Outdoor Light Spending Time, Genetic Predisposition and Incident Parkinson's Disease： The mediating effect of lifestyle and vitamin D

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Methods A cohort study based on UK Biobank enrolled participants between 2006 and 2010, with the latest follow-up in November 2022. In the prospective population-based study 375,599 UK adults aged 37–73 years were enrolled. The outdoor light time was assessed using a questionnaire survey to investigate how many hours were spent outdoors on typical summer and winter days. New-onset PD was identified through linkage with inpatient hospitalization and death registers. Multivariate Cox proportional hazard regression models were used. The polygenic risk score (PRS) for PD comprised 44 single-nucleotide variants. Results A total of 375,599 participants (mean age, 56.8 years; 46.3% males) were included, and 2,824 individuals were first-ever diagnosed with PD. Compared with the individuals with shorter outdoor light time, those with longer time in summer (HR 0.77; 95% CI, 0.68–0.88), in winter (HR 0.85; 95% CI, 0.75–0.96), and on average (HR 0.83; 95% CI, 0.74–0.93), were prone to have lower PD risk. There is no interaction between outdoor light time and genetic predisposition in PD. In mediation analyses, physical activities explained 13.24%, 25.72%, and 15.55% of the associations between outdoor light time and PD, respectively. Conclusion In this cohort study, a longer duration of outdoor light exposure was associated with a lower risk of PD, and independent of genetic risk of PD. This association is partly mediated by physical activity, vitamin D, and sleep patterns. Parkinson's disease Outdoor light UK Biobank Life style polygenic risk score Figures Figure 1 Introduction Parkinson's disease (PD) is the second most common neurodegenerative disease in the world and is characterised by bradykinesia, rigidity, postural instability, and resting tremor 1 . In 2019, the global estimates show over 8.5 million individuals living with PD, resulting in 329,000 deaths and 5.8 million disability-adjusted life years 2 . The global burden of PD, in terms of deaths and disability, has more than doubled in the past two decades, representing the fastest-increasing disease among all neurological disorders 3 . Importantly, PD is a progressive disease with limited therapeutic effectiveness, suggesting the importance of prevention. Growing evidence has suggested that outdoor light is beneficial for promoting health 4 , and outdoor light exposure is associated with a variety of neurobehaviors related to the central nervous system 5 . However, there is little research on the effects of time spent in outdoor light on the risk of developing PD. Outdoor light exposure has an important effect on vitamin D status, sleep and circadian rhythms, and physical activity, many of these are closely related to PD. A case-control study of 201 newly diagnosed PD patients and 199 controls found that PD patients had shorter outdoor sunlight exposure time than control 6 . Due to the small sample size, the findings may not be generalisable to the general population. To date, the correlation between outdoor light and PD risk in prospective studies based on large populations is unknown, and the dose-response association between them remains uncertain. We also conducted a mediation analysis of above factors to ascertain the relationship between outdoor sunlight exposure time and the incidence of PD. The development of PD is influenced by both genetic and environmental factors 7 – 9 . yet the role of genetic predisposition in the relationship between time spent in outdoor light and PD remains largely uncertain. Exploring the association between sunlight exposure time and the genetic risk of PD can aid in identifying effective strategies to mitigate PD risk. To address these knowledge gaps, we investigated the optimal duration for protection against PD risk and examined if exposure to outdoor light could modify the association between genetic predisposition and PD risk. Methods Study population The UK Biobank is a large population-based cohort study that recruited approximately half a million participants aged 40–69 years from 2006 to 2010 across England, Scotland, and Wales. Each participant completed touchscreen questionnaires, underwent a physical examination, and provided biological samples 10 . For the current analyses, we excluded individuals who subsequently withdrew from the study (n = 1,432), those diagnosed with Parkinson's Disease (PD) (n = 944) at baseline, those with incomplete data on time spent in outdoor light, and respondents who reported 'do not know' or 'prefer not to answer' regarding outdoor light, or provided extreme values exceeding the typical day length in the UK during summer (16 h) and winter (8 h) (n = 45,233), based on the effective daytime duration in the UK 11 . Participants with incomplete genetic information (n = 10,338), those displaying non-conforming sex in phenotypic and genetic data (n = 314), and individuals not of European descent (n = 68,634) were also excluded from the analysis. Following these exclusions, 375,599 participants were included in the main analysis (Fig S1 ). Ascertainment of outcomes Participants with Parkinson’s disease were identified using the algorithm recommended by the UK Biobank 12 , and detailed definitions are shown in Table S1 . Disease information was obtained from hospital admission electronic health records and death registers through linkages with the Hospital Episode Statistics for England, Scottish Morbidity Records for Scotland, and the Patient Episode Database for Wales. At the time of our analyses, the censoring dates for Hospital Episode Statistics were 1 November, 2021, for England, 25 September, 2021, for Scotland, and 29 May, 2021, for Wales. We calculated the follow-up time from baseline to PD diagnosis, death, loss to follow-up, or censorship, whichever occurred first. Assessment of time spent in outdoor light The duration of outdoor light during typical daylight in summer or winter was recorded using an electronic questionnaire at baseline 11 , 13 . Participants were asked, 'In a typical day in summer or winter, how many hours do you spend outdoors?' They could enter a specific number or choose from pre-set options including 'less than an hour a day', 'do not know', or 'prefer not to answer'. Participants spending considerable time outdoors reported the average time spent. A moderate correlation was observed between summer and winter outdoor light exposure, as per Pearson's correlation analysis (r = 0.64, P < 0.001). Consequently, we examined the association between outdoor light exposure in summer and winter and the risk of incident Parkinson’s disease. Furthermore, to derive a singular measure of outdoor light exposure, we calculated the average time based on summer and winter data. Assessment of covariates Structured questionnaires were used to assess several possible confounding variables: sociodemographic characteristics (age, sex, ethnicity, education, and occupation), socioeconomic status (Townsend Deprivation Index), lifestyle factors (physical activity, sleep pattern, smoking, alcohol consumption, and usual diet), comorbidities (hypertension, dyslipidaemia, cardiovascular disease, and cancer) at the time of recruitment, vitamin D supplementation, vitamin D levels, and outdoor environmental-related variables (use of sun/UV protection and PM2.5). Townsend Deprivation Index scores represent the level of socioeconomic deprivation. Body mass index (BMI) was determined as weight in kilograms divided by the square of the height in meters. Physical activity, including moderate and vigorous-intensity activities, was evaluated as the metabolic equivalent of task (MET) minutes per week and was categorised as < 10 MET-h/week or ≥ 10 MET-h/week. The healthy sleep pattern score was generated based on a combination of chronotype, sleep duration, insomnia, snoring, and excessive daytime sleepiness. Smoking status was categorised as 'never smoked', 'former smoker', or 'current smoker'. Hypertension was defined as elevated mean blood pressure (mean systolic/diastolic blood pressure ≥ 140/90 mmHg), a physician’s diagnosis of hypertension, or self-reported current use of antihypertensive medications. We defined hyperlipidaemia as those with a physician’s diagnosis of the condition or self-reported current usage of lipid-lowering medications. Additionally, we included the PD-polygenic risk score (PRS), a genotyping array, and the first 10 principal components of ancestry as covariates. Assessment of polygenic risk score The PRS showed the association between genotype and risk of PD by score points and was composed of 44 single nucleotide polymorphisms (SNPs), which were associated with the incidence of PD in white participants 14 . Details regarding these SNPs are provided in Table S2. Moreover, details on genotyping and quality control can be found online 15 . We constructed the weighted PRS of PD based on 44 SNPs using the following formula: PRS = (β1 × SNP1 + β2 × SNP2 + … + β44 × SNP44) × (44 / sum of β coefficients) The PRS of PD exhibited a normal distribution (Fig S2), with a higher score signifying increased genetic susceptibility to PD (Table S3).Participants were classified as having low (quintile 1), intermediate (quintiles 2 to 4), or high (quintile 5) genetic risk for each outcome. Statistical analysis Sample characteristics are reported as mean ± standard deviations for normally distributed continuous variables, medians (interquartile ranges) for non-normally distributed continuous variables, and numbers with percentages for categorical variables. Differences between groups were compared using the Student's t-test, Wilcoxon test, or chi-squared test, when appropriate. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between the time spent outdoors and the risk of incident PD. Schoenfeld residuals were used to test the proportional hazards assumption, and no violations were observed. In model 1, we adjusted for age and sex. Model 2 (full model) was further adjusted for education, Townsend deprivation index, smoking status, alcohol consumption, BMI, dietary pattern, vitamin D supplementation, use of sun/UV protection, PM2.5, baseline hypertension, dyslipidaemia, cancer, cardiovascular disease, PRS, the first ten principal components of ancestry, and genotype measurement batch. To investigate the dose-response relationship between time spent in outdoor light and the risk of PD, a restricted cubic spline model with three knots (at the 10th, 50th, and 90th percentiles) was employed. The missing values of the covariates were imputed and analysed using multiple imputations with five imputations (SAS PROC MI and PROC MIANALYZE). To assess the joint association between outdoor light time and PD-PRS on the risk of PD, we treated participants with a low PRS and long outdoor light time as the reference group to conduct a joint analysis of the association between outdoor light time and the genetic risk of PD. Furthermore, we calculated the interaction between the outdoor light time and PD-PRS on a multiplicative scale. Multiplicative interactions were assessed by comparing models with and without a cross-product interaction term for outdoor light and the genetic risk of PD using likelihood ratio tests. Stratified analyses and interactions were performed to examine the association between outdoor light time and incident PD according to age, sex, BMI, and occupation. A directed acyclic graph explaining the association between the exposures, the outcome, and the covariates is available in Fig S3. Mediation analysis was performed to evaluate the proportional contribution of vitamin D, physical activity, and sleep patterns to the association between outdoor light time and PD risk (SAS PROC CAUSALMED). The mediation analysis models were adjusted for the same set of confounders as in Model 2 of the primary analyses. To test the robustness of the results, vitamin D levels, total physical activity, and sleep patterns were adjusted in addition to the variables in Model 2. We also repeated the analyses after excluding individuals who died or developed PD within 2 years of follow-up to minimise potential reverse causality and used the Fine-Gray subdistribution hazard model. