The association between individual-level social capital and health: cross-sectional, prospective cohort and fixed-effects models

2015 ◽  
Vol 70 (1) ◽  
pp. 25-30 ◽  
Author(s):  
Takashi Oshio
Keyword(s):  
Social Capital ◽  
Prospective Cohort ◽  
Fixed Effects ◽  
Cross Sectional ◽  
Individual Level ◽  
Fixed Effects Models

Social Capital and Self-Perceived Health in Lone Mothers: A Multilevel Cross-Sectional Study across Europe

2021 ◽  
pp. 0192513X2199416
Author(s):  
Sara Trujillo-Alemán ◽  
Åsa Tjulin ◽  
Glòria Pérez ◽  
Emma Hagqvist
Keyword(s):  
Social Capital ◽  
Family Policy ◽  
Social Activity ◽  
Perceived Health ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Policy Model ◽  
Individual Level ◽  
Country Level ◽  
Lone Mothers

This study aimed to explore the distribution of social capital and its relation to self-perceived health in lone mothers across Europe. Data were drawn from the European Social Survey Round 5. The sample was restricted to women (15–64 years), not cohabiting with a partner, and with children (≤ 18 years) living in the household. Social capital was measured using variables, representing both structural (political engagement, social support, and social activity) and cognitive (generalized trust, institutionalized trust, reciprocity, and a feeling of safety) components. Individual-level measurements: age, educational attainment, employment status, income level, and household economy. Country-level measurements: family policy model and collective social capital. A multilevel analysis was conducted. The results revealed cross-country variance in the level of lone mothers’ social capital. After adjustment for individual-level and country-level measurements, only reciprocity and a feeling of safety were related to good self-perceived health among lone mothers in Europe.

Limitations of Fixed-Effects Models for Panel Data

2019 ◽  
Vol 63 (3) ◽  
pp. 357-369 ◽  
Author(s):  
Terrence D. Hill ◽  
Andrew P. Davis ◽  
J. Micah Roos ◽  
Michael T. French
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Statistical Power ◽  
Unobserved Heterogeneity ◽  
Critical Discussion ◽  
Causal Inferences ◽  
Cross Sectional ◽  
Fixed Effects Models ◽  
Time Invariance ◽  
Type Ii Errors

Although fixed-effects models for panel data are now widely recognized as powerful tools for longitudinal data analysis, the limitations of these models are not well known. We provide a critical discussion of 12 limitations, including a culture of omission, low statistical power, limited external validity, restricted time periods, measurement error, time invariance, undefined variables, unobserved heterogeneity, erroneous causal inferences, imprecise interpretations of coefficients, imprudent comparisons with cross-sectional models, and questionable contributions vis-à-vis previous work. Instead of discouraging the use of fixed-effects models, we encourage more critical applications of this rigorous and promising methodology. The most important deficiencies—Type II errors, biased coefficients and imprecise standard errors, misleading p values, misguided causal claims, and various theoretical concerns—should be weighed against the likely presence of unobserved heterogeneity in other regression models. Ultimately, we must do a better job of communicating the pitfalls of fixed-effects models to our colleagues and students.

scholarly journals Examining the relationship between poverty and length of stay: a repeated cross-sectional study of paediatric hospitalisations in Chile

BMJ Open ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. e034512
Author(s):  
Florencia Borrescio-Higa ◽  
Dominiquo Santistevan
Keyword(s):  
Length Of Stay ◽  
Fixed Effects ◽  
Patient Discharge ◽  
Cross Sectional Study ◽  
Poverty Rate ◽  
Sectional Study ◽  
Cross Sectional ◽  
Discharge Data ◽  
Individual Level ◽  
The Relationship

ObjectiveTo measure poverty-based disparities in inpatient length of stay for paediatric hospitalisations. In particular, this paper examines the relationship between municipality level poverty rates and length of stay, accounting for individual level characteristics.DesignWe use patient discharge data to conduct a repeated cross-sectional study of the totality of paediatric hospitalisations in 15 regions of Chile, in the years 2011, 2013, 2015 and 2017.SettingAll hospital discharges in 15 regions of Chile.Participants1 033 222 discharges for children under the age of 15, between 2011 and 2017.Outcome measuresLength of stay (LOS); LOS by type of insurance and type of hospital; hospitalisation rates; municipality-level average LOS.ResultsWe find that municipality level poverty rates are a significant predictor of LOS, even after controlling for individual and area level characteristics, including type of insurance. Children from municipalities in the poorest quintile have a LOS that is 14% shorter as compared with children from municipalities in the richest quintile. This relationship is stronger for publicly insured children: the decrease in LOS associated with the same poverty change is of 22%.ConclusionsThis paper shows that there is an association between municipality-level poverty rates and length of stay for paediatric hospitalisations in Chile. For the vast majority of the sample, and after controlling for individual level characteristics, an increase in the municipality level poverty rate is associated with a decrease in the length of stay. Further, there is a non-linearity in the relationship, where at the highest poverty rates, poverty and LOS are positively associated. These findings are robust after controlling for type of hospital (public vs private), type of insurance (public vs private), type of diagnosis, as well as year and region fixed effects.

