Using Longitudinal Surveillance of Unemployment Claims During Public Health Emergencies to Provide Timely and Granular Data on the Social Determinants of Health.

OBJECTIVE: Employment is a well-documented social determinant of physical and mental health and can be used to determine who is disproportionately affected by public health emergencies. We examined trends in unemployment overall and by gender, by race or ethnic group, and by their interaction for 2 public health emergencies (the COVID-19 pandemic and the 2020 California wildfires). METHODS: We obtained summary data files on the number of initial unemployment insurance (IUI) claims made in all 58 California counties from January 2018 through December 2021. We fit fixed-effects Poisson regression models to county data on weekly IUI claims cross-classified by gender and race or ethnic group. We used models to evaluate the overall effect of COVID-19, whether this effect changed over time increasing under compounding emergencies, and whether the overall and compounding effects of COVID-19 differed by gender and race or ethnic group. RESULTS: During the COVID-19 pandemic, weekly IUI claims rates increased to as much as 10 times their prepandemic level. The increase in IUI claims for COVID-19 weeks, compared with weeks from the same month in the 2 years prior, was greater for women than for men of all race or ethnic groups, except for Black women. The higher rates of IUI claims for most women during COVID-19 entailed a reversal of prepandemic gender differences in claims that persisted through 2021. CONCLUSION: Public health officials should consider using IUI claims for surveillance of social determinants of health, particularly in the context of emergencies, which we show can have a persisting effect on the social patterning of social determinants. Future research is needed to forecast these affects and inform public health and policy mitigation and prevention strategies.

Association of the Healthy, Hunger-Free Kids Act of 2010 With Body Mass Trajectories of Children in Low-Income Families.

Importance: Implemented in 2012, the Healthy, Hunger-Free Kids Act of 2010 (HHFKA) increased nutritional requirements of the National School Lunch Program (NSLP) to reverse the potential role of the NSLP in childhood obesity. Objective: To evaluate whether associations between the free or reduced-price NSLP and body mass growth differed after implementation of the HHFKA. Design, Setting, and Participants: This cohort study used data from 2 nationally representative cohorts of US kindergarteners sampled in 1998 to 1999 and 2010 to 2011 and followed up for 6 years, through grade 5, in the Early Childhood Longitudinal Study Kindergarten Class of 1998-1999 (ECLS-K:1999, in 2003-2004) and Kindergarten Class of 2010-2011 (ECLS-K:2011, in 2015-2016). In total, 5958 children were selected for analysis from low-income families eligible for the free or reduced-price NSLP (household income <185% of the federal poverty level) who attended public schools and had no missing data on free or reduced-price NSLP participation or on body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) at kindergarten or grades 1 and 5. Data were analyzed from January 1 to September 7, 2021. Exposures: Cross-cohort comparison of before vs after implementation of the HHFKA for free or reduced-price NSLP participation at kindergarten and grades 1 and 5. Main Outcomes and Measures: Body mass index difference (BMID) from obesity threshold was the difference in BMI units from the age- and sex-specific obesity thresholds (95th percentile) and is sensitive to change at high BMI. Multigroup models by cohort included weights to balance the distribution of the 2 cohorts across a wide range of covariates. A Wald test was used to assess whether associations differed between the cohorts. Results: In the final analysis, 3388 children in ECLS-K:1999 (1696 girls [50.1%]; mean [SD] age at baseline, 74.6 [4.3] months) and 2570 children in ECLS-K:2011 (1348 males [52.5%]; mean [SD] age at baseline, 73.6 [4.2] months) were included. The best fitting model for BMID change by free or reduced-price NSLP participation across the cohorts included fixed and time-varying associations. Before HHFKA implementation, grade 5 free or reduced-price NSLP participants had higher BMID, adjusted for their prior BMID trajectory, than nonparticipants (ß = 0.54; 95% CI, 0.27-0.81). After HHFKA implementation, this association was attenuated (ß = -0.07; 95% CI, -0.58 to 0.45), and grade 5 associations were different across cohorts (χ21 = 4.29, P = .04). Conclusions and Relevance: In this cohort study using cross-cohort comparisons, children from low-income families who participated in the free or reduced-price NSLP had a higher likelihood of progression to high BMI that was no longer observed after HHFKA implementation. This finding suggests that the HHFKA may have attenuated the previous association of the NSLP with child obesity disparities.

