You Wenpeng, Sevastidis Jacob, Henneberg Maciej
School of Biomedicine, the University of Adelaide, Adelaide, Australia.
School of Nursing and Midwifery, Western Sydney University, Sydney, Australia.
Future Sci OA. 2025 Dec;11(1):2495537. doi: 10.1080/20565623.2025.2495537. Epub 2025 May 6.
To investigate the population-level association between family size and cardiovascular disease (CVD) incidence, focusing on broad patterns rather than causal mechanisms or individual-level effects.
Population level correlations of family size to CVD incidence were analyzed with scatter plots, simple regression, partial correlation and multivariate regression separately. Aging, economic affluence, obesity and urbanization were incorporated in models as potential confounders.
Globally, family size negatively correlated to CVD incidence rate. This relationship remained in partial correlation analyses when controlling for confounders. Stepwise multiple regression revealed that family size may be the most significant predictor of CVD incidence.
Large family size is significantly associated with lower cardiovascular disease (CVD) incidence, potentially due to biological, psychological, and social factors. However, as the data are cross-sectional, this relationship should be interpreted as correlational rather than causal. The association appears more pronounced in developing countries, where contextual factors may amplify its effects.
研究家庭规模与心血管疾病（CVD）发病率之间的人群水平关联，重点关注总体模式而非因果机制或个体水平效应。
分别用散点图、简单回归、偏相关和多元回归分析家庭规模与CVD发病率的人群水平相关性。将衰老、经济富裕程度、肥胖和城市化作为潜在混杂因素纳入模型。
在全球范围内，家庭规模与CVD发病率呈负相关。在控制混杂因素的偏相关分析中，这种关系依然存在。逐步多元回归显示，家庭规模可能是CVD发病率的最显著预测因素。
大家庭规模与较低的心血管疾病（CVD）发病率显著相关，这可能是由于生物学、心理学和社会因素。然而，由于数据是横断面的，这种关系应解释为相关性而非因果关系。这种关联在发展中国家似乎更为明显，在这些国家，背景因素可能会放大其影响。
