scholarly journals Cohort Profile: The China Multi-Ethnic Cohort (CMEC) Study

2020 ◽  
Author(s):  
Xing Zhao ◽  
Feng Hong ◽  
Jianzhong Yin ◽  
Wenge Tang ◽  
Gang Zhang ◽  
...  
Keyword(s):  
Clinical Laboratory ◽  
Disease Incidence ◽  
Data Access ◽  
Population Based ◽  
Baseline Survey ◽  
Individual Level ◽  
Long Term Storage ◽  
Level Data ◽  
The Individual ◽  
Study Participants

AbstractCohort purposeThe China Multi-Ethnic Cohort (CMEC) is a community population-based prospective observational study aiming to address the urgent need for understanding NCD prevalence, risk factors and associated conditions in resource-constrained settings for ethnic minorities in China.Cohort BasicsA total of 99 556 participants aged 30 to 79 years (Tibetan populations include those aged 18 to 30 years) from the Tibetan, Yi, Miao, Bai, Bouyei, and Dong ethnic groups in Southwest China were recruited between May 2018 and September 2019.Follow-up and attritionAll surviving study participants will be invited for re-interviews every 3-5 years with concise questionnaires to review risk exposures and disease incidence. Furthermore, the vital status of study participants will be followed up through linkage with established electronic disease registries annually.Design and MeasuresThe CMEC baseline survey collected data with an electronic questionnaire and face-to-face interviews, medical examinations and clinical laboratory tests. Furthermore, we collected biological specimens, including blood, saliva and stool, for long-term storage. In addition to the individual level data, we also collected regional level data for each investigation site.Collaboration and data accessCollaborations are welcome. Please send specific ideas to corresponding author at: [email protected].

Missing Data in Research on Youth and Family Programs

2021 ◽  
pp. 003329412110268
Author(s):  
Jaime Ballard ◽  
Adeya Richmond ◽  
Suzanne van den Hoogenhof ◽  
Lynne Borden ◽  
Daniel Francis Perkins
Keyword(s):  
Missing Data ◽  
Statistical Methods ◽  
Self Report ◽  
Program Participation ◽  
Multilevel Data ◽  
Individual Level ◽  
Level Data ◽  
Before And After ◽  
Post Test ◽  
The Individual

Background Multilevel data can be missing at the individual level or at a nested level, such as family, classroom, or program site. Increased knowledge of higher-level missing data is necessary to develop evaluation design and statistical methods to address it. Methods Participants included 9,514 individuals participating in 47 youth and family programs nationwide who completed multiple self-report measures before and after program participation. Data were marked as missing or not missing at the item, scale, and wave levels for both individuals and program sites. Results Site-level missing data represented a substantial portion of missing data, ranging from 0–46% of missing data at pre-test and 35–71% of missing data at post-test. Youth were the most likely to be missing data, although site-level data did not differ by the age of participants served. In this dataset youth had the most surveys to complete, so their missing data could be due to survey fatigue. Conclusions Much of the missing data for individuals can be explained by the site not administering those questions or scales. These results suggest a need for statistical methods that account for site-level missing data, and for research design methods to reduce the prevalence of site-level missing data or reduce its impact. Researchers can generate buy-in with sites during the community collaboration stage, assessing problematic items for revision or removal and need for ongoing site support, particularly at post-test. We recommend that researchers conducting multilevel data report the amount and mechanism of missing data at each level.

scholarly journals How does area-level deprivation depress an individual’s self-rated health and life satisfaction? Evidence from a nationwide population-based survey in Japan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Takashi Oshio ◽  
Hiromi Kimura ◽  
Toshimi Nishizaki ◽  
Takashi Omori
Keyword(s):  
Life Satisfaction ◽  
Health Behavior ◽  
Well Being ◽  
Population Based ◽  
Internet Survey ◽  
Subjective Well Being ◽  
Individual Level ◽  
Self Rated Health ◽  
Level Data ◽  
The Impact

Abstract Background Area-level deprivation is well known to have an adverse impact on mortality, morbidity, or other specific health outcomes. This study examined how area-level deprivation may affect self-rated health (SRH) and life satisfaction (LS), an issue that is largely understudied. Methods We used individual-level data obtained from a nationwide population-based internet survey conducted between 2019 and 2020, as well as municipality-level data obtained from a Japanese government database (N = 12,461 living in 366 municipalities). We developed multilevel regression models to explain an individual’s SRH and LS scores using four alternative measures of municipality-level deprivation, controlling for individual-level deprivation and covariates. We also examined how health behavior and interactions with others mediated the impact of area-level deprivation on SRH and LS. Results Participants in highly deprived municipalities tended to report poorer SRH and lower LS. For example, when living in municipalities falling in the highest tertile of municipality-level deprivation as measured by the z-scoring method, SRH and LS scores worsened by a standard deviation of 0.05 (p < 0.05) when compared with those living in municipalities falling in the lowest tertile of deprivation. In addition, health behavior mediated between 17.6 and 33.1% of the impact of municipality-level deprivation on SRH and LS, depending on model specifications. Conclusion Results showed that area-level deprivation modestly decreased an individual’s general health conditions and subjective well-being, underscoring the need for public health policies to improve area-level socioeconomic conditions.

