The difference-in-difference method: assessing the selection bias in the effects of neighborhood environment on health

Moving to greener pastures: Health selection into neighborhood green space among a highly mobile and diverse population in California

Global urbanization has sparked substantial environmental, public health, and social science research on the importance of conserving and propagating natural environments. A large subset of this work focuses on the benefits of green space for health. An often-overlooked methodological concern when examining relations between green space and health, however, involves residential self-selection. The selective movement of individuals into greener neighborhoods on the basis of preexisting health and correlated social factors may bias associations, particularly in cross-sectional studies, which predominate existing green space/health research. To quantify the extent of residential self-selection bias, this study used a longitudinal sibling comparison design with repeated individual and neighborhood measures to estimate associations between pre-move health factors, including maternal body mass index (BMI) and infant birthweight, and post-move neighborhood green space in a residentially mobile sample of mothers in California, 2007 to 2015 (n = 288,333). Results show that better health before moving predicted higher levels of neighborhood green space after moving, providing evidence of health selection. Findings also indicate some support for differential health selection into neighborhood green space by race/ethnicity, including that evidence of selection emerges for white and Hispanic, but not Black, mothers. However, weak relations between pre-move individual factors and post-move neighborhood green space across analyses suggest that potential bias due to residential self-selection appears relatively minimal in a large, diverse, and highly mobile sample of families in California. Findings support calls to increase green space in historically marginalized neighborhoods as a means to promote environmental and health equity.

Impact Assessment of Seed Village Programme by Using Difference in Difference (DiD) Approach in Telangana, India

Seed village programmes are becoming popular in developing countries due to their potential to supply of affordable seed to farmers in a timely manner. Under the programme, the profitability of seed growing farmers is important as it incentivizes them to grow more seed for distribution of seed to other farmers. This paper tried to analyze the impact of the seed village programme on profitability of seed growing farmers of paddy crop by using Difference-in-Difference approach. The study was conducted during the year 2020 in India. A significant increase in profitability of seed growing farmers compared to non-seed farmers was noticed due to the SVP scheme. It was observed that after the introduction of SVP, there was about 69.01% increase in profits of seed-farmers compared to only 5.63% among non-seed-farmers. Age, education, acreage under seed production and farming experience contributed 71.6% of the total variation in the higher profits through SVP in paddy crop, leaving the rest to extraneous factors. The difference-in-difference regression results showed that, with the introduction of the SVP in India, there was an increase in the profits of seed growing farmers by INR 13,032/acre (186 USD). These results show that most of the seed growing farmers are in favor of the growing seed under SVP and benefited from this programme.

Age-Friendly Communities and Older Adults’ Health in the United States

As age-friendly community (AFC) initiatives grow, it will be essential to determine whether older adults who live in an AFC have better health than those who live in other environments. This study uses data from the 2017 AARP AFC Surveys and the AARP Livability Index to assess whether AFCs promote the health of older adults. We analyze data for 3027 adults aged 65 and older who reside in 262 zip code areas. Following AARP guidelines, we allocated the sample into two groups: an AFC group (livability score of 51+; n = 2364) and a non-AFC (score ≤ 50, n = 663). The outcome variable was self-rated health (M = 3.5; SD = 1.1; range: 1–5). We used an inverse probability weighting approach to evaluate whether older adults who live in an AFC reported better self-rated health than those who live in a non-AFC. Findings showed that older adults who lived in an AFC had better self-rated health than those in a non-AFC (b = 0.08, p = 0.027). Compared to non-Hispanic Whites, Black and Hispanic older adults reported worse self-rated health. Inasmuch as living in an AFC can promote the well-being of older adults, policymakers and practitioners should continue to develop and sustain high-quality, accessible built and social environments.

Impact of Statewide Mandatory Medicaid Managed Care (SMMC) Programs on Hospital Obstetric Outcomes