A Simple Method for Simulating Dementia Onset and Death within an Existing Demographic Model.

BACKGROUND: Dementia is a common disease that has an impact on both the affected individual and family members who provide caregiving. Simulation models can assist in setting policy that anticipates public health needs by predicting the demand for and availability of care. OBJECTIVE: We developed a relatively simple method for simulating the onset of dementia that can be used in combination with an existing microsimulation model. METHODS: We started with Socsim, a demographic microsimulation model that simulates a population with family kinship networks. We simulated dementia in the Socsim population by simulating the number of individuals diagnosed with dementia in their lifetime and the ages of onset and death from dementia for each of these dementia cases. We then matched dementia cases to the simulated population based on age at death, so for each individual, we simulate whether they develop dementia and, if so, their age at onset. This approach simulates dementia onset but does not alter the demographic model's simulated age of death. RESULTS: We selected model dementia parameters so that the combined Socsim-Dementia model reproduces published dementia prevalence rates and survival times after diagnosis. CONCLUSIONS: Adding simulation of dementia to a kinship network model enables prediction of the availability of family caregivers for people with dementia under a range of different assumptions about future fertility, mortality, and dementia risk. We demonstrated how to add simulation of dementia onset and death to an existing microsimulation model to obtain a method for predicting dementia prevalence in the context of another more detailed model. The approach we developed can be generalized to simulate other progressive health conditions that affect mortality.

Disparities in Prostate Cancer Survival According to Neighborhood Archetypes, A Population-Based Study.

OBJECTIVES: To examine survival among men with prostate cancer according to neighborhood archetypes. As an advancement beyond measures of neighborhood socioeconomic status (nSES) or specific measures of the neighborhood environment, archetypes consider interactions among many social and built environment attributes. METHODS: Neighborhood archetypes for California census tracts in the year 2000 were previously developed through latent class analysis of 39 measures of social and built environment attributes. We assessed associations between archetypes and overall and prostate cancer-specific survival in this population-based study using geocoded cancer registry data for prostate cancer patients diagnosed 1996-2005 in California, followed through 2017 (n = 185,613). We used Cox proportional hazard models stratified by race/ethnicity and adjusted for age at diagnosis, year of diagnosis, tumor factors, treatment, marital status and cluster effect by census tract. Additional analyses examined associations between race/ethnicity and survival, while accounting for neighborhood archetypes. RESULTS: We observed disparities in overall and prostate cancer-specific risk of death by neighborhood archetypes. Classes with the highest risk of death were defined by lower nSES, but also other domains such as rural/urban status, racial/ethnic composition or age of residents, commuting and traffic patterns, residential mobility, and food environment. Associations between archetypes and survival varied by race/ethnicity. CONCLUSION: We observe interactions among several domains of neighborhood social and built environment attributes as demonstrated by the associations between neighborhood archetypes and prostate cancer survival. These results highlight opportunities for multilevel neighborhood interventions to reduce neighborhood disparities in prostate cancer survival.

Neighborhood archetypes and breast cancer survival in California.