scholarly journals Predicting the duration of sickness absence spells due to back pain: a population-based study from Sweden

2019 ◽  
Vol 77 (2) ◽  
pp. 115-121
Author(s):  
Annina Ropponen ◽  
Katalin Gémes ◽  
Paolo Frumento ◽  
Gino Almondo ◽  
Matteo Bottai ◽  
...  
Keyword(s):  
Back Pain ◽  
Sickness Absence ◽  
A Priori ◽  
Population Based ◽  
Final Model ◽  
Individual Level ◽  
Discriminatory Accuracy ◽  
C Statistic ◽  
International Statistical Classification ◽  
The Individual

ObjectivesWe aimed to develop and validate a prediction model for the duration of sickness absence (SA) spells due to back pain (International Statistical Classification of Diseases and Related Health Problems 10th Revision: M54), using Swedish nationwide register microdata.MethodsInformation on all new SA spells >14 days from 1 January 2010 to 30 June 2012 and on possible predictors were obtained. The duration of SA was predicted by using piecewise constant hazard models. Nine predictors were selected for the final model based on a priori decision and log-likelihood loss. The final model was estimated in a random sample of 70% of the SA spells and later validated in the remaining 30%.ResultsOverall, 64 048 SA spells due to back pain were identified during the 2.5 years; 74% lasted ≤90 days, and 9% >365 days. The predictors included in the final model were age, sex, geographical region, employment status, multimorbidity, SA extent at the start of the spell, initiation of SA spell in primary healthcare and number of SA days and specialised outpatient healthcare visits from the preceding year. The overall c-statistic (0.547, 95% CI 0.542 to 0.552) suggested a low discriminatory capacity at the individual level. The c-statistic was 0.643 (95% CI 0.634 to 0.652) to predict >90 days spells, 0.686 (95% CI 0.676 to 0.697) to predict >180 spells and 0.753 (95% CI 0.740 to 0.766) to predict >365 days spells.ConclusionsThe model discriminates SA spells >365 days from shorter SA spells with good discriminatory accuracy.

scholarly journals Welsh Government Flying Start Programme Evaluation Using Linked Data

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Sarah Lowe ◽  
Laura McGinn ◽  
Marcos Quintela ◽  
Luke Player ◽  
Karen Tingay
Keyword(s):  
Evidence Base ◽  
Development Project ◽  
Early Years ◽  
Local Authorities ◽  
Parenting Support ◽  
Individual Level ◽  
Level Data ◽  
Part Time ◽  
The Individual ◽  
Families With Children

BackgroundFlying Start (FS) is the Welsh Government’s (WG) flagship Early Years programme for families with children aged less than 4 years of age. Running since 2006, the four entitlements are: Free part-time childcare for 2-3 year olds Enhanced Health Visiting Parenting support Speech, language, and communication support ObjectivesCurrently, while we know which areas in Wales are receiving FS support, individual-level data on which child received what entitlements is not available. Area-level outcomes can be used as proxy indicators but the individual impact of receiving FS support cannot be examined.The project aims to evaluate FS by linking the FS cohort to a range of outcomes including health, education and social care. MethodsA Dataflow Development Project (DDP) has been launched to install SAIL (Secure Anonymised Information Linkage) appliances into 6 pilot Local Authorities in Wales which will test acquiring and linking the individual level FS data from pilot Local Authorities with other datasets in SAIL. FindingsThe project will report some emerging findings from the analysis of pilot data. ImplicationsThere is a growing interest in using linked administrative data to evaluate government initiatives, and mounting enthusiasm in Local Government. If successful, this model is likely to be adopted by related WG programmes; improving the evidence base, facilitating effective evaluation, and adding to the data available for re-use in Wales.

scholarly journals Sickness absence among privately employed white-collar workers: A total population study in Sweden

2020 ◽  
pp. 140349482093427
Author(s):  
Kristin Farrants ◽  
Kristina Alexanderson
Keyword(s):  
Sickness Absence ◽  
Rural Areas ◽  
White Collar ◽  
Sociodemographic Factors ◽  
Population Based ◽  
Small Towns ◽  
Older Individuals ◽  
Individual Level ◽  
White Collar Workers ◽  
The Individual