scholarly journals The influence of social capital on self-rated health and depression – The Nord-Trøndelag health study (HUNT)

2009 ◽  
Vol 17 (1) ◽  
Author(s):  
Erik R. Sund ◽  
Stig H. Jørgensen ◽  
Andy Jones ◽  
Steinar Krokstad ◽  
Marit Heggdal
Keyword(s):  
Social Capital ◽  
Health Outcomes ◽  
Health Study ◽  
Cross Sectional ◽  
Individual Level ◽  
Self Rated Health ◽  
Geographical Variations ◽  
Organizational Activity ◽  
Increased Risk ◽  
Ward Level

The article examines the relationship between neighbourhood social capital and two health outcomes: selfrated health and depression. A total of 42,571 individuals aged 30–67 years participated in a cross-sectional total population health study in Nord-Trøndelag in 1995–1997 (HUNT II) and were investigated using multilevel modelling. Aims were, first, to investigate potential area effects after accounting for the characteristics of individuals in the neighbourhoods (N = 155), and, second, to explore the relationships between contextual social capital (the level of trust at the neighbourhood level and the level of local organizational activity) and the two health measures. Models with stepwise inclusion of individual level factors attenuated the ward level variance for both self-rated health (PCV: 41%) and depression (PCV: 43%). The inclusion of the two contextual social capital items attenuated the ward level variance for both self-rated health and depression, however to varying degrees. At the individual level, contextual social capital was associated with both self-rated health and depression. Individuals living in wards with a low level of trust experienced an increased risk of 1.36 (95% CI: 1.13-1.63) for poor self-rated health compared to individuals in wards with a high level of trust. For depression, this effect was even stronger (OR 1.52, 1.23-1.87). The associations with the level of organizational activity were inconsistent and weaker for both health outcomes. It was concluded that geographical variations in self-rated health and depression are largely due to the socioeconomic characteristics of individuals. Nevertheless, contextual social capital, expressed as the level of trust, was found to be associated with depression and self-rated health at individual level.

scholarly journals Reevaluating Agricultural Productivity Gaps with Longitudinal Microdata

2020 ◽  
Author(s):  
Joan Hamory ◽  
Marieke Kleemans ◽  
Nicholas Y Li ◽  
Edward Miguel
Keyword(s):  
Cross Sections ◽  
Low Income ◽  
Urban Areas ◽  
Fixed Effects ◽  
Agricultural Sector ◽  
Low Income Countries ◽  
National Accounts ◽  
Cross Sectional ◽  
Individual Level ◽  
Rural And Urban Areas

Abstract Recent research has pointed to large gaps in labor productivity between the agricultural and non-agricultural sectors in low-income countries, as well as between workers in rural and urban areas. Most estimates are based on national accounts or repeated cross-sections of microsurvey data, and as a result typically struggle to account for individual selection between sectors. This paper uses long-run individual-level panel data from two low-income countries (Indonesia and Kenya) to explore these gaps. Accounting for individual fixed effects leads to much smaller estimated productivity gains from moving into the non-agricultural sector (or urban areas), reducing estimated gaps by roughly 67%–92%. Furthermore, gaps do not emerge up to 5 years after a move between sectors. We evaluate whether these findings imply a re-assessment of the conventional wisdom regarding sectoral gaps, discuss how to reconcile them with existing cross-sectional estimates, and consider implications for the desirability of sectoral reallocation of labor.

The impact of mass-level ideological orientations on immigration policy preferences over time

2018 ◽  
Vol 49 (3) ◽  
pp. 279-291
Author(s):  
Jens Peter Frølund Thomsen ◽  
Arzoo Rafiqi
Keyword(s):  
Immigration Policy ◽  
Political Ideology ◽  
Fixed Effects ◽  
Policy Preferences ◽  
Cross Sectional ◽  
Individual Level ◽  
Level Data ◽  
The Impact ◽  
Mass Level ◽  
Over Time

AbstractThis paper introduces a dynamic perspective on how (personal) political ideology shapes reactions to immigration policies at the mass level. Greater ethnic diversity and growing calls for multiculturalism represent a disproportionately greater challenge to rightists because they value conformity, tradition, and stability more than leftists. Consequently, we hypothesize that the impact of political ideology on opposition to immigration has become stronger over time. Analyses show that: (a) leftists were less opposed to immigration than rightists in both 2002 and 2014, and (b) rightists have become more opposed to immigration in the time between 2002 and 2014, whereas leftists’ reactions remained stable across this period. We tested our motivated reasoning hypothesis in a repeated cross-sectional (fixed effects regression) analysis of individual-level data from 18 countries (N = 55,367). The individual-level data on political ideology and immigration policy preferences is from the European Social Survey data sets fielded in 2002 and 2014.

