Maternal residential exposure to solvents from industrial sources during pregnancy and childhood cancer risk in California.

BACKGROUND: Maternal solvent exposure has been suspected to increase offspring cancer risk. The study aimed to evaluate the associations between maternal residential exposure to solvents from industrial pollution during pregnancy and childhood cancer. METHODS: The present study included 15,744 cancer cases (aged 0-19 years at diagnosis) identified from California Cancer Registry and 283,141 controls randomly selected from California Birth Registry (20:1 frequency-matched by birth year: 1998-2016). We examined industrial releases of tetrachloroethylene and 1,1,1-trichloroethane within 3 km of the birth address, while we used a 5 km buffer for carbon disulfide. We calculated the total exposure from all linked Toxic Release Inventory sites during each index pregnancy and assigned "ever/never" and "high/low exposed/unexposed" exposure, using median values. We performed quadratic decay models to estimate cancer risks associated with maternal solvent exposure in pregnancy. RESULTS: 1,1,1-Trichloroethane was associated with rhabdomyosarcoma (adjusted Odds Ratio (aOR): 1.96; 95% Confidence Interval (CI): 1.16, 3.32) in the "ever exposed" group. Ever exposure to carbon disulfide was associated with increased risks of medulloblastoma (OR = 1.85, 95% CI 1.01, 3.40) and ependymoma (OR = 1.63, 95% CI 0.97, 2.74). CONCLUSIONS: Overall, our findings suggested maternal residential exposure to solvents from industrial sources might be associated with elevated childhood cancer risks.

Genetically Determined Circulating Lactase/Phlorizin Hydrolase Concentrations and Risk of Colorectal Cancer: A Two-Sample Mendelian Randomization Study.

Previous research has found that milk is associated with a decreased risk of colorectal cancer (CRC). However, it is unclear whether the milk digestion by the enzyme lactase-phlorizin hydrolase (LPH) plays a role in CRC susceptibility. Our study aims to investigate the direct causal relationship of CRC risk with LPH levels by applying a two-sample Mendelian Randomization (MR) strategy. Genetic instruments for LPH were derived from the Fenland Study, and CRC-associated summary statistics for these instruments were extracted from the FinnGen Study, PLCO Atlas Project, and Pan-UK Biobank. Primary MR analyses focused on a cis-variant (rs4988235) for LPH levels, with results integrated via meta-analysis. MR analyses using all variants were also undertaken. This analytical approach was further extended to assess CRC subtypes (colon and rectal). Meta-analysis across the three datasets illustrated an inverse association between genetically predicted LPH levels and CRC risk (OR: 0.92 [95% CI, 0.89-0.95]). Subtype analyses revealed associations of elevated LPH levels with reduced risks for both colon (OR: 0.92 [95% CI, 0.89-0.96]) and rectal cancer (OR: 0.92 [95% CI, 0.87, 0.98]). Consistency was observed across varied analytical methods and datasets. Further exploration is warranted to unveil the underlying mechanisms and validate LPH's potential role in CRC prevention.

Association Between Gestational Diabetes Mellitus and Hypertension: A Systematic Review and Meta-Analysis of Cohort Studies With a Quantitative Bias Analysis of Uncontrolled Confounding.

BACKGROUND: Whether individuals with gestational diabetes mellitus (GDM) had an increased risk of hypertension remains unclear. We conducted a systematic literature review and meta-analysis to examine the association between GDM and hypertension and performed a quantitative bias analysis to quantify the impact of uncontrolled confounding due to antenatal psychological stress. METHODS: We searched databases (PUBMED, EMBASE, and Web of Science) through 2022/11. Eligible studies were cohort studies that reported the association of GDM with hypertension. We assessed the risk of bias using the Newcastle-Ottawa Scale for cohort studies. We pooled adjusted risk ratios with 95% CIs using a random effects model. We performed the quantitative bias analysis using the bias formula. RESULTS: We included 15 cohort studies, with a total of 3 959 520 (GDM, 175 378; non-GDM, 3 784 142) individuals. During the follow-up of 2 to 20 years, 106 560 cases of hypertension were reported. We found that GDM was associated with a higher risk of hypertension (pooled risk ratio, 1.78 [95% CI, 1.47, 2.17]). The risk ratio was lower among cohorts assessing incident (1.58 [95% CI, 1.29, 1.95]) than prevalent hypertension (2.60 [95% CI, 2.40, 2.83]). However, other subgroup analyses showed no differences. The quantitative bias analysis revealed that if the uncontrolled confounder of antenatal psychological stress was additionally adjusted, the positive association between GDM and hypertension would attenuate slightly (≤18%) but remains positive. CONCLUSIONS: Limitations of this study included residual confounding and discrepancies in GDM and hypertension ascertainments. Our findings indicate that GDM is positively associated with hypertension after the index pregnancy.

