1. • The results and trends observed in our study confirm the findings of previous
studies that vitamin D insufficiency has increased and are significantly
differential by race/ethnicity groups across the U.S. population
• We found the presence of substantial social demographic variations in cohort
trends of vitamin D insufficiency
• This analysis accounted for the fixed effects of aging and random period and
birth year effects that not only address the secular changes in sociocultural,
economic, technological, and environmental factors, but correctly model the data
in an unbiased manner, which has not been shown in the literature before with
regards to vitamin D status.
• Juxtaposed with the deeper understanding of vitamin D and health, increasing
racial differentials in the cohort trends of vitamin D insufficiency in the population
are worthy of attention as this surge insufficiency risks threaten non-Hispanic
black cohorts the most and pose a significant challenge in overcoming public
health goals to overcome health disparities as outlined by Healthy People 2020
Limitations:
•No sun protection information in NHANES III; the data presented represents a best-case
scenario, in that serum was preferentially collected (Northern states in the summer months
and southern states in the winter months), thus the true prevalence of vitamin D
insufficiency should yield even higher in a random sample across all seasons
Future Research:
•Mediation models to gain a deeper understanding of vitamin D trends
Sample
• An integrated dataset for NHANES III- NHANES 2006
• Restricted sample to those 21 years and older and with non-missing
information for significant covariates
Trends in Vitamin D Insufficiency: Age, Period, Cohort Effects
Jessica J. Davies MPH1
; Brian K. Lee MSPH, PhD1
1
Drexel University School of Public Health, Philadelphia, PA
• To explore three temporal dimensions of vitamin D insufficiency trends by
employing age, period, cohort models for repeated cross-sectional surveys
(NHANES).
• Estimate cohort and period trends, while controlling for age by employing
cross-classified random effects regression models.
Table 1: Descriptive Characteristics of Sample• Vitamin D insufficiency is associated with suboptimal health
• Studies have shown the prevalence of vitamin D insufficiency is rising in the U.S.
population
• March 2011 The National Center for Health Statistics reported:
• 24% of the U.S. population over the age of 1 is at risk for vitamin D deficiency
• 8% were at risk for vitamin D insufficiency
• Differential risks have been reported by age, sex, race, and ethnicity
• In 2011 in an analysis adjusting for age and season:
• 73% of non-Hispanic blacks, 42% of Mexican Americans, and 21% of non-
Hispanic whites were at risk for inadequacy or deficiency
• No study has looked at this trend with secular trends
• Disentangled period effects from age and birth cohort effects
• Thus, the importance of secular change relative to cohort membership is
currently unknown
• Period and cohort effects are not direct causes, but rather surrogates for the
underlying process of this present trend
• Important to include age, period, and cohort effects simultaneously in health