The state of Florida implemented mandatory managed care for Medicaid enrollees via the Statewide Medicaid Managed Care (SMMC) program in April of 2014. The objective of this study was to examine the impact of the implementation of the SMMC program on the access to care and quality of maternal care for Medicaid enrollees, as measured by several hospital obstetric outcomes. The primary data source for this retrospective observational study was the Hospital Cost and Utilization Project (HCUP) all-payer State ED (SED) visit and State Inpatient Databases (SIDs) from 2010 to 2017. The primary health outcomes for obstetric care were primary cesarean, preterm birth, postpartum preventable ED visits, postpartum preventable readmissions, and vaginal delivery after cesarean (VBAC) rates. Using difference-in-differences (DID) estimation, selected health outcomes were examined for Florida residents with Medicaid beneficiaries (treatment) and the commercially insured population (comparison), before and after the implementation of SMMC. Improvement in disparities for racial/ethnic minority Medicaid enrollees was estimated relative to whites, compared to the relative change among commercially insured patients. From the DID estimation, the findings showed that SMMC is statistically significantly associated with a higher reduction in primary cesarean rates, preterm births, preventable postpartum ED visits, and readmissions among Medicaid beneficiaries relative to their commercially insured counterparts. However, this study did not find any significant reduction in racial/ethnic disparities in obstetric outcomes. In general, this study highlights the impact of SMMC implementation on obstetric outcomes in Florida and provides important insights and potential scope for improvement in obstetric care quality and associated racial/ethnic disparities.

The Asian Games, air pollution and birth outcomes in South China: An instrumental variable approach

We estimate the effects of air-pollution exposure on low birthweight, birthweight, and prematurity risk in South China, for all expectant mothers and by maternal age group and child sex. We do so by exploiting exogenous improvement in air quality during the 2010 Guangzhou Asian Games, when strict regulations were mandated to assure better air quality. We use daily air-pollution levels collected from monitoring stations in Guangzhou, the Asian Games host city, and Shenzhen, a nearby control city, between 2009 and 2011. We first show that air quality during the Asian Games significantly improved in Guangzhou, relative to Shenzhen. Next, using birth-certificate data for both cities for 2009-2011 and using expected pregnancy overlap with the Asian Games as an instrumental variable, we study the effects of three pollutants (PM₁₀, SO₂, and NO₂) on birth outcomes. Four main conclusions emerge: 1) air pollutants significantly reduce average birthweight and increase preterm risk; 2) for birthweight, late pregnancy is most sensitive to PM₁₀ exposure, but there is not consistent evidence of a sensitive period for other pollutants and outcomes; 3) for birthweight, babies of mothers who are at least 35 years old show more vulnerability to all three air pollutants; and 4) male babies show more vulnerability than female babies to PM₁₀ and SO₂, but birthweights of female babies are more sensitive than those of male babies to NO₂.

Evaluation of the Implementation Effect of the Ecological Compensation Policy in the Poyang Lake River Basin Based on Difference-in-Difference Method

Watershed environments play an important supporting role in sustainable high-quality economic development in China, but they have been deteriorating. In order to solve environmental problems in the Poyang Lake River Basin brought about by economic development, the Jiangxi Provincial Government promulgated relevant river basin protection policies in 2015. However, after several years of this policy, the specific effects of its implementation are a matter of general concern to the government and academic circles. After years of policy implementation, the implementation effect of the watershed ecological compensation policy needs to be evaluated. Based on 4248 observations from the Jiangxi and Hunan Provinces, we adopt the difference-in-difference method to analyze the impact of the ecological compensation policy on the Poyang Lake River Basin. The empirical results show that the ecological compensation policy has a significant effect on water-quality improvement. Water quality in the upstream area is better than that in the downstream area; areas with small administrative areas have a smaller population, which in turn leads to better water quality in the river basin; and the higher the per capita GDP, the worse the water quality. Our results highlight the need for the following policy improvements: ecological priority, customizing measures to local conditions, tracing the main body, and strengthening supervision.

Methods to Address Self-Selection and Reverse Causation in Studies of Neighborhood Environments and Brain Health

Preliminary evidence suggests that neighborhood environments, such as socioeconomic disadvantage, pedestrian and physical activity infrastructure, and availability of neighborhood destinations (e.g., parks), may be associated with late-life cognitive functioning and risk of Alzheimer’s disease and related disorders (ADRD). The supposition is that these neighborhood characteristics are associated with factors such as mental health, environmental exposures, health behaviors, and social determinants of health that in turn promote or diminish cognitive reserve and resilience in later life. However, observed associations may be biased by self-selection or reverse causation, such as when individuals with better cognition move to denser neighborhoods because they prefer many destinations within walking distance of home, or when individuals with deteriorating health choose residences offering health services in neighborhoods in rural or suburban areas (e.g., assisted living). Research on neighborhood environments and ADRD has typically focused on late-life brain health outcomes, which makes it difficult to disentangle true associations from associations that result from reverse causality. In this paper, we review study designs and methods to help reduce bias due to reverse causality and self-selection, while drawing attention to the unique aspects of these approaches when conducting research on neighborhoods and brain aging.

