scholarly journals Individual-level data sources used for secondary analysis

2017 ◽  
pp. xiii-xiii
Keyword(s):  
Secondary Analysis ◽  
Data Sources ◽  
Individual Level ◽  
Level Data

An Introduction to the OPCS Longitudinal Study

1993 ◽  
Vol 25 (10) ◽  
pp. 1387-1398 ◽  
Author(s):  
A Dale ◽  
R Creeser ◽  
B Dodgeon ◽  
S Gleave ◽  
H Filakti
Keyword(s):  
Longitudinal Study ◽  
Research Area ◽  
Data Sources ◽  
Considerable Importance ◽  
Cancer Registration ◽  
Regional Research ◽  
Migration Studies ◽  
England And Wales ◽  
Individual Level ◽  
Level Data

The Office of Population Censuses and Surveys (OPCS). Longitudinal Study (LS) is introduced, and its value for migration and area-based studies is highlighted. The LS is a 1% sample of records drawn from the 1971, 1981, and 1991 Censuses for England and Wales, to which are linked information on certain vital events (for example, births, deaths, and cancer registration) for the same individuals. The basis for selection is having one of four birthdates in the year. Although confidentiality constraints mean that individual-level data from the LS cannot be released, OPCS welcome analysis of the data, and arrangements for access and user support are described in the paper. Because most of the data sources that go to make up the LS contain some area coding, it is of considerable importance in urban and regional research and in migration studies. Those aspects of the LS of most relevance to this research area are reviewed, and the different geographical bases available are highlighted. Also, examples of the kinds of research that can be supported by the LS are provided.

scholarly journals Partnership Context of First Births in Russia: The Enduring Significance of Marriage

2021 ◽  
Author(s):  
Evgeny M. Andreev ◽  
Elena Churilova ◽  
Aiva Jasilioniene
Keyword(s):  
Empirical Evidence ◽  
Data Sources ◽  
Unique Pattern ◽  
Individual Level ◽  
Average Interval ◽  
Level Data ◽  
Birth Records ◽  
The Stability ◽  
The Relationship ◽  
Historical Periods

AbstractWhile cohabitation and non-marital childbearing have been increasing in Russia since 1990, the share of marital first births that are conceived prior to marriage has changed very little since the Soviet era. The prior findings on the stability of trends in premarital conceptions in Russia have been contradictory and inconclusive. This study aims to extend the existing empirical evidence on premarital conceptions in Russia and to contribute to the discussion on the persistence of marriage as the preferred partnership context for parenthood. We focus on births that occurred within the first two years of marriage, and compare the childbearing patterns of Russian women who married in different historical periods. For our investigation of fertility among marital cohorts who married during the Soviet era (1960–1991), we use individual-level data from the 1994 microcensus. For our examination of fertility among more recent marital cohorts (2000, 2011, and 2016), we draw on data from birth records in civil registers. We also use relevant complementary data sources. Our findings show that there has been a marked shift in the relationship between conception and marriage in Russia. Increasingly, conceptions have been occurring before marriage, and in the most recent marital cohorts, the level of premarital first conceptions has even surpassed the level of marital first conceptions. The average interval between conception and entry into marriage has also been lengthening. We describe this unique pattern of childbearing and discuss some potential explanations for the ongoing association between marriage and childbearing in Russia.

scholarly journals Review of Associations between Built Environment Characteristics and Severe Acute Respiratory Syndrome Coronavirus 2 Infection Risk

2021 ◽  
Vol 18 (14) ◽  
pp. 7561
Author(s):  
Jingjing Wang ◽  
Xueying Wu ◽  
Ruoyu Wang ◽  
Dongsheng He ◽  
Dongying Li ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Built Environment ◽  
Longitudinal Research ◽  
Empirical Studies ◽  
Infection Risk ◽  
Design Guidelines ◽  
Individual Level ◽  
Transit Accessibility ◽  
Level Data ◽  
Transmission Pathways

