{
  "abstract": "Objectives To systematically review the utilisation of the Grading of Recommendations Assessment, Development and Evaluations (GRADE) framework within the context of WHO public health guidelines (PHGs), identifying key features, areas of concentration and potential deficiencies.Design and setting From 2007 to February 2024, a comprehensive search of the WHO website was conducted to identify PHGs that have incorporated the GRADE methodology.Participants The study focused on the PHGs identified through the above search.Interventions Data extraction and analysis were independently conducted by researchers using Microsoft Excel 2019.Main outcome measures For each PHG, key recorded characteristics included publication details, thematic areas, the strength of recommendations, the certainty of evidence, and characteristics of the GRADE downgrading/upgrading domains.Results Out of 228 PHGs examined, 9234 (90.55%) outcome indicators used the GRADE rating system, predominantly in the area of sexual and reproductive health (50%). Only 31.62% of the outcomes reported moderate and high certainty in evidence. The main clustering results were dominated by adverse events. Among the 4013 recommendations, 2067 (51.51%) were strong, while 1477 (36.81%) were weak/conditional. It is noteworthy that 46.83% of the strong recommendations were based on low or very low confidence in evidence. Among these strong recommendations, 119 met the criteria of five paradigmatic situations where it was necessary to issue a strong recommendation despite low or very low confidence in the effect estimates. Among the 13 230 instances of downgrading, 41.09% were due to the risk of bias and 35.90% were due to imprecision. Only 0.25% outcomes were upgraded by the magnitude of effect size and 0.03% by dose–response gradient.Conclusion The GRADE approach is widely used in the development of PHGs. More than half of the recommendations in PHGs are based on low or very low-quality evidence, primarily due to risks of bias and imprecision. Additionally, strong recommendations based on low-confidence or very low-confidence estimates are frequently made. Therefore, it is necessary to enhance guideline developers’ understanding of the GRADE methodology and to further investigate and clarify discordant recommendations in PHGs.",
  "authors": [
    {
      "affiliations": [
        "Health Technology Assessment Center/Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China",
        "Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China"
      ],
      "name": "Xiuxia Li"
    },
    {
      "affiliations": [
        "Health Technology Assessment Center/Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China",
        "Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China"
      ],
      "name": "Tao Nian"
    },
    {
      "affiliations": [
        "Health Technology Assessment Center/Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China",
        "Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China",
        "Zhengzhou People's Hospital, Zhengzhou, China"
      ],
      "name": "Wendi Liu"
    },
    {
      "affiliations": [
        "School of Sociology, Huazhong University of Science and Technology, Wuhan, Hubei, China"
      ],
      "name": "Xue Shang"
    },
    {
      "affiliations": [
        "Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"
      ],
      "name": "Xinxin Deng"
    },
    {
      "affiliations": [
        "Department of Infection Management, Gansu Provincial Hospital, Lanzhou, Gansu, China"
      ],
      "name": "Kangle Guo"
    },
    {
      "affiliations": [
        "Shanghai YangZhi Rehabilitation Hospital (ShanghaiSunshine Rehabilitation Center), Tongji University School of Medicine, Shanghai, China"
      ],
      "name": "Nan Chen"
    },
    {
      "affiliations": [
        "Data Centre, Shangluo Central Hospital, Shangluo, Shaanxi, China"
      ],
      "name": "Yan Wang"
    },
    {
      "affiliations": [
        "Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China",
        "Institute of Health Data Science, Lanzhou University, Lanzhou, Gansu, China"
      ],
      "name": "Yaolong Chen"
    },
    {
      "affiliations": [
        "Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China",
        "Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou, Gansu, China"
      ],
      "name": "Kehu Yang"
    }
  ],
  "title": "Exploring the application of GRADE in formulating WHO public health guidelines: a scoping evidence review",
  "uid": "cab9416c-b294-5db7-9c07-c1b15d83dece"
}