studies to avoid model misspecification and bias interpretations of age and
period effects
Statistical Analysis
•Adopted hierarchical APC (HAPC) and specified cross-classified random effects
models (CCREMs)
•This estimated fixed effects for age and it’s quadratic term and any potential
covariates:
Yijk = αijk + β1jkA + β2jkA2
+ eijk
•Also, estimates random effects for periods and birth cohorts by treating these
variables as level 2-factors:
αjk = π0 + t0j + c0k
•Additionally in the level 2-factors the final model considered the between
race/ethnicity groups effects for the random effect of birth cohort
NHANES III
1988-1994
NHANES
2001-2002
NHANES
2003-2004
NHANES
2005-2006
NHANES age (years)
81-85 1906-1910 1911-1915 1916-1920 1921-1925
76-80 1911-1915 1916-1920 1921-1925 1926-1930
71-75 1916-1920 1921-1925 1926-1930 1931-1935
66-70 1921-1925 1926-1930 1931-1935 1936-1940
61-65 1926-1930 1931-1935 1936-1940 1941-1945
56-60 1931-1935 1936-1940 1941-1945 1946-1950
51-55 1936-1940 1941-1945 1946-1950 1951-1955
46-50 1941-1945 1946-1950 1951-1955 1956-1960
41-45 1946-1950 1951-1955 1956-1960 1961-1965
36-40 1951-1955 1956-1960 1961-1965 1966-1970
31-35 1956-1960 1961-1965 1966-1970 1971-1975
26-30 1961-1965 1966-1970 1971-1975 1976-1980
21-25 1966-1970 1971-1975 1976-1980 1981-1985
Measures
•Outcome: dichotomized serum
vitamin D{ 25 (OH)D] insufficiency
(<12ng/mL) or not (≥12 ng/mL)
•Age: model in polynomial terms of
age as a linear nonparametric
transformation
•Period: Measured in 4 survey
periods (NHANES III (1988-1994),
NHANES 2001-2002, NHANES 2003-
2004, NHANES 2005-2006)
•Birth Cohort: Constructed
synthetic birth cohorts by
subtracted age from the half-way
point of each periodthen divided
into 5-year increme
Figure 1: 16 Synthetic Birth Cohorts
Figure 2: Weighted Prevalence of Serum 25-(OH) vitamin D less than 12 ng/ml in the US
Population (NHANES 1988-2006)
Fix Effect
Coefficient p-value
Lower
Coefficient
Upper
Coefficient
Point
Estimate
Lower OR Upper OR
Intercept -3.011 0.002 -4.008 -2.013 0.993 0.98 1.007
Age -0.007 0.322 -0.021 0.007 1 1 1
Age2 0 0.099 0 0 1.034 1.027 1.041
Male -0.689 <.0001 -0.791 -0.587 0.502 0.453 0.556
BMI 0.033 <.0001 0.026 0.04 1.034 1.027 1.041
Surveyyed in the
Summer -0.608 <.0001 -0.708 -0.508 0.545 0.493 0.602
Took Supplements -0.772 <.0001 -0.878 -0.666 0.462 0.416 0.514
Highest Grade of
Education (Ref=College
or more)
Lessthanhighschool
graduateor equivalent -0.176 0.007 -0.303 -0.049 0.839 0.739 0.952
HighSchool graduateor
equivalent -0.034 0.58 -0.156 0.088 0.966 0.855 1.091
Marital Status
(Ref=Married)
Single 0.402 <.0001 0.274 0.53 1.494 1.315 1.698
PreviouslyMarried 0.296 <.0001 0.175 0.416 1.344 1.192 1.516
Daily Milk Drinker -0.861 <.0001 -0.97 -0.753 0.423 0.379 0.471
Smoking Status
(Ref=Never smoked)
Current Smoker 0.355 <.0001 0.24 0.471 1.427 1.271 1.601
Former Smoker -0.001 0.984 -0.129 0.127 0.999 0.879 1.135
PIR Status
(Ref=PIR>3.00)
PIR<1.00 -0.166 0.084 -0.355 0.022 0.847 0.701 1.023
PIR1.00-3.00 -0.136 0.017 -0.248 -0.025 0.873 0.781 0.975
Race/Ethnicity (Ref=non-
Hispanic White)
MexicanAmerican 0.924 <.0001 0.666 1.182 2.519 1.946 3.26
Non-HispanicBlack 2.05 <.0001 1.808 2.291 7.765 6.098 9.888
Other 0.705 <.0001 0.381 1.029 2.024 1.463 2.799
Age_c*Race 0.007 0.002 0.003 0.012 1.007 1.003 1.012