The coronavirus disease 2019 pandemic has stimulated intensive research interest in its transmission pathways and infection factors, e.g., socioeconomic and demographic characteristics, climatology, baseline health conditions or pre-existing diseases, and government policies. Meanwhile, some empirical studies suggested that built environment attributes may be associated with the transmission mechanism and infection risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, no review has been conducted to explore the effect of built environment characteristics on the infection risk. This research gap prevents government officials and urban planners from creating effective urban design guidelines to contain SARS-CoV-2 infections and face future pandemic challenges. This review summarizes evidence from 25 empirical studies and provides an overview of the effect of built environment on SARS-CoV-2 infection risk. Virus infection risk was positively associated with the density of commercial facilities, roads, and schools and with public transit accessibility, whereas it was negatively associated with the availability of green spaces. This review recommends several directions for future studies, namely using longitudinal research design and individual-level data, considering multilevel factors and extending to diversified geographic areas.

scholarly journals The Role of Snack Choices, Body Weight Stereotypes and Smoking Behavior in Assessing Risk Factors for Adolescent Overweight and Obesity

Foods ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 557
Author(s):  
Elena Raptou
Keyword(s):  
Body Weight ◽  
Smoking Behavior ◽  
Negative Influence ◽  
Overweight And Obesity ◽  
Individual Level ◽  
Level Data ◽  
Prevention Interventions ◽  
Frequent Consumption ◽  
Adolescent Overweight ◽  
Relationship Of

This study investigated the relationship of behavioral factors, such as snack choices, obesity stereotypes and smoking with adolescents’ body weight. Individual-level data for 1254 Greek youths were selected via a formal questionnaire. Snack choices seem to be gender specific with girls showing a stronger preference for healthier snacks. Frequent consumption of high-calorie and more filling snacks was found to increase Body Mass Index (BMI) in both genders. Fruit/vegetable snacks were associated with lower body weight in females, whereas cereal/nut snacks had a negative influence in males’ BMI. The majority of participants expressed anti-fat attitudes and more boys than girls assigned positive attributes to lean peers. The endorsement of the thin-ideal was positively associated with the BMI of both adolescent boys and girls. This study also revealed that neglecting potential endogeneity issues can lead to biased estimates of smoking. Gender may be a crucial moderator of smoking–BMI relationships. Male smokers presented a higher obesity risk, whereas female smokers were more likely to be underweight. Nutrition professionals should pay attention to increase the acceptance of healthy snack options. Gender differences in the influence of weight stereotypes and smoking on BMI should be considered in order to enhance the efficacy of obesity prevention interventions.

When Marriage Gets Hard: Intra-Coalition Conflict and Electoral Accountability

2021 ◽  
pp. 001041402110243
Author(s):  
Carolina Plescia ◽  
Sylvia Kritzinger
Keyword(s):  
Economic Performance ◽  
Political Representation ◽  
Economic Evaluations ◽  
Responsibility Attribution ◽  
Electoral Accountability ◽  
Individual Level ◽  
Coalition Governments ◽  
Level Data ◽  
European Election ◽  
Election Studies

Combining individual-level with event-level data across 25 European countries and three sets of European Election Studies, this study examines the effect of conflict between parties in coalition government on electoral accountability and responsibility attribution. We find that conflict increases punishment for poor economic performance precisely because it helps clarify to voters parties’ actions and responsibilities while in office. The results indicate that under conditions of conflict, the punishment is equal for all coalition partners when they share responsibility for poor economic performance. When there is no conflict within a government, the effect of poor economic evaluations on vote choice is rather low, with slightly more punishment targeted to the prime minister’s party. These findings have important implications for our understanding of electoral accountability and political representation in coalition governments.

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.

