{
  "abstract": "Objective To assess contributions of 22 risk factors (each related to life style, diet, reproduction, environment or infection) to the incidence of all cancer cases.Design Secondary data analysis, reference year 2019. Independence of risk factors was assumed.Setting The Netherlands, nationwide.Population Dutch men and women, ages >30 years.Main outcome measures Population attributable fractions and numbers of newly diagnosed cancers by gender.Results Of all newly diagnosed cancers, an estimated 34% (40 054 out of 119 728 cancers, excluding basal cell carcinoma of the skin) was attributable to the evaluated risk factors (35% in men, 32% in women). Among these factors, smoking was by far the largest contributor, accounting for 16% of all cancers (19 095 cases), followed by the combined impact of dietary factors (5%, 6 452 cases) and overweight and obesity (4%, 4995 cases). Limited data on basal and squamous cell carcinoma led to an underestimation of the burden of ultraviolet radiation.Conclusions A substantial proportion of cancer cases arises from potentially modifiable risk factors. Implementation of effective public health strategies to reduce exposures is crucial to alleviate the future burden of cancer.",
  "authors": [
    {
      "affiliations": [
        "Child Health, TNO, The Hague, The Netherlands"
      ],
      "name": "Caren Lanting"
    },
    {
      "affiliations": [
        "Child Health, Netherlands Institute for Applied Scientific Research—TNO, Leiden, The Netherlands"
      ],
      "name": "Ellian Lebbink"
    },
    {
      "affiliations": [
        "Child Health, Netherlands Institute for Applied Scientific Research—TNO, Leiden, The Netherlands"
      ],
      "name": "Ernest de Vroome"
    },
    {
      "affiliations": [
        "Child Health, Netherlands Institute for Applied Scientific Research—TNO, Leiden, The Netherlands"
      ],
      "name": "Iris Eekhout"
    }
  ],
  "title": "Proportion of cancer attributable to modifiable factors in the Netherlands in 2019: a secondary data analysis",
  "uid": "3a3f21f9-dd1b-541e-8ee2-591ba35f850d"
}