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA) and R software (version 4.3.1; R Foundation for Statistical Computing). A two-sided p < 0.05 was considered statistically significant. Ethical Compliance All participants in the UK Biobank provided informed consent at the time of recruitment, allowing their data to be used for a wide range of research purposes. We adhere to the terms and conditions set by the UK Biobank in the use of this data. Results Characteristics of the study population A total of 375,599 participants (mean age, 56.8 years; 173688 males 46.3%) with a median follow-up of 13.7 years (interquartile range: 13.13–14.31) were included in this prospective study, and 2,824 individuals were first-ever diagnosed with PD. Baseline demographics and characteristics according to outdoor light hours are shown in Table 1 . Overall, individuals with longer outdoor light exposure times (> 3 h/day in summer; >2 h/day in winter; >2.5 h/day on average) tended to be older, male, retired, current smokers, have lower education levels, and have a higher genetic risk of PD. Table 1 Baseline characteristics of participants. Characteristics Outdoor light time in summer Outdoor light time in winter Outdoor light time on average 3 h/day P 2 h/day P 2.5 h/day P No. of participants 48668 146765 180166 71832 218953 84814 70375 141577 163647 Age (years), mean (SD) 54.2 ± 7.5 55.8 ± 7.9 58.5 ± 7.8 < 0.001 55.0 ± 7.7 56.8 ± 8.0 58.7 ± 7.9 < 0.001 54.3 ± 7.6 56.1 ± 8.0 58.6 ± 7.8 < 0.001 Female (%) 28347 (58.3) 84660 (57.7) 88904 (49.4) < 0.001 45634 (63.5) 121957 (55.7) 34320 (40.5) < 0.001 42383 (60.2) 81824 (57.8) 77704 (47.5) < 0.001 Townsend deprivation index, median (IQR) -2.27 (-3.74 to -0.27) -2.41 (-3.79 to -0.13) -2.39 (-3.74 to -0.03) < 0.001 -2.51 (-3.85 to -0.25) -2.43 (-3.79 to -0.15) -2.14 (-3.60 to -0.49) < 0.001 -2.40 (-3.81 to -0.04) -2.44 (-3.80 to -0.18) -2.33 (-3.70 to 0.12) < 0.001 College or University degree (%) 22349 (46.1) 54921 (37.6) 41998 (23.6) < 0.001 28506 (39.9) 74674 (34.3) 16090 (19.2) < 0.001 31126 (44.4) 51547 (36.6) 36595 (22.6) < 0.001 Smoking status (%) < 0.001 < 0.001 < 0.001 Never 29394 (60.5) 84444 (57.7) 91060 (50.7) 41884 (58.5) 121183 (55.5) 41831 (49.5) 42396 (60.4) 80441 (56.9) 82061 (50.3) Previous 14955 (30.8) 49052 (33.5) 68429 (38.1) 23072 (32.2) 76858 (35.2) 32506 (38.5) 21886 (31.2) 48041 (34.0) 62509 (38.4) Current 4225 (8.7) 12942 (8.8) 20017 (11.2) 6705 (9.4) 20376 (9.3) 10103 (12.0) 5957 (8.5) 12783 (9.1) 18444 (11.31) Alcohol consumption (%) < 0.001 < 0.001 0.374 Never/special occasions only 9204 (18.9) 23046 (15.7) 29984 (16.7) 12552 (17.5) 34126 (15.6) 15556 (18.4) 12359 (17.6) 21929 (15.5) 27946 (17.1) No more than 2 times/week 17876 (36.8) 55169 (37.6) 67168 (37.3) 27104 (37.8) 81193 (37.1) 31916 (37.7) 26236 (37.3) 52903 (37.4) 61074 (37.3) More than 2 times/week 21566 (44.3) 68500 (46.7) 82922 (46.05) 32148 (44.8) 103554 (47.3) 37286 (44.0) 31756 (45.1) 66692 (47.1) 74540 (45.6) Body mass index (kg/m 2 ), mean (SD) 27.3 ± 5.2 27.2 ± 4.7 27.5 ± 4.6 < 0.001 27.5 ± 5.2 27.2 ± 4.6 27.7 ± 4.5 < 0.001 27.3 ± 5.1 27.2 ± 4.7 27.5 ± 4.5 < 0.001 Occupation (%) < 0.001 < 0.001 < 0.001 retired 7326 (15.1) 39381 (26.9) 81935 (45.7) 15787 (22.06) 74867 (34.3) 37988 (45.0) 11869 (16.9) 41720 (29.6) 75053 (46.1) others 41161 (84.9) 106786 (73.1) 97441 (54.3) 55790 (77.94) 143182 (65.7) 46416 (55.0) 58258 (83.1) 99276 (70.4) 87854 (53.9) PM 2.5 (ug/m 3 ), mean (SD) 10.01 ± 1.07 9.93 ± 1.03 9.88 ± 1.02 < 0.001 9.90 ± 1.01 9.91 ± 1.03 9.94 ± 1.05 < 0.001 9.96 ± 1.05 9.92 ± 1.02 9.89 ± 1.03 < 0.001 Dietary pattern (%) < 0.001 < 0.001 < 0.001 unhealthy 25425 (52.2) 67690 (46.1) 77732 (43.1) 37118 (51.7) 96850 (44.2) 36879 (43.5) 36420 (51.8) 64311 (45.4) 70116 (42.9) healthy 23243 (47.8) 79075 (53.9) 102434 (56.9) 34714 (48.3) 122103 (55.8) 47935 (56.5) 33955 (48.3) 77266 (54.6) 93531 (57.2) Table 1 . Baseline characteristics of participants (continued). Vitamin D supplementation (%) 2038 (4.2) 5439 (3.7) 6441 (3.6) < 0.001 2737 (3.8) 8277 (3.8) 2904 (3.4) < 0.001 2799 (4.0) 5310 (3.8) 5809 (3.6) < 0.001 Use of sun/UV protection (%) 0.04 < 0.001 < 0.001 Never/rarely 4127 (8.5) 10214 (7.0) 15497 (8.6) 5159 (7.2) 15557 (7.1) 9122 (10.8) 5374 (7.6) 9661 (6.8) 14803 (9.1) Sometimes 16026 (32.9) 48724 (33.2) 59470 (33.0) 22971 (32.0) 71920 (32.9) 29329 (34.6) 23049 (32.8) 46660 (33.0) 54511 (33.3) Most of the time 18190 (37.4) 57147 (39.0) 63951 (35.5) 27784 (38.7) 83907 (38.3) 27597 (32.6) 27065 (38.5) 55261 (39.0) 56962 (34.8) Always 9471 (19.5) 30062 (20.5) 40836 (22.7) 15266 (21.3) 46665 (21.3) 18438 (21.8) 14008 (19.9) 29439 (20.8) 36922 (22.6) Do not go out in sunshine 837 (1.7) 576 (0.4) 352 (0.2) 632 (0.9) 852 (0.4) 281 (0.33) 861 (1.2) 518 (0.37) 386 (0.2) Genetic risk category (%) < 0.001 0.003 < 0.001 Lower 9867 (20.3) 29603 (20.2) 35649 (19.8) 14595 (20.3) 43768 (20.0) 16756 (19.8) 14312 (20.3) 28411 (20.1) 32396 (19.8) Intermediate 29308 (60.2) 87837 (59.9) 108215 (60.1) 43049 (59.9) 131341 (60.0) 50970 (60.1) 42336 (60.2) 84817 (59.9) 98207 (60.0) Higher 9493 (19.5) 29325 (20.0) 36302 (20.2) 14188 (19.8) 43844 (20.0) 17088 (20.2) 13727 (19.5) 28349 (20.0) 33044 (20.2) Hypertension (%) 22981 (47.2) 75450 (51.4) 107742 (59.8) < 0.001 35752 (49.8) 118429 (54.1) 51992 (61.3) < 0.001 33649 (47.8) 74009 (52.3) 98495 (60.2) < 0.001 Dyslipidaemia (%) 4616 (9.5) 15529 (10.6) 25796 (14.3) < 0.001 7426 (10.3) 25891 (11.8) 12624 (14.9) < 0.001 6662 (9.5) 15446 (10.9) 23833 (14.6) < 0.001 Cardiovascular disease (%) 3275 (6.7) 10267 (7.0) 17525 (9.7) < 0.001 5326 (7.4) 17077 (7.8) 8664 (10.2) < 0.001 4680 (6.7) 10138 (7.2) 16249 (9.9) < 0.001 Cancer (%) 3432 (7.1) 11008 (7.5) 14909 (8.3) < 0.001 5395 (7.5) 17262 (7.9) 6692 (7.9) 0.008 5034 (7.2) 10892 (7.7) 13423 (8.2) < 0.001 IQR, interquartile range; SD, standard deviation; MET, metabolic equivalent. Association of time spent in outdoor light with PD In the fully adjusted model, individuals with longer outdoor light exposure, compared with those with shorter exposure (< 2 hours/day in summer, < 1 hour/day in winter, and < 1.5 hours/day on average), demonstrated a lower risk of PD. Specifically, the risk was 23% lower in summer (HR 0.77; 95% CI, 0.68–0.88), 15% lower in winter (HR 0.85; 95% CI, 0.75–0.96), and 17% lower on average (HR 0.83; 95% CI, 0.73–0.93), following adjustment for covariates. Per 1 hour increase in outdoor light time the risk of PD is decreased by 4%, 4%, and 6% in summer, winter, and on average, respectively (All p < 0.001) (Table 2 ). Table 2 Association between time spent in outdoor light and incident Parkinson’s disease Time spent in outdoor light Events / Total Model 1 a Model 2 b Per 1 hour increase in outdoor light time P Value HR (95% CI) P Value HR (95% CI) P Value Summer 0.96 (0.94, 0.97) < 0.001 3 h/day 1514 / 180166 0.76 (0.67, 0.86) < .0001 0.77 (0.68, 0.88) < 0.001 Winter 0.96 (0.93, 0.98) < 0.001 2 h/day 747 / 84814 0.86 (0.76, 0.97) 0.012 0.85 (0.75, 0.96) 0.010 Average 0.94 (0.92, 0.97) < 0.001 2.5 h/day 1399 / 163647 0.82 (0.73, 0.92) < 0.001 0.83 (0.73, 0.93) 0.001 Abbreviation: HR, hazard ratio; 95% CI, 95% confidence interval. a. Model 1 was adjusted for age and sex. b. Model 2 was adjusted for age, sex, education, Townsend deprivation index, smoking status, alcohol consumption, body mass index, occupation, dietary pattern, vitamin D supplementation, use of sun/UV protection, PM2.5, baseline hypertension, dyslipidaemia, cancer, cardiovascular disease, PRS, first 10 principal components of ancestry, and genotype measurement batch. HR: hazard ratio; CI: confidence interval. Restricted cubic spline analyses suggested a nonlinear association between time spent outdoors light and PD. There was no evidence of non-linearity between outdoor light duration and the incidence of PD. After adjusting for potential covariates, a significant linear relationship correlation was observed between outdoor light time and PD during summer, winter, and the average time existed (All p < 0.001) (Fig S4). In the mediation analyses, physical activity proportions mediated 13.5%, 25.96%, and 15.83% of the associations between time spent in outdoor light and incident PD in summer, winter, and on average, respectively. The proportions mediated by vitamin D were 4.67%, 6.19%, and 4.91%, respectively, and those by sleep patterns were 2.05%, 4.32%, and 2.71%, respectively (All p < 0.05) (Table 3 ). Table 3 Mediation analysis to evaluate whether physical activities, Vitamin D status, and sleep patterns mediated the associations of the time spent in outdoor light with Parkinson’s disease risk Time spent in outdoor light Total Physical activities P Value Vitamin D P Value Sleep patterns P Value Proportion mediated, % (95% CI) Proportion mediated, % (95% CI) Proportion mediated, % (95% CI) Summer 13.5 (2.58, 24.42) 0.015 4.67 (0.23, 9.11) 0.039 2.05 (0.75, 3.36) 0.002 Winter 25.96 (3.96, 47.96) 0.021 6.19 (0.06, 12.31) 0.048 4.32 (1.06, 7.58) 0.009 Average 15.83 (2.00, 29.11) 0.025 4.91 (0.19, 9.63) 0.041 2.71 (0.97, 4.46) 0.002 Adjusted for age, sex, education, Townsend deprivation index, smoking status, alcohol consumption, body mass index, occupation, dietary pattern, vitamin D supplementation, use of sun/UV protection, PM 2.5 , baseline hypertension, dyslipidaemia, cancer, cardiovascular disease, PRS, first 10 principal components of ancestry, and genotype measurement batch. The weighted PRS for PD was normally distributed, and the joint association between PRS, outdoor light time, and the incidence of PD was analysed (Fig. 1 ). Participants with shorter outdoor light time and high PRS had the highest risk of PD in summer (HR 2.48; 95% CI, 1.93–3.19), winter (HR 2.13; 95% CI, 1.65–2.76), and on average (HR 2.27; 95% CI, 1.80–2.86), respectively, compared to the reference group with longer outdoor light time and low PRS. There were no genetic multiplicative interactions in the longitudinal association between outdoor sunlight duration and the incidence of PD (all p interaction > 0.05). In the stratified analyses, studies were categorised according to BMI, sex, age, and occupation. In Tables S4-S6, the interactions of outdoor light time and PD were more pronounced in women and in older adults compared to younger adults in summer and winter ( p interaction < 0.05). The results were consistent across normal-weight and overweight/obese individuals and among different occupations. In the sensitivity analysis, significant associations between outdoor light time and PD remained in summer and on average after further adjusting for total physical activity, vitamin D levels, and sleep patterns (Table S7). Excluding individuals who developed PD within the first 2 years of follow-up and adjusting for competing risk using the Fine-Gray model did not alter the assessment of the association between outdoor light time and PD risk (Table S8). Discussion In this