scholarly journals Not belonging where others do: a cross-sectional analysis of multi-level social capital interactions on health and mental well-being in Wales

2020 ◽  
pp. jech-2020-215188
Author(s):  
Christopher W N Saville
Keyword(s):  
Social Capital ◽  
Spatial Scale ◽  
Positive Association ◽  
Well Being ◽  
Cross Sectional ◽  
Social Good ◽  
Individual Level ◽  
Fine Grained ◽  
Mental Well Being ◽  
The Relationship

BackgroundSocial capital may be a social good in health terms, but it is not necessarily a universal good. Several studies have shown that while there is a positive association between ecological social capital and health in people with high individual-level social capital, this relationship is weaker or even reversed in those with low individual-level social capital. Such studies, however, have used relatively coarse levels of geography for quantifying ecological social capital. The present study looks at this relationship at a more fine-grained spatial scale.MethodsData from the National Survey for Wales (n=27 828, weighted mean age=48.4) were linked to previously published small-area estimates (n=410) of ecological social capital for Wales. Mixed effects models were then used to assess whether the relationship between mental well-being and self-reported health on one hand, and ecological social capital (sense of belonging) on the other, was moderated by individual-level social capital.ResultsThe models found the same moderation of the relationship that has been demonstrated previously: Although ecological social capital is positively associated with health in respondents with high individual-level social capital, the relationship is negative in those with low individual-level social capital.ConclusionThis study replicates this association at a spatial scale orders of magnitude more fine-grained than had been shown previously. Ecological social capital is not an unambiguously positive factor for public health, and may be a risk factor for marginalised people.

scholarly journals Relationship between Prefecture-Level Yield of Not-for-Sale Fruits and Vegetables and Individual-Level Fruit and Vegetable Intake in Japan: A Cross-Sectional Study

Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 4072
Author(s):  
Daisuke Machida
Keyword(s):  
Fixed Effects ◽  
Fruits And Vegetables ◽  
Vegetable Intake ◽  
Cross Sectional Study ◽  
Fruit And Vegetable Intake ◽  
Fruit And Vegetable ◽  
Nutrition Survey ◽  
Related Factors ◽  
Cross Sectional ◽  
Individual Level

This study investigated the relationship between prefecture-level yield of not-for-sale fruits and vegetables and individual-level fruit and vegetable intake in Japan. Data were drawn from the Japanese National Health and Nutrition Survey and National Crop Survey of 2016. Random intercept models were used for the analyses. Individual-level fruit and vegetable intake was used for the dependent variable, and prefecture-level yield of not-for-sale fruits and vegetables was used for the independent variable as a fixed effect. In addition, participants’ characteristics and health-related factors at the individual level were also put into independent variables as fixed effects. The prefectures were used as random intercepts. It was found that prefecture-level yield of not-for-sale fruits and vegetables was significantly related to individual-level fruit and vegetable intake (vegetable: B = 0.390, p < 0.001; fruit: B = 0.268, p = 0.003; fruits and vegetables: B = 0.357, p < 0.001). These relationships were also significant in the gender-specific analysis. Thus, the yield of not-for-sale fruits and vegetables might contribute to the intake of fruits and vegetables in Japan.

scholarly journals A General Panel Model for Unobserved Time Heterogeneity with Application to the Politics of Mass Incarceration

2021 ◽  
pp. 008117502110160
Author(s):  
Scott W. Duxbury
Keyword(s):  
Fixed Effects ◽  
Unobserved Heterogeneity ◽  
Panel Data Analysis ◽  
Time Varying ◽  
Cross Sectional ◽  
Common Trends ◽  
Varying Coefficients ◽  
Panel Model ◽  
Fixed Effects Models ◽  
Time Varying Coefficients

Panel data analysis is common in the social sciences. Fixed effects models are a favorite among sociologists because they control for unobserved heterogeneity (unexplained variation) among cross-sectional units, but estimates are biased when there is unobserved heterogeneity in the underlying time trends. Two-way fixed effects models adjust for unobserved time heterogeneity but are inefficient, cannot include unit-invariant variables, and eliminate common trends: the portion of variance in a time-varying variable that is invariant across cross-sectional units. This article introduces a general panel model that can include unit-invariant variables, corrects for unobserved time heterogeneity, and provides the effect of common trends while also allowing for unobserved unit heterogeneity, time-varying coefficients, and time-invariant variables. One-way and two-way fixed effects models are shown to be restrictive forms of this general model. Other restrictive forms are also derived that offer all the usual advantages of one-way and two-way fixed effects models but account for unobserved time heterogeneity. The author uses the models to examine the increase in state incarceration rates between 1970 and 2015.

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