender, marital status, living situation, education, household income), special diets in household and food motives (Food Choice Questionnaire) were utilized in the present analyses (N = 10,795). Age- and gender-adjusted linear models were performed separately for each sociodemographic predictor and motive dimension (derived by factor analysis) outcome. The importance of each sociodemographic predictor was evaluated based on an increase in R 2 value after adding the predictor to the age- and gender-adjusted model. Results Age emerged as a central determinant of food motives with the following strongest associations: young adults emphasized convenience (∆R 2 = 0.09, P

Abstract Vegan diets are gaining popularity, also in families with young children. However, the effects of strict plant‐based diets on metabolism and micronutrient status of children are unknown. We recruited 40 Finnish children with a median age 3.5 years—vegans, vegetarians, or omnivores from same daycare centers—for a cross‐sectional study. They enjoyed nutritionist‐planned vegan or omnivore meals in daycare, and the full diets were analyzed with questionnaires and food records. Detailed analysis of serum metabolomics and biomarkers indicated vitamin A insufficiency and border‐line sufficient vitamin D in all vegan participants. Their serum total, HDL and LDL cholesterol, essential amino acid, and docosahexaenoic n‐3 fatty acid (DHA) levels were markedly low and primary bile acid biosynthesis, and phospholipid balance was distinct from omnivores. Possible combination of low vitamin A and DHA status raise concern for their visual health. Our evidence indicates that (i) vitamin A and D status of vegan children requires special attention; (ii) dietary recommendations for children cannot be extrapolated from adult vegan studies; and (iii) longitudinal studies on infant‐onset vegan diets are warranted.

AbstractBackground Increased left ventricular mass (LVM) predicts cardiovascular events and mortality. The objective of this study was to determine whether early-life exposures to body mass index (BMI) and systolic blood pressure (SPB) affects the left ventricular structure in adulthood.Methods We used longitudinal data from a 31-year follow-up to examine the associations between early-life (between ages 6–18) BMI and SPB on LVM in an adult population (N = 1864, aged 34–49). The burden of early-life BMI and SBP was defined as area under the curve.Results After accounting for contemporary adult determinants of LVM, early-life BMI burden associated significantly with LVM (3.61 g/SD increase in early-life BMI; [1.94 − 5.28], p 25 kg/m2) associated with 4.7% (2.5–6.9%, p 30kg/m2) resulted in a 21% (17.3–32.9%, p

BackgroundEarly childhood education and care (ECEC) centers are ideal venues for food education. As smartphones and tablets are becoming increasingly popular in ECEC centers, technology can be used to deliver such pedagogical content. Evidence suggests that video games can affect fruit and vegetable (FV) consumption among 9- to 12-year-old children, but studies among preschoolers are scarce. ObjectiveThis paper describes the development of the Mole’s Veggie Adventures app and its effectiveness in increasing FV acceptance among Finnish and Polish preschoolers aged 3 to 6 years. MethodsA multiprofessional team created an app to be used in ECEC centers in groups of 3 to 10 children. The app aimed to increase vegetable acceptance, and it was built using elements that support the development of self-regulation and social skills. Altogether, 7 Finnish and 4 Polish ECEC centers participated in the study. Before randomization, parents reported background factors and their children’s willingness to taste different FVs. The ECEC professionals in the intervention arm were instructed to use the app at least once a week during the 3- to 4-week intervention period. The main outcomes in this unblinded, cluster-randomized study were FV acceptance and relative FV acceptance. The first was calculated as a sum variable describing the children’s willingness to taste 25 different FVs, the second as FV acceptance divided by the number of FVs served. We used analysis of covariance to compare the FV acceptance and relative FV acceptance scores between the intervention and control groups at follow-up. ResultsA total of 221 children were included in the analysis. At follow-up, the intervention group (115/221, 52%) had higher FV acceptance scores (baseline adjusted difference of mean 7.22; 95% CI 1.41-13.03) than the control group (106/221, 48%). The intervention effect was parallel for relative FV acceptance scores (baseline adjusted difference of mean 0.28; 95% CI 0.05-0.52). ConclusionsThe Mole’s Veggie Adventures app has the potential to increase FV acceptance among preschoolers and can be a valuable tool in supporting food education in ECEC centers. Furthermore, the app can be feasibly incorporated into preschool routines in countries with different educational environments. Trial RegistrationClinicalTrials.gov NCT05173311; https://tinyurl.com/4vfbh283

