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Zhao L, Wang Y, Bawa EM, Meng Z, Wei J, Newman-Norlund S, Trivedi T, Hasturk H, Newman-Norlund RD, Fridriksson J, Merchant AT. Identifying a group of factors predicting cognitive impairment among older adults. PLoS One 2024; 19:e0301979. [PMID: 38603668 PMCID: PMC11008866 DOI: 10.1371/journal.pone.0301979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 03/26/2024] [Indexed: 04/13/2024] Open
Abstract
BACKGROUND Cognitive impairment has multiple risk factors spanning several domains, but few studies have evaluated risk factor clusters. We aimed to identify naturally occurring clusters of risk factors of poor cognition among middle-aged and older adults and evaluate associations between measures of cognition and these risk factor clusters. METHODS We used data from the National Health and Nutrition Examination Survey (NHANES) III (training dataset, n = 4074) and the NHANES 2011-2014 (validation dataset, n = 2510). Risk factors were selected based on the literature. We used both traditional logistic models and support vector machine methods to construct a composite score of risk factor clusters. We evaluated associations between the risk score and cognitive performance using the logistic model by estimating odds ratios (OR) and 95% confidence intervals (CI). RESULTS Using the training dataset, we developed a composite risk score that predicted undiagnosed cognitive decline based on ten selected predictive risk factors including age, waist circumference, healthy eating index, race, education, income, physical activity, diabetes, hypercholesterolemia, and annual visit to dentist. The risk score was significantly associated with poor cognitive performance both in the training dataset (OR Tertile 3 verse tertile 1 = 8.15, 95% CI: 5.36-12.4) and validation dataset (OR Tertile 3 verse tertile 1 = 4.31, 95% CI: 2.62-7.08). The area under the receiver operating characteristics curve for the predictive model was 0.74 and 0.77 for crude model and model adjusted for age, sex, and race. CONCLUSION The model based on selected risk factors may be used to identify high risk individuals with cognitive impairment.
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Affiliation(s)
- Longgang Zhao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Yuan Wang
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Eric Mishio Bawa
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Zichun Meng
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Jingkai Wei
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Sarah Newman-Norlund
- Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Tushar Trivedi
- Regional Medical Center Primary Care Stroke, Orangeburg, SC, United States of America
| | - Hatice Hasturk
- Center for Clinical and Translational Research, Forsyth Institute, Boston, MA, United States of America
| | - Roger D. Newman-Norlund
- Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Julius Fridriksson
- Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Anwar T. Merchant
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
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Lohman MC, Wei J, Bawa EM, Fallahi A, Verma M, Merchant AT. Longitudinal Associations of Diet, Food Insecurity, and Supplemental Nutrition Assistance Program Use with Global Cognitive Performance in Middle-Aged and Older Adults. J Nutr 2024; 154:714-721. [PMID: 38158186 DOI: 10.1016/j.tjnut.2023.12.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/29/2023] [Accepted: 12/26/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Diet quality, food access, and food assistance policies may be key modifiable factors related to cognitive decline. OBJECTIVE We aimed to evaluate whether diet quality, food insecurity, and Supplemental Nutrition Assistance Program (SNAP) use are associated with longitudinal changes in cognition among older adults in the United States. METHODS Food intake data from the Health Care and Nutrition Study were linked with longitudinal health information from 5 waves of the Health and Retirement Study (2012-2020). The analytic sample (n = 6968) included community-dwelling United States adults aged ≥51 y without cognitive impairment. Global cognition was measured using a telephone-based cognitive status interview (range: 0-27). Diet quality was measured with the Healthy Eating Index, using participants' average intake of 13 dietary components. Questions regarding food access and affordability were used to determine food insecurity and use of SNAP benefits. Linear mixed-effects regression models were used to estimate longitudinal associations between diet-related factors and cognitive score changes. RESULTS Poorer diets [β: -0.24; 95% confidence interval (CI): -0.33, -0.15], food insecurity (β: -1.08; 95% CI: -1.31, -0.85), and SNAP use (β: -0.57; 95% CI: -0.82, -0.32) were associated with lower baseline cognitive scores. Poorer diets (β: -0.17; 95% CI: -0.29, -0.05) and food insecurity (β: -0.23; 95% CI: -0.47, -0.01) were associated with significantly steeper declines in cognitive scores over time, after 8 and 2 y of follow-up, respectively; however, SNAP use was not significantly associated with the rate of cognitive decline over time. Estimates were qualitatively similar when restricting the sample to participants aged ≥65 y. CONCLUSIONS Results suggest that food access and adherence to healthy diet recommendations may be important elements to maintain cognitive health in aging. SNAP benefits may be insufficient to prevent negative cognitive effects of poor diet and limited access to nutritious foods.