Prevalence of maternal hyperglycemic subtypes by race/ethnicity and associations between these subtypes with adverse pregnancy outcomes: Findings from a large retrospective multi-ethnic cohort in the United States.

AIMS: With the two-step gestational diabetes mellitus (GDM) screening approach, hyperglycemic subtypes can be identified. We aimed to investigate racial/ethnic differences in the prevalence of hyperglycemic subtypes and to examine the associations between these subtypes and adverse pregnancy outcomes. METHODS: In this retrospective cohort, 11,405 pregnancies were screened using the two-step approach. Hyperglycemic subtypes included: pregnancy-impaired glucose intolerance-I (PIGT-I), PIGT-II, GDM-I (abnormal post-load glucose only), and GDM-II (abnormal fasting & post-load glucose). Modified Poisson regressions with robust error variance were used to estimate age-adjusted prevalence ratios (PR) of hyperglycemic subtypes and multivariable-adjusted risk ratios (RR) of adverse pregnancy outcomes. RESULTS: The prevalence of hyperglycemic subtypes was higher in Asians (PIGT-I: 1.51 [95% confidence interval 1.35-1.69]; PIGT-II: 2.18 [1.78-2.68]; GDM-I: 2.55 [2.10-3.10]; GDM-II: 1.55 [1.08-2.21]) and Hispanics (PIGT-I: 1.32 [1.16-1.50]; PIGT-II: 2.07 [1.67-2.57]; GDM-I: 1.69 [1.35-2.13]; GDM-II: 2.68 [1.93-3.71]) than non-Hispanic Whites (NHW). Despite low GDM prevalence, Japanese and Koreans had higher PIGT prevalence than NHW. PIGT-II was positively associated with hypertensive disorders of pregnancy (1.19 [1.02-1.38]), large-for-gestational age (1.73 [1.37-2.18]), and preterm birth (PB, 1.33 [1.05-1.68]). PIGT-I (1.23 [1.04-1.45]) and GDM-I (1.56 [0.87-1.71]) were positively related to PB. CONCLUSIONS: The prevalence of hyperglycemic subtypes varies by race/ethnicity and they have distinct health implications.

Evaluating the impact of the Medicaid expansion program on diabetes hospitalization.

Diabetes is the most expensive chronic disease in the United States, and hospital inpatient care accounts for 30% of the total medical expenditures. Medical costs for people with limited resources are covered by Medicaid, a joint federal and state program, and its expansion that extent the coverage to those with incomes up to 138% of the federal poverty level. We investigated the impact of Medicaid expansion on diabetes hospitalizations by states and payer, among adults aged 19 to 64 years old, 5 years after the expansion. We found that Medicaid expansion decreased total diabetes hospitalization in most states and a diabetes hospitalization payer mix shifted from private insurance and uninsured to Medicaid. The percentage of diabetes hospitalizations paid by Medicaid increased by 11% (95% CI 7%, 16%), while the percentage paid by private insurance decreased by 6% (95% CI - 8%, - 3%) and the percentage of uninsured diabetes hospitalization decreased by 13% (95% CI - 18%, - 9%).

The role of breastfeeding support in racial/ethnic disparities in breastfeeding practices.