Does the Price Support Policy Drive a Balanced Distribution of Profits in the Chinese Dairy Supply Chain? Implications for Supplier and Consumer Psychology

Evaluating the price policy of raw milk is of great significance to the sustainable development of an industry supply chain. In this context, our study used the multi-period difference-in-difference method to systematically examine the impact of the policy implementation on product price and profit distribution in the supply chain. The results showed the following: (1) the price of raw milk in the implementation area of the price support policy is 13.54% higher than that of the unimplemented area; (2) the effect of price increase in the western region (15.5%) is higher than that in the eastern region (13%), and the central region (10.73%); (3) furthermore, the purchase price guidance policy of raw milk drives price increase or price suppression in the links of the supply chain to promote a balanced distribution of profits among the participants in the chain. These conclusions all have good stability and have reference significance for further improving and adjusting the price support policy of raw milk to realize the sustainable development of the Chinese dairy industry. This will enhance the production confidence of Chinese raw milk producers and improve Chinese consumers' expectations and consumer psychology regarding domestic dairy products.

Disadvantaged neighborhoods, birth weight, and problem behavior in five- and six-year-old pre-school children: Evidence from a cohort born in Amsterdam

RATIONALE

Low birth weight has been found to increase the problem behavior of children. Yet, little attention has been given to adequately account for the impact of the child's neighborhood on this relation. The residential neighborhood is a choice, based on factors that are usually not observed that may also influence birth weight and problem behavior.

OBJECTIVE

Using a model that accounts for such endogeneity of both neighborhood choice and birth weight, we have analyzed behavioral problems in 4210 pre-school children between the ages of 5 and 6, birth weight, and neighborhood status, simultaneously.

METHOD

The data used are from the Amsterdam Born Children and their Development (ABCD) cohort for whom a complete prospective record of birth outcomes, pregnancy, socio-demographic characteristics, and indicators of problem behavior are available. Neighborhood data obtained from Statistics Netherlands are merged with the ABCD data file.

RESULTS

Our results suggest that ignoring endogeneity attenuates the effect of disadvantaged neighborhoods on both birth weight and problem behavior in pre-school children. Living in a disadvantaged neighborhood decreases the birth weight and increases the probability of problem behavior. Accounting for the endogeneity of neighborhood choice increases the estimated impacts (marginal effects: from -10% to -44% for birth weight and from 3% to 11% for problem behavior). Lower birth weight increases the probability of problem behavior, but it is only significant after adjusting for endogeneity. The coefficients of other factors have the expected associations with problem behavior.

CONCLUSIONS

These significant effects of disadvantaged neighborhood on birth weight and problem behavior could inform policies and practices that improve neighborhood development for children born in Amsterdam.

Methods for accounting for neighbourhood self-selection in physical activity and dietary behaviour research: a systematic review

BACKGROUND

Self-selection into residential neighbourhoods is a widely acknowledged, but under-studied problem in research investigating neighbourhood influences on physical activity and diet. Failure to handle neighbourhood self-selection can lead to biased estimates of the association between the neighbourhood environment and behaviour. This means that effects could be over- or under-estimated, both of which have implications for public health policies related to neighbourhood (re)design. Therefore, it is important that methods to deal with neighbourhood self-selection are identified and reviewed. The aim of this review was to assess how neighbourhood self-selection is conceived and accounted for in the literature.

METHODS

Articles from a systematic search undertaken in 2017 were included if they examined associations between neighbourhood environment exposures and adult physical activity or dietary behaviour. Exposures could include any objective measurement of the built (e.g., supermarkets), natural (e.g., parks) or social (e.g., crime) environment. Articles had to explicitly state that a given method was used to account for neighbourhood self-selection. The systematic review was registered with the PROSPERO International Prospective Register of Systematic Reviews (number CRD42018083593) and was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.

RESULTS

Of 31 eligible articles, almost all considered physical activity (30/31); few examined diet (2/31). Methods used to address neighbourhood self-selection varied. Most studies (23/31) accounted for items relating to participants' neighbourhood preferences or reasons for moving to the neighbourhood using multi-variable adjustment in regression models (20/23) or propensity scores (3/23). Of 11 longitudinal studies, three controlled for neighbourhood self-selection as an unmeasured confounder using fixed effects regression.