large prospective cohort study, we demonstrated that time spent outdoors light was associated with PD risk. This association was independent of sociodemographic factors, lifestyles, multiple morbidities, and genetic background, and remained in the sensitivity analysis. The correlation between outdoor light time and PD was mainly linear, with the lowest risk of PD at longer outdoor light times (> 3 h/day in summer, > 2 h/day in winter, and > 2.5 h/day on average), which was modestly mediated by physical activity, vitamin D, and healthy sleep patterns. To our knowledge, the large prospective studies to investigate the longitudinal association between outdoor light time and the incidence of PD are scarce. Our findings are consistent with those of previous studies; however, a majority of the studies were cross-sectional and had a limited incidence of PD. In a Danish population-based study, 3819 men diagnosed with PD and 19,282 matched controls were assessed for outdoor work as a measure of sunlight exposure, demonstrating that outdoor workers have a reduced PD risk 6 . Another observational study from a French cohort reported a decreased risk of PD in participants with longer UV-B exposure 16 . Although 69,010 people with PD were included in this study, no exact sunlight exposure time was available. In addition, only UV-B exposure was estimated because of its biological role in vitamin D synthesis, which might overlook the effects of other components of sunlight on the development of PD. Red and near-infrared rays, key sunlight elements, demonstrate health benefits in mitigating age-related chronic diseases like Alzheimer's disease, PD, cardiovascular diseases, and diabetes, as per preliminary studies 17 . These studies suggest that sunlight's protective effect is likely mediated by other components. However, mechanisms underlying the association between sunlight exposure and PD remain unclear. Given that vitamin D, sleep patterns, and physical activity are linked to sunlight exposure, these factors may play essential roles in the association between outdoor light time and PD. Several cross-sectional studies have shown that vitamin D deficiency is common in adults with PD 18 , 19 , and that exposure to sunlight can protect against PD through the synthesis of vitamin D 20 , which has been reported to play various roles in normal brain physiology and to participate in multiple brain processes, including regulation of synaptic plasticity and dopaminergic neurotransmission 21 . Consistent with our mediation analyses, vitamin D had a moderate mediation proportion between time spent in outdoor light and PD. In addition to promoting vitamin D synthesis, sunlight exposure regulates sleep and circadian rhythms via the suprachiasmatic nuclei, which transmits the light information to a network of clocks in tissues and organs, thereby synchronising body physiology and behaviour 22 . A UK Biobank study confirmed that reduced daytime light exposure is a risk factor for sleep and circadian outcomes 13 . The circadian system, crucial in regulating reactive oxygen species homeostasis, influences PD development through melatonin secretion, impacting the brain's antioxidant defence and triggering PD 23 . Consequently, circadian rhythm disruption could hasten PD-related pathology 24 elucidating the link between sunlight exposure, sleep patterns, and PD in our analysis. The strong association of physical activity with PD incidence and prognosis is well-established. Physical activity is strongly associated with the incidence and prognosis of PD has already well known 25 , 26 . Individuals with more outdoor light time may engage in regular physical activity over time, which helps to improve gait speed, muscle strength, and fitness in patients with PD 27 . Furthermore, our mediation analysis revealed a notable mediative effect of physical activity on the sunlight exposure-PD relationship, particularly in winter. The seasonal variation in PD could stem from winter's colder, cloudier conditions with reduced sunlight. Thus, sunlight's role in this association is less significant compared to summer. Recent studies have shown a link between sunlight and dopamine transporters (DAT). In PD patients, left caudate nucleus DAT availability peaked in spring/summer, correlating positively with prolonged sunlight exposure, indicating daylight-dependent dopaminergic neurotransmission alterations 28 . The relationship between sunlight exposure and PD was more robust among older and female participants than among younger and male ones; this age tendency is consistent with previous studies 16 . Some reasons might explain our findings that females are more likely to be affected by temperature and have fewer clothes with more skin exposed compared to males 29 . Older adults are more susceptible to PD due to age-related changes 1 . Outdoor light's benefits manifest slower in this group, attributed to diminished skin thickness and declining serum 25(OH)D levels with age 30 . Increasing outdoor light exposure might be a simple, accessible, non-pharmacological method to protect aginst PD in community settings. Nevertheless, excessive sunlight is linked to skin cancer, diabetes, and dementia 11 , 31 , 32 . Thus, enhance clinicians’ understanding of the association of outdoor sunlight and PD, and then give comprehensive guidance on optimal outdoor light duration, which is essential for PD prevention in the elderly. Our study’s strengths lie in its large sample size and the prolonged follow-up, covering a crucial PD development phase. Furthermore, utilizing the UK Biobank we examined this association in a well-characterized general population cohort, adjusting for numerous potential confounders, including PD’s genetic susceptibility. This study has some limitations. First, the observational nature precludes causal inference, leaving open the possibility of reverse causality in the observed associations. Second, potential recall bias arises from self-reported outdoor light exposure. Third, the exclusive inclusion of Caucasian participants limits generalisability to other ethnicities. Fourth, while accounting for numerous confounders, various psychosocial and environmental factors influencing PD onset remain unaddressed. Finally, PD diagnosis relied on hospital admissions and death records, possibly overlooking early PD stages. Conclusions Longer outdoor light time (> 3 h/day in summer, > 2 h/day in winter, and > 2.5 h/day on average) was associated with a lower PD risk over 13 years of follow-up and was modestly mediated by physical activity, vitamin D, and sleep patterns. The associations of outdoor light exposure and PD were independent of genetic risk. These findings probably highlight the importance of providing detailed guidance on sunlight exposure for long-term PD prevention. Declarations Funding sources YFL was supported by the National Nature Science Foundation of China (82070830) and National Key Research and Development Program of Hubei province (2022BCA036). CrediT Author Contribution Statement Yumei Huang : Methodology, Data curation, Investigation, Validation, Writing – original draft, Writing – review & editing. Shufan Tian : Methodology, Formal analysis, Software, Writing – original draft. Kangli Qiu : Visualization, Roles/Writing-original draft, Writing-review&editing. Jinchi Xie : Data curation, Methodology. An Pan : Supervision, Resources. Gang Liu : Project administration, Resources, Validation. Yunfei Liao : Conceptualization, Supervision, Project administration, Funding acquisition. Data Availability This research has been carried out using the UKB resource under application number 68307. Data is available on application to the UKB at http://www.ukbiobank.ac.uk/register-apply Declaration of competing interest The authors declare that there are no known competing financial interests. Data Statement The data has not been previously presented orally or by poster at scientific meetings. Author Contribution Yumei Huang, Shufan Tian and Kangli Qiu wrote the main manuscript text. Yumei Huang, Kangli Qiu, and Jinchi Xie contributed to the methodology and data curation. Shufan Tian performed formal analysis while Yumei Huang was responsible for visualization. An Pan provided supervision and resources, and Gang Liu handled project administration and validation. Yunfei Liao conceptualized the project and acquired funding. Acknowledgement We thank all participants in the UKB study and all those involved in the UKB study construction. References Tansey MG, et al. Inflammation and immune dysfunction in Parkinson disease. Nat Rev Immunol. 2022;22:657–73. 10.1038/s41577-022-00684-6 . WHO. WHO's Parkinson disease technical brief , https://www.who.int/news/item/14-06-2022-launch-of-who-s-parkinson-disease-technical-brief Deuschl G, et al. The burden of neurological diseases in Europe: an analysis for the Global Burden of Disease Study 2017. Lancet Public Health. 2020;5:e551–67. 10.1016/s2468-2667(20)30190-0 . Knekt P, et al. Serum vitamin D and the risk of Parkinson disease. Arch Neurol. 2010;67:808–11. 10.1001/archneurol.2010.120 . Wang J, Yang D, Yu Y, Shao G, Wang Q. Vitamin D and Sunlight Exposure in Newly-Diagnosed Parkinson's Disease. Nutrients. 2016;8:142. 10.3390/nu8030142 . Kenborg L, et al. Outdoor work and risk for Parkinson's disease: a population-based case-control study. Occup Environ Med. 2011;68:273–8. 10.1136/oem.2010.057448 . Gasser T. Mendelian forms of Parkinson's disease. Biochim Biophys Acta. 2009;1792:587–96. 10.1016/j.bbadis.2008.12.007 . Wirdefeldt K, Adami HO, Cole P, Trichopoulos D, Mandel J. Epidemiology and etiology of Parkinson's disease: a review of the evidence. Eur J Epidemiol. 2011;26(Suppl 1):S1–58. 10.1007/s10654-011-9581-6 . Pang SY, et al. The interplay of aging, genetics and environmental factors in the pathogenesis of Parkinson's disease. Transl Neurodegener. 2019;8:23. 10.1186/s40035-019-0165-9 . Littlejohns TJ, Sudlow C, Allen NE, Collins R. UK Biobank: opportunities for cardiovascular research. Eur Heart J. 2019;40:1158–66. 10.1093/eurheartj/ehx254 . Ma LZ, et al. Time spent in outdoor light is associated with the risk of dementia: a prospective cohort study of 362094 participants. BMC Med. 2022;20:132. 10.1186/s12916-022-02331-2 . UK, Biobank. Algorithmically-defined outcomes (ADOs) Version 2.0. (Accessed February 3, 2023.). Burns AC, et al. Time spent in outdoor light is associated with mood, sleep, and circadian rhythm-related outcomes: A cross-sectional and longitudinal study in over 400,000 UK Biobank participants. J Affect Disord. 2021;295:347–52. 10.1016/j.jad.2021.08.056 . Chang D, et al. A meta-analysis of genome-wide association studies identifies 17 new Parkinson's disease risk loci. Nat Genet. 2017;49:1511–6. 10.1038/ng.3955 . Bycroft C, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9. 10.1038/s41586-018-0579-z . Kravietz A, et al. Association of UV radiation with Parkinson disease incidence: A nationwide French ecologic study. Environ Res. 2017;154:50–6. 10.1016/j.envres.2016.12.008 . Heiskanen V, Pfiffner M, Partonen T. Sunlight and health: shifting the focus from vitamin D3 to photobiomodulation by red and near-infrared light. Ageing Res Rev. 2020;61:101089. 10.1016/j.arr.2020.101089 . Barichella M, et al. Vitamin D Status and Parkinson's Disease. Brain Sci. 2022;12. 10.3390/brainsci12060790 . Evatt ML, et al. High prevalence of hypovitaminosis D status in patients with early Parkinson disease. Arch Neurol. 2011;68:314–9. 10.1001/archneurol.2011.30 . Pertile RA, Cui X, Eyles DW. Vitamin D signaling and the differentiation of developing dopamine systems. Neuroscience. 