BACKGROUND: Persistent racial/ethnic disparities in breastfeeding practices in the United States are well documented but the underlying causes remain unclear. While racial/ethnic disparities are often intertwined with socioeconomic disparities in breastfeeding, studies suggest that lack of breastfeeding support from family, health care organizations and workplaces may contribute to racial/ethnic disparities in breastfeeding rates. No studies have investigated the extent to which racial/ethnic disparities in breastfeeding practices can be explained by breastfeeding support. METHODS: We used survey data from participants of a federal nutrition assistance program in Los Angeles County, the most populous county in the United States, to examine causal mechanisms underlying racial/ethnic disparities in breastfeeding in five groups: Spanish-speaking Latina, English-speaking Latina, Non-Hispanic White (NHW), Non-Hispanic Black (NHB) and Non-Hispanic Asian (NHA). Applying causal mediation analysis, this study estimated the proportion of racial/ethnic differences in breastfeeding ('any' breastfeeding, i.e., partial or exclusive) rates at 6 months that could be explained by differential access to breastfeeding support from family, birth hospitals and workplaces. RESULTS: NHB and English-speaking Latina mothers were less likely, and Spanish-speaking Latina mothers more likely to breastfeed through 6 months than NHW mothers. Lack of breastfeeding support from family, hospitals and workplaces accounted for approximately 68% of the difference in any breastfeeding rates at 6 months between NHW and NHB mothers and 36% of the difference between NHW and English-speaking Latina mothers. CONCLUSION: These findings highlight the importance of improving support from family, hospitals and workplaces for breastfeeding mothers to reduce racial/ethnic disparities in breastfeeding.

Medicaid Expansion and Racial-Ethnic and Sex Disparities in Cardiovascular Diseases Over 6 Years: A Generalized Synthetic Control Approach.

BACKGROUND: Studies have suggested Medicaid expansion enacted in 2014 has resulted in a reduction in overall cardiovascular disease (CVD) mortality in the United States. However, it is unknown whether Medicaid expansion has a similar effect across race-ethnicity and sex. We investigated the effect of Medicaid expansion on CVD mortality across race-ethnicity and sex. METHODS: Data come from the behavioral risk factor surveillance system and the US Centers for Disease Control's Wide-ranging Online Data for Epidemiologic Research, spanning the period 2000-2019. We used the generalized synthetic control method, a quasi-experimental approach, to estimate effects. RESULTS: Medicaid expansion was associated with -5.36 (mean difference [MD], 95% confidence interval [CI] = -22.63, 11.91) CVD deaths per 100,000 persons per year among Blacks; -4.28 (MD, 95% CI = -30.08, 21.52) among Hispanics; -3.18 (MD, 95% CI = -8.30, 1.94) among Whites; -5.96 (MD, 95% CI = -15.42, 3.50) among men; and -3.34 (MD, 95% CI = -8.05, 1.37) among women. The difference in mean difference (DMD) between the effect of Medicaid expansion in Blacks compared with Whites was -2.18; (DMD, 95% CI = -20.20, 15.83); between that in Hispanics compared with Whites: -1.10; (DMD, 95% CI = -27.40, 25.20) and between that in women compared with men: 2.62; (DMD, 95% CI = -7.95, 13.19). CONCLUSIONS: Medicaid expansion was associated with a reduction in CVD mortality overall and in White, Black, Hispanic, male, and female subpopulations. Also, our study did not find any difference or disparity in the effect of Medicaid on CVD across race-ethnicity and sex-gender subpopulations, likely owing to imprecise estimates.

Gestational diabetes mellitus and risk of neurodevelopmental disorders in young offspring: does the risk differ by race and ethnicity?

