Contributors to Excess Infant Mortality in the U.S. South

American Journal of Preventive Medicine
Volume 46, Issue 3 , Pages 219-227, March 20141

Contributors to Excess Infant Mortality in the U.S. South

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Ashley H.Hirai, PhD

William M.Sappenfield, MD, MPH

Michael D.Kogan, PhD

Wanda D.Barfield, MD, MPH

David A.Goodman, PhD

Reem M.Ghandour, DrPH

Michael C.Lu, MD, MPH

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This activity is available for CME credit. See page A3 for information.

Background

Infant mortality rates (IMRs) are disproportionally high in the U.S. South; however, the proximate contributors that could inform regional action remain unclear.

Purpose

To quantify the components of excess infant mortality in the U.S. South by maternal race/ethnicity, underlying cause of death, and gestational age.

Methods

U.S. Period Linked Birth/Infant Death Data Files 2007−2009 (analyzed in 2013) were used to compare IMRs between the South (U.S. Public Health Regions IV and VI) and all other regions combined.

Results

Compared to other regions, there were 1.18 excess infant deaths per 1000 live births in the South, representing about 1600 excess infant deaths annually. New Mexico and Texas did not have elevated IMRs relative to other regions; excess death rates among other states ranged from 0.62 per 1000 in Kentucky to 3.82 per 1000 in Mississippi. Racial/ethnic compositional differences, generally the greater proportion of non-Hispanic black births in the South, explained 59% of the overall regional difference; the remainder was mostly explained by higher IMRs among non-Hispanic whites. The leading causes of excess Southern infant mortality were sudden unexpected infant death (SUID; 36%, range=12% in Florida to 90% in Kentucky) and preterm-related death (22%, range= −71% in Kentucky to 51% in North Carolina). Higher rates of preterm birth, predominantly <34 weeks, accounted for most of the preterm contribution.

Conclusions

To reduce excess Southern infant mortality, comprehensive strategies addressing SUID and preterm birth prevention for both non-Hispanic black and white births are needed, with state-level findings used to tailor state-specific efforts.

Published by Elsevier Inc.

American Journal of Preventive Medicine
Volume 46, Issue 3 , Pages 228-236, March 20142

Understanding Current Racial/Ethnic Disparities in Colorectal Cancer Screening in the United States

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David T.Liss, PhD

David W.Baker, MD, MPH

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Background

Prior studies have shown racial/ethnic disparities in colorectal cancer (CRC) screening but have not provided a full national picture of disparities across all major racial/ethnic groups.

Purpose

To provide a more complete, up-to-date picture of racial/ethnic disparities in CRC screening and contributing socioeconomic and access barriers.

Methods

Behavioral Risk Factor Surveillance System data from 2010 were analyzed in 2013. Hispanic/Latino participants were stratified by preferred language (Hispanic-English versus Hispanic-Spanish). Non-Hispanics were categorized as White, Black, Asian, Native Hawaiian/Pacific Islander, or American Indian/Alaska Native. Sequential regression models estimated adjusted relative risks (RRs) and the degree to which SES and access to care explained disparities.

Results

Overall, 59.6% reported being up-to-date on CRC screening. Self-reported CRC screening was highest in the White (62.0%) racial/ethnic group; followed by Black (59.0%); Native Hawaiian/Pacific Islander (54.6%); Hispanic-English (52.5%); American Indian/Alaska Native (49.5%); Asian (47.2%); and Hispanic-Spanish (30.6%) groups. Adjustment for SES and access partially explained disparities between Whites and Hispanic-Spanish (final relative risk [RR]=0.76, 95% CI=0.69, 0.83); Hispanic-English (RR=0.94, 95% CI=0.91, 0.98); and American Indian/Alaska Native (RR=0.91, 95% CI=0.85, 0.97) groups. The RR of screening among Asians was unchanged after adjustment for SES and access (0.78, p<0.001). After full adjustment, screening rates were not significantly different among Whites, Blacks, or Native Hawaiian/Pacific Islanders.

Conclusions

Large racial/ethnic disparities in CRC screening persist, including substantial differences between English-speaking versus Spanish-speaking Hispanics. Disparities are only partially explained by SES and access to care. Future studies should explore the low rate of screening among Asians and how it varies by racial/ethnic subgroup and language.

American Journal of Preventive Medicine
Volume 46, Issue 3 , Pages 237-248, March 20143

Prevalence of Obesity Among U.S. Workers and Associations with Occupational Factors

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Sara E.Luckhaupt, MD, MPH

Martha A.Cohen, PhD

JiaLi, MS

Geoffrey M.Calvert, MD, MPH

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This activity is available for CME credit. See page A4 for information.

Background

Along with public health and clinical professionals, employers are taking note of rising obesity rates among their employees, as obesity is strongly related to chronic health problems and concomitant increased healthcare costs. Contributors to the obesity epidemic are complex and numerous, and may include several work characteristics.

Purpose

To explore associations between occupational factors and obesity among U.S. workers.

