Odds ratios or p_values from individual observational studies can be combined to examine a common cause_effect research question in meta_analysis. However, reliability of individual studies used in meta_analysis should not be taken for granted as claimed cause_effect associations may not reproduce. An evaluation was undertaken on meta_analysis of base papers examining gas stove cooking, including nitrogen dioxide, NO2, and childhood asthma and wheeze associations. Numbers of hypotheses tested in 14 of 27 base papers, 52 percent, used in meta_analysis of asthma and wheeze were counted. Test statistics used in the meta_analysis, 40 odds ratios with 95 percent confidence limits, were converted to p_values and presented in p_value plots. The median and interquartile range of possible numbers of hypotheses tested in the 14 base papers was 15,360, 6,336_49,152. None of the 14 base papers made mention of correcting for multiple testing, nor was any explanation offered if no multiple testing procedure was used. Given large numbers of hypotheses available, statistics drawn from base papers and used for meta-analysis are likely biased. Even so, p-value plots for gas stove_current asthma and gas stove_current wheeze associations show randomness consistent with unproven gas stove harms. The meta-analysis fails to provide reliable evidence for public health policy making on gas stove harms to children in North America. NO2 is not established as a biologically plausible explanation of a causal link with childhood asthma. Biases_multiple testing and p-hacking_cannot be ruled out as explanations for a gas stove_current asthma association claim. Selective reporting is another bias in published literature of gas stove_childhood respiratory health studies. Keywords gas stove, asthma, meta-analysis, p-value plot, multiple testing, p_hacking
翻译:联合观察研究中的比率或p值可以组合起来,通过元分析来研究一个共同的因果关系问题。然而,在元分析中使用的个体研究的可靠性不能被视为理所当然,因为所声称的因果关系可能并不重现。对关于气灶烹饪、包括二氮化氮(NO2)和儿童哮喘和气喘部分的基础论文的元分析进行了评估。计算了14篇用于哮喘和气喘的元分析的基础论文中测试的假设数目。在元分析中使用的测试统计量为40个带有95%置信限的比率,将这些统计量转换为p值,并以p值图的形式呈现。在14篇基础论文中,可能测试的假设数目的中位数和四分位距分别为15,360、6,336 ~ 49,152。没有一篇基础论文提到进行多重检验纠正,也没有任何解释为什么没有使用多重检验程序。鉴于有大量的假设可用,从基础论文中获得的并用于元分析的统计量很可能存在偏误。即使如此,气灶_当前哮喘和气喘关联的p值图表现出随机性,一致地表明了未被证实的气灶危害。元分析未能提供关于北美儿童气灶危害的公共卫生政策制定的可靠证据。NO2尚未被证明是与儿童哮喘有因果联系的生物学上合理的解释。偏误_多重检验和p-hacking_不能被排除为气灶_当前哮喘关联主张的解释。选择性报道是气灶_儿童呼吸健康研究发表文献中的另一种偏误。关键词:气灶,哮喘,元分析,p值图,多重检验,p_hacking。