VarianceComponents
Variance* Z-Value
Standard
Error
p-value
Period 0.291 1.21 0.24 0.113
Birth Cohort
Intercept
Race/Ethnicity 0.073 3.11 3.11 <0.001
Model Fit
(-2 Res Log P-Like) 145833 p-value <0.0001
95% Confidence Limits 95% Confidence Limits
Table 2: The Logit CCREM estimates for vitamin D insufficiency
*Showing the level 2 variance components for the CCREM model random effects of period and birth cohort
between race/ethnicity groups
Background
Purpose
Methods
Results
Conclusions/ Public Health Impact
Limitations/ Extensions
NHANES III
NHANES 2001-
2002
NHANES
2001-2004
NHANES
2005-2006
Entire Sample
No (%) No (%) No (%) No (%) No (%)
Total 13863 3139 3981 2897 23, 880
25(OH)D
level, ng/ml
<12 1, 071 (7.73) 394 (12.5) 460 (11.6) 435 (15.0) 2360 (9.88)
12 to <20 3, 674 (26.5) 896 (28.5) 1,175 (29.5) 846 (29.2) 6591 (27.6)
≥20 9, 118 (65.8) 1, 849 (58.9) 2, 346 (58.9) 1, 616 (55.8) 14, 929 (62.5)
Mean ± SD
(Range)
25.7 ± 11.1
(3.5-70)
22.0 ± 9.15 (3-
63)
22.3 ± 9.13
(3-70)
21.6 ± 9.26 (2-
70)
24.7 ± 10.6 (2-
70)
Sex
Male 6, 520 (47.0) 1, 481 (47.2) 1, 941 (48.8) 1,398 (48.3) 11, 340 (47.5)
Female 7, 343 (53.0) 1,658 (52.8) 2, 040 (51.2) 1, 499 (51.7) 12, 540 (52.5)
Race/Ethnicity
Mexican
American
3, 710 (26.8) 671 (21.4) 804 (20.2) 570 (19.7) 5755 (24.1)
Non-Hispanic
White
5, 842 (43.1) 1, 682 (53.6) 2, 145 (53.8) 1, 467 (50.6) 11, 136 (46.6)
Non-Hispanic
Black
3771 (27.2) 557 (17.7) 749 (18.8) 650 (22.4) 5727 (24)
Other 540 (3.90) 229 (7.30 283 (7.11) 210 (7.25) 1262 (5.28)
Weight Status
(BMI)
Underweight
(<18.5)
3, 541 (25.5) 49 (1.56) 54 (1.36) 40 (1.38 ) 3684 (15.4)
Normal (18.5-
25)
4, 687 (33.8) 968 (30.8) 1, 184 (29.7) 813 (28.1) 7652 (32.04)
Overweight
(25-30)
3, 327 (24.0) 1, 167 (37.2) 1, 429 (35.9) 1,005 (32.7) 6928 (29.01)
Obese (≥30) 2, 308 (16.7) 955 (30.4) 1, 314 (33.0) 1, 039 (35.9) 5616 (23.52)
Mean ± SD 27.7 ± 5.8 28.2 ± 6.12 28.5 ± 6.25 28.9 ± 6.78 27.7 ± 6.06 (11.7-
Figure 5b
: Life-course (age) effects on the race disparities in vitamin D insufficiency with
predicted probabilities in adjusted model: NHANES 1988-2006
Figure 5b
: Period effects on the race disparities in vitamin D insufficiency with predicted
probabilities in adjusted model: NHANES 1988-2006
Figure 5b
: Cohort effects on the race disparities in vitamin D insufficiency with predicted
probabilities in adjusted model: NHANES 1988-2006
Figure 5a
: Life-course (age) effects on the race disparities in vitamin D insufficiency with
predicted probabilities in unadjusted model: NHANES 1988-2006
Figure 5a
: Period effects on the race disparities in vitamin D insufficiency with predicted
probabilities in unadjusted model: NHANES 1988-2006
Figure 5a
: Cohort effects on the race disparities in vitamin D insufficiency with predicted
probabilities in unadjusted model: NHANES 1988-2006
(b) Predicted probabilities estimated for females based on adjusted model with the mean BMI (27.7) and the most common categorical variable (married,
never a smoker, PIR > 3.00, college education, not a daily milk drinker, surveyed in the winter, and did not take supplements the month prior to the index
survey date)
(A) Predicted probabilities estimated for females surveyed in the winter based on unadjusted model