PURPOSE: Previous studies on neighborhoods and breast cancer survival examined neighborhood variables as unidimensional measures (e.g. walkability or deprivation) individually and thus cannot inform how the multitude of highly correlated neighborhood domains interact to impact breast cancer survival. Neighborhood archetypes were developed that consider interactions among a broad range of neighborhood social and built environment attributes and examine their associations with breast cancer survival. METHODS: Archetypes were measured using latent class analysis (LCA) fit to California census tract-level data. Thirty-nine social and built environment attributes relevant to eight neighborhood domains (socioeconomic status (SES), urbanicity, demographics, housing, land use, commuting and traffic, residential mobility, and food environment) were included.  The archetypes were linked to cancer registry data on breast cancer cases (diagnosed 1996-2005 with follow-up through Dec 31, 2017) to evaluate their associations with overall and breast cancer-specific survival using Cox proportional hazards models. Analyses were stratified by race/ethnicity. RESULTS: California neighborhoods were best described by nine archetypal patterns that were differentially associated with overall and breast cancer-specific survival. The lowest risk of overall death was observed in the upper middle class suburb (reference) and high status neighborhoods, while the highest was observed among inner city residents with a 39% greater risk of death (95% CI = 1.35 to 1.44). Results were similar for breast cancer-specific survival. Stratified analyses indicated that differences in survival by neighborhood archetypes varied according to individuals' race/ethnicity. CONCLUSIONS: By describing neighborhood archetypes that differentiate survival following breast cancer diagnosis, the study provides direction for policy and clinical practice addressing contextually-rooted social determinants of health including SES, unhealthy food environments, and greenspace.

Secular Trends in Dementia and Cognitive Impairment of U.S. Rural and Urban Older Adults.

INTRODUCTION: This is a nationally representative study of rural-urban disparities in the prevalence of probable dementia and cognitive impairment without dementia (CIND). METHODS: Data on non-institutionalized U.S. adults from the 2000 (n=16,386) and 2010 (n=16,311) cross-sections of the Health and Retirement Study were linked to respective Census assessments of the urban composition of residential census tracts. Relative risk ratios (RRR) for rural-urban differentials in dementia and CIND respective to normal cognitive status were assessed using multinomial logistic regression. Analyses were conducted in 2016. RESULTS: Unadjusted prevalence of dementia and CIND in rural and urban tracts converged so that rural disadvantages in the relative risk of dementia (RRR=1.42, 95% CI=1.10, 1.83) and CIND (RRR=1.35, 95% CI=1.13, 1.61) in 2000 no longer reached statistical significance in 2010. Adjustment for the strong protective role of educational attainment reduced rural disadvantages in 2000 to statistical nonsignificance, whereas adjustment for race/ethnicity resulted in a statistically significant increase in RRRs in 2010. Full adjustment for sociodemographic and health factors revealed persisting rural disadvantages for dementia and CIND in both periods with RRR in 2010 for dementia of 1.79 (95% CI=1.31, 2.43) and for CIND of 1.38 (95% CI=1.14, 1.68). CONCLUSIONS: Larger gains in rural adults' cognitive functioning between 2000 and 2010 that are linked with increased educational attainment demonstrate long-term public health benefits of investment in secondary education. Persistent disadvantages in cognitive functioning among rural adults compared with sociodemographically similar urban peers highlight the importance of public health planning for more rapidly aging rural communities.

The Hispanic Paradox: Race/Ethnicity and Nativity, Immigrant Enclave Residence and Cognitive Impairment Among Older US Adults.