Background: Knowledge about sickness absence (SA) and disability pension (DP) among privately employed white-collar workers is very limited. Aims: This study aimed to explore SA and DP among privately employed white-collar women and men using different measures of SA to investigate differences by branch of industry, and to analyse the association between sociodemographic factors and SA. Methods: This was a population-based study of all 1,283,516 (47% women) privately employed white-collar workers in Sweden in 2012, using register data linked at the individual level. Several different measures of SA and DP were used. Logistic regression was used to investigate associations of sociodemographic factors with SA. Results: More women than men had SA (10.9% women vs. 4.5% men) and DP (1.8% women vs. 0.6% men). While women had a higher risk of SA than men and had more SA days per employed person, they did not have more SA days per person with SA than men. The risk of SA was higher for women (odds ratio (OR)=2.54 (95% confidence interval (CI) 2.51–2.58)), older individuals (OR age 18–24 years=0.58 (95% CI 0.56–0.60); age 55–64 years OR=1.43 (95% CI 1.40–1.46) compared to age 45–54 years), living in medium-sized towns (OR=1.05 (95% CI 1.03–1.06)) or small towns/rural areas (OR=1.13 (95% CI 1.11–1.15)), with shorter education than college/university (OR compulsory only=1.64 (95% CI 1.59–1.69); OR high school=1.38 (95% CI 1.36–1.40)), born outside the EU25 (OR=1.23 (95% CI 1.20–1.27)) and singles with children at home (OR=1.33 (95% CI 1.30–1.36)). Conclusions: SA and DP among privately employed white-collar workers were lower than in the general population. SA prevalence, length and risk varied by branch of industry, sex and other sociodemographic factors, however, depending on the SA measure used.

Agricultural entrepreneurship orientation: is academic training a missing link?

2017 ◽  
Vol 59 (7/8) ◽  
pp. 856-870 ◽  
Author(s):  
Soodeh Mohammadinezhad ◽  
Maryam Sharifzadeh
Keyword(s):  
Content Type ◽  
Individual Level ◽  
Configuration Theory ◽  
University Courses ◽  
Level Data ◽  
Academic Courses ◽  
The Individual ◽  
Agricultural Entrepreneurship ◽  
Hierarchy Process ◽  
Practical Implications

Purpose The purpose of this paper is to investigate the importance of academic courses on agricultural entrepreneurship. Design/methodology/approach Modified global entrepreneurship and development index (GEDI) was used to determine entrepreneurial dimensions among 19 graduated students of agricultural colleges resided in Iran. Fuzzy analytical hierarchy process was applied to understand agricultural graduates’ preferences on effectiveness of university courses (core, free elective and restricted elective). Findings Results suggested the importance of professional restricted elective courses to provide students with necessary skills. These courses were successful in providing a context for entrepreneurial profile. Research limitations/implications Innate talent or acquired skills were always the place of debate on entrepreneurial development. The paper builds on the premise that entrepreneurs are made through education and continuing reconstruction of experience, further research is required as the field develops in experience and complexity. Practical implications The paper provides strategies to effectively modify practical route in higher education to enhance entrepreneurial orientation among students. Originality/value The paper is innovative at a conceptual level in modifying GEDI elements in individual-level variables based on GEDI configuration theory. This approach is particularly useful in addressing the bottleneck problems of entrepreneurship profile and focusses on the information interpreted at weights of the individual-level data.

On the Issues Surrounding Economic Voting

1987 ◽  
Vol 20 (1) ◽  
pp. 3-33 ◽  
Author(s):  
JOHN R. HIBBING
Keyword(s):  
United States ◽  
United Kingdom ◽  
Voting Behavior ◽  
Economic Voting ◽  
The United States ◽  
Individual Level ◽  
The United Kingdom ◽  
Level Data ◽  
Election Results ◽  
The Individual

This is an analysis of the effects of economic factors on voting behavior in the United Kingdom. Aggregate- and individual-level data are used. When the results are compared to findings generated by the United States case, some intriguing differences appear. To mention just two examples, unemployment and inflation seem to be much more important in the United Kingdom than in the United States, and changes in real per capita income are positively related to election results in the United States and negatively related in the United Kingdom. More generally, while the aggregate results are strong and the individual-level results weak in the United States, in the United Kingdom the situation is practically reversed.

Area-level relative deprivation and alcohol use in Denmark: Is there a relationship?