BACKGROUND: Previous studies examined the associations of gestational diabetes mellitus with autism spectrum disorder and attention deficit hyperactivity disorder. However, the associations between gestational diabetes mellitus and other neurodevelopmental disorders, such as the common speech/language disorder and developmental coordination disorder, are rarely studied, and whether the associations vary by race/ethnicity remains unknown. OBJECTIVE: This study aimed to examine the associations of gestational diabetes mellitus with individual neurodevelopmental disorders in young offspring, and to investigate whether the associations vary by race/ethnicity. STUDY DESIGN: This retrospective cohort study (Glucose in Relation to Women and Babies' Health [GrownB]) included 14,480 mother-offspring pairs in a large medical center in the United States from March 1, 2013 to August 31, 2021. We ascertained gestational diabetes mellitus using the validated ICD (International Classification of Diseases) codes (ICD-9: 648.8x; ICD-10: O24.4x), and identified neurodevelopmental disorders (speech/language disorder, developmental coordination disorder, autism spectrum disorder, and other neurodevelopmental disorders [attention deficit hyperactivity disorder, behavioral disorder, intellectual disability, and learning difficulty]) and their combinations using validated algorithms. We compared the hazard of neurodevelopmental disorders during the entire follow-up period between offspring born to mothers with and without gestational diabetes mellitus using multivariable Cox regression models. RESULTS: Among all mothers, 19.9% were Asian, 21.8% were Hispanic, 41.0% were non-Hispanic White, and 17.3% were of other/unknown race/ethnicity. During the median follow-up of 3.5 years (range, 1.0-6.3 years) after birth, 8.7% of offspring developed at least 1 neurodevelopmental disorder. Gestational diabetes mellitus was associated with a higher risk of speech/language disorder (adjusted hazard ratio, 1.59 [95% confidence interval, 1.07-2.35]), developmental coordination disorder (2.36 [1.37-4.04]), autism spectrum disorder (3.16 [1.36-7.37]), other neurodevelopmental disorders (3.12 [1.51-6.47]), any neurodevelopmental disorder (1.86 [1.36-2.53]), the combination of speech/language disorder and autism spectrum disorder (3.79 [1.35-10.61]), and the combination of speech/language disorder and developmental coordination disorder (4.22 [1.69-10.51]) among offspring born to non-Hispanic White mothers. No associations between gestational diabetes mellitus and any neurodevelopmental disorders or their combinations were observed among offspring born to mothers of other racial/ethnic groups. CONCLUSION: We observed an elevated risk of neurodevelopmental disorders among young offspring born to non-Hispanic White mothers with gestational diabetes mellitus, but not among other racial/ethnic groups.

The impact of maternal pertussis vaccination recommendation on infant pertussis incidence and mortality in the USA: an interrupted time series analysis.

BACKGROUND: Pertussis is a contagious respiratory disease. Maternal tetanus-diphtheria-acellular pertussis vaccination during pregnancy has been recommended by the United States Centres for Disease Control (US CDC) Advisory Committee on Immunization Practices (ACIP) for unvaccinated pregnant women since October 2011 to prevent infection among infants; in 2012, ACIP extended this recommendation to every pregnancy, regardless of previous vaccination status. The population-level effect of these recommendations on infant pertussis is unknown. This study aimed to examine the impact of the 2011/2012 ACIP pertussis recommendation on pertussis incidence and mortality among US infants. METHODS: We used monthly data on pertussis deaths among infants aged <1 year between January 2005 and December 2017 in the CDC Death Data and yearly infant pertussis incidence data from the CDC National Notifiable Disease Surveillance System to perform an interrupted time series analysis, accounting for the passage of the Affordable Care Act. RESULTS: This study included 156 months of data. A potential decline in trend in infant pertussis incidence was noted during the post-recommendations period. No appreciable differences in trend were found in population-level infant pertussis mortality after the guideline changes in both adjusted and unadjusted models. Results were similar for all mortality sensitivity analyses. CONCLUSIONS: The 2011/2012 ACIP maternal pertussis vaccination recommendations were not associated with a population-level change in the trend in mortality, but were potentially associated with a decrease in incidence in the USA between 2005 and 2017.

Cost-effectiveness analysis of insecticide ban aimed at preventing Parkinson's disease in Central California.