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Affiliation(s)
- Matthew C Lohman
- Department of Epidemiology and Biostatistics, University of South Carolina, Arnold School of Public Health, Columbia, SC, United States.
| | - Jingkai Wei
- Department of Epidemiology and Biostatistics, University of South Carolina, Arnold School of Public Health, Columbia, SC, United States
| | - Eric Mishio Bawa
- Department of Epidemiology and Biostatistics, University of South Carolina, Arnold School of Public Health, Columbia, SC, United States
| | - Afsaneh Fallahi
- Department of Epidemiology and Biostatistics, University of South Carolina, Arnold School of Public Health, Columbia, SC, United States
| | - Mansi Verma
- Department of Epidemiology and Biostatistics, University of South Carolina, Arnold School of Public Health, Columbia, SC, United States
| | - Anwar T Merchant
- Department of Epidemiology and Biostatistics, University of South Carolina, Arnold School of Public Health, Columbia, SC, United States
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Merchant AT, Zhao L, Bawa EM, Yi F, Vidanapathirana NP, Lohman M, Zhang J. Association between clusters of antibodies against periodontal microorganisms and Alzheimer disease mortality: Evidence from a nationally representative survey in the USA. J Periodontol 2024; 95:84-90. [PMID: 37452709 PMCID: PMC10788377 DOI: 10.1002/jper.23-0006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 06/26/2023] [Accepted: 07/09/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Alzheimer disease (AD) has been linked with periodontal microorganisms such as Porphyromonas gingivalis in observational and mechanistic studies. IgG antibodies against periodontal microorganisms which are markers of past and current periodontal infection have been correlated with cognitive impairment. We examined associations between empirically derived groups of 19 IgG antibodies against periodontal microorganisms and AD mortality. METHODS Individuals participating in the Third National Health and Nutrition Examination Survey (NHANES III) with complete data on IgG titers were followed up between 1988 and December 31, 2019. The outcome was AD mortality, and the main exposures were IgG antibodies against periodontal microorganisms classified into four mutually exclusive groups using cluster analysis. Survey-weighted Cox proportional hazard models were used to evaluate adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for the relationship between clusters and AD mortality. RESULTS With up to 21 years of follow-up, 160 AD-related deaths were documented. In the multivariable-adjusted model, AD mortality overall was not associated with the Red-Green (aHR 1.18; 95% CI, 0.46-3.07), Yellow-Orange (aHR 1.36; 95% CI, 0.58-3.19), Orange-Blue (aHR 0.63; 95%, CI, 0.33-1.21), and the Orange-Red (aHR 0.79; 95% CI, 0.37-1.70) when the upper tertiles were compared to the bottom tertiles. However, the subgroup of middle-aged individuals in the highest tertile of the Red-Green cluster, but not older individuals, had a 13% higher risk of AD mortality (aHR 1.13; 95% CI, 1.02-1.26) compared with those in the bottom tertile. CONCLUSION Clusters of IgG antibodies against periodontal microorganisms did not predict AD mortality in this study.