2016;333:193–203. 10.1016/j.neuroscience.2016.07.020 . McSharry C. Parkinson disease: Could sunlight offer protection from Parkinson disease? Nat Rev Neurol. 2010;6:468. 10.1038/nrneurol.2010.120 . Peterson AL, et al. Memory, mood, and vitamin D in persons with Parkinson's disease. J Parkinsons Dis. 2013;3:547–55. 10.3233/jpd-130206 . Xie L, et al. Sleep drives metabolite clearance from the adult brain. Science. 2013;342:373–7. 10.1126/science.1241224 . Kondratova AA, Kondratov RV. The circadian clock and pathology of the ageing brain. Nat Rev Neurosci. 2012;13:325–35. 10.1038/nrn3208 . Breen DP, et al. Sleep and circadian rhythm regulation in early Parkinson disease. JAMA Neurol. 2014;71:589–95. 10.1001/jamaneurol.2014.65 . Cugusi L, et al. Aquatic exercise improves motor impairments in people with Parkinson's disease, with similar or greater benefits than land-based exercise: a systematic review. J Physiother. 2019;65:65–74. 10.1016/j.jphys.2019.02.003 . Yoon SY, Suh JH, Yang SN, Han K, Kim YW. Association of Physical Activity, Including Amount and Maintenance, With All-Cause Mortality in Parkinson Disease. JAMA Neurol. 2021;78:1446–53. 10.1001/jamaneurol.2021.3926 . Booij J, Tellier SP, Seibyl J, Vriend C. Dopamine Transporter Availability in Early Parkinson's Disease is Dependent on Sunlight Exposure. Mov Disord. 2023;38:2131–5. 10.1002/mds.29597 . Keller MC, et al. A warm heart and a clear head. The contingent effects of weather on mood and cognition. Psychol Sci. 2005;16:724–31. 10.1111/j.1467-9280.2005.01602.x . Need AG, Morris HA, Horowitz M, Nordin C. Effects of skin thickness, age, body fat, and sunlight on serum 25-hydroxyvitamin D. Am J Clin Nutr. 1993;58:882–5. 10.1093/ajcn/58.6.882 . Hernando B, et al. The effect of age on the acquisition and selection of cancer driver mutations in sun-exposed normal skin. Ann Oncol. 2021;32:412–21. 10.1016/j.annonc.2020.11.023 . Lin J, et al. Association of time spent in outdoor light and genetic susceptibility with the risk of type 2 diabetes. Sci Total Environ. 2023;888:164253. 10.1016/j.scitotenv.2023.164253 . Additional Declarations No competing interests reported. Supplementary Files supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5773642","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":399407070,"identity":"e6a55c5f-12bd-4971-af6f-7734cbd99207","order_by":0,"name":"Yumei Huang","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Yumei","middleName":"","lastName":"Huang","suffix":""},{"id":399407071,"identity":"edf56ceb-cda0-4e7f-afa9-5af4089b1795","order_by":1,"name":"Shufan Tian","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Shufan","middleName":"","lastName":"Tian","suffix":""},{"id":399407074,"identity":"501aff84-3833-4046-b87b-27059242ec7b","order_by":2,"name":"Kangli Qiu","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Kangli","middleName":"","lastName":"Qiu","suffix":""},{"id":399407075,"identity":"9eea53ee-e362-49db-8b27-b764f7887b5f","order_by":3,"name":"Jinchi Xie","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Jinchi","middleName":"","lastName":"Xie","suffix":""},{"id":399407077,"identity":"41e81690-a006-495e-9b31-94a3dd8e75d9","order_by":4,"name":"An Pan","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"An","middleName":"","lastName":"Pan","suffix":""},{"id":399407078,"identity":"3a04ce48-30a3-4e96-9b32-885f9ff7c28b","order_by":5,"name":"Gang Liu","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"Liu","suffix":""},{"id":399407079,"identity":"f91286f9-a591-469e-a308-657237d7313b","order_by":6,"name":"Yunfei Liao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIie3QMUsDMRTA8RyBm55mfQfF+hESBKtw2K/yjkKnUzo6phzURXA9v4jzO4R2OXQ96HLi6pBuCkVMZzHt6JD/Ekjyg7wIEYv905zQFyCEZKbbHJSye0VSC42epEXft9NBVvMhRKBf4cy8LZ5zbSl8X3fXjXUzHKg7e46UvoIWnLhNGSI3xbz2D8OWp0iwhpG0Mnt8CpFy9A67WTpaIuEaLi2n8ihMTLX1ZNgVCyT9AprpALL7Md1NpCbi/SRrP8z83hPTLpOeeAJZ3VTBWY5XpbGf23x8snpwzdf31VipqnGbADnl33uJ/fu+bxg+jsVisZjvBzWFVl+CtbDlAAAAAElFTkSuQmCC","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Yunfei","middleName":"","lastName":"Liao","suffix":""}],"badges":[],"createdAt":"2025-01-06 12:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5773642/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5773642/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73516844,"identity":"ba0325a0-8c5b-441a-aef7-56c7193cc8c3","added_by":"auto","created_at":"2025-01-10 17:50:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":227660,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of incident Parkinson’s disease according to genetic risk and time spent outdoors\u003c/p\u003e\n\u003cp\u003eAdjusted for age, sex, education, Townsend deprivation index, smoking status, alcohol consumption, body mass index, occupation, dietary pattern, vitamin D supplementation, use of sun/UV protection, PM2.5, baseline hypertension, dyslipidaemia, cancer, cardiovascular disease, first 10 principal components of ancestry, and genotype measurement batch. HR: hazard ratio; CI: confidence interval.\u003c/p\u003e","description":"","filename":"figure.png","url":"https://assets-eu.researchsquare.com/files/rs-5773642/v1/3e36c3a1cc7f910012710981.png"},{"id":76256621,"identity":"3d4f9ba3-a2e2-4f7c-893b-073ece67a4f1","added_by":"auto","created_at":"2025-02-14 05:09:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1539731,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5773642/v1/da7650b6-c5e6-4c54-a27f-5831d5a9b42c.pdf"},{"id":73516846,"identity":"68dab53a-4289-4828-a407-eb17e5500808","added_by":"auto","created_at":"2025-01-10 17:50:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":669963,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5773642/v1/b5e3c1244169de86646c6aa9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Outdoor Light Spending Time, Genetic Predisposition and Incident Parkinson's Disease： The mediating effect of lifestyle and vitamin D","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParkinson's disease (PD) is the second most common neurodegenerative disease in the world and is characterised by bradykinesia, rigidity, postural instability, and resting tremor\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In 2019, the global estimates show over 8.5\u0026nbsp;million individuals living with PD, resulting in 329,000 deaths and 5.8\u0026nbsp;million disability-adjusted life years\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The global burden of PD, in terms of deaths and disability, has more than doubled in the past two decades, representing the fastest-increasing disease among all neurological disorders\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Importantly, PD is a progressive disease with limited therapeutic effectiveness, suggesting the importance of prevention.\u003c/p\u003e \u003cp\u003eGrowing evidence has suggested that outdoor light is beneficial for promoting health\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, and outdoor light exposure is associated with a variety of neurobehaviors related to the central nervous system\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, there is little research on the effects of time spent in outdoor light on the risk of developing PD. Outdoor light exposure has an important effect on vitamin D status, sleep and circadian rhythms, and physical activity, many of these are closely related to PD. A case-control study of 201 newly diagnosed PD patients and 199 controls found that PD patients had shorter outdoor sunlight exposure time than control\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Due to the small sample size, the findings may not be generalisable to the general population. To date, the correlation between outdoor light and PD risk in prospective studies based on large populations is unknown, and the dose-response association between them remains uncertain. We also conducted a mediation analysis of above factors to ascertain the relationship between outdoor sunlight exposure time and the incidence of PD.\u003c/p\u003e \u003cp\u003eThe development of PD is influenced by both genetic and environmental factors \u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. yet the role of genetic predisposition in the relationship between time spent in outdoor light and PD remains largely uncertain. Exploring the association between sunlight exposure time and the genetic risk of PD can aid in identifying effective strategies to mitigate PD risk. To address these knowledge gaps, we investigated the optimal duration for protection against PD risk and examined if exposure to outdoor light could modify the association between genetic predisposition and PD risk.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eThe UK Biobank is a large population-based cohort study that recruited approximately half a million participants aged 40\u0026ndash;69 years from 2006 to 2010 across England, Scotland, and Wales. Each participant completed touchscreen questionnaires, underwent a physical examination, and provided biological samples\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor the current analyses, we excluded individuals who subsequently withdrew from the study (n\u0026thinsp;=\u0026thinsp;1,432), those diagnosed with Parkinson's Disease (PD) (n\u0026thinsp;=\u0026thinsp;944) at baseline, those with incomplete data on time spent in outdoor light, and respondents who reported 'do not know' or 'prefer not to answer' regarding outdoor light, or provided extreme values exceeding the typical day length in the UK during summer (16 h) and winter (8 h) (n\u0026thinsp;=\u0026thinsp;45,233), based on the effective daytime duration in the UK\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Participants with incomplete genetic information (n\u0026thinsp;=\u0026thinsp;10,338), those displaying non-conforming sex in phenotypic and genetic data (n\u0026thinsp;=\u0026thinsp;314), and individuals not of European descent (n\u0026thinsp;=\u0026thinsp;68,634) were also excluded from the analysis. Following these exclusions, 375,599 participants were included in the main analysis (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAscertainment of outcomes\u003c/h3\u003e\n\u003cp\u003eParticipants with Parkinson\u0026rsquo;s disease were identified using the algorithm recommended by the UK Biobank\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, and detailed definitions are shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Disease information was obtained from hospital admission electronic health records and death registers through linkages with the Hospital Episode Statistics for England, Scottish Morbidity Records for Scotland, and the Patient Episode Database for Wales. At the time of our analyses, the censoring dates for Hospital Episode Statistics were 1 November, 2021, for England, 25 September, 2021, for Scotland, and 29 May, 2021, for Wales. We calculated the follow-up time from baseline to PD diagnosis, death, loss to follow-up, or censorship, whichever occurred first.\u003c/p\u003e\n\u003ch3\u003eAssessment of time spent in outdoor light\u003c/h3\u003e\n\u003cp\u003eThe duration of outdoor light during typical daylight in summer or winter was recorded using an electronic questionnaire at baseline\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Participants were asked, 'In a typical day in summer or winter, how many hours do you spend outdoors?' They could enter a specific number or choose from pre-set options including 'less than an hour a day', 'do not know', or 'prefer not to answer'. Participants spending considerable time outdoors reported the average time spent. A moderate correlation was observed between summer and winter outdoor light exposure, as per Pearson's correlation analysis (r\u0026thinsp;=\u0026thinsp;0.64, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Consequently, we examined the association between outdoor light exposure in summer and winter and the risk of incident Parkinson\u0026rsquo;s disease. Furthermore, to derive a singular measure of outdoor light exposure, we calculated the average time based on summer and winter data.