BACKGROUND: Our study assessed whether banning specific insecticides to reduce the PD burden in three Central California (CA) counties is cost-effective. METHOD: We applied a cost-effectiveness analysis using a cohort-based Markov model to estimate the impact and costs of banning seven insecticides that were previously associated with PD in these counties as well as mixture exposures to some of these pesticides. We relied for our estimations on the cohort of 65- and 66-year-olds living in these counties who were unaffected by PD at baseline in 2020 and projected their incidence, costs, and reduction in quality-adjusted-life-years (QALY) loss due to developing PD over a 20-year period. We included a shiny app for modeling different scenarios (https://sherlockli.shinyapps.io/pesticide_pd_economics_part_2/). RESULTS: According to our scenarios, banning insecticides to reduce the occurrence of PD in three Central CA counties was cost-effective relative to not banning insecticides. In the worst-case scenario of exposure to a single pesticide, methomyl, versus none would result in an estimated 205 (95 % CI: 75, 348) additional PD cases or 12 % (95 % CI: 4 %, 20 %) increase in PD cases over a 20-year period based on residential proximity to pesticide applications. The increase in PD cases due to methomyl would increase health-related costs by $72.0 million (95 % CI: $5.5 million, $187.4 million). Each additional PD patient due to methomyl exposure would incur $109,327 (95 % CI, $5554, $347,757) in costs per QALY loss due to PD. Exposure to methomyl based on workplace proximity to pesticide applications generated similar estimates. The highest PD burden and associated costs would be incurred from exposure to multiple pesticides simultaneously. CONCLUSION: Our study provides an assessment of the cost-effectiveness of banning specific insecticides to reduce PD burden in terms of health-related QALYs and related costs. This information may help policymakers and stakeholders to make decisions concerning the regulation of pesticides.

Evaluating the use of oral pre-exposure prophylaxis among pregnant and postpartum adolescent girls and young women in Cape Town, South Africa.

Background: Adolescent girls and young women (AGYW) in South Africa are at a higher risk of acquiring HIV. Despite the increasing availability of daily oral pre-exposure prophylaxis (PrEP) for HIV prevention, knowledge on PrEP use during pregnancy and postpartum periods at antenatal care (ANC) facilities remains inadequate. Methods: Data from HIV-uninfected pregnant women in Cape Town, South Africa, were used in this study. These women aged 16-24 years were enrolled in the PrEP in pregnancy and postpartum (PrEP-PP) cohort study during their first ANC visit. Using the PrEP cascade framework, the outcomes of the study were PrEP initiation (prescribed tenofovir disoproxil fumarate and emtricitabine at baseline), continuation (returned for prescription), and persistence [quantifiable tenofovir diphosphate (TFV-DP) in dried blood samples]. The two primary exposures of this study were risk perception for HIV and baseline HIV risk score (0-5), which comprised condomless sex, more than one sexual partner, partner living with HIV or with unknown serostatus, laboratory-confirmed sexually transmitted infections (STIs), and hazardous alcohol use before pregnancy (Alcohol Use Disorders Identification Test for Consumption score ≥ 3). Logistic regression was used to examine the association between HIV risk and PrEP, adjusting for a priori confounders. Results: A total of 486 pregnant women were included in the study, of which 16% were "adolescents" (aged 16-18 years) and 84% were "young women" (aged 19-24 years). The adolescents initiated ANC later than the young women [median = 28 weeks (20-34) vs. 23 weeks (16-34), p = 0.04]. Approximately 41% of the AGYW were diagnosed with sexually transmitted infection at baseline. Overall, 83% of the AGYW initiated PrEP use during their first ANC. The percentage of PrEP continuation was 63% at 1 month, 54% at 3 months, and 39% at 6 months. Approximately 27% consistently continued PrEP use through 6 months, while 6% stopped and restarted on PrEP use at 6 months. With a higher risk score of HIV (≥2 vs. ≤1), the AGYW showed higher odds of PrEP continuation [adjusted odds ratio: 1.85 (95% CI: 1.12-3.03)] through 6 months, adjusting for potential confounders. Undergoing the postpartum period (vs. pregnant) and having lower sexual risk factors were found to be the barriers to PrEP continuation. TFV-DP concentration levels were detected among 49% of the AGYW, and 6% of these women had daily adherence to PrEP at 3 months. Conclusions: AGYW were found to have high oral PrEP initiation, but just over one-third of these women continued PrEP use through 6 months. Pregnant AGYW who had a higher risk of acquiring HIV (due to condomless sex, frequent sex, and STIs) were more likely to continue on PrEP use through the postpartum period. Pregnant and postpartum AGYW require counseling and other types of support, such as community delivery and peer support to improve their effective PrEP use through the postpartum period. Clinical Trial Number: ClinicalTrials.gov, NCT03826199.