CONCLUSIONS

Most studies accounted for neighbourhood self-selection by adjusting for measured attributes of neighbourhood preference. However, commonly the impact of adjustment could not be assessed. Future studies using adjustment should provide estimates of associations with and without adjustment for self-selection; consider temporality in the measurement of self-selection variables relative to the timing of the environmental exposure and outcome behaviours; and consider the theoretical plausibility of presumed pathways in cross-sectional research where causal direction is impossible to establish.

Factors influencing high respiratory mortality in coal-mining counties: a repeated cross-sectional study

BACKGROUND

Previous studies have associated elevated mortality risk in central Appalachia with coal-mining activities, but few have explored how different non-coal factors influence the association within each county. Consequently, there is a knowledge gap in identifying effective ways to address health disparities in coal-mining counties. To specifically address this knowledge gap, this study estimated the effect of living in a coal-mining county on non-malignant respiratory diseases (NMRD) mortality, and defined this as "coal-county effect." We also investigated what factors may accentuate or attenuate the coal-county effect.

METHODS

An ecological epidemiology protocol was designed to observe the characteristics of three populations and to identify the effects of coal-mining on community health. Records for seven coal-mining counties (n = 19,692) were obtained with approvals from the Virginia Department of Health Office of Vital Statistics for the years 2005 to 2012. Also requested were records from three adjacent coal counties (n = 10,425) to provide a geographic comparison. For a baseline comparison, records were requested for eleven tobacco-producing counties (n = 27,800). We analyzed the association of 57,917 individual mortality records in Virginia with coal-mining county residency, county-level socioeconomic status, health access, behavioral risk factors, and coal production. The development of a two-level hierarchical model allowed the coal-county effect to vary by county-level characteristics. Wald tests detected sets of significant factors explaining the variation of impacts across counties. Furthermore, to illustrate how the model estimations help explain health disparities, two coal-mining county case studies were presented.

RESULTS

The main result revealed that coal-mining county residency increased the probability of dying from NMRD. The coal-county effect was accentuated by surface coal mining, high smoking rates, decreasing health insurance coverage, and a shortage of doctors. In Virginia coal-mining regions, the average coal-county effect increased by 147% (p-value< 0.01) when one doctor per 1000 left, and the effect increased by 68% (p-value< 0.01) with a 1% reduction of health insurance rates, holding other factors fixed.

CONCLUSIONS

This study showed a high mortality risk of NMRD associated with residents living in Virginia coal-mining counties. Our results also revealed the critical role of health access in reducing health disparities related to coal exposure.

Associations of multidimensional socioeconomic and built environment factors with body mass index trajectories among youth in geographically heterogeneous communities

Understanding contextual influences on obesity requires comparison of heterogeneous communities and concurrent assessment of multiple contextual domains. We used a theoretically-based measurement model to assess multidimensional socioeconomic and built environment factors theorized to influence childhood obesity across a diverse geography ranging from rural to urban. Confirmatory factor analysis specified four factors-community socioeconomic deprivation (CSED), food outlet abundance (FOOD), fitness and recreational assets (FIT), and utilitarian physical activity favorability (UTIL)-which were assigned to communities (townships, boroughs, city census tracts) in 37 Pennsylvania counties. Using electronic health records from 2001 to 2012 from 163,820 youth aged 3-18 years from 1288 communities, we conducted multilevel linear regression analyses with factor quartiles and their cross products with age, age2, and age3 to test whether community factors impacted body mass index (BMI) growth trajectories. Models controlled for sex, age, race/ethnicity, and Medical Assistance. Factor scores were lowest in townships, indicating less deprivation, fewer food and physical activity outlets, and lower utilitarian physical activity favorability. BMI at average age was lower in townships versus boroughs (beta [SE]) (0.217 [0.027], P < 0.001) and cities (0.378 [0.036], P < 0.001), as was BMI growth over time. Factor distributions across community types lacked overlap, requiring stratified analyses to avoid extrapolation. In townships, FOOD, UTIL, and FIT were inversely associated with BMI trajectories. Across community types, youth in the lowest (versus higher) CSED quartiles had lower BMI at average age and slower BMI growth, signifying the importance of community deprivation to the obesogenicity of environments.