Abstract Background Alcohol consumption is a significant cause of disease, death and social harm, and it clusters with smoking tobacco and an unhealthy diet. Using automatically registered retail data for research purposes is a novel approach, which is not subject to underreporting bias. Based on loyalty card data (LoCard) obtained by a major Finnish retailer holding a market share of 47%, we examined alcohol expenditure and their associations with food and tobacco expenditures. Methods The data consisted of 1,527,217 shopping events in 2016 among 13,274 loyalty card holders from southern Finland. A K-means cluster analysis was applied to group the shopping baskets according to their content of alcoholic beverages. The differences in the absolute and relative means of food and tobacco between the clusters were tested by linear mixed models with the loyalty card holder as the random factor. Results By far, the most common basket type contained no alcoholic beverages, followed by baskets containing a small number of beers or ciders. The expenditure on food increased along with the expenditure on alcoholic beverages. The foods most consistently associated with alcohol purchases were sausages, soft drinks and snacks. The expenditure on cigarettes relative to total basket price peaked in the mid-price alcohol baskets. Conclusion Clustering of unhealthy choices occurred on the level of individual shopping events. People who bought many alcoholic beverages did not trim their food budget. Automatically registered purchase data provide valuable insight into the health behaviours of individuals and the population.

Objective Growth-based determination of pubertal onset timing would be cheap and practical. We aimed to determine this timing based on pubertal growth markers. Secondary aims were to estimate the differences in growth between cohorts and identify the role of overweight in onset timing. Design This multicohort study includes data from three Finnish cohorts—the Type 1 Diabetes Prediction and Prevention (DIPP, N = 2,825) Study, the Special Turku Coronary Risk Factor Intervention Project (STRIP, N = 711), and the Boy cohort (N = 66). Children were monitored for growth and Tanner staging (except in DIPP). Methods The growth data were analyzed using a Super-Imposition by Translation And Rotation growth curve model, and pubertal onset analyses were run using a time-to-pubertal onset model. Results The time-to-pubertal onset model used age at peak height velocity (aPHV), peak height velocity (PHV), and overweight status as covariates, with interaction between aPHV and overweight status for girls, and succeeded in determining the onset timing. Cross-validation showed a good agreement (71.0% for girls, 77.0% for boys) between the observed and predicted onset timings. Children in STRIP were taller overall (girls: 1.7 [95% CI: 0.9, 2.5] cm, boys: 1.0 [0.3, 2.2] cm) and had higher PHV values (girls: 0.13 [0.02, 0.25] cm/year, boys: 0.35 [0.21, 0.49] cm/year) than those in DIPP. Boys in the Boy cohort were taller (2.3 [0.3, 4.2] cm) compared with DIPP. Overweight girls showed pubertal onset at 1.0 [0.7, 1.4] year earlier compared with other girls. In boys, there was no such difference. Conclusions The novel modeling approach provides an opportunity to evaluate the Tanner breast/genital stage–based pubertal onset timing in cohort studies including longitudinal data on growth but lacking pubertal follow-up.

Abstract Background Studies investigating dietary resemblance between parents and their children have gained mixed results, and the resemblance seems to vary across nutrients, foods, dietary-assessment tools used, and parent-child pairs. We investigated parent-child dietary resemblance using a novel approach in applying statistical analysis, which allowed the comparison of ‘whole-diet’ between parents and their children. Additionally, we sought to establish whether sociodemographic factors or family meals were associated with dietary resemblance and whether parent-child dietary resemblance was dependent on the parent providing food consumption data on behalf of the child (father or mother, “the respondent”). Methods The DAGIS study investigated health behaviors among Finnish preschoolers using a cross-sectional design. One parent filled in a food frequency questionnaire (FFQ) measuring the child’s food consumption outside preschool hours during the last week. In addition, we instructed both parents or legal guardians, should the child have two, to fill in a similar FFQ regarding their own food use. Parents also reported their educational level, the number of children living in the same household, and the number of family meals. As a measure of dietary resemblance between a parent and a child, we computed Spearman correlations ranging mostly from no resemblance (0) to complete resemblance (+ 1) between parent-child pairs over the ‘whole-diet’ (excluding preschool hours). These resemblance measures were further investigated using linear mixed models. Results We obtained 665 father-child and 798 mother-child resemblance measures. Mother-child resemblance was on average 0.57 and stronger than father-child resemblance (0.50, p

Abstract Background Employment protects and fosters health. Occupational health services, particularly in Finland, have a central role in protecting employee health and preventing work ability problems. However, primary care within occupational health services is currently underused in informing preventive activities. This study was designed to assess whether the recording of work ability problems and improvement of follow-up of work-related primary care visits can reduce sickness absences and work disability pensions after 1 year. Methods/design A pragmatic trial will be conducted using patient electronic registers and registers of the central pensions agency in Finland. Twenty-two occupational health centres will be randomised to intervention and control groups. Intervention units will receive training to improve recording of work ability illnesses in the primary care setting and improved follow-up procedures. The intervention impact will be assessed through examining rates of sickness absence across intervention and control clinics as well as before and after the intervention. Discussion The trial will develop knowledge of the intervention potential of primary care for preventing work disability pensions and sickness absence. The use of routine patient registers and pensions registers to assess the outcomes of a randomised controlled trial will bring forward trial methodology, particularly when using register-based data. If successful, the intervention will improve the quality of occupational health care primary care and contribute to reducing work disability. Trial registration ISRCTN Registry reference number ISRCTN45728263 . Registered on 18 April 2016.