The effect of poverty on the relationship between household education levels and obesity in U.S. children and adolescents: an observational study.

Background: Although ample evidence has shown the link between childhood obesity and socioeconomic status including family income and household education levels, the mediating role of poverty in the association between household education levels and childhood obesity is unclear. This study aimed to quantify the extent to which family poverty levels contribute to the association between household education levels and obesity among US children and adolescents. Methods: This cohort study used the nationally representative data of 21,754 US children and adolescents aged 6-17 years (National Health and Nutrition Examination Survey 1999-2018). We applied mediation analysis of the association between household education levels (less than high school, high school, and college or above) and obesity mediated through poverty (≤138% vs. >138% federal poverty level), adjusting for demographic characteristics of household head and their offspring. Obesity was defined as age- and sex-specific body mass index in the 95th percentile or greater using the 2000 Centers for Disease Control and Prevention growth charts. Findings: Among 21,754 children and adolescents (weighted N = 43,544,684; mean age, 11.6 years; female, 49%), 9720 (weighted percentage, 33.0%) were classified as living in poverty and 4671 (weighted percentage, 19.1%) met the criteria for obesity. Low household education level (less than high school) showed increased risks of poverty (adjusted relative risk [95% CI], 5.82 [4.90-6.91]) and obesity (adjusted relative risk [95% CI], 1.94 [1.68-2.25]) compared to high household education level (college or above). We also quantified that poverty mediated 18.9% of the association between household education levels and obesity among children and adolescents. The mediation effect was consistently observed across age, gender, and race/ethnicity. Interpretation: Poverty mediated the association between the low educational status of household heads and their offspring's obesity. Our findings highlight the importance of reducing obesity risk among the low-income population to minimize the burden of intergenerational health disparities due to socioeconomic status. Funding: Japan Society for the Promotion of Sciences (22K17392).

Group vs Individual Prenatal Care and Gestational Diabetes Outcomes: A Secondary Analysis of a Randomized Clinical Trial.

Importance: The impact of group-based prenatal care (GPNC) model in the US on the risk of gestational diabetes (GD) and related adverse obstetric outcomes is unknown. Objective: To determine the effects of the GPNC model on risk of GD, its progression, and related adverse obstetric outcomes. Design, Setting, and Participants: This is a single-site, parallel-group, randomized clinical trial conducted between February 2016 and March 2020 at a large health care system in Greenville, South Carolina. Participants were individuals aged 14 to 45 years with pregnancies earlier than 21 weeks' gestational age; follow-up continued to 8 weeks post partum. This study used an intention-to-treat analysis, and data were analyzed from March 2021 to July 2022. Interventions: Eligible participants were randomized to receive either CenteringPregnancy, a widely used GPNC model, with 10 group-based sessions or traditional individual prenatal care (IPNC). Main Outcomes and Measures: The primary outcome was the incidence of GD diagnosed between 24 and 30 weeks of gestation. The secondary outcomes included progression to A2 GD (ie, GD treated with medications) and GD-related adverse obstetric outcomes (ie, preeclampsia, cesarean delivery, and large for gestational age). Log binomial models were performed to estimate risk differences (RDs), 95% CIs, and P values between GPNC and IPNC groups, adjusting for all baseline covariates. Results: Of all 2348 participants (mean [SD] age, 25.1 [5.4] years; 952 Black participants [40.5%]; 502 Hispanic participants [21.4%]; 863 White participants [36.8%]), 1176 participants were randomized to the GPNC group and 1174 were randomized to the IPNC group. Among all participants, 2144 (91.3%) completed a GD screening (1072 participants [91.3%] in GPNC vs 1071 [91.2%] in IPNC). Overall, 157 participants (6.7%) developed GD, and there was no difference in GD incidence between the GPNC (83 participants [7.1%]) and IPNC (74 participants [6.3%]) groups, with an adjusted RD of 0.7% (95% CI, -1.2% to 2.7%). Among participants with GD, GPNC did not reduce the risk of progression to A2 GD (adjusted RD, -6.1%; 95% CI, -21.3% to 9.1%), preeclampsia (adjusted RD, -7.9%; 95% CI, -17.8% to 1.9%), cesarean delivery (adjusted RD, -8.2%; 95% CI, -12.2% to 13.9%), and large for gestational age (adjusted RD, -1.2%; 95% CI, -6.1% to 3.8%) compared with IPNC. Conclusions and Relevance: In this secondary analysis of a randomized clinical trial among medically low-risk pregnant individuals, the risk of GD was similar between participants who received GPNC intervention and traditional IPNC, indicating that GPNC may be a feasible treatment option for some patients. Trial Registration: ClinicalTrials.gov Identifier: NCT02640638.

