Overall findings
This analysis highlighted many issues related to women’s health. (1) Many women gained a significant amount of weight during their 20s and middle ages. (2) overweight and obesity at age 20 years increased overall and early mortality risk, even after adjusting for her BMI in late adulthood; (3) weight gain in adulthood after being underweight/healthy at age 20 years also increased overall and early mortality.
Our finding that BMI in young adulthood is positively associated with all-cause mortality and that the effect is independent of later BMI mirrors results from other large cohort studies adjusting for later BMI. doing [10,11,12].
Our analysis suggests that underweight/healthy weight women at age 20 should remain in that category or, at best, increase to overweight, and our results suggest that It is consistent with other large cohorts. [10, 18,19,20,21].
The increased risk of all-cause mortality found here among the minority of women (1.6%) who moved to the lower BMI category was likely due to reverse causality, whereby some of the deaths were due to poor health status. It’s likely the cause, and it can also lead to weight gain.Previously reported loss before death [22].
The current analysis showed that the higher premature mortality in women who were obese at age 20 years and those with an upward shift in BMI category from age 20 to mid-to-late 20s was primarily due to diabetes and CVD. rice field. Other studies have reported similar results for CVD. [11, 19, 23]other studies have shown higher mortality from obesity-related cancers among these groups [24, 25].
Strengths, Limitations, and Public Health Impacts
The strengths of this study include a large sample size with widely spread data on deprivation scores and many confounding factors, minimal missing data, and complete follow-up data for 421,359 women. Multiple imputation was employed to reduce bias due to missing data, and sensitivity analysis yielded consistent results.
Our study encountered several limitations that warrant discussion. First, there are limitations to generalizing current results to the UK population. According to the 2011 Census, when 9.8% of the North West England population was non-white, the PROCAS study recruited only 4.4% of non-white participants, but within the age group of 46-73 years of non-whites are lower.Because the non-white population of England and Wales has a lower average age [26]Despite the wide spread of deprivation scores, the PROCAS cohort was less deprived than the general population of Greater Manchester. [27]a common problem in health research [28]38% of PROCAS participants had a healthy BMI, compared to just 21.9% of women aged 55-64 in the 2012 England Health Survey, the middle year for recruitment into PROCAS. [29]The lower obesity rates in the PROCAS compared to the England Health Survey suggest that participants are more health conscious than the general population and/or that self-reported height and weight are over/underestimated. suggesting.It is recognized that overweight and obese women are more likely to underestimate their weight and more likely to overestimate their height [30]However, using recalled weight to assess BMI at age 20 in this cohort has previously been found to be reliable and should have had minimal impact on study results. [9]Self-reporting is also likely to lead to underreporting of alcohol and PA data, so it is possible that fewer women adhered to the recommendations than reported here. Born before 1970, when age-old obesity was uncommon. Only 2.5% of her in the PROCAS sample were obese at the age of 20, compared with her 37% of current women aged 16-24 in the UK. [6]Confidence intervals for analyzes that included this group were therefore wide.Our findings indicate that breast-screening-age women who are obese at age 20 years are more likely to die prematurely than women with a BMI <25 kg/m2 at the age of 20. However, a woman who is obese at age 20 would be recruited into her PROCAS because she was already in poor health, or because she had died before being recruited at age 46-73, so there is less potential. Also note that there is selection bias. In addition to the limitation of generalization to the UK population, the current results may not apply to low-income countries.
Second, there are limitations regarding the robustness of data collection. We excluded 8 385 women from the analysis due to missing BMI as their height and/or weight were not entered in the questionnaire. Higher mortality among women not included in the analysis due to lack of BMI may be due to higher rates of overweight/obesity in women not included or greater deprivation in women not included (which may have directly caused high mortality). , or indirectly through higher overweight/obesity levels). Therefore, the association between weight gain and maintenance of overweight/obesity seen here might be stronger if all cases were included. It is weight based and does not include data on weight change over time. There is also a lack of information regarding weight changes between the PROCAS entry and her June 2020 censor date. More frequent and objective measurements of body weight will help determine whether total years spent being overweight/obese should be included in mortality risk calculation models in a manner similar to cumulative body weight. Smoking damage and the concept of ‘pack years’. This also helps clarify the importance of age in weight gain/loss, as some studies suggest that weight gain in early adulthood is more detrimental than later in life. . [10, 19]on the other hand, weight loss has been shown to occur later in life and be detrimental to mortality. [19]Because the questionnaire only collected weight data at age 20, we are unable to comment on other changes from age 20 to PROCAS entry, such as changes in alcohol consumption or PA levels. Other confounding factors such as educational level, marital status, dietary patterns, and other health problems may mediate the relationship between weight change and all-cause mortality. Factors could not be reconciled. Additionally, smoking data are lacking. Smoking is a major confounding factor as it is associated with weight loss while increasing the risk of death. [22]20% of women in North West England in 2011 were current smokers [31] Therefore, this may have influenced the results by increasing mortality among women in the underweight category. Determined by updated NBSS for females. Data on the proportion of women aged 50–70 in Manchester and Trafford who migrate from the area each year suggest that up to 18% of this population may have left home during the follow-up period. Therefore, missing mortality data may be important. [32, 33]Cause-of-death analysis using death certificates has been limited to the small number of available death certificates due to cost considerations. This analysis was also limited by incomplete and potentially inaccurate reporting of cause of death.Unfortunately, some of our study subjects did not follow UK guidelines [34] It leads to the inaccuracy of the classification used here. For example, 5 cases were listed as metastatic cancer and were classified as cancer deaths because the primary cause was not listed, but could be cancer commonly associated with obesity. Obesity is primarily associated with type 2 diabetes, but not with type 1 diabetes. However, the type of diabetes was identified in only 4/5 cases and weight-related cases could not be isolated. It does not distinguish between pre- and post-menopausal BC. Because only postmenopausal BC is associated with obesity, some premenopausal BC cases in our analysis may be misclassified as obesity-related cancers.
Third, there are limitations regarding analytical techniques. We used multiple imputation to address missing data, which relies on the data being missing at random, but the missing weight data for heavier women may be biased. Unlike other studies that excluded death within the first few years of follow-up, we did not attempt to minimize the effects of reverse causality (e.g. [24]).
Finally, it is important to note that the PROCAS study is still under follow-up and the mortality figures presented here are not final. The deaths recorded so far are premature. Future studies will either repeat the current analysis if a larger cohort dies or use other factors such as population attributable ratios and weight gain in adulthood to estimate the burden of excess mortality associated with overweight and obesity at age 20. Other analyzes can be performed.
Analyzes of the PROCAS cohort have previously shown that being overweight or obese at age 20 reduces the risk of subsequent BC, [9], our present results, together with those from other cohorts, show that increased weight in young adulthood significantly increases overall and preterm mortality. Therefore, the potential benefits of obesity in early adulthood should not be overstated. Her 13-15-year-old girl obesity rate in the UK is now 18%, which could have a significant impact on future health and healthcare costs. [6]To prevent overweight or obesity by age 20, more resources need to be devoted to helping children and adolescents avoid weight gain. Results from this and other cohorts also highlight the benefits of avoiding weight gain in adulthood.
The optimal way to support children, adolescents, and adults to avoid weight gain is currently unknown. can be evaluated. Existing, peer-reviewed frameworks should be used, such as guidance from the Medical Research Council on the development of complex interventions. [35] This includes intervention development or identification, intervention feasibility assessment and evaluation design, intervention evaluation, and impactful implementation.
