| Literature DB >> 35860809 |
Pedro Henrique Alcântara da Silva1, Kezauyn Miranda Aiquoc1, Aryelly Dayane da Silva Nunes1, Wilton Rodrigues Medeiros1, Talita Araujo de Souza1, Javier Jerez-Roig2, Isabelle Ribeiro Barbosa1.
Abstract
Objective: To analyze the prevalence of access to prenatal care in the first trimester of pregnancy among black women compared to other races/ethnicities through a systematic review and meta-analysis.Entities:
Keywords: access to health services; black women; prenatal care; racial factors; systematic review
Year: 2022 PMID: 35860809 PMCID: PMC9289875 DOI: 10.3389/phrs.2022.1604400
Source DB: PubMed Journal: Public Health Rev ISSN: 0301-0422
Search strategy (Brazil, 2021).
| (“Pregnancy” or “Gestation”) and (“Prenatal Care” or “Antenatal Care”) and (“Health Services Accessibility” or “Access to Health Care”) | |
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| LILACS | (“Pregnancy” or “Gestation”) and (“Prenatal Care” or “Antenatal Care”)” or “Prenatal Care” or “Antenatal Care” and (“Access to Health Care” or “Health Services Accessibility”) |
| PubMed | (“Pregnancy” [Mesh] or “Gestation”) and (“Prenatal Care” [Mesh] or “Antenatal Care”) and (“Health Services Accessibility” [Mesh] or “Access to Health Care”) |
| Scopus | (“Pregnancy” or “Gestation”) and (“Prenatal Care” or “Antenatal Care”) and (“Health Services Accessibility” or “Access to Health Care”) |
| Web of Science | (“Pregnancy” or “Gestation”) and (“Prenatal Care” or “Antenatal Care”) and (“Health Services Accessibility” or “Access to Health Care”) |
| CINAHL | (“Pregnancy” or “Gestation”) and (“Prenatal Care” or “Antenatal Care”) and (“Health Services Accessibility” or “Access to Health Care”) |
| Google Scholar | (“Pregnancy” or “Gestation”) and (“Prenatal Care” or “Antenatal Care”) and (“Health Services Accessibility” or “Access to Health Care”) |
| OpenGrey | (“Pregnancy” or “Gestation”) and (“Prenatal Care” or “Antenatal Care”) and (“Health Services Accessibility” or “Access to Health Care”) |
FIGURE 1Flowchart for Article Selection Caption: * Web of Science; **Grey Literature Source: Designed by the authors (Brazil, 2021).
Characteristics of the included studies (n = 19) (Brazil, 2021).
| Author, year | Place | Sample (n) | Age (years old) | Other ethnic-racial groups | Prevalence of access in the first trimester of pregnancy | Odds ratio (OR) |
|---|---|---|---|---|---|---|
| [ | New York, United States | 496 | 13–41 | Hispanic | Black 59.1% | NR |
| Hispanic 48.2% | ||||||
| [ | Texas, United States | 533 | Mean = 15,9 (SD = 1,1) | White, American Mexicans and Others | Blacks 47.8% | Black compared to American Mexican women (OR = 1.9 95% CI 1.2, 3.2) and white (OR = 1.7 95% CI 1.1, 3.0) |
| White 55.8% | ||||||
| American Mexicans 59.3% | ||||||
| Another 33.3% | ||||||
| [ | New Jersey, United States | 198.881 | ≤20, between 21 and 34 and above 35 | White and black by geographic origin and country of birth | Black 62.7% | NR |
| White 86.2% | ||||||
| Mexican black women 21.4% | ||||||
| Mexican whites 46.7% | ||||||
| [ | California, United States | 3.071 | >18 | White, Hispanic (English speaking), Hispanic (Spanish speaking), Other | Black 12.3% | Black compared to white (OR = 1.33 95% CI 0.83–2.12 |
| English-speaking Hispanics 16.9% | ||||||
| Spanish-speaking Hispanics 36.6% | ||||||
| Other English-speaking ethnicities 5.6% | ||||||
| Other Spanish-speaking ethnicities 3.5% | ||||||
| [ | New Jersey, United States | 91.585 | ≤15 to over 40 | Non-Hispanic Whites, Hispanic Whites, and other Hispanics | Non-Hispanic Black Women 31.7% | Non-Hispanic black women compared to non-Hispanic women (OR = 0.65), other non-Hispanic women (OR = 0.63), Hispanic women (OR = 0.84 and other Hispanic women (OR = 0.84) |
| Non-Hispanic Whites 44.9% | ||||||
| Hispanic Whites 36.5% | ||||||
| Other Hispanic 35.4% | ||||||
| [ | California, United States | 6.364 | ≤20, 21–34, and ≥35 | Latin, European, Asian Others | Afroamericanas 8.1% | African-American compared to Europeans (OR = 0.41 CI95% 0.20–0.86) |
| Latin 64.8% | ||||||
| European 19.6% | ||||||
| Asian 7% | ||||||
| Other ethnicities 0.5% | ||||||
| [ | South Carolina, United States | 7. 533 | ≤19 years old, 20–29 years old, and ≥30 years old | White | Use of the public system: Black 60% | Black women using the public health system are more likely to start prenatal care late when compared to black women (OR = 1.9, 95% CI 1.2–3.2) and white OR = 4.1 (95% CI 2.6–6.4) who had private health insurance |
| White 73% | ||||||
| Use of private insurance | ||||||
| Black 85% | ||||||
| White 94% | ||||||
| [ | Washington, United States | 766 | 12–17 years old, 18–25 years old, 26–34 years old, and ≥35 years old | White, Hispanic, and Other | NR | African-Americans having late prenatal care or not performing prenatal care vs. white women (OR = 2.3 95% CI 0.7–6.8) |
