Background <p>While specific unhealthy behavioral lifestyles link to primary dyslipidemia (PD), cumulative effects remain unknown. We quantified the association with incidence of PD with cumulative exposure clustering of lifestyles.</p> Methods <p>Eleven thousand eight hundred forty-three government staff enrolled (2018–2020) and followed (2019–2021). PD was defined per Chinese guidelines. Behaviors and personal characteristics were collected by a questionnaire. Lifestyle score was calculated using cigarette smoking, alcohol consumption, unhealthy diet, unhealthy physical exercise, BMI ≥ 24 Kg/m<sup>2</sup>, sedentary behavior, and poor sleep quality. Cox proportional hazard models were used to explore the associations, and the Population Attributable Fraction (PAF) for the association of PD with lifestyle score was calculated. The dose-response relationship was evaluated using the restricted cubic splines method.</p> Results <p>The incidence density of PD was 78/1000 person-years. Compared with participants with 0 unhealthy behavioral lifestyles, the HR of PD was 3.18 (95% CI: 1.63–6.22, <i>p</i> = 0.008) for those with at least 6 unhealthy behavioral lifestyles, with a PAF of the cumulative exposure of unhealthy lifestyle was 33.03% (95% CI:1.58–66.81%). Additionally, the combination of unhealthy diet, unhealthy physical exercise, sedentary behavior, and poor sleep quality was the most dominant form. Notably, there was a monotonically increasing (J-shaped) relationship between unhealthy lifestyles and the risk of PD (<i>P</i> = 0.034).</p> Conclusions <p>Cumulative exposure to unhealthy lifestyles, particularly the combination of poor diet, physical inactivity, sedentariness, and poor sleep, is a major, dose-dependent risk factor for PD in Chinese governmental employees. Public health interventions should prioritize this high-risk cluster to alleviate the substantial disease burden, over one-third of which is attributable to these modifiable factors.</p>

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The effect of cumulative exposure to unhealthy behavioral lifestyles on incident primary dyslipidemia: a prospective study from the Chinese government employee cohort

  • Ling Li,
  • Yilu Li,
  • Chengcheng Zhang,
  • Jun He,
  • Feiyun Ouyang,
  • Jingya Li,
  • Dan Luo,
  • Xiuqin Hong,
  • Shuiyuan Xiao

摘要

Background

While specific unhealthy behavioral lifestyles link to primary dyslipidemia (PD), cumulative effects remain unknown. We quantified the association with incidence of PD with cumulative exposure clustering of lifestyles.

Methods

Eleven thousand eight hundred forty-three government staff enrolled (2018–2020) and followed (2019–2021). PD was defined per Chinese guidelines. Behaviors and personal characteristics were collected by a questionnaire. Lifestyle score was calculated using cigarette smoking, alcohol consumption, unhealthy diet, unhealthy physical exercise, BMI ≥ 24 Kg/m2, sedentary behavior, and poor sleep quality. Cox proportional hazard models were used to explore the associations, and the Population Attributable Fraction (PAF) for the association of PD with lifestyle score was calculated. The dose-response relationship was evaluated using the restricted cubic splines method.

Results

The incidence density of PD was 78/1000 person-years. Compared with participants with 0 unhealthy behavioral lifestyles, the HR of PD was 3.18 (95% CI: 1.63–6.22, p = 0.008) for those with at least 6 unhealthy behavioral lifestyles, with a PAF of the cumulative exposure of unhealthy lifestyle was 33.03% (95% CI:1.58–66.81%). Additionally, the combination of unhealthy diet, unhealthy physical exercise, sedentary behavior, and poor sleep quality was the most dominant form. Notably, there was a monotonically increasing (J-shaped) relationship between unhealthy lifestyles and the risk of PD (P = 0.034).

Conclusions

Cumulative exposure to unhealthy lifestyles, particularly the combination of poor diet, physical inactivity, sedentariness, and poor sleep, is a major, dose-dependent risk factor for PD in Chinese governmental employees. Public health interventions should prioritize this high-risk cluster to alleviate the substantial disease burden, over one-third of which is attributable to these modifiable factors.