Hispanics, and particularly foreign-born Mexican Americans, have been shown to fare better across a range of health outcomes than might be expected given the generally higher levels of socioeconomic disadvantage in this population, a phenomena termed the "Hispanic Paradox". Previous research on social disparities in cognitive aging, however, has been unable to address both race/ethnicity and nativity (REN) in a nationally-representative sample of US adults leaving unanswered questions about potentially "paradoxical" advantages of Mexican ethnic-origins and the role of nativity, socioeconomic status (SES), and enclave residence. We employ biennial assessments of cognitive functioning to study prevalent and incident cognitive impairment (CI) within the three largest US REN groups: US-born non-Hispanic whites (US-NHW), US-born non-Hispanic blacks (US-NHB), US-born Mexican Americans (US-MA), and foreign-born Mexican Americans (FB-MA). Data come from a nationally-representative sample of community-dwelling older adults in the Health and Retirement Study linked with the 2000 Census and followed over 10 years (N = 8,433). Large disadvantages in prevalent and incident CI were observed for all REN minorities respective to US-born non-Hispanic whites. Individual and neighborhood SES accounted substantially for these disadvantages and revealed an immigrant advantage: FB-MA odds of prevalent CI were about half those of US-NHW and hazards of incident CI were about half those of US-MA. Residence in an immigrant enclave was protective of prevalent CI among FB-MA. The findings illuminate important directions for research into the sources of cognitive risk and resilience and provide guidance about CI screening within the increasingly diverse aging US population.

Neighborhood age structure and cognitive function in a nationally-representative sample of older adults in the U.S.

Recent evidence suggests that living in a neighborhood with a greater percentage of older adults is associated with better individual health, including lower depression, better self-rated health, and a decreased risk of overall mortality. However, much of the work to date suffers from four limitations. First, none of the U.S.-based studies examine the association at the national level. Second, no studies have examined three important hypothesized mechanisms - neighborhood socioeconomic status and neighborhood social and physical characteristics - which are significantly correlated with both neighborhood age structure and health. Third, no U.S. study has longitudinally examined cognitive health trajectories. We build on this literature by examining nine years of nationally-representative data from the Health and Retirement Study (2002-2010) on men and women aged 51 and over linked with Census data to examine the relationship between the percentage of adults 65 and older in a neighborhood and individual cognitive health trajectories. Our results indicate that living in a neighborhood with a greater percentage of older adults is related to better individual cognition at baseline but we did not find any significant association with cognitive decline. We also explored potential mediators including neighborhood socioeconomic status, perceived neighborhood cohesion and perceived neighborhood physical disorder. We did not find evidence that neighborhood socioeconomic status explains this relationship; however, there is suggestive evidence that perceived cohesion and disorder may explain some of the association between age structure and cognition. Although more work is needed to identify the precise mechanisms, this work may suggest a potential contextual target for public health interventions to prevent cognitive impairment.

Functioning, Forgetting, or Failing Health: Which Factors Are Associated With a Community-Based Move Among Older Adults?

OBJECTIVE: To examine whether the health and functioning of middle-aged and older adults are associated with an increased likelihood of community-based moves. METHOD: Biennial data from adults aged 51 and older in the Health and Retirement Study (HRS) and discrete-time survival models were used to assess the likelihood of community-based moves from 2000 to 2010 as a function of 11 measures of health and functioning. RESULTS: Respondents diagnosed with heart disease, stroke, hypertension, lung disease, and psychiatric problems were more likely to move during the study period than those with no such diagnosis. Changes in activities of daily living and instrumental activities of daily living functioning, cognitive impairment, and falls were also related to a greater likelihood of moving during the study period. Cancer and diabetes were not related to overall moves, although diabetes was associated with an increased likelihood of local moves. For the most part, it was longstanding not recent diagnoses that were significantly related to the likelihood of moving. DISCUSSION: Although some health conditions precipitate moves among middle-aged and older adults, others do not. This work has important implications for understanding the role of different aspects of health and functioning in the likelihood of migration among older adults.

Constructing a Time-Invariant Measure of the Socio-economic Status of U.S. Census Tracts.

Contextual research on time and place requires a consistent measurement instrument for neighborhood conditions in order to make unbiased inferences about neighborhood change. We develop such a time-invariant measure of neighborhood socio-economic status (NSES) using exploratory and confirmatory factor analyses fit to census data at the tract level from the 1990 and 2000 U.S. Censuses and the 2008-2012 American Community Survey. A single factor model fit the data well at all three time periods, and factor loadings--but not indicator intercepts--could be constrained to equality over time without decrement to fit. After addressing remaining longitudinal measurement bias, we found that NSES increased from 1990 to 2000, and then--consistent with the timing of the "Great Recession"--declined in 2008-2012 to a level approaching that of 1990. Our approach for evaluating and adjusting for time-invariance is not only instructive for studies of NSES but also more generally for longitudinal studies in which the variable of interest is a latent construct.

