Burden and risk factors for antenatal depression and its effect on preterm birth in South Asia: A population-based cohort study
Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth. The study uses the following data: matern...
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| Vydáno v: | PloS one Ročník 17; číslo 2; s. e0263091 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
Public Library of Science
07.02.2022
Public Library of Science (PLoS) |
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth.
The study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9-question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman's age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband's education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of ≥12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP).
About 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of ≥2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02-1.74).
The increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. |
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| AbstractList | Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth. The study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9-question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman's age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband's education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of [greater than or equal to]12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP). About 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of [greater than or equal to]2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02-1.74). The increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. Introduction Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth. Methods The study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9-question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman's age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband's education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of [greater than or equal to]12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP). Results About 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of [greater than or equal to]2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02-1.74). Conclusion The increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. Introduction Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth. Methods The study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9–question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman’s age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband’s education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of ≥12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP). Results About 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of ≥2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02–1.74). Conclusion The increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. IntroductionWomen experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth.MethodsThe study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9-question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman's age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband's education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of ≥12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP).ResultsAbout 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of ≥2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02-1.74).ConclusionThe increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth.INTRODUCTIONWomen experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth.The study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9-question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman's age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband's education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of ≥12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP).METHODSThe study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9-question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman's age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband's education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of ≥12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP).About 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of ≥2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02-1.74).RESULTSAbout 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of ≥2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02-1.74).The increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors.CONCLUSIONThe increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. Introduction Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth. Methods The study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9–question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman’s age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband’s education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of ≥12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP). Results About 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of ≥2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02–1.74). Conclusion The increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan, we estimated the burden of antenatal depression, its risk factors, and its effect on preterm birth. The study uses the following data: maternal depression measured between 24 and 28 weeks of gestation using the 9-question Patient Health Questionnaire (PHQ-9); data on pregnancy including an ultrasound before 19 weeks of gestation; data on pregnancy outcomes; and data on woman's age, education, parity, weight, height, history of previous illness, prior miscarriage, stillbirth, husband's education, and household socioeconomic data collected during early pregnancy. Using PHQ-9 cutoff score of ≥12, women were categorized into none to mild depression or moderate to moderately severe depression. Using ultrasound data, preterm birth was defined as babies born <37 weeks of gestation. To identify risk ratios (RR) for antenatal depression, unadjusted and adjusted RR and 95% confidence intervals (CI) were calculated using log- binomial model. Log-binomial models were also used for determining the effect of antenatal depression on preterm birth adjusting for potential confounders. Data were analyzed using Stata version 16 (StataCorp LP). About 6% of the women reported moderate to moderately severe depressive symptoms during the antenatal period. A parity of ≥2 and the highest household wealth status were associated with an increased risk of depression. The overall incidence of preterm birth was 13.4%. Maternal antenatal depression was significantly associated with the risk of preterm birth (ARR, 95% CI: 1.34, 1.02-1.74). The increased risk of preterm birth in women with antenatal depression in conjunction with other significant risk factors suggests that depression likely occurs within a constellation of other risk factors. Thus, to effectively address the burden of preterm birth, programs require developing and providing integrated care addressing multiple risk factors. |
