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      Weight gain in pregnancy and infant birthweight after the onset of the COVID-19 pandemic: an interrupted time series analysis

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          Abstract

          Background

          Increased weight gain and decreased physical activity have been reported in some populations since the coronavirus disease 2019 (COVID-19) pandemic, but this has not been well characterized in pregnant populations.

          Objectives

          Our objective was to characterize the impact of the COVID-19 pandemic and associated countermeasures on pregnancy weight gain and infant birthweight in a US cohort.

          Methods

          Washington State pregnancies and births (1 January, 2016 to 28 December, 2020) from a multihospital quality improvement organization were examined for pregnancy weight gain, pregnancy weight gain z-score adjusted for pregestational BMI and gestational age, and infant birthweight z-score, using an interrupted time series design that controls for underlying time trends. We used mixed-effect linear regression models, controlled for seasonality and clustered at the hospital level, to model the weekly time trends and changes on 23 March, 2020, the onset of local COVID-19 countermeasures.

          Results

          Our analysis included 77,411 pregnant people and 104,936 infants with complete outcome data. The mean pregnancy weight gain was 12.1 kg ( z-score: −0.14) during the prepandemic time period (March to December 2019) and increased to 12.4 kg ( z-score: −0.09) after the onset of the pandemic (March to December 2020). Our time series analysis found that after the pandemic onset, the mean weight gain increased by 0.49 kg (95% CI: 0.25, 0.73 kg) and weight gain z-score increased by 0.080 (95% CI: 0.03, 0.13), with no changes in the baseline yearly trend. Infant birthweight z-scores were unchanged (−0.004; 95% CI: −0.04, 0.03). Overall, the results were unchanged in analyses stratified by pregestational BMI categories.

          Conclusions

          We observed a modest increase in weight gain after the onset of the pandemic among pregnant people but no changes in infant birthweights. This weight change could be more important in high BMI subgroups.

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          Most cited references60

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          A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)

          COVID-19 has prompted unprecedented government action around the world. We introduce the Oxford COVID-19 Government Response Tracker (OxCGRT), a dataset that addresses the need for continuously updated, readily usable and comparable information on policy measures. From 1 January 2020, the data capture government policies related to closure and containment, health and economic policy for more than 180 countries, plus several countries' subnational jurisdictions. Policy responses are recorded on ordinal or continuous scales for 19 policy areas, capturing variation in degree of response. We present two motivating applications of the data, highlighting patterns in the timing of policy adoption and subsequent policy easing and reimposition, and illustrating how the data can be combined with behavioural and epidemiological indicators. This database enables researchers and policymakers to explore the empirical effects of policy responses on the spread of COVID-19 cases and deaths, as well as on economic and social welfare.
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            Is Open Access

            Interrupted time series regression for the evaluation of public health interventions: a tutorial

            Abstract Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.
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              Effects of the COVID-19 pandemic on maternal and perinatal outcomes: a systematic review and meta-analysis

              Background The COVID-19 pandemic has had a profound impact on health-care systems and potentially on pregnancy outcomes, but no systematic synthesis of evidence of this effect has been undertaken. We aimed to assess the collective evidence on the effects on maternal, fetal, and neonatal outcomes of the pandemic. Methods We did a systematic review and meta-analysis of studies on the effects of the pandemic on maternal, fetal, and neonatal outcomes. We searched MEDLINE and Embase in accordance with PRISMA guidelines, from Jan 1, 2020, to Jan 8, 2021, for case-control studies, cohort studies, and brief reports comparing maternal and perinatal mortality, maternal morbidity, pregnancy complications, and intrapartum and neonatal outcomes before and during the pandemic. We also planned to record any additional maternal and offspring outcomes identified. Studies of solely SARS-CoV-2-infected pregnant individuals, as well as case reports, studies without comparison groups, narrative or systematic literature reviews, preprints, and studies reporting on overlapping populations were excluded. Quantitative meta-analysis was done for an outcome when more than one study presented relevant data. Random-effects estimate of the pooled odds ratio (OR) of each outcome were generated with use of the Mantel-Haenszel method. This review was registered with PROSPERO (CRD42020211753). Findings The search identified 3592 citations, of which 40 studies were included. We identified significant increases in stillbirth (pooled OR 1·28 [95% CI 1·07–1·54]; I 2=63%; 12 studies, 168 295 pregnancies during and 198 993 before the pandemic) and maternal death (1·37 [1·22–1·53; I 2=0%, two studies [both from low-income and middle-income countries], 1 237 018 and 2 224 859 pregnancies) during versus before the pandemic. Preterm births before 37 weeks' gestation were not significantly changed overall (0·94 [0·87–1·02]; I 2=75%; 15 studies, 170 640 and 656 423 pregnancies) but were decreased in high-income countries (0·91 [0·84–0·99]; I 2=63%; 12 studies, 159 987 and 635 118 pregnancies), where spontaneous preterm birth was also decreased (0·81 [0·67–0·97]; two studies, 4204 and 6818 pregnancies). Mean Edinburgh Postnatal Depression Scale scores were higher, indicating poorer mental health, during versus before the pandemic (pooled mean difference 0·42 [95% CI 0·02–0·81; three studies, 2330 and 6517 pregnancies). Surgically managed ectopic pregnancies were increased during the pandemic (OR 5·81 [2·16–15·6]; I 2=26%; three studies, 37 and 272 pregnancies). No overall significant effects were identified for other outcomes included in the quantitative analysis: maternal gestational diabetes; hypertensive disorders of pregnancy; preterm birth before 34 weeks', 32 weeks', or 28 weeks' gestation; iatrogenic preterm birth; labour induction; modes of delivery (spontaneous vaginal delivery, caesarean section, or instrumental delivery); post-partum haemorrhage; neonatal death; low birthweight (<2500 g); neonatal intensive care unit admission; or Apgar score less than 7 at 5 min. Interpretation Global maternal and fetal outcomes have worsened during the COVID-19 pandemic, with an increase in maternal deaths, stillbirth, ruptured ectopic pregnancies, and maternal depression. Some outcomes show considerable disparity between high-resource and low-resource settings. There is an urgent need to prioritise safe, accessible, and equitable maternity care within the strategic response to this pandemic and in future health crises. Funding None.
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                Author and article information

                Journal
                Am J Clin Nutr
                Am J Clin Nutr
                The American Journal of Clinical Nutrition
                American Society for Nutrition. Published by Elsevier Inc.
                0002-9165
                1938-3207
                28 February 2023
                February 2023
                28 February 2023
                : 117
                : 2
                : 364-372
                Affiliations
                [1 ]School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
                [2 ]Department of Obstetrics & Gynaecology, The University of British Columbia, Vancouver, British Columbia, Canada
                [3 ]Department of Obstetrics & Gynecology, University of Manitoba, Winnipeg, Manitoba, Canada
                [4 ]Department of Obstetrics & Gynaecology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
                [5 ]Centre for Health Services and Policy Research, The University of British Columbia, Vancouver, British Columbia, Canada
                [6 ]British Columbia Children’s Hospital Research Institute, Vancouver, British Columbia, Canada
                Author notes
                []Corresponding author.
                Article
                S0002-9165(22)10501-0
                10.1016/j.ajcnut.2022.09.001
                9972866
                36863829
                81546d8c-461e-4832-86f1-7d43c4959d50
                © 2022 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 21 May 2022
                : 7 September 2022
                : 12 September 2022
                Categories
                Original Research Article

                Nutrition & Dietetics
                pregnancy,gestational weight gain,infant birthweight,covid-19,interrupted time series,covid-19, coronavirus disease 2019,dci, distressed communities index

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