Evaluating Linearly Interpolated Intercensal Estimates of Demographic and Socioeconomic Characteristics of U.S. Counties and Census Tracts 2001-2009.

The American Community Survey (ACS) multiyear estimation program has greatly advanced opportunities for studying change in the demographic and socioeconomic characteristics of U.S. communities. Challenges remain, however, for researchers studying years prior to the full implementation of the ACS or areas smaller than the thresholds for ACS annual estimates (i.e., small counties and census tracts). We evaluate intercensal estimates of the demographic and socioeconomic characteristics of U.S. counties and census tracts produced via linear interpolation between the 2000 census and both the 2010 census and 2005-2009 ACS. Discrepancies between interpolated estimates and reference estimates from the Population Estimates Program, the Small Area Income and Poverty Estimates, and ACS are calculated using several measures of error. Findings are discussed in relation to the potential for measurement error to bias longitudinal estimates of linearly interpolated neighborhood change, and alternative intercensal estimation models are discussed, including those that may better capture non-linear trends in economic conditions over the 21st century.

Epidemiological Paradox or Immigrant Vulnerability? Obesity Among Young Children of Immigrants.

According to the "immigrant epidemiological paradox," immigrants and their children enjoy health advantages over their U.S.-born peers--advantages that diminish with greater acculturation. We investigated child obesity as a potentially significant deviation from this paradox for second-generation immigrant children. We evaluated two alternate measures of mother's acculturation: age at arrival in the United States and English language proficiency. To obtain sufficient numbers of second-generation immigrant children, we pooled samples across two related, nationally representative surveys. Each included measured (not parent-reported) height and weight of kindergartners. We also estimated models that alternately included and excluded mother's pre-pregnancy weight status as a predictor. Our findings are opposite to those predicted by the immigrant epidemiological paradox: children of U.S.-born mothers were less likely to be obese than otherwise similar children of foreign-born mothers; and the children of the least-acculturated immigrant mothers, as measured by low English language proficiency, were the most likely to be obese. Foreign-born mothers had lower (healthier) pre-pregnancy weight than U.S.-born mothers, and this was protective against their second-generation children's obesity. This protection, however, was not sufficiently strong to outweigh factors associated or correlated with the mothers' linguistic isolation and marginal status as immigrants.

Evaluation of bias in estimates of early childhood obesity from parent-reported heights and weights.

OBJECTIVES: We evaluated bias in estimated obesity prevalence owing to error in parental reporting. We also evaluated bias mitigation through application of Centers for Disease Control and Prevention's biologically implausible value (BIV) cutoffs. METHODS: We simulated obesity prevalence of children aged 2 to 5 years in 2 panel surveys after counterfactually substituting parameters estimated from 1999-2008 National Health and Nutrition Examination Survey data for prevalence of extreme height and weight and for proportions obese in extreme height or weight categories. RESULTS: Heights reported below the first and fifth height-for-age percentiles explained between one half and two thirds, respectively, of total bias in obesity prevalence. Bias was reduced by one tenth when excluding cases with height-for-age and weight-for-age BIVs and by one fifth when excluding cases with body mass-index-for-age BIVs. Applying BIVs, however, resulted in incorrect exclusion of nonnegligible proportions of obese children. CONCLUSIONS: Correcting the reporting of children's heights in the first percentile alone may reduce overestimation of early childhood obesity prevalence in surveys with parental reporting by one half to two thirds. Excluding BIVs has limited effectiveness in mitigating this bias.

Multiple Imputation For Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys.