Neighborhood Environment and Disparities in Health Care Access Among Urban Medicare Beneficiaries With Diabetes: A Retrospective Cohort Study

Older adults' health is sensitive to variations in neighborhood environment, yet few studies have examined how neighborhood factors influence their health care access. This study examined whether neighborhood environmental factors help to explain racial and socioeconomic disparities in health care access and outcomes among urban older adults with diabetes. Data from 123 233 diabetic Medicare beneficiaries aged 65 years and older in New York City were geocoded to measures of neighborhood walkability, public transit access, and primary care supply. In 2008, 6.4% had no office-based "evaluation and management" (E&M) visits. Multilevel logistic regression indicated that this group had greater odds of preventable hospitalization in 2009 (odds ratio = 1.31; 95% confidence interval: 1.22-1.40). Nonwhites and low-income individuals had greater odds of a lapse in E&M visits and of preventable hospitalization. Neighborhood factors did not help to explain these disparities. Further research is needed on the mechanisms underlying these disparities and older adults' ability to navigate health care. Even in an insured population living in a provider-dense city, targeted interventions may be needed to overcome barriers to chronic illness care for older adults in the community.

Relationships between the neighborhood environment and depression in older adults: a systematic review and meta-analysis

ABSTRACTBackground:While depression is a growing public health issue, the percentage of individuals with depression receiving treatment is low. Physical and social attributes of the neighborhood may influence the level of depressive symptoms and the prevalence of depression in older adults.

METHODS

This review systematically examined the literature on neighborhood environmental correlates of depression in older adults. Findings were analyzed according to three depression outcomes: depressive symptoms, possible depression, and clinical depression. Based on their description in the article, environmental variables were assigned to one of 25 categories. The strength of evidence was statistically quantified using a meta-analytical approach with articles weighted for sample size and study quality. Findings were summarized by the number of positive, negative, and statistically non-significant associations by each combination of environmental attribute - depression outcome and by combining all depression outcomes.

RESULTS

Seventy-three articles met the selection criteria. For all depression outcomes combined, 12 of the 25 environmental attribute categories were considered to be sufficiently studied. Three of these, neighborhood socio-economic status, collective efficacy, and personal/crime-related safety were negatively associated with all depression outcomes combined. Moderating effects on associations were sparsely investigated, with 52 articles not examining any. Attributes of the physical neighborhood environment have been understudied.

CONCLUSION

This review provides support for the potential influence of some neighborhood attributes on population levels of depression. However, further research is needed to adequately examine physical attributes associated with depression and moderators of both social and physical neighborhood environment attribute - depression outcome associations.

Mechanisms Linking Neighborhood Age Composition to Health

Purpose of the Study

Age integration theory posits that the age composition of spaces affects the social interactions in which people can engage. This study aimed to examine whether social interactions perceived to involve generativity (i.e., commitment to younger generations), daily discrimination, and/or social cohesion mediate associations between neighborhood age composition, self-reported health, and psychological well-being.

Design and Methods

We applied multilevel structural equation models to data from 4,017 participants aged 30-84 who participated in the 2004-2006 wave of National Survey of Midlife Development in the United States, merged with data on their 3,714 neighborhoods from the 2010U.S. Census.

Results

Neighborhoods that represented the age distribution of the United States and neighborhoods that overrepresented older adults were contexts in which residents reported the most generativity and social cohesion. In turn, generativity and social cohesion were associated with better self-reported health and higher psychological well-being.

Implications

The nature of social interaction links neighborhood age composition to health and well-being. These results clarify the results of prior studies, advance measurement, suggest elaborations to age integration theory, and point to new directions for aging-in-place initiatives.

Health selection into neighborhoods among patients enrolled in a clinical trial

Health selection into neighborhoods may contribute to geographic health disparities. We demonstrate the potential for clinical trial data to help clarify the causal role of health on locational attainment. We used data from the 20-year United Kingdom Prospective Diabetes Study (UKPDS) to explore whether random assignment to intensive blood-glucose control therapy, which improved long-term health outcomes after median 10 years follow-up, subsequently affected what neighborhoods patients lived in. We extracted postcode-level deprivation indices for the 2710 surviving participants of UKPDS living in England at study end in 1996/1997. We observed small neighborhood advantages in the intensive versus conventional therapy group, although these differences were not statistically significant. This analysis failed to show conclusive evidence of health selection into neighborhoods, but data suggest the hypothesis may be worthy of exploration in other clinical trials or in a meta-analysis.