\u003c/p\u003e\n\u003ch3\u003eAssessment of covariates\u003c/h3\u003e\n\u003cp\u003eStructured questionnaires were used to assess several possible confounding variables: sociodemographic characteristics (age, sex, ethnicity, education, and occupation), socioeconomic status (Townsend Deprivation Index), lifestyle factors (physical activity, sleep pattern, smoking, alcohol consumption, and usual diet), comorbidities (hypertension, dyslipidaemia, cardiovascular disease, and cancer) at the time of recruitment, vitamin D supplementation, vitamin D levels, and outdoor environmental-related variables (use of sun/UV protection and PM2.5). Townsend Deprivation Index scores represent the level of socioeconomic deprivation. Body mass index (BMI) was determined as weight in kilograms divided by the square of the height in meters. Physical activity, including moderate and vigorous-intensity activities, was evaluated as the metabolic equivalent of task (MET) minutes per week and was categorised as \u0026lt;\u0026thinsp;10 MET-h/week or \u0026ge;\u0026thinsp;10 MET-h/week. The healthy sleep pattern score was generated based on a combination of chronotype, sleep duration, insomnia, snoring, and excessive daytime sleepiness. Smoking status was categorised as 'never smoked', 'former smoker', or 'current smoker'. Hypertension was defined as elevated mean blood pressure (mean systolic/diastolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg), a physician\u0026rsquo;s diagnosis of hypertension, or self-reported current use of antihypertensive medications. We defined hyperlipidaemia as those with a physician\u0026rsquo;s diagnosis of the condition or self-reported current usage of lipid-lowering medications. Additionally, we included the PD-polygenic risk score (PRS), a genotyping array, and the first 10 principal components of ancestry as covariates.\u003c/p\u003e\n\u003ch3\u003eAssessment of polygenic risk score\u003c/h3\u003e\n\u003cp\u003eThe PRS showed the association between genotype and risk of PD by score points and was composed of 44 single nucleotide polymorphisms (SNPs), which were associated with the incidence of PD in white participants\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Details regarding these SNPs are provided in Table S2. Moreover, details on genotyping and quality control can be found online\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. We constructed the weighted PRS of PD based on 44 SNPs using the following formula:\u003c/p\u003e \u003cp\u003ePRS = (β1 \u0026times; SNP1\u0026thinsp;+\u0026thinsp;β2 \u0026times; SNP2 + \u0026hellip; + β44 \u0026times; SNP44) \u0026times; (44 / sum of β coefficients)\u003c/p\u003e \u003cp\u003eThe PRS of PD exhibited a normal distribution (Fig S2), with a higher score signifying increased genetic susceptibility to PD (Table S3).Participants were classified as having low (quintile 1), intermediate (quintiles 2 to 4), or high (quintile 5) genetic risk for each outcome.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eSample characteristics are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations for normally distributed continuous variables, medians (interquartile ranges) for non-normally distributed continuous variables, and numbers with percentages for categorical variables. Differences between groups were compared using the Student's t-test, Wilcoxon test, or chi-squared test, when appropriate.\u003c/p\u003e \u003cp\u003eCox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between the time spent outdoors and the risk of incident PD. Schoenfeld residuals were used to test the proportional hazards assumption, and no violations were observed. In model 1, we adjusted for age and sex. Model 2 (full model) was further adjusted for education, Townsend deprivation index, smoking status, alcohol consumption, BMI, dietary pattern, vitamin D supplementation, use of sun/UV protection, PM2.5, baseline hypertension, dyslipidaemia, cancer, cardiovascular disease, PRS, the first ten principal components of ancestry, and genotype measurement batch. To investigate the dose-response relationship between time spent in outdoor light and the risk of PD, a restricted cubic spline model with three knots (at the 10th, 50th, and 90th percentiles) was employed. The missing values of the covariates were imputed and analysed using multiple imputations with five imputations (SAS PROC MI and PROC MIANALYZE).\u003c/p\u003e \u003cp\u003eTo assess the joint association between outdoor light time and PD-PRS on the risk of PD, we treated participants with a low PRS and long outdoor light time as the reference group to conduct a joint analysis of the association between outdoor light time and the genetic risk of PD. Furthermore, we calculated the interaction between the outdoor light time and PD-PRS on a multiplicative scale. Multiplicative interactions were assessed by comparing models with and without a cross-product interaction term for outdoor light and the genetic risk of PD using likelihood ratio tests.\u003c/p\u003e \u003cp\u003eStratified analyses and interactions were performed to examine the association between outdoor light time and incident PD according to age, sex, BMI, and occupation. A directed acyclic graph explaining the association between the exposures, the outcome, and the covariates is available in Fig S3. Mediation analysis was performed to evaluate the proportional contribution of vitamin D, physical activity, and sleep patterns to the association between outdoor light time and PD risk (SAS PROC CAUSALMED). The mediation analysis models were adjusted for the same set of confounders as in Model 2 of the primary analyses. To test the robustness of the results, vitamin D levels, total physical activity, and sleep patterns were adjusted in addition to the variables in Model 2. We also repeated the analyses after excluding individuals who died or developed PD within 2 years of follow-up to minimise potential reverse causality and used the Fine-Gray subdistribution hazard model.\u003c/p\u003e \u003cp\u003eAll analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA) and R software (version 4.3.1; R Foundation for Statistical Computing). A two-sided \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical Compliance\u003c/h3\u003e\n\u003cp\u003eAll participants in the UK Biobank provided informed consent at the time of recruitment, allowing their data to be used for a wide range of research purposes. We adhere to the terms and conditions set by the UK Biobank in the use of this data.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the study population\u003c/h2\u003e \u003cp\u003eA total of 375,599 participants (mean age, 56.8 years; 173688 males 46.3%) with a median follow-up of 13.7 years (interquartile range: 13.13\u0026ndash;14.31) were included in this prospective study, and 2,824 individuals were first-ever diagnosed with PD. Baseline demographics and characteristics according to outdoor light hours are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Overall, individuals with longer outdoor light exposure times (\u0026gt;\u0026thinsp;3 h/day in summer; \u0026gt;2 h/day in winter; \u0026gt;2.5 h/day on average) tended to be older, male, retired, current smokers, have lower education levels, and have a higher genetic risk of PD.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eOutdoor light time in summer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eOutdoor light time in winter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eOutdoor light time on average\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 to 3 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 to 2 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1.5 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.5 to 2.5 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2.5 h/day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e180166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e218953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e70375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e141577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e163647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e56.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e58.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28347 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84660 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88904 (49.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45634 (63.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121957 (55.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34320 (40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42383 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e81824 (57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e77704 (47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTownsend deprivation index, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.27 (-3.74 to -0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.41 (-3.79 to -0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.39 (-3.74 to -0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.51 (-3.85 to -0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.43 (-3.79 to -0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.14 (-3.60 to -0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.40 (-3.81 to -0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.44 (-3.80 to -0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.33 (-3.70 to 0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege or University degree (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22349 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54921 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41998 (23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28506 (39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74674 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16090 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31126 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e51547 (36.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e36595 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29394 (60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84444 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91060 (50.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41884 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121183 (55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41831 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42396 (60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e80441 (56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e82061 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14955 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49052 (33.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68429 (38.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23072 (32.