2018 ◽  
Vol 47 (4) ◽  
pp. 428-438 ◽  
Author(s):  
Kim Bloomfield ◽  
Gabriele Berg-Beckhoff ◽  
Abdu Kedir Seid ◽  
Christiane Stock
Keyword(s):  
Alcohol Use ◽  
Relative Deprivation ◽  
Health Behaviours ◽  
Area Deprivation ◽  
Individual Level ◽  
Level Data ◽  
Housing Component ◽  
Disorder Identification ◽  
The Individual ◽  
The Impact

Aims: Greater area-level relative deprivation has been related to poorer health behaviours, but studies specifically on alcohol use and abuse have been equivocal. The main purpose of the present study was to investigate how area-level relative deprivation in Denmark relates to alcohol use and misuse in the country. Methods: As individual-level data, we used the national alcohol and drug survey of 2011 ( n= 5133). Data were procured from Statistics Denmark to construct an index of relative deprivation at the parish level ( n=2119). The deprivation index has two components, which were divided into quintiles. Multilevel linear and logistic regressions analysed the influence of area deprivation on mean alcohol use and hazardous drinking, as measured by the Alcohol Use Disorder Identification Test. Results: Men who lived in parishes designated as ‘very deprived’ on the socioeconomic component were more likely to consume less alcohol; women who lived in parishes designated as ‘deprived’ on the housing component were less likely to drink hazardously. But at the individual level, education was positively related to mean alcohol consumption, and higher individual income was positively related to mean consumption for women. Higher-educated men were more likely to drink hazardously. Conclusions: Area-level measures of relative deprivation were not strongly related to alcohol use, yet in the same models individual-level socioeconomic variables had a more noticeable influence. This suggests that in a stronger welfare state, the impact of area-level relative deprivation may not be as great. Further work is needed to develop more sensitive measures of relative deprivation.

scholarly journals Fair data for next-generation management of multiple sclerosis

2017 ◽  
Vol 24 (9) ◽  
pp. 1151-1156 ◽  
Author(s):  
Liesbet M Peeters
Keyword(s):  
Multiple Sclerosis ◽  
Multidisciplinary Treatment ◽  
Treatment Strategies ◽  
Population Based ◽  
Disease Modifying Drugs ◽  
Disease Epidemiology ◽  
Individual Level ◽  
Precision Level ◽  
The Central Nervous System ◽  
The Individual

Multiple sclerosis (MS) is a progressive demyelinating and degenerative disease of the central nervous system with symptoms depending on the disease type and the site of lesions and is featured by heterogeneity of clinical expressions and responses to treatment strategies. An individualized clinical follow-up and multidisciplinary treatment is required. Transforming the population-based management of today into an individualized, personalized and precision-level management is a major goal in research. Indeed, a complex and unique interplay between genetic background and environmental exposure in each case likely determines clinical heterogeneity. To reach insights at the individual level, extensive amount of data are required. Many databases have been developed over the last few decades, but access to them is limited, and data are acquired in different ways and differences in definitions and indexing and software platforms preclude direct integration. Most existing (inter)national registers and IT platforms are strictly observational or focus on disease epidemiology or access to new disease modifying drugs. Here, a method to revolutionize management of MS to a personalized, individualized and precision level is outlined. The key to achieve this next level is FAIR data.

Partisanship, Militarized International Conflict, and Electoral Support for the Incumbent

2017 ◽  
Vol 71 (1) ◽  
pp. 172-183 ◽  
Author(s):  
Shane P. Singh ◽  
Jaroslav Tir
Keyword(s):  
Political Behavior ◽  
Comparative Politics ◽  
International Conflict ◽  
Vote Choice ◽  
Individual Level ◽  
Interstate Disputes ◽  
Electoral Support ◽  
Level Data ◽  
The Individual ◽  
Militarized Interstate Disputes

Comparative politics scholarship often neglects to consider how militarized interstate disputes (MIDs) shape political behavior. In this project, we advance an argument that considers voter responses to international conflict at the individual level. In particular, we consider how the well-known conditioning effects of partisanship manifest in relation to militarized international conflict. Examining individual- and macro-level data across ninety-seven elections in forty-two countries over the 1996–2011 period, we find consistent evidence of militarized conflict impacting vote choice. This relationship is, however, moderated by partisanship, conflict side (initiator or target), and conflict hostility level. Among non-copartisan voters, the incumbent benefits the most electorally from initiating low-hostility MIDs or when the country is a target of a high-hostility MID; the opposite scenarios (initiator of a high-hostility MID or target of a low-hostility MID) lead to punishment among this voter group. Copartisans, meanwhile, tend to either maintain or intensify their support in most scenarios we examine; when a country is targeted in a low-hostility MID, copartisan support erodes mildly.

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