Migrants, health, and happiness: Evidence that health assessments travel with migrants and predict well-being

Health assessments correlate with health outcomes and subjective well-being. Immigrants offer an opportunity to study persistent social influences on health where the social conditions are not endogenous to individual outcomes. This approach provides a clear direction of causality from social conditions to health, and in a second stage to well-being. Natives and immigrants from across the world residing in 30 European countries are studied using survey data. The paper applies within country analysis using both linear regressions and two stage least squares. Natives' and immigrants' individual characteristics have similar predictive power for health, except Muslim immigrants who experience a sizeable health penalty. Average health reports in the immigrant's birth country have a significant association with the immigrant's current health. Almost a quarter of the birth country health variation is brought by the immigrants, while conditioning on socioeconomic characteristics. There is no evidence of the birth country predictive power declining neither as the immigrant spends more time in the residence country nor over the life course. The second stage estimates indicate that a one standard deviation improvement in health predicts higher happiness by 1.72 point or 0.82 of a standard deviation, more than four times the happiness difference of changing employment status from unemployed to employed. Studying life satisfaction yields similar results. Health improvements predict substantial increases in individual happiness.

Health Selection into Neighborhoods Among Families in the Moving to Opportunity Program

Moving to Opportunity for Fair Housing was a randomized experiment that moved very low-income US families from high-poverty neighborhoods to low-poverty neighborhoods starting in the early 1990s. We modeled report of a child's baseline health problem as a predictor of neighborhood outcomes for households randomly assigned to move from high- to low-poverty neighborhoods. We explored associations between baseline health problems and odds of moving with the program upon randomization (1994-1997), neighborhood poverty rate at follow-up (2002), and total time spent in affluent neighborhoods and duration-weighted poverty. Among 1,550 households randomized to low-poverty neighborhoods, a smaller share of households reporting baseline child health problems (P = 0.004) took up the intervention (38%) than those not reporting a health problem (50%). In weighted and covariate-adjusted models, a child health problem predicted nearly 40% lower odds of complying with the experimental condition (odds ratio = 0.62, 95% confidence interval: 0.42, 0.91; P = 0.015). Among compliers, a baseline child health problem predicted 2.5 percentage points' higher neighborhood poverty at take-up (95% confidence interval: 0.90, 4.07; P = 0.002). We conclude that child health problems in a household prior to randomization predicted lower likelihood of using the program voucher to move to a low-poverty neighborhood within the experiment's low-poverty treatment arm and predicted selection into poorer neighborhoods among experimental compliers. Child morbidity may constrain families attempting to improve their life circumstances.

Health Selection into Neighborhoods Among Families in the Moving to Opportunity Program

Moving to Opportunity for Fair Housing was a randomized experiment that moved very low-income US families from high-poverty neighborhoods to low-poverty neighborhoods starting in the early 1990s. We modeled report of a child's baseline health problem as a predictor of neighborhood outcomes for households randomly assigned to move from high- to low-poverty neighborhoods. We explored associations between baseline health problems and odds of moving with the program upon randomization (1994-1997), neighborhood poverty rate at follow-up (2002), and total time spent in affluent neighborhoods and duration-weighted poverty. Among 1,550 households randomized to low-poverty neighborhoods, a smaller share of households reporting baseline child health problems (P = 0.004) took up the intervention (38%) than those not reporting a health problem (50%). In weighted and covariate-adjusted models, a child health problem predicted nearly 40% lower odds of complying with the experimental condition (odds ratio = 0.62, 95% confidence interval: 0.42, 0.91; P = 0.015). Among compliers, a baseline child health problem predicted 2.5 percentage points' higher neighborhood poverty at take-up (95% confidence interval: 0.90, 4.07; P = 0.002). We conclude that child health problems in a household prior to randomization predicted lower likelihood of using the program voucher to move to a low-poverty neighborhood within the experiment's low-poverty treatment arm and predicted selection into poorer neighborhoods among experimental compliers. Child morbidity may constrain families attempting to improve their life circumstances.

Neighbourhood effects in health behaviours: a test of social causation with repeat-measurement longitudinal data

BACKGROUND

Neighbourhood characteristics have been associated with health behaviours of residents. We used longitudinal data to examine whether neighbourhood characteristics (level of urbanization and socioeconomic status) are related to within-individual variations in health behaviours (alcohol consumption, smoking, exercise and self-interest in health) as people live in different neighbourhoods over time.

METHODS

Participants were from the Young Finns prospective cohort study (N = 3145) with four repeated measurement times (1992, 2001, 2007 and 2011/2012). Neighbourhood socioeconomic status and level of urbanization were measured on the level of municipality and zip code area. Within-individual (i.e. fixed-effect) regression was used to examine whether these associations were observed within individuals who lived in different neighbourhood in different measurement times.