The utility of household Grocery Purchase Quality Index scores as an individual diet quality metric

2020 ◽  
pp. 1-28
Author(s):  
Haley Wynne Parker ◽  
Carolina de Araujo ◽  
Anne N. Thorndike ◽  
Maya Vadiveloo
Keyword(s):  
Diet Quality ◽  
Quality Index ◽  
Secondary Analysis ◽  
Weighted Kappa ◽  
Healthy Eating Index ◽  
Bachelor's Degree ◽  
Dietary Recommendations ◽  
Household Level ◽  
Individual Level ◽  
Grocery Purchase

Abstract The validated Grocery Purchase Quality Index (GPQI) reflects concordance between household grocery purchases and US dietary recommendations. However, it is unclear whether GPQI scores calculated from partial purchasing records validly reflect individual-level diet quality. Within the 9-month randomized controlled Smart Cart study examining the effect of targeted coupons on grocery purchase quality (n=209), this secondary analysis examined concordance between the GPQI (range 0-75, scaled to 100) calculated from 3-months of loyalty-card linked partial (≥50%) household grocery purchasing data and individual-level Healthy Eating Index (HEI) scores at baseline and 3-months calculated from food frequency questionnaires. HEI and GPQI concordance was assessed with overall and demographic-stratified partially-adjusted correlations; covariate-adjusted percent score differences, cross-classification, and weighted kappa coefficients assessed concordance across GPQI tertiles (T). Participants were mostly middle-aged (55.4(13.9) years), female (90.3%), from non-smoking households (96.4%), without children (70.7%). Mean GPQI (54.8(9.1)%) scores were lower than HEI scores (baseline: 73.2(9.1)%, 3-months: 72.4(9.4)%), and moderately correlated (baseline r=0.41 vs. 3-month r=0.31, p<0.001). Correlations were stronger among participants with ≤ bachelor’s degree, obesity, and children. Concordance was highest in T3. Participants with high (T3) vs. low (T1) GPQI scores had 7.3-10.6 higher odds of having HEI scores >80% at both timepoints. Weighted kappas (k=0.25) indicated moderate agreement between scores. Household-level GPQI derived from partial grocery purchasing data were moderately correlated with self-reported intake, indicating their promise for evaluating diet quality. Partial purchasing data appears to moderately reflect individual diet quality and may be useful in interventions monitoring changes in diet quality.

An individualized treatment rule to optimize probability of remission by continuation, switching, or combining antidepressant medications after failing a first-line antidepressant in a two-stage randomized trial

2021 ◽  
pp. 1-10
Author(s):  
Ronald C. Kessler ◽  
Toshi A. Furukawa ◽  
Tadashi Kato ◽  
Alex Luedtke ◽  
Maria Petukhova ◽  
...  
Keyword(s):  
Pragmatic Trial ◽  
Secondary Analysis ◽  
Individualized Treatment ◽  
Second Line ◽  
Open Label ◽  
Individual Level ◽  
Ensemble Machine Learning ◽  
Medication Selection ◽  
The Individual ◽  
Optimized Treatment

Abstract Background There is growing interest in using composite individualized treatment rules (ITRs) to guide depression treatment selection, but best approaches for doing this are not widely known. We develop an ITR for depression remission based on secondary analysis of a recently published trial for second-line antidepression medication selection using a cutting-edge ensemble machine learning method. Methods Data come from the SUN(^_^)D trial, an open-label, assessor blinded pragmatic trial of previously-untreated patients with major depressive disorder from 48 clinics in Japan. Initial clinic-level randomization assigned patients to 50 or 100 mg/day sertraline. We focus on the 1549 patients who failed to remit within 3 weeks and were then rerandomized at the individual-level to continuation with sertraline, switching to mirtazapine, or combining mirtazapine with sertraline. The outcome was remission 9 weeks post-baseline. Predictors included socio-demographics, clinical characteristics, baseline symptoms, changes in symptoms between baseline and week 3, and week 3 side effects. Results Optimized treatment was associated with significantly increased cross-validated week 9 remission rates in both samples [5.3% (2.4%), p = 0.016 50 mg/day sample; 5.1% (2.7%), p = 0.031 100 mg/day sample] compared to randomization (30.1–30.8%). Optimization was also associated with significantly increased remission in both samples compared to continuation [24.7% in both: 11.2% (3.8%), p = 0.002 50 mg/day sample; 11.7% (3.9%), p = 0.001 100 mg/day sample]. Non-significant gains were found for optimization compared to switching or combining. Conclusions An ITR can be developed to improve second-line antidepressant selection, but replication in a larger study with more comprehensive baseline predictors might produce stronger and more stable results.

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