| Audience | Academic |
| Author | Rahman, Sayedur Nizar, Ambreen Ahmed, Salahuddin Ali, Said Mohammed Muhammad, Sajid Bahl, Rajiv Mehmood, Usma Begum, Farzana Khanam, Rasheda Deb, Saikat Das, Sayan Minckas, Nicole Sazawal, Sunil Yoshida, Sachiyo Baqui, Abdullah H. Mittal, Harshita Applegate, Jennifer Dhingra, Usha Chowdhury, Nabidul Haque Nisar, Imran Ahmed, Saifuddin Jehan, Fyezah Dutta, Arup Tofail, Fahmida |
| AuthorAffiliation | 2 Aga Khan University, Department of Paediatrics and Child Health, Karachi, Sindh, Pakistan 4 Projahnmo Research Foundation, Abanti, Banani, Dhaka, Bangladesh 7 Department of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America 1 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America Texas A&M University College Station, UNITED STATES 3 Center for Public Health Kinetics, Global Division, New Delhi, India 8 World Health Organization (MCA/MRD), Geneva, Switzerland 5 Public Health Laboratory-IDC, Chake Chake, Pemba, Tanzania 6 International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh |
| AuthorAffiliation_xml | – name: 1 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America – name: 8 World Health Organization (MCA/MRD), Geneva, Switzerland – name: 6 International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh – name: 7 Department of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America – name: 2 Aga Khan University, Department of Paediatrics and Child Health, Karachi, Sindh, Pakistan – name: 4 Projahnmo Research Foundation, Abanti, Banani, Dhaka, Bangladesh – name: 5 Public Health Laboratory-IDC, Chake Chake, Pemba, Tanzania – name: 3 Center for Public Health Kinetics, Global Division, New Delhi, India – name: Texas A&M University College Station, UNITED STATES |
| Author_xml | – sequence: 1 givenname: Rasheda orcidid: 0000-0002-9365-8594 surname: Khanam fullname: Khanam, Rasheda – sequence: 2 givenname: Jennifer surname: Applegate fullname: Applegate, Jennifer – sequence: 3 givenname: Imran surname: Nisar fullname: Nisar, Imran – sequence: 4 givenname: Arup surname: Dutta fullname: Dutta, Arup – sequence: 5 givenname: Sayedur orcidid: 0000-0002-4445-3699 surname: Rahman fullname: Rahman, Sayedur – sequence: 6 givenname: Ambreen surname: Nizar fullname: Nizar, Ambreen – sequence: 7 givenname: Said Mohammed surname: Ali fullname: Ali, Said Mohammed – sequence: 8 givenname: Nabidul Haque surname: Chowdhury fullname: Chowdhury, Nabidul Haque – sequence: 9 givenname: Farzana surname: Begum fullname: Begum, Farzana – sequence: 10 givenname: Usha surname: Dhingra fullname: Dhingra, Usha – sequence: 11 givenname: Fahmida surname: Tofail fullname: Tofail, Fahmida – sequence: 12 givenname: Usma surname: Mehmood fullname: Mehmood, Usma – sequence: 13 givenname: Saikat surname: Deb fullname: Deb, Saikat – sequence: 14 givenname: Salahuddin surname: Ahmed fullname: Ahmed, Salahuddin – sequence: 15 givenname: Sajid surname: Muhammad fullname: Muhammad, Sajid – sequence: 16 givenname: Sayan surname: Das fullname: Das, Sayan – sequence: 17 givenname: Saifuddin surname: Ahmed fullname: Ahmed, Saifuddin – sequence: 18 givenname: Harshita surname: Mittal fullname: Mittal, Harshita – sequence: 19 givenname: Nicole surname: Minckas fullname: Minckas, Nicole – sequence: 20 givenname: Sachiyo orcidid: 0000-0002-1101-8535 surname: Yoshida fullname: Yoshida, Sachiyo – sequence: 21 givenname: Rajiv surname: Bahl fullname: Bahl, Rajiv – sequence: 22 givenname: Fyezah surname: Jehan fullname: Jehan, Fyezah – sequence: 23 givenname: Sunil surname: Sazawal fullname: Sazawal, Sunil – sequence: 24 givenname: Abdullah H. surname: Baqui fullname: Baqui, Abdullah H. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35130270$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2022 Public Library of Science 2022 Khanam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2022 Khanam et al 2022 Khanam et al |
| Copyright_xml | – notice: COPYRIGHT 2022 Public Library of Science – notice: 2022 Khanam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2022 Khanam et al 2022 Khanam et al |
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| DOI | 10.1371/journal.pone.0263091 |
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| DocumentTitleAlternate | Antenatal depression and preterm birth |
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| Snippet | Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh and Pakistan,... Introduction Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh... IntroductionWomen experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh... Introduction Women experience high rates of depression, particularly during pregnancy and the postpartum periods. Using population-based data from Bangladesh... |
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| SubjectTerms | Adult Asia - epidemiology Bangladesh - epidemiology Birth Childrens health Cohort analysis Cohort Studies Confidence intervals Depression - complications Depression - epidemiology Diabetes Education Female Gestation Health risks Health surveillance Humans Infant, Newborn Infants (Premature) Medical laboratories Medicine and Health Sciences Mental depression Pakistan - epidemiology Parity Pediatrics Population Population studies Population-based studies Postpartum depression Postpartum period Pregnancy Pregnancy Complications - epidemiology Pregnancy Complications - psychology Pregnancy Outcome - epidemiology Pregnancy Outcome - psychology Premature birth Premature Birth - epidemiology Prenatal Care - statistics & numerical data Prenatal depression Psychological aspects Public health Risk analysis Risk Factors Socioeconomics Ultrasound Womens health Young Adult |
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| Title | Burden and risk factors for antenatal depression and its effect on preterm birth in South Asia: A population-based cohort study |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/35130270 https://www.proquest.com/docview/2626214399 https://www.proquest.com/docview/2626891972 https://pubmed.ncbi.nlm.nih.gov/PMC8820649 https://doaj.org/article/f7d5c1efab1b43dab716aee35b7d4926 http://dx.doi.org/10.1371/journal.pone.0263091 |
| Volume | 17 |
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