Within-survey multiple imputation (MI) methods are adapted to pooled-survey regression estimation where one survey has more regressors, but typically fewer observations, than the other. This adaptation is achieved through: (1) larger numbers of imputations to compensate for the higher fraction of missing values; (2) model-fit statistics to check the assumption that the two surveys sample from a common universe; and (3) specificying the analysis model completely from variables present in the survey with the larger set of regressors, thereby excluding variables never jointly observed. In contrast to the typical within-survey MI context, cross-survey missingness is monotonic and easily satisfies the Missing At Random (MAR) assumption needed for unbiased MI. Large efficiency gains and substantial reduction in omitted variable bias are demonstrated in an application to sociodemographic differences in the risk of child obesity estimated from two nationally-representative cohort surveys.

Parent-reported height and weight as sources of bias in survey estimates of childhood obesity.

Parental reporting of height and weight was evaluated for US children aged 2-13 years. The prevalence of obesity (defined as a body mass index value (calculated as weight (kg)/height (m)(2)) in the 95th percentile or higher) and its height and weight components were compared in child supplements of 2 nationally representative surveys: the 1996-2008 Children of the National Longitudinal Survey of Youth 1979 Cohort (NLSY79-Child) and the 1997 Child Development Supplement of the Panel Study of Income Dynamics (PSID-CDS). Sociodemographic differences in parent reporting error were analyzed. Error was largest for children aged 2-5 years. Underreporting of height, not overreporting of weight, generated a strong upward bias in obesity prevalence at those ages. Frequencies of parent-reported heights below the Centers for Disease Control and Prevention's (Atlanta, Georgia) first percentile were implausibly high at 16.5% (95% confidence interval (CI): 14.3, 19.0) in the NLSY79-Child and 20.6% (95% CI: 16.0, 26.3) in the PSID-CDS. They were highest among low-income children at 33.2% (95% CI: 22.4, 46.1) in the PSID-CDS and 26.2% (95% CI: 20.2, 33.2) in the NLSY79-Child. Bias in the reporting of obesity decreased with children's age and reversed direction at ages 12-13 years. Underreporting of weight increased with age, and underreporting of height decreased with age. We recommend caution to researchers who use parent-reported heights, especially for very young children, and offer practical solutions for survey data collection and research on child obesity.

Prenatal, perinatal, early life, and sociodemographic factors underlying racial differences in the likelihood of high body mass index in early childhood.

OBJECTIVES: We investigated early childhood disparities in high body mass index (BMI) between Black and White US children. METHODS: We compared differences in Black and White children's prevalence of sociodemographic, prenatal, perinatal, and early life risk and protective factors; fit logistic regression models predicting high BMI (≥ 95th percentile) at age 4 to 5 years to 2 nationally representative samples followed from birth; and performed separate and pooled-survey estimations of these models. RESULTS: After adjustment for sample design-related variables, models predicting high BMI in the 2 samples were statistically indistinguishable. In the pooled-survey models, Black children's odds of high BMI were 59% higher than White children's (odds ratio [OR] = 1.59; 95% confidence interval [CI]= 1.32, 1.92). Sociodemographic predictors reduced the racial disparity to 46% (OR = 1.46; 95% CI = 1.17, 1.81). Prenatal, perinatal, and early life predictors reduced the disparity to nonsignificance (OR = 1.18; 95% CI = 0.93, 1.49). Maternal prepregnancy obesity and short-duration or no breastfeeding were among predictors for which racial differences in children's exposures most disadvantaged Black children. CONCLUSIONS: Racial disparities in early childhood high BMI were largely explained by potentially modifiable risk and protective factors.

Is the intergenerational transmission of smoking from mother to child mediated by children's behavior problems?