Methods

Data from the 2010 National Health Interview Survey were utilized to calculate weighted prevalence rates and prevalence ratios (PRs) for obesity in relation to workweek length, work schedule, work arrangement, hostile work environment, job insecurity, work–family imbalance, and industry and occupation of employment. Data were collected in 2010 and analyzed in 2012−2013.

Results

Overall, 27.7% of U.S. workers met the BMI criterion for obesity. Among all workers, employment for more than 40 hours per week and exposure to a hostile work environment were significantly associated with an increased prevalence of obesity, although the differences were modest. Employment in health care and social assistance and public administration industries, as well as architecture and engineering, community and social service, protective service, and office and administrative support occupations was also associated with increased obesity prevalence.

Conclusions

Work-related factors may contribute to the high prevalence of obesity in the U.S. working population. Public health professionals and employers should consider workplace interventions that target organization-level factors, such as scheduling and prevention of workplace hostility, along with individual-level factors such as diet and exercise.

Published by Elsevier Inc.

American Journal of Preventive Medicine
Volume 46, Issue 3 , Pages 259-264, March 20144

Declines in Elevated Blood Lead Levels Among Children, 1997−2011

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Byron S.Kennedy, MD, PhD, MPH

Andrew S.Doniger, MD, MPH

SusanPainting, BS

LeeHouston, BS

MichaelSlaunwhite, BS

FrankMirabella, BS

JohnFelsen, MPH

PaulHunt, BS

DawnHyde, BS

EarlStich, BS

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Background

Early childhood lead exposure is associated with numerous adverse health effects. Eliminating blood lead poisoning is a national health objective for 2020.

Objective

To assess temporal trends in childhood elevated blood lead level (EBLL) rates.

Methods

Laboratory surveillance data were collected from 1997 to 2011 and analyzed in 2013 using linear regression to assess trends in confirmed EBLL rates among children aged <6 years in the U.S., New York State ([NYS], excluding New York City), and Monroe County NY. Monroe County was also examined as a case study of local public health efforts to reduce childhood lead exposures. Blood lead screening and home lead hazard inspection data were collected from 1990 to 2012 and analyzed in 2013.

Results

The prevalence of EBLL≥10 μg/dL per 100 tested children decreased from 13.4 to 1.1 in Monroe County, 6.3 to 1.0 in NYS, and 7.6 to 0.6 in the U.S. between 1997 and 2011. The absolute yearly rate of decline in Monroe County (slope=−0.0083, p<0.001) occurred 2.4-fold faster than that in NYS (slope=−0.0034, p<0.001) and 1.8-fold faster than that in the U.S. (slope=−0.0046, p<0.001). The childhood blood lead testing rate was consistently higher in Monroe County than in NYS and the U.S.; however, testing increased for all three areas (all slopes>0, p<0.05), with greater improvements observed for U.S. children overall (slope=0.0075, p<0.001).

Conclusions

In addition to national and statewide policies, local efforts may be important drivers of population-based declines in childhood EBLL rates.

American Journal of Preventive Medicine
Volume 46, Issue 3 , Pages 265-272, March 20145

Health Care Costs Associated with Prolonged Sitting and Inactivity

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G.M.E.E. (Geeske)Peeters, PhD

Gita D.Mishra, PhD

Annette J.Dobson, PhD

Wendy J.Brown, PhD

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Background

Physical inactivity and prolonged sitting are associated with negative health outcomes.

Purpose

To examine the health-related costs of prolonged sitting and inactivity in middle-aged women.

Methods

Australian Longitudinal Study on Women’s Health participants (born 1946−1951) answered questions about time spent sitting, walking, and in moderate and vigorous leisure activities in 2001 (n=6108); 2004 (n=5902); 2007 (n=5754); and 2010 (n=5535) surveys. Sitting time was categorized as low (0−4); moderate (5−7); and high (≥8 hours/day). Physical activity was categorized as inactive (<40); low (40−600); moderate (600−1200); and high (≥1200 MET-minutes/week). National health insurance claims data averaged over the survey year ±1 year were used to calculate annual costs (Australian dollars [AU$]). Differences between categories in median costs were estimated using quantile regression over four surveys with bootstrapped 95% CIs. Analyses were performed in 2013.

Results

In 2010, annual median costs were AU$689 (interquartile range [IQR]=274, 1541) in highly active participants; AU$741 (IQR=279, 1690) in inactive participants; AU$671 (IQR=273, 1551) in participants with low sitting time; and AU$709 (IQR=283, 1575) in participants with high sitting time. The difference in median costs for inactive and highly active participants was AU$94 (CI=57, 131) after adjustment for confounders. No statistically significant associations were found between sitting time and costs. When sitting and physical activity were combined, high sitting time did not add to the inactivity-associated increased costs. Associations were consistent across normal-weight, overweight, and obese subgroups.

Conclusions

Physical inactivity, but not prolonged sitting, was associated with higher health-related costs in middle-aged women.