| [ | South Carolina, United States | 372 | ≤20 years old, 21–34 years old, and ≥35 years old | White | African American 64.3% | NR |
| White 76.3% | ||||||
| [ | Florida, Georgia, New Jersey, Texas–United States | 268.594 | NR | Non-Hispanic White, Hispanic, and Asian/Pacific Islands | Non-Hispanic black women 72.3% | Black women vs. non-Hispanic white women in Georgia (OR = 0.75 CI95% 0.71–0.79) and Texas (OR = 0.73 CI95% 0.70–0.77) |
| Non-Hispanic whites 87.9% | ||||||
| Hispanic 73.7% | ||||||
| Asian/Pacific Islands 82.1% | ||||||
| [ | Brazil and South Africa | Brazil: 3,761 women and 4,958 births South Africa: 4148 women and 4,800 births | 15–49 | Brazil: White South Africa: White and Asian | In Brazil | Brazil: no significant difference between white and mixed-race (OR = 0.93) and white and black (OR = 1.04). South Africa: less access to prenatal care among black women in the urban area (OR = 0.22) and black women in the rural area (OR = 0.22) |
| Black 61.4% | ||||||
| Sparrow 61.6% | ||||||
| White 76.3% | ||||||
| In South Africa | ||||||
| Freckles 40.4% | ||||||
| White 77.5% | ||||||
| Asian 65.5% | ||||||
| [ | United States | 4.219 | 10–40 | Non-Hispanic Whites, Non-Hispanic Blacks, Hispanics, Asian/Pacific Islands, Native American/Alaska Native | NR | The 5% increase in the rate of black users reduces the rate of use of prenatal care in the first quarter by 1%. The 5% increase in white users increases the use of prenatal care in the first quarter by 1% |
| [ | Georgia, United States | 1.096 | Between 18 and 34 years old | Non-Hispanic whites, Hispanics/others | Non-Hispanic Black Women 58,1% | Non-Hispanic blacks vs. non-Hispanic whites (OR = 0.44 95% CI 0.24–0.73) |
| Non-Hispanic White Women 70,8% | ||||||
| Hispanic/others 81,8% | ||||||
| [ | Pelotas, Brazil | 4244 | Not reported | Whites | Black 60,1% | NR |
| Sparrow 65,7% | ||||||
| White 77,9% | ||||||
| [ | Rio de Janeiro, Brazil | 2.353 | Mean = 24.6 years old | White and Yellow | Sparrow 73,6% | Brown vs. white (OR = 0.81 95% CI 0.70–0.93) and black vs. white (OR = 0.78 95% CI 0.58–1.05) |
| Black 71,7% | ||||||
| White 77,8% | ||||||
| [ | United States | 5.200 | 15–19; 20–24; 25–29; 30–34; ≥35 | White and Hispanic | Black 74.81% | NR |
| White 89.63% | ||||||
| Hispanic 78.56% | ||||||
| [ | United States | 519 | Mean = 31.8 | White, Hispanic, or Latin | Black 23% | NR |
| White 65.5% | ||||||
| Hispanic 15.6% | ||||||
| [ | United States | 167.463 | 18–24; 25–29; 30–34; +35 | Native Americans/Native Alaskans; Asians; Non-Hispanic whites; Hispanic | Non-Hispanic Black Women 85.9% | Non-Hispanic black women compared to white women (OR = 1.52; 95% CI 1.40–1.64) are more likely to start prenatal care late |
| Native American/Native Alaskan 85.2% | ||||||
| Asian 84.9% | ||||||
| Non-Hispanic whites 87.7% | ||||||
| Hispanic 87.5% | ||||||
| [ | England, United Kingdom | 122.275 | <20; 20–24; 25–29; 30–34; 35–39; ≥40 | British whites; Irish Whites; others white; others | African black women 79.1% | African black vs. white women (OR = 1.90 95% CI 1.80–2.00) are more likely to start prenatal care late |
| Caribbean black women 70.3% | ||||||
| Other black women 66.7% | ||||||
| British whites 73.3 | ||||||
| Irish whites 75.9% |
95% CI: 95% confidence interval; OR, odds ratio; SD, standard deviation; NR, not reported.
Methodological quality and bias risk analysis according to Joanna Briggs critical appraisal checklist for analytical cross-sectional studies (Brazil, 2021).
| Item | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Were the criteria for inclusion in the sample clearly defined? | + | + | + | + | + | + | + | + | − | + | − | + | + | - | + | + | + | + | + |
| Were the study subjects and the setting described in detail? | + | + | + | + | − | − | − | + | + | + | + | + | + | − | − | + | − | − | + |
| Was the exposure measured in a valid and reliable way? | + | + | + | + | + | + | + | + | + | − | − | − | + | + | + | + | + | + | + |
| Were objective, standard criteria used for measurement of the condition? | + | + | − | + | + | + | + | + | + | − | − | − | + | + | − | + | − | − | + |
| Were confounding factors identified? | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + |
| Were strategies to deal with confounding factors stated? | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + |
| Were the outcomes measured in a valid and reliable way? | + | + | − | − | + | + | + | + | − | − | − | − | + | + | + | − | − | − | − |
| Was appropriate statistical analysis used? | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + | + |
| Bias risk | L | L | L | L | L | L | L | L | L | M | M | M | L | L | L | L | M | M | L |
[8, 11–16, 18–27, 29, 31].
+: Low risk; −: High risk; L: Low Risk; M: Moderate Risk.
FIGURE 2Forest Plot for the Early Start of Prenatal Care: Black women compared to white women (Brazil, 2021).
FIGURE 3Funnel Plot for early prenatal care: black women compared to white women (Brazil, 2021).