Development and validation of a prediction equation for body fat percentage from measured BMI: a supervised machine learning approach.

Body mass index is a widely used but poor predictor of adiposity in populations with excessive fat-free mass. Rigorous predictive models validated specifically in a nationally representative sample of the US population and that could be used for calibration purposes are needed. The objective of this study was to develop and validate prediction equations of body fat percentage obtained from Dual Energy X-ray Absorptiometry using body mass index (BMI) and socio-demographics. We used the National Health and Nutrition Examination Survey (NHANES) data from 5931 and 2340 adults aged 20 to 69 in 1999-2002 and 2003-2006, respectively. A supervised machine learning using ordinary least squares and a validation set approach were used to develop and select best models based on R2 and root mean square error. We compared our findings with other published models and utilized our best models to assess the amount of bias in the association between predicted body fat and elevated low-density lipoprotein (LDL). Three models included BMI, BMI2, age, gender, education, income, and interaction terms and produced R-squared values of 0.87 and yielded the smallest standard errors of estimation. The amount of bias in the association between predicted BF% and elevated LDL from our best model was -0.005. Our models provided strong predictive abilities and low bias compared to most published models. Its strengths rely on its simplicity and its ease of use in low-resource settings.

A comparison of quasi-experimental methods with data before and after an intervention: an introduction for epidemiologists and a simulation study.

BACKGROUND: As the interest in and use of quasi-experimental methods to evaluate impacts of health policies have dramatically increased in the epidemiological literature, we set out this study to (i) systematically compare several quasi-experimental methods that use data before and after an intervention and contrast their performance within a simulation framework while providing a brief overview of the methods; and (ii) discuss challenges that could arise from using these methods as well as directions for future research in the context of epidemiological applications. METHODS: We considered single-group designs [pre-post and interrupted time series (ITS)] and multiple-group designs [controlled interrupted time series/difference-in-differences, synthetic control methods (SCMs): traditional SCMs and generalized SCMs]. We assessed performance based on bias and root mean squared error. RESULTS: We identified settings in which each method failed to provide unbiased estimates. We found that, among the methods investigated, when data for multiple time points and for multiple control groups are available (multiple-group designs), data-adaptive methods such as the generalized SCM were generally less biased than other methods evaluated in our study. In addition, when all of the included units have been exposed to treatment (single-group designs) and data for a sufficiently long pre-intervention period are available, then the ITS performs very well, provided the underlying model is correctly specified. CONCLUSIONS: When using a quasi-experimental method using data before and after an intervention, epidemiologists should strive to use, whenever feasible, data-adaptive methods that nest alternative identifying assumptions including relaxing the parallel trend assumption (e.g. generalized SCMs).

Modeling COVID-19 infection dynamics and mitigation strategies for in-person K-6 instruction.