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76858 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32506 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21886 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e48041 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e62509 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4225 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12942 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20017 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6705 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20376 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10103 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5957 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12783 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e18444 (11.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol consumption (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever/special occasions only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9204 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23046 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29984 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12552 (17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34126 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15556 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12359 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21929 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e27946 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo more than 2 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17876 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55169 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67168 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27104 (37.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81193 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31916 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26236 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e52903 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e61074 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 2 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21566 (44.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68500 (46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82922 (46.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32148 (44.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103554 (47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37286 (44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31756 (45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e66692 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e74540 (45.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e), mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eretired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7326 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39381 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81935 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15787 (22.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74867 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37988 (45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11869 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e41720 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e75053 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41161 (84.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106786 (73.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97441 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55790 (77.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e143182 (65.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e46416 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e58258 (83.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e99276 (70.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e87854 (53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM\u003csub\u003e2.5\u003c/sub\u003e (ug/m\u003csup\u003e3\u003c/sup\u003e), mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary pattern (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunhealthy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25425 (52.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67690 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77732 (43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37118 (51.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96850 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36879 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e36420 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e64311 (45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e70116 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehealthy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23243 (47.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79075 (53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102434 (56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34714 (48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e122103 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47935 (56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33955 (48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e77266 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e93531 (57.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eBaseline characteristics of participants\u003c/b\u003e \u003cem\u003e(continued).\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin D supplementation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2038 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5439 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6441 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2737 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8277 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2904 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2799 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5310 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5809 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of sun/UV protection (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever/rarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4127 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10214 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15497 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5159 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15557 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9122 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5374 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9661 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e14803 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16026 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48724 (33.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59470 (33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22971 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71920 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29329 (34.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23049 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e46660 (33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e54511 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMost of the time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18190 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57147 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63951 (35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27784 (38.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83907 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27597 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27065 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e55261 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e56962 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9471 (19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30062 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40836 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15266 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46665 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18438 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14008 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29439 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e36922 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo not go out in sunshine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e837 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e576 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e352 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e632 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e852 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e281 (0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e861 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e518 (0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e386 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenetic risk category (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9867 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29603 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35649 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14595 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43768 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16756 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14312 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e28411 (20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e32396 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29308 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87837 (59.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108215 (60.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43049 (59.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e131341 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50970 (60.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42336 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e84817 (59.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e98207 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9493 (19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29325 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36302 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14188 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43844 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17088 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13727 (19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e28349 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e33044 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22981 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75450 (51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107742 (59.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35752 (49.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e118429 (54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51992 (61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33649 (47.