Title: Sex-Specific Associations of Prenatal Chinese Famine Exposure with Cataract Risk at
Age Sixty: A Cross-Sectional Study
Version: 1 Date: 20 May 2024
Reviewer's report:
Xia et al. conducted a study on the relationship between prenatal famine exposure and cataract
risk in adulthood using data collected from subjects undergoing eye examinations at the Health
Management Center of the Second Affiliated Hospital of Chongqing Medical University. They
found that prenatal exposure to the Chinese famine could increase the risk of later-life cataracts
and that the effect estimate is larger among women compared to men. This study is important
considering the growing interests of using famines as natural experiments to examine how early-
life environmental shock may shape later life health outcomes. Overall, this is an important paper
and highlights a sadly all too topical issue – famine/malnutrition. This not only affects numerous
countries or regions worldwide today but threatens to expand greatly over coming years. Whilst
there are some strengths, I think the work would also benefit from some updates and edits.
First, several important systematic reviews on other health outcomes have been conducted on
famine exposure previously and they showed that age difference was a major reason for why
previous empirical studies observed an association between famine exposure and adverse health
outcomes (https://doi.org/10.1093/ije/dyx013; https://doi.org/10.3390/nu14142855). Xia et al.
defined individuals born between January 1, 1960, and December 31, 1960, as the famine
exposure group and selected individuals born between January 1, 1963, and December 31, 1963
as the control group. This can lead to a 3-year age difference. However, in Table 1, these two
groups seems to have comparable mean age and SD. How is this possible?
It is extremely important for the authors to address the above age issue in Table 1 and use
an age-balanced control group. Please see how this has been achieved previously (https://
doi.org/10.3390/nu14142855). This should be at least discussed as one of the major method
limitations in famine studies, especially those on Chinese famine. Also, some more recent studies
proposed a systematic method to address the age difference issue in studies on the Chinese
famine and other famines (https://doi.org/10.1093/eurjpc/zwac254; https://doi.org/10.1136/
jech-2023-221875).
Second, in famine health studies, it is equally important to establish a dose-response
relationship. This makes it important to have solid measures of famine severity. However,
Xia et al. did not examine or discuss the famine intensity of their study population despite
it is a single region study. There is emerging literature on building measures for famine
intensity in China and other countries, which should be further applied and discussed
(https://doi.org/10.1016/S2213-8587(15)00279-X; https://doi.org/10.1093/ije/dyx222; https://
doi.org/10.1073/pnas.2102809118; https://doi.org/10.1101/2021.12.24.21268375).
Third, the results section for APC models should be updated to present
the results in a clear fashion.  Please see the link and refer to
related examples: https://www.publichealth.columbia.edu/research/population-health-methods/
age-period-cohort-analysis
Last, the discussion on how to conduct mythologically rigorous famine studies
can be further expanded in the work. This will be important to guide future
famine research considering that many existing studies have major methodological
limitations. There are several important methods-driven articles which the authors can
look into (https://doi.org/10.1146/annurev-publhealth-031210-101230; https://doi.org/10.1038/
s41574-019-0195-5; https://doi.org/10.3390/nu14142855).
There are also some minor issues: (1) the format of references is not consistent; (2) the use
of consistent language especially for language including women/female, gender/sex, which
reflect related but different concepts; (3) the writing can be further improved for clarity; (4) the
flowchart should be updated following STROBE standard flowchart.