RESULTS

People living in more urban zip code areas were more likely to smoke (b = 0.06; CI = 0.03-0.09) and drink alcohol (b = 0.11; CI = 0.08-0.14), and these associations were replicated in within-individual analysis-supporting social causation. Neighbourhood socioeconomic status and urbanization were associated with higher interest in maintaining personal health (b = 0.05; CI = 0.03-0.08 and b = 0.05; CI = 0.02-0.07, respectively), and these associations were also similar in within-individual analysis. Physical exercise was not associated with neighbourhood characteristics.

CONCLUSIONS

These data lend partial support for the hypothesis that neighbourhood differences influence people's health behaviours.

Neighborhood Self-Selection: The Role of Pre-Move Health Factors on the Built and Socioeconomic Environment

Residential self-selection bias is a concern in studies of neighborhoods and health. This bias results from health behaviors predicting neighborhood choice. To quantify this bias, we examined associations between pre-move health factors (body mass index, walking, and total physical activity) and post-move neighborhood factors (County Sprawl Index, Census tract socioeconomic status (SES)) in the Nurses' Health Study (n = 14,159 moves from 1986-2008). Individuals in the highest quartile of pre-move BMI (BMI > 28.4) compared to the lowest quartile (BMI < 22.5) moved to counties that averaged 2.57 points lower on the sprawl index (95% confidence interval -3.55, -1.59) indicating that individuals moved to less dense counties; however, no associations were observed for pre-move walking nor total physical activity. Individuals with higher pre-move BMI tended to move to Census tracts with lower median income and home values and higher levels of poverty. Analyses examining the change in neighborhood environments after a move demonstrated that healthy pre-move behaviors were associated with moves to worse socioeconomic environments. This type of self-selection would bias results downward, underestimating the true relationship between SES and physical activity. Generally, the magnitudes of associations between pre-move health factors and neighborhood measures were small and indicated that residential self-selection was not a major source of bias in analyses in this population.

Ethnic density and obesity: evidence from fixed-effects models

We use data from the 1980 to 2004 waves of the National Longitudinal Survey of Youth, 1979 Cohort to examine the association between the ethnic density of metropolitan areas and obesity among U.S. blacks and Latinos. Although minority groups' obesity rates tend to be higher in metropolitan areas containing many co-ethnics, controlling for other areal characteristics and unobserved time-constant confounders via fixed-effects models dramatically alters this association. In the fixed-effects models, higher levels of co-ethnic density are inversely associated with black males' obesity risk and unrelated to the obesity risk of black females, Latinas, and Latino males. For most groups, marrying and having children increases the risk of obesity.

Have we progressed in the surgical literature? Thirty-year trends in clinical studies in 3 surgical journals

BACKGROUND

We practice in an era of evidence-based medicine. In 1993, Solomon and McLeod published an article examining study designs in 3 surgical journals from 1980 and 1990.

OBJECTIVE

The purpose of this study was to evaluate subsequent 30-year trends in the quality of selected literature.

DESIGN

All of the articles from Diseases of the Colon & Rectum, Surgery, and the British Journal of Surgery during 2000 and 2010 were classified by study design. Nonclinical studies were substratified by animal/laboratory, surgical technique, editorial/review, or miscellaneous articles. Clinical articles were categorized as case or comparative studies, further categorized by study design, and rated on a 10-point scale to determine strength. We compared interobserver reliability using a random sample.

SETTING

This study was conducted at 3 North American medical centers.

PATIENTS

Patients described in the scope of the literature were included in this study.

MAIN OUTCOME MEASURES

Frequency, type, and strength of study design were measured.

RESULTS

We evaluated 1911 articles (967 clinical; 17% comparative). There was a significant increase in multicenter clinical studies (from 12% to 27%; p < 0.0001) and mean study population (from 326 to 6775; p < 0.05). Studies using administrative data increased from 14% to 43% (p < 0.0001). Case reports decreased from 16% to 7% of all clinical studies (p < 0.001), whereas the percentage of comparative studies increased from 14% to 21% (p = 0.001). The percentage of randomized controlled trials did not increase significantly (8.5% in 2000; 10.0% in 2010; p = 0.44). The mean 10-point score for comparative studies was 6.7 for both years (p = 0.50). There was good interobserver agreement in the classification of studies (κ = 0.70) and moderate agreement in scoring comparative studies (κ = 0.47).