Introduction Finland’s success in achieving the goal of its tobacco endgame largely depends on rectifying deficiencies in the delivery of smoking cessation services. One such weakness, which has not been documented with empirical data, is misuse of nicotine replacement therapy (NRT). This study’s objective was to examine purchase patterns of NRT for estimating improper use of the medication. The study was based on the assumption that duration of a purchase episode is indicative of either proper use or misuse of NRT. Methods The participants (n=728), who purchased at least one NRT product in 2016 (mostly gum/lozenge), were selected through enrollment in a large customer loyalty program in Finland (LoCard). Participants were categorized into one of five groups according to their longest purchase episode of NRT, defined by purchases made in consecutive, 4-week intervals. Results Most participants, who did not adhere to NRT guidelines, either purchased the medication for too short (≤4 weeks, 63.5%) or too long (>24 weeks, 13.2%) of a purchase episode. Median purchases of NRT in the first month of use were one and four in the former and latter, respectively. In contrast to other groups, persistent users (>24 weeks) did not curtail purchases of NRT across several 4-week intervals, suggesting potential for dependence on NRT. Conclusions The observation that most purchase episodes were terminated prematurely is consistent with surveys reporting widespread NRT misuse. Given uncertainty of greater regulation of NRT sales through legislation, it would be prudent for Finnish retailers to promote proper use of the therapy.

Objective To study the characteristics of large-scale loyalty card data obtained in Finland, and to evaluate their potential and challenges in health research. Methods We 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. Results The 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. Conclusions Loyalty 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.

Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.

The importance of lipids for cell function and health has been widely recognized, e.g., a disorder in the lipid composition of cells has been related to atherosclerosis caused cardiovascular disease (CVD). Lipidomics analyses are characterized by large yet not a huge number of mutually correlated variables measured and their associations to outcomes are potentially of a complex nature. Differential network analysis provides a formal statistical method capable of inferential analysis to examine differences in network structures of the lipids under two biological conditions. It also guides us to identify potential relationships requiring further biological investigation. We provide a recipe to conduct permutation test on association scores resulted from partial least square regression with multiple imputed lipidomic data from the LUdwigshafen RIsk and Cardiovascular Health (LURIC) study, particularly paying attention to the left-censored missing values typical for a wide range of data sets in life sciences. Left-censored missing values are low-level concentrations that are known to exist somewhere between zero and a lower limit of quantification. To make full use of the LURIC data with the missing values, we utilize state of the art multiple imputation techniques and propose solutions to the challenges that incomplete data sets bring to differential network analysis. The customized network analysis helps us to understand the complexities of the underlying biological processes by identifying lipids and lipid classes that interact with each other, and by recognizing the most important differentially expressed lipids between two subgroups of coronary artery disease (CAD) patients, the patients that had a fatal CVD event and the ones who remained stable during two year follow-up.

Recently, new nonparametric multivariate extensions of the univariate sign methods have been proposed. Randles (2000) introduced an affine invariant multivariate sign test for the multivariate location problem. Later on, Hettmansperger and Randles (2002) considered an affine equivariant multivariate median corresponding to this test. The new methods have promising efficiency and robustness properties. In this paper, we review these developments and compare them with the classical multivariate analysis of variance model. A new SAS/IML tool for performing a spatial sign based multivariate analysis of variance is introduced.

Abstract Objective: To investigate the association between food insecurity (FI) and diet quality in private sector service workers. Design: Data were collected via electronic questionnaires (2019) and the national register data (2018–2019). FI was measured using Household Food Insecurity Access Scale (HFIAS), and diet quality using a food frequency questionnaire and a modified Healthy Food Intake Index (mHFII). The associations between HFIAS and mHFII were studied using ANOVA and ordinal regression analysis. Setting: Cross-sectional survey and register data for all municipalities in Finland in 2018 - 2019. Participants: Individuals (n=6435) belonging to the Finnish Service Union United (PAM). The members are predominantly women and work mainly in retail trade, tourism, restaurant and leisure services, property maintenance, and security services. Results: Overall diet quality, measured by mHFII, was significantly lower in those experiencing severe FI than in those who were food secure (8.0 vs. 9.1). Additionally, those with severe FI were less likely to have higher (more optimal) scores in sugar-sweetened beverages (OR: 0.67), fibre-rich grains (OR: 0.79), vegetables (OR: 0.54), fruits and berries (OR: 0.61), vegetable oil (OR: 0.80), fish (OR: 0.65), milk (OR: 0.89), and nuts and seeds (OR: 0.66) than food-secure participants. Severe FI was associated with higher odds for less frequent consumption of red and processed meat (OR: 1.15, higher score represents less frequent consumption). Conclusions: Severe FI was linked to both lower overall diet quality and suboptimal consumption of several food groups. Individuals experiencing severe FI may be predisposed to accumulating dietary risk factors for chronic diseases.