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Affiliation(s)
- Anwar T Merchant
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Longgang Zhao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Eric Mishio Bawa
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Fanli Yi
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Nadeesha P Vidanapathirana
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Matthew Lohman
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Jiajia Zhang
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
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Akonde M, Mishio Bawa E, Dakurah OB, Das Gupta R. Impact of family history of cancer on colorectal cancer screening: a propensity score-matched analysis from the Health Information National Trends Survey (HINTS). J Egypt Natl Canc Inst 2023; 35:38. [PMID: 38072859 DOI: 10.1186/s43046-023-00201-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/29/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Early detection of colon cancer leads to better survival outcomes. This can be achieved through colorectal cancer (CRC) screening. People with a family history of cancer (FHC) have increased risk of developing CRC. Increasing screening in this group will reduce CRC mortality. This study evaluated CRC screening in people with FHC. METHODS The study used data from the Health Information National Trends Survey (HINTS) 5, cycle 3. This is an annual cross-sectional survey with a nationally representative sample of American adults. The objective was to study the association between FHC and performing CRC screening. Propensity score matching was used to create a matched population with variables that constituted beliefs in cancer from the survey. Replication procedure, which is based on repeated sampling and allows for accurate computation of standard errors, was used for calculating statistical tests. Multivariable models were fitted in the matched population to assess the association between FHC and performing CRC screening. RESULTS People with FHC were 14% (OR = 1.14; 95% CI: 0.81-1.60) more likely to perform CRC screening than those without FHC, even though not statistically significant. Age in years (OR = 1.14; 95% CI: 1.12-5.27) had increased likelihood of performing CRC screening, while other races such as American Indians/Alaskan Natives (except African Americans) compared to Caucasians (OR = 0.49; 95% CI: 0.29-0.84) had significantly decreased likelihood of performing CRC screening. CONCLUSION FHC was not significantly associated with having a colorectal cancer screening test. Public health advocacy should be directed towards increasing awareness of CRC screening among people with FHC.
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Affiliation(s)
- Maxwell Akonde
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
| | - Eric Mishio Bawa
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Ottovon Bismark Dakurah
- Center for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Rajat Das Gupta
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
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Liu J, Zhao L, Zhao X, Bawa EM, Alston K, Karim S, Merchant AT, Tang J, Wilcox S. Impact of a Large Healthy Start Program on Perinatal Outcomes, South Carolina, 2009-2019. Am J Public Health 2023; 113:509-513. [PMID: 36893369 PMCID: PMC10088942 DOI: 10.2105/ajph.2023.307232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
Using linked birth and death certificates for participants served by a Healthy Start program in South Carolina and community controls, we found that the Healthy Start program contributed to significant improvements in prenatal care, breastfeeding initiation, and participation in the Special Supplemental Nutrition Program for Women, Infants, and Children and significant reductions in inadequate weight gain and large-for-gestational-age births. However, Healthy Start participants were more likely to gain excessive weight during pregnancy, and there were no significant differences in perinatal outcomes. (Am J Public Health. Published online ahead of print March 9, 2023:e1-e5. https://doi.org/10.2105/AJPH.2023.307232).
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Affiliation(s)
- Jihong Liu
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Longgang Zhao
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Xingpei Zhao
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Eric Mishio Bawa
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Kimberly Alston
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Sabrina Karim
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Anwar T Merchant
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Jun Tang
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
| | - Sara Wilcox
- Jihong Liu, Longgang Zhao, Xingpei Zhao, Eric Mishio Bawa, Sabrina Karim, and Anwar T. Merchant are with the Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. Kimberly Alston is with Midlands Healthy Start, Prisma Health, Columbia, SC. Jun Tang is with the Division of Biostatistics, South Carolina Department of Health and Environmental Control, Columbia. Sara Wilcox is with the Department of Exercise Science and the Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia
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Lohman MC, Fallahi A, Mishio Bawa E, Wei J, Merchant AT. Social Mediators of the Association Between Depression and Falls Among Older Adults. J Aging Health 2023:8982643231152276. [PMID: 36633960 DOI: 10.1177/08982643231152276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
OBJECTIVES To investigate the role of social factors in the association between depression and falls among older adults. METHODS The sample included data from 3443 older adults from three waves of the Health and Retirement Study (2010-2014). A Lifestyle Questionnaire was used to measure social engagement, social network contact, and neighborhood social context. Mediating effects of social factors were estimated through causal mediation analysis. Results: Poorer social engagement and network contact were associated with greater likelihood of falls, while poorer neighborhood context was associated with greater likelihood of fall injuries. Social engagement mediated a significant portion of the effect of depression on falls (OR: 1.03, 95% CI: 1.00, 1.06), and neighborhood context mediated a portion of the effect of depression on fall injuries (OR: 1.03, 95% CI: 1.00, 1.07). Discussion: The direct and indirect impacts of social factors suggest that considering them may help improve existing fall prevention approaches.