LIMITATIONS

This descriptive study cannot fully account for the reasons behind the identified differences.

CONCLUSIONS

Comparative and multicenter studies, mean study population, and the use of administrative data increased from 2000 to 2010. This suggests that increased use of administrative databases has allowed larger populations of patients from more institutions to be studied and may be more generalizable. Researchers should strive toward improving the level of evidence (see Video, Supplemental Digital Content 1, http://links.lww.com/DCR/A167).

Evaluating causal relationships between urban built environment characteristics and obesity: a methodological review of observational studies

Background

Existing reviews identify numerous studies of the relationship between urban built environment characteristics and obesity. These reviews do not generally distinguish between cross-sectional observational studies using single equation analytical techniques and other studies that may support more robust causal inferences. More advanced analytical techniques, including the use of instrumental variables and regression discontinuity designs, can help mitigate biases that arise from differences in observable and unobservable characteristics between intervention and control groups, and may represent a realistic alternative to scarcely-used randomised experiments. This review sought first to identify, and second to compare the results of analyses from, studies using more advanced analytical techniques or study designs.

Methods

In March 2013, studies of the relationship between urban built environment characteristics and obesity were identified that incorporated (i) more advanced analytical techniques specified in recent UK Medical Research Council guidance on evaluating natural experiments, or (ii) other relevant methodological approaches including randomised experiments, structural equation modelling or fixed effects panel data analysis.

Results

Two randomised experimental studies and twelve observational studies were identified. Within-study comparisons of results, where authors had undertaken at least two analyses using different techniques, indicated that effect sizes were often critically affected by the method employed, and did not support the commonly held view that cross-sectional, single equation analyses systematically overestimate the strength of association.

Conclusions

Overall, the use of more advanced methods of analysis does not appear necessarily to undermine the observed strength of association between urban built environment characteristics and obesity when compared to more commonly-used cross-sectional, single equation analyses. Given observed differences in the results of studies using different techniques, further consideration should be given to how evidence gathered from studies using different analytical approaches is appraised, compared and aggregated in evidence synthesis.

Role of health in predicting moves to poor neighborhoods among Hurricane Katrina survivors

In contrast to a large literature investigating neighborhood effects on health, few studies have examined health as a determinant of neighborhood attainment. However, the sorting of individuals into neighborhoods by health status is a substantively important process for multiple policy sectors. We use prospectively collected data on 569 poor, predominantly African American Hurricane Katrina survivors to examine the extent to which health problems predicted subsequent neighborhood poverty. Our outcome of interest was participants' 2009-2010 census tract poverty rate. Participants were coded as having a health problem at baseline (2003-2004) if they self-reported a diagnosis of asthma, high blood pressure, diabetes, high cholesterol, heart problems, or any other physical health problems not listed, or complained of back pain, migraines, or digestive problems at baseline. Although health problems were not associated with neighborhood poverty at baseline, those with baseline health problems ended up living in higher poverty areas by 2009-2010. Differences persisted after adjustment for personal characteristics, baseline neighborhood poverty, hurricane exposure, and residence in the New Orleans metropolitan area, with baseline health problems predicting a 3.4 percentage point higher neighborhood poverty rate (95% confidence interval: 1.41, 5.47). Results suggest that better health was protective against later neighborhood deprivation in a highly mobile, socially vulnerable population. Researchers should consider reciprocal associations between health and neighborhoods when estimating and interpreting neighborhood effects on health. Understanding whether and how poor health impedes poverty deconcentration efforts may help inform programs and policies designed to help low-income families move to--and stay in--higher opportunity neighborhoods.

Tutorial on health economics and outcomes research in nutrition

As healthcare costs climb around the world, public and private payers alike are demanding evidence of a treatment's value to support approval and reimbursement decisions. Health economics and outcomes research, or HEOR, offers tools to answer questions about a treatment's value, as well as its real-world effects and cost-effectiveness. Given that nutrition interventions have to compete for space in budgets along with biopharmaceutical products and devices, nutrition is now increasingly coming to be evaluated through HEOR. This tutorial introduces the discipline of HEOR and motivates its relevance for nutrition. We first define HEOR and explain its role and relevance in relation to randomized controlled trials. Common HEOR study types--including burden of illness, effectiveness studies, cost-effectiveness analysis, and valuation studies--are presented, with applications to nutrition. Tips for critically reading HEOR studies are provided, along with suggestions on how to use HEOR to improve patient care. Directions for future research are discussed.