Background: U.S. school closures due to the coronavirus disease 2019 (COVID-19) pandemic led to extended periods of remote learning and social and economic impact on families. Uncertainty about virus dynamics made it difficult for school districts to develop mitigation plans that all stakeholders consider to be safe. Methods: We developed an agent-based model of infection dynamics and preventive mitigation designed as a conceptual tool to give school districts basic insights into their options, and to provide optimal flexibility and computational ease as COVID-19 science rapidly evolved early in the pandemic. Elements included distancing, health behaviors, surveillance and symptomatic testing, daily symptom and exposure screening, quarantine policies, and vaccination. Model elements were designed to be updated as the pandemic and scientific knowledge evolve. An online interface enables school districts and their implementation partners to explore the effects of interventions on outcomes of interest to states and localities, under a variety of plausible epidemiological and policy assumptions. Results: The model shows infection dynamics that school districts should consider. For example, under default assumptions, secondary infection rates and school attendance are substantially affected by surveillance testing protocols, vaccination rates, class sizes, and effectiveness of safety education. Conclusions: Our model helps policymakers consider how mitigation options and the dynamics of school infection risks affect outcomes of interest. The model was designed in a period of considerable uncertainty and rapidly evolving science. It had practical use early in the pandemic to surface dynamics for school districts and to enable manipulation of parameters as well as rapid update in response to changes in epidemiological conditions and scientific information about COVID-19 transmission dynamics, testing and vaccination resources, and reliability of mitigation strategies.

Importance of Accounting for Regional Differences in Modifiable Risk Factors for Alzheimer's Disease and Related Dementias: The Case for Tailored Interventions.

BACKGROUND: We recently estimated that 36.9% of Alzheimer's disease and related dementias (ADRD) cases in the US may be attributable to modifiable risk factors, but it is not known whether national estimates generalize to specific states or regions. OBJECTIVE: To compare national estimates of modifiable risk factors of ADRD to California, overall and by sex and race/ethnicity, and to estimate number of cases potentially preventable by reducing the prevalence of key risk factors by 25%. METHODS: Adults ≥18 years who participated in the Behavioral Risk Factor Surveillance Survey in California (n = 9,836) and the US (n = 378,615). We calculated population attributable risks (PARs) for eight risk factors (physical inactivity, current smoking, depression, low education, diabetes mellitus, midlife obesity, midlife hypertension, and hearing loss) and compared estimates in California and the U.S. RESULTS: In California, overall, 28.9% of ADRD cases were potentially attributable to the combination of risk factors, compared to 36.9% in the U.S. The top three risk factors were the same in California and the U.S., although their relative importance differed (low education [CA:14.9%; U.S.:11.7% ], midlife obesity [CA:14.9%; U.S.:17.7% ], and physical inactivity [CA:10.3%; U.S.:11.8% ]). The number of ADRD cases attributable to the combined risk factors was 199,246 in California and 2,287,683 in the U.S. If the combined risk factors were reduced by 25%, we could potentially prevent more than 40,000 cases in California and 445,000 cases in the U.S. CONCLUSION: Our findings highlight the importance of examining risk factors of ADRD regionally, and within sex and race/ethnic groups to tailor dementia risk reduction strategies.

Evaluating the impact of community interventions on childhood obesity in populations living in low-income households in Los Angeles: A simulation study.

BACKGROUND: The complex multifactorial nature of childhood obesity makes community interventions difficult to evaluate using traditional approaches; innovative methods are needed. OBJECTIVE: To evaluate the impact of various interventions targeting childhood obesity-related behaviours, and classified as using a micro-level (e.g., home visitation programs) or macro-level (e.g., business practices) strategy, on obesity among children enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). METHODS: We simulated a population of 1500 children enrolled in WIC, with specific diet, physical activity, breastfeeding behaviours and body mass index z-scores (BMIz), following them from age 2 to 5 years. RESULTS: Combined interventions targeting breastfeeding appeared to be moderately effective, reducing BMIz by 0.03 (95% CI -005, -0.01). Two strategy-specific interventions, home visitation programs and business practices targeting obesity-related behaviours, appeared to be moderately effective at reducing BMIz by 0.04 (95% CI -0.06, -0.02) and 0.02 (95% CI -0.04, 0.00), respectively. Contrary to expectation, combining all micro and macro interventions appeared to have no impact or moderately increased the proportion of obesity/overweight among children. CONCLUSION: Interventions targeting breastfeeding behaviour were most effective when both micro and macro strategies were implemented. Interventions targeting obesity-related behaviours in general were effective for two strategies, home visitation and business practices.