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Affiliation(s)
- Matthew C Lohman
- Department of Epidemiology and Biostatistics, 2629University of South Carolina, Arnold School of Public Health, Columbia, SC, USA
| | - Afsaneh Fallahi
- Department of Epidemiology and Biostatistics, 2629University of South Carolina, Arnold School of Public Health, Columbia, SC, USA
| | - Eric Mishio Bawa
- Department of Epidemiology and Biostatistics, 2629University of South Carolina, Arnold School of Public Health, Columbia, SC, USA
| | - Jingkai Wei
- Department of Epidemiology and Biostatistics, 2629University of South Carolina, Arnold School of Public Health, Columbia, SC, USA
| | - Anwar T Merchant
- Department of Epidemiology and Biostatistics, 2629University of South Carolina, Arnold School of Public Health, Columbia, SC, USA
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Antuamwine BB, Herchel ED, Bawa EM. Comparative prevalence of hepatitis B virus infection among pregnant women accessing free maternal care in a tertiary hospital in Ghana. PLoS One 2022; 17:e0263651. [PMID: 35245287 PMCID: PMC8896678 DOI: 10.1371/journal.pone.0263651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 01/24/2022] [Indexed: 11/20/2022] Open
Abstract
Hepatitis B virus infection is endemic in sub-Saharan Africa, and accounts for a significant proportion of morbidities and mortalities in Ghana. Infection with HBV during pregnancy can result in life-threatening complications to both mother and child. To improve their quality of life, the free maternal care was introduced to grant pregnant women cost-free access to antenatal and postnatal services. The study analysed the prevalence of HBV infection among pregnant women receiving free antenatal care in a tertiary hospital in Ghana. This was a retrospective cross-sectional study, where secondary data of pregnant women who accessed free antenatal services at the Trafalga hospital, Ho, from 2016 to 2017 were retrieved from the hospital's database. Data on hepatitis B surface antigen reactivity test, age and period of turnout were analysed with Microsoft Excel and Graph pad prism version 6. A total of 2,634 pregnant women assessed free antenatal care from January 2016 -December 2017, with 10% rise in turnout in 2017. The age of the study population was fairly young, ranging from 13-52 years and mean of 29.87±5.83. The prevalence of HBV infection among pregnant women in the entire study was estimated to be 6.0%, while that of 2016 and 2017 were 5.3% and 6.7% respectively. Turnout for antenatal services peaked in July, which also recorded the highest prevalence of HBV infection among the pregnant women. Our study, first of its kind show an HBV prevalence of 6.0% among a large population of pregnant women who accessed free antenatal services at a tertiary hospital in Ghana. The study evaluates the influence of the free maternal care policy on antenatal attendance and HBV infection rates among pregnant women.
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Affiliation(s)
- Benedict Boateng Antuamwine
- Department of Biomedical Laboratory Sciences, School of Allied Health Sciences, University for Development Studies, Tamale, Ghana
| | - Eddie Delali Herchel
- Department of Biomedical Laboratory Sciences, School of Allied Health Sciences, University for Development Studies, Tamale, Ghana
| | - Eric Mishio Bawa
- Department of Biomedical Laboratory Sciences, School of Allied Health Sciences, University for Development Studies, Tamale, Ghana
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