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e74009 (52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e98495 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidaemia (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4616 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15529 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25796 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7426 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25891 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12624 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6662 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15446 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e23833 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3275 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10267 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17525 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5326 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17077 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8664 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4680 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10138 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e16249 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3432 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11008 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14909 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5395 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17262 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6692 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5034 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10892 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e13423 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eIQR, interquartile range; SD, standard deviation; MET, metabolic equivalent.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of time spent in outdoor light with PD\u003c/h2\u003e \u003cp\u003eIn the fully adjusted model, individuals with longer outdoor light exposure, compared with those with shorter exposure (\u0026lt;\u0026thinsp;2 hours/day in summer, \u0026lt;\u0026thinsp;1 hour/day in winter, and \u0026lt;\u0026thinsp;1.5 hours/day on average), demonstrated a lower risk of PD. Specifically, the risk was 23% lower in summer (HR 0.77; 95% CI, 0.68\u0026ndash;0.88), 15% lower in winter (HR 0.85; 95% CI, 0.75\u0026ndash;0.96), and 17% lower on average (HR 0.83; 95% CI, 0.73\u0026ndash;0.93), following adjustment for covariates. Per 1 hour increase in outdoor light time the risk of PD is decreased by 4%, 4%, and 6% in summer, winter, and on average, respectively (All \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between time spent in outdoor light and incident Parkinson\u0026rsquo;s disease\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime spent in outdoor light\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEvents / Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eModel 1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModel 2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePer 1 hour increase in outdoor light time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.96 (0.94, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298 / 48668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 to 3 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1012 / 146765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89 (0.78, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91 (0.80, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1514 / 180166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76 (0.67, 0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77 (0.68, 0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.96 (0.93, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e417 / 71832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 to 2 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1660 / 218953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.88, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.89, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e747 / 84814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86 (0.76, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.85 (0.75, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.94 (0.92, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1.5 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e403 / 70375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.5 to 2.5 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1022/ 141577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97 (0.86, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.88, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2.5 h/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1399 / 163647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82 (0.73, 0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83 (0.73, 0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eAbbreviation: HR, hazard ratio; 95% CI, 95% confidence interval.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003ea. Model 1 was adjusted for age and sex.\u003c/p\u003e \u003cp\u003eb. Model 2 was adjusted for age, sex, education, Townsend deprivation index, smoking status, alcohol consumption, body mass index, occupation, dietary pattern, vitamin\u003c/p\u003e \u003cp\u003eD supplementation, use of sun/UV protection, PM2.5, baseline hypertension, dyslipidaemia, cancer, cardiovascular disease, PRS, first 10 principal components of ancestry, and genotype measurement batch. HR: hazard ratio; CI: confidence interval.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRestricted cubic spline analyses suggested a nonlinear association between time spent outdoors light and PD. There was no evidence of non-linearity between outdoor light duration and the incidence of PD. After adjusting for potential covariates, a significant linear relationship correlation was observed between outdoor light time and PD during summer, winter, and the average time existed (All \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig S4).\u003c/p\u003e \u003cp\u003eIn the mediation analyses, physical activity proportions mediated 13.5%, 25.96%, and 15.83% of the associations between time spent in outdoor light and incident PD in summer, winter, and on average, respectively. The proportions mediated by vitamin D were 4.67%, 6.19%, and 4.91%, respectively, and those by sleep patterns were 2.05%, 4.32%, and 2.71%, respectively (All \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMediation analysis to evaluate whether physical activities, Vitamin D status, and sleep patterns mediated the associations of the time spent in outdoor light with Parkinson\u0026rsquo;s disease risk\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime spent in outdoor light\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Physical activities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c4\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVitamin D\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c7\" namest=\"c6\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSleep patterns\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c10\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion mediated, % (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProportion mediated, % (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eProportion mediated, % (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e13.5 (2.58, 24.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.67 (0.23, 9.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2.05 (0.75, 3.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e25.96 (3.96, 47.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e6.19 (0.06, 12.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e4.32 (1.06, 7.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15.83 (2.00, 29.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.91 (0.19, 9.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2.71 (0.97, 4.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eAdjusted for age, sex, education, Townsend deprivation index, smoking status, alcohol consumption, body mass index, occupation, dietary pattern, vitamin D supplementation, use of sun/UV protection, PM\u003csub\u003e2.5\u003c/sub\u003e, baseline hypertension, dyslipidaemia, cancer, cardiovascular disease, PRS, first 10 principal components of ancestry, and genotype measurement batch.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe weighted PRS for PD was normally distributed, and the joint association between PRS, outdoor light time, and the incidence of PD was analysed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Participants with shorter outdoor light time and high PRS had the highest risk of PD in summer (HR 2.48; 95% CI, 1.93\u0026ndash;3.19), winter (HR 2.13; 95% CI, 1.65\u0026ndash;2.76), and on average (HR 2.27; 95% CI, 1.80\u0026ndash;2.86), respectively, compared to the reference group with longer outdoor light time and low PRS. There were no genetic multiplicative interactions in the longitudinal association between outdoor sunlight duration and the incidence of PD (all \u003cem\u003ep\u003c/em\u003e interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In the stratified analyses, studies were categorised according to BMI, sex, age, and occupation. In Tables S4-S6, the interactions of outdoor light time and PD were more pronounced in women and in older adults compared to younger adults in summer and winter (\u003cem\u003ep\u003c/em\u003e interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The results were consistent across normal-weight and overweight/obese individuals and among different occupations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the sensitivity analysis, significant associations between outdoor light time and PD remained in summer and on average after further adjusting for total physical activity, vitamin D levels, and sleep patterns (Table S7). Excluding individuals who developed PD within the first 2 years of follow-up and adjusting for competing risk using the Fine-Gray model did not alter the assessment of the association between outdoor light time and PD risk (Table S8).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large prospective cohort study, we demonstrated that time spent outdoors light was associated with PD risk. This association was independent of sociodemographic factors, lifestyles, multiple morbidities, and genetic background, and remained in the sensitivity analysis. The correlation between outdoor light time and PD was mainly linear, with the lowest risk of PD at longer outdoor light times (\u0026gt;\u0026thinsp;3 h/day in summer, \u0026gt;\u0026thinsp;2 h/day in winter, and \u0026gt;\u0026thinsp;2.5 h/day on average), which was modestly mediated by physical activity, vitamin D, and healthy sleep patterns.\u003c/p\u003e \u003cp\u003eTo our knowledge, the large prospective studies to investigate the longitudinal association between outdoor light time and the incidence of PD are scarce. Our findings are consistent with those of previous studies; however, a majority of the studies were cross-sectional and had a limited incidence of PD. In a Danish population-based study, 3819 men diagnosed with PD and 19,282 matched controls were assessed for outdoor work as a measure of sunlight exposure, demonstrating that outdoor workers have a reduced PD risk\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Another observational study from a French cohort reported a decreased risk of PD in participants with longer UV-B exposure\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Although 69,010 people with PD were included in this study, no exact sunlight exposure time was available. In addition, only UV-B exposure was estimated because of its biological role in vitamin D synthesis, which might overlook the effects of other components of sunlight on the development of PD. Red and near-infrared rays, key sunlight elements, demonstrate health benefits in mitigating age-related chronic diseases like Alzheimer's disease, PD, cardiovascular diseases, and diabetes, as per preliminary studies\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. These studies suggest that sunlight's protective effect is likely mediated by other components.