INTRODUCTION: A previous paper used latent class analysis to assign individuals to 1 of 4 adolescent/young adult smoking trajectory classes and then established an association between maternal smoking before, during, and after pregnancy and these classes. In this paper, we examine one possible pathway for this relationship: that maternal smoking during pregnancy may set off a behavioral trajectory which increases the likelihood of problem behaviors generally, of which smoking is one manifestation. METHODS: We used the Behavior Problems Index measure from age 8 through age 12 as a potential mediator. We used a path analysis modeling approach within a multinomial logistic regression (using Mplus) to estimate direct and indirect effects (via behavioral problems) between maternal smoking pattern and child trajectory class. RESULTS: We found small but statistically significant indirect effects via behavioral problems from maternal smoking to child smoking trajectory for membership in all 3 smoking classes, relative to the nonsmoking trajectory, indicating partial mediation. Mediated effects were associated with maternal smoking after pregnancy, no statistically significant mediated effects were found for smoking before or during pregnancy. CONCLUSIONS: The results provided no evidence that the effects of maternal smoking during pregnancy on child smoking trajectory are mediated by problem behavior. Effects from smoking after birth to child smoking trajectory appear to be partially mediated by problem behavior, supporting a behavioral rather than physiological effect of smoking during pregnancy but not ruling out more complex physiological pathways.

The multidimensional relationship between early adult body weight and women's childbearing experiences.

This study has three primary goals that make an important contribution to the literature on body weight and childbearing experiences among United States' women. It sheds light on the physiological and social nature of this relationship by examining whether the consequences of early adult weight for lifetime childbearing are shaped by historical social context, women's social characteristics, and their ability to marry. We analyze data from two female cohorts who participated in the National Longitudinal Study of Youth (NLSY79). Cohort 1 entered early adulthood before the U.S. obesity prevalence increased. Cohort 2 entered early adulthood after the obesity prevalence increased. We find that early adult weight is negatively related to the childbearing trajectories and marital status of Cohort 1 but not Cohort 2. Failing to account for race/ethnicity and women's educational background as confounders masks some of these associations, which are evident for both White and Black women. Our results suggest that the health consequences of body weight do not fully drive its impact on childbearing. Rather, the lifetime fertility consequences of early adult weight are malleable, involve social processes, and are dependent on social context.

Intergenerational relationships between the smoking patterns of a population-representative sample of US mothers and the smoking trajectories of their children.

OBJECTIVES: We assessed intergenerational transmission of smoking in mother-child dyads. METHODS: We identified classes of youth smoking trajectories using mixture latent trajectory analyses with data from the Children and Young Adults of the National Longitudinal Survey of Youth (n = 6349). We regressed class membership on prenatal and postnatal exposure to maternal smoking, including social and behavioral variables, to control for selection. RESULTS: Youth smoking trajectories entailed early-onset persistent smoking, early-onset experimental discontinued smoking, late-onset persistent smoking, and nonsmoking. The likelihood of early onset versus late onset and early onset versus nonsmoking were significantly higher among youths exposed prenatally and postnatally versus either postnatally alone or unexposed. Controlling for selection, the increased likelihood of early onset versus nonsmoking remained significant for each exposure group versus unexposed, as did early onset versus late onset and late onset versus nonsmoking for youths exposed prenatally and postnatally versus unexposed. Experimental smoking was notable among youths whose mothers smoked but quit before the child's birth. CONCLUSIONS: Both physiological and social role-modeling mechanisms of intergenerational transmission are evident. Prioritization of tobacco control for pregnant women, mothers, and youths remains a critical, interrelated objective.

Using geographic information systems to match local health needs with public health services and programs.

Local health departments (LHDs) play an important role in ensuring essential public health services. Geographic information system (GIS) technology offers a promising means for LHDs to identify geographic gaps between areas of need and the reach of public health services. We examined how large LHDs could better inform planning and investments by using GIS-based methodologies to align community needs and health outcomes with public health programs. We present a framework to drive LHDs in identifying and addressing gaps or mismatches in services or health outcomes.