\u003c/p\u003e \u003cp\u003eHowever, mechanisms underlying the association between sunlight exposure and PD remain unclear. Given that vitamin D, sleep patterns, and physical activity are linked to sunlight exposure, these factors may play essential roles in the association between outdoor light time and PD. Several cross-sectional studies have shown that vitamin D deficiency is common in adults with PD\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, and that exposure to sunlight can protect against PD through the synthesis of vitamin D \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, which has been reported to play various roles in normal brain physiology and to participate in multiple brain processes, including regulation of synaptic plasticity and dopaminergic neurotransmission\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Consistent with our mediation analyses, vitamin D had a moderate mediation proportion between time spent in outdoor light and PD. In addition to promoting vitamin D synthesis, sunlight exposure regulates sleep and circadian rhythms via the suprachiasmatic nuclei, which transmits the light information to a network of clocks in tissues and organs, thereby synchronising body physiology and behaviour\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. A UK Biobank study confirmed that reduced daytime light exposure is a risk factor for sleep and circadian outcomes\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The circadian system, crucial in regulating reactive oxygen species homeostasis, influences PD development through melatonin secretion, impacting the brain's antioxidant defence and triggering PD\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Consequently, circadian rhythm disruption could hasten PD-related pathology\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e elucidating the link between sunlight exposure, sleep patterns, and PD in our analysis. The strong association of physical activity with PD incidence and prognosis is well-established. Physical activity is strongly associated with the incidence and prognosis of PD has already well known\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Individuals with more outdoor light time may engage in regular physical activity over time, which helps to improve gait speed, muscle strength, and fitness in patients with PD\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Furthermore, our mediation analysis revealed a notable mediative effect of physical activity on the sunlight exposure-PD relationship, particularly in winter. The seasonal variation in PD could stem from winter's colder, cloudier conditions with reduced sunlight. Thus, sunlight's role in this association is less significant compared to summer. Recent studies have shown a link between sunlight and dopamine transporters (DAT). In PD patients, left caudate nucleus DAT availability peaked in spring/summer, correlating positively with prolonged sunlight exposure, indicating daylight-dependent dopaminergic neurotransmission alterations\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe relationship between sunlight exposure and PD was more robust among older and female participants than among younger and male ones; this age tendency is consistent with previous studies\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Some reasons might explain our findings that females are more likely to be affected by temperature and have fewer clothes with more skin exposed compared to males\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Older adults are more susceptible to PD due to age-related changes\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Outdoor light's benefits manifest slower in this group, attributed to diminished skin thickness and declining serum 25(OH)D levels with age\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Increasing outdoor light exposure might be a simple, accessible, non-pharmacological method to protect aginst PD in community settings. Nevertheless, excessive sunlight is linked to skin cancer, diabetes, and dementia\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Thus, enhance clinicians\u0026rsquo; understanding of the association of outdoor sunlight and PD, and then give comprehensive guidance on optimal outdoor light duration, which is essential for PD prevention in the elderly.\u003c/p\u003e \u003cp\u003eOur study\u0026rsquo;s strengths lie in its large sample size and the prolonged follow-up, covering a crucial PD development phase. Furthermore, utilizing the UK Biobank we examined this association in a well-characterized general population cohort, adjusting for numerous potential confounders, including PD\u0026rsquo;s genetic susceptibility.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, the observational nature precludes causal inference, leaving open the possibility of reverse causality in the observed associations. Second, potential recall bias arises from self-reported outdoor light exposure. Third, the exclusive inclusion of Caucasian participants limits generalisability to other ethnicities. Fourth, while accounting for numerous confounders, various psychosocial and environmental factors influencing PD onset remain unaddressed. Finally, PD diagnosis relied on hospital admissions and death records, possibly overlooking early PD stages.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eLonger outdoor light time (\u0026gt;\u0026thinsp;3 h/day in summer, \u0026gt;\u0026thinsp;2 h/day in winter, and \u0026gt;\u0026thinsp;2.5 h/day on average) was associated with a lower PD risk over 13 years of follow-up and was modestly mediated by physical activity, vitamin D, and sleep patterns. The associations of outdoor light exposure and PD were independent of genetic risk. These findings probably highlight the importance of providing detailed guidance on sunlight exposure for long-term PD prevention.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cb\u003eFunding sources\u003c/b\u003e \u003c/p\u003e \u003cp\u003eYFL was supported by the National Nature Science Foundation of China (82070830) and National Key Research and Development Program of Hubei province (2022BCA036).\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCrediT Author Contribution Statement\u003c/h2\u003e \u003cp\u003e \u003cb\u003eYumei Huang\u003c/b\u003e: Methodology, Data curation, Investigation, Validation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eShufan Tian\u003c/b\u003e: Methodology, Formal analysis, Software, Writing \u0026ndash; original draft. \u003cb\u003eKangli Qiu\u003c/b\u003e: Visualization, Roles/Writing-original draft, Writing-review\u0026amp;editing. \u003cb\u003eJinchi Xie\u003c/b\u003e: Data curation, Methodology. \u003cb\u003eAn Pan\u003c/b\u003e: Supervision, Resources. \u003cb\u003eGang Liu\u003c/b\u003e: Project administration, Resources, Validation. \u003cb\u003eYunfei Liao\u003c/b\u003e: Conceptualization, Supervision, Project administration, Funding acquisition.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eThis research has been carried out using the UKB resource under application number 68307. Data is available on application to the UKB at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ukbiobank.ac.uk/register-apply\u003c/span\u003e\u003cspan address=\"http://www.ukbiobank.ac.uk/register-apply\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e \u003cp\u003eThe authors declare that there are no known competing financial interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eData Statement\u003c/h2\u003e \u003cp\u003eThe data has not been previously presented orally or by poster at scientific meetings.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYumei Huang, Shufan Tian and Kangli Qiu wrote the main manuscript text. Yumei Huang, Kangli Qiu, and Jinchi Xie contributed to the methodology and data curation. Shufan Tian performed formal analysis while Yumei Huang was responsible for visualization. An Pan provided supervision and resources, and Gang Liu handled project administration and validation. Yunfei Liao conceptualized the project and acquired funding.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank all participants in the UKB study and all those involved in the UKB study construction.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTansey MG, et al. Inflammation and immune dysfunction in Parkinson disease. 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Sci Total Environ. 2023;888:164253. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2023.164253\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2023.164253\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Parkinson's disease, Outdoor light, UK Biobank, Life style, polygenic risk score","lastPublishedDoi":"10.21203/rs.3.rs-5773642/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5773642/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCross-sectional evidence implicates sunlight exposure is associated with the risk of Parkinson's disease (PD), whereas the evidence from prospective studies is scarce.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cohort study based on UK Biobank enrolled participants between 2006 and 2010, with the latest follow-up in November 2022. In the prospective population-based study 375,599 UK adults aged 37\u0026ndash;73 years were enrolled. The outdoor light time was assessed using a questionnaire survey to investigate how many hours were spent outdoors on typical summer and winter days. New-onset PD was identified through linkage with inpatient hospitalization and death registers. Multivariate Cox proportional hazard regression models were used. The polygenic risk score (PRS) for PD comprised 44 single-nucleotide variants.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 375,599 participants (mean age, 56.8 years; 46.3% males) were included, and 2,824 individuals were first-ever diagnosed with PD. Compared with the individuals with shorter outdoor light time, those with longer time in summer (HR 0.77; 95% CI, 0.68\u0026ndash;0.88), in winter (HR 0.85; 95% CI, 0.75\u0026ndash;0.96), and on average (HR 0.83; 95% CI, 0.74\u0026ndash;0.93), were prone to have lower PD risk. There is no interaction between outdoor light time and genetic predisposition in PD. In mediation analyses, physical activities explained 13.24%, 25.72%, and 15.55% of the associations between outdoor light time and PD, respectively.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn this cohort study, a longer duration of outdoor light exposure was associated with a lower risk of PD, and independent of genetic risk of PD. This association is partly mediated by physical activity, vitamin D, and sleep patterns.\u003c/p\u003e","manuscriptTitle":"Outdoor Light Spending Time, Genetic Predisposition and Incident Parkinson's Disease： The mediating effect of lifestyle and vitamin D","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-10 17:50:00","doi":"10.21203/rs.3.rs-5773642/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e2f255a2-0d9e-46af-b535-7491d2159edd","owner":[],"postedDate":"January 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-01T12:38:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-10 17:50:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5773642","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5773642","identity":"rs-5773642","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}